Resistance to anoikis is a key characteristic of many cancer cells, promoting cell survival. However, the mechanism of anoikis in hepatocellular carcinoma (HCC) remains unknown. In this study, we applied differentially expressed overlapping anoikis-related genes to classify The Cancer Genome Atlas (TCGA) samples using an unsupervised cluster algorithm. Then, we employed weighted gene coexpression network analysis (WGCNA) to identify highly correlated genes and constructed a prognostic risk model based on univariate Cox proportional hazards regression. This model was validated using external datasets from the International Cancer Genome Consortium (ICGC) and Gene Expression Omnibus (GEO). Finally, we used a CIBERSORT algorithm to investigate the correlation between risk score and immune infiltration. Our results showed that the TCGA cohorts could be divided into two subgroups, with subgroup A having a lower survival probability. Five genes (BAK1, SPP1, BSG, PBK and DAP3) were identified as anoikis-related prognostic genes. Moreover, the prognostic risk model effectively predicted overall survival, which was validated using ICGC and GEO datasets. In addition, there was a strong correlation between infiltrating immune cells and prognostic genes and risk score. In conclusion, we identified anoikis-related subgroups and prognostic genes in HCC, which could be significant for understanding the molecular mechanisms and treatment of HCC.

Although aging and senescence have been extensively studied in the past few decades, however, there is lack of clinical treatment available for anti‐aging. This study presents the effects of berberine (BBR) on the aging process resulting in a promising extension of lifespan in model organisms. BBR extended the replicative lifespan, improved the morphology, and boosted rejuvenation markers of replicative senescence in human fetal lung diploid fibroblasts (2BS and WI38). BBR also rescued senescent cells with late population doubling (PD). Furthermore, the senescence‐associated β‐galactosidase (SA‐β‐gal)‐positive cell rates of late PD cells grown in the BBR‐containing medium were ~72% lower than those of control cells, and its morphology resembled that of young cells. Mechanistically, BBR improved cell growth and proliferation by promoting entry of cell cycles from the G₀ or G₁ phase to S/G₂‐M phase. Most importantly, BBR extended the lifespan of chemotherapy‐treated mice and naturally aged mice by ~52% and ~16.49%, respectively. The residual lifespan of the naturally aged mice was extended by 80%, from 85.5 days to 154 days. The oral administration of BBR in mice resulted in significantly improved health span, fur density, and behavioral activity. Therefore, BBR may be an ideal candidate for the development of an anti‐aging medicine.

Lung squamous cell carcinoma (LUSC) is often diagnosed at the advanced stage with poor prognosis. The mechanisms of its pathogenesis and prognosis require urgent elucidation. This study was performed to screen potential biomarkers related to the occurrence, development and prognosis of LUSC to reveal unknown physiological and pathological processes. Using bioinformatics analysis, the lung squamous cell carcinoma microarray datasets from the Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases were analyzed to identify differentially expressed genes (DEGs). Furthermore, PPI and WGCNA network analysis were integrated to identify the key genes closely related to the process of LUSC development. In addition, survival analysis was performed to achieve a prognostic model that accomplished good prediction accuracy. Three hundred and thirty–seven up–regulated and 119 down-regulated genes were identified, in which four genes have been found to play vital roles in LUSC development, namely CCNA2, AURKA, AURKB, and FEN1. The prognostic model contained 5 genes, which were all detrimental to prognosis. The AUC of the established prognostic model for predicting the survival of patients at 1, 3, and 5 years was 0.692, 0.722, and 0.651 in the test data, respectively. In conclusion, this study identified several biomarkers of significant interest for additional investigation of the therapies and methods of prognosis of lung squamous cell carcinoma.