Molecular Analysis of Clinically Defined Subsets of High-Grade Serous Ovarian Cancer

ProteoMixture: A cell type deconvolution tool for bulk tissue proteomic data

Numerous multi-omic investigations of cancer tissue have documented varying and poor pairwise transcript:protein quantitative correlations, and most deconvolution tools aiming to predict cell type proportions (cell admixture) have been developed and credentialed using transcript-level data alone. To estimate cell admixture using protein abundance data, we analyzed proteome and transcriptome data generated from contrived admixtures of tumor, stroma, and immune cell models or those selectively harvested from the tissue microenvironment by laser microdissection from high grade serous ovarian cancer (HGSOC) tumors. Co-quantified transcripts and proteins performed similarly to estimate stroma and immune cell admixture (r ≥ 0.63) in two commonly used deconvolution algorithms, ESTIMATE or ConsensusTME. We further developed and optimized protein-based signatures estimating cell admixture proportions and benchmarked these using bulk tumor proteomic data from over 150 patients with HGSOC. The optimized protein signatures supporting cell type proportion estimates from bulk tissue proteomic data are available at https://lmdomics.org/ProteoMixture/.

Proteogenomic analysis of enriched HGSOC tumor epithelium identifies prognostic signatures and therapeutic vulnerabilities

We performed a deep proteogenomic analysis of bulk tumor and laser microdissection enriched tumor cell populations from high-grade serous ovarian cancer (HGSOC) tissue specimens spanning a broad spectrum of purity. We identified patients with longer progression-free survival had increased immune-related signatures and validated proteins correlating with tumor-infiltrating lymphocytes in 65 tumors from an independent cohort of HGSOC patients, as well as with overall survival in an additional 126 HGSOC patient cohort. We identified that homologous recombination deficient (HRD) tumors are enriched in pathways associated with metabolism and oxidative phosphorylation that we validated in independent patient cohorts. We further identified that polycomb complex protein BMI-1 is elevated in HR proficient (HRP) tumors, that elevated BMI-1 correlates with poor overall survival in HRP but not HRD HGSOC patients, and that HRP HGSOC cells are uniquely sensitive to BMI-1 inhibition.

Mapping three-dimensional intratumor proteomic heterogeneity in uterine serous carcinoma by multiregion microsampling

BACKGROUND

Although uterine serous carcinoma (USC) represents a small proportion of all uterine cancer cases, patients with this aggressive subtype typically have high rates of chemotherapy resistance and disease recurrence that collectively result in a disproportionately high death rate. The goal of this study was to provide a deeper view of the tumor microenvironment of this poorly characterized uterine cancer variant through multi-region microsampling and quantitative proteomics.

METHODS

Tumor epithelium, tumor-involved stroma, and whole "bulk" tissue were harvested by laser microdissection (LMD) from spatially resolved levels from nine USC patient tumor specimens and underwent proteomic analysis by mass spectrometry and reverse phase protein arrays, as well as transcriptomic analysis by RNA-sequencing for one patient's tumor.

RESULTS

LMD enriched cell subpopulations demonstrated varying degrees of relatedness, indicating substantial intratumor heterogeneity emphasizing the necessity for enrichment of cellular subpopulations prior to molecular analysis. Known prognostic biomarkers were quantified with stable levels in both LMD enriched tumor and stroma, which were shown to be highly variable in bulk tissue. These USC data were further used in a comparative analysis with a data generated from another serous gynecologic malignancy, high grade serous ovarian carcinoma, and have been added to our publicly available data analysis tool, the Heterogeneity Analysis Portal ( https://lmdomics.org/ ).

CONCLUSIONS

Here we identified extensive three-dimensional heterogeneity within the USC tumor microenvironment, with disease-relevant biomarkers present in both the tumor and the stroma. These data underscore the critical need for upfront enrichment of cellular subpopulations from tissue specimens for spatial proteogenomic analysis.

Ovarian Cancer Diagnosis and Prognosis Based on Cell-Free DNA Methylation

Background: Ovarian cancer stands as the deadliest malignant tumor within the female reproductive tract. As a result of the absence of effective diagnostic and monitoring markers, 75% of ovarian cancer cases are diagnosed at a late stage, leading to a mere 50% survival rate within five years. The advancement of molecular biology is essential for accurate diagnosis and treatment of ovarian cancer. Methods: A review of several randomized clinical trials, focusing on the ovarian cancer, was undertaken. The advancement of molecular biology and diagnostic methods related to accurate diagnosis and treatment of ovarian cancer were examined. Results: Liquid biopsy is an innovative method of detecting malignant tumors that has gained increasing attention over the past few years. Cell-free DNA assay-based liquid biopsies show potential in delineating tumor status heterogeneity and tracking tumor recurrence. DNA methylation influences a multitude of biological functions and diseases, especially during the initial phases of cancer. The cell-free DNA methylation profiling system has emerged as a sensitive and non-invasive technique for identifying and detecting the biological origins of cancer. It holds promise as a biomarker, enabling early screening, recurrence monitoring, and prognostic evaluation of cancer. Conclusions: This review evaluates recent advancements and challenges associated with cell-free DNA methylation analysis for the diagnosis, prognosis monitoring, and assessment of therapeutic responses in the management of ovarian cancers, aiming to offer guidance for precise diagnosis and treatment of this disease.

Aptamers as Potential Therapeutic Tools for Ovarian Cancer: Advancements and Challenges

Ovarian cancer (OC) is the most common lethal gynecologic cause of death in women worldwide, with a high mortality rate and increasing incidence. Despite advancements in the treatment, most OC patients still die from their disease due to late-stage diagnosis, the lack of effective diagnostic methods, and relapses. Aptamers, synthetic, short single-stranded oligonucleotides, have emerged as promising anticancer therapeutics. Their ability to selectively bind to target molecules, including cancer-related proteins and receptors, has revolutionized drug discovery and biomarker identification. Aptamers offer unique insights into the molecular pathways involved in cancer development and progression. Moreover, they show immense potential as drug delivery systems, enabling targeted delivery of therapeutic agents to cancer cells while minimizing off-target effects and reducing systemic toxicity. In the context of OC, the integration of aptamers with non-coding RNAs (ncRNAs) presents an opportunity for precise and efficient gene targeting. Additionally, the conjugation of aptamers with nanoparticles allows for accurate and targeted delivery of ncRNAs to specific cells, tissues, or organs. In this review, we will summarize the potential use and challenges associated with the use of aptamers alone or aptamer-ncRNA conjugates, nanoparticles, and multivalent aptamer-based therapeutics for the treatment of OC.

In situ profiling reveals metabolic alterations in the tumor microenvironment of ovarian cancer after chemotherapy

In this study, we investigated the metabolic alterations associated with clinical response to chemotherapy in patients with ovarian cancer. Pre- and post-neoadjuvant chemotherapy (NACT) tissues from patients with high-grade serous ovarian cancer (HGSC) who had poor response (PR) or excellent response (ER) to NACT were examined. Desorption electrospray ionization mass spectrometry (DESI-MS) was performed on sections of HGSC tissues collected according to a rigorous laparoscopic triage algorithm. Quantitative MS-based proteomics and phosphoproteomics were performed on a subgroup of pre-NACT samples. Highly abundant metabolites in the pre-NACT PR tumors were related to pyrimidine metabolism in the epithelial regions and oxygen-dependent proline hydroxylation of hypoxia-inducible factor alpha in the stromal regions. Metabolites more abundant in the epithelial regions of post-NACT PR tumors were involved in the metabolism of nucleotides, and metabolites more abundant in the stromal regions of post-NACT PR tumors were related to aspartate and asparagine metabolism, phenylalanine and tyrosine metabolism, nucleotide biosynthesis, and the urea cycle. A predictive model built on ions with differential abundances allowed the classification of patients' tumor responses as ER or PR with 75% accuracy (10-fold cross-validation ridge regression model). These findings offer new insights related to differential responses to chemotherapy and could lead to novel actionable targets.

The murine metastatic microenvironment of experimental brain metastases of breast cancer differs by host age in vivo: a proteomic study

Breast cancer in young patients is known to exhibit more aggressive biological behavior and is associated with a less favorable prognosis than the same disease in older patients, owing in part to an increased incidence of brain metastases. The mechanistic explanations behind these findings remain poorly understood. We recently reported that young mice, in comparison to older mice, developed significantly greater brain metastases in four mouse models of triple-negative and luminal B breast cancer. Here we have performed a quantitative mass spectrometry-based proteomic analysis to identify proteins potentially contributing to age-related disparities in the development of breast cancer brain metastases. Using a mouse hematogenous model of brain-tropic triple-negative breast cancer (MDA-MB-231BR), we harvested subpopulations of tumor metastases, the tumor-adjacent metastatic microenvironment, and uninvolved brain tissues via laser microdissection followed by quantitative proteomic analysis using high resolution mass spectrometry to characterize differentially abundant proteins potentially contributing to age-dependent rates of brain metastasis. Pathway analysis revealed significant alterations in signaling pathways, particularly in the metastatic microenvironment, modulating tumorigenesis, metabolic processes, inflammation, and neuronal signaling. Tenascin C (TNC) was significantly elevated in all laser microdissection (LMD) enriched compartments harvested from young mice relative to older hosts, which was validated and confirmed by immunoblot analysis of whole brain lysates. Additional in vitro studies including migration and wound-healing assays demonstrated TNC as a positive regulator of tumor cell migration. These results provide important new insights regarding microenvironmental factors, including TNC, as mechanisms contributing to the increased brain cancer metastatic phenotype observed in young breast cancer patients.

Targeting RAS-ERK pathway alterations with MEK inhibitors to improve chemosensitivity in high grade serous ovarian cancers

OBJECTIVE

Assess if MEK inhibitor blockade of RAS-ERK pathway adaptive response in high grade serous ovarian cancers (HGSOC) improves platinum sensitivity.

METHODS

Three HGSOC cell lines and three patient derived organoid (PDOs) samples from ascites of platinum resistant HGSOC patients were collected. Cell lines and PDOs were exposed to carboplatin and MEK inhibitors cobimetinib or trametinib. Cytotoxic effects of MEK inhibitors alone or combined with carboplatin were established. Western blots demonstrated RAS-ERK pathway blockage after MEK inhibitor treatment. RNA sequencing assessed gene expression after MEK inhibitor treatment. Cell line NF1 gene knockdown was performed with corresponding chemosensitivity levels.

RESULTS

High carboplatin IC50 levels indicated platinum resistance in cell lines and PDOs. Cobimetinib induced cytotoxicity in cell lines and PDOs, while trametinib was less effective. Western blot confirmed MEK-ERK pathway blockage at minimal concentrations of MEK inhibitors in cell lines and PDOs. Phosphorylated-ERK levels of untreated cells indicated higher levels of RAS-ERK pathway activation in OVSAHO and OVCAR7 compared to OVCAR3. OVSAHO harbors a NF1 mutation and had highest levels of RAS-ERK activation. Cotreatment with carboplatin and MEK inhibitors showed varying synergistic cytotoxic effects at different combinations. Synergistic effect was most prominent in the OVSAHO carboplatin and cobimetinib combination. RNA sequencing identified downregulation of c-MYC and FOXM1 gene expression after MEK inhibitor treatment. NF1 gene knockdown showed an acquired increased IC50 compared to parental cells.

CONCLUSION

MEK inhibitors block RAS-ERK pathways in platinum resistant HGSOC cells and PDOs. MEK inhibitors with carboplatin have select synergistic effects which may indicate a strategy to improve platinum sensitivity.

Brain proteomic atlas of alcohol use disorder in adult males

Alcohol use disorder (AUD) affects transcriptomic, epigenetic and proteomic expression in several organs, including the brain. There has not been a comprehensive analysis of altered protein abundance focusing on the multiple brain regions that undergo neuroadaptations occurring in AUD. We performed a quantitative proteomic analysis using a liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis of human postmortem tissue from brain regions that play key roles in the development and maintenance of AUD, the amygdala (AMG), hippocampus (HIPP), hypothalamus (HYP), nucleus accumbens (NAc), prefrontal cortex (PFC) and ventral tegmental area (VTA). Brain tissues were from adult males with AUD (n = 11) and matched controls (n = 16). Across the two groups, there were >6000 proteins quantified with differential protein abundance in AUD compared to controls in each of the six brain regions. The region with the greatest number of differentially expressed proteins was the AMG, followed by the HYP. Pathways associated with differentially expressed proteins between groups (fold change > 1.5 and LIMMA p < 0.01) were analyzed by Ingenuity Pathway Analysis (IPA). In the AMG, adrenergic, opioid, oxytocin, GABA receptor and cytokine pathways were among the most enriched. In the HYP, dopaminergic signaling pathways were the most enriched. Proteins with differential abundance in AUD highlight potential therapeutic targets such as oxytocin, CSNK1D (PF-670462), GABAB receptor and opioid receptors and may lead to the identification of other potential targets. These results improve our understanding of the molecular alterations of AUD across brain regions that are associated with the development and maintenance of AUD. Proteomic data from this study is publicly available at www.lmdomics.org/AUDBrainProteomeAtlas/ .

Unlocking Exosome-Based Theragnostic Signatures: Deciphering Secrets of Ovarian Cancer Metastasis

Ovarian cancer (OC) is a common gynecological cancer worldwide. Unfortunately, the lack of early detection methods translates into a substantial cohort of women grappling with the pressing health crisis. The discovery of extracellular vesicles (EVs) (their major subpopulation exosomes, microvesicles, and apoptotic bodies) has provided new insights into the understanding of cancer. Exosomes, a subpopulation of EVs, play a crucial role in cellular communication and reflect the cellular status under both healthy and pathological conditions. Tumor-derived exosomes (TEXs) dynamically influence ovarian cancer progression by regulating uncontrolled cell growth, immune suppression, angiogenesis, metastasis, and the development of drug and therapeutic resistance. In the field of OC diagnostics, TEXs offer potential biomarkers in various body fluids. On the other hand, exosomes have also shown promising abilities to cure ovarian cancer. In this review, we address the interlink between exosomes and ovarian cancer and explore their theragnostic signature. Finally, we highlight future directions of exosome-based ovarian cancer research.

Metronomic dosing of ovarian cancer cells with the ATR inhibitor AZD6738 leads to loss of CDC25A expression and resistance to ATRi treatment

OBJECTIVE

ATR kinase inhibitors promote cell killing by inducing replication stress and through potentiation of genotoxic agents in gynecologic cancer cells. To explore mechanisms of acquired resistance to ATRi in ovarian cancer, we characterized ATRi-resistant ovarian cancer cells generated by metronomic dosing with the clinical ATR inhibitor AZD6738.

METHODS

ATRi-resistant ovarian cancer cells (OVCAR3 and OV90) were generated by dosing with AZD6738 and assessed for sensitivity to Chk1i (LY2603618), PARPi (Olaparib) and combination with cisplatin or a CDK4/6 inhibitor (Palbociclib). Models were characterized by diverse methods including silencing CDC25A in OV90 cells and assessing impact on ATRi response. Serum proteomic analysis of ATRi-resistant OV90 xenografts was performed to identify circulating biomarker candidates of ATRi-resistance.

RESULTS

AZD6738-resistant cell lines are refractory to LY2603618, but not to Olaparib or combinations with cisplatin. Cell cycle analyses showed ATRi-resistant cells exhibit G1/S arrest following AZD6738 treatment. Accordingly, combination with Palbociclib confers resistance to AZD6738. AZD6738-resistant cells exhibit altered abundances of G1/S phase regulatory proteins, including loss of CDC25A in AZD6738-resistant OV90 cells. Silencing of CDC25A in OV90 cells confers resistance to AZD6738. Serum proteomics from AZD6738-resistant OV90 xenografts identified Vitamin D-Binding Protein (GC), Apolipoprotein E (APOE) and A1 (APOA1) as significantly elevated in AZD6738-resistant backgrounds.

CONCLUSIONS

We show that metronomic dosing of ovarian cancer cells with AZD6738 results in resistance to ATR/ Chk1 inhibitors, that loss of CDC25A expression represents a mechanism of resistance to ATRi treatment in ovarian cancer cells and identify several circulating biomarker candidates of CDC25A low, AZD6738-resistant ovarian cancer cells.

PTEN in triple-negative breast carcinoma: protein expression and genomic alteration in pretreatment and posttreatment specimens

Background

Recent advances have been made in targeting the phosphoinositide 3-kinase pathway in breast cancer. Phosphatase and tensin homolog (PTEN) is a key component of that pathway.

Objective

To understand the changes in PTEN expression over the course of the disease in patients with triple-negative breast cancer (TNBC) and whether PTEN copy number variation (CNV) by next-generation sequencing (NGS) can serve as an alternative to immunohistochemistry (IHC) to identify PTEN loss.

Methods

We compared PTEN expression by IHC between pretreatment tumors and residual tumors in the breast and lymph nodes after neoadjuvant chemotherapy in 96 patients enrolled in a TNBC clinical trial. A correlative analysis between PTEN protein expression and PTEN CNV by NGS was also performed.

Results

With a stringent cutoff for PTEN IHC scoring, PTEN expression was discordant between pretreatment and posttreatment primary tumors in 5% of patients (n = 96) and between posttreatment primary tumors and lymph node metastases in 9% (n = 33). A less stringent cutoff yielded similar discordance rates. Intratumoral heterogeneity for PTEN loss was observed in 7% of the patients. Among pretreatment tumors, PTEN copy numbers by whole exome sequencing (n = 72) were significantly higher in the PTEN-positive tumors by IHC compared with the IHC PTEN-loss tumors (p < 0.0001). However, PTEN-positive and PTEN-loss tumors by IHC overlapped in copy numbers: 14 of 60 PTEN-positive samples showed decreased copy numbers in the range of those of the PTEN-loss tumors.

Conclusion

Testing various specimens by IHC may generate different PTEN results in a small proportion of patients with TNBC; therefore, the decision of testing one versus multiple specimens in a clinical trial should be defined in the patient inclusion criteria. Although a distinct cutoff by which CNV differentiated PTEN-positive tumors from those with PTEN loss was not identified, higher copy number of PTEN may confer positive PTEN, whereas lower copy number of PTEN would necessitate additional testing by IHC to assess PTEN loss.

Trial registration

NCT02276443.

Genomic analyses of germline and somatic variation in high-grade serous ovarian cancer

BACKGROUND

High-grade serous ovarian cancers (HGSCs) display a high degree of complex genetic alterations. In this study, we identified germline and somatic genetic alterations in HGSC and their association with relapse-free and overall survival. Using a targeted capture of 557 genes involved in DNA damage response and PI3K/AKT/mTOR pathways, we conducted next-generation sequencing of DNA from matched blood and tumor tissue from 71 HGSC participants. In addition, we performed the OncoScan assay on tumor DNA from 61 participants to examine somatic copy number alterations (SCNA).

RESULTS

Approximately one-third of tumors had loss-of-function (LOF) germline (18/71, 25.4%) or somatic (7/71, 9.9%) variants in the DNA homologous recombination repair pathway genes BRCA1, BRCA2, CHEK2, MRE11A, BLM, and PALB2. LOF germline variants also were identified in other Fanconi anemia genes and in MAPK and PI3K/AKT/mTOR pathway genes. Most tumors harbored somatic TP53 variants (65/71, 91.5%). Using the OncoScan assay on tumor DNA from 61 participants, we identified focal homozygous deletions in BRCA1, BRCA2, MAP2K4, PTEN, RB1, SLX4, STK11, CREBBP, and NF1. In total, 38% (27/71) of HGSC patients harbored pathogenic variants in DNA homologous recombination repair genes. For patients with multiple tissues from the primary debulking or from multiple surgeries, the somatic mutations were maintained with few newly acquired point mutations suggesting that tumor evolution was not through somatic mutations. There was a significant association of LOF variants in homologous recombination repair pathway genes and high-amplitude somatic copy number alterations. Using GISTIC analysis, we identified NOTCH3, ZNF536, and PIK3R2 in these regions that were significantly associated with an increase in cancer recurrence and a reduction in overall survival.

CONCLUSIONS

From 71 patients with HGCS, we performed targeted germline and tumor sequencing and provided a comprehensive analysis of these 557 genes. We identified germline and somatic genetic alterations including somatic copy number alterations and analyzed their associations with relapse-free and overall survival. This single-site long-term follow-up study provides additional information on genetic alterations related to occurrence and outcome of HGSC. Our findings suggest that targeted treatments based on both variant and SCNA profile potentially could improve relapse-free and overall survival.

Optimal First-Line Medico-Surgical Strategy in Ovarian Cancers: Are We There Yet?

In spite of tremendous advances in advanced ovarian cancer management through the past decade, notably owing to surgical expertise and novel combination molecules (including bevacizumab and PARP inhibitors), the optimal initial sequential strategy remains a major concern. Indeed, following seminal clinical trials, primary cytoreductive surgery (PCS) followed by adjuvant systemic therapy and interval cytoreductive surgery (ICS) following neoadjuvant chemotherapy (NACT) have been positioned as validated alternatives with distinct pros and cons, although a definite response is still unassessed. In clinical practice, decisions between PCS and ICS rely on multilayer parameters: the tumor itself, the patient, and the health structure. In this state-of-the-art review, we will discuss the current evidence based on clinical trials and real-world data and highlight the remaining questions, including the fittest positioning of PCS vs. ICS and the optimal number of NACT cycles; subsequently, we will discuss current axes of research such as dedicated clinical trials and more global perspectives. These ongoing strategies and perspectives could contribute to improving the patient journey through personalized medicine.

Genetic characterization of primary and metastatic high-grade serous ovarian cancer tumors reveals distinct features associated with survival

High-grade serous ovarian cancer (HGSC) is the most lethal histotype of ovarian cancer and the majority of cases present with metastasis and late-stage disease. Over the last few decades, the overall survival for patients has not significantly improved, and there are limited targeted treatment options. We aimed to better characterize the distinctions between primary and metastatic tumors based on short- or long-term survival. We characterized 39 matched primary and metastatic tumors by whole exome and RNA sequencing. Of these, 23 were short-term (ST) survivors (overall survival (OS) < 3.5 years) and 16 were long-term (LT) survivors (OS > 5 years). We compared somatic mutations, copy number alterations, mutational burden, differential gene expression, immune cell infiltration, and gene fusion predictions between the primary and metastatic tumors and between ST and LT survivor cohorts. There were few differences in RNA expression between paired primary and metastatic tumors, but significant differences between the transcriptomes of LT and ST survivors in both their primary and metastatic tumors. These findings will improve the understanding of the genetic variation in HGSC that exist between patients with different prognoses and better inform treatments by identifying new targets for drug development.

Spatial and temporal intra-tumoral heterogeneity in advanced HGSOC: Implications for surgical and clinical outcomes

Limited evidence exists on the impact of spatial and temporal heterogeneity of high-grade serous ovarian cancer (HGSOC) on tumor evolution, clinical outcomes, and surgical operability. We perform systematic multi-site tumor mapping at presentation and matched relapse from 49 high-tumor-burden patients, operated up front. From SNP array-derived copy-number data, we categorize dendrograms representing tumor clonal evolution as sympodial or dichotomous, noting most chemo-resistant patients favor simpler sympodial evolution. Three distinct tumor evolutionary patterns from primary to relapse are identified, demonstrating recurrent disease may emerge from pre-existing or newly detected clones. Crucially, we identify spatial heterogeneity for clinically actionable homologous recombination deficiency scores and for poor prognosis biomarkers CCNE1 and MYC. Copy-number signature, phenotypic, proteomic, and proliferative-index heterogeneity further highlight HGSOC complexity. This study explores HGSOC evolution and dissemination across space and time, its impact on optimal surgical cytoreductive effort and clinical outcomes, and its consequences for clinical decision-making.

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.

Targeting receptor tyrosine kinases in ovarian cancer: Genomic dysregulation, clinical evaluation of inhibitors, and potential for combinatorial therapies

Epithelial ovarian cancer (EOC) remains one of the leading causes of cancer-related deaths among women worldwide. Receptor tyrosine kinases (RTKs) have long been sought as therapeutic targets for EOC, as they are frequently hyperactivated in primary tumors and drive disease relapse, progression, and metastasis. More recently, these oncogenic drivers have been implicated in EOC response to poly(ADP-ribose) polymerase (PARP) inhibitors and epigenome-interfering agents. This evidence revives RTKs as promising targets for therapeutic intervention of EOC. This review summarizes recent studies on the role of RTKs in EOC malignancy and the use of their inhibitors for clinical treatment. Our focus is on the ERBB family, c-Met, and VEGFR, as they are linked to drug resistance and targetable using commercially available drugs. The importance of these RTKs and their inhibitors is highlighted by their impact on signal transduction and intratumoral heterogeneity in EOC and successful use as maintenance therapy in the clinic through suppression of the VEGF/VEGFR axis. Finally, the therapeutic potential of RTK inhibitors is discussed in the context of combinatorial targeting via co-inhibiting proliferative and anti-apoptotic pathways, epigenomic/transcriptional programs, and harnessing the efficacy of PARP inhibitors and programmed cell death 1/ligand 1 immune checkpoint therapies.

Resistance prediction in high-grade serous ovarian carcinoma with neoadjuvant chemotherapy using data-independent acquisition proteomics and an ovary-specific spectral library

High-grade serous ovarian carcinoma (HGSOC) is the most common subtype of ovarian cancer with 5-year survival rates below 40%. Neoadjuvant chemotherapy (NACT) followed by interval debulking surgery (IDS) is recommended for patients with advanced-stage HGSOC unsuitable for primary debulking surgery (PDS). However, about 40% of patients receiving this treatment exhibited chemoresistance of uncertain molecular mechanisms and predictability. Here, we built a high-quality ovary-specific spectral library containing 130 735 peptides and 10 696 proteins on Orbitrap instruments. Compared to a published DIA pan-human spectral library (DPHL), this spectral library provides 10% more ovary-specific and 3% more ovary-enriched proteins. This library was then applied to analyze data-independent acquisition (DIA) data of tissue samples from an HGSOC cohort treated with NACT, leading to 10 070 quantified proteins, which is 9.73% more than that with DPHL. We further established a six-protein classifier by parallel reaction monitoring (PRM) to effectively predict the resistance to additional chemotherapy after IDS (Log-rank test, P = 0.002). The classifier was validated with 57 patients from an independent clinical center (P = 0.014). Thus, we have developed an ovary-specific spectral library for targeted proteome analysis, and propose a six-protein classifier that could potentially predict chemoresistance in HGSOC patients after NACT-IDS treatment.

Genomic Analyses of Germline and Somatic Variation in High-Grade Serous Ovarian Cancer

Background High-grade serous ovarian cancers (HGSCs) display a high degree of complex genetic alterations. In this study, we identified germline and somatic genetic alterations in HGSC and their association with relapse-free and overall survival. Using a targeted capture of 577 genes involved in DNA damage response and PI3K/AKT/mTOR pathways, we conducted next-generation sequencing of DNA from matched blood and tumor tissue from 71 HGSC participants. In addition, we performed the OncoScan assay on tumor DNA from 61 participants to examine somatic copy number alterations. Results Approximately one-third of tumors had loss-of-function germline (18/71, 25.4%) or somatic (7/71, 9.9%) variants in the DNA homologous recombination repair pathway genes BRCA1, BRCA2, CHEK2, MRE11A, BLM , and PALB2 . Loss-of-function germline variants also were identified in other Fanconi anemia genes and in MAPK and PI3K/AKT/mTOR pathway genes. Most tumors harbored somatic TP53 variants (65/71, 91.5%). Using the OncoScan assay on tumor DNA from 61 participants, we identified focal homozygous deletions in BRCA1, BRCA2, MAP2K4, PTEN, RB1, SLX4, STK11, CREBBP , and NF1 . In total, 38% (27/71) of HGSC patients harbored pathogenic variants in DNA homologous recombination repair genes. For patients with multiple tissues from the primary debulking or from multiple surgeries, the somatic mutations were maintained with few newly acquired point mutations suggesting that tumor evolution was not through somatic mutations. There was a significant association of loss-of-function variants in homologous recombination repair pathway genes and high-amplitude somatic copy number alterations. Using GISTIC analysis, we identified NOTCH3, ZNF536 , and PIK3R2 in these regions that were significantly associated with an increase in cancer recurrence and a reduction in overall survival. Conclusions From 71 patients with HGCS, we performed targeted germline and tumor sequencing and provided a comprehensive analysis of these 577 genes. We identified germline and somatic genetic alterations including somatic copy number alterations and analyzed their associations with relapse-free and overall survival. This single-site long-term follow-up study provides additional information on genetic alterations related to occurrence and outcome of HGSC. Our findings suggest that targeted treatments based on both variant and SCNA profile potentially could improve relapse-free and overall survival.

Integrated multi-omic analysis of low-grade ovarian serous carcinoma collected from short and long-term survivors

BACKGROUND

Low-grade serous ovarian cancer (LGSOC) is a rare disease that occurs more frequently in younger women than those with high-grade disease. The current treatment is suboptimal and a better understanding of the molecular pathogenesis of this disease is required. In this study, we compared the proteogenomic analyses of LGSOCs from short- and long-term survivors (defined as < 40 and > 60 months, respectively). Our goal was to identify novel mutations, proteins, and mRNA transcripts that are dysregulated in LGSOC, particularly in short-term survivors.

METHODS

Initially, targeted sequencing of 409 cancer-related genes was performed on 22 LGSOC and 6 serous borderline ovarian tumor samples. Subsequently, whole-genome sequencing analysis was performed on 14 LGSOC samples (7 long-term survivors and 7 short-term survivors) with matched normal tissue samples. RNA sequencing (RNA-seq), quantitative proteomics, and phosphoproteomic analyses were also performed.

RESULTS

We identified single-nucleotide variants (SNVs) (range: 5688-14,833 per sample), insertion and deletion variants (indels) (range: 880-1065), and regions with copy number variants (CNVs) (range: 62-335) among the 14 LGSOC samples. Among all SNVs and indels, 2637 mutation sites were found in the exonic regions. The allele frequencies of the detected variants were low (median12%). The identified recurrent nonsynonymous missense mutations included KRAS, NRAS, EIF1AX, UBR5, and DNM3 mutations. Mutations in DNM3 and UBR5 have not previously been reported in LGSOC. For the two samples, somatic DNM3 nonsynonymous missense mutations in the exonic region were validated using Sanger sequencing. The third sample contained two missense mutations in the intronic region of DNM3, leading to a frameshift mutation detected in RNA transcripts in the RNA-seq data. Among the 14 LGSOC samples, 7754 proteins and 9733 phosphosites were detected by global proteomic analysis. Some of these proteins and signaling pathways, such as BST1, TBXAS1, MPEG1, HBA1, and phosphorylated ASAP1, are potential therapeutic targets.

CONCLUSIONS

This is the first study to use whole-genome sequencing to detect somatic mutations in LGSOCs with matched normal tissues. We detected and validated novel mutations in DNM3, which were present in 3 of the 14 samples analyzed. Additionally, we identified novel indels, regions with CNVs, dysregulated mRNA, dysregulated proteins, and phosphosites that are more prevalent in short-term survivors. This integrated proteogenomic analysis can guide research into the pathogenesis and treatment of LGSOC.

Biobehavioral factors predict an exosome biomarker of ovarian carcinoma disease progression

BACKGROUND

Biobehavioral factors such as social isolation and depression have been associated with disease progression in ovarian and other cancers. Here, the authors developed a noninvasive, exosomal RNA profile for predicting ovarian cancer disease progression and subsequently tested whether it increased in association with biobehavioral risk factors.

METHODS

Exosomes were isolated from plasma samples from 100 women taken before primary surgical resection or neoadjuvant (NACT) treatment of ovarian carcinoma and 6 and 12 months later. Biobehavioral measures were sampled at all time points. Plasma from 76 patients was allocated to discovery analyses in which morning presurgical/NACT exosomal RNA profiles were analyzed by elastic net machine learning to identify a biomarker predicting rapid (≤6 months) versus more extended disease-free intervals following initial treatment. Samples from a second subgroup of 24 patients were analyzed by mixed-effects linear models to determine whether the progression-predictive biomarker varied longitudinally as a function of biobehavioral risk factors (social isolation and depressive symptoms).

RESULTS

An RNA-based molecular signature was identified that discriminated between individuals who had disease progression in ≤6 months versus >6 months, independent of clinical variables (age, disease stage, and grade). In a second group of patients analyzed longitudinally, social isolation and depressive symptoms were associated with upregulated expression of the disease progression propensity biomarker, adjusting for covariates.

CONCLUSION

These data identified a novel exosome-derived biomarker indicating propensity of ovarian cancer progression that is sensitive to biobehavioral variables. This derived biomarker may be potentially useful for risk assessment, intervention targeting, and treatment monitoring.

Proteogenomic analysis of lung adenocarcinoma reveals tumor heterogeneity, survival determinants, and therapeutically relevant pathways

We present a deep proteogenomic profiling study of 87 lung adenocarcinoma (LUAD) tumors from the United States, integrating whole-genome sequencing, transcriptome sequencing, proteomics and phosphoproteomics by mass spectrometry, and reverse-phase protein arrays. We identify three subtypes from somatic genome signature analysis, including a transition-high subtype enriched with never smokers, a transversion-high subtype enriched with current smokers, and a structurally altered subtype enriched with former smokers, TP53 alterations, and genome-wide structural alterations. We show that within-tumor correlations of RNA and protein expression associate with tumor purity and immune cell profiles. We detect and independently validate expression signatures of RNA and protein that predict patient survival. Additionally, among co-measured genes, we found that protein expression is more often associated with patient survival than RNA. Finally, integrative analysis characterizes three expression subtypes with divergent mutations, proteomic regulatory networks, and therapeutic vulnerabilities. This proteogenomic characterization provides a foundation for molecularly informed medicine in LUAD.

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.

Classification of High-Grade Serous Ovarian Cancer Using Tumor Morphologic Characteristics

IMPORTANCE

Despite similar histologic appearance among high-grade serous ovarian cancers (HGSOCs), clinical observations suggest vast differences in gross appearance. There is currently no systematic framework by which to classify HGSOCs according to their gross morphologic characteristics.

OBJECTIVE

To develop and characterize a gross morphologic classification system for HGSOC.

DESIGN, SETTING, AND PARTICIPANTS

This cohort study included patients with suspected advanced-stage ovarian cancer who presented between April 1, 2013, and August 5, 2016, to the University of Texas MD Anderson Cancer Center, a large referral center. Patients underwent laparoscopic assessment of disease burden before treatment and received a histopathologic diagnosis of HGSOC. Researchers assigning morphologic subtype and performing molecular analyses were blinded to clinical outcomes. Data analysis was performed between April 2020 and November 2021.

EXPOSURES

Gross tumor morphologic characteristics.

MAIN OUTCOMES AND MEASURES

Clinical outcomes and multiomic profiles of representative tumor samples of type I or type II morphologic subtypes were compared.

RESULTS

Of 112 women (mean [SD] age 62.7 [9.7] years) included in the study, most patients (84% [94]) exhibited a predominant morphologic subtype and many (63% [71]) had a uniform morphologic subtype at all involved sites. Compared with those with uniform type I morphologic subtype, patients with uniform type II morphologic subtype were more likely to have a favorable Fagotti score (83% [19 of 23] vs 46% [22 of 48]; P = .004) and thus to be triaged to primary tumor reductive surgery. Similarly, patients with uniform type II morphologic subtype also had significantly higher mean (SD) estimated blood loss (639 [559; 95% CI, 391-887] mL vs 415 [527; 95% CI, 253-577] mL; P = .006) and longer mean (SD) operative time (408 [130; 95% CI, 350-466] minutes vs 333 [113; 95% CI, 298-367] minutes; P = .03) during tumor reductive surgery. Type I tumors had enrichment of epithelial-mesenchymal transition (false discovery rate [FDR] q-value, 3.10 × 10-24), hypoxia (FDR q-value, 1.52 × 10-5), and angiogenesis pathways (FDR q-value, 2.11 × 10-2), whereas type II tumors had enrichment of pathways related to MYC signaling (FDR q-value, 2.04 × 10-9) and cell cycle progression (FDR q-value, 1.10 × 10-5) by integrated proteomic and transcriptomic analysis. Abundances of metabolites and lipids also differed between the 2 morphologic subtypes.

CONCLUSIONS AND RELEVANCE

This study identified 2 novel, gross morphologic subtypes of HGSOC, each with unique clinical features and molecular signatures. The findings may have implications for triaging patients to surgery or chemotherapy, identifying outcomes, and developing tailored therapeutic strategies.

Identification and validation of a gene-based signature reveals SLC25A10 as a novel prognostic indicator for patients with ovarian cancer

Background

Ovarian cancer is a common gynecological cancer with poor prognosis and poses a serious threat to woman life and health. In this study, we aimed to establish a prognostic signature for the risk assessment of ovarian cancer.

Methods

The Cancer Genome Atlas (TCGA) dataset was used as the training set and the International Cancer Genome Consortium (ICGC) dataset was set as an independent external validation. A multi-stage screening strategy was used to determine the prognostic features of ovarian cancer with R software. The relationship between the prognosis of ovarian cancer and the expression level of SLC25A10 was selected for further analysis.

Results

A total of 16 prognosis-associated genes were screened to construct the risk score signature. Survival analysis showed that patients in the high-risk score group had a poor prognosis compared to the low-risk group. Accuracy of this prognostic signature was confirmed by the receiver operating characteristic (ROC) curve and decision curve analysis (DCA), and validated with ICGC cohort. This signature was identified as an independent factor for predicting overall survival (OS). Nomogram constructed by multiple clinical parameters showed excellent performance for OS prediction. Finally, it’s found that patients with low expression of SLC25A10 generally had poor survival and higher resistance to most chemotherapeutic drugs.

Conclusions

In sum, we developed a 16-gene prognostic signature, which could serve as a promising tool for the prognostic prediction of ovarian cancer, and the expression level of SLC25A10 was tightly associated with OS of the patients.

High-throughput proteomic sample preparation using pressure cycling technology

High-throughput lysis and proteolytic digestion of biopsy-level tissue specimens is a major bottleneck for clinical proteomics. Here we describe a detailed protocol of pressure cycling technology (PCT)-assisted sample preparation for proteomic analysis of biopsy tissues. A piece of fresh frozen or formalin-fixed paraffin-embedded tissue weighing ~0.1–2 mg is placed in a 150 μL pressure-resistant tube called a PCT-MicroTube with proper lysis buffer. After closing with a PCT-MicroPestle, a batch of 16 PCT-MicroTubes are placed in a Barocycler, which imposes oscillating pressure to the samples from one atmosphere to up to ~3,000 times atmospheric pressure. The pressure cycling schemes are optimized for tissue lysis and protein digestion, and can be programmed in the Barocycler to allow reproducible, robust and efficient protein extraction and proteolysis digestion for mass spectrometry-based proteomics. This method allows effective preparation of not only fresh frozen and formalin-fixed paraffin-embedded tissue, but also cells, feces and tear strips. It takes ~3 h to process 16 samples in one batch. The resulting peptides can be analyzed by various mass spectrometry-based proteomics methods. We demonstrate the applications of this protocol with mouse kidney tissue and eight types of human tumors.

High-throughput lysis and proteolytic digestion of biopsy-level tissue specimens is a major bottleneck for clinical proteomics. This protocol describes pressure cycling technology (PCT)-assisted sample preparation of biopsy tissues.

Molecular Profiles of Serum-Derived Extracellular Vesicles in High-Grade Serous Ovarian Cancer

Patients with high-grade serous ovarian cancer (HGSC) who have no visible residual disease (R0) after primary surgery have the best clinical outcomes, followed by patients who undergo neoadjuvant chemotherapy (NACT) and have a response enabling interval cytoreductive surgery. Clinically useful biomarkers for predicting these outcomes are still lacking. Extracellular vesicles (EVs) have been recognized as liquid biopsy-based biomarkers for early cancer detection and disease surveillance in other disease settings. In this study, we performed extensive molecular characterization of serum-derived EVs and correlated the findings with therapeutic outcomes in patients with HGSC. Using EV-DNA whole-genome sequencing and EV-RNA sequencing, we identified distinct somatic EV-DNA alterations in cancer-hallmark genes and in ovarian cancer genes, as well as significantly altered oncogenic pathways between the R0 group and NACT groups. We also found significantly altered EV-RNA transcriptomic variations and enriched pathways between the groups. Taken together, our data suggest that the molecular characteristics of EVs could enable prediction of patients with HGSC who could undergo R0 surgery or respond to chemotherapy.

Somatic genomic landscape of East Asian epithelial ovarian carcinoma and its clinical implications from prospective clinical sequencing; A Korean Gynecologic Oncology Group study (KGOG 3047)

Through the wide adaptation of next-generation sequencing (NGS) technology within clinical practice, molecular profiling of the tumor has been the principal component of personalized treatment. In this study, we have generated a large collection of cancer genomes on East Asian epithelial ovarian carcinoma (EOC) patients and demonstrate the feasibility and utility of NGS platforms to explore the dynamic interrelations of major cancer driver alterations and their impacts on clinical prognosis and management. A total of 652 EOC patients have undergone clinical NGS panels to determine the prevalence of germline and somatic mutations. Notably, TP53 was the most frequently altered event (73%), followed by both BRCA1 and BRCA2 (22% each) and MYC (19%) through pan-EOC analysis. When analyzed based on individual histopathological levels, TP53 mutation was highly dominant in high-grade serous and mucinous histology, whereas mutations in PIK3CA and ARID1A were mostly observed in clear cell carcinoma, and KRAS, BRAF, and CDKN2A mutations were enriched in endometrioid, low-grade serous, and mucinous tumors, respectively. The network-based probabilistic model showed significant co-occurrences of TP53 with BRCA1 and ALK with BRCA2, NOTCH1, and ROS1, whereas mutual exclusivity of TP53 with KRAS and PIK3CA was evident. Furthermore, we utilized machine-learning algorithms to identify molecular correlates that conferred increased sensitivity to platinum and olaparib treatments including somatic mutations in BRCA1, ATM, and MYC. Conversely, patients with ALK mutation were considerably resistant to both treatment modalities. Collectively, our results demonstrate the clinical feasibility of prospective genetic sequencing to facilitate personalized treatment opportunities for patients with EOC.

Genomic and Single-Cell Landscape Reveals Novel Drivers and Therapeutic Vulnerabilities of Transformed Cutaneous T-cell Lymphoma

ABSTRACT

Cutaneous T-cell lymphoma (CTCL) is a rare cancer of skin-homing T cells. A subgroup of patients develops large cell transformation with rapid progression to an aggressive lymphoma. Here, we investigated the transformed CTCL (tCTCL) tumor ecosystem using integrative multiomics spanning whole-exome sequencing (WES), single-cell RNA sequencing, and immune profiling in a unique cohort of 56 patients. WES of 70 skin biopsies showed high tumor mutation burden, UV signatures that are prognostic for survival, exome-based driver events, and most recurrently mutated pathways in tCTCL. Single-cell profiling of 16 tCTCL skin biopsies identified a core oncogenic program with metabolic reprogramming toward oxidative phosphorylation (OXPHOS), cellular plasticity, upregulation of MYC and E2F activities, and downregulation of MHC I suggestive of immune escape. Pharmacologic perturbation using OXPHOS and MYC inhibitors demonstrated potent antitumor activities, whereas immune profiling provided in situ evidence of intercellular communications between malignant T cells expressing macrophage migration inhibitory factor and macrophages and B cells expressing CD74.

SIGNIFICANCE

Our study contributes a key resource to the community with the largest collection of tCTCL biopsies that are difficult to obtain. The multiomics data herein provide the first comprehensive compendium of genomic alterations in tCTCL and identify potential prognostic signatures and novel therapeutic targets for an incurable T-cell lymphoma. This article is highlighted in the In This Issue feature, p. 1171.

Multi-omics approaches for biomarker discovery in early ovarian cancer diagnosis

Ovarian cancer (OC) is a heterogeneous disease with the highest mortality rate and the poorest prognosis among gynecological malignancies. Because of the absence of specific early symptoms, most OC patients are often diagnosed at late stages. Thus, improved biomarkers of OC for use in research and clinical practice are urgently needed. The last decade has seen increasingly rapid advances in sequencing and biotechnological methodologies. Consequently, multiple omics technologies, including genomic/transcriptomic sequencings and proteomic/metabolomic mass spectra, have been widely applied to analyze tissue- and liquid-derived samples from OC patients. The integration of multi-omics data has increased our knowledge of the disease and identified valuable OC biomarkers. In this review, we summarize the recent advances and perspectives in the use of multi-omics technologies in OC research and highlight potential applications of multi-omics for identifying novel biomarkers and improving clinical assessments.

The Long Non-Coding RNA SNHG12 as a Mediator of Carboplatin Resistance in Ovarian Cancer via Epigenetic Mechanisms

Simple Summary

Epithelial ovarian cancer is a lethal malignancy in which recurrence and therapy resistance are the major causes of death. We investigated the transcriptome and DNA methylation profile of ovarian cancer cell lines sensitive and resistant to carboplatin, aiming to identify genes associated with therapy resistance. We focused on long non-coding RNAs (lncRNAs), known as epigenetic regulators of several cellular and biological processes. We found 11 lncRNAs associated with carboplatin resistance, including SNHG12 (small nucleolar RNA host gene 12), also confirmed in an external dataset (The Cancer Genome Atlas). SNHG12 gene silencing increased the sensitivity to carboplatin, giving evidence that this lncRNA contributes to resistance to carboplatin in ovarian cancer cell lines. We also demonstrated that SNHG12 could control the expression of nearby genes probably by altering epigenetic markers and modifying the transcript levels.

Abstract

Genetic and epigenetic changes contribute to intratumor heterogeneity and chemotherapy resistance in several tumor types. LncRNAs have been implicated, directly or indirectly, in the epigenetic regulation of gene expression. We investigated lncRNAs that potentially mediate carboplatin-resistance of cell subpopulations, influencing the progression of ovarian cancer (OC). Four carboplatin-sensitive OC cell lines (IGROV1, OVCAR3, OVCAR4, and OVCAR5), their derivative resistant cells, and two inherently carboplatin-resistant cell lines (OVCAR8 and Ovc316) were subjected to RNA sequencing and global DNA methylation analysis. Integrative and cross-validation analyses were performed using external (The Cancer Genome Atlas, TCGA dataset, n = 111 OC samples) and internal datasets (n = 39 OC samples) to identify lncRNA candidates. A total of 4255 differentially expressed genes (DEGs) and 14529 differentially methylated CpG positions (DMPs) were identified comparing sensitive and resistant OC cell lines. The comparison of DEGs between OC cell lines and TCGA-OC dataset revealed 570 genes, including 50 lncRNAs, associated with carboplatin resistance. Eleven lncRNAs showed DMPs, including the SNHG12. Knockdown of SNHG12 in Ovc316 and OVCAR8 cells increased their sensitivity to carboplatin. The results suggest that the lncRNA SNHG12 contributes to carboplatin resistance in OC and is a potential therapeutic target. We demonstrated that SNHG12 is functionally related to epigenetic mechanisms.

Spatially resolved transcriptomics of high-grade serous ovarian carcinoma

Bulk and single-cell RNA sequencing do not provide full characterization of tissue spatial diversity in cancer samples, and currently available in situ techniques (multiplex immunohistochemistry and imaging mass cytometry) allow for only limited analysis of a small number of targets. The current study represents the first comprehensive approach to spatial transcriptomics of high-grade serous ovarian carcinoma using intact tumor tissue. We selected a small cohort of patients with highly annotated high-grade serous ovarian carcinoma, categorized them by response to neoadjuvant chemotherapy (poor or excellent), and analyzed pre-treatment tumor tissue specimens. Our study uncovered extensive differences in tumor composition between the poor responders and excellent responders to chemotherapy, related to cell cluster organization and localization. This in-depth characterization of high-grade serous ovarian carcinoma tumor tissue from poor and excellent responders showed that spatial interactions between cell clusters may influence chemo-responsiveness more than cluster composition alone.

Molecular Correlates of Venous Thromboembolism (VTE) in Ovarian Cancer

BACKGROUND

The incidence of venous thromboembolism (VTE) in patients with ovarian cancer is higher than most solid tumors, ranging between 10-30%, and a diagnosis of VTE in this patient population is associated with worse oncologic outcomes. The tumor-specific molecular factors that may lead to the development of VTE are not well understood.

OBJECTIVES

The aim of this study was to identify molecular features present in ovarian tumors of patients with VTE compared to those without.

METHODS

We performed a multiplatform omics analysis incorporating RNA and DNA sequencing, quantitative proteomics, as well as immune cell profiling of high-grade serous ovarian carcinoma (HGSC) samples from a cohort of 32 patients with or without VTE.

RESULTS

Pathway analyses revealed upregulation of both inflammatory and coagulation pathways in the VTE group. While DNA whole-exome sequencing failed to identify significant coding alterations between the groups, the results of an integrated proteomic and RNA sequencing analysis indicated that there is a relationship between VTE and the expression of platelet-derived growth factor subunit B (PDGFB) and extracellular proteins in tumor cells, namely collagens, that are correlated with the formation of thrombosis.

CONCLUSIONS

In this comprehensive analysis of HGSC tumor tissues from patients with and without VTE, we identified markers unique to the VTE group that could contribute to development of thrombosis. Our findings provide additional insights into the molecular alterations underlying the development of VTE in ovarian cancer patients and invite further investigation into potential predictive biomarkers of VTE in ovarian cancer.

Toward More Comprehensive Homologous Recombination Deficiency Assays in Ovarian Cancer, Part 1: Technical Considerations

Simple Summary

High-grade serous ovarian cancer (HGSOC) is the most frequent and lethal form of ovarian cancer and is associated with homologous recombination deficiency (HRD) in 50% of cases. This specific alteration is associated with sensitivity to PARP inhibitors (PARPis). Despite vast prognostic improvements due to PARPis, current molecular assays assessing HRD status suffer from several limitations, and there is an urgent need for a more accurate evaluation. In these companion reviews (Part 1: Technical considerations; Part 2: Medical perspectives), we develop an integrative review to provide physicians and researchers involved in HGSOC management with a holistic perspective, from translational research to clinical applications.

Abstract

High-grade serous ovarian cancer (HGSOC), the most frequent and lethal form of ovarian cancer, exhibits homologous recombination deficiency (HRD) in 50% of cases. In addition to mutations in BRCA1 and BRCA2, which are the best known thus far, defects can also be caused by diverse alterations to homologous recombination-related genes or epigenetic patterns. HRD leads to genomic instability (genomic scars) and is associated with PARP inhibitor (PARPi) sensitivity. HRD is currently assessed through BRCA1/2 analysis, which produces a genomic instability score (GIS). However, despite substantial clinical achievements, FDA-approved companion diagnostics (CDx) based on GISs have important limitations. Indeed, despite the use of GIS in clinical practice, the relevance of such assays remains controversial. Although international guidelines include companion diagnostics as part of HGSOC frontline management, they also underscore the need for more powerful and alternative approaches for assessing patient eligibility to PARP inhibitors. In these companion reviews, we review and present evidence to date regarding HRD definitions, achievements and limitations in HGSOC. Part 1 is dedicated to technical considerations and proposed perspectives that could lead to a more comprehensive and dynamic assessment of HR, while Part 2 provides a more integrated approach for clinicians.

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.

Next-Generation Sequencing Reveals a Very Low Prevalence of Deleterious Mutations of Homologous Recombination Repair Genes and Homologous Recombination Deficiency in Ovarian Clear Cell Carcinoma

Ovarian clear cell carcinoma (OCCC) is aggressive and drug-resistant. The prevalence of homologous recombination repair (HRR) gene mutations and homologous recombination deficiency (HRD) remains largely unknown. It is also not clear whether the commonly used molecular-based classification for endometrial carcinoma (EC) is potentially applicable in OCCC. In this study, surgically resected samples were collected from 44 patients with OCCC. Genomic alterations were determined using next-generation sequencing. HRD was estimated by genomic instability. Of 44 patients with OCCC, two (4.5%) harbored likely pathogenic mutations in HRR genes. Notably, no pathogenic or likely pathogenic mutations were found in BRCA1/2. A total of 24 variants of uncertain significance (VUS) in HRR-related genes occurred in 18 (40.9%) patients. HRD was observed in only one case (2.3%). In addition, TP53 mutation and microsatellite instability-high (MSI-H) were identified in three patients (6.8%) and in one patient (2.3%), respectively. TP53 mutation was significantly associated with disease-free survival and overall survival. No POLE mutations were found. In conclusion, our results revealed a very low prevalence of HRR gene mutations and HRD in OCCC. Moreover, TP53 mutations and MSI-H are uncommon, while POLE mutations are extremely rare in OCCC. Our findings indicate that the evaluation of HRR gene mutations, HRD status, POLE mutations, and MSI-H may have limited clinical significance for OCCC treatment and prognostic stratification.

Peptide ancestry informative markers in uterine neoplasms from women of European, African, and Asian ancestry

Characterization of ancestry-linked peptide variants in disease-relevant patient tissues represents a foundational step to connect patient ancestry with disease pathogenesis. Nonsynonymous single-nucleotide polymorphisms encoding missense substitutions within tryptic peptides exhibiting high allele frequencies in European, African, and East Asian populations, termed peptide ancestry informative markers (pAIMs), were prioritized from 1000 genomes. In silico analysis identified that as few as 20 pAIMs can determine ancestry proportions similarly to >260K SNPs (R² = 0.99). Multiplexed proteomic analysis of >100 human endometrial cancer cell lines and uterine leiomyoma tissues combined resulted in the quantitation of 62 pAIMs that correlate with patient race and genotype-confirmed ancestry. Candidates include a D451E substitution in GC vitamin D-binding protein previously associated with altered vitamin D levels in African and European populations. pAIMs will support generalized proteoancestry assessment as well as efforts investigating the impact of ancestry on the human proteome and how this relates to the pathogenesis of uterine neoplasms.

Somatic Mutational Profile of High-Grade Serous Ovarian Carcinoma and Triple-Negative Breast Carcinoma in Young and Elderly Patients: Similarities and Divergences

Background: Triple-negative breast cancer (TNBC) and High-Grade Serous Ovarian Cancer (HGSOC) are aggressive malignancies that share similarities; however, different ages of onset may reflect distinct tumor behaviors. Thus, our aim was to compare somatic mutations in potential driver genes in 109 TNBC and 81 HGSOC from young (Y ≤ 40 years) and elderly (E ≥ 75 years) patients. Methods: Open access mutational data (WGS or WES) were collected for TNBC and HGSOC patients. Potential driver genes were those that were present in the Cancer Gene Census—CGC, the Candidate Cancer Gene Database—CCGD, or OncoKB and those that were considered pathogenic in variant effect prediction tools. Results: Mutational signature 3 (homologous repair defects) was the only gene that was represented in all four subgroups. The median number of mutated CGCs per sample was similar in HGSOC (Y:3 vs. E:4), but it was higher in elderly TNBC than it was in young TNBC (Y:3 vs. E:6). At least 90% of the samples from TNBC and HGSOC from Y and E patients presented at least one known affected TSG. Besides TP53, which was mutated in 67–83% of the samples, the affected TSG in TP53 wild-type samples were NF1 (yHGSOC and yTNBC), PHF6 (eHGSOC and yTNBC), PTEN, PIK3R1 and ZHFX3 (yTNBC), KMT2C, ARID1B, TBX3, and ATM (eTNBC). A few samples only presented one affected oncogene (but no TSG): KRAS and TSHR in eHGSOC and RAC1 and PREX2 (a regulator of RAC1) in yTNBC. At least ⅔ of the tumors presented mutated oncogenes associated with tumor suppressor genes; the Ras and/or PIK3CA signaling pathways were altered in 15% HGSOC and 20–35% TNBC (Y vs. E); DNA repair genes were mutated in 19–33% of the HGSOC tumors but were more frequently mutated in E-TNBC (56%). However, in HGSOC, 9.5% and 3.3% of the young and elderly patients, respectively, did not present any tumors with an affected CGC nor did 4.65% and none of the young and elderly TNBC patients. Conclusion: Most HGSOC and TNBC from young and elderly patients present an affected TSG, mainly TP53, as well as mutational signature 3; however, a few tumors only present an affected oncogene or no affected cancer-causing genes.

Dynamically Accumulating Homologous Recombination Deficiency Score Served as an Important Prognosis Factor in High-Grade Serous Ovarian Cancer

Background: The homologous recombination (HR) pathway defects in cancers induced abrogation of cell cycle checkpoints, resulting in the accumulation of DNA damage, mitotic catastrophe, and cell death. Cancers with BRCA1/2 loss and other accumulation of similar genomic scars resulting in HRD displayed increased sensitivity to chemotherapy. Our study aimed to explore HRD score genetic mechanisms and subsequent clinical outcomes in human cancers, especially ovarian cancer.

Methods: We analyzed TCGA data of HRD score in 33 cancer types and evaluated HRD score distribution and difference among tumor stages and between primary and recurrent tumor tissues. A weighted gene co-expression network analysis (WGCNA) was performed to identify highly correlated genes representing essential modules contributing to the HRD score and distinguish the hub genes and significant pathways. We verified HRD status predicting roles in patients’ overall survival (OS) with univariate and multivariate Cox regression analyses and built the predicting model for patient survival.

Results: We found that the HRD score increased with the rise in tumor stage, except for stage IV. The HRD score tended to grow up higher in recurrent tumor tissue than in their primary counterparts (p = 0.083). We constructed 15 co-expression modules with WGCNA, identified co-expressed genes and pathways impacting the HRD score, and concluded that the HRD score was tightly associated with tumor cells replication and proliferation. A combined HRD score ≥42 was associated with shorter OS in 33 cancer types (HR = 1.010, 95% CI: 1.008–1.011, p < 0.001). However, in ovarian cancer, which ranked the highest HRD score among other cancers, HRD ≥42 cohort was significantly associated with longer OS (HR = 0.99, 95% CI: 0.98–0.99, p < 0.0001). We also built a predicting model for 3 and 5 years survival in HGSC patients.

Conclusion: A quantitative HRD score representing the accumulated genomic scars was dynamically increasing in proliferating tumor cells since the HRD score was tightly correlated to tumor cell division and replication. We highlighted HRD score biomarker role in prognosis prediction of ovarian cancer.

Construction of a microenvironment immune gene model for predicting the prognosis of endometrial cancer

Background

Infiltrating immune and stromal cells are important components of the endometrial cancer (EC) microenvironment, which has a significant effect on the biological behavior of EC, suggesting that unique immune-related genes may be associated with the prognosis of EC. However, the association of immune-related genes with the prognosis of EC has not been elucidated. We attempted to identify immune-related genes with potentially prognostic value in EC using The Cancer Genome Atlas database and the relationship between immune microenvironment and EC.

Methods

We analyzed 578 EC samples from TCGA database and used weighted gene co-expression network analysis to screen out immune-related genes. We constructed a protein–protein interaction network and analyzed it using STRING and Cytoscape. Immune-related genes were analyzed through conjoint Cox regression and random forest algorithm analysis were to identify a multi-gene prediction model and stratify low-risk and high-risk groups of EC patients. Based on these data, we constructed a nomogram prediction model to improve prognosis assessment. Evaluation of Immunological, gene mutations and gene enrichment analysis were applied on these groups to quantify additional differences.

Results

Using conjoint Cox regression and random forest algorithm, we found that TRBC2, TRAC, LPXN, and ARHGAP30 were associated with the prognosis of EC and constructed four gene risk models for overall survival and a consistent nomogram. The time-dependent receiver operating characteristic curve analysis revealed that the area under the curve for 1-, 3-, and 5-y overall survival was 0.687, 0.699, and 0.76, respectively. These results were validated using a validation cohort. Immune-related pathways were mostly enriched in the low-risk group, which had higher levels of immune infiltration and immune status.

Conclusion

Our study provides new insights for novel biomarkers and immunotherapy targets in EC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08935-w.

Neoadjuvant chemotherapy induces genomic and transcriptomic changes in ovarian cancer

The growing use of neoadjuvant chemotherapy to treat advanced-stage high-grade serous ovarian cancer (HGSOC) creates an opportunity to better understand chemotherapy-induced mutational and gene expression changes. Here we performed a cohort study including 34 patients with advanced stage IIIC or IV HGSOC to assess changes in the tumor genome and transcriptome in women receiving neoadjuvant chemotherapy. RNA-sequencing and panel DNA-sequencing of 596 cancer-related genes was performed on paired FFPE specimens collected before and after chemotherapy, and differentially expressed genes (DEGs) and CNVs in pre- and post-chemotherapy samples were identified. Following tissue and sequencing quality control, the final patient cohort consisted of 32 paired DNA and 20 paired RNA samples. Genomic analysis of paired samples did not reveal any recurrent chemotherapy-induced mutations. Gene expression analyses found that most DEGs were upregulated by chemotherapy, primarily in the chemotherapy resistant specimens. AP-1 transcription factor family genes (FOS, FOSB, FRA-1) were particularly upregulated in chemotherapy resistant samples. CNV analysis identified recurrent 11q23.1 amplification, which encompasses SIK2. In vitro, combined treatment with AP-1 or SIK2 inhibitors with carboplatin or paclitaxel demonstrated synergistic effects. These data suggest that AP-1 activity and SIK2 copy number amplification are induced by chemotherapy and may represent mechanisms by which chemotherapy resistance evolves in HGSOC. AP-1 and SIK2 are druggable targets with available small molecule inhibitors and represent potential targets to circumvent chemotherapy resistance.

Dysfunctional activity of classical DNA end-joining renders acquired resistance to carboplatin in human ovarian cancer cells

Ovarian cancer is the deadliest gynecological malignancy worldwide. Although chemotherapy is required as the most standard treatment strategy for ovarian cancer, the survival rates are very low, largely because of high incidence of recurrence due to resistance to conventional surgery and genotoxic chemotherapies. Carboplatin-resistant ovarian cancer cells were generated by continuous treatment over six months. Carboplatin-resistance induced morphological alterations and promoted the rates of proliferation and migration of SKOV3 compared to the parental cells. Interestingly, carboplatin-resistant SKOV3 showed the high levels of γH2AX foci formed at the basal level, and the levels of γH2AX foci remained even after the recovery time, suggesting that the DNA damage response and repair machinery were severely attenuated by carboplatin-resistance. Surprisingly, the expression levels of XRCC4, a critical factor in non-homologous end joining (NHEJ) DNA repair, were significantly decreased in carboplatin-resistant SKOV3 compared with those in non-resistant controls. Furthermore, restoration of NHEJ in carboplatin-resistant SKOV3 by suppression of ABCB1 and/or AR re-sensitized carboplatin-resistant cells to genotoxic stress and reduced their proliferation ability. Our findings suggest that attenuation of the NHEJ DNA repair machinery mediated by resistance to genotoxic stress might be a critical cause of chemoresistance in patients with ovarian cancer.

Image-Based Identification and Genomic Analysis of Single Circulating Tumor Cells in High Grade Serous Ovarian Cancer Patients

Simple Summary

Ovarian Cancer (OC) is one of the leading causes of death among gynecological tumors and there is still an insufficient understanding of its evolution. Blood, as a minimal invasive tool, allows multiple sampling over the treatment course and genomic single circulating tumor cell (sCTC) data provide the opportunity to investigate the genetic tumor evolution. CTC detection in OC remains difficult, due to epithelial-mesenchymal transition (EMT). This proof of principle study presents a workflow to generate sCTC genomic data, with the need of further studies to improve the CTC detection rate and enable insights into tumor evolution on a sCTC resolution to identify new treatment targets and/or biomarkers for an early treatment intervention.

Abstract

In Ovarian Cancer (OC), the analysis of single circulating tumor cells (sCTCs) might help to investigate genetic tumor evolution during the course of treatment. Since common CTC identification features failed to reliably detect CTCs in OC, we here present a workflow for their detection and genomic analysis. Blood of 13 high-grade serous primary OC patients was analyzed, using negative immunomagnetic enrichment, followed by immunofluorescence staining and imaging for Hoechst, ERCC1, CD45, CD11b and cytokeratin (CK) and sCTC sorting with the DEPArray^TM NxT. The whole genome of single cells was amplified and profiled for copy number variation (CNV). We detected: Type A-cells, epithelial (Hoechst^pos, ERCC1^pos, CD45^neg, CD11b^pos, CK^pos); Type B-cells, potentially epithelial (Hoechst^pos, ERCC1^pos, CD45^neg, CD11b^pos, CK^neg) and Type C-cells, potentially mesenchymal (Hoechst^pos, ERCC1^pos, CD45^neg, CD11b^neg, CK^neg). In total, we identified five (38.5%) patients harboring sCTCs with an altered CN profile, which were mainly Type A-cells (80%). In addition to inter-and intra-patient genomic heterogeneity, high numbers of Type B- and C-cells were identified in every patient with their aberrant character only confirmed in 6.25% and 4.76% of cases. Further identification markers and studies in the course of treatment are under way to expand sCTC analysis for the identification of tumor evolution in OC.

Extensive three-dimensional intratumor proteomic heterogeneity revealed by multiregion sampling in high-grade serous ovarian tumor specimens

Enriched tumor epithelium, tumor-associated stroma, and whole tissue were collected by laser microdissection from thin sections across spatially separated levels of ten high-grade serous ovarian carcinomas (HGSOCs) and analyzed by mass spectrometry, reverse phase protein arrays, and RNA sequencing. Unsupervised analyses of protein abundance data revealed independent clustering of an enriched stroma and enriched tumor epithelium, with whole tumor tissue clustering driven by overall tumor "purity." Comparing these data to previously defined prognostic HGSOC molecular subtypes revealed protein and transcript expression from tumor epithelium correlated with the differentiated subtype, whereas stromal proteins (and transcripts) correlated with the mesenchymal subtype. Protein and transcript abundance in the tumor epithelium and stroma exhibited decreased correlation in samples collected just hundreds of microns apart. These data reveal substantial tumor microenvironment protein heterogeneity that directly bears on prognostic signatures, biomarker discovery, and cancer pathophysiology and underscore the need to enrich cellular subpopulations for expression profiling.

Association of somatic mutations in BRCA2 BRC domain with chemotherapy sensitivity and survival in high grade serous ovarian cancer

BACKGROUND

Mutations at sites crucial for the interaction between RAD51 and BRC domains impair the ability of BRCA2 homologous recombination. We aimed to clarify whether BRCA2 BRC domain-associated mutation correlates with sensibility of platinum-based chemotherapy and survival in high-grade serous ovarian cancer (HGSOC).

METHODS

We identified BRCA2 BRC domain mutations by sequencing PCR-amplified amplicons of genomic DNA isolated from tumor tissues and peripheral blood leukocytes (PBL)in 113 patients with advanced EOC, and assessed platinum-free interval (PFI), progression-free survival (PFS) and overall survival (OS).

RESULTS

21.23% (24 of 113) cases with somatic missense mutation but not germline mutation were identified. Among 24 cases with mutation, 33.3% (8 of 24) cases with nonsense mutation (C-terminal truncation) significantly prolonged median PFI (37 vs 8 months,P = 0.000), PFS (43 vs 14 months, p = 0.000) and OS (56 vs 31 months, P = 0.002); 66.7% (16 of 24) cases with missense mutation also prolonged median PFI (15 vs 8 months, P = 0.044), PFS (21 vs 14 months, P = 0.049) and OS (38 vs 31 months, P = 0.037), compared to those without any mutation.

CONCLUSIONS

Somatic mutations in BRCA2 BRC domain confer a higher sensitivity to platinum-based therapy and are associated with a favourable survival in HGSOC.

Factors associated with response to neoadjuvant chemotherapy in advanced stage ovarian cancer

OBJECTIVES

To evaluate the factors associated with response to neoadjuvant chemotherapy (NACT) and the ability to undergo interval tumor reductive surgery (iTRS) in patients with advanced ovarian cancer.

METHODS

We performed a retrospective review from April 2013 to March 2019 of patients with advanced stage ovarian cancer triaged to NACT based on our standard triage algorithm. Clinicopathologic and treatment data were analyzed for factors associated with response to NACT, outcomes at iTRS, and their impact on progression-free survival (PFS).

RESULTS

562 patients met inclusion criteria and triaged to NACT following laparoscopy (n = 132) or without laparoscopy (n = 430). 413 patients underwent iTRS (74%). Factors that correlated with a patient reaching iTRS included increasing age (p < 0.001), higher Charlson comorbidity index (p < 0.001), ECOG status 2 or 3 (<0.001), and laparoscopic assessment (<0.001). Patients with CA-125 ≤ 35 U/mL at iTRS had higher rates of complete gross resection (88% vs. 65%, p < 0.001) and improved PFS (16.8 vs. 12.7 months, p < 0.001). Patients receiving dose-dense paclitaxel (76% vs. 60%, p = 0.004) and CA-125 ≤ 35 U/mL at iTRS (85% vs. 66%, p < 0.001) had higher rates of complete radiographic response. On multivariate analysis, germline BRCA 1/2 mutation (p = 0.001), iTRS vs. no surgery (R0, p < 0.001; ≤1 cm, p < 0.001; >1 cm, p < 0.001), dose-dense chemotherapy (p = 0.01), and CA-125 ≤ 35 U/mL at iTRS (p = 0.001) were independent significant factors affecting PFS.

CONCLUSIONS

Normalization of CA-125 at the time of iTRS following NACT may serve as a surrogate marker for prognosis in this high-risk population. Our NACT cohort experienced improved response rates and PFS with dose-dense therapy compared to conventional dosing.

Joint IARC/NCI International Cancer Seminar Series Report: expert consensus on future directions for ovarian carcinoma research

Recently, ovarian cancer research has evolved considerably because of the emerging recognition that rather than a single disease, ovarian carcinomas comprise several different histotypes that vary by etiologic origin, risk factors, molecular profiles, therapeutic approaches and clinical outcome. Despite significant progress in our understanding of the etiologic heterogeneity of ovarian cancer, as well as important clinical advances, it remains the eighth most frequently diagnosed cancer in women worldwide and the most fatal gynecologic cancer. The International Agency for Research on Cancer and the United States National Cancer Institute jointly convened an expert panel on ovarian carcinoma to develop consensus research priorities based on evolving scientific discoveries. Expertise ranged from etiology, prevention, early detection, pathology, model systems, molecular characterization and treatment/clinical management. This report summarizes the current state of knowledge and highlights expert consensus on future directions to continue advancing etiologic, epidemiologic and prognostic research on ovarian carcinoma.

Proteogenomic landscape of uterine leiomyomas from hereditary leiomyomatosis and renal cell cancer patients

Pathogenic mutations in fumarate hydratase (FH) drive hereditary leiomyomatosis and renal cell cancer (HLRCC) and increase the risk of developing uterine leiomyomas (ULMs). An integrated proteogenomic analysis of ULMs from HLRCC (n = 16; FH-mutation confirmed) and non-syndromic (NS) patients (n = 12) identified a significantly higher protein:transcript correlation in HLRCC (R = 0.35) vs. NS ULMs (R = 0.242, MWU p = 0.0015). Co-altered proteins and transcripts (228) included antioxidant response element (ARE) target genes, such as thioredoxin reductase 1 (TXNRD1), and correlated with activation of NRF2-mediated oxidative stress response signaling in HLRCC ULMs. We confirm 185 transcripts previously described as altered between HLRCC and NS ULMs, 51 co-altered at the protein level and several elevated in HLRCC ULMs are involved in regulating cellular metabolism and glycolysis signaling. Furthermore, 367 S-(2-succino)cysteine peptides were identified in HLRCC ULMs, of which sixty were significantly elevated in HLRCC vs. NS ULMs (LogFC = 1.86, MWU p < 0.0001). These results confirm and define novel proteogenomic alterations in uterine leiomyoma tissues collected from HLRCC patients and underscore conserved molecular alterations correlating with inactivation of the FH tumor suppressor gene.

Proteomic Studies on the Management of High-Grade Serous Ovarian Cancer Patients: A Mini-Review

High-grade serous ovarian cancer (HGSC) remains the most common and deadly subtype of ovarian cancer. It is characterized by its late diagnosis and frequent relapse despite standardized treatment with cytoreductive surgery and platinum-based chemotherapy. The past decade has seen significant advances in the clinical management and molecular understanding of HGSC following the publication of the Cancer Genome Atlas (TCGA) researchers and the introduction of targeted therapies with anti-angiogenic drugs and poly(ADP-ribose) polymerase inhibitors in specific subgroups of patients. We provide a comprehensive review of HGSC, focusing on the most important molecular advances aimed at providing a better understanding of the disease and its response to treatment. We emphasize the role that proteomic technologies are now playing in these two aspects of the disease, through the identification of proteins and their post-translational modifications in ovarian cancer tumors. Finally, we highlight how the integration of proteomics with genomics, exemplified by the work performed by the Clinical Proteomic Tumor Analysis Consortium (CPTAC), can guide the development of new biomarkers and therapeutic targets.