The genomic variant features (mutations, deletions, structural variants, etc.) within gastric cancer impact its evolution and immunogenicity. The tumor has developed several coping strategies to respond to these changes by DNA repair and replication (DRR). However, the intrinsic relationship between the associated DRR-related genes and gastric cancer progression remained unknown. This study selected DRR-related genes with tumor mutation burden based on the TCGA (The Cancer Genome Atlas) database of gastric cancer transcriptome and mutation data. The prognosis model of seven genes (LAMA2, CREB3L3, SELP, ABCC9, CYP1B1, CDH2, and GAMT) was constructed by a univariate and LASSO regression analysis and divided into high-risk and low-risk groups with the median risk score. Survival analysis showed that overall survival (OS) was lower in the high-risk group than that in the low-risk group. Moreover, patients with gastric cancer in the high-risk group have worse survival in different subgroups, including age, gender, histological grade, and TNM stage. The nomogram that included risk scores for DRR-related genes could accurately foresee OS of patients with gastric cancer. Interestingly, the tumor mutation burden score was higher in the low-risk group than that in the high-risk group, and the risk score for DRR-related genes was negatively correlated with tumor mutation burden in gastric cancer. Next, we further combined the risk score and tumor mutation burden to evaluate the prognosis of gastric cancer patients. The low-risk cohort had a better prognosis than the high-risk cohort in the high tumor mutation burden subgroup. The number of mutation types in the high-risk group was lower than that in the low-risk group. In the immune microenvironment of gastric cancer, more naïve B cells, memory resting CD4+ T cells, Treg cells, monocytes cells, and resting mast cells were infiltrated in the high-risk group. At last, PD-L1 and IAP expressions were negatively correlated with the risk scores; patients with gastric cancer in the low-risk group showed better immunotherapy outcomes than those in the high-risk group. Overall, the DRR-related gene signature based on tumor mutation burden is a novel biomarker for prognostic and immunotherapy response in patients with gastric cancer.

MicroRNAs (miRNAs) play critical roles in the development of vascular diseases. However, the effects of miR-130a-5p and its functional targets on atherosclerosis (AS) are still largely unknown. In this regard, our aim is to explore the potentially important role of miR-130a-5p and its target gene during the progression of endothelial cell injury. We first found oxidized low-density lipoprotein (ox-LDL) induced FAS and cell apoptosis in HUVECs. Subsequently, miR-130a-5p expression was verified to be downregulated after ox-LDL treatment and negatively correlated with FAS, and FAS was identified as substantially upregulated in the ox-LDL-treated HUVEC cells. After that, the knockdown of FAS and overexpression of miR-130a-5p together were observed to aggregate ox-LDL-induced reduction of cell viability and apoptosis, cell cycle progression, cell proliferation, cell migration and invasion. In conclusion, we detected that miR-130a-5p contributed to the progression of endothelial cell injury by regulating of FAS, which may provide a new and promising therapeutic target for AS.

Peptidyl arginine deiminase 1 (PADI1) catalyzes protein citrullination and has a role in regulating immune responses. The tumor immune microenvironment has been reported to be important in colorectal cancer (CRC), which was correlated with the ability of CRC patients to benefit from immunotherapy. However, there is a lack of molecular markers for matching CRC immunotherapy. Previously, single-gene risk models have only considered the effect of individual genes on intrinsic tumor properties, ignoring the role of genes and their co-expressed genes as a whole. In this study, we analyzed the differential expression of PADI1 in colorectal cancer (CRC). We found that PADI1 was highly expressed in CRC. Subgroup survival analysis revealed a prognostic survival difference for PADI1 in CRC patients aged less than 65 years, male, T stage, N0, M0, and stage I-II ( ). In addition, we analyzed the functions and signaling pathways associated with PADI1 in CRC and found that it was highly enriched in several immune-related functions and pathways. Then, a set of PADI1 co-expressed genes (PCGs) risk-prognosis scores was developed with PADI1 as the core, which could accurately predict the prognosis of CRC ( ). PCGs risk score can be an independent prognostic factor for CRC. A new set of Norman plot models were developed for clinical characteristics with age, sex, and TNM stage, which can accurately predict CRC 1, 3, and 5 years survival, and calibration curves and decision curve analysis (DCA) validated the accuracy of the models. The risk score assessed the immune microenvironment of CRC and found that the immune score was higher in the low-risk group, and CD4+ T cells, helper T cells, and eosinophils were more infiltrated in the low-risk group ( ). Immunotherapy efficacy was better in the low-risk group ( ). The underlying mechanism may be that the high-risk group of PCGs was enriched in some pathways that promote immune escape and immune dysfunction. In conclusion, PCGs may better predict CRC prognosis and immunotherapeutic response.

NCOA5 has been identified as a crucial factor in the progression of hepatocellular carcinoma (HCC). This study investigates the expression of NCOA5 in HCC, revealing its significant overexpression in tumor tissues compared to healthy liver tissues, as evidenced by analysis of the TCGA dataset and RT-qPCR in patient samples. Higher NCOA5 levels correlate with poor overall survival, highlighting its role as a prognostic indicator. Furthermore, our findings suggest that elevated NCOA5 is associated with resistance to sorafenib, a common chemotherapeutic agent for HCC, as shown through analysis of publicly available datasets and the establishment of sorafenib-resistant HCC cell lines. Mechanistically, NCOA5 appears to inhibit ferroptosis in HCC cells by modulating glutathione peroxidase 4 (GPX4) levels. Knockdown of NCOA5 sensitizes resistant cell lines to sorafenib and induces ferroptosis by decreasing GPX4 expression. Additionally, NCOA5 regulation of GPX4 is mediated through the transcription factor MYC. In vivo studies further validate that targeting NCOA5 enhances the efficacy of sorafenib in resistant HCC models by promoting ferroptosis. Collectively, these findings underscore the potential of NCOA5 as a therapeutic target to overcome drug resistance in HCC, providing insights into its role in modulating treatment responses and patient prognosis.

Background Ongoing research has underlined the significant biological dimensions of anoikis in carcinogenicity and progression of multiple tumors. However, there is no definitive role for anoikis in the prognosis of lung adenocarcinoma (LUAD) and the tumor microenvironment (TME). Methods In this study, we employed ssGSEA to construct anoikis scores for 273 anoikis genes and screened 184 anoikis-associated genes by WGCNA and single-cell sequencing. The LASSO algorithm configured the LUAD prognostic risk cohort, and the CIBERSORT algorithm assessed differences in the infiltration abundance of 22 immune cells. The TIDE algorithm calculated discrimination based on anoikis risk cohort for immune therapy variation. Finally, the prognostic value of the two models was evaluated separately by machine learning algorithms. Results ssGSEA calculated the anoikis-related gene score (ARGS), which was classified into high ARGS and low ARGS based on the prognosis of LUAD patients. Single-cell sequencing verified the distribution of ARGS on different cellular taxa and constructed a set of models to predict LUAD based on the differential genes of high and low ARGS. Single-cell sequencing was performed to validate the distribution of ARGS in different cell populations and to construct a set of predictive models for LUAD based on the differential genes of high and low ARGS, Risk was developed based on LOX, MSX1, FSTL3, STEAP1, PMEPA1, SNAI1, ABCA6, PLOD2, SEMA3A, FRMD6. Further validation was performed in the Gene Expression Omnibus score (GEO) dataset. The immune and mesenchymal scores were generated by an estimation algorithm for LUAD patients from The Cancer Genome Atlas (TCGA) database and assessed the relationship between higher and lower-risk groups of the model. Higher risk was also negatively associated with the abundance of B cells, CD4 + T cells, and other stromal or immune cells. Mutations in genes occurred more frequently in the high-risk group. These mutations may be associated with changes in TME and suggest the patient's response to immunotherapy. For the drug sensitivity analysis, the high-risk group had a lower IC50 in some chemotherapeutic agents and targeted agents, suggesting that the high-risk group is more sensitive to these agents. Conclusion This study reinforces that anoikis patterns are significantly associated with the diversity and complexity of TME. Quantitative assessment of anoikis modification patterns in LUAD will reinforce our insights into TME characteristics and catalyze more effective immunotherapeutic strategies.