Background. Although accumulating evidence suggested that a molecular signature panel may be more effective for the prognosis prediction than routine clinical characteristics, current studies mainly focused on colorectal or colon cancers. No reports specifically focused on the signature panel for rectal cancers (RC). Our present study was aimed at developing a novel prognostic signature panel for RC. Methods. Sequencing (or microarray) data and clinicopathological details of patients with RC were retrieved from The Cancer Genome Atlas (TCGA-READ) or the Gene Expression Omnibus (GSE123390, GSE56699) database. A weighted gene coexpression network was used to identify RC-related modules. The least absolute shrinkage and selection operator analysis was performed to screen the prognostic signature panel. The prognostic performance of the risk score was evaluated by survival curve analyses. Functions of prognostic genes were predicted based on the interaction proteins and the correlation with tumor-infiltrating immune cells. The Human Protein Atlas (HPA) tool was utilized to validate the protein expression levels. Results. A total of 247 differentially expressed genes (DEGs) were commonly identified using TCGA and GSE123390 datasets. Brown and yellow modules (including 77 DEGs) were identified to be preserved for RC. Five DEGs (ASB2, GPR15, PRPH, RNASE7, and TCL1A) in these two modules constituted the optimal prognosis signature panel. Kaplan-Meier curve analysis showed that patients in the high-risk group had a poorer prognosis than those in the low-risk group. Receiver operating characteristic (ROC) curve analysis demonstrated that this risk score had high predictive accuracy for unfavorable prognosis, with the area under the ROC curve of 0.915 and 0.827 for TCGA and GSE56699 datasets, respectively. This five-mRNA classifier was an independent prognostic factor. Its predictive accuracy was also higher than all clinical factor models. A prognostic nomogram was developed by integrating the risk score and clinical factors, which showed the highest prognostic power. ASB2, PRPH, and GPR15/TCL1A were predicted to function by interacting with CASQ2/PDK4/EPHA67, PTN, and CXCL12, respectively. TCL1A and GPR15 influenced the infiltration levels of B cells and dendritic cells, while the expression of PRPH was positively associated with the abundance of macrophages. HPA analysis supported the downregulation of PRPH, RNASE7, CASQ2, EPHA6, and PDK4 in RC compared with normal controls. Conclusion. Our immune-related signature panel may be a promising prognostic indicator for RC.

Background Sepsis is a systemic inflammatory response that can lead to the dysfunction of many organs. The aberrant expression of miRNAs is associated with the pathogenesis of sepsis. However, the biological functions of miR-128-3p in sepsis remain largely unknown, and its mechanism should be further investigated. This study aimed to determine the regulatory network of miR-128-3p and TGFBR2 in lipopolysaccharide (LPS)-induced sepsis. Methods The expression levels of miR-128-3p and transforming growth factor beta receptors II (TGFBR2) were detected by quantitative polymerase chain reaction (qPCR). The protein levels of TGFBR2, Bcl-2, Bax, cleaved caspase 3, Smad2, and Smad3 were measured by western blot. Cell apoptosis was analyzed by flow cytometry. Cytokine production was detected by enzyme-linked immunosorbent assay (ELISA). The binding sites of miR-128-3p and TGFBR2 were predicted by Targetscan online software and confirmed by dual-luciferase reporter assay and RNA immunoprecipitation (RIP) assay. Results The level of miR-128-3p was decreased, and TGFBR2 expression was increased in serum samples of sepsis patients and LPS-induced HK2 cells. Overexpression of miR-128-3p or knockdown of TGFBR2 ameliorated LPS-induced inflammation and apoptosis. Moreover, TGFBR2 was a direct target of miR-128-3p, and its overexpression reversed the inhibitory effects of miR-128-3p overexpression on inflammation and apoptosis in LPS-induced HK2 cells. Besides, overexpression of miR-128-3p downregulated TGFBR2 to suppress the activation of the Smad signaling pathway. Conclusion miR-128-3p could inhibit apoptosis and inflammation by targeting TGFBR2 in LPS-induced HK2 cells, which might provide therapeutic strategy for the treatment of sepsis.

Sepsis is a life-threatening condition in which the immune response is directed towards the host tissues, causing organ failure. Since sepsis does not present with specific symptoms, its diagnosis is often delayed. The lack of diagnostic accuracy results in a non-specific diagnosis, and to date, a standard diagnostic test to detect sepsis in patients remains lacking. Therefore, it is vital to identify sepsis-related diagnostic genes. This study aimed to conduct an integrated analysis to assess the immune scores of samples from patients diagnosed with sepsis and normal samples, followed by weighted gene co-expression network analysis (WGCNA) to identify immune infiltration-related genes and potential transcriptome markers in sepsis. Furthermore, gene regulatory networks were established to screen diagnostic markers for sepsis based on the protein-protein interaction networks involving these immune infiltration-related genes. Moreover, we integrated WGCNA with the support vector machine (SVM) algorithm to build a diagnostic model for sepsis. Results showed that the immune score was significantly lower in the samples from patients with sepsis than in normal samples. A total of 328 and 333 genes were positively and negatively correlated with the immune score, respectively. Using the MCODE plugin in Cytoscape, we identified four modules, and through functional annotation, we found that these modules were related to the immune response. Gene Ontology functional enrichment analysis showed that the identified genes were associated with functions such as neutrophil degranulation, neutrophil activation in the immune response, neutrophil activation, and neutrophil-mediated immunity. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis showed the enrichment of pathways such as primary immunodeficiency, Th1- and Th2-cell differentiation, T-cell receptor signaling pathway, and natural killer cell-mediated cytotoxicity. Finally, we identified a four-gene signature, containing the hub genes LCK, CCL5, ITGAM, and MMP9, and established a model that could be used to diagnose patients with sepsis.

Introduction: As one of the most common digestive system malignancies, colorectal cancer (CRC) imposed grave danger on the public health. Cellular senescence involves gradual changes in functionality and reproducibility leading to abnormalities, including apoptosis resistance and enhanced secretion of inflammatory factors. Methods Cellular senescence-related gene set was determined by the application of WCGNA. We performed single-cell annotations of CRC cells and determined crucial signaling pathways through Cell chat analysis. Using LASSO and Cox analyses, we identified a gene set with prognostic values. Our model was validated using independent external cohort. In addition, we employed ssGSEA and xCell analyses to describe the detailed profile of infiltrated immune cells. Results We identified 3 distinct cell clusters in CRC samples, including T cells, myeloid cells, and B cells. We found that MIF signaling to CD74 + CD44 and CXCR4 displayed the highest interaction probability in the B cells communication. We determined a set of 6 genes of prognostic significance, GPR88, PTH1R, SFRP2, GPX3, ELFN1, and MS4A2. The prognostic differences between the two groups in the internal and external sets were found to be statistically significant. We observed higher infiltration of the activated B cells, CD4 + T cells, and CD8 + T cells in the LR group, which was characterized with an inferior prognosis. The abundance of CD8 + T cells were highly correlated with plasmacytoid and activated dendritic cells and follicular T helper cells. Conclusion Our study developed a prognostic model based on cellular senescence, which demonstrated significant efficacy in stratifying patients with CRC. Our findings offer new insights into potential precision immune treatments for this disease, with the hope of improving patient outcomes.