Background: The transforming growth factor-β (TGF-β) pathway plays a pivotal role in inducing epithelial-mesenchymal transition (EMT), which is a key step in cancer invasion and metastasis. However, the regulatory mechanism of TGFβ in inducing EMT in colorectal cancer (CRC) has not been fully elucidated. In previous studies, it was found that S100A8 may regulate EMT. This study aimed to clarify the role of S100A8 in TGF-β-induced EMT and explore the underlying mechanism in CRC. Methods: S100A8 and upstream transcription factor 2 (USF2) expression was detected by immunohistochemistry in 412 CRC tissues. Kaplan-Meier survival analysis was performed. In vitro, Western blot, and migration and invasion assays were performed to investigate the effects of S100A8 and USF2 on TGF-β-induced EMT. Mouse metastasis models were used to determine in vivo metastasis ability. Luciferase reporter and chromatin immunoprecipitation assay were used to explore the role of USF2 on S100A8 transcription. Results: During TGF-β-induced EMT in CRC cells, S100A8 and the transcription factor USF2 were upregulated. S100A8 promoted cell migration and invasion and EMT. USF2 transcriptionally regulated S100A8 expression by directly binding to its promoter region. Furthermore, TGF-β enhanced the USF2/S100A8 signaling axis of CRC cells whereas extracellular S100A8 inhibited the USF2/S100A8 axis of CRC cells. S100A8 expression in tumor cells was associated with poor overall survival in CRC. USF2 expression was positively related to S100A8 expression in tumor cells but negatively related to S100A8-positive stromal cells.

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Objective: This study was conducted in order to construct a competitive endogenous RNA (ceRNA) network to screen RNA that plays an important role in colon cancer and to construct a model to predict the prognosis of patients.Methods: The gene expression data of colon cancer were downloaded from the TCGA database. The difference was analyzed by the R software and the ceRNA network was constructed. The survival-related RNA was screened out by combining with clinical information, and the prognosis model was established by lasso regression. CIBERSORT was used to analyze the infiltration of immune cells in colon cancer, and the differential expression of immune cells related to survival was screened out by combining clinical information. The correlation between RNA and immune cells was analyzed by lasso regression. PCR was used to verify the expression of seven RNAs in colon cancer patients with different prognoses.Results: Two hundred and fifteen lncRNAs, 357 miRNAs, and 2,955 mRNAs were differentially expressed in colon cancer. The constructed ceRNA network contains 18 lncRNAs, 42 miRNAs, and 168 mRNAs, of which 18 RNAs are significantly related to survival. Through lasso analysis, we selected seven optimal RNA construction models. The AUC value of the model was greater than 0.7, and there was a significant difference in the survival rate between the high- and low-risk groups. Two kinds of immune cells related to the prognosis of patients were screened out. The results showed that the expression of seven RNA markers in colon cancer patients with different prognoses was basically consistent with the model analysis.Conclusion: We have established the regulatory network of ceRNA in colon cancer, screened out seven core RNAs and two kinds of immune cells, and constructed a comprehensive prognosis model of colon cancer patients.

Purpose The aim of this study was to analyze prognostic factors for ovarian metastases (OM) in colorectal cancer (CRC) using data from a Chinese center. In addition, the study aimed at developing a new clinical scoring system for prognosis of OM of CRC patients after surgery. Patients and methods Data of CRC patients with OM were collected from a single Chinese institution (n = 67). Kaplan-Meier analysis was used to evaluate cumulative survival of patients. Factors associated with prognosis of overall survival (OS) were explored using Cox’s proportional hazard regression models. A scoring system to determine effectiveness of prognosis was developed. Results Median OS values for patients with or without surgery were 22 and 7 months, respectively. Size of OM, number of OM, peritoneal metastasis (PM), Peritoneal cancer index (PCI), and completeness of cytoreduction (CC) were associated with OS of patients through univariate analysis. Multivariate analysis using a Cox regression model showed that only CC was an independent predictor for OS. Three variables (the size of OM >15cm, PCI ≥ 10, and carcinoembryonic antigen (CEA) >30 ng/mL) assigned one point each were used to develop a risk score. The resulting score was used for prognosis of OS. Conclusion Surgical treatment of metastatic sites is effective and safe for CRC patients with OM. CC-0 is recommended for improved prognosis. The scoring system developed in this study is effective for prediction of OS of patients after surgery.