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.

Zonulin protein is a newly discovered modulator which modulates the permeability of the intestinal epithelial barrier by disassembling intercellular tight junctions (TJ). Disruption of TJ is associated with neonatal necrotizing enterocolitis (NEC). It has been shown bifidobacterium could protect the intestinal barrier function and prophylactical administration of bifidobacterium has beneficial effects in NEC patients and animals. However, it is still unknown whether the zonulin is involved in the gut barrier dysfunction of NEC, and the protective mechanisms of bifidobacterium on intestinal barrier function are also not well understood. The present study aims to investigate the effects of bifidobacterium on intestinal barrier function, zonulin regulation, and TJ integrity both in LPS-induced enterocyte barrier injury of Caco-2 monolayers and in a rat NEC model. Our results showed bifidobacterium markedly attenuated the decrease in transepithelial electrical resistance and the increase in paracellular permeability in the Caco-2 monolayers treated with LPS (P < 0.01). Compared with the LPS group, bifidobacterium significantly decreased the production of IL-6 and TNF-α (P < 0.01) and suppressed zonulin release (P < 0.05). In addition, bifidobacterium pretreatment up-regulated occludin, claudin-3 and ZO-1 expression (P < 0.01) and also preserved these proteins localization at TJ compared with the LPS group. In the in vivo study, bifidobacterium decreased the incidence of NEC from 88 to 47% (P < 0.05) and reduced the severity in the NEC model. Increased levels of IL-6 and TNF-α in the ileum of NEC rats were normalized in bifidobacterium treated rats (P < 0.05). Moreover, administration of bifidobacterium attenuated the increase in intestinal permeability (P < 0.01), decreased the levels of serum zonulin (P < 0.05), normalized the expression and localization of TJ proteins in the ileum compared with animals with NEC. We concluded that bifidobacterium may protect against intestinal barrier dysfunction both in vitro and in NEC. This protective effect is associated with inhibition of proinflammatory cytokine secretion, suppression of zonulin protein release and improvement of intestinal TJ integrity.

The present study was to investigate the clinical significance of peroxiredoxin 2 (PRDX2), an oncoenzyme, in the development and progression of colorectal cancer(CRC).We found levels of PRDX2 mRNA and protein were higher in CRC cell lines than in normal human colonic epithelial cells. PRDX2 expression was significantly up-regulated in CRC lesions compared with that in the adjacent noncancerous tissues. CRC tissues from 148 of 226 (65.5%) patients revealed high level of PRDX2 protein expression in contrast to only 13 of 226 (5.8%) PRDX2 strong staining cases in the adjacent noncancerous tissues. Increased expression of PRDX2 protein was significantly associated with poor tumor differentiation (p = 0.001), advanced local invasion (p = 0.046), increased lymph node metastasis (p = 0.008), and advanced TNM stage (p = 0.020). Patients with higher PRDX2 expression had a significantly shorter disease-free survival and worse disease-specific survival than those with low expression. Importantly, PRDX2 up-regulation was an independent prognostic indicator for stage I–III, early stage (stage I-II) and advanced stage (stage III) patients. In conclusion, our findings suggest PRDX2 up-regulation correlates with tumor progression and could serve as a useful marker for the prognosis of CRC.

Several long noncoding RNAs (lncRNAs) have been identified in various malignant tumors and determined to contribute to the process of tumorigenesis, including that of colorectal cancer (CRC). Cancer stem cells (CSCs) have been demonstrated to promote the expansion and maintain the invasion and metastasis of cancer cells, owing to their self-renewal capacity. However, the underlying modulation mechanism of CSC-associated lncRNAs in CRC remains largely unclear. Using integrated bioinformatic analysis, we identified a novel lncRNA (lncRNA-cCSC1) that is highly expressed in CRC and colorectal cancer stem cells (CRCSCs). The biological functions of lncRNA-cCSC1 were assessed in vitro and vivo through the silencing or upregulation of its expression. The depletion of lncRNA-cCSC1 markedly inhibited the self-renewal capacity of the CRCSCs and reduced their drug resistance to 5-fluorouracil. In contrast, lncRNA-cCSC1 overexpression increased the self-renewal effect. Furthermore, aberrant lncRNA-cCSC1 expression resulted in a concomitant alteration of smoothened (SMO) and GLI family zinc finger 1 (Gli1) expression in the Hedgehog (Hh) signaling pathway. Our study is the first to identify a novel lncRNA-cCSC1 in CRC and to indicate that it may regulate CSC-like properties via the Hh signaling pathway. Thus, lncRNA-cCSC1 could be a potential biomarker and promising therapeutic target for CRC. K E Y W O R D Scancer stem cells, colorectal cancer, Hedgehog, long noncoding RNA, stemness | INTRODUCTIONColorectal cancer (CRC), one of the most common and lethal types of malignant tumors, is an important contributor to cancer mortality and morbidity. 1 The incidence of CRC has increased gradually in recent years, with a total of 1800 977 estimated new cases (males 1006 019 cases and females 794 958 cases) diagnosed globally in 2018, making it the third-highest cancer types. 2 Despite the considerable progress made in surgical and chemoradiotherapeutic techniques, the prognosis for patients with CRC is still not ideal. 3 Therefore, new therapeutic approaches based on an improved understanding of the molecular mechanism of CRC are urgently needed.The high rates of cancer recurrence and heterogeneity are often considered to be associated with chemo-and radio-resistance, leading to the failure of these traditional therapies against CRC. 4 Increasing evidence has

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.