Immune infiltration of colorectal cancer (CRC) is closely associated with clinical outcome. However, previous work has not accounted for the diversity of functionally distinct cell types that make up the immune response. In this study, based on a deconvolution algorithm (known as CIBERSORT) and clinical annotated expression profiles, we comprehensively analyzed the tumor‐infiltrating immune cells present in CRC for the first time. The fraction of 22 immune cells subpopulations was evaluated to determine the associations between each cell type and survival and response to chemotherapy. As a result, profiles of immune infiltration vary significantly between paired cancer and paracancerous tissue and the variation could characterize the individual differences. Of the cell subpopulations investigated, tumors lacking M1 macrophages or with an increased number of M2 macrophages, eosinophils, and neutrophils were associated with the poor prognosis. Unsupervised clustering analysis using immune cell proportions revealed five subgroups of tumors, largely defined by the balance between macrophages M1, M2, and NK resting cells, with distinct survival patterns, and associated with well‐established molecular subtype. Collectively, our data suggest that subtle differences in the cellular composition of the immune infiltrate in CRC appear to exist, and these differences are likely to be important determinants of both prognosis and response to treatment.

BackgroundMetastasis is a major threat to colorectal cancer (CRC) patients. We have reported that peroxiredoxin-2 (PRDX2) is associated with CRC invasion and metastasis. However, the mechanisms regulating PRDX2 expression remain unclear. We investigate whether microRNAs (miRNAs) regulate PRDX2 expression in CRC progression.MethodsQuantitative real-time polymerase chain reaction (qPCR) was used to measure microRNA-200b-3p (miR-200b-3p) expression. Immunohistochemistry (IHC) was performed to detect c-Myc and PRDX2 protein levels in CRC tissue samples (n = 97). Western blot was used to quantify PRDX2, c-Myc, AKT2/GSK3β pathway-associated proteins and epithelial-mesenchymal transition (EMT)-related proteins in CRC cells. Luciferase reporter assays were used to analyze the interaction between miR-200b-3p and 3′untranslated region (3′UTR) of PRDX2 mRNA and AKT2 mRNA as well as c-Myc and the miR-200b-3p promoter. Chromatin immunoprecipitation (ChIP) assay was used to evaluate binding of c-Myc to the miR-200b-3p promoter. Invasive assay and metastatic model were used to assess invasive and metastatic capacities of CRC cells in vitro and in vivo. Moreover, drug-induced apoptosis was measured by flow cytometry.ResultsWe found that miR-200b-3p was significantly downregulated, whereas c-Myc and PRDX2 were upregulated in metastatic CRC cells and CRC tissues compared to their counterparts. An inverse correlation existed between c-Myc and miR-200b-3p, and between miR-200b-3p and PRDX2. We also found that PRDX2 was a target of miR-200b-3p. Importantly, overexpression of nontargetable PRDX2 eliminated the suppressive effects of miR-200b-3p on proliferation, invasion, EMT, chemotherapeutic resistance and metastasis of CRC cells. Moreover, c-Myc bound to the promoter of miR-200b-3p and repressed its transcription. In turn, miR-200b-3p disrupted the stability of c-Myc protein by inducing c-Myc protein threonine 58 (T58) phosphorylation and serine 62 (S62) dephosphorylation via AKT2/GSK3β pathway.ConclusionsOur findings reveal that the c-Myc/miR-200b/PRDX2 loop regulates CRC progression and its disruption enhances tumor metastasis and chemotherapeutic resistance in CRC.Electronic supplementary materialThe online version of this article (10.1186/s12967-017-1357-7) contains supplementary material, which is available to authorized users.

Cancer stem cells (CSCs) are a key target for reducing tumor growth, metastasis, and recurrence. Redox status is a critical factor in the maintenance of CSCs, and the antioxidant enzyme Peroxiredoxin 2 (Prdx2) plays an important role in the development of colon cancer. Therefore, we investigated the contribution of Prdx2 to the maintenance of stemness of colon CSCs. Here, we used short-hairpin RNAs and a Prdx2-overexpression vector to determine the effects of Prdx2. We demonstrated that knockdown of Prdx2 reduced the self-renewal and sphere formation and resulted in increased 5-FU-induced apoptosis in human colon CSCs. Prdx2 overexpression induced reversion of the self-renewal and sphere formation. Furthermore, the effects of Prdx2 resulted in an altered expression of stemness associated with the Hh/Gli1 signaling pathway. Finally, knockdown of Prdx2 in CD133+ cells reduced the volume of xenograft tumors in BALB/c-nu mice. Taken together, colon CSCs overexpress Prdx2, which promotes their stem cell properties via the Hh/Gli1 signaling pathway. The results suggest that Prdx2 may be an effective therapeutic target for the elimination of CSCs in colorectal cancer.

Although the outcome of patients with colorectal cancer (CRC) has improved significantly, prognosis evaluation still presents challenges due to the disease heterogeneity. Increasing evidences revealed the close correlation between aberrant expression of certain RNAs and the prognosis. We envisioned that combined multiple types of RNAs into a single classifier could improve postoperative risk classification and add prognostic value to the current stage system. Firstly, differentially expressed RNAs including mRNAs, miRNAs and lncRNAs were identified by two different algorithms. Then survival and LASSO analysis was conducted to screen survival-related DERs and build a multi-RNA-based classifier for CRC patient stratification. The prognostic value of the classifier was self-validated in the TCGA CRC cohort and further validated in an external independent set. Finally, survival receiver operating characteristic analysis was used to assess the performance of prognostic prediction. We found that the multi-RNA-based classifier consisted by 12 mRNAs, 1miRNA and 1 lncRNA, which could divide the patients into high and low risk groups with significantly different overall survival (training set: HR 2.54, 95%CI 1.67-3.87, p<0.0001; internal testing set: HR 2.54, 95%CI 1.67-3.87, p<0.0001; validation set: HR 5.02, 95% CI 2.2–11.6; p=0·0002). In addition, the classifier is not only independent of clinical features but also with a similar prognostic ability to the well-established TNM stage (AUC of ROC 0.83 versus 0.74, 95% CI = 0.608-0.824, P =0.0878). Furthermore, combination of the multi-RNA-based classifier with clinical features was a more powerful predictor of prognosis than either of the two parameters alone. In conclusion, the multi-RNA-based classifier may have important clinical implications in the selection of patients with CRC who are at high risk of mortality and add prognostic value to the current stage system.

Although hundreds of colorectal cancer- (CRC-) related genes have been screened, the significant hub genes still need to be further identified. The aim of this study was to identify the hub genes based on protein-protein interaction network and uncover their clinical value. Firstly, 645 CRC patients' data from the Tumor Cancer Genome Atlas were downloaded and analyzed to screen the differential expression genes (DEGs). And then, the Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis was performed, and PPI network of the DEGs was constructed by Cytoscape software. Finally, four hub genes (CXCL3, ELF5, TIMP1, and PHLPP2) were obtained from four subnets and further validated in our clinical setting and TCGA dataset. The results showed that mRNA expression of CXCL3, ELF5, and TIMP1 was increased in CRC tissues, whereas PHLPP2 mRNA expression was decreased. More importantly, high expression of CXCL3, ELF5, and TIMP1 was significantly associated with lymphatic invasion, distance metastasis, and advanced tumor stage. In addition, a shorter overall survival was observed in patients with increased CXCL3, TIMP1, and ELF5 expression and decreased PHLPP2 expression. In conclusion, the four hub genes screened by our strategy could serve as novel biomarkers for prognosis prediction of CRC patients.