Proteogenomic analysis of chemo-refractory high-grade serous ovarian cancer.

To improve the understanding of chemo-refractory high-grade serous ovarian cancers (HGSOCs), we characterized the proteogenomic landscape of 242 (refractory and sensitive) HGSOCs, representing one discovery and two validation cohorts across two biospecimen types (formalin-fixed paraffin-embedded and frozen). We identified a 64-protein signature that predicts with high specificity a subset of HGSOCs refractory to initial platinum-based therapy and is validated in two independent patient cohorts. We detected significant association between lack of Ch17 loss of heterozygosity (LOH) and chemo-refractoriness. Based on pathway protein expression, we identified 5 clusters of HGSOC, which validated across two independent patient cohorts and patient-derived xenograft (PDX) models. These clusters may represent different mechanisms of refractoriness and implicate putative therapeutic vulnerabilities.

Interfaces of Malignant and Immunologic Clonal Dynamics in Ovarian Cancer.

High-grade serous ovarian cancer (HGSC) exhibits extensive malignant clonal diversity with widespread but non-random patterns of disease dissemination. We investigated whether local immune microenvironment factors shape tumor progression properties at the interface of tumor-infiltrating lymphocytes (TILs) and cancer cells. Through multi-region study of 212 samples from 38 patients with whole-genome sequencing, immunohistochemistry, histologic image analysis, gene expression profiling, and T and B cell receptor sequencing, we identified three immunologic subtypes across samples and extensive within-patient diversity. Epithelial CD8+ TILs negatively associated with malignant diversity, reflecting immunological pruning of tumor clones inferred by neoantigen depletion, HLA I loss of heterozygosity, and spatial tracking between T cell and tumor clones. In addition, combinatorial prognostic effects of mutational processes and immune properties were observed, illuminating how specific genomic aberration types associate with immune response and impact survival. We conclude that within-patient spatial immune microenvironment variation shapes intraperitoneal malignant spread, provoking new evolutionary perspectives on HGSC clonal dispersion.

The genomic trajectory of ovarian high-grade serous carcinoma can be observed in STIC lesions.

Ovarian high-grade serous carcinoma (HGSC) originates in the fallopian tube, with secretory cells carrying a TP53 mutation, known as p53 signatures, identified as potential precursors. p53 signatures evolve into serous tubal intraepithelial carcinoma (STIC) lesions, which in turn progress into invasive HGSC, which readily spreads to the ovary and disseminates around the peritoneal cavity. We recently investigated the genomic landscape of early- and late-stage HGSC and found higher ploidy in late-stage (median 3.1) than early-stage (median 2.0) samples. Here, to explore whether the high ploidy and possible whole-genome duplication (WGD) observed in late-stage disease were determined early in the evolution of HGSC, we analysed archival formalin-fixed paraffin-embedded (FFPE) samples from five HGSC patients. p53 signatures and STIC lesions were laser-capture microdissected and sequenced using shallow whole-genome sequencing (sWGS), while invasive ovarian/fallopian tube and metastatic carcinoma samples underwent macrodissection and were profiled using both sWGS and targeted next-generation sequencing. Results showed highly similar patterns of global copy number change between STIC lesions and invasive carcinoma samples within each patient. Ploidy changes were evident in STIC lesions, but not p53 signatures, and there was a strong correlation between ploidy in STIC lesions and invasive ovarian/fallopian tube and metastatic samples in each patient. The reconstruction of sample phylogeny for each patient from relative copy number indicated that high ploidy, when present, occurred early in the evolution of HGSC, which was further validated by copy number signatures in ovarian and metastatic tumours. These findings suggest that aberrant ploidy, suggestive of WGD, arises early in HGSC and is detected in STIC lesions, implying that the trajectory of HGSC may be determined at the earliest stages of tumour development. © 2024 The Author(s). The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Proteomic Discovery of Plasma Protein Biomarkers and Development of Models Predicting Prognosis of High-Grade Serous Ovarian Carcinoma.

Ovarian cancer is one of the most lethal female cancers. For accurate prognosis prediction, this study aimed to investigate novel, blood-based prognostic biomarkers for high-grade serous ovarian carcinoma (HGSOC) using mass spectrometry-based proteomics methods. We conducted label-free liquid chromatography-tandem mass spectrometry using frozen plasma samples obtained from patients with newly diagnosed HGSOC (n = 20). Based on progression-free survival (PFS), the samples were divided into two groups: good (PFS ≥18 months) and poor prognosis groups (PFS <18 months). Proteomic profiles were compared between the two groups. Referring to proteomics data that we previously obtained using frozen cancer tissues from chemotherapy-naïve patients with HGSOC, overlapping protein biomarkers were selected as candidate biomarkers. Biomarkers were validated using an independent set of HGSOC plasma samples (n = 202) via enzyme-linked immunosorbent assay (ELISA). To construct models predicting the 18-month PFS rate, we performed stepwise selection based on the area under the receiver operating characteristic curve (AUC) with 5-fold cross-validation. Analysis of differentially expressed proteins in plasma samples revealed that 35 and 61 proteins were upregulated in the good and poor prognosis groups, respectively. Through hierarchical clustering and bioinformatic analyses, GSN, VCAN, SND1, SIGLEC14, CD163, and PRMT1 were selected as candidate biomarkers and were subjected to ELISA. In multivariate analysis, plasma GSN was identified as an independent poor prognostic biomarker for PFS (adjusted hazard ratio, 1.556; 95% confidence interval, 1.073-2.256; p = 0.020). By combining clinical factors and ELISA results, we constructed several models to predict the 18-month PFS rate. A model consisting of four predictors (FIGO stage, residual tumor after surgery, and plasma levels of GSN and VCAN) showed the best predictive performance (mean validated AUC, 0.779). The newly developed model was converted to a nomogram for clinical use. Our study results provided insights into protein biomarkers, which might offer clues for developing therapeutic targets.

Tumor FAK orchestrates immunosuppression in ovarian cancer via the CD155/TIGIT axis.

High-grade serous ovarian cancer (HGSOC) is a lethal malignancy characterized by an immunosuppressive tumor microenvironment containing few tumor infiltrating lymphocytes (TILs) and an insensitivity to checkpoint inhibitor immunotherapies. Gains in the PTK2 gene encoding focal adhesion kinase (FAK) at Chr8 q24.3 occur in ∼70% of HGSOC tumors, and elevated FAK messenger RNA (mRNA) levels are associated with poor patient survival. Herein, we show that active FAK, phosphorylated at tyrosine-576 within catalytic domain, is significantly increased in late-stage HGSOC tumors. Active FAK costained with CD155, a checkpoint receptor ligand for TIGIT (T cell immunoreceptor with immunoglobulin and immunoreceptor tyrosine-based inhibitory motif domains), in HGSOC tumors and a selective association between FAK and TIGIT checkpoint ligands were supported by patient transcriptomic database analysis. HGSOC tumors with high FAK expression were associated with low CD3 mRNA levels. Accordingly, late-stage tumors showed elevated active FAK staining and significantly lower levels of CD3+ TILs. Using the KMF (Kras, Myc, FAK) syngeneic ovarian tumor model containing spontaneous PTK2 (FAK) gene gains, the effects of tumor intrinsic genetic or oral small molecule FAK inhibitior (FAKi; VS-4718) were evaluated in vivo. Blocking FAK activity decreased tumor burden, suppressed ascites KMF-associated CD155 levels, and increased peritoneal TILs. The combination of FAKi with blocking TIGIT antibody (1B4) maintained elevated TIL levels and reduced TIGIT+ T regulatory cell levels, prolonged host survival, increased CXCL13 levels, and led to the formation of omental tertiary lymphoid structures. Collectively, our studies support FAK and TIGIT targeting as a rationale immunotherapy combination for HGSOC.

Targeted Mass Spectrometry of Longitudinal Patient Sera Reveals LTBP1 as a Potential Surveillance Biomarker for High-Grade Serous Ovarian Carcinoma.

High-grade serous ovarian carcinoma (HGSC) is the most prevalent subtype of epithelial ovarian cancer. The combination of a high rate of recurrence and novel therapies in HGSC necessitates an accurate assessment of the disease. Currently, HGSC response to treatment and recurrence are monitored via immunoassay of serum levels of the glycoprotein CA125. CA125 levels predictably rise at HGSC recurrence; however, it is likely that the disease is progressing even before it is detectable through CA125. This may explain why treating solely based on CA125 increase has not been associated with improved outcomes. Thus, additional biomarkers that monitor HGSC progression and cancer recurrence are needed. For this purpose, we developed a scheduled parallel reaction monitoring mass spectrometry (PRM-MS) assay for the quantification of four previously identified HGSC-derived glycopeptides (from proteins FGL2, LGALS3BP, LTBP1, and TIMP1). We applied the assay to quantify their longitudinal expression profiles in 212 serum samples taken from 34 HGSC patients during disease progression. Analyses revealed that LTBP1 best-mirrored tumor load, dropping as a result of cancer treatment in 31 out of 34 patients and rising at HGSC recurrence in 28 patients. Additionally, LTBP1 rose earlier during remission than CA125 in 11 out of 25 platinum-sensitive patients with an average lead time of 116.4 days, making LTBP1 a promising candidate for monitoring of HGSC recurrence.

Trps1 predicts poor prognosis in advanced high grade serous ovarian carcinoma.

TRPS1 is aberrantly expressed in a variety of tumors, including breast, prostate, and gastric cancers, and is strongly associated with tumorigenesis or prognosis. However, the role of TRPS1 in high grade serous ovarian carcinoma (HGSC) is unknown. We investigated the relationship between TRPS1 expression and clinicopathology in HGSC patients. The tumor-related regulatory mechanisms of TRPS1 was explored through in vivo and vitro experiments. The results showed that TRPS1 was highly expressed in HGSC compared to normal tissues. It was also linked to the cell proliferation index Ki67 and poor prognosis. In vivo experiments showed that knockdown of TRPS1 could inhibit tumor growth. In vitro experiments, knockdown of TRPS1 inhibited the proliferation of ovarian cancer cells. TRPS1 exerted its regulatory role as a transcription factor, binding to the PSAT1 promoter and promoting the expression of PSAT1 gene. Meanwhile, PSAT1 was positively correlated with CCND1 expression. These results suggest that TRPS1 affects HGSC proliferation and cell cycle by regulating PSAT1 and thus CCND1 expression.

Altered tumor signature and T-cell profile after chemotherapy reveal new therapeutic opportunities in high-grade serous ovarian carcinoma.

Chemotherapy combined with debulking surgery is the standard treatment protocol for high-grade serous ovarian carcinoma (HGSOC). Nonetheless, a significant number of patients encounter relapse due to the development of chemotherapy resistance. To better understand and address this resistance, we conducted a comprehensive study investigating the transcriptional alterations at the single-cell resolution in tissue samples from patients with HGSOC, using single-cell RNA sequencing and T-cell receptor sequencing techniques. Our analyses unveiled notable changes in the tumor signatures after chemotherapy, including those associated with epithelial-mesenchymal transition and cell cycle arrest. Within the immune compartment, we observed alterations in the T-cell profiles, characterized by naïve or pre-exhausted populations following chemotherapy. This phenotypic change was further supported by the examination of adjoining T-cell receptor clonotypes in paired longitudinal samples. These findings underscore the profound impact of chemotherapy on reshaping the tumor landscape and the immune microenvironment. This knowledge may provide clues for the development of future therapeutic strategies to combat treatment resistance in HGSOC.

Opening the Black Box: Spatial Transcriptomics and the Relevance of Artificial Intelligence-Detected Prognostic Regions in High-Grade Serous Carcinoma.

Image-based deep learning models are used to extract new information from standard hematoxylin and eosin pathology slides; however, biological interpretation of the features detected by artificial intelligence (AI) remains a challenge. High-grade serous carcinoma of the ovary (HGSC) is characterized by aggressive behavior and chemotherapy resistance, but also exhibits striking variability in outcome. Our understanding of this disease is limited, partly due to considerable tumor heterogeneity. We previously trained an AI model to identify HGSC tumor regions that are highly associated with outcome status but are indistinguishable by conventional morphologic methods. Here, we applied spatially resolved transcriptomics to further profile the AI-identified tumor regions in 16 patients (8 per outcome group) and identify molecular features related to disease outcome in patients who underwent primary debulking surgery and platinum-based chemotherapy. We examined formalin-fixed paraffin-embedded tissue from (1) regions identified by the AI model as highly associated with short or extended chemotherapy response, and (2) background tumor regions (not identified by the AI model as highly associated with outcome status) from the same tumors. We show that the transcriptomic profiles of AI-identified regions are more distinct than background regions from the same tumors, are superior in predicting outcome, and differ in several pathways including those associated with chemoresistance in HGSC. Further, we find that poor outcome and good outcome regions are enriched by different tumor subpopulations, suggesting distinctive interaction patterns. In summary, our work presents proof of concept that AI-guided spatial transcriptomic analysis improves recognition of biologic features relevant to patient outcomes.

SPCS: a spatial and pattern combined smoothing method for spatial transcriptomic expression.

High-dimensional, localized ribonucleic acid (RNA) sequencing is now possible owing to recent developments in spatial transcriptomics (ST). ST is based on highly multiplexed sequence analysis and uses barcodes to match the sequenced reads to their respective tissue locations. ST expression data suffer from high noise and dropout events; however, smoothing techniques have the promise to improve the data interpretability prior to performing downstream analyses. Single-cell RNA sequencing (scRNA-seq) data similarly suffer from these limitations, and smoothing methods developed for scRNA-seq can only utilize associations in transcriptome space (also known as one-factor smoothing methods). Since they do not account for spatial relationships, these one-factor smoothing methods cannot take full advantage of ST data. In this study, we present a novel two-factor smoothing technique, spatial and pattern combined smoothing (SPCS), that employs the k-nearest neighbor (kNN) technique to utilize information from transcriptome and spatial relationships. By performing SPCS on multiple ST slides from pancreatic ductal adenocarcinoma (PDAC), dorsolateral prefrontal cortex (DLPFC) and simulated high-grade serous ovarian cancer (HGSOC) datasets, smoothed ST slides have better separability, partition accuracy and biological interpretability than the ones smoothed by preexisting one-factor methods. Source code of SPCS is provided in Github (https://github.com/Usos/SPCS).

Quantification of putative ovarian cancer serum protein biomarkers using a multiplexed targeted mass spectrometry assay.

BACKGROUND: Ovarian cancer is the most lethal gynecologic malignancy in women, and high-grade serous ovarian cancer (HGSOC) is the most common subtype. Currently, no clinical test has been approved by the FDA to screen the general population for ovarian cancer. This underscores the critical need for the development of a robust methodology combined with novel technology to detect diagnostic biomarkers for HGSOC in the sera of women. Targeted mass spectrometry (MS) can be used to identify and quantify specific peptides/proteins in complex biological samples with high accuracy, sensitivity, and reproducibility. In this study, we sought to develop and conduct analytical validation of a multiplexed Tier 2 targeted MS parallel reaction monitoring (PRM) assay for the relative quantification of 23 putative ovarian cancer protein biomarkers in sera. METHODS: To develop a PRM method for our target peptides in sera, we followed nationally recognized consensus guidelines for validating fit-for-purpose Tier 2 targeted MS assays. The endogenous target peptide concentrations were calculated using the calibration curves in serum for each target peptide. Receiver operating characteristic (ROC) curves were analyzed to evaluate the diagnostic performance of the biomarker candidates. RESULTS: We describe an effort to develop and analytically validate a multiplexed Tier 2 targeted PRM MS assay to quantify candidate ovarian cancer protein biomarkers in sera. Among the 64 peptides corresponding to 23 proteins in our PRM assay, 24 peptides corresponding to 16 proteins passed the assay validation acceptability criteria. A total of 6 of these peptides from insulin-like growth factor-binding protein 2 (IBP2), sex hormone-binding globulin (SHBG), and TIMP metalloproteinase inhibitor 1 (TIMP1) were quantified in sera from a cohort of 69 patients with early-stage HGSOC, late-stage HGSOC, benign ovarian conditions, and healthy (non-cancer) controls. Confirming the results from previously published studies using orthogonal analytical approaches, IBP2 was identified as a diagnostic biomarker candidate based on its significantly increased abundance in the late-stage HGSOC patient sera compared to the healthy controls and patients with benign ovarian conditions. CONCLUSIONS: A multiplexed targeted PRM MS assay was applied to detect candidate diagnostic biomarkers in HGSOC sera. To evaluate the clinical utility of the IBP2 PRM assay for HGSOC detection, further studies need to be performed using a larger patient cohort.

Human peritoneal fluid exerts ovulation- and nonovulation-sourced oncogenic activities on transforming fallopian tube epithelial cells.

Secretory cells in the fallopian tube fimbria epithelium (FTE) are regarded as the main cells of origin of ovarian high-grade serous carcinoma (HGSC). Ovulation is the main cause of FTE oncogenesis, which proceeds through a sequence of TP53 mutations, chromosomal instability due to Rb/cyclin E aberration, in situ carcinoma (STIC), and metastasis to the ovary and peritoneum (metastatic HGSC). Previously, we have identified multiple oncogenic activities of the ovulatory follicular fluid (FF), which exerts the full spectrum of transforming activity on FTE cells at different stages of transformation. After ovulation, the FF is transfused into the peritoneal fluid (PF), in which the FTE constantly bathes. We wondered whether PF exerts the same spectrum of oncogenic activities as done by FF and whether these activities are derived from FF. By using a panel of FTE cell lines with p53 mutation (FT282-V), p53/CCNE1 aberrations (FT282-CCNE1), and p53/Rb aberrations plus spontaneous transformation, and peritoneal metastasis (FEXT2), we analyzed the changes of different transformation phenotypes after treating with FF and PF collected before or after ovulation. Similar to effects exhibited by FF, we found that, to a lesser extent, PF promoted anchorage-independent growth (AIG), migration, anoikis resistance, and peritoneal attachment in transforming FTE cells. The more transformed cells were typically more affected. Among the transforming activities exhibited by PF treatment, AIG, Matrigel invasion, and peritoneal attachment growth were higher with luteal-phase PF treatment than with the proliferative-phase PF treatment, suggesting an ovulation source. In contrast, changes in anoikis resistance and migration activities were similar in response to treatment with PF collected before and after ovulation, suggesting an ovulation-independent source. The overall transforming activity of luteal-phase PF was verified in an i.p. co-injection xenograft mouse model. Co-injection of Luc-FEXT2 cells with either FF or luteal-phase PF supported early peritoneal implantation, whereas co-injection with follicular-phase PF did not. This study, for the first time, demonstrates that PF from ovulating women can promote different oncogenic phenotypes in FTE cells at different stages of malignant transformation. Most of these activities, other than anoikis resistance and cell migration, are sourced from ovulation.

Comprehensive Genomic Characterization in Ovarian Low-Grade and Chemosensitive and Chemoresistant High-Grade Serous Carcinomas.

INTRODUCTION: Genomic characterization of serous ovarian carcinoma (SOC), which includes low-grade serous carcinoma (LGSC) and high-grade serous carcinoma (HGSC), remains necessary to improve efficacy of platinum-based chemotherapy. The aim of this study was to investigate the genomic variations in these SOC groups, also in relation to chemoresponse. METHODS: Forty-five samples of SOC were retrospectively analyzed by next-generation sequencing on DNA/RNA extracts from formalin-fixed, paraffin-embedded (FFPE) tumor samples obtained at diagnosis. HGSCs were classified as platinum-resistant and platinum-sensitive. RESULTS: In the LGSC group, 44% of the carcinomas had mutually exclusive variants in the RAS/RAF pathway, while additional likely oncogenic variants in the CDKN2A, SMARCA4, and YAP1 genes were observed in the remaining LGSCs. Tumor mutation burden (TMB) was significantly lower in the intrinsically chemoresistant LGSC group than in the HGSC group. In the HGSC cohort, TP53 variants were found in 90% and homologous recombination repair (HRR) pathway variants in 41% of the neoplasms. HGSCs of the chemoresistant group without classic mutations in the HRR pathway were characterized by additional variants in FGFR2 and with an FGFR3::TACC3 fusion. In addition, HGSCs showed MYC, CCNE1, and AKT2 gains that were almost exclusively observed in the chemosensitive HGSC group. CONCLUSION: These results suggest that very low TMB and MYC, CCNE1, and AKT2 gains in SOC patients may be biomarkers related to platinum treatment efficacy. Thorough genomic characterization of SOCs prior to treatment might lead to more specific platinum-based chemotherapy strategies.

Survival time prediction in patients with high-grade serous ovarian cancer based on 18F-FDG PET/CT- derived inter-tumor heterogeneity metrics.

BACKGROUND: The presence of heterogeneity is a significant attribute within the context of ovarian cancer. This study aimed to assess the predictive accuracy of models utilizing quantitative 18F-FDG PET/CT derived inter-tumor heterogeneity metrics in determining progression-free survival (PFS) and overall survival (OS) in patients diagnosed with high-grade serous ovarian cancer (HGSOC). Additionally, the study investigated the potential correlation between model risk scores and the expression levels of p53 and Ki-67. METHODS: A total of 292 patients diagnosed with HGSOC were retrospectively enrolled at Shengjing Hospital of China Medical University (median age: 54 ± 9.4 years). Quantitative inter-tumor heterogeneity metrics were calculated based on conventional measurements and texture features of primary and metastatic lesions in 18F-FDG PET/CT. Conventional models, heterogeneity models, and integrated models were then constructed to predict PFS and OS. Spearman's correlation coefficient (ρ) was used to evaluate the correlation between immunohistochemical scores of p53 and Ki-67 and model risk scores. RESULTS: The C-indices of the integrated models were the highest for both PFS and OS models. The C-indices of the training set and testing set of the integrated PFS model were 0.898 (95% confidence interval [CI]: 0.881-0.914) and 0.891 (95% CI: 0.860-0.921), respectively. For the integrated OS model, the C-indices of the training set and testing set were 0.894 (95% CI: 0.871-0.917) and 0.905 (95% CI: 0.873-0.936), respectively. The integrated PFS model showed the strongest correlation with the expression levels of p53 (ρ = 0.859, p < 0.001) and Ki-67 (ρ = 0.829, p < 0.001). CONCLUSIONS: The models based on 18F-FDG PET/CT quantitative inter-tumor heterogeneity metrics exhibited good performance for predicting the PFS and OS of patients with HGSOC. p53 and Ki-67 expression levels were strongly correlated with the risk scores of the integrated predictive models.

Whole-exome sequencing reveals candidate high-risk susceptibility genes for endometriosis.

BACKGROUND: Endometriosis is a common, chronic disease among fertile-aged women. Disease course may be highly invasive, requiring extensive surgery. The etiology of endometriosis remains elusive, though a high level of heritability is well established. Several low-penetrance predisposing loci have been identified, but high-risk susceptibility remains undetermined. Endometriosis is known to increase the risk of epithelial ovarian cancers, especially of endometrioid and clear cell types. Here, we have analyzed a Finnish family where four women have been diagnosed with surgically verified, severely symptomatic endometriosis and two of the patients also with high-grade serous carcinoma. RESULTS: Whole-exome sequencing revealed three rare candidate predisposing variants segregating with endometriosis. The variants were c.1238C>T, p.(Pro413Leu) in FGFR4, c.5065C>T, p.(Arg1689Trp) in NALCN, and c.2086G>A, p.(Val696Met) in NAV2. The only variant predicted deleterious by in silico tools was the one in FGFR4. Further screening of the variants in 92 Finnish endometriosis and in 19 endometriosis-ovarian cancer patients did not reveal additional carriers. Histopathology, positive p53 immunostaining, and genetic analysis supported the high-grade serous subtype of the two tumors in the family. CONCLUSIONS: Here, we provide FGFR4, NALCN, and NAV2 as novel high-risk candidate genes for familial endometriosis. Our results also support the association of endometriosis with high-grade serous carcinoma. Further studies are required to validate the findings and to reveal the exact pathogenesis mechanisms of endometriosis. Elucidating the genetic background of endometriosis defines the etiology of the disease and provides opportunities for expedited diagnostics and personalized treatments.

A spatial proteomic study of platinum refractory HGSOC implicates dual AKT and WNT activity linked to an immunosuppressive tumor microenvironment.

OBJECTIVE: Advanced-stage high-grade serous ovarian cancer (HGSOC) remains a deadly gynecologic malignancy with high rates of disease recurrence and limited, effective therapeutic options for patients. There is a significant need to better stratify HGSOC patients into platinum refractory (PRF) vs. sensitive (PS) cohorts at baseline to improve therapeutic responses and survival outcomes for PRF HGSOC. METHODS: We performed NanoString for GeoMx Digital Spatial Profile (G-DSP) multiplex protein analysis on PRF and PS tissue microarrays (TMAs) to study the bidirectional communication of cancer cells with immune cells in the tumor microenvironment (TME) of HGSOC. We demonstrate robust stratification of PRF and PS tumors at baseline using multiplex spatial proteomic biomarkers with implications for tailoring subsequent therapy. RESULTS: PS patients had elevated apoptotic and anti-tumor immune profiles, while PRF patients had dual AKT1 and WNT signaling with immunosuppressive profiles. We found that dual activity of AKT1 and WNT signaling supported the exclusion of immune cells, specifically tumor infiltrating lymphocytes (TILs), from the TME in PRF tumors, and this was not observed in PS tumors. The exclusion of immune cells from the TME of PRF tumors corresponded to abnormal endothelial cell structure in tumors with dual AKT1 and WNT signaling activity. CONCLUSIONS: We believe our findings provide improved understanding of tumor-immune crosstalk in HGSOC TME highlighting the importance of the relationship between AKT and WNT pathways, immune cell function, and platinum response in HGSOC.

5-Hydroxymethylcytosine signals in serum are a predictor of chemoresistance in high-grade serous ovarian cancer.

OBJECTIVE: The genome-wide profiling of 5-hydroxymethylcytosines (5hmC) on circulating cell-free DNA (cfDNA) has revealed promising biomarkers for various diseases. The purpose of this study was to investigate 5hmC signals in serum cfDNA and identify novel predictive biomarkers for the development of chemoresistance in high-grade serous ovarian cancer (HGSOC). We hypothesized that 5hmC profiles in cfDNA reflect the development of chemoresistance and elucidate pathways that may drive chemoresistance in HGSOC. Moreover, we sought to identify predictors that would better stratify outcomes for women with intermediate-sensitive HGSOC. METHODS: Women diagnosed with HGSOC and known platinum sensitivity status were selected for this study. Nano-hmC-Seal was performed on cfDNA isolated from archived serum samples, and differential 5hmC features were identified using DESeq2 to establish a model predictive of chemoresistance. RESULTS: A multivariate model consisting of three features (preoperative CA-125, largest residual implant after surgery, 5hmC level of OSGEPL), stratified samples from intermediate sensitive, chemo-naive women diagnosed with HGSOC into chemotherapy-resistant- and sensitive-like strata with a significant difference in overall survival (OS). Independent analysis of The Cancer Genome Atlas data further confirmed that high OSGEPL1 expression is a favorable prognostic factor for HGSOC. CONCLUSIONS: We have developed a novel multivariate model based on clinico-pathologic data and a cfDNA-derived 5hmC modified gene, OSGEPL1, that predicted response to platinum-based chemotherapy in intermediate-sensitive HGSOC. Our multivariate model applies to chemo-naïve samples regardless if the patint was treated with adjuvant or neoadjuvant chemotherapy. These results merit further investigation of the predictive capability of our model in larger cohorts.

Long-term outcome of high-grade serous carcinoma established in risk-reducing salpingo-oophorectomy specimens in asymptomatic BRCA1/2 germline pathogenic variant carriers.

OBJECTIVE: The aim of this study was to describe the long-term outcome of asymptomatic BRCA1/2 germline pathogenic variant (GPV) carriers with high-grade serous carcinoma (HGSC) in their risk-reducing salpingo-oophorectomy (RRSO) specimen. METHODS: In a previously described cohort of asymptomatic BRCA1/2 GPV carriers derived from the Hereditary Breast and Ovarian cancer in the Netherlands (HEBON) study, women with HGSC at RRSO were identified. Main outcome was ten-year disease-free survival (DFS). Secondary outcomes were time to recurrence, ten-year disease-specific survival (DSS), ten-year overall survival (OS). Patient, disease and treatment characteristics associated with recurrence were described. RESULTS: The 28 included women with HGSC at RRSO were diagnosed at a median age of 55.3 years (range: 33.5-74.3). After staging, eighteen women had (FIGO) stage I, three stage II and five had stage III disease. Two women did not undergo surgical staging and were classified as unknown stage. After a median follow-up of 13.5 years (range: 9.1-24.7), six women with stage I (33%), one woman with stage II (33%), two women with stage III (40%) and none of the women with unknown stage developed a recurrence. Median time to recurrence was 6.9 years (range: 0.8-9.2 years). Ten-year DFS was 68%, ten-year DSS was 88% and ten-year OS was 82%. CONCLUSION: Most asymptomatic BRCA1/2 GPV carriers with HGSC at RRSO were diagnosed at an early stage. Nevertheless, after a median follow-up of 13.5 years, nine of the 28 women with HGSC at RRSO developed a recurrence after a median of 6.9 years.

HRD related signature 3 predicts clinical outcome in advanced tubo-ovarian high-grade serous carcinoma.

OBJECTIVES: We evaluated usability of single base substitution signature 3 (Sig3) as a biomarker for homologous recombination deficiency (HRD) in tubo-ovarian high-grade serous carcinoma (HGSC). MATERIALS AND METHODS: This prospective observational trial includes 165 patients with advanced HGSC. Fresh tissue samples (n = 456) from multiple intra-abdominal areas at diagnosis and after neoadjuvant chemotherapy (NACT) were collected for whole-genome sequencing. Sig3 was assessed by fitting samples independently with COSMIC v3.2 reference signatures. An HR scar assay was applied for comparison. Progression-free survival (PFS) and overall survival (OS) were studied using Kaplan-Meier and Cox regression analysis. RESULTS: Sig3 has a bimodal distribution, eliminating the need for an arbitrary cutoff typical in HR scar tests. Sig3 could be assessed from samples with low (10%) cancer cell proportion and was consistent between multiple samples and stable during NACT. At diagnosis, 74 (45%) patients were HRD (Sig3+), while 91 (55%) were HR proficient (HRP, Sig3-). Sig3+ patients had longer PFS and OS than Sig3- patients (22 vs. 13 months and 51 vs. 34 months respectively, both p < 0.001). Sig3 successfully distinguished the poor prognostic HRP group among BRCAwt patients (PFS 19 months for Sig3+ and 13 months for Sig3- patients, p < 0.001). However, Sig3 at diagnosis did not predict chemoresponse anymore in the first relapse. The patient-level concordance between Sig3 and HR scar assay was 87%, and patients with HRD according to both tests had the longest median PFS. CONCLUSIONS: Sig3 is a prognostic marker in advanced HGSC and useful tool in patient stratification for HRD.

Does serous tubal intraepithelial carcinoma (STIC) metastasize? The clonal relationship between STIC and subsequent high-grade serous carcinoma in BRCA1/2 mutation carriers several years after risk-reducing salpingo-oophorectomy.

OBJECTIVE: The majority of high-grade serous carcinomas (HGSC) of the ovary, fallopian tube, and peritoneum arise from the precursor lesion called serous tubal intraepithelial carcinoma (STIC). It has been postulated that cells from STICs exfoliate into the peritoneal cavity and give rise to peritoneal HGSC several years later. While co-existent STICs and HGSCs have been reported to share similarities in their mutational profiles, clonal relationship between temporally distant STICs and HGSCs have been infrequently studied and the natural history of STICs remains poorly understood. METHODS: We performed focused searches in two national databases from the Netherlands and identified a series of BRCA1/2 germline pathogenic variant (GPV) carriers (n = 7) who had STIC, and no detectable invasive carcinoma, at the time of their risk-reducing salpingo-oophorectomy (RRSO), and later developed peritoneal HGSC. The clonal relationship between these STICs and HGSCs was investigated by comparing their genetic mutational profile by performing next-generation targeted sequencing. RESULTS: Identical pathogenic mutations and loss of heterozygosity of TP53 were identified in the STICs and HGSCs of five of the seven patients (71%), confirming the clonal relationship of the lesions. Median interval for developing HGSC after RRSO was 59 months (range: 24-118 months). CONCLUSION: Our results indicate that cells from STIC can shed into the peritoneal cavity and give rise to HGSC after long lag periods in BRCA1/2 GPV carriers, and argues in favor of the hypothesis that STIC lesions may metastasize.