The Evolution of Ovarian Carcinoma Subclassification

The phenotypically informed histotype classification remains the mainstay of ovarian carcinoma subclassification. Histotypes of ovarian epithelial neoplasms have evolved with each edition of the WHO Classification of Female Genital Tumours. The current fifth edition (2020) lists five principal histotypes: high-grade serous carcinoma (HGSC), low-grade serous carcinoma (LGSC), mucinous carcinoma (MC), endometrioid carcinoma (EC) and clear cell carcinoma (CCC). Since histotypes arise from different cells of origin, cell lineage-specific diagnostic immunohistochemical markers and histotype-specific oncogenic alterations can confirm the morphological diagnosis. A four-marker immunohistochemical panel (WT1/p53/napsin A/PR) can distinguish the five principal histotypes with high accuracy, and additional immunohistochemical markers can be used depending on the diagnostic considerations. Histotypes are further stratified into molecular subtypes and assessed with predictive biomarker tests. HGSCs have recently been subclassified based on mechanisms of chromosomal instability, mRNA expression profiles or individual candidate biomarkers. ECs are composed of the same molecular subtypes (POLE-mutated/mismatch repair-deficient/no specific molecular profile/p53-abnormal) with the same prognostic stratification as their endometrial counterparts. Although methylation analyses and gene expression and sequencing showed at least two clusters, the molecular subtypes of CCCs remain largely elusive to date. Mutational and immunohistochemical data on LGSC have suggested five molecular subtypes with prognostic differences. While our understanding of the molecular composition of ovarian carcinomas has significantly advanced and continues to evolve, the need for treatment options suitable for these alterations is becoming more obvious. Further preclinical studies using histotype-defined and molecular subtype-characterized model systems are needed to expand the therapeutic spectrum for women diagnosed with ovarian carcinomas.

Characterization of an Aging-Based Diagnostic Gene Signature and Molecular Subtypes With Diverse Immune Infiltrations in Atherosclerosis

Objective: Advancing age is a major risk factor of atherosclerosis (AS). Nevertheless, the mechanism underlying this phenomenon remains indistinct. Herein, this study conducted a comprehensive analysis of the biological implications of aging-related genes in AS.Methods: Gene expression profiles of AS and non-AS samples were curated from the GEO project. Differential expression analysis was adopted for screening AS-specific aging-related genes. LASSO regression analysis was presented for constructing a diagnostic model, and the discriminatory capacity was evaluated with ROC curves. Through consensus clustering analysis, aging-based molecular subtypes were conducted. Immune levels were estimated based on the expression of HLAs, immune checkpoints, and immune cell infiltrations. Key genes were then identified via WGCNA. The effects of CEBPB knockdown on macrophage polarization were examined with western blotting and ELISA. Furthermore, macrophages were exposed to 100 mg/L ox-LDL for 48 h to induce macrophage foam cells. After silencing CEBPB, markers of cholesterol uptake, esterification and hydrolysis, and efflux were detected with western blotting.Results: This study identified 28 AS-specific aging-related genes. The aging-related gene signature was developed, which could accurately diagnose AS in both the GSE20129 (AUC = 0.898) and GSE43292 (AUC = 0.685) datasets. Based on the expression profiling of AS-specific aging-related genes, two molecular subtypes were clustered, and with diverse immune infiltration features. The molecular subtype–relevant genes were obtained with WGCNA, which were markedly associated with immune activation. Silencing CEBPB triggered anti-inflammatory M2-like polarization and suppressed foam cell formation.Conclusion: Our findings suggest the critical implications of aging-related genes in diagnosing AS and modulating immune infiltrations.

Combined PD-1/PD-L1 and tumor-infiltrating immune cells redefined a unique molecular subtype of high-grade serous ovarian carcinoma

Background High-grade serous ovarian carcinoma is highly heterogeneous, and although many studies have been conducted to identify high-grade serous ovarian carcinoma molecular subtypes that are sensitive to immunotherapy, no precise molecular subtype has been proposed to date. Immune cell infiltration and immune checkpoints are highly correlated with immunotherapy. Here, we investigated immune cell infiltration and immune checkpoint values for prognosis and precise immunotherapy for high-grade serous ovarian carcinoma based on molecular subtype classification. Results “High antigen-presenting cells infiltration molecular subtype of high-grade serous ovarian carcinoma” was identified in immune cell infiltration profiles. Each of the three immune cell infiltration clusters (A, B, and C) demonstrated distinct immune cell characterization, with immune cell infiltration cluster C exhibiting high antigen-presenting cell infiltration, improved prognosis, and higher sensitivity to immunotherapy. Programmed death-1/programmed death ligand 1 has a prognostic and predictive role that can help classify molecular subtypes. Conclusions Our findings redefined a unique molecular subtype of high-grade serous ovarian carcinoma, suggesting that high-grade serous ovarian carcinoma patients with higher antigen-presenting cell infiltration and programmed death-1/programmed death ligand 1 expression can benefit from precise immunotherapy.

Signature Construction and Molecular Subtype Identification Based on Pyroptosis-Related Genes for Better Prediction of Prognosis in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common malignancies worldwide. However, there is a lack of adequate means of treatment prognostication for HCC. Pyroptosis is a newly discovered way of programmed cell death. However, the prognostic role of pyroptosis in HCC has not been thoroughly investigated. Here, we generated a novel prognostic signature to evaluate the prognostic value of pyroptosis-related genes (PRGs) using the data from The Cancer Genome Atlas (TCGA) database. The accuracy of the signature was validated using survival analysis through the International Cancer Genome Consortium cohort ( n = 231 ) and the First Affiliated Hospital of Wenzhou Medical University cohort ( n = 180 ). Compared with other clinical factors, the risk score of the signature was found to be associated with better patient outcomes. The enrichment analysis identified multiple pathways related with pyroptosis in HCC. Furthermore, drug sensitivity testing identified six potential chemotherapeutic agents to provide possible treatment avenues. Interestingly, patients with low risk were confirmed to be associated with lower tumor mutation burden (TMB). However, patients at high risk were found to have a higher count of immune cells. Consensus clustering was performed to identify two main molecular subtypes (named clusters A and B) based on the signature. It was found that compared with cluster B, better survival outcomes and lower TMB were observed in cluster A. In conclusion, signature construction and molecular subtype identification of PRGs could be used to predict the prognosis of HCC, which may provide a specific reference for the development of novel biomarkers for HCC treatment.

Identification of Thrombosis-Related Genes in Patients with Advanced Gastric Cancer: Data from AGAMENON-SEOM Registry

Advanced gastric cancer is one of the most thrombogenic neoplasms. However, genetic mechanisms underlying this complication remain obscure, and the molecular and histological heterogeneity of this neoplasm hinder the identification of thrombotic biomarkers. Therefore, our main objective was to identify genes related to thrombosis regardless of Lauren subtypes. Furthermore, in a secondary exploratory study, we seek to discover thrombosis-associated genes that were specific to each TCGA molecular subtype. We designed a nested case-control study using the cohort of the AGAMENON national advanced gastric cancer registry. Ninety-seven patients were selected—48 with and 49 without venous thromboembolism (using propensity score matching to adjust for confounding factors)—and a differential gene expression array stratified by Lauren histopathological subtypes was carried out in primary tumor samples. For the secondary objective, the aforementioned differential expression analysis was conducted for each TCGA group. Fifteen genes were determined to be associated with thrombosis with the same expression trend in both the intestinal and diffuse subtypes. In thrombotic subjects, CRELD1, KCNH8, CRYGN, MAGEB16, SAA1, ARL11, CCDC169, TRMT61A, RIPPLY3 and PLA2G6 were underexpressed (adjusted-p < 0.05), while PRKD3, MIR5683, SDCBP, EPS8 and CDC45 were overexpressed (adjusted-p < 0.05), and correlated, by logistic regression, with lower or higher thrombotic risk, respectively, in the overall cohort. In each TCGA molecular subtype, we identified a series of genes differentially expressed in thrombosis that appear to be subtype-specific. We have identified several genes associated with venous thromboembolism in advanced gastric cancer that are common to Lauren intestinal and diffuse subtypes. Should these genetic factors be validated in the future, they could be complemented with existing clinical models to bolster the ability to predict thrombotic risk in individuals with advanced gastric adenocarcinoma.

Multiplatform Analysis of Primary and Metastatic Breast Tumors from the AURORA US Network identifies microenvironment and epigenetics drivers of metastasis

Patients with metastatic breast cancer (MBC) typically have short survival times and their successful treatment represents one of most challenging aspects of patient care. This poor prognostic behavior is in part due to molecular features including increased tumor cell clonal heterogeneity, multiple drug resistance mechanisms, and alterations of the tumor microenvironment. The AURORA US Metastasis Project was established with the goal to identify molecular features specifically associated with metastasis. We therefore collected and molecularly characterized specimens from 55 metastatic breast cancer (BC) patients representing 51 primary cancers and 102 metastases. The 153 unique tumors were assayed using RNAseq, tumor/germline DNA exomes and low pass whole genome sequencing, and global DNA methylation microarrays. We found intrinsic molecular subtype differences between primary tumors and their matched metastases to be rare in triple negative breast cancer (TNBC)/Basal-like subtype tumors. Conversely, tumor subtype changes were relatively frequent in estrogen receptor positive (ER+) cancers where ~30% of Luminal A cases switched to Luminal B or HER2-enriched (HER2E) subtypes. Clonal evolution studies identified changes in expression subtype coincident with DNA clonality shifts, especially involving HER2 amplification and/or the HER2E expression subtype. We further found evidence for ER-mediated downregulation of genes involved in cell-cell adhesion in metastases. Microenvironment differences varied according to tumor subtype where ER+/Luminal metastases had lower fibroblast and endothelial cell content, while TNBC/Basal-like metastases showed a dramatic decrease in B cells and T cells. In 17% of metastatic tumors, we identified DNA hypermethylation and/or focal DNA deletions near HLA-A that were associated with its’ significantly reduced expression, and with lower immune cell infiltrates. We also identified low immune cell features in brain and liver metastases when compared to other metastatic sites, even within the same patient. These findings have direct implications for the treatment of metastatic breast cancer patients with immune- and HER2-targeting therapies and suggest potential novel therapeutic avenues for the improvement of outcomes for some patients with MBC.

Fusion Oncogenes Are Associated With Increased Metastatic Capacity and Persistent Disease in Pediatric Thyroid Cancers

PURPOSE In 2014, data from a comprehensive multiplatform analysis of 496 adult papillary thyroid cancer samples reported by The Cancer Genome Atlas project suggested that reclassification of thyroid cancer into molecular subtypes, RAS-like and BRAF-like, better reflects clinical behavior than sole reliance on pathologic classification. The aim of this study was to categorize the common oncogenic variants in pediatric differentiated thyroid cancer (DTC) and investigate whether mutation subtype classification correlated with the risk of metastasis and response to initial therapy in pediatric DTC. METHODS Somatic cancer gene panel analysis was completed on DTC from 131 pediatric patients. DTC were categorized into RAS-mutant ( H-K-NRAS), BRAF-mutant ( BRAF p.V600E), and RET/ NTRK fusion ( RET, NTRK1, and NTRK3 fusions) to determine differences between subtype classification in regard to pathologic data (American Joint Committee on Cancer TNM) as well as response to therapy 1 year after initial treatment had been completed. RESULTS Mutation-based subtype categories were significant in most variables, including age at diagnosis, metastatic behavior, and the likelihood of remission at 1 year. Patients with RET/ NTRK fusions were significantly more likely to have advanced lymph node and distant metastasis and less likely to achieve remission at 1 year than patients within RAS- or BRAF-mut subgroups. CONCLUSION Our data support that genetic subtyping of pediatric DTC more accurately reflects clinical behavior than sole reliance on pathologic classification with patients with RET/ NTRK fusions having worse outcomes than those with BRAF-mutant disease. Future trials should consider inclusion of molecular subtype into risk stratification.

Patient-derived xenograft models capture genomic heterogeneity in endometrial cancer

Background Endometrial cancer (EC) is a major gynecological cancer with increasing incidence. It comprises four molecular subtypes with differing etiology, prognoses, and responses to chemotherapy. In the future, clinical trials testing new single agents or combination therapies will be targeted to the molecular subtype most likely to respond. As pre-clinical models that faithfully represent the molecular subtypes of EC are urgently needed, we sought to develop and characterize a panel of novel EC patient-derived xenograft (PDX) models. Methods Here, we report whole exome or whole genome sequencing of 11 PDX models and their matched primary tumor. Analysis of multiple PDX lineages and passages was performed to study tumor heterogeneity across lineages and/or passages. Based on recent reports of frequent defects in the homologous recombination (HR) pathway in EC, we assessed mutational signatures and HR deficiency scores and correlated these with in vivo responses to the PARP inhibitor (PARPi) talazoparib in six PDXs representing the copy number high/p53-mutant and mismatch-repair deficient molecular subtypes of EC. Results PDX models were successfully generated from grade 2/3 tumors, including three uterine carcinosarcomas. The models showed similar histomorphology to the primary tumors and represented all four molecular subtypes of EC, including five mismatch-repair deficient models. The different PDX lineages showed a wide range of inter-tumor and intra-tumor heterogeneity. However, for most PDX models, one arm recapitulated the molecular landscape of the primary tumor without major genomic drift. An in vivo response to talazoparib was detected in four copy number high models. Two models (carcinosarcomas) showed a response consistent with stable disease and two models (one copy number high serous EC and another carcinosarcoma) showed significant tumor growth inhibition, albeit one consistent with progressive disease; however, all lacked the HR deficiency genomic signature. Conclusions EC PDX models represent the four molecular subtypes of disease and can capture intra-tumor heterogeneity of the original primary tumor. PDXs of the copy number high molecular subtype showed sensitivity to PARPi; however, deeper and more durable responses will likely require combination of PARPi with other agents.

Identification of an at-risk subpopulation with high immune infiltration based on the peroxisome pathway and TIM3 in colorectal cancer

Background Peroxisomes are pivotal metabolic organelles that exist in almost all eukaryote cells. A reduction in numbers and enzymatic activities of peroxisomes was found in colon adenocarcinomas. However, the role of peroxisomes or the peroxisome pathway in colorectal cancer (CRC) is not defined. Methods In the current study, a peroxisome score was calculated to indicate the activity of the peroxisome pathway using gene set variant analysis based on transcriptomic datasets. CIBERSORTx was chosen to infer enriched immune cells for tumors among subgroups. The SubMap algorithm was applied to predict its sensitivity to immunotherapy. Results The patients with a relatively low peroxisome score and high level of T-cell immunoglobulin and mucin domain 3 (TIM-3) presented the worse overall survival than others. Moreover, low peroxisome scores were associated with high infiltration of lymphocytes and poor prognosis in those CRC patients. Thus, a PERLowTIM3High CRC risk subpopulation was identified and characterized by high immune infiltration. The results also showed that CD8 T cells and macrophages highly infiltrated tumors of the PERLowTIM3High group, regardless of consortium molecular subtype and microsatellite instability status. This subgroup had the highest tumor mutational burden and overexpression of immune checkpoint genes. Further, the PERLowTIM3High group showed a higher probability of responding to programmed cell death protein-1-based immunotherapy. In addition, genes involved in peroxisomal metabolic processes in CRC were also investigated since peroxisome is a rather pleiotropic and highly metabolic organelle in cell. The results indicated that only those genes involved in fatty acid alpha oxidation could be used to stratify CRC patients as similar as peroxisome pathway genes. Conclusions We revealed the favorable prognostic value of the peroxisome pathway in CRC and provided a new CRC stratification based on peroxisomes and TIM3, which might be helpful for CRC diagnostics and personalized treatment.

Characteristics of HER2-negative breast cancers with FISH-equivocal status according to 2018 ASCO/CAP guideline

Background According to 2018 ASCO/CAP guideline, HER2 FISH-equivocal breast cancers will be categorized as HER2 negative except those with IHC 3+. However, whether or not HER2 FISH-equivocal breast cancers was a heterogeneous group has not been well illustrated. Methods 195 HER2 FISH-equivocal breast cancer samples were collected from 2014 to 2018. The molecular subtype was identified according to 2013 St Gallen consensus, and HER2 status was also re-determined following 2018 ASCO/CAP guideline. All samples were classified into 4 groups according to the average HER2 copy number (4.0–4.4, 4.5–4.9, 5.0–5.4, 5.5–5.9 signals/cell). The relationship between HER2 copy number and clinicopathological parameters was analyzed. Results 183 (93.8%) of 195 FISH-equivocal cases were classified as luminal-like subtype, while the other 12 (6.2%) were undetermined. Following 2018 ASCO/CAP guideline, all FISH-equivocal cases were recategorized as HER2 negative. Therefore, 31(15.9%) cases were luminal A-like, 152 (77.9%) were luminal B-like (HER2 negative) and 12 (6.2%) were triple negative. The average HER2 copy number showed a positive correlation with chromosome 17 polysomy, but had no significant association with other clinicopathological parameters as well as prognosis. 17 (8.7%) patients were treated with trastuzumab, but showed no difference in prognosis with those who didn’t receive targeted therapy. Conclusions In this study, all HER2 FISH-equivocal breast cancers were recategorized as HER2 negative according to 2018 ASCO/CAP guideline. Most of these patients were luminal B-like (HER2 negative). The average HER2 copy number had no significant association with clinicopathological parameters, as well as prognosis.