Eleni Maniati

High-Grade Serous Ovarian Carcinoma in the Genomics Era: Current Applications, Challenges and Future Directions

High-grade serous ovarian carcinoma (HGSOC) is characterised by profound genomic instability and limited durable responses to standard therapy, leading to poor prognosis. The use of next-generation sequencing technologies has improved understanding of its molecular landscape, revealing consistent Tumour Protein p53 (TP53) mutations, homologous recombination defects, pathway alterations, and epigenetic dysregulation. Such genomic profiling now underpins the classification criteria between the ovarian cancer subtypes described by the Cancer Genome Atlas. Widespread chromosomal instability and pathogenic variants in multiple genes distinguish HGSOC from other subtypes of ovarian cancer and, further, from low-grade serous ovarian cancer. Importantly, the new-found understanding of the genomic landscape of HGSOC guides the use of platinum-based chemotherapies and Poly(ADP-ribose) Polymerase (PARP) inhibitors, with homologous recombination deficiency emerging as a cancer vulnerability that enhances treatment response. A combined multi-omics approach integrates transcriptomics, proteomics, metabolomics, and epigenomics to further the understanding of the characteristics, therapeutic targets and treatment resistance within HGSOC. Despite these advances, major challenges persist, including intratumoural heterogeneity and the poor diversity of genomic datasets. Artificial Intelligence (AI) technology, Clustered regularly interspaced short palindromic repeats (CRISPR)-based gene editing, neoantigen-guided immunotherapy and ovarian cancer vaccination indicate a promising future for genomics-guided interventions and support the integration of genomics within multi-omic approaches to improve HGSOC outcomes.

Specific Mechanisms of Chromosomal Instability Indicate Therapeutic Sensitivities in High-Grade Serous Ovarian Carcinoma

Abstract Chromosomal instability (CIN) comprises continual gain and loss of chromosomes or parts of chromosomes and occurs in the majority of cancers, often conferring poor prognosis. Because of a scarcity of functional studies and poor understanding of how genetic or gene expression landscapes connect to specific CIN mechanisms, causes of CIN in most cancer types remain unknown. High-grade serous ovarian carcinoma (HGSC), the most common subtype of ovarian cancer, is the major cause of death due to gynecologic malignancy in the Western world, with chemotherapy resistance developing in almost all patients. HGSC exhibits high rates of chromosomal aberrations and knowledge of causative mechanisms would represent an important step toward combating this disease. Here we perform the first in-depth functional characterization of mechanisms driving CIN in HGSC in seven cell lines that accurately recapitulate HGSC genetics. Multiple mechanisms coexisted to drive CIN in HGSC, including elevated microtubule dynamics and DNA replication stress that can be partially rescued to reduce CIN by low doses of paclitaxel and nucleoside supplementation, respectively. Distinct CIN mechanisms indicated relationships with HGSC-relevant therapy including PARP inhibition and microtubule-targeting agents. Comprehensive genomic and transcriptomic profiling revealed deregulation of various genes involved in genome stability but were not directly predictive of specific CIN mechanisms, underscoring the importance of functional characterization to identify causes of CIN. Overall, we show that HGSC CIN is complex and suggest that specific CIN mechanisms could be used as functional biomarkers to indicate appropriate therapy. Significance: These findings characterize multiple deregulated mechanisms of genome stability that lead to CIN in ovarian cancer and demonstrate the benefit of integrating analysis of said mechanisms into predictions of therapy response.

The Tumor Microenvironment of Clear-Cell Ovarian Cancer

Abstract Some patients with advanced clear-cell ovarian cancer (CCOC) respond to immunotherapy; however, little is known about the tumor microenvironment (TME) of this relatively rare disease. Here, we describe a comprehensive quantitative and topographical analysis of biopsies from 45 patients, 9 with Federation Internationale des Gynaecologistes et Obstetristes (FIGO) stage I/II (early CCOC) and 36 with FIGO stage III/IV (advanced CCOC). We investigated 14 immune cell phenotype markers, PD-1 and ligands, and collagen structure and texture. We interrogated a microarray data set from a second cohort of 29 patients and compared the TMEs of ARID1A-wildtype (ARID1Awt) versus ARID1A-mutant (ARID1Amut) disease. We found significant variations in immune cell frequency and phenotype, checkpoint expression, and collagen matrix between the malignant cell area (MCA), leading edge (LE), and stroma. The MCA had the largest population of CD138+ plasma cells, the LE had more CD20+ B cells and T cells, whereas the stroma had more mast cells and αSMA+ fibroblasts. PD-L2 was expressed predominantly on malignant cells and was the dominant PD-1 ligand. Compared with early CCOC, advanced-stage disease had significantly more fibroblasts and a more complex collagen matrix, with microarray analysis indicating “TGFβ remodeling of the extracellular matrix” as the most significantly enriched pathway. Data showed significant differences in immune cell populations, collagen matrix, and cytokine expression between ARID1Awt and ARID1Amut CCOC, which may reflect different paths of tumorigenesis and the relationship to endometriosis. Increased infiltration of CD8+ T cells within the MCA and CD4+ T cells at the LE and stroma significantly associated with decreased overall survival.

Immune Mechanisms of Resistance to Cediranib in Ovarian Cancer

Abstract This article investigates mechanisms of resistance to the VEGF receptor inhibitor cediranib in high-grade serous ovarian cancer (HGSOC), and defines rational combination therapies. We used three different syngeneic orthotopic mouse HGSOC models that replicated the human tumor microenvironment (TME). After 4 to 5 weeks treatment of established tumors, cediranib had antitumor activity with increased tumor T-cell infiltrates and alterations in myeloid cells. However, continued cediranib treatment did not change overall survival or the immune microenvironment in two of the three models. Moreover, treated mice developed additional peritoneal metastases not seen in controls. Cediranib-resistant tumors had intrinsically high levels of IL6 and JAK/STAT signaling and treatment increased endothelial STAT3 activation. Combination of cediranib with a murine anti-IL6 antibody was superior to monotherapy, increasing mouse survival, reducing blood vessel density, and pSTAT3, with increased T-cell infiltrates in both models. In a third HGSOC model, that had lower inherent IL6 JAK/STAT3 signaling in the TME but high programmed cell death protein 1 (PD-1) signaling, long-term cediranib treatment significantly increased overall survival. When the mice eventually relapsed, pSTAT3 was still reduced in the tumors but there were high levels of immune cell PD-1 and Programmed death-ligand 1. Combining cediranib with an anti–PD-1 antibody was superior to monotherapy in this model, increasing T cells and decreasing blood vessel densities. Bioinformatics analysis of two human HGSOC transcriptional datasets revealed distinct clusters of tumors with IL6 and PD-1 pathway expression patterns that replicated the mouse tumors. Combination of anti-IL6 or anti–PD-1 in these patients may increase activity of VEGFR inhibitors and prolong disease-free survival.

Immunotherapy that improves response to chemotherapy in high-grade serous ovarian cancer

AbstractSingle-cell RNA sequencing (scRNAseq) of tumour-infiltrating immune cells in high-grade serous ovarian cancer (HGSOC) omental biopsies reveals potential targets that could enhance response to neo-adjuvant chemotherapy (NACT). Analysis of 64,097 cells identifies NACT-induced overexpression of stabilin-1 (clever-1) on macrophages and FOXP3 in Tregs that is confirmed at the protein level. STAB1 inhibition in vitro induces anti-tumour macrophages. FOXP3 anti-sense oligonucleotide (FOXP3-ASO), repolarises Tregs to an effector T cell phenotype. ScRNAseq on 69,781 cells from an HGSOC syngeneic mouse model recapitulates the patients’ data. Combining chemotherapy with anti-stabilin1 antibody and/or Foxp3-ASO significantly increases survival of mice with established peritoneal disease in two HGSOC syngeneic models and progression-free survival in a third model. Long-term survivors (300 days + ) are resistant to tumour rechallenge. Anti-stabilin1 antibody enriches the tumours with CXCL9+ macrophages and Foxp3-ASO increases TBET cell infiltration. Our results suggest that targeting these molecules in immune cells may improve chemotherapy response in patients.

Human 3D Ovarian Cancer Models Reveal Malignant Cell–Intrinsic and –Extrinsic Factors That Influence CAR T-cell Activity

Abstract In vitro preclinical testing of chimeric antigen receptor (CAR) T cells is mostly carried out in monolayer cell cultures. However, alternative strategies are needed to take into account the complexity and the effects of the tumor microenvironment. Here, we describe the modulation of CAR T-cell activity by malignant cells and fibroblasts in human three-dimensional (3D) in vitro cell models of increasing complexity. In models combining mucin-1 (MUC1) and TnMUC1 CAR T cells with human high-grade serous ovarian cancer cell spheroids, malignant cell–intrinsic resistance to CAR T-cell killing was due to defective death receptor signaling involving TNFα. Adding primary human fibroblasts to spheroids unexpectedly increased the ability of CAR T cells to kill resistant malignant cells as CCL2 produced by fibroblasts activated CCR2/4+ CAR T cells. However, culturing malignant cells and fibroblasts in collagen gels engendered production of a dense extracellular matrix that impeded CAR T-cell activity in a TGFβ-dependent manner. A vascularized microfluidic device was developed that allowed CAR T cells to flow through the vessels and penetrate the gels in a more physiological way, killing malignant cells in a TNFα-dependent manner. Complex 3D human cell models may provide an efficient way of screening multiple cytotoxic human immune cell constructs while also enabling evaluation of mechanisms of resistance involving cell–cell and cell–matrix interactions, thus accelerating preclinical research on cytotoxic immune cell therapies in solid tumors. Significance: Three-dimensional in vitro models of increasing complexity uncover mechanisms of resistance to CAR T cells in solid tumors, which could help accelerate development of improved CAR T-cell constructs.