Close proximity between cytotoxic T lymphocytes and tumour cells is required for effective immunotherapy. However, what determines the spatial distribution of T cells in the tumour microenvironment is not well understood. Coupling digital pathology and transcriptome analysis on large ovarian tumour cohorts, here we report classification and functionally dissection of tumour-immune contexture in human ovarian cancer.
CD8 IHC and RNAseq analysis were performed on 370 ovarian tumours from the ICON7 phase III clinical trial. Coupling digital pathology with transcriptome analysis, a random forest machine learning algorithm was developed and independently validated for classifying tumour-immune phenotypes in ovarian cancer. Anti-tumour activity of TGFβ blockade in combination with anti-PD-L1 was evaluated in an ovarian cancer mouse model.
We show the identified tumour-immune phenotypes are of biological and clinical importance with interconnection to molecular subtypes and association with clinical outcome in ovarian cancer. Two important hallmarks of T cell exclusion were identified: 1) loss of antigen presentation on tumour cells and 2) upregulation of TGFβ and activated stroma. We identified TGFβ as a key mediator of T cell exclusion. TGFβ reduced MHC class I expression in ovarian cancer cells and induced extracellular matrix (ECM) production and immunosuppressive molecules in human primary fibroblasts. Finally, we demonstrated that combination of anti-TGFβ and anti-PD-L1 in a mouse ovarian cancer model significantly improved the anti-tumour efficacy and survival.
This study provided the first systematic and in-depth characterization of the molecular features and mechanisms underlying the tumour-immune phenotypes in ovarian cancer. We illuminated a multi-faceted role of TGFβ in mediating consequential crosstalk between tumour cells and cancer associated fibroblasts to shape the tumour-immune contexture. Our findings support that targeting the TGFβ pathway represents a promising therapeutic strategy to overcome T cell exclusion and optimize response to cancer immunotherapy.
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All authors have declared no conflicts of interest.