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PurposeThe purpose of this study was to evaluate RB1 expression and survival across ovarian carcinoma histotypes and how co-occurrence of BRCA1 or BRCA2 (BRCA) alterations and RB1 loss influences survival in tubo-ovarian high-grade serous carcinoma (HGSC).Experimental designRB1 protein expression was classified by immunohistochemistry in ovarian carcinomas of 7,436 patients from the Ovarian Tumor Tissue Analysis consortium. We examined RB1 expression and germline BRCA status in a subset of 1,134 HGSC, and related genotype to overall survival (OS), tumor-infiltrating CD8+ lymphocytes, and transcriptomic subtypes. Using CRISPR-Cas9, we deleted RB1 in HGSC cells with and without BRCA1 alterations to model co-loss with treatment response. We performed whole-genome and transcriptome data analyses on 126 patients with primary HGSC to characterize tumors with concurrent BRCA deficiency and RB1 loss.ResultsRB1 loss was associated with longer OS in HGSC but with poorer prognosis in endometrioid ovarian carcinoma. Patients with HGSC harboring both RB1 loss and pathogenic germline BRCA variants had superior OS compared with patients with either alteration alone, and their median OS was three times longer than those without pathogenic BRCA variants and retained RB1 expression (9.3 vs. 3.1 years). Enhanced sensitivity to cisplatin and paclitaxel was seen in BRCA1-altered cells with RB1 knockout. Combined RB1 loss and BRCA deficiency correlated with transcriptional markers of enhanced IFN response, cell-cycle deregulation, and reduced epithelial-mesenchymal transition. CD8+ lymphocytes were most prevalent in BRCA-deficient HGSC with co-loss of RB1.ConclusionsCo-occurrence of RB1 loss and BRCA deficiency was associated with exceptionally long survival in patients with HGSC, potentially due to better treatment response and immune stimulation.

Objectives: Ovarian carcinosarcoma (OCS) is a rare and lethal type of ovarian cancer. Despite its incredibly poor prognosis, it has received little research attention. In this study, we aim to evaluate the molecular features of OCS and elucidate their clinical significance. Study methods: We examined 30 OCS by immunohistochemistry (IHC) and targeted panel sequencing collected from a single institution (2003–2013) as the initial molecularly characterized cohort (Cohort A). From November 2016 to April 2023, we collected an additional 67 OCS cases from three institutions across British Columbia and Alberta as the contemporary cohort (Cohort B) for clinical correlation. The Kaplan–Meier method was used to estimate overall and progression-free survival, and differences in survival rates were compared using the log-rank test. All tests were two-sided. A p-value of less than 0.05 was considered statistically significant. Results: The majority of OCS (82%) in the initial Cohort A were p53-mutated, and the carcinomatous component displayed the histological and molecular features of a high-grade tubo-ovarian serous carcinoma (HGSC-like). In a minority of OCS, the epithelial components were characteristics of endometrioid or clear cell carcinomas, and IHC staining was wild type for p53. In the contemporary Cohort B, we observed the same histological findings related to the p53 IHC staining pattern. The median overall survival of the p53-mutated HGSC-like OCS (47 patients) was significantly higher (43.5 months) compared with that of the p53 wild-type OCS (10 patients, 8.8 months; P < 0.01). Pathogenic BRCA1/2 germline/ somatic mutations were observed in 7 patients (17.5%) of HGSC-like OCS, and all these patients were alive at 3 years from diagnosis compared to a 51% 3-year survival among the patients with BRCA1/2 wild-type HGSC-like OCS (33 patients) (p = 0.022). Majority of patients (6/7) with BRCA1/2-mutated OCS received poly (ADP-ribose) polymerase inhibitor as maintenance therapy in this cohort. Conclusions: Most OCSs have a morphologic and molecular profile resembling HGSC; however, some OCSs display a molecular profile that suggests origin through non-serous oncogenic pathways. This molecular distinction has both prognostic and treatment (predictive) implications. These findings underscore the importance of routine p53 IHC testing on all OCS and BRCA1/2 testing on p53-mutated OCS. [ABSTRACT FROM AUTHOR]

Investigation of histopathology slides by pathologists is an indispensable component of the routine diagnosis of cancer. Artificial intelligence (AI) has the potential to enhance diagnostic accuracy, improve efficiency, and patient outcomes in clinical pathology. However, variations in tissue preparation, staining protocols, and histopathology slide digitization could result in over-fitting of deep learning models when trained on the data from only one center, thereby underscoring the necessity to generalize deep learning networks for multi-center use. Several techniques, including the use of grayscale images, color normalization techniques, and Adversarial Domain Adaptation (ADA) have been suggested to generalize deep learning algorithms, but there are limitations to their effectiveness and discriminability. Convolutional Neural Networks (CNNs) exhibit higher sensitivity to variations in the amplitude spectrum, whereas humans predominantly rely on phase-related components for object recognition. As such, we propose Adversarial fourIer-based Domain Adaptation (AIDA) which applies the advantages of a Fourier transform in adversarial domain adaptation. We conducted a comprehensive examination of subtype classification tasks in four cancers, incorporating cases from multiple medical centers. Specifically, the datasets included multi-center data for 1113 ovarian cancer cases, 247 pleural cancer cases, 422 bladder cancer cases, and 482 breast cancer cases. Our proposed approach significantly improved performance, achieving superior classification results in the target domain, surpassing the baseline, color augmentation and normalization techniques, and ADA. Furthermore, extensive pathologist reviews suggested that our proposed approach, AIDA, successfully identifies known histotype-specific features. This superior performance highlights AIDA's potential in addressing generalization challenges in deep learning models for multi-center histopathology datasets. [ABSTRACT FROM AUTHOR]

Mesonephric‐type (or ‐like) adenocarcinomas (MAs) of the ovary are an uncommon and aggressive histotype. They appear to arise through transdifferentiation from Müllerian lesions creating diagnostic challenges. Thus, we aimed to develop a histologic and immunohistochemical (IHC) approach to optimize the identification of MA over its histologic mimics, such as ovarian endometrioid carcinoma (EC). First, we screened 1,537 ovarian epithelial neoplasms with a four‐marker IHC panel of GATA3, TTF1, ER, and PR followed by a morphological review of EC to identify MA in retrospective cohorts. Interobserver reproducibility for the distinction of MA versus EC was assessed in 66 cases initially without and subsequently with IHC information (four‐marker panel). Expression of PAX2, CD10, and calretinin was evaluated separately, and survival analyses were performed. We identified 23 MAs from which 22 were among 385 cases initially reported as EC (5.7%) and 1 as clear cell carcinoma. The interobserver reproducibility increased from fair to substantial (κ = 0.376–0.727) with the integration of the four‐marker IHC panel. PAX2 was the single most sensitive and specific marker to distinguish MA from EC and could be used as a first‐line marker together with ER/PR and GATA3/TTF1. Patients with MA had significantly increased risk of earlier death from disease (hazard ratio = 3.08; 95% CI, 1.62–5.85; p < 0.0001) compared with patients with EC, when adjusted for age, stage, and p53 status. A diagnosis of MA has prognostic implications for stage I disease, and due to the subtlety of morphological features in some tumors, a low threshold for ancillary testing is recommended. [ABSTRACT FROM AUTHOR]

Aims: Mucinous ovarian carcinoma (MOC) is a rare ovarian cancer histotype with generally good prognosis when diagnosed at an early stage. However, MOC with the infiltrative pattern of invasion has a worse prognosis, although to date studies have not been large enough to control for covariables. Data on reproducibility of classifying the invasion pattern are limited, as are molecular correlates for infiltrative invasion. We hypothesized that the invasion pattern would be associated with an aberrant tumour microenvironment. Methods and results: Four subspecialty pathologists assessed interobserver reproducibility of the pattern of invasion in 134 MOC. Immunohistochemistry on fibroblast activation protein (FAP) and THBS2 was performed on 98 cases. Association with survival was tested using Cox regression. The average interobserver agreement for the infiltrative pattern was moderate (kappa 0.60, agreement 86.3%). After reproducibility review, 24/134 MOC (18%) were determined to have the infiltrative pattern and this was associated with a higher risk of death, independent of FIGO stage, grade, and patient age in a time‐dependent manner (hazard ratio [HR] = 10.2, 95% confidence interval [CI] 3.0–34.5). High stromal expression of FAP and THBS2 was more common in infiltrative MOC (FAP: 60%, THBS2: 58%, both P < 0.001) and associated with survival (multivariate HR for FAP: 1.5 [95% CI 1.1–2.1] and THBS2: 1.91 [95% CI 1.1–3.2]). Conclusions: The pattern of invasion should be included in reporting for MOC due to the strong prognostic implications. We highlight the histological features that should be considered to improve reproducibility. FAP and THBS2 are associated with infiltrative invasion in MOC. [ABSTRACT FROM AUTHOR]

Mesonephric‐like adenocarcinoma (MLA) of the female genital tract is an uncommon histotype that can arise in both the endometrium and the ovary. The exact cell of origin and histogenesis currently remain unknown. Here, we investigated whole genome DNA methylation patterns and copy number variations (CNVs) in a series of MLAs in the context of a large cohort of various gynaecological carcinoma types. CNV analysis of 19 MLAs uncovered gains of chromosomes 1q (18/19, 95%), 10 (15/19, 79%), 12 (14/19, 74%), and 2 (10/19, 53%), as well as loss of chromosome 1p (7/19, 37%). Gains of chromosomes 1q, 10, and 12 were also identified in the majority of mesonephric adenocarcinomas of the uterine cervix (MAs) as well as subsets of endometrioid carcinomas (ECs) and low‐grade serous carcinomas of the ovary (LGSCs) but only in a minority of serous carcinomas of the uterine corpus (USCs), clear cell carcinomas (CCCs), and tubo‐ovarian high‐grade serous carcinomas (HGSCs). While losses of chromosome 1p together with gains of chromosome 1q were also identified in both MA and LGSC, gains of chromosome 2 were almost exclusively identified in MLA and MA. Unsupervised hierarchical clustering and t‐SNE analysis of DNA methylation data (Illumina EPIC array) identified a co‐clustering for MLAs and MAs, which was distinct from clusters of ECs, USCs, CCCs, LGSCs, and HGSCs. Group‐wise comparisons confirmed a close epigenetic relationship between MLA and MA. These findings, in conjunction with the established histological and immunophenotypical overlap, suggest bona fide mesonephric differentiation, and support a more precise terminology of mesonephric‐type adenocarcinoma instead of MLA in these tumours. © 2023 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland. [ABSTRACT FROM AUTHOR]

Compartmentation of the immune response into 3 main spatial cancer-immune phenotypes (SCIs) - inflamed, excluded, and desert - has been proposed as the main predictor of response to immune checkpoint inhibitors in solid tumors. The objective of the study was to define and characterize the SCI in a consecutive series of 213 endometrial carcinomas (ECs) by correlating it with molecular subtypes, clinicopathologic features, and prognosis. Immunohistochemistry (IHC) and next-generation sequencing were used to assign surrogate molecular EC subtypes: POLE mutant (POLE), mismatch repair deficient (MMRd), TP53 mutant (p53abn), and no specific molecular profile (NSMP). Immune cell markers (CD20, CD3, CD8, CD68, PD-L1) were assessed by IHC on whole sections and quantified by digital image analysis to define the 3 SCIs. ECs were stratified into 4 molecular subtypes: 17 (8.0%) POLE, 68 (31.9%) MMRd, 42 (19.7%) p53abn, and 86 (40.4%) NSMP. SCI determination showed 105 (49.3%) inflamed, 62 (29.1%) desert, and 46 (25.6%) excluded tumors. The inflamed phenotype was more prevalent in MMRd (64.7%) and POLE (76.5%) subtypes compared with NSMP (45.3%) and p53abn (21.4%). SCI revealed a strong correlation with disease-free survival in NSMP tumors: inflamed 96.2%, desert 83.2%, and excluded 40.5%. The SCI prognostic impact was also maintained in NSMP cases treated with adjuvant therapy resulting in a significant difference in recurrence between the inflamed and excluded phenotypes. To simplify SCI determination, a subset of immune cell markers was selected as appropriate to define the 3 SCI patterns: high intraepithelial CD8 for the inflamed phenotype; CD68, CD20, and PD-L1 to discriminate between desert and excluded tumors. The integration of SCI into molecular classification could be a promising opportunity to improve the prognostic risk stratification of patients and may guide the therapeutic approach, particularly in the NSMP subtype. Thus, the different patterns of immune response are a new prognostic parameter in the NSMP subtype., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

Objective: Systemic immune, inflammatory, and nutritional indices are prognostic across multiple tumor sites. Comprehensive analysis of these markers in patients with locally advanced cervical cancer (LACC) treated with definitive (chemo)radiotherapy [(C)RT] is limited and may assist with future prognostication., Methods: For this retrospective cohort study, patients with LACC treated with definitive (C)RT were identified from a comprehensive cancer center's clinicopathological database. Pre-treatment indices were derived including systemic immune-inflammation index (SII), platelet lymphocyte ratio (PLR), neutrophil lymphocyte ratio (NLR), monocyte lymphocyte ratio (MLR), albumin to alkaline phosphatase ratio (AAPR) and prognostic nutritional index (PNI). Univariate analysis was performed for PFS and OS. ROC curves were analyzed to determine optimal cut points. PFS and OS were assessed by the Kaplan-Meier method and Log-Rank test. Multivariate analysis was performed using Cox regression., Results: 196 patients were identified: median follow-up 7 years (IQR 2-11). Higher SII (≤700 vs >700; p = 0.01), higher PLR (≤ 250 vs >250; p < 0.001) and higher NLR (≤ 5 vs >5; p = 0.003) were associated with worse PFS. Higher SII (≤700 vs >700: p = 0.02), higher PLR (≤ 250 vs >250: p < 0.001) and higher NLR (≤ 5 vs >5; p = 0.01) were associated with worse OS. On multivariate analysis, SII, NLR and PLR were independently associated with PFS. SII and PLR were independently associated with OS., Conclusions: SII and PLR were independently associated with PFS and OS in patients with LACC treated with definitive (C)RT. NLR was independently associated with PFS. High inflammatory state is associated with shorter survival suggesting this as a target for interventions if validated in future studies., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: MK is a consultant for Helix Biopharma (outside the scope of this study). MK is an Editorial Board Member for Gynecologic Oncology and was not involved in the editorial review or the decision to publish this article. The other authors have no relevant financial or non-financial interests to disclose., (Copyright © 2024 Elsevier Inc. All rights reserved.)