Tumor microenvironment characterization in colorectal cancer to identify prognostic and immunotherapy genes signature.

BACKGROUND: The tumor microenvironment (TME) plays a crucial role in tumorigenesis, progression, and therapeutic response in many cancers. This study aimed to comprehensively investigate the role of TME in colorectal cancer (CRC) by generating a TMEscore based on gene expression. METHODS: The TME patterns of CRC datasets were investigated, and the TMEscores were calculated. An unsupervised clustering method was used to divide samples into clusters. The associations between TMEscores and clinical features, prognosis, immune score, gene mutations, and immune checkpoint inhibitors were analyzed. A TME signature was constructed using the TMEscore-related genes. The results were validated using external and clinical cohorts. RESULTS: The TME pattern landscape was for CRC was examined using 960 samples, and then the TMEscore pattern of CRC datasets was evaluated. Two TMEscore clusters were identified, and the high TMEscore cluster was associated with early-stage CRC and better prognosis in patients with CRC when compared with the low TMEscore clusters. The high TMEscore cluster indicated elevated tumor cell scores and tumor gene mutation burden, and decreased tumor purity, when compared with the low TMEscore cluster. Patients with high TMEscore were more likely to respond to immune checkpoint therapy than those with low TMEscore. A TME signature was constructed using the TMEscore-related genes superimposing the results of two machine learning methods (LASSO and XGBoost algorithms), and a TMEscore-related four-gene signature was established, which had a high predictive value for discriminating patients from different TMEscore clusters. The prognostic value of the TMEscore was validated in two independent cohorts, and the expression of TME signature genes was verified in four external cohorts and clinical samples. CONCLUSION: Our study provides a comprehensive description of TME characteristics in CRC and demonstrates that the TMEscore is a reliable prognostic biomarker and predictive indicator for patients with CRC undergoing immunotherapy.

Oxaliplatin related lncRNAs prognostic models predict the prognosis of patients given oxaliplatin-based chemotherapy.

BACKGROUND: Oxaliplatin-based chemotherapy is the first-line treatment for colorectal cancer (CRC). Long noncoding RNAs (lncRNAs) have been implicated in chemotherapy sensitivity. This study aimed to identify lncRNAs related to oxaliplatin sensitivity and predict the prognosis of CRC patients underwent oxaliplatin-based chemotherapy. METHODS: Data from the Genomics of Drug Sensitivity in Cancer (GDSC) was used to screen for lncRNAs related to oxaliplatin sensitivity. Four machine learning algorithms (LASSO, Decision tree, Random-forest, and support vector machine) were applied to identify the key lncRNAs. A predictive model for oxaliplatin sensitivity and a prognostic model based on key lncRNAs were established. The published datasets, and cell experiments were used to verify the predictive value. RESULTS: A total of 805 tumor cell lines from GDSC were divided into oxaliplatin sensitive (top 1/3) and resistant (bottom 1/3) groups based on their IC50 values, and 113 lncRNAs, which were differentially expressed between the two groups, were selected and incorporated into four machine learning algorithms, and seven key lncRNAs were identified. The predictive model exhibited good predictions for oxaliplatin sensitivity. The prognostic model exhibited high performance in patients with CRC who underwent oxaliplatin-based chemotherapies. Four lncRNAs, including C20orf197, UCA1, MIR17HG, and MIR22HG, displayed consistent responses to oxaliplatin treatment in the validation analysis. CONCLUSION: Certain lncRNAs were associated with oxaliplatin sensitivity and predicted the response to oxaliplatin treatment. The prognostic models established based on the key lncRNAs could predict the prognosis of patients given oxaliplatin-based chemotherapy.

Tumor-infiltrating immune cells based TMEscore and related gene signature is associated with the survival of CRC patients and response to fluoropyrimidine-based chemotherapy.

Background: Tumor-infiltrating immune cells (TIICs) are associated with chemotherapy response. This study aimed to explore the prognostic value of a TIIC-related tumor microenvironment score (TMEscore) in patients with colorectal cancer (CRC) who underwent chemotherapy and construct a TMEscore-related gene signature to determine its predictive value. Methods: Gene profiles of patients who underwent fluoropyrimidine-based chemotherapy were collected, and their TIIC fractions were calculated and clustered. Differentially expressed genes (DEGs) between clusters were used to calculate the TMEscore. The association between the TMEscore, chemotherapy response, and survival rate was analyzed. Machine learning methods were used to identify key TMEscore-related genes, and a gene signature was constructed to verify the predictive value. Results: Two clusters based on the TIIC fraction were identified, and the TMEscore was calculated based on the DEGs of the two clusters. The TMEscore was higher in patients who responded to chemotherapy than in those who did not, and was associated with the survival rate of patients who underwent chemotherapy. Three machine learning methods, support vector machine (SVM), decision tree (DT), and Extreme Gradient Boosting (XGBoost), identified three TMEscore-related genes (ADH1C, SLC26A2, and NANS) associated with the response to chemotherapy. A TMEscore-related gene signature was constructed, and three external cohorts validated that the gene signature could predict the response to chemotherapy. Five datasets and clinical samples showed that the expression of the three TMEscore-related genes was increased in tumor tissues compared to those in control tissues. Conclusions: The TIIC-based TMEscore was associated with the survival of CRC patients who underwent fluoropyrimidine-based chemotherapy, and predicted the response to chemotherapy. The TMEscore-related gene signature had a better predictive value for response to chemotherapy than for survival.

[Interleukin-9 promotes pancreatic cancer cell proliferation and migration via activation of STAT3 pathway].

Objective To investigate the impact of interleukin-9 (IL-9) on proliferation, invasion and migration of pancreatic cancer cells and its mechanism. Methods PANC-1 cells were cultured in vitro and treated with IL-9 at different concentrations (5, 10, 20 ng/mL) for 24 hours. The level of IL-9R mRNA was analyzed by quantitative real-time PCR. CCK-8 assay was used to test the proliferation of the cells and flow cytometry to detect the cell apoptosis. TranswellTM assay was employed to determine the invasion and migration of PANC-1 cells. Western blotting was used to detect the STAT3 and p-STAT3 protein expression levels. After PANC-1 cells were treated with different concentrations of STAT3 pathway inhibitor AG490, followed by IL-9 treatment, the STAT3 and p-STAT3 protein expressions, as well as the proliferation of the cells were detected again. Results The level of IL-9R mRNA and the proliferation rate of PANC-1 cells were enhanced with the increase of IL-9 concentration, and the capacities of cell invasion and migration were promoted significantly. The relative protein expression of p-STAT3 increased greatly in PANC-1 cells after the treatment of IL-9, but STAT3 were not changed significantly compared with the ones without IL-9 treatment. The proliferation-promoting effect of IL-9 on AG490-pretreated PANC-1 cells was induced, and the p-STAT3 protein expression level was notably inhibited. Conclusion The activation of STAT3 pathway is strongly associated with the process that IL-9 mediates the promotion of proliferation, invasion and migration in pancreatic cancer cells.

Interleukin-9 Promotes Pancreatic Cancer Cells Proliferation and Migration via the miR-200a/Beta-Catenin Axis.

Background. Both IL-9 and miR-200a are involved in the pathogenesis of cancers; however, the role of IL-9 in pancreatic cancer and the possible underlying mechanisms remain unknown. The aim of this study was to investigate the effect of IL-9 on pancreatic cancer cells and its interaction with miR-200a. Methods. Pancreatic cancer cells (PANC-1 and AsPC-1) were treated with IL-9 and the expression of miR-200a and ß-catenin in pancreatic cancer cells was measured. ß-Catenin was examined as a target gene of miR-200a in pancreatic cancer cells. The interaction between IL-9 and miR-200a in pancreatic cancer cells was determined by infecting miR-200a mimics prior to IL-9 treatment and then measuring miR-200a and ß-catenin expression. Results. IL-9 significantly promoted the proliferation, invasion, and migration of pancreatic cancer cells; however, the effect on pancreatic cancer cell apoptosis was insignificant. ß-Catenin was verified as a target gene of miR-200a in pancreatic cancer cells. Overexpression of miR-200a in pancreatic cancer cells significantly attenuated proliferation and metastasis and reduced ß-catenin expression. IL-9 treatment of pancreatic cancer cells decreased miR-200a expression and increased ß-catenin expression. The effect of miR-200a on pancreatic cancer cells decreased following IL-9 treatment. Conclusions. IL-9 promotes proliferation and metastasis in pancreatic cancer cells; this effect may partly involve regulation of the miR-200a/ß-catenin axis.

IL-9 promotes proliferation and metastasis of hepatocellular cancer cells by activating JAK2/STAT3 pathway.

The role of IL-9 in hepatocellular carcinoma (HCC) remains unknown. This study was designed to investigate the effect of IL-9 on HCC cells and the underlying signaling pathway. HCC cell lines SMMC-7721 was treated by IL-9, and the activities of cells were tested. The expression of JAK2, STAT3, p-JAK2 and p-STAT3 was detected by Western Blot assay. RT-PCR was used to detect the expression of MMP-2, MMP-9 and VEGF. SMMC-7721 cells were pre-treated with AG490, which is the inhibitor of JAK2/STAT3 pathway, and then incubated with IL-9. The expression of STAT3, p-STAT3, VEGF, MMP-2 and MMP-9 was detected, and the activities of SMMC-7721 cells was tested. The data showed that IL-9 significantly promoted the proliferation, invasion and migration of SMMC-7721 cells in a concentration dependent manner. Exposure to IL-9 increased the activation of p-STAT3 and p-JAK2, and increased the expression of MMP-2, MMP-9 and VEGF at the same time. Suppression of JAK2/STAT3 pathway by AG490 attenuated the promotive effects of IL-9 on SMMC-7721 cells, and reduced the expression of VEGF, MMP-2 and MMP-9. The present study demonstrated that IL-9 promotes the proliferation and metastasis in HCC cells and the effect may partly through the regulation of JAK2/STAT3 pathway.

Interleukin-22 ameliorates liver fibrosis through miR-200a/beta-catenin.

IL-22 ameliorates liver fibrosis by inhibiting hepatic stellate cells (HSC), and loss of miR-200a is associated with the development of liver fibrosis. The study aimed to investigate the interplay between IL-22 and miR-200a in regulating liver fibrosis in vivo and in vitro. We observed that IL-22 significantly reduced the proliferation of HSC and increased the expression of p-STAT3. ß-catenin was identified as a target gene of miR-200a by luciferase reporter assay, and upregulation of miR-200a significantly attenuated the proliferation of HSC and reduced ß-catenin expression. IL-22 treatment increased expression of miR-200a and decreased expression of ß-catenin in HSC. The expression of p-STAT3 and miR-200a was elevated while ß-catenin was decreased in fibrotic rat liver after IL-22 treatment. Expression levels of ß-catenin and p-STAT3 were inversely correlated in fibrotic rat liver and HSC. Upregulation of ß-catenin suppressed expression of p-STAT3 in HSC. We concluded that IL-22 inhibits HSC activation and ameliorates liver fibrosis through enhancing expression of miR-200a and reducing expression of ß-catenin, suggesting there may be a crosstalk between IL-22/STAT3 and ß-catenin pathway.