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Infiltration of myeloid-derived suppressor cells (MDSCs) leads to Immunosuppressive tumor microenvironment (TME), which is one of the major causes for low objective response rates of immune checkpoint blockade (ICB) therapy. Here, we report that chemical inhibition of p38α reverses this MDSC-induced immunosuppressive TME and improves the immunotherapy efficacy in triple negative breast cancer (TNBC). Firstly, by combining the tumor immunological phenotype (TIP) gene signature and high throughput sequencing based high throughput screening (HTS2), we identified that ponatinib significantly inhibits the expression of “cold” tumor associated chemokines CXCL1 and CXCL2 in cancer cells. This inhibition decreases the infiltration of MDSCs and consequently increased the accumulation of “hot” tumor associated T cells and NK cells and thus reverses the immunosuppressive TME. Then, by multiple preclinical models, we found that ponatinib significantly inhibits tumor growth in a TME-dependent manner and enhances the efficacy of anti-PD-L1 immunotherapy on TNBCin vivo. Notably, ponatinib exhibits no significant inhibition on immune cells in mouse spleens. Mechanistically, ponatinib directly inhibits the kinase activity of p38α, which results in the reduction of the phosphorylation of STAT1 at Ser727, and thus the decreased expression of CXCL1 and CXCL2 in cancer cells. Our study provided the therapeutic potential of combining p38α inhibition with ICB for the treatment of TNBC.

SummaryImmune checkpoint inhibitors (ICIs) are a breakthrough in oncology treatment, and studies of screening predictive biomarkers of ICIs are emerging. We developed a web server named IMPACT (http://impact.brbiotech.com/) to thoroughly explore immunotherapeutic predictive or prognostic biomarkers. IMPACT contains a large dataset of 6,276 patients treated with ICIs and integrates 11 well-designed function modules, enabling an in-depth solution for biomarkers exploration. Compared with the existing tools, IMPACT was implemented with one exclusive module for interaction analysis and several optimized conventional functions for discovering novel biomarkers. Specifically, the interaction analysis of biomarker-treatment effect is essential to determine whether a biomarker is predictive and/or prognostic for ICIs. Moreover, several optimized functions allow complicated biomarker exploration, including customized selections of variant types in more detail, automatically screening meaningful co-mutations among multiple genes, and selecting cut-off values for gene expression biomarkers. In summary, IMPACT is a comprehensive analysis resource to facilitate biomarker research of ICIs.

SUMMARYTumor metastasis is the cause of death for 90% of cancer patients, and no currently-available therapies target this multi-step process in which cancer cells spread from the local tissue of a primary tumor to distant organs where they establish secondary tumors1. Although epithelial-to-mesenchymal transition2, tumor-secreted exosomes3, epigenetic regulators as well as other genes4-8 have been implicated in metastasis, little is known about how cells adapt to and colonize new tissue environments. Here, we show that the epigenetics-mediated reprogramming of tissue-specific gene transcription in cancer cells promotes metastasis. Using colorectal cancer (CRC) as a model, we found in both clinical and cell line studies that metastatic CRC cells lose their colon-specific gene transcription program and gain a liver-specific gene transcription program as they metastasize in the liver. Further, we found this transcription reprogramming is driven by a reshaped epigenetic landscape of both typical and super-enhancers. Chemical inhibition of enhancer activity disrupts the ability of cells to execute altered transcription programs and consequently inhibits metastasis. Binding motif analysis of the enhancers in liver metastatic CRC cells identified the liver-specific transcription factor FOXA2 as a key regulator, and knocking down of FOXA2 expression prevents the colonization of metastatic CRC cells in the liver of a mice xenograft model. These results, together with additional observations of similar reprogramming in several cohorts of clinical CRC tumor samples and in multiple other forms of metastatic cancers, indicate that this reprogramming may be a common feature of metastasis in multiple cancers and suggest the targeted disruption of this epigenetic reprogramming as a strategy for the development of therapies to treat metastasis, the leading cause of cancer-related mortality.