CXCL8 induces M2 macrophage polarization and inhibits CD8+ T cell infiltration to generate an immunosuppressive microenvironment in colorectal cancer

The poor prognosis of immunotherapy in patients with colorectal cancer (CRC) necessitates a comprehensive understanding of the immunosuppressive mechanisms within tumor microenvironment (TME). Undoubtedly, the anti-tumor immune cells play an indispensable role in immune tolerance. Therefore, it is imperative to investigate novel immune-related factors that have the capacity to enhance anti-tumor immunity. Here, we employed bioinformatic analysis using R and Cytoscape to identify the hub gene chemokine (C-X-C motif) ligand 8 (CXCL8), which is overexpressed in CRC, in the malignant progression of CRC. However, its specific role of CXCL8 in CRC immunity remains to be elucidated. For this purpose, we evaluated how tumor-derived CXCL8 promotes M2 macrophage infiltration by in vivo and in vitro, which can be triggered by IL-1β within TME. Mechanistically, CXCL8-induced polarization of M2 macrophages depends on the activation of the STAT3 signaling. Finally, immunohistochemistry and multiplexed immunohistochemistry analysis identified that CXCL8 not only enhances PD-L1+ M2 macrophage infiltration but also attenuates the recruitment of PD-1+ CD8+ T cells in murine CRC models. Together, these findings emphasize the critical role for CXCL8 in promoting M2 macrophage polarization and inhibiting CD8+ T cell infiltration, thereby links CXCL8 to the emergency of immunosuppressive microenvironment facilitating tumor evasion. Overall, these findings may provide novel strategy for CRC immunotherapy.

Prognostic modelling of colorectal cancer based on oxidative stress-related genes

BACKGROUND

Colon cancer is one of the most prevalent cancers of the digestive tract. There is mounting evidence that genes associated with oxidative stress might affect the tumour immune microenvironment during tumour growth, maintenance, and treatment response. However, how oxidative stress-related genes affect prognostic importance, tumour microenvironment features, and treatment outcomes in colon cancer patients has not been fully elucidated.

METHODS

The Cancer Genome Atlas (TCGA) dataset was used to construct a signature model and nomogram using step and Cox regression approaches to investigate how gene expression affected immunological responses to colon cancer, including the degree of immune infiltration, MSI, and drug sensitivity.

RESULTS AND CONCLUSIONS

The nomogram and the signature model had strong prognostic potential for colon cancer, with gene expression highly correlated with multiple immune cells. The first signature model and nomogram including oxidative stress-related genes were constructed for use in clinical decision-making. In addition, SRD5A1, GSR, TXN, TRAF2 and TRAP1 were identified as potential biomarkers for colon cancer diagnosis and indicators for immunotherapy.

Transcriptomics Based Network Analyses and Molecular Docking Highlighted Potentially Therapeutic Biomarkers for Colon Cancer

In this study, machine learning-based multiple bioinformatics analysis was carried out for the purpose of the deep and efficient mining of high-throughput transcriptomics data from the TCGA database. Compared with normal colon tissue, 2469 genes were significantly differentially expressed in colon cancer tissue. Gene functional annotation and pathway analysis suggested that most DEGs were functionally related to the cell cycle and metabolism. Weighted gene co-expression network analysis revealed a significant module and the enriched genes that were closely related to fatty acid degradation and metabolism. Based on colon cancer progression, the trend analysis highlighted that several gene sets were significantly correlated with disease development. At the same time, the most specific genes were functionally related to cancer cell features such as the high performance of DNA replication and cell division. Moreover, survival analysis and target drug prediction were performed to prioritize reliable biomarkers and potential drugs. In consideration of a combination of different evidence, four genes (ACOX1, CPT2, CDC25C and PKMYT1) were suggested as novel biomarkers in colon cancer. The potential biomarkers and target drugs identified in our study may provide new ideas for colonic-related prevention, diagnosis, and treatment; therefore, our results have high clinical value for colon cancer.

miRNA in Molecular Diagnostics

MicroRNAs are a class of small non-coding RNA molecules that regulate gene expression on post-transcriptional level. Their biogenesis consists of a complex series of sequential processes, and they regulate expression of many genes involved in all cellular processes. Their function is essential for maintaining the homeostasis of a single cell; therefore, their aberrant expression contributes to development and progression of many diseases, especially malignant tumors and viral infections. Moreover, they can be associated with certain states of a specific disease, obtained in the least invasive manner for patients and analyzed with basic molecular methods used in clinical laboratories. Because of this, they have a promising potential to become very useful biomarkers and potential tools in personalized medicine approaches. In this review, miRNAs biogenesis, significance in cancer and infectious diseases, and current available test and methods for their detection are summarized.

The Value of Serum miR-139-3p Expression Level in Predicting Postoperative Survival of Colon Cancer Patients

Background

To explore the value of serum miR-139-3p expression level in predicting postoperative survival of colon cancer patients.

Methods

We selected 158 cases enrolled in our hospital from January 2017 to December 2019. Using real-time fluorescence quantitative PCR, the expression extents of serum miR-139-3p among patients suffering from colon cancer were detected. The enrollment of patients was performed in the high or low miR-139-3p group on the basis of the cutoff value determined by ROC curve analysis. The risk elements influencing the postoperative survival of colon cancer patients were analyzed by the Kaplan–Meier approach and univariate and multivariate Cox regression models.

Results

Compared with control group, significantly lower expression level of serum miR-139-3p was shown in colon cancer group (P < 0.05). Its low expression of miR-139-3p was associated with TNM stage, degree of differentiation, tumor sizes, lymph node metastasis and vascular infiltration in patients with colon cancer (all P < 0.05), which was also significantly associated with short survival time of colon cancer patients (P < 0.05). Multivariate Cox regression model analysis displayed that TNM phase, lymph node metastasis and miR-139-3p <2.17 were independent risk elements affecting postoperative survival (P < 0.05).

Conclusion

The low expression level of miR-139-3p is related to the short survival time of colon cancer patients, and it is expected to be used as a biological indicator to predict the postoperative survival of colon cancer.

S100P acts as a target of miR-495 in pancreatic cancer through bioinformatics analysis and experimental verification

S100 calcium binding protein P (S100P) and miR-495 are aberrantly expressed and exert essential roles in cancers. However, the mechanisms of miR-495-S100P in pancreatic cancer are yet to be illustrated. Thus, we explored the regulatory functions of miR-495-S100P axis in pancreatic adenocarcinoma cells growth and invasion. In this study, we identified that S100P was upregulated in pancreatic adenocarcinoma by bioinformatics analysis of the GEO (Gene Expression Omnibus database) microarray dataset (GSE16515). Western blotting and luciferase reporter gene analysis exhibited that miR-495 negatively determined the level of S100P via binging to its 3'-untranslated regions (3'-UTRs). A series of functional experiments indicated that upregulation of miR-495 or S100P knockdown suppressed pancreatic adenocarcinoma cells proliferation, invasion, and promoted apoptosis. Furthermore, the expression of S100P was negatively associated with the level of miR-495 in The Cancer Genome Atlas (TCGA) pancreatic adenocarcinoma case-cohort. Besides, reintroduction of S100P debilitated the anti-cancer action of miR-495 in pancreatic adenocarcinoma cells. Our data indicated that miR-495 performed suppressive roles in pancreatic adenocarcinoma through targeting S100P.

Identification of the AQP8-miR-92a network associated with the aggressive traits of colorectal cancer

Even though earlier reports have revealed that Aquaporin 8 (AQP8) exert essential roles in diverse malignancies, its relationship between specific microRNAs (miRNAs) in regulation of colorectal carcinoma (CRC) progression has never been elaborated. Herein, we proved that AQP8 was downregulated in CRC and high level of AQP8 was significantly associated with better survival in CRC patients. Overexpression of AQP8 restrained CRC cell proliferation, migration and invasion capacities in vitro. In vivo, upregulation of AQP8 also suppressed CRC cell growth. Mechanistic analyses illustrated that AQP8 was a directly target of miR-92a. The expression of AQP8 was negatively modulated by miR-92a. Rescues analysis indicated that miR-92a facilitated CRC cell growth and invasion via modulating the expression of AQP8. Our work validated that miR-92a regulated the aggressiveness of CRC cell via targeting AQP8.

Development of a Novel Six-miRNA-Based Model to Predict Overall Survival Among Colon Adenocarcinoma Patients

Introduction: Colon carcinoma is a common malignant tumor worldwide. Accurately predicting prognosis of colon adenocarcinoma (CA) patients may facilitate clinical individual decision-making. Many studies have reported that microRNAs (miRNAs) were associated with prognosis for patients with colon carcinoma. This study aimed to identify the prognosis-related miRNAs for predicting the overall survival (OS) of CA patients. Methods: Firstly, we analyzed the CA datasets from the Cancer Genome Atlas (TCGA), and looked for the prognosis-related miRNAs. Then, we developed a novel prediction model based on these miRNAs and the clinical characteristics. Time-dependent receiver operating characteristics (ROC) curves and calibration plots were used to evaluate the discrimination and accuracy of the signature and model. Finally, cell function assays and bioinformatics analyses were performed to evaluate the role of these selected miRNAs in modulating biological process in CA. Results: Six prognosis-related miRNAs were included in the miRNA-based signature, and it could effectively distinguish low-risk patients and high-risk patients. Furthermore, we established a prognostic model incorporating the six-miRNA-based signature and clinical characteristics. Areas under curves (AUCs) indicated that the six-miRNA-based model has a better predictive ability than TNM stage (AUC: 0.805 vs. 0.694). The calibration plots suggested close agreement between model predictions and actual observations. GO analysis showed that the target genes of these miRNAs are mainly involved in enrichment in protein binding and regulation of transcript and cytosol. KEGG pathway enrichment analysis indicated that these genes were mainly enriched in PI3K-Akt signaling pathway. Finally, we found that the five miRNAs except miR-152 were upregulated in tumor tissues and CA cells. The functional experiments revealed that miR-1245a, miR-3682, miR-33b, and miR-5683 promoted the migratory abilities and proliferation of CA cell, whereas miR-152 showed opposite effects. However, miR-4444-2 did not influence the migratory ability and proliferation of CA cell. Conclusions: In conclusion, we developed a novel six-miRNA-based model to predict 5-year survival probabilities for CA patients. This model has the potential to facilitate individualized treatment decisions.

Prediction of overall survival time in patients with colon adenocarcinoma using DNA methylation profiling of long non-coding RNAs

Long non-coding RNAs (lncRNAs) are a subgroup of RNAs able to regulate gene expression at the epigenetic level, and are therefore central to the regulation of numerous biological processes and the progression of multiple cancer types. However, lncRNAs have not been identified to considerably influence overall survival (OS) outcome in numerous different types of cancer. The majority of studies investigating the association between lncRNAs and epigenetic regulation have focused on their altered expression levels in cancerous cells, and few studies have focused on determining the correlation between lncRNAs and OS time. In the present study, comprehensive lncRNA expression analysis was performed on a cohort of patients diagnosed with colon adenocarcinoma (COAD) using the least absolute shrinkage and selection operator method (LASSO). Subsequently, the construction of a prognostic methylation-based predictive system was performed based on the results of LASSO analysis. Functional enrichment analysis of lncRNA co-expression genes was also performed. According to the results of the present study, the classifier was able to significantly predict the prognosis of patients with COAD, and the investigation of the relevant elucidated genes further revealed the mechanism of COAD pathogenesis.