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.

Background: This prospective study aimed to explore the correlation between circulating mitochondrial DNA (mtDNA), intestinal barrier function impairment, and postoperative SIRS in patients undergoing gastrointestinal surgery. Methods: Patients were recruited into this study after signing an informed consent form. Circulating mitochondrial DNA and serum DAO concentrations were measured preoperatively and on day 1 and day 7 postoperatively. Postoperative vitals, routine tests, and biochemical indicators were recorded in detail. Results: Forty patients undergoing gastrointestinal surgery were recruited for and completed this study. Patients were divided into non-fever, fever, and SIRS groups according to their postoperative temperature and other corresponding indexes. The mtDNA was expressed as the number of PCR cycles using three specific sequences. Circulating mtDNA tended to increase in patients after gastrointestinal surgery, but the difference was not significant. Nevertheless, mtDNA in the SIRS group was significantly higher than in patients in the fever and non-fever groups (p < 0.05). Serum DAO showed a trend of increase on the first day after surgery compared with that before surgery, but the difference was not significant (p > 0.05). However, patients in the SIRS group showed a significant increase (p < 0.05) compared with the others. Both circulating mtDNA and DAO showed a downward trend on the seventh day after surgery. Conclusions: Circulating mtDNA presented a trend of increase after gastrointestinal surgery, and the degree of the increased fold was related to the extent of the inflammation response. In general, the intestinal barrier damage indicator DAO was the same as mtDNA and tended to increase after gastrointestinal surgery and then gradually decrease, which may play a synergistic role in inducing postoperative fever and SIRS.

Substantial uncertainties remain regarding the establishment of an optimal examined lymph node (ELN) count for the comprehensive management of resectable colorectal cancer (CRC). The correlation of the ELN count with cancer-specific survival (CSS) and benefit from adjuvant chemotherapy (AC) in CRC was investigated using a large database, and the minimal threshold for ELN count in LN-negative patients was determined. The data on stage I to III CRC available in the SEER database (2010–2015) were analyzed to determine the correlation of ELN count with CSS and the benefit of AC using multivariable models. The series of odds ratios (ORs) and hazard ratios (HRs) were fitted using the join-point regression analysis. External validation was performed using the data of patients with stage I to III CRC (2004 to 2009) available in the SEER database. Among LN-negative patients, both cohorts indicated that an increase in the ELN count (≤ 18) led to incremental enhancements in CSS, while no additional improvement in CSS was noted beyond an ELN count of 18. Notably, the efficacy of AC diminished gradually as the ELN count increased. Moreover, post-AC CSS was impaired when the ELN count exceeded 18 (serial HRs > 1), a trend that was accentuated with a higher ELN count. Among the LN-positive patients, two cohorts exhibited proportional increases in ELNs, from one positive LN (PLN) to 20 PLN disease, and incremental benefit from AC, as the ELN count increased (serial HRs < 1). The present study recommends an ELN threshold of 18 when evaluating the quality of prognostic stratification and guiding AC for LN-negative cases. A higher ELN count would be associated with further accurate PLN detection and incremental benefit from AC in LN-positive diseases.

Background: Few studies have focused on the underlying relationship between the prognosis of tumor mutation burden (TMB) and immune cell infiltration in gastric cancer (GC). This study aims to explore the relationship among TMB and various components in tumor microenvironment (TME). Methods: The transcription profiles and somatic mutation data of 375 tumor and 32 normal samples were obtained from TCGA. The specific mutation information was summarized and visualized with waterfall chart, then number of TMB per million bases of each GC sample was calculated. Immune/stromal scores and tumor purity were calculated by the ‘ESTIMATE’ package, and the fractions of 22 immune cells in each sample were evaluated by CIBERSORT algorithm. Finally, Lass regression analysis was utilized to generate a prognostic scoring signature with TCGA cohort as the training set, while GES84437 cohort as the validation set. Results: Higher TMB indicated favorable overall survival (OS, P = 0.043)，better disease specific survival (P = 0.029), and longer progression free interval (P = 0.004). TMB was positively correlated with MSI and tumor purity, while negatively associated with immune/stromal scores. Moreover, TMB^high group has lower T cells CD4 memory resting (P < 0.001) and T cells regulatory (P < 0.001), and more T cells CD4 memory activated (P < 0.001) and T cells follicular helper (P = 0.009). More importanly, the infiltration of dendritic cells activated predicted a worse OS, while T cells CD4 memory activated and T cells follicular helper meant a better OS. Finally, a nomogram combined TMB-related signature with clinicopathologic variables can successfully predict the OS with high accuracy and efficiency.Conclusion: TMB can effectively reveal the immune infiltration status in TME of GC, and might serve as a prognostic classifier for individualized treatment of clinical decision-making.