In metastatic cancer, the degree of heterogeneity of the tumor microenvironment (TME) and its molecular underpinnings remain largely unstudied. To characterize the tumor–immune interface at baseline and during neoadjuvant chemotherapy (NACT) in high-grade serous ovarian cancer (HGSOC), we performed immunogenomic analysis of treatment-naive and paired samples from before and after treatment with chemotherapy. In treatment-naive HGSOC, we found that immune-cell-excluded and inflammatory microenvironments coexist within the same individuals and within the same tumor sites, indicating ubiquitous variability in immune cell infiltration. Analysis of TME cell composition, DNA copy number, mutations and gene expression showed that immune cell exclusion was associated with amplification of Myc target genes and increased expression of canonical Wnt signaling in treatment-naive HGSOC. Following NACT, increased natural killer (NK) cell infiltration and oligoclonal expansion of T cells were detected. We demonstrate that the tumor–immune microenvironment of advanced HGSOC is intrinsically heterogeneous and that chemotherapy induces local immune activation, suggesting that chemotherapy can potentiate the immunogenicity of immune-excluded HGSOC tumors.
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Data for this work can be accessed at GitHub (https://github.com/cansysbio/HGSOC_TME_Heterogeneity). Requests for additional data should be directed to the corresponding author. The IF images discussed in this study will be provided by the corresponding author upon request. Microarray data are available through the GEO database (accession number GSE146965). Mutation data are available in Supplementary Table 4a. TITAN copy-number-segment data are available in Supplementary Table 4f. The TCR sequencing data discussed in this study will be provided by the corresponding author upon request.
Software used for this work can be accessed at GitHub (https://github.com/cansysbio/HGSOC_TME_Heterogeneity). Requests for additional custom code should be directed to the corresponding author.
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We thank D. Pe’er for her support to A.J.-S. in finalizing this project. We thank J. Conejo-Garcia for providing the UPK10 cell line. We acknowledge T. Wu for his insightful comments on the manuscript. A.S. was supported by grants from the Marsha Rivkin Organization, Memorial Sloan Kettering Cancer Center, Translational and Integrative Medicine Research Fund (MSKCC) and Kaleidoscope of Hope. This work has been supported in part by a Kaleidoscope of Hope grant (H.A.V. and B.W.) and an MSK Cancer Center Support Grant of the National Cancer Institute at the National Institutes of Health (P30 CA008748). D.Z. received funding from the Ovarian Cancer Research Alliance Liz Tilberis Award. L.M.G. was supported by a Wellcome Trust grant through the Mathematical Genomics and Medicine programme. M.L.M. was supported by a Cancer Research UK core grant (C14303/A17197), a Brown Performance Innovation in Cancer Informatics Discovery Award (BD523775) and the Target Ovarian Cancer Translational Project Grant (Cambridge-MM18). J.D.B. was supported by a Cancer Research UK core grant (A22905). J.D.B. and E.S. were supported by the Mark Foundation for Cancer Research and Cancer Research UK Cambridge Centre (C9685/A25177). A.J.-S. was supported by a doctoral fellowship from the Cancer Research UK Cambridge Institute and the Mexican National Council of Science and Technology (CONACyT). Research by A.J.-S. was funded in part through the NIH/NCI Cancer Center Support Grant (P30 CA008748). J.S.R.-F. is funded in part by a Breast Cancer Research Foundation grant and by Department of Defense Congressionally Directed Medical Research Programs (W81XWH-15-1-0547; GC229671). D.M. was supported by the joint EMBL-EBI and NIHR Cambridge Biomedical Research Centre (EBPOD) postdoctoral program. F.M. was supported by a Cancer Research UK core grant (A19274). R.M.D. is supported by a doctoral fellowship from the Cancer Research UK Cambridge Institute. O.C. was supported by a doctoral fellowship from the University of Cambridge Harding Distinguished Postgraduate Scholars Programme. D.-L.C. was supported by a Cancer Research UK core grant (C14303/A17197). B.W. is funded in part by Breast Cancer Research Foundation and Cycle for Survival grants. G.M. would like to acknowledge the support of the University of Cambridge, Cancer Research UK and Hutchison Whampoa Limited. G.M. was funded by Cancer Research UK grants (C14303/A17197, A19274 and A15973) and by the Instituto de Salud Carlos III (ISCIII), Spanish Ministry of Science and Innovation.
A.S. is a current employee of, and owns stock in, Merck. D.S.C. is a member of two medical advisory boards and invested in two surgical companies, none of which are related to this research. J.S.R.-F. is a paid consultant of Goldman Sachs Merchant Banking, Paige.AI and REPARE Therapeutics; a member of the scientific advisory board with paid honoraria of Paige.AI and Volition Rx; and an ad hoc member of the scientific advisory boards of Roche Tissue Diagnostics, Ventana, InVicro, Genentech, Novartis, GRAIL and Roche, outside the scope of the submitted work. D.Z. reports personal/consultancy fees from Merck, Synlogic Therapeutics, Biomed Valley Discoveries, Trieza Therapeutics, Tesaro and Agenus, outside of the scope of the submitted work. M.L.M. has received honoraria from GSK not related to this research. E.S. is a cofounder and shareholder of Cambridge AI Health and a consultant for Amazon and has received honoraria from GSK; none of these are related to this research. G.M. is founder and CTO of Pinpoint Oncology Ltd. A.J.-S. has owned and sold stocks while this work was in progress, none of which is directly related to this publication.
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Jiménez-Sánchez, A., Cybulska, P., Mager, K.L. et al. Unraveling tumor–immune heterogeneity in advanced ovarian cancer uncovers immunogenic effect of chemotherapy. Nat Genet 52, 582–593 (2020). https://doi.org/10.1038/s41588-020-0630-5
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