Long noncoding RNAs (lncRNAs) have recently been identified to be involved in various diseases including cancer. NEAT1 is a recently identified lncRNA with its function largely unknown in human malignancy. In the present study, we investigated NEAT1 expression in 239 cases of clinical colorectal cancer specimens and matched normal tissues. Statistical methods were utilized to analyze the association of NEAT1 with clinical features, disease-free and overall survival of patients. Results showed that NEAT1 expression in colorectal cancer was up-regulated in 72.0% (172/239) cases compared with corresponding normal counterparts, and related to tumor differentiation, invasion, metastasis and TNM stage. Kaplan-Meier analysis proved that NEAT1 was associated with both disease-free survival and overall survival of patients with colorectal cancer that patients with high NEAT1 expression tend to have unfavorable outcome. Moreover, cox’s proportional hazards analysis showed that high NEAT1 expression was an independent prognostic marker of poor outcome. These results provided the first evidence that the expression of NEAT1 in colorectal cancer may play an oncogenic role in colorectal cancer differentiation, invasion and metastasis. It also proved that NEAT1 may serve as an indicator of tumor recurrence and prognosis of colorectal cancer.

Background Mesenchymal stem cells (MSCs) therapy is a novel treatment strategy for cancer and a wide range of diseases with an excessive immune response such as ulcerative colitis (UC), due to its powerful immunomodulatory properties and its capacity for tissue regeneration and repair. One of the promising therapeutic options can focus on MSC-secreted exosomes (MSC-Exo), which have been identified as a type of paracrine interaction. In light of a wide variety of recent experimental studies, the present review aims to seek the recent research advances of therapies based on the MSC-Exo for treating UC and colorectal cancer (CRC). Methods A systematic literature search in MEDLINE, Scopus, and Google Scholar was performed from inception to December 2021 using the terms [(“colorectal cancer” OR “bowel cancer” OR “colon cancer” OR “rectal cancer”) AND (exosome) AND (stem cell) AND (“inflammatory bowel disease” OR “Crohn's disease” OR “colitis”)] in titles and abstracts. Findings Exosomes derived from various sources of MSCs, including human umbilical cord-derived MSCs (hUC-MSCs), human adipose-derived MSCs (hAD-MSCs), human bone marrow-derived MSCs (hBM-MSCs), and olfactory ecto-MSCs (OE-MSCs), have shown the protective role against UC and CRC. Exosomes from hUC-MSCs, hBM-MSCs, AD-MSCs, and OE-MSCs have been found to ameliorate the experimental UC through suppressing inflammatory cells including macrophages, Th1/Th17 cells, reducing the expression of proinflammatory cytokines, as well as inducing the anti-inflammatory function of Treg and Th2 cells and enhancing the expression of anti-inflammatory cytokines. In addition, hBM-MSC-Exo and hUC-MSC-Exo containing tumor-suppressive miRs (miR-3940-5p/miR-22-3p/miR‐16‐5p) have been shown to suppress proliferation, migration, and invasion of CRC cells via regulation of RAP2B/PI3K/AKT signaling pathway and ITGA2/ITGA6. Key messages The MSC-Exo can exert beneficial effects on UC and CRC through two different mechanisms including modulating immune responses and inducing anti-tumor responses, respectively.

<abstract> <p>Colorectal cancer (CRC), one of the most common malignancies worldwide, leads to abundant cancer-related mortalities annually. Pyroptosis, a new kind of programmed cell death, plays a critical role in immune response and tumor progression. Our study aimed to identify a prognostic signature for CRC based on pyroptosis-related genes (PRGs). The difference in PRGs between CRC tissues and normal tissues deposited in the TCGA database was calculated by "limma" R package. The tumor microenvironment (TME) of CRC cases was accessed by the ESTIMATE algorithm. The prognostic PRGs were identified using Cox regression analysis. A least absolute shrinkage and selector operation (LASSO) algorithm was used to calculate the risk scores and construct a clinical predictive model of CRC. Gene Set Enrichment Analysis (GSEA) was performed for understanding the function annotation of the signature in the tumor microenvironment. We found that most PRGs were significantly dysregulated in CRC. Through the LASSO method, three key PRGs were selected to calculate the risk scores and construct the prognostic model for CRC. The risk score was an independent indicator of patient's prognosis. In addition, we classified the CRC patients into two clusters based on risk scores and discovered that CRC patients in cluster 2 underwent worse overall survival and owned higher expression levels of immune checkpoint genes in tumor tissues. In conclusion, our study identified a PRG-related prognostic signature for CRC, according to which we classified the CRC patients into two clusters with distinct prognosis and immunotherapy potential.</p> </abstract>