In metastatic cancer, the role of heterogeneity at the tumor-immune microenvironment, its molecular underpinnings and clinical relevance remain largely unexplored. To understand tumor-immune dynamics at baseline and upon chemotherapy treatment, we performed unbiased pathway and cell type-specific immunogenomics analysis of treatment-naive (38 5 samples from 8 patients) and paired chemotherapy treated (80 paired samples from 40 patients) high-grade serous ovarian cancer (HGSOC) samples. Whole transcriptome analysis and imagebased quantification of T cells from treatment-naive tumors revealed ubiquitous variability in immune signaling and distinct immune microenvironments co-existing within the same individuals and within tumor deposits at diagnosis. To systematically explore cell type composition of the tumor microenvironment using bulk mRNA, we derived consensus immune and stromal cell gene signatures by intersecting state-of-the-art deconvolution methods, providing improved accuracy and sensitivity when compared to HGSOC immunostaining and leukocyte methylation data sets. Cell-type deconvolution and pathway analyses revealed that Myc and Wnt signaling associate with immune cell exclusion in untreated HGSOC. To evaluate the effect of chemotherapy on the intrinsic tumor-immune heterogeneity, we compared sitematched and site-unmatched tumors before and after neoadjuvant chemotherapy.Transcriptomic and T-cell receptor sequencing analyses showed that site-matched samples had increased cytotoxic immune activation and oligoclonal expansion of T cells after chemotherapy, which was not seen in site-unmatched samples where heterogeneity could not be accounted for. These results demonstrate that the tumor-immune interface in advanced HGSOC is intrinsically heterogeneous, and thus requires site-specific analysis to reliably unmask the impact of therapy on the tumor-immune microenvironment..

High-grade serous ovarian cancer (HGSOC) is an archetypal cancer of genomic instability1–4 patterned by distinct mutational processes5,6, tumour heterogeneity7–9 and intraperitoneal spread7,8,10. Immunotherapies have had limited efficacy in HGSOC11–13, highlighting an unmet need to assess how mutational processes and the anatomical sites of tumour foci determine the immunological states of the tumour microenvironment. Here we carried out an integrative analysis of whole-genome sequencing, single-cell RNA sequencing, digital histopathology and multiplexed immunofluorescence of 160 tumour sites from 42 treatment-naive patients with HGSOC. Homologous recombination-deficient HRD-Dup (BRCA1 mutant-like) and HRD-Del (BRCA2 mutant-like) tumours harboured inflammatory signalling and ongoing immunoediting, reflected in loss of HLA diversity and tumour infiltration with highly differentiated dysfunctional CD8+ T cells. By contrast, foldback-inversion-bearing tumours exhibited elevated immunosuppressive TGFβ signalling and immune exclusion, with predominantly naive/stem-like and memory T cells. Phenotypic state associations were specific to anatomical sites, highlighting compositional, topological and functional differences between adnexal tumours and distal peritoneal foci. Our findings implicate anatomical sites and mutational processes as determinants of evolutionary phenotypic divergence and immune resistance mechanisms in HGSOC. Our study provides a multi-omic cellular phenotype data substrate from which to develop and interpret future personalized immunotherapeutic approaches and early detection research.

Patients with high-grade serous ovarian cancer suffer poor prognosis and variable response to treatment. Known prognostic factors for this disease include homologous recombination deficiency status, age, pathological stage and residual disease status after debulking surgery. Recent work has highlighted important prognostic information captured in computed tomography and histopathological specimens, which can be exploited through machine learning. However, little is known about the capacity of combining features from these disparate sources to improve prediction of treatment response. Here, we assembled a multimodal dataset of 444 patients with primarily late-stage high-grade serous ovarian cancer and discovered quantitative features, such as tumor nuclear size on staining with hematoxylin and eosin and omental texture on contrast-enhanced computed tomography, associated with prognosis. We found that these features contributed complementary prognostic information relative to one another and clinicogenomic features. By fusing histopathological, radiologic and clinicogenomic machine-learning models, we demonstrate a promising path toward improved risk stratification of patients with cancer through multimodal data integration.

In metastatic cancer, the role of heterogeneity at the tumor-immune microenvironment, its molecular underpinnings and clinical relevance remain largely unexplored. To understand tumor-immune dynamics at baseline and upon chemotherapy treatment, we performed unbiased pathway and cell type-specific immunogenomics analysis of treatment-naive (38 5 samples from 8 patients) and paired chemotherapy treated (80 paired samples from 40 patients) high-grade serous ovarian cancer (HGSOC) samples. Whole transcriptome analysis and imagebased quantification of T cells from treatment-naive tumors revealed ubiquitous variability in immune signaling and distinct immune microenvironments co-existing within the same individuals and within tumor deposits at diagnosis. To systematically explore cell type 10 composition of the tumor microenvironment using bulk mRNA, we derived consensus immune and stromal cell gene signatures by intersecting state-of-the-art deconvolution methods, providing improved accuracy and sensitivity when compared to HGSOC immunostaining and leukocyte methylation data sets. Cell-type deconvolution and pathway analyses revealed that Myc and Wnt signaling associate with immune cell exclusion in untreated HGSOC. To evaluate 15 the effect of chemotherapy on the intrinsic tumor-immune heterogeneity, we compared sitematched and site-unmatched tumors before and after neoadjuvant chemotherapy.Transcriptomic and T-cell receptor sequencing analyses showed that site-matched samples had increased cytotoxic immune activation and oligoclonal expansion of T cells after chemotherapy, which was not seen in site-unmatched samples where heterogeneity could not be accounted 20for. These results demonstrate that the tumor-immune interface in advanced HGSOC is intrinsically heterogeneous, and thus requires site-specific analysis to reliably unmask the impact of therapy on the tumor-immune microenvironment. 1050 Conceptualization [Ideas; formulation or evolution of overarching research goals and aims] AS, AJS, MLM, ES Data curation [Management activities to annotate (produce metadata), scrub data and maintain research data (including software code, where necessary for interpreting the data itself) for 1055 initial use and later re-use] AJS, KL, PC Formal analysis [Application of statistical, mathematical, computational, or other formal techniques to analyse or synthesize study data] 1060 AJS Funding acquisition [Acquisition of the financial support for the project leading to this publication] AV, ES, AS, MLM 1065 Investigation [Conducting a research and investigation process, specifically performing the experiments, or data/evidence collection] PC, KL, TW, YM, IN, BW, DC, ES 1070 50 Methodology [Development or design of methodology; creation of models] ES Project administration [Management and coordination responsibility for the research activity planning and execution] 1075 AS, MLM, ES Resources [Provision of study materials, reagents, materials, patients, laboratory samples, animals, instrumentation, computing resources, or other a...

Purpose: Fumarate hydratase–deficient renal cell carcinoma (FH-RCC) is a rare, aggressive form of RCC associated with hereditary leiomyomatosis and RCC syndrome. Evidence for systemic therapy efficacy is lacking. Experimental Design: We studied clinical and genomic characteristics of FH-RCC, including response [objective response rate (ORR)] to systemic therapies and next-generation sequencing (NGS). Patients with metastatic FH-RCC, defined by presence of pathogenic germline or somatic FH mutation plus IHC evidence of FH loss, were included. Results: A total of 28 of 32 included patients (median age 46; range, 20–74; M:F, 20:12) underwent germline testing; 23 (82%) harbored a pathogenic FH germline variant. Five (16%) were negative for germline FH mutations; all had biallelic somatic FH loss. Somatic NGS (31/32 patients) revealed co-occurring NF2 mutation most frequently (n = 5). Compared with clear-cell RCC, FH-RCC had a lower mutation count (median 2 vs. 4; P < 0.001) but higher fraction of genome altered (18.7% vs. 10.3%; P = 0.001). A total of 26 patients were evaluable for response to systemic therapy: mTOR/VEGF combination (n = 18, ORR 44%), VEGF monotherapy (n = 15, ORR 20%), checkpoint inhibitor therapy (n = 8, ORR 0%), and mTOR monotherapy (n = 4, ORR 0%). No complete responses were seen. Median overall and progression-free survival were 21.9 months [95% confidence interval (CI): 14.3–33.8] and 8.7 months (95% CI: 4.8–12.3), respectively. Conclusions: Although most FH-RCC tumors are due to germline FH alterations, a significant portion result from biallelic somatic FH loss. Both somatic and germline FH-RCC have similar molecular characteristics, with NF2 mutations, low tumor mutational burden, and high fraction of genome altered. Although immunotherapy alone produced no objective responses, combination mTOR/VEGF therapy showed encouraging results.