Evolution of core archetypal phenotypes in progressive high grade serous ovarian cancer

From metabolism to malignancy: the multifaceted role of PGC1α in cancer

PGC1α, a central player in mitochondrial biology, holds a complex role in the metabolic shifts seen in cancer cells. While its dysregulation is common across major cancers, its impact varies. In some cases, downregulation promotes aerobic glycolysis and progression, whereas in others, overexpression escalates respiration and aggression. PGC1α's interactions with distinct signaling pathways and transcription factors further diversify its roles, often in a tissue-specific manner. Understanding these multifaceted functions could unlock innovative therapeutic strategies. However, challenges exist in managing the metabolic adaptability of cancer cells and refining PGC1α-targeted approaches. This review aims to collate and present the current knowledge on the expression patterns, regulators, binding partners, and roles of PGC1α in diverse cancers. We examined PGC1α's tissue-specific functions and elucidated its dual nature as both a potential tumor suppressor and an oncogenic collaborator. In cancers where PGC1α is tumor-suppressive, reinstating its levels could halt cell proliferation and invasion, and make the cells more receptive to chemotherapy. In cancers where the opposite is true, halting PGC1α's upregulation can be beneficial as it promotes oxidative phosphorylation, allows cancer cells to adapt to stress, and promotes a more aggressive cancer phenotype. Thus, to target PGC1α effectively, understanding its nuanced role in each cancer subtype is indispensable. This can pave the way for significant strides in the field of oncology.

The Imageable Genome

Understanding human disease on a molecular level, and translating this understanding into targeted diagnostics and therapies are central tenets of molecular medicine1. Realizing this doctrine requires an efficient adaptation of molecular discoveries into the clinic. We present an approach to facilitate this process by describing the Imageable Genome, the part of the human genome whose expression can be assessed via molecular imaging. Using a deep learning-based hybrid human-AI pipeline, we bridge individual genes and their relevance in human diseases with specific molecular imaging methods. Cross-referencing the Imageable Genome with RNA-seq data from over 60,000 individuals reveals diagnostic, prognostic and predictive imageable genes for a wide variety of major human diseases. Having both the critical size and focus to be altered in its expression during the development and progression of any human disease, the Imageable Genome will generate new imaging tools that improve the understanding, diagnosis and management of human diseases.

Unveiling the novel immune and molecular signatures of ovarian cancer: insights and innovations from single-cell sequencing

Ovarian cancer is a highly heterogeneous and lethal malignancy with limited treatment options. Over the past decade, single-cell sequencing has emerged as an advanced biological technology capable of decoding the landscape of ovarian cancer at the single-cell resolution. It operates at the level of genes, transcriptomes, proteins, epigenomes, and metabolisms, providing detailed information that is distinct from bulk sequencing methods, which only offer average data for specific lesions. Single-cell sequencing technology provides detailed insights into the immune and molecular mechanisms underlying tumor occurrence, development, drug resistance, and immune escape. These insights can guide the development of innovative diagnostic markers, therapeutic strategies, and prognostic indicators. Overall, this review provides a comprehensive summary of the diverse applications of single-cell sequencing in ovarian cancer. It encompasses the identification and characterization of novel cell subpopulations, the elucidation of tumor heterogeneity, the investigation of the tumor microenvironment, the analysis of mechanisms underlying metastasis, and the integration of innovative approaches such as organoid models and multi-omics analysis.

A single-cell landscape of pre- and post-menopausal high-grade serous ovarian cancer ascites

High-grade serous ovarian cancer (HGSOC) is a hormone-related cancer with high mortality and poor prognosis. Based on the transcriptome of 57,444 cells in ascites from 10 patients with HGSOC (including 5 pre-menopausal and 5 post-menopausal patients), we identified 14 cell clusters which were further classified into 6 cell types, including T cells, B cells, NK cells, myeloid cells, epithelial cells, and stromal cells. We discovered an increased proportion of epithelial cells and a decreased proportion of T cells in pre-menopausal ascites compared with post-menopausal ascites. GO analysis revealed the pre-menopausal tumor microenvironments (TME) are closely associated with viral infection, while the post-menopausal TME are mostly related to the IL-17 immune pathway. SPP1/CD44-mediated crosstalk between myeloid cells and B cells, NK cells, and stromal cells mainly present in the pre-menopausal group, while SPP1/PTGER4 -mediated crosstalk between myeloid cells and epithelial cells mostly present in the post-menopausal group.

Overview of Tumor Heterogeneity in High-Grade Serous Ovarian Cancers

Ovarian cancers encompass a group of neoplasms originating from germinal tissues and exhibiting distinct clinical, pathological, and molecular features. Among these, epithelial ovarian cancers (EOCs) are the most prevalent, comprising five distinct tumor histotypes. Notably, high-grade serous ovarian cancers (HGSOCs) represent the majority, accounting for over 70% of EOC cases. Due to their silent and asymptomatic behavior, HGSOCs are generally diagnosed in advanced stages with an evolved and complex genomic state, characterized by high intratumor heterogeneity (ITH) due to chromosomal instability that distinguishes HGSOCs. Histologically, these cancers exhibit significant morphological diversity both within and between tumors. The histologic patterns associated with solid, endometrioid, and transitional (SET) and classic subtypes of HGSOCs offer prognostic insights and may indicate specific molecular profiles. The evolution of HGSOC from primary to metastasis is typically characterized by clonal ITH, involving shared or divergent mutations in neoplastic sub-clones within primary and metastatic sites. Disease progression and therapy resistance are also influenced by non-clonal ITH, related to interactions with the tumor microenvironment and further genomic changes. Notably, significant alterations occur in nonmalignant cells, including cancer-associated fibroblast and immune cells, during tumor progression. This review provides an overview of the complex nature of HGSOC, encompassing its various aspects of intratumor heterogeneity, histological patterns, and its dynamic evolution during progression and therapy resistance.

ONC201/TIC10 enhances durability of mTOR inhibitor everolimus in metastatic ER+ breast cancer

The mTOR inhibitor, everolimus, is an important clinical management component of metastatic ER+ breast cancer (BC). However, most patients develop resistance and progress on therapy, highlighting the need to discover strategies that increase mTOR inhibitor effectiveness. We developed ER+ BC cell lines, sensitive or resistant to everolimus, and discovered that combination treatment of ONC201/TIC10 with everolimus inhibited cell growth in 2D/3D in vitro studies. We confirmed increased therapeutic response in primary patient cells progressing on everolimus, supporting clinical relevance. We show that ONC201/TIC10 mechanism in metastatic ER+ BC cells involves oxidative phosphorylation inhibition and stress response activation. Transcriptomic analysis in everolimus resistant breast patient tumors and mitochondrial functional assays in resistant cell lines demonstrated increased mitochondrial respiration dependency, contributing to ONC201/TIC10 sensitivity. We propose that ONC201/TIC10 and modulation of mitochondrial function may provide an effective add-on therapy strategy for patients with metastatic ER+ BCs resistant to mTOR inhibitors.

Quantifying cancer cell plasticity with gene regulatory networks and single-cell dynamics

Phenotypic plasticity of cancer cells can lead to complex cell state dynamics during tumor progression and acquired resistance. Highly plastic stem-like states may be inherently drug-resistant. Moreover, cell state dynamics in response to therapy allow a tumor to evade treatment. In both scenarios, quantifying plasticity is essential for identifying high-plasticity states or elucidating transition paths between states. Currently, methods to quantify plasticity tend to focus on 1) quantification of quasi-potential based on the underlying gene regulatory network dynamics of the system; or 2) inference of cell potency based on trajectory inference or lineage tracing in single-cell dynamics. Here, we explore both of these approaches and associated computational tools. We then discuss implications of each approach to plasticity metrics, and relevance to cancer treatment strategies.

Evolutionary states and trajectories characterized by distinct pathways stratify patients with ovarian high grade serous carcinoma

Ovarian high-grade serous carcinoma (HGSC) is typically diagnosed at an advanced stage, with multiple genetically heterogeneous clones existing in the tumors long before therapeutic intervention. Herein we integrate clonal composition and topology using whole-genome sequencing data from 510 samples of 148 patients with HGSC in the prospective, longitudinal, multiregion DECIDER study. Our results reveal three evolutionary states, which have distinct features in genomics, pathways, and morphological phenotypes, and significant association with treatment response. Nested pathway analysis suggests two evolutionary trajectories between the states. Experiments with five tumor organoids and three PI3K inhibitors support targeting tumors with enriched PI3K/AKT pathway with alpelisib. Heterogeneity analysis of samples from multiple anatomical sites shows that site-of-origin samples have 70% more unique clones than metastatic tumors or ascites. In conclusion, these analysis and visualization methods enable integrative tumor evolution analysis to identify patient subtypes using data from longitudinal, multiregion cohorts.

Spatial Transcriptomics Depict Ligand-Receptor Cross-talk Heterogeneity at the Tumor-Stroma Interface in Long-Term Ovarian Cancer Survivors

Advanced high-grade serous ovarian cancer (HGSC) is an aggressive disease that accounts for 70% of all ovarian cancer deaths. Nevertheless, 15% of patients diagnosed with advanced HGSC survive more than 10 years. The elucidation of predictive markers of these long-term survivors (LTS) could help identify therapeutic targets for the disease, and thus improve patient survival rates. To investigate the stromal heterogeneity of the tumor microenvironment (TME) in ovarian cancer, we used spatial transcriptomics to generate spatially resolved transcript profiles in treatment-naïve advanced HGSC from LTS and short-term survivors (STS) and determined the association between cancer-associated fibroblasts (CAF) heterogeneity and survival in patients with advanced HGSC. Spatial transcriptomics and single-cell RNA-sequencing data were integrated to distinguish tumor and stroma regions, and a computational method was developed to investigate spatially resolved ligand-receptor interactions between various tumor and CAF subtypes in the TME. A specific subtype of CAFs and its spatial location relative to a particular ovarian cancer cell subtype in the TME correlated with long-term survival in patients with advanced HGSC. Also, increased APOE-LRP5 cross-talk occurred at the stroma-tumor interface in tumor tissues from STS compared with LTS. These findings were validated using multiplex IHC. Overall, this spatial transcriptomics analysis revealed spatially resolved CAF-tumor cross-talk signaling networks in the ovarian TME that are associated with long-term survival of patients with HGSC. Further studies to confirm whether such cross-talk plays a role in modulating the malignant phenotype of HGSC and could serve as a predictive biomarker of patient survival are warranted.

SIGNIFICANCE

Generation of spatially resolved gene expression patterns in tumors from patients with ovarian cancer surviving more than 10 years allows the identification of novel predictive biomarkers and therapeutic targets for better patient management. See related commentary by Kelliher and Lengyel, p. 1383.

Probing the Potential of Defense Response-Associated Genes for Predicting the Progression, Prognosis, and Immune Microenvironment of Osteosarcoma

BACKGROUND

The defense response is a type of self-protective response of the body that protects it from damage by pathogenic factors. Although these reactions make important contributions to the occurrence and development of tumors, the role they play in osteosarcoma (OS), particularly in the immune microenvironment, remains unpredictable.

METHODS

This study included the clinical information and transcriptomic data of 84 osteosarcoma samples and the microarray data of 12 mesenchymal stem cell samples and 84 osteosarcoma samples. We obtained 129 differentially expressed genes related to the defense response (DRGs) by taking the intersection of differentially expressed genes with genes involved in the defense response pathway, and prognostic genes were screened using univariate Cox regression. Least absolute shrinkage and selection operator (LASSO) penalized Cox regression and multivariate Cox regression were then used to establish a DRG prognostic signature (DGPS) via the stepwise method. DGPS performance was examined using independent prognostic analysis, survival curves, and receiver operating characteristic (ROC) curves. In addition, the molecular and immune mechanisms of adverse prognosis in high-risk populations identified by DGPS were elucidated. The results were well verified by experiments.

RESULT

BNIP3, PTGIS, and ZYX were identified as the most important DRGs for OS progression (hazard ratios of 2.044, 1.485, and 0.189, respectively). DGPS demonstrated outstanding performance in the prediction of OS prognosis (area under the curve (AUC) values of 0.842 and 0.787 in the training and test sets, respectively, adj-p < 0.05 in the survival curve). DGPS also performed better than a recent clinical prognostic approach with an AUC value of only 0.674 [metastasis], which was certified in the subsequent experimental results. These three genes regulate several key biological processes, including immune receptor activity and T cell activation, and they also reduce the infiltration of some immune cells, such as B cells, CD8+ T cells, and macrophages. Encouragingly, we found that DGPS was associated with sensitivity to chemotherapeutic drugs including JNK Inhibitor VIII, TGX221, MP470, and SB52334. Finally, we verified the effect of BNIP3 on apoptosis, proliferation, and migration of osteosarcoma cells through experiments.

CONCLUSIONS

This study elucidated the role and mechanism of BNIP3, PTGIS, and ZYX in OS progression and was well verified by the experimental results, enabling reliable prognostic means and treatment strategies to be proposed for OS patients.

Radiomics and Radiogenomics of Ovarian Cancer

Ovarian cancer, one of the deadliest gynecologic malignancies, is characterized by high intra- and inter-site genomic and phenotypic heterogeneity. The traditional information provided by the conventional interpretation of diagnostic imaging studies cannot adequately represent this heterogeneity. Radiomics analyses can capture the complex patterns related to the microstructure of the tissues and provide quantitative information about them. This review outlines how radiomics and its integration with other quantitative biological information, like genomics and proteomics, can impact the clinical management of ovarian cancer.

Multiomic analysis of homologous recombination-deficient end-stage high-grade serous ovarian cancer

High-grade serous ovarian cancer (HGSC) is frequently characterized by homologous recombination (HR) DNA repair deficiency and, while most such tumors are sensitive to initial treatment, acquired resistance is common. We undertook a multiomics approach to interrogate molecular diversity in end-stage disease, using multiple autopsy samples collected from 15 women with HR-deficient HGSC. Patients had polyclonal disease, and several resistance mechanisms were identified within most patients, including reversion mutations and HR restoration by other means. We also observed frequent whole-genome duplication and global changes in immune composition with evidence of immune escape. This analysis highlights diverse evolutionary changes within HGSC that evade therapy and ultimately overwhelm individual patients.

Proteomic alterations associated with residual disease in neoadjuvant chemotherapy treated ovarian cancer tissues

BACKGROUND

Optimal cytoreduction to no residual disease (R0) correlates with improved disease outcome for high-grade serous ovarian cancer (HGSOC) patients. Treatment of HGSOC patients with neoadjuvant chemotherapy, however, may select for tumor cells harboring alterations in hallmark cancer pathways including metastatic potential. This study assessed this hypothesis by performing proteomic analysis of matched, chemotherapy naïve and neoadjuvant chemotherapy (NACT)-treated HGSOC tumors obtained from patients who had suboptimal (R1, n = 6) versus optimal (R0, n = 14) debulking at interval debulking surgery (IDS).

METHODS

Tumor epithelium was harvested by laser microdissection from formalin-fixed, paraffin-embedded tissues from matched, pre- and post-NACT treated tumors for twenty HGSOC patients and analyzed by quantitative mass spectrometry-based proteomics.

RESULTS

Differential analysis of patient matched pre- and post-NACT treated tumors revealed proteins associated with cell survival and metabolic signaling to be significantly altered in post-NACT treated tumor cells. Comparison of pre-NACT treated tumors from suboptimal (R1) versus optimally (R0) debulked patients identified proteins associated with tumor cell viability and invasion signaling enriched in R1 patients. We identified five proteins altered between R1 and R0 patients in pre- NACT treated tumors that significantly correlated with PFS in an independent cohort of HGSOC patients, including Fermitin family homolog 2 (FERMT2), a protein elevated in R1 that correlated with disease progression in HGSOC patients (multivariate Cox HR = 1.65, Wald p = 0.022) and increased metastatic potential in solid-tumor malignancies.

CONCLUSIONS

This study identified distinct proteome profiles in patient matched pre- and post-NACT HGSOC tumors that correlate with NACT resistance and that may predict residual disease status at IDS that collectively warrant further pre-clinical investigation.

Unraveling phenotypic plasticity and evolution in small cell lung cancer

Malignant cell populations in a tumor often exist in distinct phenotypic states. Deciphering tumor heterogeneity requires determining how many such unique states exist and what the biological traits associated with each are. Archetype analysis of SCLC transcriptomes reveals key phenotypic states in SCLC tumors and their patterns of evolution.

Peritoneal dissemination of high-grade serous ovarian cancer: pivotal roles of chromosomal instability and epigenetic dynamics

Epithelial ovarian cancer remains the lethal gynecological malignancy in women. The representative histotype is high-grade serous carcinoma (HGSC), and most patients with HGSC present at advanced stages with peritoneal dissemination. Since the peritoneal dissemination is the most important factor for poor prognosis of the patients, complete exploration for its molecular mechanisms is mandatory. In this narrative review, being based on the clinical, pathologic, and genomic findings of HGSC, chromosomal instability and epigenetic dynamics have been discussed as the potential drivers for cancer development in the fallopian tube, acquisition of cancer stem cell (CSC)-like properties, and peritoneal metastasis of HGSC. The natural history of carcinogenesis with clonal evolution, and adaptation to microenvironment of peritoneal dissemination of HGSC should be targeted in the novel development of strategies for prevention, early detection, and precision treatment for patients with HGSC.

Identification of an Immune Gene-Based Cisplatin Response Model and CD27 as a Therapeutic Target against Cisplatin Resistance for Ovarian Cancer

Objective. Evidence demonstrates that the immune microenvironment is extensively associated with chemotherapy response of ovarian cancer (OV). Herein, this study is aimed at establishing a cisplatin response prediction model for OV on the basis of immune genes. Methods. The expression profiles of cisplatin-sensitive and cisplatin-resistant OV specimens were integrated from multiple public datasets. The abundance scores of 22 immune cells were estimated with CIBERSORT algorithm. Differentially expressed immune genes (DEGs) were determined between cisplatin-sensitive and cisplatin-resistant groups. Thereafter, a cisplatin response model was constructed based on prognostic DEGs with logistic regression analysis. The prediction performance was validated in independent cohorts. The possible relationships between the model and immunotherapy were then assessed. Results. Treg scores were significantly decreased in cisplatin-resistant than cisplatin-sensitive OV specimens, with the opposite results for naïve B cells and activated dendritic cells. Fourteen prognostic DEGs were identified and used to develop a cisplatin-response model. The response scores, estimated by the model, showed favorable performance in discriminating cisplatin-response and nonresponse samples. The response scores also presented significantly negative correlations with three well-known cisplatin-resistant pathways and a positive correlation with the expression of CD274 (PD-L1). Moreover, the decreased CD27 expression was observed in cisplatin-resistant groups, and OV specimens with higher CD27 expressions were more sensitive to cisplatin treatment. Conclusion. Altogether, our findings proposed a cisplatin response prediction model and identified CD27 that might be involved in cisplatin resistance. Further investigations suggested that CD27 could be a promising immunotherapeutic target for cisplatin-resistant subset of OV.

Metastatic Voyage of Ovarian Cancer Cells in Ascites with the Assistance of Various Cellular Components

Epithelial ovarian cancer (EOC) is the most lethal gynecologic malignancy and has a unique metastatic route using ascites, known as the transcoelomic root. However, studies on ascites and contained cellular components have not yet been sufficiently clarified. In this review, we focus on the significance of accumulating ascites, contained EOC cells in the form of spheroids, and interaction with non-malignant host cells. To become resistant against anoikis, EOC cells form spheroids in ascites, where epithelial-to-mesenchymal transition stimulated by transforming growth factor-β can be a key pathway. As spheroids form, EOC cells are also gaining the ability to attach and invade the peritoneum to induce intraperitoneal metastasis, as well as resistance to conventional chemotherapy. Recently, accumulating evidence suggests that EOC spheroids in ascites are composed of not only cancer cells, but also non-malignant cells existing with higher abundance than EOC cells in ascites, including macrophages, mesothelial cells, and lymphocytes. Moreover, hetero-cellular spheroids are demonstrated to form more aggregated spheroids and have higher adhesion ability for the mesothelial layer. To improve the poor prognosis, we need to elucidate the mechanisms of spheroid formation and interactions with non-malignant cells in ascites that are a unique tumor microenvironment for EOC.

Natural Killer Cells: the Missing Link in Effective Treatment for High-Grade Serous Ovarian Carcinoma

OPINION STATEMENT

Ovarian cancer (OC), especially high-grade serous cancer (HGSC), is a highly heterogeneous malignancy with limited options for curative treatment and a high frequency of relapse. Interactions between OC and the immune system may permit immunoediting and immune escape, and current standard of care therapies can influence immune cell infiltration and function within the tumor microenvironment. Natural killer (NK) cells are involved in cancer immunosurveillance and immunoediting and can be activated by therapy, but deliberate approaches to maximize NK cell reactivity for treatment of HGSC are in their infancy. NK cells may be the ideal target for immunotherapy of HGSC. The diverse functions of NK cells, and their established roles in immunosurveillance, make them attractive candidates for more precise and effective HGSC treatment. NK cells' functional capabilities differ because of variation in receptor expression and genetics, with meaningful impacts on their anticancer activity. Studying HGSC:NK cell interactions will define the features that predict the best outcomes for patients with the disease, but the highly diverse nature of HGSC will likely require combination therapies or approaches to simultaneously target multiple, co-existing features of the tumor to avoid tumor escape and relapse. We expect that the ideal therapy will enable NK cell infiltration and activity, reverse immunosuppression within the tumor microenvironment, and enable effector functions against the diverse subpopulations that comprise HGSC.

Toward More Comprehensive Homologous Recombination Deficiency Assays in Ovarian Cancer Part 2: Medical Perspectives

Simple Summary

High-grade serous ovarian cancer (HGSOC—the most frequent and aggressive form of ovarian cancer) represents an important challenge for clinicians. Half of HGSOC cases exhibit homologous recombination deficiency (HRD), mainly through alterations in BRCA1 and BRCA2. This leads to sensitivity to PARP inhibitors, a novel class of breakthrough molecules that improved HGSOC prognoses. To date, three companion diagnostic assays have received FDA approval for the evaluation of HRD status, but their use remains controversial. In this companion review (Part 1: Technical considerations; Part 2: Medical perspectives), we develop an integrative perspective, from translational research to clinical application, that could help physicians and researchers manage HGSOC.

Abstract

High-grade serous ovarian cancer (HGSOC) is the most frequent and aggressive form of ovarian cancer, representing an important challenge for clinicians. Half of HGSOC cases have homologous recombination deficiency (HRD), which has specific causes (mainly alterations in BRCA1/2, but also other alterations encompassed by the BRCAness concept) and consequences, both at molecular (e.g., genomic instability) and clinical (e.g., sensitivity to PARP inhibitor) levels. Based on its prevalence and clinical impact, HRD status merits investigation. To date, three PARP inhibitors have received FDA/EMA approval. For some approvals, the presence of specific molecular alterations is required. Three companion diagnostic (CDx) assays based on distinct technical and medical considerations have received FDA approval to date. However, their use remains controversial due to their technical and medical limitations. In this companion and integrated review, we take a “bench-to-bedside” perspective on HRD definition and evaluation in the context of HGSOC. Part 1 of the review adopts a molecular perspective regarding technical considerations and the development of CDx. Part 2 focuses on the clinical impact of HRD evaluation, primarily through currently validated CDx and prescription of PARP inhibitors, outlining achievements, limitations and medical perspectives.

Leveraging Genomics, Transcriptomics, and Epigenomics to Understand the Biology and Chemoresistance of Ovarian Cancer

Ovarian cancer is a major cause of fatality due to a gynecological malignancy. This lethality is largely due to the unspecific clinical manifestations of ovarian cancer, which lead to late detection and to high resistance to conventional therapies based on platinum. In recent years, we have advanced our understanding of the mechanisms provoking tumor relapse, and the advent of so-called omics technologies has provided exceptional tools to evaluate molecular mechanisms leading to therapy resistance in ovarian cancer. Here, we review the contribution of genomics, transcriptomics, and epigenomics techniques to our knowledge about the biology and molecular features of ovarian cancers, with a focus on therapy resistance. The use of these technologies to identify molecular markers and mechanisms leading to chemoresistance in these tumors is discussed, as well as potential further applications.

Mutated p53 in HGSC-From a Common Mutation to a Target for Therapy

Simple Summary

Ovarian high-grade serous cancer (HGSC), the most common and the deadliest subtype of epithelial ovarian cancer, is characterized by frequent mutations in the TP53 tumor suppressor gene, encoding for the p53 protein in nearly 100% of cases. This makes p53 the focus of many studies trying to understand its role in HGSC. The aim of our review paper is to provide updates on the latest findings related to the role of mutant p53 in HGSC. This includes the clinical outcomes of TP53 mutations in HGSC, upstream regulators and downstream effectors of p53, its function in the earliest stages of HGSC development and in the interplay between the tumor cells and their microenvironment. We summarize with the likelihood of p53 mutants to serve as biomarkers for early diagnosis and as targets for therapy in HGSC.

Abstract

Mutations in tumor suppressor gene TP53, encoding for the p53 protein, are the most ubiquitous genetic variation in human ovarian HGSC, the most prevalent and lethal histologic subtype of epithelial ovarian cancer (EOC). The majority of TP53 mutations are missense mutations, leading to loss of tumor suppressive function of p53 and gain of new oncogenic functions. This review presents the clinical relevance of TP53 mutations in HGSC, elaborating on several recently identified upstream regulators of mutant p53 that control its expression and downstream target genes that mediate its roles in the disease. TP53 mutations are the earliest genetic alterations during HGSC pathogenesis, and we summarize current information related to p53 function in the pathogenesis of HGSC. The role of p53 is cell autonomous, and in the interaction between cancer cells and its microenvironment. We discuss the reduction in p53 expression levels in tumor associated fibroblasts that promotes cancer progression, and the role of mutated p53 in the interaction between the tumor and its microenvironment. Lastly, we discuss the potential of TP53 mutations to serve as diagnostic biomarkers and detail some more advanced efforts to use mutated p53 as a therapeutic target in HGSC.