Prognostic value of baculoviral IAP repeat containing 5 expression as a new biomarker in lung adenocarcinoma: a meta-analysis

Prognostic significance of Dickkopf-1 in head and neck squamous cell carcinoma

BACKGROUND

Dickkopf-1 (DKK1) exhibits abnormal expression in various cancers and correlates with poor prognosis. This study investigates DKK1's prognostic relevance in head and neck squamous cell carcinoma (HNSC).

METHODS

We conducted a comprehensive search across literature and sequencing databases to gather eligible studies and HNSC datasets. We calculated pooled standardized mean differences (SMD) and 95% confidence intervals (CI) for clinical characteristics, as well as hazard ratios (HR) with 95% CIs for overall survival (OS) and progression-free/disease-free survival (PFS/DFS). Sensitivity analysis gauged result stability, and Egger's test assessed publication bias.

RESULTS

Pooled results indicated that HNSC patients with higher T-stage exhibited elevated DKK1 expression levels, and this elevated expression was associated with shorter OS and PFS/DFS. While sensitivity analysis identified some studies significantly affecting pooled results, most were unaffected, and no publication bias was detected.

CONCLUSION

DKK1 holds promise as a potential biomarker for predicting poor prognosis in HNSC patients, but further research is needed for confirmation.

Identification of Molecular Subtypes and Prognostic Characteristics of Adrenocortical Carcinoma Based on Unsupervised Clustering

Adrenocortical carcinoma (ACC) is a rare endocrine malignancy with a poor prognosis. Increasing evidence highlights the significant role of immune-related genes (IRGs) in ACC progression and immunotherapy, but the research is still limited. Based on the Cancer Genome Atlas (TCGA) database, immune-related molecular subtypes were identified by unsupervised consensus clustering. Univariate Cox analysis and Least Absolute Shrinkage and Selection Operator (LASSO) regression were employed to further establish immune-related gene signatures (IRGS). An evaluation of immune cell infiltration, biological function, tumor mutation burden (TMB), predicted immunotherapy response, and drug sensitivity in ACC patients was conducted to elucidate the applicative efficacy of IRGS in precision therapy. ACC patients were divided into two molecular subtypes through consistent clustering. Furthermore, the 3-gene signature (including PRKCA, LTBP1, and BIRC5) based on two molecular subtypes demonstrated consistent prognostic efficacy across the TCGA and GEO datasets and emerged as an independent prognostic factor. The low-risk group exhibited heightened immune cell infiltration, TMB, and immune checkpoint inhibitors (ICIs), associated with a favorable prognosis. Pathways associated with drug metabolism, hormone regulation, and metabolism were activated in the low-risk group. In conclusion, our findings suggest IRGS can be used as an independent prognostic biomarker, providing a foundation for shaping future ACC immunotherapy strategies.

Development of a prognostic model for anoikis and identifies hub genes in hepatocellular carcinoma

Considering the high fatality of hepatocellular carcinoma (HCC), current prognostic systems are insufficient to accurately forecast HCC patients' outcomes. In our study, nine anoikis‑related genes (PTRH2, ITGAV, ANXA5, BIRC5, BDNF, BSG, DAP3, SKP2, and EGF) were determined to establish a risk scoring model using LASSO regression, which could be validated in ICGC dataset. Kaplan-Meier curves and time-dependent receiver operating characteristic (ROC) curve analysis confirmed the risk score possessed an accurate predictive value for the prognosis of HCC patients. The high-risk group showed a higher infiltration of aDCs, macrophages, T-follicular helper cells, and Th2 cells. Besides, PD-L1 was significantly higher in the high-risk group compared to the low-risk group. Several anoikis‑related genes, such as ANX5, ITGAV, BDNF and SKP2, were associated with drug sensitivity in HCC. Finally, we identified BIRC5 and SKP2 as hub genes among the nine model genes using WGCNA analysis. BIRC5 and SKP2 were over-expressed in HCC tissues, and their over-expression was associated with poor prognosis, no matter in our cohort by immunohistochemical staining or in the TCGA cohort by mRNA-Seq. In our cohort, BIRC5 expression was highly associated with the T stage, pathologic stage, histologic grade and AFP of HCC patients. In general, our anoikis-related risk model can enhance the ability to predict the survival outcomes of HCC patients and provide a feasible therapeutic strategy for immunotherapy and drug resistance in HCC. BIRC5 and SKP2 are hub genes of anoikis‑related genes in HCC.

RASAL3 predicts overall survival and CD8+ T lymphocyte infiltration in lung adenocarcinoma

RAS-activating protein-like 3 (RASAL3) is a synaptic Ras GTPase-activating protein (SynGAP) and a potential novel biomarker of CD8+ T cell infiltration in lung adenocarcinoma (LUAD). This study explored RASAL3 expression in LUAD, the prognostic impact of RASAL3 and the relationship with immune cell infiltration. RASAL3 expression in LUAD tissues was considerably low, with high RASAL3 expression associated with better overall survival, whereas the low expression was linked to advanced T, N, M classifications, TNM stage and lower grade. Furthermore, RASAL3 expression positively correlated with CD8+ T lymphocyte infiltration. In conclusion, RASAL3 expression is a potential prognostic and immunological biomarker of LUAD.