A Study of High-Grade Serous Ovarian Cancer Origins Implicates the SOX18 Transcription Factor in Tumor Development

Spatial transcriptomic profiling of the human fallopian tube epithelium reveals region-specific gene expression patterns

The fallopian tube (FT) plays a crucial role in fertility, gynecological health, and high-grade serous ovarian cancer (HGSOC) development. Despite its importance, the spatial transcriptome of the FT's distinct anatomical regions (fimbria, infundibulum, ampulla, and isthmus) remains underexplored. Using the GeoMx Digital Spatial Profiler (DSP) and a targeted ~1800 gene panel, we analyze premenopausal FT epithelium, identifying region-specific gene expression patterns. Our analysis reveals upregulation of mature ciliated cell markers (FOXJ1, MLF1, SPA17, and CTSS) approaching the fimbria, elevated ROS and apoptosis-related transcripts (TXNIP, PRDX5, BAD, GAS1) in the distal FT, and a switch in cell-cell adhesion transcripts (CDH1, CDH3) along the distal-to-proximal axis. We also provide evidence that MHC-II transcripts in the FT are differentially regulated throughout the menstrual cycle, with lower expression in follicular phase. These results suggest spatially regulated expression of FT transcripts with implications for fertilization and early neoplastic changes contributing to HGSOC.

Aggressive Serous Carcinomas of the Female Reproductive Tract: Cancer-Prone Cell States and Genetic Drivers

In 2025, gynecological cancers are projected to account for approximately 10% of cancer-related deaths in women. High-grade serous ovarian carcinoma (HGSC) and serous endometrial carcinoma (SEC) are the most lethal gynecological cancer subtypes. Both malignancies commonly have TP53 mutations, alterations of the RB1 pathway, and numerous secondary mutations. Both carcinoma types consist of poorly differentiated and highly heterogeneous cell populations at the time of detection. Latent development and rapid progression of HGSC and SEC impede the identification of definitive cells of origin and genetic drivers. Here, we review our current knowledge about cancer-prone cell states and genetic drivers. We also discuss how emerging transcriptomic and genetic tools applied to contemporary model systems may facilitate the identification of novel targets for timely detection and therapeutic intervention.

ClassifieR 2.0: expanding interactive gene expression-based stratification to prostate and high-grade serous ovarian cancer

BACKGROUND

Advances in transcriptional profiling methods have enabled the discovery of molecular subtypes within and across traditional tissue-based cancer classifications. Such molecular subgroups hold potential for improving patient outcomes by guiding treatment decisions and revealing physiological distinctions and targetable pathways. Computational methods for stratifying transcriptomic data into molecular subgroups are increasingly abundant. However, assigning samples to these subtypes and other transcriptionally inferred predictions is time-consuming and requires significant bioinformatics expertise. To address this need, we recently reported "ClassifieR," a flexible, interactive cloud application for the functional annotation of colorectal and breast cancer transcriptomes. Here, we report "ClassifieR 2.0" which introduces additional modules for the molecular subtyping of prostate and high-grade serous ovarian cancer (HGSOC).

RESULTS

ClassifieR 2.0 introduces ClassifieRp and ClassifieRov, two specialised modules specifically designed to address the challenges of prostate and HGSOC molecular classification. ClassifieRp includes sigInfer, a method we developed to infer commercial prognostic prostate gene expression signatures from publicly available gene-lists or indeed any user-uploaded gene-list. ClassifieRov utilizes consensus molecular subtyping methods for HGSOC, including tools like consensusOV, for accurate ovarian cancer stratification. Both modules include functionalities present in the original ClassifieR framework for estimating cellular composition, predicting transcription factor (TF) activity and single sample gene set enrichment analysis (ssGSEA).

CONCLUSIONS

ClassifieR 2.0 combines molecular subtyping of prostate cancer and HGSOC with commonly used sample annotation tools in a single, user-friendly platform, allowing scientists without bioinformatics training to explore prostate and HGSOC transcriptional data without the need for extensive bioinformatics knowledge or manual data handling to operate various packages. Our sigInfer method within ClassifieRp enables the inference of commercially available gene signatures for prostate cancer, while ClassifieRov incorporates consensus molecular subtyping for HGSOC. Overall, ClassifieR 2.0 aims to make molecular subtyping more accessible to the wider research community. This is crucial for increased understanding of the molecular heterogeneity of these cancers and developing personalised treatment strategies.

Screening and identification of key biomarkers associated with endometriosis using bioinformatics and next-generation sequencing data analysis

Background

Endometriosis is a common cause of endometrial-type mucosa outside the uterine cavity with symptoms such as painful periods, chronic pelvic pain, pain with intercourse and infertility. However, the early diagnosis of endometriosis is still restricted. The purpose of this investigation is to identify and validate the key biomarkers of endometriosis.

Methods

Next-generation sequencing dataset GSE243039 was obtained from the Gene Expression Omnibus database, and differentially expressed genes (DEGs) between endometriosis and normal control samples were identified. After screening of DEGs, gene ontology (GO) and REACTOME pathway enrichment analyses were performed. Furthermore, a protein–protein interaction (PPI) network was constructed and modules were analyzed using the Human Integrated Protein–Protein Interaction rEference database and Cytoscape software, and hub genes were identified. Subsequently, a network between miRNAs and hub genes, and network between TFs and hub genes were constructed using the miRNet and NetworkAnalyst tool, and possible key miRNAs and TFs were predicted. Finally, receiver operating characteristic curve analysis was used to validate the hub genes.

Results

A total of 958 DEGs, including 479 upregulated genes and 479 downregulated genes, were screened between endometriosis and normal control samples. GO and REACTOME pathway enrichment analyses of the 958 DEGs showed that they were mainly involved in multicellular organismal process, developmental process, signaling by GPCR and muscle contraction. Further analysis of the PPI network and modules identified 10 hub genes, including vcam1, snca, prkcb, adrb2, foxq1, mdfi, actbl2, prkd1, dapk1 and actc1. Possible target miRNAs, including hsa-mir-3143 and hsa-mir-2110, and target TFs, including tcf3 (transcription factor 3) and clock (clock circadian regulator), were predicted by constructing a miRNA-hub gene regulatory network and TF-hub gene regulatory network.

Conclusions

This investigation used bioinformatics techniques to explore the potential and novel biomarkers. These biomarkers might provide new ideas and methods for the early diagnosis, treatment and monitoring of endometriosis.

Pre-ciliated tubal epithelial cells are prone to initiation of high-grade serous ovarian carcinoma

The distal region of the uterine (Fallopian) tube is commonly associated with high-grade serous carcinoma (HGSC), the predominant and most aggressive form of ovarian or extra-uterine cancer. Specific cell states and lineage dynamics of the adult tubal epithelium (TE) remain insufficiently understood, hindering efforts to determine the cell of origin for HGSC. Here, we report a comprehensive census of cell types and states of the mouse uterine tube. We show that distal TE cells expressing the stem/progenitor cell marker Slc1a3 can differentiate into both secretory (Ovgp1+) and ciliated (Fam183b+) cells. Inactivation of Trp53 and Rb1, whose pathways are commonly altered in HGSC, leads to elimination of targeted Slc1a3+ cells by apoptosis, thereby preventing their malignant transformation. In contrast, pre-ciliated cells (Krt5+, Prom1+, Trp73+) remain cancer-prone and give rise to serous tubal intraepithelial carcinomas and overt HGSC. These findings identify transitional pre-ciliated cells as a cancer-prone cell state and point to pre-ciliation mechanisms as diagnostic and therapeutic targets.

Neoadjuvant PARPi or chemotherapy in ovarian cancer informs targeting effector Treg cells for homologous-recombination-deficient tumors

Homologous recombination deficiency (HRD) is prevalent in cancer, sensitizing tumor cells to poly (ADP-ribose) polymerase (PARP) inhibition. However, the impact of HRD and related therapies on the tumor microenvironment (TME) remains elusive. Our study generates single-cell gene expression and T cell receptor profiles, along with validatory multimodal datasets from >100 high-grade serous ovarian cancer (HGSOC) samples, primarily from a phase II clinical trial (NCT04507841). Neoadjuvant monotherapy with the PARP inhibitor (PARPi) niraparib achieves impressive 62.5% and 73.6% response rates per RECIST v.1.1 and GCIG CA125, respectively. We identify effector regulatory T cells (eTregs) as key responders to HRD and neoadjuvant therapies, co-occurring with other tumor-reactive T cells, particularly terminally exhausted CD8+ T cells (Tex). TME-wide interferon signaling correlates with cancer cells upregulating MHC class II and co-inhibitory ligands, potentially driving Treg and Tex fates. Depleting eTregs in HRD mouse models, with or without PARP inhibition, significantly suppresses tumor growth without observable toxicities, underscoring the potential of eTreg-focused therapeutics for HGSOC and other HRD-related tumors.

Novel Cancer Prevention Strategies in Individuals With Hereditary Cancer Syndromes: Focus on BRCA1, BRCA2, and Lynch Syndrome

Germline pathogenic variants (PVs) in the BRCA1 and BRCA2 genes confer elevated risks of breast, ovarian, and other cancers. Lynch syndrome (LS) is associated with increased risks of multiple cancer types including colorectal and uterine cancers. Current cancer risk mitigation strategies have focused on pharmacologic risk reduction, enhanced surveillance, and preventive surgeries. While these approaches can be effective, they stand to be improved on because of either limited efficacy or undesirable impact on quality of life. The current review summarizes ongoing investigational efforts in cancer risk prevention strategies for patients with germline PVs in BRCA1, BRCA2, or LS-associated genes. These efforts span radiation, surgery, and pharmacology including vaccine strategies. Understanding the molecular events involved in the premalignant to malignant transformation in high-risk individuals may ultimately contribute significantly to novel prevention strategies.

Fallopian tube single cell analysis reveals myeloid cell alterations in high-grade serous ovarian cancer

Most high-grade serous ovarian cancers (HGSCs) likely initiate from fallopian tube (FT) epithelia. While epithelial subtypes have been characterized using single-cell RNA-sequencing (scRNA-Seq), heterogeneity of other compartments and their involvement in tumor progression are poorly defined. Integrated analysis of human FT scRNA-Seq and HGSC-related tissues, including tumors, revealed greater immune and stromal transcriptional diversity than previously reported. We identified abundant monocytes in FTs across two independent cohorts. The ratio of macrophages to monocytes is similar between benign FTs, ovaries, and adjacent normal tissues but significantly greater in tumors. FT-defined monocyte and macrophage signatures, cell-cell communication, and gene set enrichment analyses identified monocyte- and macrophage-specific interactions and functional pathways in paired tumors and adjacent normal tissues. Further reanalysis of HGSC scRNA-Seq identified monocyte and macrophage subsets associated with neoadjuvant chemotherapy. Taken together, our work provides data that an altered FT myeloid cell composition could inform the discovery of early detection markers for HGSC.

High-grade serous ovarian carcinoma, the "Achiles' hill" for clinicians and molecular biologists: a molecular insight

High-grade serous ovarian carcinoma (HGSOC), the deadliest ovarian cancer, alone accounts for 90% of all its subtypes. Characterized by hallmark mutation of TP53, HGSOC show diverse molecular etiology. HGSOC can arise from both ovarian epithelium as well as the fimbrial epithelium of the fallopian tube. Ovulation induced reactive oxygen species, follicular fluid associated growth factor induced stemness, deregulation of hormone receptors like ER, FSHR, AR and hormones like FSH, LH, prolonged ovulation cycle, use of oral contraceptives are agonists of HGSOC while parity, breastfeeding provide protective effect from HGSOC development. Apart from a generic TP53 mutation, mutation of BRCA1/2, RAD51, BRIP1, PALB2, CHEK2, RAD50 etc., were reportedly associated with development of HGSOC. Epigenetic events like methylation of RASSF1A of RAS signaling pathway,OR51L1, OR51I1, OR51F1 etc. has been reported in HGSOC. Micro-RNAs like miR-1290, miR 27-a-3p miR23a, miR205 were reportedly upregulated in HGSOC. Amongst its cognate subtypes viz. differentiated, immunoreactive, mesenchymal, and proliferative, mesenchymal, and proliferative show worst prognosis. A system biology approach showed five major altered pathways in HGSOC, namely, RB, PI3K/RAS, NOTCH, HRR and FOXM1 signaling. For chemonaive patients, drugs that helps in efflux of reduced glutathione or prevent the redox coupling of GSH-GSSG, like Cisplatin, could be considered as the best therapeutic choice for HGSOC. For patients with BRCA1/2 mutations, PARP inhibitors alone or with Bevacizumab can be effective. Immune checkpoint inhibitors could be effective against immunoreactive subtypes. Identification of genes deregulated in chemoresistance could provide better insights in dealing with the disease.

Targeting SOX18 Transcription Factor Activity by Small-Molecule Inhibitor Sm4 in Non-Small Lung Cancer Cell Lines

The transcription factor SOX18 has been shown to play a crucial role in lung cancer progression and metastasis. In this study, we investigated the effect of Sm4, a SOX18 inhibitor, on cell cycle regulation in non-small cell lung cancer (NSCLC) cell lines LXF-289 and SK-MES-1, as well as normal human lung fibroblast cell line IMR-90. Our results demonstrated that Sm4 treatment induced cytotoxic effects on all three cell lines, with a greater effect observed in NSCLC adenocarcinoma cells. Sm4 treatment led to S-phase cell accumulation and upregulation of p21, a key regulator of the S-to-G2/M phase transition. While no significant changes in SOX7 or SOX17 protein expression were observed, Sm4 treatment resulted in a significant upregulation of SOX17 gene expression. Furthermore, our findings suggest a complex interplay between SOX18 and p21 in the context of lung cancer, with a positive correlation observed between SOX18 expression and p21 nuclear presence in clinical tissue samples obtained from lung cancer patients. These results suggest that Sm4 has the potential to disrupt the cell cycle and target cancer cell growth by modulating SOX18 activity and p21 expression. Further investigation is necessary to fully understand the relationship between SOX18 and p21 in lung cancer and to explore the therapeutic potential of SOX18 inhibition in lung cancer.

In silico enhancer mining reveals SNS-032 and EHMT2 inhibitors as therapeutic candidates in high-grade serous ovarian cancer

BACKGROUND

Epigenomic dysregulation has been linked to solid tumour malignancies, including ovarian cancers. Profiling of re-programmed enhancer locations associated with disease has the potential to improve stratification and thus therapeutic choices. Ovarian cancers are subdivided into histological subtypes that have significant molecular and clinical differences, with high-grade serous carcinoma representing the most common and aggressive subtype.

METHODS

We interrogated the enhancer landscape(s) of normal ovary and subtype-specific ovarian cancer states using publicly available data. With an initial focus on H3K27ac histone mark, we developed a computational pipeline to predict drug compound activity based on epigenomic stratification. Lastly, we substantiated our predictions in vitro using patient-derived clinical samples and cell lines.

RESULTS

Using our in silico approach, we highlighted recurrent and privative enhancer landscapes and identified the differential enrichment of a total of 164 transcription factors involved in 201 protein complexes across the subtypes. We pinpointed SNS-032 and EHMT2 inhibitors BIX-01294 and UNC0646 as therapeutic candidates in high-grade serous carcinoma, as well as probed the efficacy of specific inhibitors in vitro.

CONCLUSION

Here, we report the first attempt to exploit ovarian cancer epigenomic landscapes for drug discovery. This computational pipeline holds enormous potential for translating epigenomic profiling into therapeutic leads.

Super-enhancer landscape rewiring in cancer: The epigenetic control at distal sites

Super-enhancers evolve as elements at the top of the hierarchical control of gene expression. They are important end-gatherers of signaling pathways that control stemness, differentiation or adaptive responses. Many epigenetic regulations focus on these regions, and not surprisingly, during the process of tumorigenesis, various alterations can account for their dysfunction. Super-enhancers are emerging as key drivers of the aberrant gene expression landscape that sustain the aggressiveness of cancer cells. In this review, we will describe and discuss about the structure of super-enhancers, their epigenetic regulation, and the major changes affecting their functionality in cancer.

Total Polyunsaturated Fatty Acid Level in Abdominal Adipose Tissue as an Independent Predictor of Recurrence-Free Survival in Women with Ovarian Cancer

Prognostic factors for epithelial ovarian cancers (EOCs) are in particular clinical factors such as pathology staging at diagnosis (FIGO stages), genetic mutation, or histological phenotypes. In the present study, FIGO stage, tumor residue after surgery, and body mass index were clinical predictors of recurrence-free survival (RFS). Nonetheless, a number of studies support a lipid metabolism disorder in ovarian cancer patients. The objective of this pilot study was to explore whether fatty acid composition of adipose reflecting the qualitative dietary intake and fatty acids metabolism may be associated with RFS. Forty-six women with EOCs and six with borderline ovarian tumors between March 2017 and January 2020 were included in this prospective study at Tours university teaching hospital (central France). The patients involved in the present study are part of the METERMUS trial (clinicaltrials.gov NCT03027479). Adipose tissue specimens from four abdominal locations (superficial and deep subcutaneous, visceral (pericolic), and omental) were collected during surgery or exploratory laparoscopy. A fatty acid profile of adipose tissue triglycerides was established by gas chromatography. Fatty acids composition was compared among the four locations using nonparametric Friedman’s ANOVA test for repeated measures. Median follow-up of EOC patients was 15 months and patients’ RFS was analyzed using Kaplan−Meier survival curves and log-rank test by separating patients into two groups according to median fatty acid levels. The content of long-chain saturated fatty acids (SFAs) was increased and that of long-chain polyunsaturated fatty acids (PUFAs) decreased in deep versus superficial subcutaneous adipose tissue in EOC patients. Nevertheless, the content of total SFAs was ~28%, monounsaturated fatty acids (MUFAs) ~55%, PUFAs n-6 ~11.5%, and PUFAs n-3 about 1.3%, whatever the adipose tissue. When EOC patients were separated into two groups by median fatty acid content, total PUFAs (n-6+n-3) levels, whatever the adipose tissue, were positively and independently associated with RFS. RFS was about two times longer in EOC patients with high versus low total PUFA content (median survival: 12 vs. 27 months, p = 0.01 to <0.0001 according to the tissue). Content of total PUFAs (n-6+n-3) in abdominal adipose tissue (visceral and subcutaneous) are new prognostic factors in EOC.

Current Update on PET/MRI in Gynecological Malignancies-A Review of the Literature

Early detection of gynecological malignancies is vital for patient management and prolonging the patient's survival. Molecular imaging, such as positron emission tomography (PET)/computed tomography, has been increasingly utilized in gynecological malignancies. PET/magnetic resonance imaging (MRI) enables the assessment of gynecological malignancies by combining the metabolic information of PET with the anatomical and functional information from MRI. This article will review the updated applications of PET/MRI in gynecological malignancies.

The Challenges and Prospects of p53-Based Therapies in Ovarian Cancer

It has been well established that mutations in the tumor suppressor gene, p53, occur readily in a vast majority of cancer tumors, including ovarian cancer. Typically diagnosed in stages three or four, ovarian cancer is the fifth leading cause of death in women, despite accounting for only 2.5% of all female malignancies. The overall 5-year survival rate for ovarian cancer is around 47%; however, this drops to an abysmal 29% for the most common type of ovarian cancer, high-grade serous ovarian carcinoma (HGSOC). HGSOC has upwards of 96% of cases expressing mutations in p53. Therefore, wild-type (WT) p53 and p53-based therapies have been explored as treatment options via a plethora of drug delivery vehicles including nanoparticles, viruses, polymers, and liposomes. However, previous p53 therapeutics have faced many challenges, which have resulted in their limited translational success to date. This review highlights a selection of these historical p53-targeted therapeutics for ovarian cancer, why they failed, and what the future could hold for a new generation of this class of therapies.

DNA methylation and transcriptomic features are preserved throughout disease recurrence and chemoresistance in high grade serous ovarian cancers

Background

Little is known about the role of global DNA methylation in recurrence and chemoresistance of high grade serous ovarian cancer (HGSOC).

Methods

We performed whole genome bisulfite sequencing and transcriptome sequencing in 62 primary and recurrent tumors from 28 patients with stage III/IV HGSOC, of which 11 patients carried germline, pathogenic BRCA1 and/or BRCA2 mutations.

Results

Landscapes of genome-wide methylation (on average 24.2 million CpGs per tumor) and transcriptomes in primary and recurrent tumors showed extensive heterogeneity between patients but were highly preserved in tumors from the same patient. We identified significant differences in the burden of differentially methylated regions (DMRs) in tumors from BRCA1/2 compared to non-BRCA1/2 carriers (mean 659 DMRs and 388 DMRs in paired comparisons respectively). We identified overexpression of immune pathways in BRCA1/2 carriers compared to non-carriers, implicating an increased immune response in improved survival (P = 0.006) in these BRCA1/2 carriers.

Conclusion

These findings indicate methylome and gene expression programs established in the primary tumor are conserved throughout disease progression, even after extensive chemotherapy treatment, and that changes in methylation and gene expression are unlikely to serve as drivers for chemoresistance in HGSOC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13046-022-02440-z.

Molecular Management of High-Grade Serous Ovarian Carcinoma

High-grade serous ovarian carcinoma (HGSOC) represents the most common form of epithelial ovarian carcinoma. The absence of specific symptoms leads to late-stage diagnosis, making HGSOC one of the gynecological cancers with the worst prognosis. The cellular origin of HGSOC and the role of reproductive hormones, genetic traits (such as alterations in P53 and DNA-repair mechanisms), chromosomal instability, or dysregulation of crucial signaling pathways have been considered when evaluating prognosis and response to therapy in HGSOC patients. However, the detection of HGSOC is still based on traditional methods such as carbohydrate antigen 125 (CA125) detection and ultrasound, and the combined use of these methods has yet to support significant reductions in overall mortality rates. The current paradigm for HGSOC management has moved towards early diagnosis via the non-invasive detection of molecular markers through liquid biopsies. This review presents an integrated view of the relevant cellular and molecular aspects involved in the etiopathogenesis of HGSOC and brings together studies that consider new horizons for the possible early detection of this gynecological cancer.

TumorMet: A repository of tumor metabolic networks derived from context-specific Genome-Scale Metabolic Models

Studies about the metabolic alterations during tumorigenesis have increased our knowledge of the underlying mechanisms and consequences, which are important for diagnostic and therapeutic investigations. In this scenario and in the era of systems biology, metabolic networks have become a powerful tool to unravel the complexity of the cancer metabolic machinery and the heterogeneity of this disease. Here, we present TumorMet, a repository of tumor metabolic networks extracted from context-specific Genome-Scale Metabolic Models, as a benchmark for graph machine learning algorithms and network analyses. This repository has an extended scope for use in graph classification, clustering, community detection, and graph embedding studies. Along with the data, we developed and provided Met2Graph, an R package for creating three different types of metabolic graphs, depending on the desired nodes and edges: Metabolites-, Enzymes-, and Reactions-based graphs. This package allows the easy generation of datasets for downstream analysis.

Measurement(s)	gene expression, metabolic relationships
Technology Type(s)	Genome Scale Metabolic Models; Computational network biology
Sample Characteristic - Organism	Homo sapiens

Dissection of transcriptome dysregulation and immune characterization in women with germline BRCA1 mutation at single-cell resolution

BACKGROUND

High-grade serous carcinoma (HGSC) is the most frequent and lethal type of ovarian cancer. It has been proposed that tubal secretory cells are the origin of ovarian HGSC in women with familial BRCA1/2 mutations. However, the molecular changes underlying malignant transformation remain unknown.

METHOD

We performed single-cell RNA and T cell receptor sequencing of tubal fimbriated ends from 3 BRCA1 germline mutation carriers (BRCA1 carriers) and 3 normal controls with no high-risk history (non-BRCA1 carriers).

RESULTS

Exploring the transcriptomes of 19,008 cells, predominantly from BRCA1+ samples, we identified 5 major cell populations in the fallopian tubal mucosae. The secretory cells of BRCA1+ samples had differentially expressed genes involved in tumor growth and regulation, chemokine signaling, and antigen presentation compared to the wild-type BRCA1 controls. There are several novel findings in this study. First, a subset of the fallopian tubal secretory cells from one BRCA1 carrier exhibited an epithelial-to-mesenchymal transition (EMT) phenotype, which was also present in the mucosal fibroblasts. Second, we identified a previously unreported phenotypic split of the EMT secretory cells with distinct evolutionary endpoints. Third, we observed increased clonal expansion among the CD8+ T cell population from BRCA1+ carriers. Among those clonally expanded CD8+ T cells, PD-1 was significantly increased in tubal mucosae of BRCA1+ patients compared with that of normal controls, indicating that T cell exhaustion may occur before the development of any premalignant or malignant lesions.

CONCLUSION

These results indicate that EMT and immune evasion in normal-looking tubal mucosae may represent early events leading to the development of HGSC in women with BRCA1 germline mutation. Our findings provide a probable molecular mechanism explaining why some, but not all, women with BRCA1 germline mutation present with early development and rapid dissemination of HGSC.

Machine learning applications in gynecological cancer: A critical review

Machine Learning (ML) represents a computer science capable of generating predictive models, by exposure to raw, training data, without being rigidly programmed. Over the last few years, ML has gained attention within the field of oncology, with considerable strides in both diagnostic, predictive, and prognostic spectrum of malignancies, but also as a catalyst of cancer research. In this review, we discuss the state of ML applications on gynecologic oncology and systematically address major technical and ethical concerns, with respect to their real-world medical practice translation. Undoubtedly, advances in ML will enable the analysis of large, rather complex, datasets for improved, cost-effective, and efficient clinical decisions.

A multi-omic dissection of super-enhancer driven oncogenic gene expression programs in ovarian cancer

The human genome contains regulatory elements, such as enhancers, that are often rewired by cancer cells for the activation of genes that promote tumorigenesis and resistance to therapy. This is especially true for cancers that have little or no known driver mutations within protein coding genes, such as ovarian cancer. Herein, we utilize an integrated set of genomic and epigenomic datasets to identify clinically relevant super-enhancers that are preferentially amplified in ovarian cancer patients. We systematically probe the top 86 super-enhancers, using CRISPR-interference and CRISPR-deletion assays coupled to RNA-sequencing, to nominate two salient super-enhancers that drive proliferation and migration of cancer cells. Utilizing Hi-C, we construct chromatin interaction maps that enable the annotation of direct target genes for these super-enhancers and confirm their activity specifically within the cancer cell compartment of human tumors using single-cell genomics data. Together, our multi-omic approach examines a number of fundamental questions about how regulatory information encoded into super-enhancers drives gene expression networks that underlie the biology of ovarian cancer.

The transcription factor PAX8 promotes angiogenesis in ovarian cancer through interaction with SOX17

PAX8 is a master transcription factor that is essential during embryogenesis and promotes neoplastic growth. It is expressed by the secretory cells lining the female reproductive tract, and its deletion during development results in atresia of reproductive tract organs. Nearly all ovarian carcinomas express PAX8, and its knockdown results in apoptosis of ovarian cancer cells. To explore the role of PAX8 in these tissues, we purified the PAX8 protein complex from nonmalignant fallopian tube cells and high-grade serous ovarian carcinoma cell lines. We found that PAX8 was a member of a large chromatin remodeling complex and preferentially interacted with SOX17, another developmental transcription factor. Depleting either PAX8 or SOX17 from cancer cells altered the expression of factors involved in angiogenesis and functionally disrupted tubule and capillary formation in cell culture and mouse models. PAX8 and SOX17 in ovarian cancer cells promoted the secretion of angiogenic factors by suppressing the expression of SERPINE1, which encodes a proteinase inhibitor with antiangiogenic effects. The findings reveal a non-cell-autonomous function of these transcription factors in regulating angiogenesis in ovarian cancer.

USP13 promotes development and metastasis of high-grade serous ovarian carcinoma in a novel mouse model

Epithelial ovarian cancer is the most lethal gynecologic malignancy and one of the most common causes of cancer mortality among women worldwide. Ubiquitin-Specific Peptidase 13 (USP13) gene copy is strongly amplified in human epithelial ovarian cancer, and high USP13 expression is correlated with poor survival outcomes. Yet, its pathological contribution to ovarian tumorigenesis remains unknown. We crossed a conditional Usp13 overexpressing knock-in mouse with a conditional knockout of Trp53 and Pten mouse and generated a novel ovarian cancer genetically engineered mouse model (GEMM), which closely recapitulates the genetic changes driving ovarian cancer in humans. Overexpression of USP13 with deletion of Trp53 and Pten in murine ovarian surface epithelium accelerated ovarian tumorigenesis and led to decreased survival in mice. Notably, USP13 greatly enhanced peritoneal metastasis of ovarian tumors with frequent development of hemorrhagic ascites. The primary and metastatic tumors exhibited morphology and clinical behavior similar to human high-grade serous ovarian cancer. Co-inhibition of USP13 and AKT significantly decreased the viability of the primary murine ovarian cancer cells isolated from the GEMM. USP13 also increased the tumorigenic and metastatic abilities of primary murine ovarian cancer cells in a syngeneic mouse study. These findings suggest a critical role of USP13 in ovarian cancer development and reveal USP13 as a potential therapeutic target for ovarian cancer.

Human Papillomaviruses as Infectious Agents in Gynecological Cancers. Oncogenic Properties of Viral Proteins

Human papillomaviruses (HPVs), which belong to the Papillomaviridae family, constitute a group of small nonenveloped double-stranded DNA viruses. HPV has a small genome that only encodes a few proteins, and it is also responsible for 5% of all human cancers, including cervical, vaginal, vulvar, penile, anal, and oropharyngeal cancers. HPV types may be classified as high- and low-risk genotypes (HR-HPVs and LR-HPVs, respectively) according to their oncogenic potential. HR-HPV 16 and 18 are the most common types worldwide and are the primary types that are responsible for most HPV-related cancers. The activity of the viral E6 and E7 oncoproteins, which interfere with critical cell cycle points such as suppressive tumor protein p53 (p53) and retinoblastoma protein (pRB), is the major contributor to HPV-induced neoplastic initiation and progression of carcinogenesis. In addition, the E5 protein might also play a significant role in tumorigenesis. The role of HPV in the pathogenesis of gynecological cancers is still not fully understood, which indicates a wide spectrum of potential research areas. This review focuses on HPV biology, the distribution of HPVs in gynecological cancers, the properties of viral oncoproteins, and the molecular mechanisms of carcinogenesis.

Functional analysis of the 1p34.3 risk locus implicates GNL2 in high-grade serous ovarian cancer

The high-grade serous ovarian cancer (HGSOC) risk locus at chromosome 1p34.3 resides within a frequently amplified genomic region signifying the presence of an oncogene. Here, we integrate in silico variant-to-function analysis with functional studies to characterize the oncogenic potential of candidate genes in the 1p34.3 locus. Fine mapping of genome-wide association statistics identified candidate causal SNPs local to H3K27ac-demarcated enhancer regions that exhibit allele-specific binding for CTCF in HGSOC and normal fallopian tube secretory epithelium cells (FTSECs). SNP risk associations colocalized with eQTL for six genes (DNALI1, GNL2, RSPO1, SNIP1, MEAF6, and LINC01137) that are more highly expressed in carriers of the risk allele, and three (DNALI1, GNL2, and RSPO1) were upregulated in HGSOC compared to normal ovarian surface epithelium cells and/or FTSECs. Increased expression of GNL2 and MEAF6 was associated with shorter survival in HGSOC with 1p34.3 amplifications. Despite its activation of β-catenin signaling, RSPO1 overexpression exerted no effects on proliferation or colony formation in our study of ovarian cancer and FTSECs. Instead, GNL2, MEAF6, and SNIP1 silencing impaired in vitro ovarian cancer cell growth. Additionally, GNL2 silencing diminished xenograft tumor formation, whereas overexpression stimulated proliferation and colony formation in FTSECs. GNL2 influences 60S ribosomal subunit maturation and global protein synthesis in ovarian cancer and FTSECs, providing a potential mechanism of how GNL2 upregulation might promote ovarian cancer development and mediate genetic susceptibility of HGSOC.

Does the "Devil" originate from the fallopian tubes?

Epithelial ovarian cancer (OC) is a heterogeneous disease and continues to be mostly diagnosed in advanced stages. The high lethality, the high rate of platinum-resistance, and the poor survival outcomes are the principal factors for categorizing OC among the most aggressive gynecological cancers. Only recently, a substantial progress has been made in our latest understanding of the origins of OC, particularly of high-grade serous histology. For a long time, the accumulation of genetic alterations in epithelial single layer cells of ovarian cysts caused by cyclic ovulations was considered as the most important driver and the long-standing dogma of ovarian tumorigenesis. Besides, the unique biological features and high histological heterogeneity of OC did not support this hypothesis. Indeed, various extra-ovarian cells of origin and multiple sites to each histotype were proposed, supported by cogent evidence from clinical cohorts and animal studies. In light of this enigma, this review was conducted to discuss the recent evidence supporting the revised origins of ovarian carcinoma histotypes with a particular focus on high-grade serous OC which may impact diagnostic and preventive approaches.

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.

Advances in understanding the molecular pathology of gynecological malignancies: the role and potential of RNA sequencing

For many years technological limitations restricted the progress of identifying the underlying genetic causes of gynecologicalcancers. However, during the past decade, high-throughput next-generation sequencing technologies have revolutionized cancer research. RNA sequencing has arisen as a very useful technique in expanding our understanding of genome changes in cancer. Cancer is characterized by the accumulation of genetic alterations affecting genes, including substitutions, insertions, deletions, translocations, gene fusions, and alternative splicing. If these aberrant genes become transcribed, aberrations can be detected by RNA sequencing, which will also provide information on the transcript abundance revealing the expression levels of the aberrant genes. RNA sequencing is considered the technique of choice when studying gene expression and identifying new RNA species. This is due to the quantitative and qualitative improvement that it has brought to transcriptome analysis, offering a resolution that allows research into different layers of transcriptome complexity. It has also been successful in identifying biomarkers, fusion genes, tumor suppressors, and uncovering new targets responsible for drug resistance in gynecological cancers. To illustrate that we here review the role of RNA sequencing in studies that enhanced our understanding of the molecular pathology of gynecological cancers.

High-grade serous tubo-ovarian cancer refined with single-cell RNA sequencing: specific cell subtypes influence survival and determine molecular subtype classification

BACKGROUND

High-grade serous tubo-ovarian cancer (HGSTOC) is characterised by extensive inter- and intratumour heterogeneity, resulting in persistent therapeutic resistance and poor disease outcome. Molecular subtype classification based on bulk RNA sequencing facilitates a more accurate characterisation of this heterogeneity, but the lack of strong prognostic or predictive correlations with these subtypes currently hinders their clinical implementation. Stromal admixture profoundly affects the prognostic impact of the molecular subtypes, but the contribution of stromal cells to each subtype has poorly been characterised. Increasing the transcriptomic resolution of the molecular subtypes based on single-cell RNA sequencing (scRNA-seq) may provide insights in the prognostic and predictive relevance of these subtypes.

METHODS

We performed scRNA-seq of 18,403 cells unbiasedly collected from 7 treatment-naive HGSTOC tumours. For each phenotypic cluster of tumour or stromal cells, we identified specific transcriptomic markers. We explored which phenotypic clusters correlated with overall survival based on expression of these transcriptomic markers in microarray data of 1467 tumours. By evaluating molecular subtype signatures in single cells, we assessed to what extent a phenotypic cluster of tumour or stromal cells contributes to each molecular subtype.

RESULTS

We identified 11 cancer and 32 stromal cell phenotypes in HGSTOC tumours. Of these, the relative frequency of myofibroblasts, TGF-β-driven cancer-associated fibroblasts, mesothelial cells and lymphatic endothelial cells predicted poor outcome, while plasma cells correlated with more favourable outcome. Moreover, we identified a clear cell-like transcriptomic signature in cancer cells, which correlated with worse overall survival in HGSTOC patients. Stromal cell phenotypes differed substantially between molecular subtypes. For instance, the mesenchymal, immunoreactive and differentiated signatures were characterised by specific fibroblast, immune cell and myofibroblast/mesothelial cell phenotypes, respectively. Cell phenotypes correlating with poor outcome were enriched in molecular subtypes associated with poor outcome.

CONCLUSIONS

We used scRNA-seq to identify stromal cell phenotypes predicting overall survival in HGSTOC patients. These stromal features explain the association of the molecular subtypes with outcome but also the latter's weakness of clinical implementation. Stratifying patients based on marker genes specific for these phenotypes represents a promising approach to predict prognosis or response to therapy.

Most Commonly Mutated Genes in High-Grade Serous Ovarian Carcinoma Are Nonessential for Ovarian Surface Epithelial Stem Cell Transformation

High-grade serous ovarian carcinoma (HGSOC) is the fifth leading cause of cancer-related deaths of women in the United States. Disease-associated mutations have been identified by the Cancer Genome Atlas Research Network. However, aside from mutations in TP53 or the RB1 pathway that are common in HGSOC, the contributions of mutation combinations are unclear. Here, we report CRISPR mutagenesis of 20 putative HGSOC driver genes to identify combinatorial disruptions of genes that transform either ovarian surface epithelium stem cells (OSE-SCs) or non-stem cells (OSE-NSs). Our results support the OSE-SC theory of HGSOC initiation and suggest that most commonly mutated genes in HGSOC have no effect on OSE-SC transformation initiation. Our results indicate that disruption of TP53 and PTEN, combined with RB1 disruption, constitutes a core set of mutations driving efficient transformation in vitro. The combined data may contribute to more accurate modeling of HGSOC development.

Reduced SKP1 and CUL1 expression underlies increases in Cyclin E1 and chromosome instability in cellular precursors of high-grade serous ovarian cancer

BACKGROUND

High-grade serous ovarian cancer (HGSOC) is the most common and lethal ovarian cancer histotype. Chromosome instability (CIN, an increased rate of chromosome gains and losses) is believed to play a fundamental role in the development and evolution of HGSOC. Importantly, overexpression of Cyclin E1 protein induces CIN, and genomic amplification of CCNE1 contributes to HGSOC pathogenesis in ~20% of patients. Cyclin E1 levels are normally regulated in a cell cycle-dependent manner by the SCF (SKP1-CUL1-FBOX) complex, an E3 ubiquitin ligase that includes the proteins SKP1 and CUL1. Conceptually, diminished SKP1 or CUL1 expression is predicted to underlie increases in Cyclin E1 levels and induce CIN.

METHODS

This study employs fallopian tube secretory epithelial cell models to evaluate the impact diminished SKP1 or CUL1 expression has on Cyclin E1 and CIN in both short-term (siRNA) and long-term (CRISPR/Cas9) studies.

RESULTS

Single-cell quantitative imaging microscopy approaches revealed changes in CIN-associated phenotypes and chromosome numbers and increased Cyclin E1 in response to diminished SKP1 or CUL1 expression.

CONCLUSIONS

These data identify SKP1 and CUL1 as novel CIN genes in HGSOC precursor cells that may drive early aetiological events contributing to HGSOC development.

Single-cell transcriptomics identifies gene expression networks driving differentiation and tumorigenesis in the human fallopian tube

The human fallopian tube harbors the cell of origin for the majority of high-grade serous "ovarian" cancers (HGSCs), but its cellular composition, particularly the epithelial component, is poorly characterized. We perform single-cell transcriptomic profiling of around 53,000 individual cells from 12 primary fallopian specimens to map their major cell types. We identify 10 epithelial subpopulations with diverse transcriptional programs. Based on transcriptional signatures, we reconstruct a trajectory whereby secretory cells differentiate into ciliated cells via a RUNX3^high intermediate. Computational deconvolution of advanced HGSCs identifies the "early secretory" population as a likely precursor state for the majority of HGSCs. Its signature comprises both epithelial and mesenchymal features and is enriched in mesenchymal-type HGSCs (p = 6.7 × 10^-27), a group known to have particularly poor prognoses. This cellular and molecular compendium of the human fallopian tube in cancer-free women is expected to advance our understanding of the earliest stages of fallopian epithelial neoplasia.

The current landscape of single-cell transcriptomics for cancer immunotherapy

Immunotherapies such as immune checkpoint blockade and adoptive cell transfer have revolutionized cancer treatment, but further progress is hindered by our limited understanding of tumor resistance mechanisms. Emerging technologies now enable the study of tumors at the single-cell level, providing unprecedented high-resolution insights into the genetic makeup of the tumor microenvironment and immune system that bulk genomics cannot fully capture. Here, we highlight the recent key findings of the use of single-cell RNA sequencing to deconvolute heterogeneous tumors and immune populations during immunotherapy. Single-cell RNA sequencing has identified new crucial factors and cellular subpopulations that either promote tumor progression or leave tumors vulnerable to immunotherapy. We anticipate that the strategic use of single-cell analytics will promote the development of the next generation of successful, rationally designed immunotherapeutics.

Genetically Defined, Syngeneic Organoid Platform for Developing Combination Therapies for Ovarian Cancer

The paucity of genetically informed, immunocompetent tumor models impedes evaluation of conventional, targeted, and immune therapies. By engineering mouse fallopian tube epithelial organoids using lentiviral gene transduction and/or CRISPR/Cas9 mutagenesis, we generated multiple high-grade serous tubo-ovarian cancer (HGSC) models exhibiting mutational combinations seen in patients with HGSC. Detailed analysis of homologous recombination (HR)-proficient (Trp53^-/-;Ccne1^OE;Akt2^OE;Kras^OE ), HR-deficient (Trp53^-/-;Brca1^-/-;Myc^OE ), and unclassified (Trp53^-/-;Pten^-/-;Nf1^-/- ) organoids revealed differences in in vitro properties (proliferation, differentiation, and "secretome"), copy-number aberrations, and tumorigenicity. Tumorigenic organoids had variable sensitivity to HGSC chemotherapeutics, and evoked distinct immune microenvironments that could be modulated by neutralizing organoid-produced chemokines/cytokines. These findings enabled development of a chemotherapy/immunotherapy regimen that yielded durable, T cell-dependent responses in Trp53^-/-;Ccne1^OE;Akt2^OE;Kras HGSC; in contrast, Trp53^-/-;Pten^-/-;Nf1^-/- tumors failed to respond. Mouse and human HGSC models showed genotype-dependent similarities in chemosensitivity, secretome, and immune microenvironment. Genotype-informed, syngeneic organoid models could provide a platform for the rapid evaluation of tumor biology and therapeutics. SIGNIFICANCE: The lack of genetically informed, diverse, immunocompetent models poses a major barrier to therapeutic development for many malignancies. Using engineered fallopian tube organoids to study the cell-autonomous and cell-nonautonomous effects of specific combinations of mutations found in HGSC, we suggest an effective combination treatment for the currently intractable CCNE1-amplified subgroup.This article is highlighted in the In This Issue feature, p. 211.

Transcription factors in epithelial ovarian cancer: histotype-specific drivers and novel therapeutic targets

Transcription factors (TFs) are major contributors to cancer risk and somatic development. In preclinical and clinical studies, direct or indirect inhibition of TF-mediated oncogenic gene expression profiles have proven to be effective in many tumor types, highlighting this group of proteins as valuable therapeutic targets. In spite of this, our understanding of TFs in epithelial ovarian cancer (EOC) is relatively limited. EOC is a heterogeneous disease composed of five major histologic subtypes; high-grade serous, low-grade serous, endometrioid, clear cell and mucinous. Each histology is associated with unique clinical etiologies, sensitivity to therapies, and molecular signatures - including diverse transcriptional regulatory programs. While some TFs are shared across EOC subtypes, a set of TFs are expressed in a histotype-specific manner and likely explain part of the histologic diversity of EOC subtypes. Targeting TFs present with unique opportunities for development of novel precision medicine strategies for ovarian cancer. This article reviews the critical TFs in EOC subtypes and highlights the potential of exploiting TFs as biomarkers and therapeutic targets.

A cell-of-origin epigenetic tracer reveals clinically distinct subtypes of high-grade serous ovarian cancer

BACKGROUND

High-grade serous ovarian cancer (HGSOC) is a major unmet need in oncology. The remaining uncertainty on its originating tissue has hampered the discovery of molecular oncogenic pathways and the development of effective therapies.

METHODS

We used an approach based on the retention in tumors of a DNA methylation trace (OriPrint) that distinguishes the two putative tissues of origin of HGSOC, the fimbrial (FI) and ovarian surface epithelia (OSE), to stratify HGSOC by several clustering methods, both linear and non-linear. The identified tumor subtypes (FI-like and OSE-like HGSOC) were investigated at the RNAseq level to stratify an in-house cohort of macrodissected HGSOC FFPE samples to derive overall and disease-free survival and identify specific transcriptional alterations of the two tumor subtypes, both by classical differential expression and weighted correlation network analysis. We translated our strategy to published datasets and verified the co-occurrence of previously described molecular classification of HGSOC. We performed cytokine analysis coupled to immune phenotyping to verify alterations in the immune compartment associated with HGSOC. We identified genes that are both differentially expressed and methylated in the two tumor subtypes, concentrating on PAX8 as a bona fide marker of FI-like HGSOC.

RESULTS

We show that: - OriPrint is a robust DNA methylation tracer that exposes the tissue of origin of HGSOC. - The tissue of origin of HGSOC is the main determinant of DNA methylation variance in HGSOC. - The tissue of origin is a prognostic factor for HGSOC patients. - FI-like and OSE-like HGSOC are endowed with specific transcriptional alterations that impact patients' prognosis. - OSE-like tumors present a more invasive and immunomodulatory phenotype, compatible with its worse prognostic impact. - Among genes that are differentially expressed and regulated in FI-like and OSE-like HGSOC, PAX8 is a bona fide marker of FI-like tumors.

CONCLUSIONS

Through an integrated approach, our work demonstrates that both FI and OSE are possible origins for human HGSOC, whose derived subtypes are both molecularly and clinically distinct. These results will help define a new roadmap towards rational, subtype-specific therapeutic inroads and improved patients' care.

Cancer and SOX proteins: New insight into their role in ovarian cancer progression/inhibition

Transcription factors are potential targets in disease therapy, particularly in cancer. This is due to the fact that transcription factors regulate a variety of cellular events, and their modulation has opened a new window in cancer therapy. Sex-determining region Y (SRY)-related high-mobility group (HMG) box (SOX) proteins are potential transcription factors that are involved in developmental processes such as embryogenesis. It has been reported that abnormal expression of SOX proteins is associated with development of different cancers, particularly ovarian cancer (OC). In the present review, our aim is to provide a mechanistic review of involvement of SOX members in OC. SOX members may suppress and/or promote aggressiveness and proliferation of OC cells. Clinical studies have also confirmed the potential of transcription factors as diagnostic and prognostic factors in OC. Notably, studies have demonstrated the relationship between SOX members and other molecular pathways such as ST6Ga1-I, PI3K, ERK and so on, leading to more complexity. Furthermore, SOX members can be affected by upstream mediators such as microRNAs, long non-coding RNAs, and so on. It is worth mentioning that the expression of each member of SOX proteins is corelated with different stages of OC. Furthermore, their expression determines the response of OC cells to chemotherapy. These topics are discussed in this review to shed some light on role of SOX transcription factors in OC.

Assessing the origin of high-grade serous ovarian cancer using CRISPR-modification of mouse organoids

High-grade serous ovarian cancer (HG-SOC)—often referred to as a “silent killer”—is the most lethal gynecological malignancy. The fallopian tube (murine oviduct) and ovarian surface epithelium (OSE) are considered the main candidate tissues of origin of this cancer. However, the relative contribution of each tissue to HG-SOC is not yet clear. Here, we establish organoid-based tumor progression models of HG-SOC from murine oviductal and OSE tissues. We use CRISPR-Cas9 genome editing to introduce mutations into genes commonly found mutated in HG-SOC, such as Trp53, Brca1, Nf1 and Pten. Our results support the dual origin hypothesis of HG-SOC, as we demonstrate that both epithelia can give rise to ovarian tumors with high-grade pathology. However, the mutated oviductal organoids expand much faster in vitro and more readily form malignant tumors upon transplantation. Furthermore, in vitro drug testing reveals distinct lineage-dependent sensitivities to the common drugs used to treat HG-SOC in patients.

The relative contribution of fallopian tube (FT) or ovarian surface epithelium (OSE) to high-grade serous ovarian cancer (HG-SOC) development is unclear. Here, the authors establish organoid models from murine oviductal and OSE tissues that allow cancer modeling via CRISPR-Cas9 genome editing, and report a dual origin of murine HG-SOC.

Why the dual origins of high grade serous ovarian cancer matter

Utilising identical genetic aberrations but targeting different cells, Zhang and colleagues seek to uncover how the cell of origin influences high-grade serous ovarian cancer biology, metastasis and response to treatment.