MASARYK UNIVERSITY
FACULTY OF SCIENCE
Department of Experimental Biology
Section of Animal Physiology and Immunology
Plasticity of cell identity and its role in cancer progression
HABILITATION THESIS
Field: Experimental Animal Biology
Brno 2024 Mgr. Karel Souček, Ph.D.
BIBLIOGRAPHIC RECORD
Author: Mgr. Karel Souček, Ph.D.
Field: Experimental Animal Biology
Title of Thesis: Plasticity of cell identity and its role in cancer progression
Year: 2024
Number of Pages: 450
Keywords: tumor heterogeneity, cell plasticity, epithelial-tomesenchymal
transition, dissemination, metastasis
BIBLIOGRAFICKÝ ZÁZNAM
Autor: Mgr. Karel Souček, Ph.D.
Obor: Experimentální biologie živočichů
Název práce: Plasticita buněčné identity a její role v progresi nádoru
Rok: 2024
Počet stran: 450
Klíčová slova: heterogenita nádorů, buněčná plasticita, epiteliálně-mezenchymální
přechod, diseminace, metastázy
DECLARATION
I hereby declare that I worked on this thesis independently using the sources listed in the
bibliography.
Brno, 2024 ……..……….…………………..
Mgr. Karel Souček, Ph.D.
“Not everything that can be counted counts, and not everything
that counts can be counted.”
William Bruce Cameron
To A2I
ABSTRACT
Cancer remains a formidable global health challenge, contributing significantly to
morbidity and mortality worldwide. Despite substantial progress in cancer research and
treatment, the intricate nature of this disease presents significant obstacles in developing
effective therapies. In cancer biology, the concepts of cancer cell plasticity and tumor
heterogeneity have garnered considerable attention. This attention is driven by
recognizing their crucial roles in cancer progression, resistance to treatment, metastasis,
and the recurrence of the disease. This thesis briefly summarizes our current
understanding of cell plasticity and tumor heterogeneity and specifies the author's
contribution to this topic.
ABSTRAKT
Nádorová onemocnění zůstávají obrovským celosvětovým zdravotním problémem, který
významně přispívá k nemocnosti a úmrtnosti na celém světě. Navzdory značnému
pokroku ve výzkumu a léčbě nádorů představuje složitá povaha tohoto onemocnění
významné překážky při vývoji účinných léčebných postupů. Mezi novými koncepty v
biologii nádorů zaujala značnou pozornost plasticita nádorových buněk a heterogenita
nádorů, a to vzhledem k její zásadní roli při progresi, rezistenci na léčbu, metastazování a
recidivě onemocnění. Tato práce stručně shrnuje naše současné poznatky o plasticitě
buněk a nádorové heterogenitě a specifikuje přínos autora k tomuto tématu.
PODĚKOVÁNÍ
Měl jsem a mám štěstí a privilegium, že se v mém životě objevily osobnosti, bez kterých by mé
individuální úsilí bylo marné. Za to jim náleží velké poděkování a zasloužený kredit. Jejich seznam je
dlouhý a omlouvám se těm, které jsem níže nevyjmenoval. I vám děkuji.
Rád bych poděkoval svým mentorům, Vladimíru Šimkovi za počáteční důvěru a Aloisovi Kozubíkovi, za
opakovanou příležitost, podporu a některé pravdy, které se dříve či později ukázaly. Jiřině Hofmanové
za to, že ním tvořila dokonalý tým, ve kterém pomohli roztlačit a nasměrovat „káru“, na které se řada
z nás popovezla a společně ji tlačíme dodnes. Poděkování patří též mému postdoc školiteli Jasonu
Eiserichovi za otevření očí ve „velkém světě“ a Petrovi Dvořákovi nejen za CBCE a příležitost v rámci
budování velkých infrastruktur. Rád bych poděkoval Janovi Šmardovi, Janě Šmardové, Antonínovi
Lojkovi a Jiřímu Damborskému za pomoc a inspiraci. Slovy lze jen těžko poděkovat Alešovi Hamplovi,
bez kterého by v mém pracovním životě jednoduše nebylo nic. Mám to privilegium (stejně jako velká
řada dalších kolegů, kterým se rozhodl nezištně pomáhat), že jsem se ocitl v kruhu jeho kamarádů, na
stejné cestě s ním a jeho týmem, a jsem za to vděčný.
Chci také poděkovat svým dlouholetým spolupracovníkům, kolegům a kamarádům a jejich týmům, s
jejichž pomocí a při práci s nimiž vzniká esenciální radost ze společného bádání – Petrovi Benešovi,
Luďkovi Bláhovi, Marcele Buchtové, Aleně Hyršlové Vaculové, Jiřímu Kohoutkovi, Lumírovi Krejčímu,
Lukášovi Kubalovi, Miroslavovi Machalovi, Petře Ovesné, Jiřímu Pacherníkovi, Vendule Hlaváčkové
Pospíchalové, Petrovi Vaňharovi, Stjepanovi Uldrijanovi, Janovi Vondráčkovi a všem kolegům
z Oddělení cytokinetiky BFÚ AV ČR. Děkuji kolegům z klinických pracovišť, zejména pak Janovi
Bouchalovi, Gvantse Kharaishvili, Milanovi Královi, Daniele Kurfürstové, Haně Študentové, Zoranu
Culigovi, Markovi Svobodovi, Jiřímu Navrátilovi a Pavlovi Fabiánovi za to, že můžeme spolupracovat.
Rád bych poděkoval Kamilovi Paruchovi a jeho týmu za spolupráci a projekty, které, přestože nejsou
tematicky zahrnuty v této habilitační práci, tvoří v mnoha ohledech důležitou a motivující část mého
úsilí. Speciální poděkování si zaslouží Víťa Bryja nejen za „Pánský klub“, ale hlavně za spolupráci a
ochotu se rozdělit o úspěch i udržování ostrůvku pozitivní deviace v rámci OFIŽ/ÚEB. Děkuji Martinovi
Váchovi, nejen za to, že v tom pokračuje, a Janovi Vondráčkovi za stejné úsilí na OC BFÚ. Děkuji též
kolegům okolo ČSAC, zejména Tomášovi Kalinovi a Jaroslavovi Doleželovi za inspiraci a mnohaletou
společnou radost z práce pro komunitu „cytometristů“.
Mojí laboratoří prošlo několik generací studentů a postdoktorandů, z některých se stali dlouholetí a
nenahraditelní kolegové, to považuji za své další velké privilegium. Všem bych rád poděkoval za
vložení energie a času do nelehkých úkolů a za veškerou pomoc, podporu a sounáležitost. Tato práce
by nevznikla zejména bez Evy Slabákové, Zuzany Kahounové, Jana Remšíka, Terezy Suchánkové,
Stanislava Drápely, Jiřiny Procházkové a Radka Fedra, byli za vším klíčovým, čeho jsme v naší
laboratoři společně s ostatními dokázali. To by nebylo možné bez pomoci a podpory Kateřiny
Svobodové a zázemí, které nám spoluvytváří Iva Lišková, Martina Urbánková, Ráchel Víchová, Nina
Tokanová, Ivana Kvisová, Katarína Marečková a v minulosti Jiřina Holá, Jaroslava Netíková, Lenka
Bryjová a další. Děkuji Anežce Celé a Kateřině Svobodové za pomoc s přípravou formálních podkladů
k habilitačnímu řízení.
Děkuji institucím včetně MU a ICRC-FNUSA, grantovým agenturám AV, MŠMT, GAČR, AZV, ale na
prvním místě Biofyzikálnímu ústavu AV ČR za zázemí a dlouholetou podporu naší práce.
Tuto práci bych rád věnoval všem členům své rodiny, za jejich pochopení, podporu a toleranci.
FUNDING
The following grant projects supported this work:
• Role of transforming growth factor-β in regulation of proliferation, differentiation
and apoptosis in prostate and colon cancer. GAČR, 204/07/0834, 2007-2009, PI
• The role of environmental pollutants in mechanisms regulating development of
prostate carcinoma. GAČR, 310/07/0961, 2007-2010, co-PI
• Modulation of signaling pathways leading to neuroendocrine differentiation in
prostate cancer. IGA MZD 9600-4, 2008-2011, PI
• Significance of asporin and other extracellular matrix proteins in invasive
carcinomas of breast and prostate. IGA MZD 9956-4, 2008-2011, co-PI
• FNUSA-ICRC, OP RDI CZ.1.05/1.1.00/02.0123, 2010-2015, researcher
• HistoPARK - Centre for Analysis and Modeling of Tissues and organs. MŠMT,
CZ.1.07/2.3.00/20.0185, 2012-2015, group leader
• OrganoNET - partnership for education and research in the field of visualization of
tissues and organs. MŠMT, CZ.1.07/2.4.00/31.0245, 2012-2014, co-PI
• Role of S-phase kinase-associated protein 2 in biology of prostate cancer stem cells
and tumor progression. AZV NT13573, 2012-2015, co-PI
• The role of epithelial-mesenchymal transition in the plasticity of normal and cancer
stem cell phenotypes. CAS PIPPMS M 200041203, 2012-2015, PI
• ICRC-ERA-HumanBridge, MŠMT, FP7-REGPOT, 2013-2017, researcher
• Centrosomal abnormalities in human pluripotent stem cells. GAČR 15-11707S,
2015-2017, co-PI
• Development of novel small-molecule anticancer compounds with synthetic lethal
effect. AZV 15-33999A, 2015-2018, co-PI, awarded by the minister of health in
2019
• Cancer cell plasticity and tumor heterogeneity in relation to aggressiveness of
prostate cancer and validation of selected prognostic factors. AZV 15-28628A,
2015-2019, co-PI
• FNUSA-ICRC Translational Medicine, MŠMT ČR, NPU II, LQ1605, 2016-2020, group
leader
• Toll-like receptors in prostate carcinogenesis and therapy resistance. AZV 17-
28518A, 2017-2020, co-PI
• Analysis of tumor heterogeneity in advanced prostate cancer and novel
approaches for therapy selection. AZV NU20-03-00201, 2020-2023, co-PI
• Multiparametric single cell analysis of tumor cells and microenvironment in the
triple-negative breast cancer. AZV NV18-08-00245, 2018-2021, PI
1
CONTENTS
ABBREVIATIONS ...................................................................................................................3
INTRODUCTION....................................................................................................................6
Chapter 1 Regulation of cell signaling and tumor suppression in the context of EpithelialMesenchymal
plasticity .......................................................................................................8
Chapter 2 Neuroendocrine differentiation and cellular senescence in the context of
androgen depletion in prostate cancer .............................................................................12
Chapter 3 Epithelial-mesenchymal plasticity and metastasis...........................................17
Chapter 4 Cytometric analysis of heterogeneity and plasticity of cell identity ................27
FUTURE PERSPECTIVES ......................................................................................................36
LIST OF SELECTED PUBLICATIONS......................................................................................38
APPENDIX: COMMENTED OVERVIEW OF SELECTED PUBLICATIONS.................................41
REFERENCES.....................................................................................................................443
2
ABBREVIATIONS
ACCA Automatic Cell Clonning Assay
ADT Androgen Deprivation Therapy
AML Acute Myeloid Leukemia
AR Androgen Receptor
CSC Cancer Stem Cell
DDR DNA Damage Response
ECM Extracellular Matrix
EGF Epidermal Growth Factor
EMP Epithelial-Mesenchymal Plasticity
EMT Epithelial-Mesenchymal Transition
ER Estrogen Receptor
EnR Endoplasmatic Reticulum
FACS Fluorescence-Activated Cell Sorting
FC Flow Cytometry
FCB Fluorescent Cell Barcoding
FGF Fibroblast Growth Factor
GDF-15 Growth/Differention Factor - 15
HGF Hepatocyte Growth Factor
HR Homologous Recombination
HTCP High-Throughput Cytometry-Based Profiling
IB IB kinase
IL-6 Interleukin - 6
JAK Janus Kinase
MAPK Mitogen-Activated Protein Kinase
MC Mass Cytometry
MCSF Macrophage Colony-Stimulating Factor
MDM2 Mouse Double Minute 2
MDMX Mouse Double Minute X
MET Mesenchymal-Epithelial Transition
MYB MYB (myeloblastosis) family of transcription factors
NE Neuroendocrine
NED Neuroendocrine Differentiation
3
NEP Neuroendocrine Phenotype
NEPC Neuroendocrine Prostate Cancer
NF-B Nuclear Factor -Β
NOTCH Notch signaling pathway
p38 p38 mitogen-activated protein kinase
PCa Prostate Cancer
Ras Ras (Rat Sarcoma) GTPase
RANKL Receptor Activator of Nuclear factor -Β Ligand
Rb Retinoblastoma
SASP Senescence-Associated Secretory Phenotype
SMAD homologs to the Caenorhabditis elegans SMA ("small" worm phenotype)
and MAD family ("Mothers Against Decapentaplegic") of genes in
Drosophila
Slug Zinc finger protein SNAI2
Snail Zinc finger protein SNAI1
Sox SRY-related HMG-box genes
p53 Tumor Protein 53
TGF-β Transforming Growth Factor β
TME Tissue Microenvironment
TNBC Triple-Negative Breast Cancer
TNM Tumor, Node, Metastasis (Staging System)
Trop2 Tumor-Associated Calcium Signal Transducer 2
t-SNE t-distributed Stochastic Neighbor Embedding
TUSC3 Tumor Suppressor Candidate 3
TWIST Twist-related protein
UPR Unfolded Protein Response
ZEB1 Zinc finger E-box-binding homeobox 1
Wnt Wnt signalling pathway
4
5
INTRODUCTION
Cancer is the leading cause of morbidity and mortality worldwide. In 2020, there were
approximately 18 million new cases and 10 million deaths from cancer. Moreover, by
2040, it is projected to rise further to 28 million new cancer cases per year.
(Cancer_Research_UK, 2023). The leading cause of death in solid cancers relates to
metastasis, a complex process involving multiple steps. This process consists of the
escape of cancer cells from the primary site, their entry into the bloodstream,
extravasation, and subsequent colony formation in distant organs. Clonal selection and
the high phenotypic plasticity of tumor cells play a crucial role in the colonization
process, allowing for reversible switching between cellular states (Massague and
Obenauf, 2016). This plasticity of cancer cell identity contributes to diverse cell
populations in the tumor, leading to intratumoral heterogeneity and increased cancer
fitness. Although traditionally associated with epithelial-mesenchymal transition (EMT),
recent research has expanded the definition of tumor cell plasticity to include a variety of
other biological processes (Jehanno et al., 2022).
The heterogeneity of tumor populations is further associated with cellular
differentiation. In the cancer stem cell (CSC) model, tumors exhibit a hierarchical
organization characterized by cells with stem cell-like properties. The CSC population
maintains tumor growth through processes of self-renewal and differentiation (Shibue
and Weinberg, 2017). In addition, the tumor microenvironment, comprised of a nonmalignant
stroma that includes fibroblasts, endothelial cells, immune cells, and
extracellular matrix (ECM), introduces additional intratumoral heterogeneity to the
tumor. This heterogeneity is induced by varying selection pressures exerted in different
tumor regions. These patterns are not mutually exclusive; collectively, they constitute a
complex system with numerous layers of heterogeneity stemming from diverse genetic,
epigenetic, transcriptomic, proteomic, and functional properties exhibited by distinct cell
types. Plasticity, a significant impediment to effective anticancer therapy, emerges from
intrinsic and extrinsic cellular factors (Lawson et al., 2018). Single-cell technologies have
contributed to unraveling tumor heterogeneity and cell plasticity (Marusyk et al., 2012;
Hinohara and Polyak, 2019). However, only new approaches to drug development, using
knowledge of the complexity of the tumor ecosystem combined with advances in clinical
trial design and precision medicine, will improve patient outcomes in the future
(McGranahan and Swanton, 2017).
6
In organogenesis, cells develop, determine, and organize into tissues, culminating in
terminal differentiation, where progenitor cells cease growth. This anti-proliferative
outcome poses a barrier to neoplasia. Evidence suggests that unlocking restricted
phenotypic plasticity is crucial in cancer pathogenesis, allowing cells to evade terminal
differentiation (Yuan et al., 2019). Cancer cells may dedifferentiate from a mature state
to a progenitor-like state or maintain a partially differentiated state, deviating from the
end-stage pathway. Additionally, transdifferentiation may occur, leading cells down a
different developmental program (Figure 1). The various manifestations of cellular
plasticity collectively represent a distinct hallmark capability in cancer (Hanahan, 2022).
Figure 1. Unlocking phenotypic plasticity. (i) The process of dedifferentiation, involving the
transition from mature states to progenitor states, (ii) the block of terminal differentiation
in progenitor cell states, and (iii) the phenomenon of transdifferentiation into diverse cell
lineages are recognized as three notable modes of perturbed differentiation intrinsic to
the pathogenesis of cancer. Adapted from (Hanahan, 2022). Created with BioRender.com
7
CHAPTER 1 REGULATION OF CELL SIGNALING AND
TUMOR SUPPRESSION IN THE CONTEXT OF
EPITHELIAL-MESENCHYMAL PLASTICITY
Epithelial-mesenchymal plasticity (EMP) is a process through which epithelial cells can
change their phenotype and acquire mesenchymal characteristics. Various signaling
pathways (Figure 2 (Haerinck et al., 2023; Perez-Gonzalez et al., 2023)), including the
TGF-β family of cytokines, regulate this process (Katsuno and Derynck, 2021). TGF-β
signaling is pivotal in inducing epithelial cell plasticity, encompassing EMT, a critical
process in fibrosis and tumor progression (Fabregat and Caballero-Díaz, 2018). Chronic
long-term inflammation is also implicated in fibrosis and cancer, with TGF-β as a primary
mediator in these processes (Katsuno and Derynck, 2021). Furthermore, TGF-β1 exhibits
potent immunosuppressive and anti-inflammatory effects (Nixon et al., 2022).
Interestingly, it plays a dual role in the process of carcinogenesis. TGF-β1, as a tumor
suppressor, can inhibit the proliferation of cancer cells (Massague, 2008); on the other
hand, it can support cancer progression by stimulating angiogenesis or through induction
of EMT (Massague, 2008). It has been demonstrated that there is a communication
between TGF-β1 and IL-6 pathways, which are both involved in the development of
prostate cancer and inflammation (Culig and Puhr, 2018). This communication affects the
expression of miR34a (as summarized in Appendix 12, (Slabakova et al., 2017)).
Additionally, TGF-β1 can decrease the signaling of IL-6, as seen in intestinal epithelial
cells or AML blast cells. In the prostate epithelial cells, where particularly TGF-β and IL-6
signaling pathways are crucial for tissue homeostasis, we demonstrated that TGF-β1
inhibits IL-6-induced STAT3 activation and expression of the cancer-associated gene
MUC1 through down-regulation of Jak2 expression (Appendix 2, (Starsíchová et al.,
2010)). These findings uncovered a new interaction between TGF-β1 and IL-6 signaling,
suggesting an additional way defects in TGF-β signaling, commonly linked to prostate
issues, may disrupt tissue homeostasis. Growth/differentiation factor-15 (GDF-15), a
unique member of the TGF-β family, is a stress-induced cytokine with suggested
immunomodulatory roles (Soucek et al., 2010), often highly expressed in cancer
progression, including PCa (Savita Wakchoure et al., 2009). However, there is still a lack
of studies clearly illustrating the mechanisms for signal transduction and functions
related to cell interaction, cancer progression, and therapy (summarized in review
Appendix 6, (Vanhara et al., 2012)). Interestingly, GDF-15 has been recognized for its role
in influencing the development of osteoclasts and its potential use in treating bone
8
metastases (Savita Wakchoure et al., 2009). Our study demonstrates that both pure GDF-
15 and the growth medium containing GDF-15 from prostate adenocarcinoma LNCaP
cells, treated with 1,25(OH)(2)-vitamin D(3), hinder the formation of mature osteoclasts
derived from RAW264.7 macrophages and bone-marrow precursors through MCSF/RANKL
in a dose-dependent manner.
Figure 2. Molecular mechanisms regulating plasticity. Cancer cell plasticity is influenced
extrinsically, through signals from the microenvironment, and intrinsically, via various
signaling pathways, transcriptional programs, and chromatin remodeling. Key pathways,
such as TGFβ, RAS–MAPK, CD44, Wnt, Notch, JAK–STAT, and integrins, regulate EMT and
context-dependent stemness. Factors like hypoxia and NF-κB further contribute to
plasticity and inflammation. Transcriptional programs involve crucial factors like SNAI1,
SNAI2, ZEB1, ZEB2, Twist1, Twist2, SOX2, and KLF4, and are modulated by microRNAs and
chromatin landscape. Enzymes like LSD1, NSD2, and KDM2A play roles in histone
modifications, influencing EMT. Polycomb repressive complex 2 (PRC2) and type 2 lysine
methyltransferase (KMT2) – the complex of proteins associated with Set1 (COMPASS) are
9
vital for regulating the epithelial state. Adapted from (Perez-Gonzalez et al., 2023).
Created with BioRender.com
GDF-15 suppresses the expression of c-Fos and the activity of NFB by delaying the
degradation of IB. Additionally, GDF-15 inhibits the expression of crucial osteoclast
enzymes, carbonic anhydrase II, and cathepsin K while causing changes in SMAD and p38
signaling. The absence of functional osteoclasts may contribute to the accumulation of
bone matrix by reducing bone resorption. These findings reveal a new role for GDF-15 in
influencing the differentiation of osteoclasts and potentially in the treatment of bone
metastases (See Appendix 1, (Vanhara et al., 2009)).
c-Myb is a transcription factor that plays a role in cell plasticity and adaptation during the
formation of bone metastasis (Fang and Kang, 2022), primarily through its essential role
in controlling the balance between cell proliferation, differentiation, and survival
(Ramsay and Gonda, 2008). Recent investigations have uncovered the presence of c-Myb
expression in osteosarcoma cell lines, suggesting its functional significance in bone
development (Guo et al., 2016). A retrospective clinical study found high c-Myb levels
correlated with poor overall survival and metastatic progression in young osteosarcoma
patients. Depleting MYB in metastatic cell lines reduced growth, colony-forming capacity,
migration, and increased chemosensitivity. MYB knock-out diminished metastatic activity
in vivo. Transcriptomic analysis has unveiled that c-Myb significantly impacts cell growth,
stress response, adhesion, and cell differentiation, with the Wnt signaling pathway being
recognized as a target.
In summary, c-Myb acts as an adverse prognostic factor in osteosarcoma, influencing cell
behavior and the occurrence of metastasis (Appendix 25, (Rihova et al., 2022)).
Furthermore, we showed that c-Myb controls the invasive tendencies of breast cancer
cells, relying on the type of matrix involved, potentially through a new signaling pathway
that disrupts the expression of MMP1, MMP9, and cathepsin D (Appendix 5, (Knopfova
et al., 2012)). In this context, c-Myb controls the inflammatory response and determines
the metastatic capability of breast cancer cells. The recognized inflammatory pattern
enhances the ability to identify high-risk patients for lung relapse in most analyzed
datasets compared to just assessing MYB alone. Significantly, these markers predict lung
relapses in breast cancer patients, regardless of estrogen receptor expression. Blocking
the c-Myb-driven paracrine inflammatory pathway could enhance the targeting of tumor
10
cells that are not easily reached by standard anti-proliferative therapy, potentially
reducing the occurrence of metastasis (Appendix 14, (Knopfova et al., 2018)).
The tumor suppressor candidate 3 (TUSC3 or N33) gene is in the chromosomal region
8p22, commonly lost in various epithelial cancers like breast, prostate, oral squamous,
and ovarian cancer (Yu et al., 2017). Additionally, TUSC3 has been identified as a
promoter of cancer growth and inducer of EMT in non-small-cell lung cancer cells (Feng
et al., 2018). Loss of TUSC3 has been linked to modified endoplasmic reticulum (EnR)
stress response and increased growth of prostate cancer in vivo (Horak et al., 2014). We
establish TUSC3 as a newly identified EnR-associated tumor suppressor involved in the
pathobiology of ovarian cancer. Both at the morphological and molecular levels, our
findings indicate that TUSC3 plays a role in maintaining rough EnR balance, and its
absence triggers markers of EMT and boosts tumor growth in vivo (Appendix 10,
(Kratochvilova et al., 2015)).
In conclusion, epithelial plasticity, driven by processes such as EMT, is a dynamic
phenomenon regulated by signaling pathways, notably the TGF-β family. The dual role of
TGF-β in suppressing and promoting cancer highlights its complexity. The interaction
between TGF-β1 and IL-6 adds a layer of complexity to prostate epithelial cells, impacting
tissue homeostasis. GDF-15, a member of the TGF-β family, demonstrates potential in
modulating osteoclast differentiation and presents a novel avenue for therapy in bone
metastases. The transcription factor c-Myb emerges as a critical player in cellular
plasticity, influencing metastasis in osteosarcoma and breast cancer, with potential
implications for predictive assessments. TUSC3 is a significant EnR-associated tumor
suppressor implicated in cancer growth and EMT, particularly in ovarian cancer. These
findings contribute valuable insights into the intricate molecular mechanisms underlying
cancer progression and show possible avenues for targeted therapeutic interventions.
11
CHAPTER 2 NEUROENDOCRINE DIFFERENTIATION
AND CELLULAR SENESCENCE IN THE CONTEXT OF
ANDROGEN DEPLETION IN PROSTATE CANCER
Pathologists have long acknowledged the concept of transdifferentiation through tissue
metaplasia, where cells with a specific differentiated phenotype undergo marked
morphological changes, exemplified by Barrett's esophagus. In this condition, chronic
inflammation induces transdifferentiation of the stratified squamous epithelium into a
simple columnar epithelium resembling the intestine (Yuan et al., 2019; Hanahan, 2022).
This transformation facilitates the development of adenocarcinomas rather than the
expected squamous cell carcinomas. Molecular determinants are now uncovering
transdifferentiation mechanisms in various cancers, whether characterized by evident
tissue metaplasia or more subtle transformations, as illustrated in the example of
neuroendocrine (trans)differentiation (NED) (Hanahan, 2022).
NED refers to the process by which cancer cells acquire characteristics of neuroendocrine
cells, which are specialized cells that release hormones and neurotransmitters. This
phenomenon has been documented in diverse cancer types, such as prostate cancer,
breast cancer, and colorectal cancer (Yuan et al., 2007a; Kleist and Poetsch, 2015; Tsang
and Tse, 2021). Neuroendocrine differentiation is associated with increased tumor
aggressiveness, resistance to therapy, and poor prognosis (Parimi et al., 2014). The
presence of neurosecretory granules in neoplastic cells is a hallmark of neuroendocrine
differentiation, and these cells express neuroendocrine markers and exhibit architectural
patterns and cytologic features like nonneoplastic neuroendocrine cells (Tsang and Tse,
2021). Mechanistically, NED is associated with altered expression and activity of several
transcription factors, including, for example, those of the SOX family. They are broadly
implicated in cell fate specification and lineage switching during development (Parimi et
al., 2014) while also exhibiting connections to various tumor-associated phenotypes
(Grimm et al., 2020).
In neuroendocrine tumors, the loss of RB and p53 tumor suppressors represents a
necessary yet insufficient condition for transforming well-differentiated prostate cancer
cells into carcinoma cells with molecular and histologic characteristics resembling
neuroendocrine cells. Notably, these transformed cells exhibit a notable absence of
androgen receptor expression. Beyond the loss of RB and p53, resistance to
antiandrogen therapy involves the heightened expression of the developmental
12
regulatory gene SOX2. SOX2 plays a pivotal role in driving the transdifferentiation of
adenocarcinoma cells responsive to therapy into derivatives adopting a neuroendocrine
cell state unresponsive to the treatment (Mu et al., 2017; Hanahan, 2022). In this
context, there is a notable dearth of experimentally relevant models to comprehensively
elucidate the mechanisms underlying aggressive prostate carcinoma with a
neuroendocrine phenotype (Faugeroux et al., 2020).
Androgen deprivation therapy (ADT) is a crucial treatment for advanced-stage prostate
cancer, accomplished by blocking the androgen receptor (AR) or performing medical or
surgical castration (Harris et al., 2009; Sharifi et al., 2010). While ADT is initially highly
effective, tumors under treatment eventually advance to castrate-resistant prostate
cancer (CRPC), which is presently incurable and fatal. Therefore, understanding the
mechanism by which ADT leads to androgen independence is of significant clinical
importance (Pernicova et al., 2011). The plasticity of prostate cancer cells in the context
of ADT is a well-documented phenomenon. The plasticity of prostate cancer cells results
in resistance to ADT, during which cells can transdifferentiate into neuroendocrine
prostate cancer (NEPC) (Tiwari et al., 2020). This reprogramming, involving phenotype
switching, is part of the cellular plasticity that enables prostate cancer cells to adapt to
the absence of androgens and develop resistance to ADT (De Velasco et al., 2014). The
tumor microenvironment (TME) plays a critical role in regulating and inducing NEPC
formation during androgen deprivation therapy, further highlighting the impact of the
TME on prostate cancer cell plasticity (Zhou et al., 2022). NEPC is an example of the
diverse levels of tumor cell heterogeneity and plasticity, posing a significant challenge for
effective clinical diagnosis and therapy (Pernicova et al., 2011). Since normal prostate
neuroendocrine (NE) cells are postmitotic and do not divide (Abrahamsson, 1999), new
cells with NE-like properties are assumed to emerge through a process known as
neuroendocrine differentiation (NED) from existing epithelial tumor cells (Yuan et al.,
2007b). These tumor cells acquire an NE-like phenotype, meaning they can release
different neuropeptides and are independent of androgens. Research has suggested that
NED can be induced in vitro by various triggering factors such as androgen depletion
(Ismail et al., 2002; Yuan et al., 2006), increased IL-6 levels (Deeble et al., 2001), Wnt
activation (Yang et al., 2005) and EGF (Cortes et al., 2012), activation of the cyclic
adenosine 3′, 5′-monophosphate (cAMP) signaling pathway (Cox et al., 2000; Zelivianski
et al., 2001; Cantile et al., 2005), or exposure to ionizing radiation (Deng et al., 2008;
Deng et al., 2011). Additionally, various genes and transcription factors, like
protocadherin-PC and the transcription factors Foxa2 and Neuro D1, as well as miRNAs,
13
were found to be involved in NED (Summarized in (Cindolo et al., 2007; Slabakova et al.,
2021)). Androgen depletion, known to induce NED, is linked to a halt in the cell cycle at
the G1 phase (Knudsen et al., 1998; Balk and Knudsen, 2008). This cell cycle arrest is
associated with adjustments in well-known regulators of cell cycle progression from the
G1 to S phase (Knudsen et al., 1998; Fribourg et al., 2000). Another contributing factor to
cell cycle arrest is contact inhibition. Cells in high-density arrest in the G1 phase,
accompanied by decreased Cdk2 and Cdk4 activity, even in cancer cells that typically do
not follow the normal contact inhibition seen in normal cells (Pernicova et al., 2014).
Furthermore, cell density can also affect intracellular signaling, as demonstrated by
density-dependent changes in the distribution of cAMP inside and outside the cells (Orbo
et al., 1994). Therefore, we focused on understanding how cell cycle adjustments
regulate NED in prostate cancer cells. Our study showed that both androgen depletion
and cell cycle adjustments due to high cell density encourage NED. It was evidenced by
increased expression of characteristic markers in both AR-positive and AR-negative
prostate epithelial cell lines of different origins. We identified a crucial role of Cdk1 and
Cdk2 activity in promoting NED through cell cycle slowing and suggested that the
activation of cAMP signaling plays a role in promoting NED in AR-positive prostate cancer
cell (Appendix 9, (Pernicova et al., 2014)). The activation of senescence in cancer cells is
thought to be a powerful way to suppress tumors (Schmitt et al., 2022). However,
senescent cells, while inactive in terms of cell division, stay metabolically active. They
release a variety of substances, influencing the tissue surroundings, and potentially
encouraging the development of tumors in nearby malignant cells. It is crucial to note
that some growth factors and cytokines produced by senescent cells might contribute to
the development of CRPC and the induction of NED (Figure 3, for review see Appendix 8,
(Pernicova et al., 2013)).
The induction of the senescence-associated secretory phenotype (SASP) due to androgen
depletion is closely linked to the control of the cell cycle machinery by reducing the levels
of S-phase kinase-associated protein 2 (refer to Appendix 3 (Pernicova et al., 2011)). Skp2
is a crucial component of the SCFSkp2 E3 ubiquitin ligase and is often excessively
expressed in various cancer types, including PCa (Wang et al., 2012). Our research
discovered that the nuclear presence of Skp2 was higher in PCa patients than those with
benign hyperplasia and was associated with a higher Gleason score in PCa patients.
Elevated Skp2 expression was also noted in PCa cell lines with a mesenchymal and cancer
stem cell (CSC) - like phenotype compared to their epithelial counterparts. Conversely,
when SKP2 expression was suppressed, the CSC-like phenotype diminished. Additionally,
14
we observed that lowering Skp2 levels decreased the subpopulation of CD44+CD24−
cancer stem-like cells (see Appendix 18, (Šimečková et al., 2019)).
Figure 3. Senescent stromal and neuroendocrine cells modify the prostate
microenvironment with autocrine and paracrine soluble molecules. In PCa, cancer cells
acquire both SASP and neuroendocrine phenotype (NEP) that promote the formation of
epithelial neoplasia and the development of the androgen-independent phenotype.
Reproduced from (Pernicova et al., 2013).
Apart from employing ADT, treatment approaches encompass chemotherapeutic agents
like docetaxel, exhibiting restricted efficacy, which could eventually develop resistance
and result in a metastatic state (Marin-Aguilera et al., 2012). Recently, increased focus
has shifted towards using poly (ADP-ribose) polymerase inhibitors and immunotherapy
(Slovin, 2023), aiming to suppress tumor growth and enhance clinical outcomes. Toll-like
receptors (TLRs) play a crucial role in the immune response. Over the past decade, more
studies have focused on the potential involvement of TLRs in either promoting or
inhibiting cancer progression (Muresan et al., 2020). Specifically, TLR3, expressed in
15
various cancer types, has been linked to patient context-dependent prognoses. Recent
investigations have revealed its expression in PCa (summarized in (Muresan et al., 2020)).
Conversely, emerging evidence suggests that TLR3 stimulation might impact the
metabolism of PCa cells and sustain tumor progression (Magnifico et al., 2019). These
findings imply that TLR3 could be significant in both the progression and regression of
PCa, although its specific role in each pathway remains to be defined. Our study proved
that the exogenous activation of TLR3 in PCa cell lines induces a significant increase in
the secretion of cytokines such as IL-6, IL-8, and interferon-β. The specific cytokine
response depended on the model and the chemoresistance status. Transcriptomic
analysis of cells overexpressing TLR3 unveiled a functional program enriched with genes
regulating cell motility, migration, and tumor invasiveness. Augmented motility,
migration, and invasion in the TLR3-overexpressing cell line were confirmed through
various in vitro assays and validated using an orthotopic prostate xenograft model in
vivo. These findings suggest that TLR3 may play a role in the progression and metastasis
of prostate cancer. However, it also raises the possibility that TLR3 could be a
vulnerability in PCa, presenting an opportunity for targeted therapeutic interventions
(refer to Appendix 24, (Muresan et al., 2022)).
In summary, ADT is a crucial treatment for advanced prostate cancer, achieved through
androgen receptor blockade or castration. However, the inevitable progression to CRPC
poses a significant clinical challenge. Prostate cancer cells exhibit plasticity during ADT,
often transdifferentiating into NEPC, contributing to treatment resistance. The TME plays
a pivotal role in inducing NEPC after ADT, highlighting the impact of TME on cancer cell
plasticity. NED in prostate cancer cells can be caused by various stimuli, including
androgen depletion, IL-6, Wnt, EGF signaling pathways, cAMP signaling, and ionizing
radiation.
Additionally, cell cycle modulation, senescence, and the SASP are implicated in
promoting NEPC, further complicating therapeutic strategies. The roles of Skp2 and TLR3
overexpressed in PCa add other layers to the intricate mechanisms involved in prostate
cancer progression. These findings underscore the complexity of prostate cancer
plasticity and emphasize the need for comprehensive approaches to diagnosis and
therapy.
16
CHAPTER 3 EPITHELIAL-MESENCHYMAL
PLASTICITY AND METASTASIS
EMT is a cellular process where epithelial cells take on mesenchymal characteristics and
behavior by reducing their typical features (Yang et al., 2020). This dynamic process is
crucial for normal embryonic development and maintenance of tissue homeostasis via
tissue regeneration and wound healing (Katsuno and Derynck, 2021).
In neoplasias, EMT imparts increased tumor-initiating and metastatic potential to cancer
cells, rendering them more resistant to various therapeutic regimens (see Figure 4)
(Chaffer et al., 2016). EMT also plays a pivotal role in the progression of tumors,
facilitating metastatic spread and leading to the development of tumor cells with stem
cell characteristics. These cells contribute significantly to resistance against cancer
treatment (Shibue and Weinberg, 2017). The emerging mesenchymal-like cells can
undergo a reverse change to an epithelial state, called mesenchymal-epithelial transition
(MET) (Katsuno and Derynck, 2021). During EMT, cells lose their adhesion and polarity,
becoming more mobile and invasive (Chaffer et al., 2016).
The processes of EMT and MET, which were initially thought to be binary processes
involving a transition between epithelial and mesenchymal phenotypes, have undergone
a paradigm shift (Haerinck et al., 2023). Recent profiling at the single-cell level using both
RNA and protein analyses (Pastushenko et al., 2018) revealed that cells can exist in
transitional states along the epithelial-mesenchymal axis (Pastushenko and Blanpain,
2019). These partial EMT states simultaneously exhibit features of both epithelial and
mesenchymal (E/M) phenotypes. Depending on the specific context, cells with hybrid
E/M phenotypes can either be fixed (Kroger et al., 2019; Pastushenko et al., 2021) or
flexibly undergo a diverse range of alternative states, a phenomenon referred to as
epithelial-mesenchymal plasticity (EMP) (Yang et al., 2020).
EMT is not a uniform phenomenon but manifests as a localized event in each context
(Nieto et al., 2016). Each cellular entity exists in and is shaped by a microenvironment of
neighboring cells, the extracellular matrix, and cytokine gradients. Epithelial cells can
initiate EMT only by recognizing changes in this microenvironment. Ligands such as TGFβ
(Slabakova et al., 2011), IL-6/STAT (Xie et al., 2012), HGF (Farrell et al., 2014), FGF (Sun
and Stathopoulos, 2018), EGF, Wnt/β-catenin and Notch (Sun and Stathopoulos, 2018)
have demonstrated the ability to induce or enhance EMT (Figure 3, (Haerinck et al., 2023;
Perez-Gonzalez et al., 2023)).
17
Figure 4. (Patho)physiological and morphological changes in EMT/MET. a - summary of
pathophysiological outcomes of EMT/EMT in cancer. b – An overview of EMT/EMTassociated
changes and cellular level. Adapted from (Shibue and Weinberg, 2017; Fanelli
et al., 2020). Created with BioRender.com
18
Additional microenvironmental factors, including hypoxia (Jiang et al., 2007), nutrient
availability (Recouvreux et al., 2020), shear forces (Heise et al., 2011), and matrix rigidity
(Deng et al., 2021), also contribute to EMT. It is crucial to note that investigations into
these parameters have predominantly occurred under diverse artificial in vitro conditions
employing fully transformed and genetically unstable cancer cell lines. The use of these
models has been one reason why EMT has long been seen as controversial and
questioned (Ledford, 2011). The controversy primarily arose from the skepticism voiced
by pathologists, as they had not encountered compelling evidence of EMT in human
carcinoma samples with sufficient frequency to confidently affirm the widespread
implication of the EMT program in the pathogenesis of numerous cancer types (Tarin,
2005; Shibue and Weinberg, 2017). Nonetheless, these studies underscore the profound
impact of the microenvironment in dictating a cell's susceptibility to EMT or even driving
EMT itself. The microenvironmental influences may act synergistically or antagonistically;
however, the intricate nuances of these interactions are yet to be fully elucidated
(Haerinck et al., 2023). An asymmetry arises when comparing the interactions of
epithelial cells with mesenchymal cells in the microenvironment. Epithelial cells,
anchored in place by their strong adhesive properties, are "overcome" by their
microenvironment. In contrast, migrating mesenchymal cells, guided by chemotactic
signals, actively seek out specific environments. These chemotactic mechanisms play a
crucial role during development and contribute to organotropism in cancer cell
metastasis (Gao et al., 2019). Cells in a state of partial EMT may associate motility with
some environmental stability by migrating in clusters. In such cases, the migratory unit
involves a "traveling microenvironment". In addition to cancer cells, these clusters may
include platelets, immune cells, cancer-associated fibroblasts, and extracellular matrix
(Kan et al., 2020). These clusters enable partial EMT state maintenance through
persistent TGFβ signaling (Kan et al., 2020). In addition, clustering prevents anoikis (a
specific mechanism of programmed cell death observed in anchorage-dependent cells
when they detach from the ECM). It protects tumor cells from immune system attacks,
shear forces, and other external stressors (Tiwari et al., 2012). In metastasis, clusters are
very effective in colonizing secondary tumors (Aceto et al., 2014; Haerinck et al., 2023).
19
Figure 5. Cellular plasticity and metastasis cascade. Tumor cells acquire metastasisinitiating
properties through internal and external stimuli that induce EMT. EMT enables
metastasis-initiating cells to detach from the primary tumor and intravasate into the
bloodstream. Circulating tumor cells, either single or clustered, display high plasticity and
hybrid EMT. Interactions with platelets and macrophages enhance plasticity, and platelet
coating protects CTCs. The primary tumor primes the secondary organ by secreting
extracellular vesicles and soluble factors, establishing a permissive microenvironment.
Colonization of the metastatic site involves the reversion of tumor cells to the epithelial
state, influenced by signals from the metastatic niche. Post-seeding, tumor cells may enter
dormancy, gain immune evasion traits and therapy resistance, or proliferate to form
macroscopic metastases. CDH1 - Cadherin 1), SNAI1 – SNAIL, UPR - unfolded protein
response. Adapted from (Perez-Gonzalez et al., 2023). Created with BioRender.com
20
As mentioned above, cellular plasticity and tumor heterogeneity are some of the
significant obstacles to the successful treatment of advanced and disseminated tumors
(Figure 5). Its contribution to the capacity of cancer cells to adapt to changing conditions,
evade therapy, and promote metastasis is leading to poor patient outcomes (Fanelli et
al., 2020; Lüönd et al., 2021). Therefore, developing treatment strategies to target cancer
cell plasticity directly is reasonable and promising (Shibue and Weinberg, 2017). Residual
carcinoma cells that survive diverse therapies, including chemotherapy, molecularly
targeted therapy, and immunotherapy, often exhibit signs of EMT activation. Targeting
cancer cells with activated EMT components may enhance these therapies' efficacy for
durable clinical responses. However, the mechanisms responsible for maintaining or
inducing the EMT program in these residual cells are poorly understood.
The complexity and redundancy of the mechanisms that drive EMT in cancer cells pose a
significant challenge to this program's selective and efficient targeting. Overcoming these
challenges is essential for developing treatment strategies with minimal risk of
resistance, ultimately leading to curative cancer treatment. Many biological properties of
cancer cells are influenced by non-genetic mechanisms, highlighting the limitations of
information derived from cancer genome sequencing and the need for integrated
approaches such as proteomics, epigenomics, and transcriptomics to gain a
comprehensive view of cancer cell biology (Shibue and Weinberg, 2017; Jehanno et al.,
2022; Perez-Gonzalez et al., 2023).
EMT is a crucial mechanism in embryonic development and maintenance of tissue
homeostasis. However, in carcinoma cells, this process gives rise to harmful traits, such
as invasive behavior, cancer stem cell activity, and increased resistance to chemotherapy
(Lu and Kang, 2019). EMP plasticity refers to the ability of epithelial cells to undergo a
transition to a mesenchymal state, which is characterized by increased motility and
invasiveness, and vice versa (Summarized in Appendix 22, (Kvokackova et al., 2021)).
Cancer cells in transitional states between epithelial and mesenchymal (known as partial
EMT) exhibit high adaptability throughout cancer progression, making them critical
contributors to tumor development (Kvokackova et al., 2021). Cells displaying hybrid
epithelial and mesenchymal characteristics are more effective at entering the
bloodstream and establishing metastases (Lu and Kang, 2019; Kvokackova et al., 2021).
Understanding the underlying molecular and cellular mechanisms of EMP offers essential
insights into the origins of cancer and can potentially guide the development of new
therapeutic approaches (Lu and Kang, 2019; Kvokackova et al., 2021).
21
As mentioned above, the TGF-β family is one of the essential inducers of EMT (Lee and
Massagué, 2022). The spectrum of mechanisms in this context is broad and includes
canonical (SMAD-dependent) and non-canonical signaling (Katsuno and Derynck, 2021;
Lee and Massagué, 2022). We previously described that benign prostate hyperplasia cells
undergo EMT upon TGF-β1 treatment (Appendix 2, (Starsíchová et al., 2010)). Next, we
focused on the kinetics of expression of EMT markers, transcription factors, and miRNAs
regulating the EMT process in the benign and derived tumorigenic clones. In these cells,
the transition to EMT was marked by a swift increase in SNAI2/Slug and ZEB1
transcription factors, with alterations in the expression of ZEB2 and miR-200 family
members observed over more extended periods. Our findings suggest that SNAI2/Slug is
essential for the TGF-β1-induced increase in vimentin and migration in benign prostate
epithelial cells. Additionally, the ZEB family of transcription factors, in collaboration with
the miR-200 family, may play a role in suppressing the TGF-β1-induced EMT phenotype
(See Appendix 4, (Slabakova et al., 2011)). Next, we explored how the TGF-β family
regulates Sca-1, a widely used marker for adult stem cells (Upadhyay et al., 2011). Our
evidence suggests that TGF-β disrupts lineage commitment and encourages the
accumulation of tumor-initiating cells in pre-neoplastic cells. Brief exposure of these cells
to TGF-β resulted in the loss of Sca-1 and the selection or enrichment of cells with
enhanced tumorigenic potential. While endogenous TGF-β signaling suppressed Sca-1
through Smad2/3/4, the inhibition of Sca-1 expression due to external TGF-β stimuli was
Smad2/3-independent. Our study demonstrates that TGF-β signaling regulates Sca-1
expression, tumorigenicity, and plasticity in mammary epithelial and cancer stem cells
(Refer to Appendix 21 (Remsik et al., 2020)).
Stimuli inducing the EMT process include cytokines, oncogenes, and TME-associated
molecules (Lamouille et al., 2014). EMT can stem from defects in the tumor suppressor
p53, with gain-of-function mutations and loss associated with EMT (Kogan-Sakin et al.; Lu
and Kang, 2019).
22
Figure 6. Crosstalk between MDM2, Slug, and Twist in EMT. A. In the case of intact p53
function, MDM2 cooperates with p53 in the degradation of Slug, thereby preserving the
epithelial phenotype. B. When p53 function is impaired, elevated expression of MDM2
correlates with the epithelial phenotype. Slug and Twist inhibit the expression of MDM2
and promote EMT, which is associated with upregulated expression of MDMX. Solid lines
delineate direct effects; dotted lines represent indirect mechanisms. Adapted from
(Slabakova et al., 2015). Created with BioRender.com
Proper p53 function is vital for maintaining the epithelial phenotype, regulated tightly by
MDM2 and MDMX. MDM2, through various mechanisms, controls p53 functions, while
MDMX lacks E3 ubiquitin ligase activity but regulates p53 and MDM2 (Wade et al., 2010).
Inhibiting MDM2 sensitizes cancer cell lines to chemotherapy, and clinical trials explore
p53 reactivation via MDM2 inhibitors (Wade and Wahl, 2009). We demonstrated that the
EMT phenotype is linked to a reduction in MDM2 and an increase in MDMX expression in
various cellular models and clinical prostate and breast cancer samples. Modulating EMTassociated
alterations in MDM2 expression in benign and transformed prostate epithelial
cells impacts their migration capacity and responsiveness to docetaxel. Examination of
potential mechanisms controlling MDM2 expression reveals that, in the presence of
impaired p53 function, EMT-inducing transcription factors Slug and Twist regulate MDM2
expression. These findings unveil an alternative, context-specific role of MDM2 in EMT,
cell migration, metastasis, and resistance to therapy (Figure 6, Appendix 11, (Slabakova
et al., 2015)).
A growing body of research indicates that EMT is a pivotal process influencing the
responsiveness of cancer cells to chemotherapy. Zinc finger E-box binding homeobox 1
(ZEB1) plays a central role within a network of transcription factors governing EMT.
23
Additionally, it has been recognized as a significant molecule in regulating DNA damage,
cancer cell differentiation, and metastasis (Summarized in Figure 7, Appendix 19,
(Drapela et al., 2020)).
Figure 7. Pleiotropic roles of ZEB1 in the cell plasticity, EMT, and therapy resistance. The
ZEB1 represents a core transcriptional factor and central determinant of cell fate, which
controls fundamental intracellular processes, including cell plasticity, EMT, or therapy
resistance. Downstream signaling pathways triggered by ZEB1 regulate the activity of the
proteins and miRNAs involved in cell differentiation, proliferation, or motility. ZEB1
overexpression is accompanied by an overall changeover of the cell phenotype, higher
tumorigenic potential, and increased migratory character. ZEB1 also promotes immune
escape as well as contributes to the formation of a pre-metastatic niche. Given the tumor
heterogeneity, ZEB1 plays an essential role in the stemness of cancer cells and increased
radio- and chemoresistance. The green and red arrows illustrate the significant activating
or inhibitory effects of ZEB1, respectively. CSCs, cancer stem cells; EMT, epithelial-tomesenchymal
transition; MET, mesenchymal-to-epithelial transition; DDR, DNA damage
response; HR, homologous recombination. Created with Biorender.com. Reproduced from
(Drapela et al., 2020).
Trop2, also known as trophoblast cell-surface antigen 2, is a cell surface glycoprotein that
has been found to play a role in the promotion of EMT in various types of cancer
(Summarized in Appendix 20 (Lenart et al., 2020)). Most studies characterize Trop2 as an
24
oncogene and a mediator of metastasis in prostate cancer, attributing its impact to
regulating focal adhesions and integrins (Trerotola et al., 2015). Conversely, a separate
study demonstrated that the loss of Trop2 in mice lacking Arf results in the development
of squamous cell carcinoma with features of EMT (Wang et al., 2011). Despite the
approval of therapies targeting Trop2-expressing cells, the functional role of Trop2 within
the tumor mass remains unknown or subject to controversy (Lenart et al., 2020; Yao et
al., 2023). Our research indicates that the membrane expression of Trop2 is positively
correlated with E-cadherin expression and negatively correlated with the mesenchymal
gene signature in a broad range of human and murine breast and prostate cancer cell
lines, as well as human tumors (See Appendix 15, (Remšík et al., 2018)). Our findings
suggest that in breast and prostate cancers, the surface expression of Trop-2 is
associated with the epithelial phenotype. Additionally, we demonstrated that Trop-2
expression is either epigenetically suppressed through DNA hypermethylation or EMT
transcription factors, such as ZEB1 during EMT. Furthermore, our data suggest that
intratumoral heterogeneity in Trop-2 expression, driven by cancer plasticity, may
significantly contribute to both the response and resistance to therapies targeting Trop2expressing
cells (Appendix 15 (Remšík et al., 2018)).
To understand EMP-driven intratumoral heterogeneity, we implemented a highthroughput
screening platform to identify surface antigens that are linked to EMP in
distinct pairs of epithelial cell lines and their mesenchymal counterparts (see Chapter
below and Appendix 16 & Appendix 21 (Remsik et al., 2018; Remsik et al., 2020; Drápela
et al., 2021)). We identified ten surface antigens that reflect EMP in vitro using antibodybased
high-throughput profiling and verified their expression in dissociated breast cancer
patient samples. The depicted antigens showed heterogeneous expression in clinical
specimens. CD9, CD29, CD49c, and integrin β5 (ITGB5) exhibited significant
downregulation in a subset of breast cancer cells undergoing EMT in vivo. CD9, a
tetraspanin with various functions in development and disease, consistently experienced
reduced levels both in vitro and in vivo despite being commonly overexpressed in breast
cancer (Ondrussek et al., 2023). We correlated the expression of CD9 with the epithelial
phenotype, EMP, and a favorable prognosis in extensive cohorts of breast cancer
patients. The identification of molecules associated with cancer plasticity and the
comprehension of mechanisms involved in transcriptional reprogramming may uncover
potential biomarkers and therapies targeting tumor-initiating cells, thereby preventing
cancer relapse and the growth of macrometastases in the future (Refer to Appendix 16,
(Remsik et al., 2018)).
25
As a continuation of this study, and considering the acknowledged inaccuracies in
identifying cell subtypes, such as fibroblasts using single markers (refer to Appendix 13
(Kahounova et al., 2018)), we have delineated creating a comprehensive mass cytometry
panel. This panel is specifically designed for the multiparametric identification of 23
phenotypic markers and 13 signaling molecules. Employing this single-cell proteomic
approach, we investigated the landscape of heterogeneity in triple-negative breast
cancer (TNBC), focusing on the tumor microenvironment (Figure 11). Our prospective
profiling involved the examination of freshly resected tumors from 26 TNBC patients,
unveiling unique subsets of cancer and stromal cells with connections to the patient's
clinical condition at the time of primary tumor resection. We also examined the EMP of
tumor cells and molecularly delineated various phenotypes within the tumor-associated
stroma. Furthermore, in a retrospective tissue-microarray cohort of TNBC, we revealed
the prognostic capability of CD97 levels (Refer to Appendix 26, (Kvokackova et al., 2023)).
Understanding EMP in cancer reveals a complex regulatory network involving factors like
TGF-β, p53, MDM2, and Trop2. These findings provide better insight into cancer
development and suggest a pathway for new therapeutic strategies targeting tumorinitiating
cells. Developing a comprehensive mass cytometry panel is a significant
technological opportunity to accurately identify cell subtypes and phenotypic markers
and improve our understanding of tumor heterogeneity and microenvironment (see next
chapter).
26
CHAPTER 4 CYTOMETRIC ANALYSIS OF
HETEROGENEITY AND PLASTICITY OF CELL
IDENTITY
The complexity of cancer is underscored by the intricate interplay of diverse molecular
mechanisms and the remarkable tumor heterogeneity exhibited within and among
cancer types, challenging conventional therapeutic approaches and necessitating a
comprehensive understanding of the complex biological landscapes underlying this
formidable disease. This heterogeneity can manifest as variations in morphology, gene
expression, metabolism, and metastatic potential (Jehanno et al., 2022). It occurs at both
inter-tumor and intra-tumor levels, posing significant challenges to effective treatment
and contributing to tumor resistance and aggressive metastasizing (Bhatia et al., 2012;
Boyd et al., 2012).
The TME plays a vital role in the complexity of cancer. This complex ecosystem
surrounding the tumor includes various non-tumor components, including endothelial
and immune cells, fibroblasts, soluble factors, extracellular vesicles, and ECM (Witz,
2008; Monteran et al., 2023). Dynamic interactions between tumor cells and their
microenvironment are essential for inducing tumor cell heterogeneity, clonal evolution
and promoting multidrug resistance, ultimately resulting in tumor cell progression and
metastasis (Baghban et al., 2020). Much of our current knowledge of the TME is based on
studies conducted in primary tumors. Nevertheless, when tumor cells disseminate to
distant organs, they must adapt to distinct organ-specific microenvironments
characterized by variations in stromal cell composition and ECM compared to the
primary site. It necessitates the utilization of unique molecular and cellular interactions
to either support or counteract the growth of disseminated cancer cells (Massague and
Obenauf, 2016; Monteran et al., 2023). Notably, the reprogramming and activating of
stromal cells in metastatic organs precede the actual formation of metastases (Hu et al.,
2023; Monteran et al., 2023). Stromal cells receive multiple activating signals throughout
the metastatic cascade, leading to functional impairment. Instead of resolving the tissue
damage caused by disseminated cancer cells, these stromal cells transform into
facilitators of metastatic growth (Lavie et al., 2022; Monteran et al., 2023).
27
Additionally, activated stromal cells are pivotal in attracting tumor cells, fostering cancer
cell dormancy and awakening, and promoting tumor cell invasion, survival, and
proliferation. Ultimately, these stromal cells support metastatic outgrowth (Lawson et
al., 2015; Monteran et al., 2023). Considering these observations, targeting the TME
emerges as an appealing and innovative strategy to indirectly disrupt the intricate
interplay among cancer cells, potentially contributing to developing effective cancer
therapies (Anderson and Simon, 2020). Most tumors originate from a single mutated cell
and accrue additional mutations during their progression to advanced disease through
Darwinian evolution (Marusyk et al., 2012; Hinohara and Polyak, 2019). Mutations
facilitating tumor progression and conferring therapeutic resistance may be present in
early preinvasive or premalignant lesions (Spira et al., 2017). Topographic single-cell
sequencing applied to both in situ and invasive regions within the same breast tumor
tissue sections unveiled the evolution of multiple mutated clones within ducts before the
invasion. Specific subclones were more prevalent in the invasive areas, indicating
multiclonal invasion (Casasent et al., 2018).
Microenvironmental factors, such as hypoxia, tissue stiffness, and chronic inflammation,
exert both direct and indirect influences on the epigenetic and phenotypic heterogeneity
of cancer cells (Lawson et al., 2018). Another source contributing to intratumoral
heterogeneity is the epigenetic variation associated with the inherent differentiation
hierarchy in normal tissues. The differentiation state of the transformed cell and its
normal cell-of-origin collectively determine the molecular subtypes of the tumor. In
breast cancer, for instance, luminal A, luminal B, basal-like, and HER2+ subtypes are
believed to originate from distinct luminal and basal progenitors (Perou et al., 2000;
Hinohara and Polyak, 2019).
EMT plays an essential role in regulating cellular heterogeneity, as cells undergoing EMT
acquire stem cell-like features (refer to the subsequent chapter, (Mani et al., 2008).
While many studies on intratumoral heterogeneity primarily focus on genetic changes,
treatment resistance often stems from a malfunction of pathways targeted by the
therapy (McGranahan and Swanton, 2017). Nevertheless, non-genetic variability, such as
epigenetic heterogeneity, impacts therapeutic resistance through diverse mechanisms
(Brock et al., 2009; Saxena et al., 2022).
The master regulator of EMT, ZEB1, induces the expression of histone methyltransferase,
establishing a positive feedback loop that sustains ZEB1 expression and maintains the
invasive EMT regulatory state (Lindner et al., 2020). A previous study similarly
28
demonstrated that the induction of EMT by upregulated expression of the related
transcription factor SNAIL1 led to significant alterations in the chromatin landscape. This
induction activated several chromatin modifiers, and their activity was indispensably
necessary for maintaining the phenotypic state (Javaid et al., 2013; Hanahan, 2022).
These findings underscore the complexity and interconnectedness of individual
processes and modes of regulation that give rise to dynamic changes and the
demonstration of different tumor phenotypes. Consequently, the combined
manipulation of the microenvironment, genomic, and epigenetic landscape in cancer
cells could be a potent therapeutic tool, enhancing the efficacy of targeted therapies or
chemotherapies (Hinohara and Polyak, 2019).
Cytometry methods, particularly single-cell analysis, have played a significant role in
understanding cancer heterogeneity and cell plasticity. These methods have enabled
researchers to isolate and characterize different tumor cell populations, assess tumor cell
heterogeneity, and investigate the dynamics of immune cells and tumor-associated
fibroblasts in the TME (Luo et al., 2022; Zhao and Rosen, 2022). Single-cell techniques
such as RNA sequencing and single-cell proteomics have yielded valuable insights into
the complexity of cancer cell heterogeneity and plasticity, empowering researchers to
devise more effective strategies for cancer diagnosis, treatment, and personalized
medicine.
The proven technology applied in this field is undoubtedly flow cytometry. It is a
powerful technology that enables rapid multiparametric analysis of single cells in
suspension (McKinnon, 2018). Flow cytometry proves valuable in various fields, including
immunology, molecular biology, and cancer biology (McKinnon, 2018). Essential for
quantifying the expression of cell surface and intracellular molecules, assessing the purity
of isolated cell subpopulations, and sorting different cell populations through
fluorescence-activated cell sorting (FACS), flow cytometry has no full-fledged alternative
to date. Its capacity for multiparametric analysis, high speed, and the ability to separate
complex, defined populations or single cells remains unmatched.
29
Figure 8. (A) The illustration shows the experimental workflow used to determine the in
vitro plasticity of parental 4T1 cells with high-content microscopy. (B) Histograms show
the single-cell Trop2 surface intensity of colonies derived from sorted Trop2- and Trop2+
cells. Representative images show Trop2 (red) and DAPI (blue) staining of the colonies
(scale = 100 μm). Reproduced with modification from (Remšík et al., 2018).
These features find simple applications in an automated cell clonogenic assay (ACCA). We
employed ACCA to evaluate the cloning ability of different prostate and colon cancer cell
subsets, considering the expression of specific markers associated with stem cells (CD44
and CD133) and cancer stem cells (Trop2, CD49f, and CD44). Our findings demonstrated
that the newly introduced ACCA is an effective method for measuring the clonogenic
capacity of cancer stem cells, as identified in both cell lines and patient samples (See
Appendix 7, (Fedr et al., 2013). This methodology, in conjunction with high-content
microscopy and image analysis, was applied to assess the variability of Trop2 expression
within a diverse in vitro 4T1 cell model containing both Trop2- and Trop2+ cells (Appendix
15 (Remšík et al., 2018)). Initially, we sorted both cellular factions as single cells based on
their surface Trop2 levels and allowed them to develop colonies. Subsequently, we
assessed the quality of the colonies and the surface Trop2 expression intensity at a
single-cell level through high-content microscopy (see Figure 8). Intriguingly, both cell
types generated colonies with low and moderate surface Trop2 intensity, but only Trop2+
cells proliferated into colonies exhibiting high Trop2 staining. It confirms, among other
30
things, that this experimental approach is suitable for uncovering the link between cell
identity and function ( See Appendix 15, (Remšík et al., 2018)).
Complex analysis of the cellular response and cell fate (cytokinetics) following
experimental treatment is essential for screening and understanding treatment (drug)
effects and identifying sensitive or resistant cell types with a characteristic phenotype.
For such analyses, a variety of methodological approaches might be used. Typically, these
can involve adapting several parallel methods, which may have different readouts. Most
frequently used single readout methods (e.g., western blot or qPCR) cannot detect cellto-cell
heterogeneity in response to the tested compound unless performed at the
single-cell level (Heath et al., 2016). A modern cell analysis method should take full
advantage of flow cytometry's multicolor character to simultaneously measure several
types of cell responses and analyze the treated cells' phenotype and functional
characteristics. In this perspective, we have established a multiparametric flow
cytometric assay for the complex analysis of cellular phenotypes in response to
experimental therapy (Appendix 17 (Simeckova et al., 2017)). Using this assay, we can
simultaneously detect changes in viability, cell cycle profile, DNA synthesis and damage,
and apoptosis in cells characterized by the expression of two surface markers. The main
benefit of this approach is that various biological responses to a specific treatment can
be evaluated in a single assay on a single-cell level.
Furthermore, we demonstrate the possible application of this established procedure to
analyze heterogeneous samples and to compare the effects of drugs on different subsets
of cell populations (Figure 9). Moreover, the protocol can be applied to both human and
mouse and adherent and non-adherent cells. It creates an opportunity to analyze mixed
cell populations efficiently, including infiltrating host cells in xenografts.
31
Figure 9. Comparison of complex responses to treatment among Trop2– and Trop2+
subpopulations. Response to treatment was analyzed separately in the Trop2– and Trop2+
subpopulations in the DU 145 cell line (A). Differences in proliferation (B), DNA damage (C,
E), and induction of apoptosis (D, E) were examined. Reproduced from (Simeckova et al.,
2017).
Fluorescent cell barcoding (FCB) is a method that facilitates high-throughput and highcontent
flow cytometry through the multiplexing of samples before specific staining and
acquisition (Krutzik and Nolan, 2006; Giudice et al., 2017). The general concept behind
the FCB utilizes one, two, or more fluorescent dyes at different concentrations “barcodes”—allowing
for subsequent discrimination of pooled cell samples using flow
cytometry based on their distinct fluorescence emission wavelengths and corresponding
intensities (Krutzik and Nolan, 2006). This method reduces reagent usage, shortens the
time per sample (including staining, handling, and acquisition), and eliminates technical
variability related to differences in staining volume and antibody concentration (batch
32
effect). It maximizes data robustness and assay efficiency (Krutzik and Nolan, 2006;
Giudice et al., 2017). Applications that already demonstrated the effectivity of FCB
methods include the analysis of intracellular phosphoproteome (Manohar et al., 2019),
large-scale drug screenings (Krutzik and Nolan, 2006), or investigation of intratumoral
heterogeneity within various cell samples (Appendix 16 & Appendix 21, (Remsik et al.,
2018; Remsik et al., 2020; Drápela et al., 2021)). The absence of technologies enabling
cost-effective profiling of a substantial number of cells using an antibody-based approach
led us to create a high-throughput cytometry-based platform for surface profiling (see
Figure 10). We combined fluorescent cell barcoding with existing commercially available
screening tools to analyze cell surface fingerprints on a large scale (Refer to Appendix 23,
(Drapela et al., 2022)). This robust approach allowed characterizing cell surface
fingerprints linked to epithelial plasticity (See Appendix 16 & Appendix 21, (Remsik et al.,
2018; Remsik et al., 2020; Drápela et al., 2021) and has the potential to identify novel
biomarkers and druggable targets.
Figure 10. The experimental workflow of fluorescent barcoding and high-throughput flow
cytometry screening of surface markers includes data acquisition, deconvolution of cell
lines based on the fluorescent barcode, and data analysis. Reproduced from (Drápela et
al., 2021).
Mass cytometry is a flow cytometry-based technique (CyTOF) that combines flow
cytometry principles with elemental mass spectrometry to detect and quantify multiple
markers on single cells (Iyer et al., 2022). In the context of flow cytometry, mass
cytometry offers several advantages, including higher parameter detection. Mass
cytometry allows for the simultaneous detection of up to 50 markers, compared to the
33
limitations of traditional flow cytometry, which are typically restricted to the detection of
around a dozen parameters due to spectral overlap between fluorochromes. Several
studies utilized single-cell mass cytometry to reveal the inter and intra-tumor
heterogeneity. For example, Petrilli et al. demonstrated the significant phenotypic
heterogeneity of pediatric-type diffuse high-grade gliomas among the analyzed tumor
cell lines. They highlighted the degree of plasticity within the tumors (Petrilli et al., 2022).
Figure 11. Characterization of tumor heterogeneity in TNBC samples by mass cytometry.
(A) The scheme depicting the experimental approach and analytical workflow for primary
TNBC patient samples was used in this study. (B) List of cell surface and signaling
molecules selected to characterize tumor and microenvironmental compartments. (C)
Two-dimensional t-SNE visualization of PanCK, CD45, and CD90 expression in all cells and
all samples (n = 26). The combination of these three markers was used for the
identification of cancer (PanCK+), immune (CD45+), and stromal (PanCK-CD90+) cells,
respectively. Reproduced from (Kvokackova et al., 2023).
34
Moreover, a study published in Nature Cancer in 2021 introduced the development of
three-dimensional imaging mass cytometry for multiplexed 3D tissue analysis at singlecell
resolution (Kuett et al., 2022). Mass cytometry is an excellent tool for
comprehensively understanding cancer heterogeneity and plasticity, particularly in the
tumor microenvironment and the spatial organization of cells within tissues. Recently,
we employed this technology and described the generation of a comprehensive mass
cytometry (CyTOF) panel for multiparametric detection of 23 phenotypic markers and 13
signaling molecules. This proteomic approach at the single-cell level allowed us to
investigate TNBC heterogeneity with a specific focus on the tumor microenvironment
(Figure 11, Appendix 26, (Kvokackova et al., 2023)).
In summary, cytometric methods, encompassing single-cell analysis, flow cytometry, FCB,
and mass cytometry, play a crucial role in revealing the heterogeneity and plasticity of
cancer cells. These techniques provide valuable insights into tumor dynamics, facilitating
the development of more effective cancer diagnosis and treatment strategies. With its
multiparametric analysis, flow cytometry remains indispensable for studying cell surface
markers, intracellular molecules, and clonogenic capacity. FCB streamlines highthroughput
analyses, while mass cytometry offers a powerful tool for comprehensively
investigating the proteomics of single cells. These advanced cytometric methods
significantly contribute to our understanding of cancer biology and hold promise for
biomarker discovery and targeted therapeutic approaches.
35
FUTURE PERSPECTIVES
Future perspectives in the context of cellular plasticity and tumor heterogeneity include
understanding the complex interactions between different cell types and the tumor
microenvironment and developing personalized treatment strategies targeting tumor cell
plasticity. Advances in this research area are closely tied to progress in analytical
cytometry and data analysis methods. Flow cytometry, single-cell RNA sequencing, mass
cytometry, and spatial cytometry provide relevant answers to novel biological and clinical
questions.
The presented research opens avenues for future investigation in several areas:
Precision targeting: Identified signaling pathways and molecules, such as TGF-β, c-Myb,
and Trop2, offer potential targets for precision therapy in the context of cellular plasticity
and cancer heterogeneity. A more precise understanding of the biology associated with
these molecules is needed for further research to develop targeted interventions
exploiting their dual roles in tumor suppression and progression. Given the
immunosuppressive effects of TGF-β1 and its interactions with inflammatory pathways,
exploring immunomodulatory strategies could reveal novel approaches to manipulate
the tumor microenvironment and enhance the anti-tumor immune response. It is
essential to elucidate the functional roles of Trop2 and its interactions in various aspects
of tumor biology, including proliferation, invasion, and metastasis. Understanding these
roles could reveal new tumor vulnerabilities and therapeutic opportunities.
Clinical biomarkers: Surface molecules associated with epithelial-mesenchymal plasticity,
such as CD9, CD29, CD49c, and CD97, are promising clinical biomarkers. Validating their
significance in large patient cohorts may lead to developing prognostic tools to predict
cancer progression and response to treatment.
Cell plasticity, cancer heterogeneity, and resistance: Exploring the role of cellular
heterogeneity, particularly concerning surface antigen expression, provides insight into
resistance mechanisms and may guide the development of combination therapies
targeting different tumor subpopulations. Elucidating the molecular mechanisms
underlying treatment resistance and cellular plasticity is essential for developing
strategies to overcome resistance and prevent cancer recurrence. Understanding these
processes can increase treatment efficacy for resistant tumors and address the
challenges of heterogeneity and plasticity in cancer therapy.
36
Spatial analysis: Advances in mass cytometry, genomic techniques, and threedimensional
imaging techniques allow spatial analysis of the tumor microenvironment.
Understanding the spatial organization of different cell types within tumors can unravel
critical interactions influencing cancer progression. Together with the massive advances
in spectral cytometry and the opening of new possibilities in multi-parameter flow
cytometry with image analysis and intracellular signal localization, it brings entirely new
tools for revealing and understanding cellular phenotypes and their roles in cancer
development.
Integration of omics data: Integrating data from diverse “omics” approaches, including
genomics, transcriptomics, proteomics, and cytometry, will provide a holistic view of
cancer biology. This integration can uncover novel therapeutic targets and enhance our
understanding of the molecular networks driving cancer progression.
In conclusion, the future of cancer research lies in unraveling the complexities of tumor
heterogeneity and plasticity, translating these findings into precision therapies, and
exploring innovative technologies that allow a deeper understanding of cancer biology in
both experimental and clinical settings.
37
LIST OF SELECTED PUBLICATIONS
List of articles representing the author´s contribution to understanding cell plasticity and
cancer heterogeneity. Author’s articles in the Appendix below represents a selection of
19 primary research articles, two book chapters, and five reviews (out of 140 author’s
publication records available on WOS on January 31st
, 2024), which are related to the
topic of the habilitation.
1. Vanhara P, Lincova E, Kozubik A, Jurdic P, Soucek K*, Smarda J.
Growth/differentiation factor-15 inhibits differentiation into osteoclasts-A novel
factor involved in control of osteoclast differentiation. Differentiation 2009;78:
213-22. * shared corresponding author
2. Starsichova A, Lincova E, Pernicova Z, Kozubik A, Soucek K. TGF-β 1 suppresses IL-
6-induced STAT3 activation through regulation of Jak2 expression in prostate
epithelial cells. Cellular Signalling 2010;22: 1734-44.
3. Pernicova Z, Slabakova E, Kharaishvili G, Bouchal J, Kral M, Kunicka Z, Machala M,
Kozubik A, Soucek K. Androgen Depletion Induces Senescence in Prostate Cancer
Cells through Down-regulation of Skp2. Neoplasia 2011;13: 526-36.
4. Slabakova E, Pernicova Z, Slavickova E, Starsichova A, Kozubik A, Soucek K. TGFβ1-Induced
EMT of Non-Transformed Prostate Hyperplasia Cells Is Characterized
by Early Induction of SNAI2/Slug. Prostate 2011;71: 1332-43.
5. Knopfova L, Benes P, Pekarcikova L, Hermanova M, Masarik M, Pernicova Z,
Soucek K, Smarda J. c-Myb regulates matrix metalloproteinases 1/9, and
cathepsin D: implications for matrix-dependent breast cancer cell invasion and
metastasis. Molecular Cancer 2012;11.
6. Vanhara P, Hampl A, Kozubik A, Soucek K. Growth/differentiation factor-15:
prostate cancer suppressor or promoter? Prostate Cancer and Prostatic Diseases
2012;15: 320-8.
7. Fedr R, Pernicova Z, Slabakova E, Strakova N, Bouchal J, Grepl M, Kozubik A,
Soucek K. Automatic cell cloning assay for determining the clonogenic capacity of
cancer and cancer stem-like cells. Cytometry A 2013;83A: 472-82.
8. Pernicova Z, Vanhara P, Soucek K. Formation of secretory senescent cells in
prostate tumors: the role of androgen receptor activity and cell cycle regulation.
In: Tumor Dormancy, Quiescence, and Senescence, Volume 1: Aging, Cancer, and
Noncancer Pathologies, Springer Netherlands, 2013: 303-16.
9. Pernicova Z, Slabakova E, Fedr R, Simeckova S, Jaros J, Suchankova T, Bouchal J,
Kharaishvili G, Kral M, Kozubik A, Soucek K. The role of high cell density in the
38
promotion of neuroendocrine transdifferentiation of prostate cancer cells.
Molecular Cancer 2014;13: 113.
10. Kratochvilova K, Horak P, Esner M, Soucek K, Pils D, Anees M, Tomasich E, Drafi F,
Jurtikova V, Hampl A, Krainer M, Vanhara P. Tumor suppressor candidate 3
(TUSC3) prevents the epithelial-to-mesenchymal transition and inhibits tumor
growth by modulating the endoplasmic reticulum stress response in ovarian
cancer cells. Int J Cancer 2015;137: 1330-1340.
11. Slabakova E, Kharaishvili G, Smejova M, Pernicova Z, Suchankova T, Remsik J,
Lerch S, Strakova N, Bouchal J, Kral M, Culig Z, Kozubik A, Soucek K. Opposite
regulation of MDM2 and MDMX expression in acquisition of mesenchymal
phenotype in benign and cancer cells. Oncotarget 2015;6: 36156-71.
12. Slabakova E, Culig Z, Remsik J, Soucek K. Alternative mechanisms of miR-34a
regulation in cancer. Cell Death & Disease 2017;8.
13. Kahounova Z, Kurfurstova D, Bouchal J, Kharaishvili G, Navratil J, Remsik J,
Simeckova S, Student V, Kozubik A, Soucek K. The fibroblast surface markers FAP,
anti-fibroblast, and FSP are expressed by cells of epithelial origin and may be
altered during epithelial-to-mesenchymal transition. Cytometry A 2018;93: 941-
51.
14. Knopfova L, Biglieri E, Volodko N, Masarik M, Hermanova M, Glaus Garzon JF,
Ducka M, Kucirkova T, Soucek K, Smarda J, Benes P, Borsig L. Transcription factor
c-Myb inhibits breast cancer lung metastasis by suppression of tumor cell seeding.
Oncogene 2018;37: 1020-30.
15. Remsik J, Bino L, Kahounova Z, Kharaishvili G, Simeckova S, Fedr R, Kucirkova T,
Lenart S, Muresan XM, Slabakova E, Knopfova L, Bouchal J, Kral M, Benes P,
Soucek K. Trop-2 plasticity is controlled by epithelial-to-mesenchymal transition.
Carcinogenesis 2018;39: 1411-1418.
16. Remsik J, Fedr R, Navratil J, Bino L, Slabakova E, Fabian P, Svoboda M, Soucek K.
Plasticity and intratumoural heterogeneity of cell surface antigen expression in
breast cancer. British Journal of Cancer 2018;118: 813-819.
17. Simeckova S, Fedr R, Remsik J, Kahounova Z, Slabakova E, Soucek K.
Multiparameter cytometric analysis of complex cellular response. Cytometry A
2018;93: 239-248.
18. Simeckova S, Kahounova Z, Fedr R, Remsik J, Slabakova E, Suchankova T,
Prochazkova J, Bouchal J, Kharaishvili G, Kral M, Benes P, Soucek K. High Skp2
expression is associated with a mesenchymal phenotype and increased
tumorigenic potential of prostate cancer cells. Sci Rep 2019;9: 5695.
19. Drapela S, Bouchal J, Jolly MK, Culig Z, Soucek K. ZEB1: A Critical Regulator of Cell
Plasticity, DNA Damage Response, and Therapy Resistance. Front Mol Biosci
2020;7: 36.
20. Lenart S, Lenart P, Smarda J, Remsik J, Soucek K, Benes P. Trop2: Jack of All
Trades, Master of None. Cancers (Basel) 2020;12: 3328.
39
21. Remsik J, Pickova M, Vacek O, Fedr R, Bino L, Hampl A, Soucek K. TGF-β regulates
Sca-1 expression and plasticity of pre-neoplastic mammary epithelial stem cells.
Sci Rep 2020;10: 11396.
22. Kvokackova B, Remsik J, Jolly MK, Soucek K. Phenotypic Heterogeneity of TripleNegative
Breast Cancer Mediated by Epithelial-Mesenchymal Plasticity. Cancers
(Basel) 2021;13: 2188.
23. Drapela S, Fedr R, Vacek O, Remsik J, Soucek K. High-Throughput, Parallel Flow
Cytometry Screening of Hundreds of Cell Surface Antigens Using Fluorescent
Barcoding. Methods Mol Biol 2022;2543: 99-111.
24. Muresan XM, Slabakova E, Prochazkova J, Drapela S, Fedr R, Pickova M, Vacek O,
Vichova R, Suchankova T, Bouchal J, Kurfurstova D, Kral M, Hulinova T, Sykora RP,
Student V, Hejret V, van Weerden WM, Puhr M, Pustka V, Potesil D, Zdrahal Z,
Culig Z, Soucek K. Toll-Like Receptor 3 Overexpression Induces Invasion of
Prostate Cancer Cells, whereas Its Activation Triggers Apoptosis. Am J Pathol
2022;192: 1321-35.
25. Rihova K, Ducka M, Zambo IS, Vymetalova L, Sramek M, Trcka F, Verner J, Drapela
S, Fedr R, Suchankova T, Pavlatovska B, Ondrouskova E, Kubelkova I, Zapletalova
D, Tucek S, Mudry P, Krakorova DA, Knopfova L, Smarda J, Soucek K, Borsig L,
Benes P. Transcription factor c-Myb: novel prognostic factor in osteosarcoma. Clin
Exp Metastasis 2022;39: 375-90.
26. Kvokackova B, Fedr R, Kuzilkova D, Stuchly J, Vavrova A, Navratil J, Fabian P,
Ondrussek R, Ovesna P, Remsik J, Bouchal J, Kalina T, Soucek K. Single-cell protein
profiling defines cell populations associated with triple-negative breast cancer
aggressiveness. Molecular Oncology 2023;17: 1024-40.
40
APPENDIX: COMMENTED OVERVIEW OF SELECTED
PUBLICATIONS
Commented list of articles representing the author´s contribution to understanding cell
plasticity and cancer heterogeneity. Articles below represents a selection of 19 primary
research articles, two book chapters, and five reviews (out of 140 author’s publication
records available on WOS on January 31st
, 2024), which are related to the topic of the
habilitation.
41
Appendix 1 Vanhara P, Lincova E, Kozubik A, Jurdic P, Soucek K*, Smarda J:
Growth/differentiation factor-15 inhibits differentiation into osteoclasts-a novel
factor involved in control of osteoclast differentiation. Differentiation 2009,
78:213-22.
Significance: Survival and capability of cancer cells to form metastases fundamentally
depend on interactions with their microenvironment. Secondary tumors originating from
prostate carcinomas affect the remodeling of bone tissue and can induce both osteolytic
and osteocondensing lesions. However, molecular mechanisms responsible for selective
homing and activity of cancer cells in bone microenvironment have not been clarified
yet. Growth/differentiation factor-15 (GDF-15), a distant member of the TGF-β protein
family, has recently been associated with many human cancers, including prostate. In this
work, we unveiled the new role of GDF-15 in the modulation of osteoclast differentiation
and possibly in the therapy of bone metastases.
DOI: 10.1016/j.diff.2009.07.008
Journal: Differentiation
Impact factor (WOS, 2008): 3,180, Q2
Number of citations (WOS, 2023): 36
Most important citation:
1. Amin A, Karpowicz PA, Carey TE, Arbiser J, Nahta R, Chen ZG, et al: Evasion of antigrowth
signaling: A key step in tumorigenesis and potential target for treatment and
prophylaxis by natural compounds. Seminars in Cancer Biology 2015, 35:S55-S77.
IF(2014): 9,330
2. Siddiqui JA, et al: GDF15 promotes prostate cancer bone metastasis and colonization
through osteoblastic CCL2 and RANKL activation. Bone Research 2022; 10(1). IF(2021):
13,362
3. Silva-Bermudez LS, et al. Titanium Nanoparticles Enhance Production and Suppress
Stabilin-1-Mediated Clearance of GDF-15 in Human Primary Macrophages. Frontiers in
Immunology 2021; 12. IF(2020): 7,561
Contribution of the author/author’s team: *Shared corresponding author.
Conceptualization and data interpretation, manuscript revision.
53
Appendix 2 Starsichova A, Lincova E, Pernicova Z, Kozubik A, Soucek K: TGF-β1
suppresses IL-6-induced STAT3 activation through regulation of Jak2 expression in
prostate epithelial cells. Cell Signal 2010, 22:1734-44.
Significance: Chronic inflammation plays an essential role in the initiation and
progression of various human diseases, including benign prostatic hyperplasia or
prostate cancer. Here, we show the interaction between TGF-β1 and IL-6 signaling and
suggest another mechanism of how defects in TGF-β signaling, frequently associated with
prostate pathologies, can contribute to the disruption of tissue homeostasis.
DOI: 10.1016/j.cellsig.2010.06.014
Journal: CELLULAR SIGNALLING
Impact factor (WOS, 2009): 4,094, Q2
Number of citations (WOS, 2023): 25
Most important citation:
1. de Boer HR, Pool M, Joosten E, Everts M, Samplonius DF, Helfrich W, et al.
Quantitative proteomics analysis identifies MUC1 as an effect sensor of EGFR
inhibition. Oncogene 2019, 38(9):1477-1488. IF(2018): 6,634
2. De Nunzio C, Kramer G, Marberger M, Montironi R, Nelson W, Schröder F, et al. The
Controversial Relationship Between Benign Prostatic Hyperplasia and Prostate Cancer:
The Role of Inflammation. European Urology 2011, 60(1):106-117. IF(2010): 8,843
3. Menon DR, Wels C, Rad EB, Joshi S, Knausz H, Lade-Keller J, et al. TGF-β1 and TNF-α
differentially regulate Twist1 mediated resistance towards BRAF/MEK inhibition in
melanoma. Pigment Cell & Melanoma Research 2013, 26(6). IF(2012): 5,839
Contribution of the author/author’s team: Corresponding author. Conceptualization and
data interpretation, manuscript revision.
67
Appendix 3 Pernicova Z, Slabakova E, Kharaishvili G, Bouchal J, Kral M, Kunicka Z,
Machala M, Kozubik A, Soucek K: Androgen depletion induces senescence in
prostate cancer cells through down-regulation of Skp2. Neoplasia 2011, 13:526-
36.
Significance: Although the induction of senescence in cancer cells is a potent mechanism
of tumor suppression, senescent cells remain metabolically active and may secrete a
broad spectrum of factors that promote tumorigenicity in neighboring malignant cells.
Here, we showed that androgen deprivation therapy (ADT), a widely used treatment for
advanced prostate cancer, induces a senescence-associated secretory phenotype in
prostate cancer epithelial cells. We revealed a previously unrecognized link between
inhibition of androgen receptor signaling, down-regulation of S-phase kinase-associated
protein 2, and the appearance of secretory, tumor-promoting senescent cells in prostate
tumors.
DOI: 10.1593/neo.11182
Journal: NEOPLASIA
Impact factor (WOS, 2010): 5,476, Q1
Number of citations (WOS, 2023): 59
Most important citation:
1. de Bono JS, Guo C, Gurel B, De Marzo AM, Sfanos KS, Mani RS, et al: Prostate
carcinogenesis: inflammatory storms. Nature Reviews Cancer 2020, 20(8):455-469.
IF(2019): 53,030
2. Fiard G, Stavrinides V, Chambers ES, Heavey S, Freeman A, Ball R, et al. Cellular
senescence as a possible link between prostate diseases of the ageing male. Nature
Reviews Urology 2021, 18(10):597-610. IF(2020): 14,432
3. Galsky MD. Resistance to prostate-cancer treatment is driven by immune cells.
Nature 2018, 559(7714):338-339. IF(2017): 41,577
Contribution of the author/author’s team: Corresponding author. Conceptualization and
data interpretation, manuscript revision.
85
Appendix 4 Slabakova E, Pernicova Z, Slavickova E, Starsichova A, Kozubik A,
Soucek K: TGF-β1-induced EMT of non-transformed prostate hyperplasia cells is
characterized by early induction of SNAI2/Slug. Prostate 2011, 71:1332-43.
Significance: Epithelial-mesenchymal transition (EMT) underlying cancer cell invasion and
metastasis has been thoroughly studied in prostate cancer. Although EMT markers have
been clinically observed in benign prostate hyperplasia, molecular events underlying the
onset and progression of EMT in benign prostate cells have not been described. In this
study, we suggest that in benign prostate hyperplasia cells, the transcription factor
SNAI2/Slug is essential for EMT initiation. In contrast, in cooperation with the miR-200
family, the ZEB family of transcription factors may oppose the EMT phenotype's reversal.
DOI: 10.1002/pros.21350
Journal: PROSTATE
Impact factor (WOS, 2010): 3,377, Q1
Number of citations (WOS, 2023): 83
Most important citation:
1. Fang YX, Gao WQ. Roles of microRNAs during prostatic tumorigenesis and tumor
progression. Oncogene 2014, 33(2):135-147. IF(2013): 8,559
2. Jung HY, Fattet L, Yang J. Molecular Pathways: Linking Tumor Microenvironment to
Epithelial-Mesenchymal Transition in Metastasis. Clinical Cancer Research 2015,
21(5):962-968. IF(2014): 8,722
3. Jurj A, Ionescu C, Berindan-Neagoe I, Braicu C. The extracellular matrix alteration,
implication in modulation of drug resistance mechanism: friends or foes? Journal of
Experimental & Clinical Cancer Research 2022, 41(1). IF(2022): 12,658
Contribution of the author/author’s team: Corresponding author. Conceptualization and
data interpretation, manuscript revision.
99
Appendix 5 Knopfova L, Benes P, Pekarcikova L, Hermanova M, Masarik M,
Pernicova Z, Soucek K, Smarda J: c-Myb regulates matrix metalloproteinases 1/9,
and cathepsin D: implications for matrix-dependent breast cancer cell invasion
and metastasis. Molecular Cancer 2012; 11:15.
Significance: The significance of this study lies in its contribution to the understanding of
the mechanisms behind tumor development and metastasis, as well as the potential
implications for future cancer treatment strategies. The research highlights the
importance of c-Myb in regulating tumor growth and metastasis, specifically in the
context of MMP-19. This knowledge can contribute to developing more effective cancer
treatments that target the c-Myb pathway and inhibit tumor growth and metastasis.
DOI: 10.1186/1476-4598-11-15
Journal: MOLECULAR CANCER
Impact factor (WOS, 2011): 3,993, Q1
Number of citations (WOS, 2023): 53
Most important citation:
1. Abhange K, Makler A, Wen Y, Ramnauth N, Mao WJ, Asghar W, et al. Small
extracellular vesicles in cancer. Bioactive Materials 2021, 6(11):3705-3743. IF(2020):
14,593
2. Anand S, Vikramdeo KS, Sudan SK, Sharma A, Acharya S, Khan MA, et al. From
modulation of cellular plasticity to potentiation of therapeutic resistance: new and
emerging roles of MYB transcription factors in human malignancies. Cancer and
Metastasis Reviews 2023. IF(2022): 9,2
3. van Gogh M, Garzon JFG, Sahin D, Knopfova L, Benes P, Boyman O, et al. Tumor CellIntrinsic
c-Myb Upregulation Stimulates Antitumor Immunity in a Murine Colorectal
Cancer Model. Cancer Immunology Research 2023, 11(10):1432-1444. IF(2022): 10,1
Contribution of the author/author’s team: Co-author. Methodology and manuscript
revision.
117
Appendix 6 Vanhara P, Hampl A, Kozubik A, Soucek K: Growth/differentiation
factor-15: prostate cancer suppressor or promoter? Prostate Cancer Prostatic Dis
2012, 15:320-8.
Significance: In this review, we focused on growth/differentiation factor-15 (GDF-15), a
divergent member of the TGF-β family. This stress-induced cytokine has been proposed
to possess immunomodulatory functions, and its high expression is often associated with
cancer progression, including prostate cancer (PCa). We discussed studies that focus on
regulating GDF-15 expression and its role in tissue homeostasis, repair, and the immune
response, emphasizing the role in PCa development.
DOI: 10.1038/pcan.2012.6
Journal: PROSTATE CANCER AND PROSTATIC DISEASES
Impact factor (WOS, 2011): 2,421, Q2
Number of citations (WOS, 2023): 50
Most important citation:
1. Ge RB, Wang ZW, Cheng L. Tumor microenvironment heterogeneity an important
mediator of prostate cancer progression and therapeutic resistance. Npj Precision
Oncology 2022, 6(1). IF(2021): 10,123
2. Mullican SE, Rangwala SM. Uniting GDF15 and GFRAL: Therapeutic Opportunities in
Obesity and Beyond. Trends in Endocrinology and Metabolism 2018, 29(8):560-570.
IF(2027): 10,769
3. Ratnam NM, Peterson JM, Talbert EE, Ladner KJ, Rajasekera PV, Schmidt CR, et al. NFκB
regulates GDF-15 to suppress macrophage surveillance during early tumor
development. Journal of Clinical Investigation 2017, 127(10):3796-3809. IF(2016): 12,784
Contribution of the author/author’s team: Corresponding author. Conceptualization and
manuscript revision.
129
Appendix 7 Fedr R, Pernicova Z, Slabakova E, Strakova N, Bouchal J, Grepl M,
Kozubik A, Soucek K: Automatic cell cloning assay for determining the clonogenic
capacity of cancer and cancer stem-like cells. Cytometry A 2013, 83:472-82.
Significance: The clonogenic assay is a well-established in vitro method for testing cells'
survival and proliferative capability. It can be used to determine the cytotoxic effects of
various treatments, including chemotherapeutics and ionizing radiation. However, this
approach can also characterize cells with different phenotypes and biological properties,
such as stem cells or cancer stem cells. Here, we implemented a faster and more precise
method for assessing the cloning efficiency of cancer stem-like cells characterized and
separated using a high-speed cell sorter. We demonstrated a straightforward approach
for determining the clonogenic capacity of cancer stem-like cells identified in both cell
lines and patient samples.
DOI: 10.1002/cyto.a.22273
Journal: CYTOMETRY PART A
Impact factor (WOS, 2012): 3,711, Q2
Number of citations (WOS, 2023): 26
Most important citation:
1. Dayal JHS, Mason SM, Salas-Alanis JC, McGrath JA, Taylor RG, Mellerio JE, et al.
Heterogeneous addiction to transforming growth factor-beta signalling in recessive
dystrophic epidermolysis bullosa-associated cutaneous squamous cell carcinoma.
British Journal of Dermatology 2021, 184(4):697-708. IF(2020): 9,302
2. Liu NQ, Maresca M, van den Brand T, Braccioli L, Schijns M, Teunissen H, et al. WAPL
maintains a cohesin loading cycle to preserve cell-type-specific distal gene regulation.
Nature Genetics 2021, 53(1). IF(2020): 38,330
3. ter Huurne M, Chappell J, Dalton S, Stunnenberg HG. Distinct Cell-Cycle Control in Two
Different States of Mouse Pluripotency. Cell Stem Cell 2017, 21(4):449. IF(2016): 23,394
Contribution of the author/author’s team: Corresponding author. Conceptualization,
data interpretation and manuscript revision.
143
Appendix 8 Pernicova Z, Vanhara P, Soucek K: Formation of secretory senescent
cells in prostate tumors: the role of androgen receptor activity and cell cycle
regulation. Tumor Dormancy, Quiescence, and Senescence, Volume 1: Aging,
Cancer, and Noncancer Pathologies. Edited by MA H. Springer Netherlands, 2013.
pp. 303-16.
Significance: The induction of senescence in cancer cells is believed to be a potent
mechanism of tumor suppression; however, senescent cells remain metabolically active
and secrete a broad spectrum of factors, modulate the tissue microenvironment, and
potentially promote tumorigenicity in neighboring malignant cells. In this chapter, we
summarized possible mechanisms and consequences of the formation of the secretory
phenotypes in prostate tumors and the role of the androgen receptor and cell cycle
regulation in these processes.
DOI: 10.1007/978-94-007-5958-9_26
Book: Tumor Dormancy, Quiescence, and Senescence, Volume 1: Aging, Cancer, and
Noncancer Pathologies.
Impact factor (WOS): n-a
Number of citations (WOS): n-a
Most important citation: n-a
Contribution of the author/author’s team: Corresponding author. Conceptualization and
manuscript revision.
159
Appendix 9 Pernicova Z, Slabakova E, Fedr R, Simeckova S, Jaros J, Suchankova T,
Bouchal J, Kharaishvili G, Kral M, Kozubik A, Soucek K: The role of high cell density
in the promotion of neuroendocrine transdifferentiation of prostate cancer cells.
Mol Cancer 2014, 13:113.
Significance: Neuroendocrine transdifferentiation (NED) and the emergence of
neuroendocrine-like cancer cells in prostate tumors frequently arise from androgendepleted
prostate adenocarcinoma and are associated with the development of
castration-resistant prostate cancer and poor prognosis. In this study, we showed a new
relationship between cell cycle attenuation and the promotion of NED. We suggested
high cell density as a trigger for cAMP signaling that can mediate reversible NED in
prostate cancer cells.
DOI: 10.1186/1476-4598-13-113
Journal: MOLECULAR CANCER
Impact factor (WOS, 2013): 5,397, Q1
Number of citations (WOS, 2023): 25
Most important citation:
1. Friedrich M, Wiedemann K, Reiche K, Puppel SH, Pfeifer G, Zipfel I, et al. The Role of
lncRNAs TAPIR-1 and-2 as Diagnostic Markers and Potential Therapeutic Targets in
Prostate Cancer. Cancers 2020, 12(5). IF(2019): 6,126
2. Jorda R, Hendrychová D, Voller J, Reznícková E, Gucky T, Krystof V. How Selective Are
Pharmacological Inhibitors of Cell-Cycle-Regulating Cyclin-Dependent Kinases? Journal
of Medicinal Chemistry 2018, 61(20):9105-9120. IF(2017): 6,253
3. Santer FR, Erb HHH, McNeill RV. Therapy escape mechanisms in the malignant
prostate. Seminars in Cancer Biology 2015, 35:133-144. IF(2014): 9,330
4. Santer, F. R., Erb, H. H. H. & Mcneill, R. V. Therapy escape mechanisms in the
malignant prostate. Seminars in Cancer Biology, 35, 133-144, (2015). Doi:
10.1016/j.semcancer.2015.08.005. IF (2014): 9,330
Contribution of the author/author’s team: Corresponding author. Conceptualization,
data interpretation and manuscript revision.
177
Appendix 10 Kratochvilova K, Horak P, Esner M, Soucek K, Pils D, Anees M,
Tomasich E, Drafi F, Jurtikova V, Hampl A, Krainer M, Vanhara P: Tumor
suppressor candidate 3 (TUSC3) prevents the epithelial-to-mesenchymal transition
and inhibits tumor growth by modulating the endoplasmic reticulum stress
response in ovarian cancer cells. Int J Cancer 2015, 137:1330-40.
Significance: Tumor suppressor candidate 3 (TUSC3) is a putative tumor suppressor gene
located at chromosomal region 8p22, which is often lost in epithelial cancers. Epigenetic
silencing of TUSC3 has been associated with poor prognosis, and hypermethylation of its
promoter provides an independent biomarker of overall and disease-free survival in
ovarian cancer patients. In this study, we establish TUSC3 as a novel ovarian cancer
tumor suppressor using a xenograft mouse model and demonstrate that loss of TUSC3
alters the molecular response to endoplasmic reticulum stress and induces hallmarks of
the epithelial-to-mesenchymal transition in ovarian cancer cells.
DOI: 10.1002/ijc.29502
Journal: INTERNATIONAL JOURNAL OF CANCER
Impact factor (WOS, 2014): 5,085, Q1
Number of citations (WOS, 2023): 37
Most important citation:
1. Deng RX, et al. Downregulation of TUSC3 promotes EMT and hepatocellular
carcinoma progression through LIPC/AKT axis. Journal of Translational Medicine 2022,
20(1). IF(2021): 8,448
2. Jeon YJ, et al. miRNA-mediated TUSC3 deficiency enhances UPR and ERAD to
promote metastatic potential of NSCLC. Nature Communications 2018, 9. IF(2017):
12,353
3. Zhang Y, et al. Scavenger Receptor A1 Prevents Metastasis of Non-Small Cell Lung
Cancer via Suppression of Macrophage Serum Amyloid A1. Cancer Research 2017,
77(7):1586-1598. IF(2016): 9,122
Contribution of the author/author’s team: EMT data interpretation and manuscript
revision.
191
Appendix 11 Slabakova E, Kharaishvili G, Smejova M, Pernicova Z, Suchankova T,
Remsik J, Lerch S, Strakova N, Bouchal J, Kral M, Culig Z, Kozubik A, Soucek K:
Opposite regulation of MDM2 and MDMX expression in acquisition of
mesenchymal phenotype in benign and cancer cells. Oncotarget 2015, 6:36156-71.
Significance: The plasticity of cancer cells, manifested by transitions between epithelial
and mesenchymal phenotypes, represents a challenging issue in treating neoplasias. Both
epithelial-mesenchymal transition (EMT) and mesenchymal-epithelial transition (MET)
are implicated in metastasis formation and acquiring stem cell-like properties. Mouse
double minute (MDM) 2 and MDMX are essential players in cancer progression, as they
act as regulators of p53, but their function in EMT and metastasis may be contradictory.
Here, we showed that the EMT phenotype in multiple cellular models and clinical
prostate and breast cancer samples is associated with a decrease in MDM2 and an
increase in MDMX expression and provided an alternative context-specific role of MDM2
in EMT, cell migration, metastasis, and therapy resistance.
DOI: 10.18632/oncotarget.5392
Journal: ONCOTARGET
Impact factor (WOS, 2014): 6,359, Q1
Number of citations (WOS, 2023): 16
Most important citation:
1. Gao C, Xiao G, Piersigilli A, Gou JT, Ogunwobi O, Bargonetti J. Context-dependent roles
of MDMX (MDM4) and MDM2 in breast cancer proliferation and circulating tumor
cells. Breast Cancer Research 2019, 21. IF(2018): 5,676
2. Giridhar PV, Williams K, VonHandorf AP, Deford PL, Kasper S. Constant Degradation of
the Androgen Receptor by MDM2 Conserves Prostate Cancer Stem Cell Integrity.
Cancer Research 2019, 79(6):1124-1137. IF(2018): 8,378
Contribution of the author/author’s team: Corresponding author. Conceptualization,
data interpretation, and manuscript revision.
209
Appendix 12 Slabakova E, Culig Z, Remsik J, Soucek K: Alternative mechanisms of
miR-34a regulation in cancer. Cell Death Dis 2017, 8:e3100.
Significance: MicroRNA miR-34a is recognized as a master regulator of tumor
suppression. In this work, we reviewed p53-independent mechanisms regulating the
expression of miR-34a, including multiple mechanisms that operate in the context of
cancer-associated phenomena, such as aberrant oncogene signaling, EMT, or
inflammation.
DOI: 10.1038/cddis.2017.495
Journal: CELL DEATH & DISEASE
Impact factor (WOS, 2016): 5,965, Q1
Number of citations (WOS, 2023): 183
Most important citation:
1. Chen S, et al. Non-coding RNAs, guardians of the p53 galaxy. Seminars in Cancer
Biology 2021, 75:72-83. IF(2020): 15,707
2. Joo JI, et al. Realizing Cancer Precision Medicine by Integrating Systems Biology and
Nanomaterial Engineering. Advanced Materials 2020, 32(35). IF(2019): 27,398
3. Pathak GA, et al. Two-stage Bayesian GWAS of 9576 individuals identifies SNP regions
that are targeted by miRNAs inversely expressed in Alzheimer's and cancer. Alzheimers
& Dementia 2020, 16(1):162-177. IF(2019): 17,127
4. Proença C, et al. The role of flavonoids in the regulation of epithelial-mesenchymal
transition in cancer: A review on targeting signaling pathways and metastasis.
Medicinal Research Reviews 2023, 43(6):1878-1945. IF(2022): 13,3
5. Sehgal K, Barbie DA. Targeting the mutant p53 secretome. Journal of Clinical
Investigation 2021, 131(1). IF(2020): 14,808
Contribution of the author/author’s team: Corresponding author. Conceptualization,
and manuscript revision.
221
Appendix 13 Kahounova Z, Kurfurstova D, Bouchal J, Kharaishvili G, Navratil J,
Remsik J, Simeckova S, Student V, Kozubik A, Soucek K: The fibroblast surface
markers FAP, anti-fibroblast, and FSP are expressed by cells of epithelial origin
and may be altered during epithelial-to-mesenchymal transition. Cytometry A
2018, 93:941-51.
Significance: This study supports the findings that the widely used fibroblast markers are
not fibroblast specific and may also be expressed by cells of epithelial origin (e.g., cells
undergoing EMT). Therefore, the expression of these markers should be interpreted with
caution, and the combination of several epitopes for both positive (anti-fibroblast or
fibroblast activation protein alpha) and negative (EpCAM) identification of fibroblasts
from breast and prostate tumor tissues is advised.
DOI: 10.1002/cyto.a.23101
Journal: CYTOMETRY PART A
Impact factor (WOS, 2017): 3,260, Q2
Number of citations (WOS, 2023): 45
Most important citation:
1. Hettiarachchi SU, Li YH, Roy J, Zhang FH, Puchulu-Campanella E, Lindeman SD, et al.
Targeted inhibition of PI3 kinase/mTOR specifically in fibrotic lung fibroblasts
suppresses pulmonary fibrosis in experimental models. Science Translational Medicine
2020, 12(567). IF(2019): 16,304
2. Wan ZP, Zhang S, Zhong AX, Shelton SE, Campisi M, Sundararaman SK, et al. A robust
vasculogenic microfluidic model using human immortalized endothelial cells and Thy1
positive fibroblasts. Biomaterials 2021, 276. IF(2020): 12,479
3. Yang DK, Liu J, Qian H, Zhuang Q. Cancer-associated fibroblasts: from basic science to
anticancer therapy. Experimental and Molecular Medicine 2023, 55(7):1322-1332.
IF(2022): 12,8
4. Pure, E. & Blomberg, R. Pro-tumorigenic roles of fibroblast activation protein in
cancer: back to the basics. Oncogene 2018, 37(32), 4343-4357. IF(2018): 6,854
Contribution of the author/author’s team: Corresponding author. Conceptualization,
data interpretation, and manuscript revision.
235
Appendix 14 Knopfova L, Biglieri E, Volodko N, Masarik M, Hermanova M, Glaus
Garzon JF, Ducka M, Kucirkova T, Soucek K, Smarda J, Benes P, Borsig L:
Transcription factor c-Myb inhibits breast cancer lung metastasis by suppression
of tumor cell seeding. Oncogene 2018;37: 1020-30.
Significance: Here, we investigate the role of the transcription factor c-Myb in breast
cancer (BC) lung metastasis and its potential as a prognostic marker and therapeutic
target. We showed increased c-Myb expression in breast cancer (BC) cells inhibits
spontaneous lung metastasis through impaired tumor cell extravasation. BC cells with
increased lung metastatic capacity exhibit low c-Myb levels. These findings demonstrate
the potential role of c-Myb as a prognostic marker for lung metastasis in BC patients and
suggest that it could serve as a therapeutic target for improving patient outcomes.
DOI: 10.1038/onc.2017.392
Journal: ONCOGENE
Impact factor (WOS, 2017): 6,854, Q1
Number of citations (WOS, 2023): 15
Most important citation:
1. Bayley R, Ward C, Garcia P. MYBL2 amplification in breast cancer: Molecular
mechanisms and therapeutic potential. Biochimica Et Biophysica Acta-Reviews on
Cancer 2020, 1874(2). IF(2019): 7,365
2. Hashemi M, et al. Biological functions and molecular interactions of Wnt/13-catenin
in breast cancer: Revisiting signaling networks. International Journal of Biological
Macromolecules 2023, 232. IF(2022): 8,2
3. van Gogh M, et al. Tumor Cell-Intrinsic c-Myb Upregulation Stimulates Antitumor
Immunity in a Murine Colorectal Cancer Model. Cancer Immunology Research 2023,
11(10):1432-1444. IF(2022): 10,1
Contribution of the author/author’s team: Co-author. Methodology and manuscript
revision.
249
Appendix 15 Remsik J, Bino L, Kahounova Z, Kharaishvili G, Simeckova S, Fedr R,
Kucirkova T, Lenart S, Muresan XM, Slabakova E, Knopfova L, Bouchal J, Kral M,
Benes P, Soucek K: Trop2 plasticity is controlled by epithelial-to-mesenchymal
transition. Carcinogenesis 2018, 39:1411-8.
Significance: The cell surface glycoprotein Trop2 is commonly overexpressed in
carcinomas and represents an exceptional antigen for targeted therapy. Here, we
provide evidence that surface Trop2 expression is functionally connected with an
epithelial phenotype in breast and prostate cell lines and patient tumor samples.
Moreover, our data suggest that the cancer plasticity-driven intratumoral heterogeneity
in Trop2 expression may significantly contribute to response and resistance to therapies
targeting Trop2-expressing cells.
DOI: 10.1093/carcin/bgy095
Journal: CARCINOGENESIS
Impact factor (WOS, 2017): 5,072, Q1
Number of citations (WOS, 2023): 18
Most important citation:
1. Bardia A, Tolaney SM, Punie K, Loirat D, Oliveira M, Kalinsky K, et al. Biomarker
analyses in the phase III ASCENT study of sacituzumab govitecan versus chemotherapy
in patients with metastatic triple-negative breast cancer. Annals of Oncology 2021,
32(9):1148-1156. IF(2020): 32,976
2. Liu HC, Bai LL, Huang L, Ning N, Li L, Li YJ, et al. Bispecific antibody targeting
TROP2xCD3 suppresses tumor growth of triple negative breast cancer. Journal for
Immunotherapy of Cancer 2021, 9(10). IF(2020): 13,751
3. Liu XL, Deng JW, Yuan Y, Chen WJ, Sun WS, Wang YH, et al. Advances in Trop2targeted
therapy: Novel agents and opportunities beyond breast cancer. Pharmacology
& Therapeutics 2022, 239. IF(2022): 13,5
Contribution of the author/author’s team: Corresponding author. Conceptualization,
data interpretation, and manuscript revision.
259
Appendix 16 Remsik J, Fedr R, Navratil J, Bino L, Slabakova E, Fabian P, Svoboda
M, Soucek K: Plasticity and intratumoural heterogeneity of cell surface antigen
expression in breast cancer. Br J Cancer 2018, 118:813-9.
Significance: The intratumoral heterogeneity, often driven by epithelial-to-mesenchymal
transition (EMT), significantly contributes to chemoresistance and disease progression in
adenocarcinomas. Here, we introduced a high-throughput screening platform to identify
surface antigens associated with epithelial-mesenchymal plasticity in well-defined pairs
of epithelial cell lines and their mesenchymal counterparts. We found that surface CD9,
CD29, CD49c, and integrin β5 are lost in breast cancer cells undergoing EMT in vivo. We
propose that the overall landscape of the 10-molecule surface signature expression
reflects the epithelial-mesenchymal plasticity in breast cancer.
DOI: 10.1038/bjc.2017.497
Journal: BRITISH JOURNAL OF CANCER
Impact factor (WOS, 2017): 5,922, Q1
Number of citations (WOS, 2023): 17
Most important citation:
1. Abou-Fadel J, et al. CCM signaling complex (CSC) couples both classic and non-classic
Progesterone receptor signaling. Cell Communication and Signaling 2022, 20(1).
IF(2021): 7,54
2. Kopylov AT, et al. Convolutional neural network in proteomics and metabolomics for
determination of comorbidity between cancer and schizophrenia. Journal of Biomedical
Informatics 2021, 122. IF(2020): 6,317
3. Morales E, Olson M, Iglesias F, Dahiya S, Luetkens T, Atanackovic D. Role of
immunotherapy in Ewing sarcoma. Journal for Immunotherapy of Cancer 2020, 8(2).
IF(2019): 10,252
Contribution of the author/author’s team: Corresponding author. Conceptualization,
data interpretation and manuscript revision.
269
Appendix 17 Simeckova S, Fedr R, Remsik J, Kahounova Z, Slabakova E, Soucek K:
Multiparameter cytometric analysis of complex cellular response. Cytometry A
2018;93: 239-48.
Significance: The study focuses on using flow cytometry to analyze the effects of various
treatments on cellular responses by introducing a multiparametric protocol for complex
analysis of cytokinetics by simultaneously detecting seven fluorescence parameters. We
demonstrated that this protocol has the potential to provide complex and simultaneous
analysis of cytokinetics and analyze the heterogeneity of the response at the single-cell
level.
DOI: 10.1002/cyto.a.23295
Journal: CYTOMETRY PART A
Impact factor (WOS, 2018): 3,260
Number of citations (Google Scholar, 2023): 2
Contribution of the author/author’s team: Corresponding author. Conceptualization,
data interpretation and manuscript revision.
281
Appendix 18 Simeckova S, Kahounova Z, Fedr R, Remsik J, Slabakova E, Suchankova
T, Prochazkova J, Bouchal J, Kharaishvili G, Kral M, Benes P, Soucek K: High Skp2
expression is associated with a mesenchymal phenotype and increased
tumorigenic potential of prostate cancer cells. Sci Rep 2019, 9:5695.
Significance: Skp2 is a crucial component of SCFSkp2 E3 ubiquitin ligase and is often
overexpressed in various types of cancer, including prostate cancer (PCa). This study
uncovered the Skp2-mediated CSC-like phenotype with oncogenic functions in PCa.
DOI: 10.1038/s41598-019-42131-y
Journal: SCIENTIFIC REPORTS
Impact factor (WOS, 2018): 4,011, Q1
Number of citations (WOS, 2023): 20
Most important citation:
1. Asmamaw MD, Liu Y, Zheng YC, Shi XJ, Liu HM. Skp2 in the ubiquitin-proteasome
system: A comprehensive review. Medicinal Research Reviews 2020, 40(5):1920-1949.
IF(2019): 9,3
2. Celada SI, Li GL, Celada LJ, Lu WF, Kanagasabai T, Feng WR, et al. Lysosome-dependent
FOXA1 ubiquitination contributes to luminal lineage of advanced prostate cancer.
Molecular Oncology 2023. IF(2022): 6,6
3. Khan AQ, Al-Tamimi M, Uddin S, Steinhoff M. F-box proteins in cancer stemness: An
emerging prognostic and therapeutic target. Drug Discovery Today 2021, 26(12):2905-
2914. IF(2020): 7,851
Contribution of the author/author’s team: Corresponding author. Conceptualization,
data interpretation and manuscript revision.
293
Appendix 19 Drapela S, Bouchal J, Jolly MK, Culig Z, Soucek K: ZEB1: A Critical
Regulator of Cell Plasticity, DNA Damage Response, and Therapy Resistance. Front
Mol Biosci 2020, 7:36.
Significance: Zinc finger E-box binding homeobox 1 (ZEB1) is a prime element of a
network of transcription factors controlling EMT and has been identified as an essential
molecule in regulating DNA damage, cancer cell differentiation, and metastasis. In this
review, we focused on the role of ZEB1 in regulating DDR and described the mechanisms
of ZEB1-dependent chemoresistance.
DOI: 10.3389/fmolb.2020.00036
Journal: FRONT MOL BIOSCI
Impact factor (WOS, 2019): 4,188, Q2
Number of citations (WOS, 2023): 90
Most important citation:
1. Ervin EH, et al. Inside the stemness engine: Mechanistic links between deregulated
transcription factors and stemness in cancer. Seminars in Cancer Biology 2022, 87:48-83.
IF(2021): 17,012
2. Pommier RM, et al. Comprehensive characterization of claudin-low breast tumors
reflects the impact of the cell-of-origin on cancer evolution. Nature Communications
2020, 11(1). IF(2019): 12,121
3. Proença C, et al. The role of flavonoids in the regulation of epithelial-mesenchymal
transition in cancer: A review on targeting signaling pathways and metastasis.
Medicinal Research Reviews 2023, 43(6):1878-1945. IF(2022): 13,3
4. Zhang N, et al. Novel therapeutic strategies: targeting epithelial-mesenchymal
transition in colorectal cancer. Lancet Oncology 2021, 22(8):E358-E368. IF(2020): 41,316
5. Zhang QM, et al. Adipocyte-Derived Exosomal MTTP Suppresses Ferroptosis and
Promotes Chemoresistance in Colorectal Cancer. Advanced Science 2022, 9(28).
IF(2021): 17,521
Contribution of the author/author’s team: Corresponding author. Conceptualization and
manuscript revision.
305
Appendix 20 Lenart S, Lenart P, Smarda J, Remsik J, Soucek K, Benes P: Trop2: Jack
of All Trades, Master of None. Cancers (Basel) 2020, 12.
Significance: Trophoblast cell surface antigen 2 (Trop2) is a widely expressed
glycoprotein and an epithelial cell adhesion molecule (EpCAM) family member. In this
article, we review the current knowledge about the yet controversial function of Trop2 in
homeostasis and pathology.
DOI: 10.3390/cancers12113328
Journal: CANCERS
Impact factor (WOS, 2020): 6,126, Q1
Number of citations (WOS, 2023): 46
Most important citation:
1. Lei ZN, Teng QX, Tian Q, Chen W, Xie YH, Wu KM, et al. Signaling pathways and
therapeutic interventions in gastric cancer. Signal Transduction and Targeted Therapy
2022, 7(1). IF(2021): 38,120
2. Li CC, Liu J, Yang X, Yang Q, Huang WP, Zhang MY, et al. Theranostic application of
64Cu/177Lu-labeled anti-Trop2 monoclonal antibody in pancreatic cancer tumor models.
European Journal of Nuclear Medicine and Molecular Imaging 2022, 50(1):168-183.
IF(2021): 10,057
3. Micalizzi DS, Che D, Nicholson BT, Edd JF, Desai N, Lang ER, et al. Targeting breast and
pancreatic cancer metastasis using a dual-cadherin antibody. Proceedings of the
National Academy of Sciences of the United States of America 2022, 119(43). IF(2021):
12,779
Contribution of the author/author’s team: Manuscript revision.
335
Appendix 21 Remsik J, Pickova M, Vacek O, Fedr R, Bino L, Hampl A, Soucek K: TGFβ
regulates Sca-1 expression and plasticity of pre-neoplastic mammary epithelial
stem cells. Sci Rep 2020, 10:11396.
Significance: The epithelial-mesenchymal plasticity, in tight association with stemness,
contributes to the mammary gland homeostasis, evolution of early neoplastic lesions,
and cancer dissemination. In this study, we mechanistically dissected the TGF-β familydriven
regulation of Sca-1, one of the most commonly used adult stem cell markers. We
further proved that TGF-β disrupts the lineage commitment and promotes the
accumulation of tumor-initiating cells in pre-neoplastic cells.
DOI: 10.1038/s41598-020-67827-4
Journal: SCI REP
Impact factor (WOS, 2020): 3,998, Q1
Number of citations (WOS, 2023): 4
Most important citation:
1. Chhetri D, Vengadassalapathy S, Venkadassalapathy S, Balachandran V, Umapathy VR,
Veeraraghavan VP, et al. Pleiotropic effects of DCLK1 in cancer and cancer stem cells.
Frontiers in Molecular Biosciences 2022, 9. IF(2021): 6,113
Contribution of the author/author’s team: Corresponding author. Conceptualization of
data interpretation and manuscript revision.
349
Appendix 22 Kvokackova B, Remsik J, Jolly MK, Soucek K: Phenotypic Heterogeneity
of Triple-Negative Breast Cancer Mediated by Epithelial-Mesenchymal Plasticity.
Cancers (Basel) 2021, 13.
Significance: Triple-negative breast cancer (TNBC) is a subtype of breast carcinoma
known for its unusually aggressive behavior and poor clinical outcome. Besides the lack
of molecular targets for therapy and profound intratumoral heterogeneity, the quick
overt metastatic spread remains a significant obstacle to effective clinical management.
In this review, we focus on cellular drivers underlying EMT/MET phenotypic plasticity and
its detrimental consequences in the context of TNBC cancer.
DOI: 10.3390/cancers13092188
Journal: CANCERS
Impact factor (WOS, 2020): 6,639, Q1
Number of citations (WOS, 2023): 31
Most important citation:
1. Chen CR, Shen M, Wan XF, Sheng LL, He Y, Xu ML, et al. Activated T cell-derived
exosomes for targeted delivery of AXL-siRNA loaded paclitaxel-poly-L-lysine prodrug to
overcome drug resistance in triple-negative breast cancer. Chemical Engineering Journal
2023, 468. IF(2022): 15,1
2. Li F, Sun HZ, Yu YH, Che N, Han JY, Cheng RF, et al. RIPK1-dependent necroptosis
promotes vasculogenic mimicry formation via eIF4E in triple-negative breast cancer.
Cell Death & Disease 2023, 14(5). IF(2022): 9,0
3. Queen A, Bhutto HN, Yousuf M, Syed MA, Hassan MI. Carbonic anhydrase IX: A tumor
acidification switch in heterogeneity and chemokine regulation. Seminars in Cancer
Biology 2022, 86:899-913. IF(2021): 17,012
Contribution of the author/author’s team: Corresponding author. Conceptualization and
manuscript revision.
371
Appendix 23 Drapela S, Fedr R, Vacek O, Remsik J, Soucek K: High-Throughput,
Parallel Flow Cytometry Screening of Hundreds of Cell Surface Antigens Using
Fluorescent Barcoding. Apoptosis and Cancer: Methods in Molecular Biology.
Edited by Barcenilla H, Diaz D. New York, USA: Springer Nature, 2022.
Significance: Multicolor flow cytometry allows the analysis of tens of cellular parameters
in millions of cells at a single-cell resolution within minutes. Here, we developed a highthroughput
cytometry-based platform for profiling the expression of surface molecules
using immunofluorescence. This powerful approach will help to identify novel biomarkers
and druggable targets and facilitate the discovery of new concepts in immunology,
oncology, and developmental biology.
DOI: 10.1007/978-1-0716-2553-8_9
Book: Apoptosis and Cancer: Methods and Protocol.
Impact factor (WOS, 2022): n-a
Number of citations (WOS, 2023): n-a
Most important citation: n-a
Contribution of the author/author’s team: Corresponding author. Conceptualization and
manuscript revision.
387
Appendix 24 Muresan XM, Slabakova E, Prochazkova J, Drapela S, Fedr R, Pickova
M, Vacek O, Vichova R, Suchankova T, Bouchal J, Kurfurstova D, Kral M, Hulinova
T, Sykora RP, Student V, Hejret V, van Weerden WM, Puhr M, Pustka V, Potesil D,
Zdrahal Z, Culig Z, Soucek K: Toll-like receptor 3 (TLR3) overexpression induces
invasion of prostate cancer cells, whereas its activation triggers apoptosis. Am J
Pathol 2022.
Significance: Toll-like receptor 3 (TLR3) is an endosomal receptor expressed in several
immune and epithelial cells. Recent studies have highlighted its expression also in solid
tumors, including prostate cancer (PCa), and described its role mainly in the proinflammatory
response and induction of apoptosis. It has been found to be upregulated
in some castration-resistant prostate cancers. However, the role of TLR3 in prostate
cancer progression remains largely unknown. In this study, we demonstrated that TLR3
may be involved in prostate cancer progression and metastasis. However, it might also
represent an Achilles' heel of PCa, which can be exploited for targeted therapy.
DOI: 10.1016/j.ajpath.2022.05.009
Journal: AM J PATHOL
Impact factor (WOS, 2022): 5,770, Q1
Number of citations (WOS, 2023): 2
Most important citation:
1. Zapletal E, Vasiljevic T, Busson P, Glavan TM. Dialog beyond the Grave: Necrosis in the
Tumor Microenvironment and Its Contribution to Tumor Growth. International Journal
of Molecular Sciences 2023, 24(6). IF(2022): 5,6
Contribution of the author/author’s team: Corresponding author. Conceptualization,
data interpretation and manuscript revision.
405
Appendix 25 Rihova K, Ducka M, Zambo IS, Vymetalova L, Sramek M, Trcka F,
Verner J, Drapela S, Fedr R, Suchankova T, Pavlatovska B, Ondrouskova E,
Kubelkova I, Zapletalova D, Tucek S, Mudry P, Krakorova DA, Knopfova L, Smarda
J, Soucek K, Borsig L, Benes P: Transcription factor c-Myb: novel prognostic factor
in osteosarcoma. Clin Exp Metastasis 2022;39: 375-90.
Significance: We have shown that c-Myb plays a role in cell cycle progression and
differentiation in various types of cancer, including osteosarcoma. It has also been
associated with stemness-related genes and the WNT/β-catenin signaling pathway in
cancer cells. Additionally, c-Myb has been linked to calcium storage and the regulation of
differentiation in both normal and tumoral-developing nervous systems. These findings
suggest that c-Myb may affect the prognosis and therapeutic opportunities in
osteosarcoma and other cancers.
DOI: 10.1007/s10585-021-10145-4
Impact factor (WOS, 2021): 4,510, Q2
Number of citations (WOS, 2023): 3
Most important citation:
1. Li YW, Azmi AS, Mohammad RM. Deregulated transcription factors and poor clinical
outcomes in cancer patients. Seminars in Cancer Biology 2022, 86:122-134. IF(2021):
17,012
2. van Gogh M, Garzon JFG, Sahin D, Knopfova L, Benes P, Boyman O, et al. Tumor CellIntrinsic
c-Myb Upregulation Stimulates Antitumor Immunity in a Murine Colorectal
Cancer Model. Cancer Immunology Research 2023, 11(10):1432-1444. IF(2022): 10,1
Contribution of the author/author’s team: Co-author. Methodology and manuscript
revision.
423
Appendix 26 Kvokackova B, Fedr R, Kuzilkova D, Stuchly J, Vavrova A, Navratil J,
Fabian P, Ondrussek R, Ovesna P, Remsik J, Bouchal J, Kalina T, Soucek K: Singlecell
protein profiling defines cell populations associated with triple-negative
breast cancer aggressiveness. Molecular Oncology, 2022;17(6):1024-1040.
Significance: The generation of a comprehensive mass cytometry panel for
multiparametric detection of 23 phenotypic markers and 13 signaling molecules is
described, and it is shown that the level of CD97 at the time of surgery has predictive
potential.
DOI: 10.1002/1878-0261.13365
Impact factor (WOS, 2021): 6,6, Q1
Number of citations (WOS, 2023): 1
Contribution of the author/author’s team: Corresponding author. Conceptualization and
manuscript revision.
443
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