Introducing novel key genes and transcription factors associated with rectal cancer response to chemoradiation through co-expression network analysis

Effective treatment strategies and key factors influencing therapeutic efficacy in advanced SMARCA4-deficient non-small cell lung cancer

INTRODUCTION

SMARCA4/BRG1-deficient non-small cell lung cancer (SD-NSCLC) with high invasiveness and poor prognosis is associated with primary resistance to standard treatment, especially in late-stage patients. This study aimed to explore effective treatments and identify critical factors impacting therapeutic efficacy to enhance outcomes for SD-NSCLC patients.

METHODS

103 SD-NSCLC patients in stage III/IV diagnosed by immunohistochemistry from May 2019 to March 2024 were included in this study. We assessed the patients' clinical and genetic features, analyzed the clinical outcomes of local treatment and immunotherapy according to the TNM stage, and further evaluated the factors impacting therapeutic efficacy.

RESULTS

In stage III patients, no significant differences in the median progression-free survival (mPFS) and median overall survival (mOS) were observed between patients receiving local treatment at the primary site and those who did not (p > 0.05), while adding ICIs (immune checkpoint inhibitors) to local treatment significantly improved mPFS compared with non-ICIs (15.0 vs. 7.7 months, p = 0.033), though not mOS (p > 0.05). For stage IV patients, ICIs significantly improved mPFS (8.9 vs. 4.2 months, p = 0.006) and mOS (19.7 vs. 13.1 months, p = 0.007) compared to non-ICIs treatments. However, among ICIs-treated patients, the addition of local treatment to the primary lesion did not significantly affect mPFS and mOS (p > 0.05). Patients with STK11/KEAP1 mutations had significantly shorter mPFS (3.6 vs. 16.2 months, p = 0.001) and mOS (17.7 vs. 31.3 months, p = 0.002), while no significant difference was observed in mPFS and mOS in patients with different tumor mutation burden (TMB) and PD-L1 expression levels.

CONCLUSION

The addition of ICIs to local treatment shows promising results for locally advanced patients with SD-NSCLC, and first-line ICIs are associated with improved survival in metastatic SD-NSCLC. STK11/KEAP1 mutations may be linked to reduced efficacy of immunotherapy.

POLE -related gene signature predicts prognosis, immune feature, and drug therapy in human endometrioid carcinoma

The POLE subtype of Endometrial carcinoma (EC) is linked to a favourable prognosis in the molecular classification. We proposed to ascertain the potential connection between the POLE subtype and improved prognosis. In order to forecast the prognosis, least absolute shrinkage and selection operator (LASSO) Cox regression analysis and weighted gene co-expression network analysis (WGCNA) were employed, and a POLE-related risk signature (PRS) model was developed and validated. Single-sample gene set enrichment analysis (ssGSEA) with the "GSVA" package was employed to analyse immunity characteristics. Drug susceptibility studies were conducted to compare the half-maximal inhibitory concentration (IC50) of medicines between high- and low-risk groups. The PRS model was generated employing the LASSO Cox regression coefficients of the ELF1, MMADHC, andAL021707.6 genes. Our study demonstrated that the risk score was linked to tumour stage, grade, and survival. Furthermore, the low-risk group possessed elevated levels of gene expression connected with immunological checkpoints and HLA. Our outcomes emerged that the PRS model might have value in identifying patients with a good prognosis and in facilitating personalised treatment in the clinic.

Potential mechanisms and drug prediction of Rheumatoid Arthritis and primary Sjögren's Syndrome: A public databases-based study

Rheumatoid arthritis (RA) and primary Sjögren's syndrome (pSS) are the most common systemic autoimmune diseases, and they are increasingly being recognized as occurring in the same patient population. These two diseases share several clinical features and laboratory parameters, but the exact mechanism of their co-pathogenesis remains unclear. The intention of this study was to investigate the common molecular mechanisms involved in RA and pSS using integrated bioinformatic analysis. RNA-seq data for RA and pSS were picked up from the Gene Expression Omnibus (GEO) database. Co-expression genes linked with RA and pSS were recognized using weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analysis. Then, we screened two public disease-gene interaction databases (GeneCards and Comparative Toxicogenomics Database) for common targets associated with RA and pSS. The DGIdb database was used to predict therapeutic drugs for RA and pSS. The Human microRNA Disease Database (HMDD) was used to screen out the common microRNAs associated with RA and pSS. Finally, a common miRNA-gene network was created using Cytoscape. Four hub genes (CXCL10, GZMA, ITGA4, and PSMB9) were obtained from the intersection of common genes from WGCNA, differential gene analysis and public databases. Twenty-four drugs corresponding to hub gene targets were predicted in the DGIdb database. Among the 24 drugs, five drugs had already been reported for the treatment of RA and pSS. Other drugs, such as bortezomib, carfilzomib, oprozomib, cyclosporine and zidovudine, may be ideal drugs for the future treatment of RA patients with pSS. According to the miRNA-gene network, hsa-mir-21 may play a significant role in the mechanisms shared by RA and pSS. In conclusion, we identified commom targets as potential biomarkers in RA and pSS from publicly available databases and predicted potential drugs based on the targets. A new understanding of the molecular mechanisms associated with RA and pSS is provided according to the miRNA-gene network.