Emerging biomarkers and molecular targets for precision medicine in cervical cancer.

Cervical cancer remains a significant global health burden, necessitating innovative approaches for improved diagnostics and personalized treatment strategies. Precision medicine has emerged as a promising paradigm, leveraging biomarkers and molecular targets to tailor therapy to individual patients. This review explores the landscape of emerging biomarkers and molecular targets in cervical cancer, highlighting their potential implications for precision medicine. By integrating these biomarkers into comprehensive diagnostic algorithms, clinicians can identify high-risk patients at an earlier stage, enabling timely intervention and improved patient outcomes. Furthermore, the identification of specific molecular targets has paved the way for the development of targeted therapies aimed at disrupting key pathways implicated in cervical carcinogenesis. In conclusion, the evolving landscape of biomarkers and molecular targets presents exciting opportunities for advancing precision medicine in cervical cancer. By harnessing these insights, clinicians can optimize treatment selection, enhance patient outcomes, and ultimately transform the management of this devastating disease.

The ELF3 transcription factor is associated with an epithelial phenotype and represses epithelial-mesenchymal transition.

BACKGROUND: Epithelial-mesenchymal plasticity (EMP) involves bidirectional transitions between epithelial, mesenchymal and multiple intermediary hybrid epithelial/mesenchymal phenotypes. While the process of epithelial-mesenchymal transition (EMT) and its associated transcription factors are well-characterised, the transcription factors that promote mesenchymal-epithelial transition (MET) and stabilise hybrid E/M phenotypes are less well understood. RESULTS: Here, we analyse multiple publicly-available transcriptomic datasets at bulk and single-cell level and pinpoint ELF3 as a factor that is strongly associated with an epithelial phenotype and is inhibited during EMT. Using mechanism-based mathematical modelling, we also show that ELF3 inhibits the progression of EMT. This behaviour was also observed in the presence of an EMT inducing factor WT1. Our model predicts that the MET induction capacity of ELF3 is stronger than that of KLF4, but weaker than that of GRHL2. Finally, we show that ELF3 levels correlates with worse patient survival in a subset of solid tumour types. CONCLUSION: ELF3 is shown to be inhibited during EMT progression and is also found to inhibit the progression of complete EMT suggesting that ELF3 may be able to counteract EMT induction, including in the presence of EMT-inducing factors, such as WT1. The analysis of patient survival data indicates that the prognostic capacity of ELF3 is specific to cell-of-origin or lineage.

Mapping Spatiotemporal Heterogeneity in Tumor Profiles by Integrating High-Throughput Imaging and Omics Analysis.

Intratumoral heterogeneity associates with more aggressive disease progression and worse patient outcomes. Understanding the reasons enabling the emergence of such heterogeneity remains incomplete, which restricts our ability to manage it from a therapeutic perspective. Technological advancements such as high-throughput molecular imaging, single-cell omics, and spatial transcriptomics allow recording of patterns of spatiotemporal heterogeneity in a longitudinal manner, thus offering insights into the multiscale dynamics of its evolution. Here, we review the latest technological trends and biological insights from molecular diagnostics as well as spatial transcriptomics, both of which have witnessed burgeoning growth in the recent past in terms of mapping heterogeneity within tumor cell types as well as the stromal constitution. We also discuss ongoing challenges, indicating possible ways to integrate insights across these methods to have a systems-level spatiotemporal map of heterogeneity in each tumor and a more systematic investigation of the implications of heterogeneity for patient outcomes.

Cancer: More than a geneticist's Pandora's box.

Despite identical genetic constitution, a cancer cell population can exhibit phenotypic variations termed as nongenetic/ non-mutational heterogeneity. Such heterogeneity - a ubiquitous nature of biological systems - has been implicated in metastasis, therapy resistance and tumour relapse. Here, we review the evidence for existence, sources and implications of non-genetic heterogeneity in multiple cancer types. Stochasticity/noise in transcription, protein conformation and/or external microenvironment can underlie such heterogeneity. Moreover, the existence of multiple possible cell states (phenotypes) as a consequence of the emergent dynamics of gene regulatory networks may enable reversible cell-state transitions (phenotypic plasticity) that can facilitate adaptive drug resistance and higher metastatic fitness. Finally, we highlight how computational and mathematical models can drive a better understanding of non-genetic heterogeneity and how a systemslevel approach integrating mathematical modeling and in (vitro/in vivo) experiments can map the diverse phenotypic repertoire and identify therapeutic vulnerabilities of an otherwise clonal cell population.

A Multistep Tumor Growth Model of High Grade Serous Ovarian Carcinoma Identifies Hypoxia Associated Signatures.

High-grade serous ovarian carcinoma (HGSC) is associated with late-stage disease presentation and poor prognosis, with limited understanding of early transformation events. Our study presents a comprehensive analysis of tumor progression and organ-specific metastatic dissemination to identify hypoxia-associated molecular, cellular, and histological alterations during HGSC tumor growth. H&E staining and subsequent histological assessment of tumor volume-based categories revealed recapitulation of numerous clinical features, including the prevalence of >0.0625≤0.5cm3 volume tumors and metastatic spread by orthotopic xenografts. The constant evolution of the tissue architecture concerning increased hyaluronic acid deposition, tumor vasculature, necrosis, altered proliferative potential, and gland forming ability of the tumor cells was identified. Flow cytometry and label chase-based molecular profiling across the tumor regenerative hierarchy identified the hypoxia-vasculogenic niche and the hybrid epithelial-mesenchymal tumor-cell state as determinants of self-renewal capabilities of progenitors and cancer stem cells (CSCs). A regulatory network and mathematical model based on tumor histology and molecular signatures predicted hypoxia-inducible factor 1-alpha (HIF1A) as a central node connecting epithelial-mesenchymal transition, metabolic and necrotic pathways in HGSC tumors. Thus, our findings provide a temporal resolution of hypoxia-associated events that sculpt HGSC tumor growth, and an in-depth understanding of it may aid in the early detection and treatment of HGSC.

Biophysical and biochemical attributes of hybrid epithelial/mesenchymal phenotypes.

The epithelial-mesenchymal transition (EMT) is a biological phenomenon associated with explicit phenotypic and molecular changes in cellular traits. Unlike the earlier-held popular belief of it being a binary process, EMT is now thought of as a landscape including diverse hybrid E/M phenotypes manifested by varying degrees of the transition. These hybrid cells can co-express both epithelial and mesenchymal markers and/or functional traits, and can possess the property of collective cell migration, enhanced tumor-initiating ability, and immune/targeted therapy-evasive features, all of which are often associated with worse patient outcomes. These characteristics of the hybrid E/M cells have led to a surge in studies that map their biophysical and biochemical hallmarks that can be helpful in exploiting their therapeutic vulnerabilities. This review discusses recent advances made in investigating hybrid E/M phenotype(s) from diverse biophysical and biochemical aspects by integrating live cell-imaging, cellular morphology quantification and mathematical modeling, and highlights a set of questions that remain unanswered about the dynamics of hybrid E/M states.

KLF4 Induces Mesenchymal-Epithelial Transition (MET) by Suppressing Multiple EMT-Inducing Transcription Factors.

Epithelial-Mesenchymal Plasticity (EMP) refers to reversible dynamic processes where cells can transition from epithelial to mesenchymal (EMT) or from mesenchymal to epithelial (MET) phenotypes. Both these processes are modulated by multiple transcription factors acting in concert. While EMT-inducing transcription factors (TFs)-TWIST1/2, ZEB1/2, SNAIL1/2/3, GSC, and FOXC2-are well-characterized, the MET-inducing TFs are relatively poorly understood (OVOL1/2 and GRHL1/2). Here, using mechanism-based mathematical modeling, we show that transcription factor KLF4 can delay the onset of EMT by suppressing multiple EMT-TFs. Our simulations suggest that KLF4 overexpression can promote a phenotypic shift toward a more epithelial state, an observation suggested by the negative correlation of KLF4 with EMT-TFs and with transcriptomic-based EMT scoring metrics in cancer cell lines. We also show that the influence of KLF4 in modulating the EMT dynamics can be strengthened by its ability to inhibit cell-state transitions at the epigenetic level. Thus, KLF4 can inhibit EMT through multiple parallel paths and can act as a putative MET-TF. KLF4 associates with the patient survival metrics across multiple cancers in a context-specific manner, highlighting the complex association of EMP with patient survival.

Lineage Plasticity in Cancer: The Tale of a Skin-Walker.

Lineage plasticity, the switching of cells from one lineage to another, has been recognized as a cardinal property essential for embryonic development, tissue repair and homeostasis. However, such a highly regulated process goes awry when cancer cells exploit this inherent ability to their advantage, resulting in tumorigenesis, relapse, metastasis and therapy resistance. In this review, we summarize our current understanding on the role of lineage plasticity in tumor progression and therapeutic resistance in multiple cancers. Lineage plasticity can be triggered by treatment itself and is reported across various solid as well as liquid tumors. Here, we focus on the importance of lineage switching in tumor progression and therapeutic resistance of solid tumors such as the prostate, lung, hepatocellular and colorectal carcinoma and the myeloid and lymphoid lineage switch observed in leukemias. Besides this, we also discuss the role of epithelial-mesenchymal transition (EMT) in facilitating the lineage switch in biphasic cancers such as aggressive carcinosarcomas. We also discuss the mechanisms involved, current therapeutic approaches and challenges that lie ahead in taming the scourge of lineage plasticity in cancer.

NFATc Acts as a Non-Canonical Phenotypic Stability Factor for a Hybrid Epithelial/Mesenchymal Phenotype.

Metastasis remains the cause of over 90% of cancer-related deaths. Cells undergoing metastasis use phenotypic plasticity to adapt to their changing environmental conditions and avoid therapy and immune response. Reversible transitions between epithelial and mesenchymal phenotypes - epithelial-mesenchymal transition (EMT) and its reverse mesenchymal-epithelial transition (MET) - form a key axis of phenotypic plasticity during metastasis and therapy resistance. Recent studies have shown that the cells undergoing EMT/MET can attain one or more hybrid epithelial/mesenchymal (E/M) phenotypes, the process of which is termed as partial EMT/MET. Cells in hybrid E/M phenotype(s) can be more aggressive than those in either epithelial or mesenchymal state. Thus, it is crucial to identify the factors and regulatory networks enabling such hybrid E/M phenotypes. Here, employing an integrated computational-experimental approach, we show that the transcription factor nuclear factor of activated T-cell (NFATc) can inhibit the process of complete EMT, thus stabilizing the hybrid E/M phenotype. It increases the range of parameters enabling the existence of a hybrid E/M phenotype, thus behaving as a phenotypic stability factor (PSF). However, unlike previously identified PSFs, it does not increase the mean residence time of the cells in hybrid E/M phenotypes, as shown by stochastic simulations; rather it enables the co-existence of epithelial, mesenchymal and hybrid E/M phenotypes and transitions among them. Clinical data suggests the effect of NFATc on patient survival in a tissue-specific or context-dependent manner. Together, our results indicate that NFATc behaves as a non-canonical PSF for a hybrid E/M phenotype.