BackgroundAbundant evidence shows that triple-negative breast cancer (TNBC) is heterogeneous, and many efforts have been devoted to identifying TNBC subtypes on the basis of genomic profiling. However, few studies have explored the classification of TNBC specifically based on immune signatures that may facilitate the optimal stratification of TNBC patients responsive to immunotherapy.MethodsUsing four publicly available TNBC genomics datasets, we classified TNBC on the basis of the immunogenomic profiling of 29 immune signatures. Unsupervised and supervised machine learning methods were used to perform the classification.ResultsWe identified three TNBC subtypes that we named Immunity High (Immunity_H), Immunity Medium (Immunity_M), and Immunity Low (Immunity_L) and demonstrated that this classification was reliable and predictable by analyzing multiple different datasets. Immunity_H was characterized by greater immune cell infiltration and anti-tumor immune activities, as well as better survival prognosis compared to the other subtypes. Besides the immune signatures, some cancer-associated pathways were hyperactivated in Immunity_H, including apoptosis, calcium signaling, MAPK signaling, PI3K–Akt signaling, and RAS signaling. In contrast, Immunity_L presented depressed immune signatures and increased activation of cell cycle, Hippo signaling, DNA replication, mismatch repair, cell adhesion molecule binding, spliceosome, adherens junction function, pyrimidine metabolism, glycosylphosphatidylinositol (GPI)-anchor biosynthesis, and RNA polymerase pathways. Furthermore, we identified a gene co-expression subnetwork centered around five transcription factor (TF) genes (CORO1A, STAT4, BCL11B, ZNF831, and EOMES) specifically significant in the Immunity_H subtype and a subnetwork centered around two TF genes (IRF8 and SPI1) characteristic of the Immunity_L subtype.ConclusionsThe identification of TNBC subtypes based on immune signatures has potential clinical implications for TNBC treatment.Electronic supplementary materialThe online version of this article (10.1186/s13046-018-1002-1) contains supplementary material, which is available to authorized users.

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CD73 is a glycosylphosphatidylinositol (GPI)‐anchored protein that attenuates tumour immunity via cooperating with CD39 to generate immunosuppressive adenosine. Therefore, CD73 blockade has been incorporated into clinical trials for cancers based on preclinical efficacy. However, the biological role and underlying mechanism of CD73 in pancreatic cancer (PC) microenvironment and its prognostic impact have not been comprehensively studied. In this article, we found that the expression of CD73 was up‐regulated in PC tissues and patients with higher CD73 expression had poorer overall survival (OS) and disease‐free survival (DFS) in multiple publicly available databases. Higher CD73 expression was significantly associated with its reduced methylation, and only the hypomethylation of CpG site at cg23172664 was obviously correlated with poorer OS. Then, Metascape analysis and GSEA showed that CD73 may play an important role in PC progression and immune regulations. Notably, CD73 was verified to be negatively correlated with infiltrating levels of CD8 + T cells and γδ + T cells in both TCGA and GEO cohorts via the CIBERSORT algorithm. In addition, patients with higher CD73 expression also tended to have higher PD‐L1 expression and tumour mutation load. It seemed that CD73 might be a promising biomarker for the response to the anti‐PD‐1/PD‐L1 treatment in PC. In conclusion, these results reveal that CD73 may function as a promotor in cancer progression and a regulator in immune patterns via CD73‐related pathways. Blockade of CD73 might be a promising therapeutic strategy for PC.