Pyroptosis is a newly discovered programmed cell death that is associated with tumor progression, prognosis, and treatment response. However, the potential roles of pyroptosis-related genes (PRGs) in the tumor microenvironment (TME) remain unclear. We described the alterations of PRGs in 1109 colorectal cancer (CRC) samples from genetic and transcriptional fields and evaluated their expression patterns from four independent datasets. We identified two distinct molecular subtypes and found that multi-layer PRG alterations were correlated with patient clinicopathological features, prognosis, and TME cell-infiltrating characteristics. Then, a PRG_score for predicting recurrence-free survival (RFS) was constructed and its predictive capability in CRC patients was validated. Consequently, we constructed a highly accurate nomogram for improving the clinical applicability of the PRG_score. A low PRG_score, characterized by increased microsatellite instability-high (MSI-H), mutation burden, and immunity activation, indicated favorable odds of RFS. Moreover, the PRG_score was significantly associated with the cancer stem cell (CSC) index and chemotherapeutic drug sensitivity. Our comprehensive analysis of PRGs in CRC demonstrated their potential roles in the tumor-immune-stromal microenvironment, clinicopathological features, and prognosis. These findings may improve our understanding of PRGs in CRC and pave a new path for the assessment of prognosis and the development of more effective immunotherapy strategies.

Evidence is increasingly indicating that circular RNAs (circRNAs) are closely involved in tumorigenesis and cancer progression. However, the function of circRNAs in gastric cancer (GC) are still unknown. Here, we aimed to determine the regulatory mechanism of circRNAs in GC. Expression profiles of circRNAs were downloaded from four Gene Expression Omnibus (GEO) microarray datasets. Expression profiles of miRNAs and mRNAs were collected from The Cancer Genome Atlas (TCGA) database. We used the robust rank aggregation method to identify differentially expressed circRNAs (DEcircRNAs) and a ceRNA network was constructed based on circRNA–miRNA pairs and miRNA–mRNA pairs. Functional and pathway enrichment analyses were performed and interactions between proteins were predicted using Cytoscape. Aa subnetwork regulatory module was built using the MCODE plugin. A total of eight DEcircRNAs, 240 DEmiRNAs, and 4578 DEmRNAs were identified. The circRNA–miRNA–mRNA network was constructed based on seven circRNAs, 33 miRNAs, 69 mRNAs in GC. GO and KEGG pathway analysis indicated DEmRNAs might be associated with GC onset and progression. A PPI network was established and four hub genes (MCM4, KIF23, MCM8, and NCAPD2) were determined from the network. Then a circRNA–miRNA-hub gene subnetwork was constructed based on the four DEcircRNAs, three DEmiRNAs, and four DEmRNAs. Our findings provide a deeper understanding the circRNA-related competing endogenous RNA regulatory mechanism in GC pathogenesis.

Lin28B is a RNA-binding protein that inhibits the let-7 microRNA family and acts as an oncogene in various human malignant diseases. Conversely, the members of let-7 family function as tumor suppressers and are often inactivated in cancers. The interaction of Lin28B/let-7 plays a crucial part of tumorigenesis. In this study, the authors examined the Lin28B expression using immunohistochemistry in 190 breast cancers and analyzed the correlation of Lin28B immunostaining and clinicopathological characteristics. Breast cancer patients previously diagnosed with invasive ductal carcinomas were enrolled in this study. All cases went through surgical procedures as the initial treatment. The characteristics of every case were collected, including tumor size, pathologic grade, metastatic lymphoid nodes, and estrogen receptor α (ERα), progesterone receptor (PR), and HER2 status. The immunostaining was scored by two independent investigators. Eighty-three (43.7%) of 190 cases showed positive expression of Lin28B. Lin28B immunostaining was increased in tumors compared with the adjacent tissues. Overexpression of Lin28B was linked to poor differentiation, advanced-stage disease, and Ki67-positive status (all p<0.05). Besides, Lin28B expression was significantly different among breast cancer subtypes. This study addresses the role of Lin28B in breast cancers and provides insight of its predictive effects in disease development.

Background: The N6-methyladenosine (m6A) RNA modification can modify long non-coding RNAs (lncRNAs), thereby affecting the tumorigenesis and progression of tumors. However, the underlying role of m6A-modified lncRNAs in colorectal cancer (CRC) remains largely unknown. Therefore, our aim was to assess the prognostic value of m6A-modified lncRNAs in CRC patients. Methods: The gene expression and clinicopathological data of CRC were extracted from The Cancer Genome Atlas (TCGA) database. Pearson correlation analysis was used to investigate the m6A-modified lncRNAs. Consensus clustering was conducted to identify molecular subtypes of CRC, and the clinical significance of molecular subtypes was identified. The least absolute shrinkage and selection operator analysis (LASSO) was applied to establish a risk signature. Finally, a prognostic nomogram with risk score and clinicopathological variables was established. Results: In total, 29 m6A-modified lncRNAs were identified as prognostic lncRNAs. Two molecular clusters were identified and significant differences were found with respect to clinicopathological features and prognosis. Cluster1 is associated with poor overall survival (OS), down-regulation of Programmed cell death ligand-1 (PD-L1) expression, lower immune score, and less immune cell infiltration. Then, an m6A-modified lncRNA signature for predicting OS was constructed in the TCGA training cohort. The signature demonstrated favorable prediction performance in both training and validation sets. Compared with low-risk patients, patients with high risk showed worse clinical outcomes, lower immune scores, and downregulated PD-L1 expression. Further analysis indicated that the signature was an independent prognostic indicator, and then a prognostic nomogram based on risk score, tumor location, and tumor stage was established. Conclusions: Our study identified a seven m6A-modified lncRNA signature and established a prognostic nomogram that reliably predicts OS in CRC. These findings may improve the understanding of m6A modifications in CRC and provide insights into the prognosis and treatment strategy of CRC.

Background: The potential role of pyroptosis in tumor microenvironment (TME) reprogramming and immunotherapy has received increasing attention. As most studies have concentrated on a single TME cell type or a single pyroptosis regulator (PR), the overall TME cell-infiltrating characteristics mediated by the integrated roles of multiple PRs have not been comprehensively recognized. Methods: This study curated 33 PRs and conducted consensus clustering to identify distinct pyroptosis patterns in gastric cancer (GC) patients. A single-sample gene set enrichment analysis algorithm was used to quantify the infiltration density of TME immune cells and the enrichment scores of well-defined biological signatures. The pyroptosis patterns of individuals were quantified using a principal component analysis algorithm called the pyroptosis score (PS). Results: Three distinct pyroptosis patterns with significant survival differences were identified from 1422 GC samples; these patterns were closely associated with three TME cell-infiltrating landscapes—namely, the immune-inflamed, immune-excluded, and immune-desert phenotypes. The PS model generated on the basis of the pyroptosis pattern-related signature genes could accurately predict the TME status, existing molecular subtypes, genetic variation, therapeutic response, and clinical outcome; among which, a relatively high PS was highly consistent with immune activation, molecular subtypes with survival advantages, high tumor mutation burden, high microsatellite instability, and other favorable characteristics. In particular, from the Cancer Genome Atlas database, the PS model exhibited significant prognostic relevance in a pan-cancer analysis, and patients with a relatively high PS exhibited durable therapeutic advantages and better prognostic benefits in anti-PD1/L1 therapy. Conclusions: This study demonstrates that pyroptosis is prominently correlated with TME diversity and complexity, and quantification of the pyroptosis patterns of individuals will enhance our cognition of TME infiltration landscapes and help in formulating more effective immunotherapeutic strategies.