T cell–induced CSF1 promotes melanoma resistance to PD1 blockade

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Abstract

Colony-stimulating factor 1 (CSF1) is a key regulator of monocyte/macrophage differentiation that sustains the protumorigenic functions of tumor-associated macrophages (TAMs). We show that CSF1 is expressed in human melanoma, and patients with metastatic melanoma have increased CSF1 in blood compared to healthy subjects. In tumors, CSF1 expression correlated with the abundance of CD8 + T cells and CD163 + TAMs. Human melanoma cell lines consistently produced CSF1 after exposure to melanoma-specific CD8 + T cells or T cell–derived cytokines in vitro, reflecting a broadly conserved mechanism of CSF1 induction by activated CD8 + T cells. Mining of publicly available transcriptomic data sets suggested co-enrichment of CD8 + T cells with CSF1 or various TAM-specific markers in human melanoma, which was associated with nonresponsiveness to programmed cell death protein 1 (PD1) checkpoint blockade in a smaller patient cohort. Combination of anti-PD1 and anti–CSF1 receptor (CSF1R) antibodies induced the regression of BRAF V600E -driven, transplant mouse melanomas, a result that was dependent on the effective elimination of TAMs. Collectively, these data implicate CSF1 induction as a CD8 + T cell–dependent adaptive resistance mechanism and show that simultaneous CSF1R targeting may be beneficial in melanomas refractory to immune checkpoint blockade and, possibly, other T cell–based therapies.

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The Cancer Genome Atlas revealed the genomic landscapes of human cancers. In parallel, immunotherapy is transforming the treatment of advanced cancers. Unfortunately, the majority of patients do not respond to immunotherapy, making the identification of predictive markers and the mechanisms of resistance an area of intense research. To increase our understanding of tumor-immune cell interactions, we characterized the intratumoral immune landscapes and the cancer antigenomes from 20 solid cancers and created The Cancer Immunome Atlas (https://tcia.at/). Cellular characterization of the immune infiltrates showed that tumor genotypes determine immunophenotypes and tumor escape mechanisms. Using machine learning, we identified determinants of tumor immunogenicity and developed a scoring scheme for the quantification termed immunophenoscore. The immunophenoscore was a superior predictor of response to anti-cytotoxic T lymphocyte antigen-4 (CTLA-4) and anti-programmed cell death protein 1 (anti-PD-1) antibodies in two independent validation cohorts. Our findings and this resource may help inform cancer immunotherapy and facilitate the development of precision immuno-oncology.