Construction of a risk model and prediction of prognosis and immunotherapy based on cuproptosis-related LncRNAs in the urinary system pan-cancer.

BACKGROUND: Urinary pan-cancer system is a general term for tumors of the urinary system including renal cell carcinoma (RCC), prostate cancer (PRAD), and bladder cancer (BLCA). Their location, physiological functions, and metabolism are closely related, making the occurrence and outcome of these tumors highly similar. Cuproptosis is a new type of cell death that is different from apoptosis and plays an essential role in tumors. Therefore, it is necessary to study the molecular mechanism of cuproptosis-related lncRNAs to urinary system pan-cancer for the prognosis, clinical diagnosis, and treatment of urinary tumors. METHOD: In our study, we identified 35 co-expression cuproptosis-related lncRNAs (CRLs) from the urinary pan-cancer system. 28 CRLs were identified as prognostic-related CRLs by univariate Cox regression analysis. Then 12 CRLs were obtained using lasso regression and multivariate cox analysis to construct a prognostic model. We divided patients into high- and low-risk groups based on the median risk scores. Next, Kaplan-Meier analysis, principal component analysis (PCA), functional rich annotations, and nomogram were used to compare the differences between the high- and low-risk groups. Finally, the prediction of tumor immune dysfunction and rejection, gene mutation, and drug sensitivity were discussed. CONCLUSION: Finally, the candidate molecules of the urinary system pan-cancer were identified. This CRLs risk model may be promising for clinical prediction of prognosis and immunotherapy response in urinary system pan-cancer patients.

Construction of a Prognostic Model for Hypoxia-Related LncRNAs and Prediction of the Immune Landscape in the Digestive System Pan-Cancer.

Digestive system pan-cancer is a general term for digestive system tumors including colorectal carcinoma (CRC), esophageal carcinoma (ESCA), stomach adenocarcinoma (STAD), and liver hepatocellular carcinoma (LIHC). Since the anatomical location, function and metabolism are closely related, there may be similarities in development and progression of these tumors. Hypoxia is the consequence of an imbalance between oxygen demand and supply, and intracellular hypoxia is associated with malignant progression, treatment resistance, and poor prognosis in tumors. Therefore, an urgent and challenging task is to investigate the molecular mechanisms associated with hypoxia in digestive system pan-cancer for the prognosis and treatment of digestive tract tumors. In this study, we identified 18 hypoxia-related lncRNAs (HRlncRNAs) by co-expression analysis between hypoxia genes and lncRNAs from digestive system pan-cancer. Six HRlncRNAs were then obtained using lasso regression and multivariate cox analysis to construct a prognostic model. Next, the Akaike information criterion (AIC) values for 3-year receiver operating curve (ROC) were counted to determine the cut-off point and establish an optimal model to distinguish between high- or low-risk groups among patients with digestive system pan-cancer. To evaluate the stability of the prognosis model, we validated it in terms of survival outcomes, clinicopathological stage, tumor-infiltrating immune cells, immune checkpoint inhibitors (ICIs) and anticancer drugs sensitivity. The results suggested that high- risk group had a worse prognosis and a more positive association with tumor-infiltrating immune cells such as B cells, cancer-associated fibroblasts, endothelial cells, monocytes, macrophages and bone marrow dendritic cells in digestive system pan-cancer. Immune checkpoint inhibitors (ICIs) related biomarkers discovered that high-risk group was positively correlated with high expression of HAVCR2 in digestive system pan-cancer. The anticancer drugs sensitivity analysis showed that the high-risk group was associated with the lower half-inhibitory centration (IC50) of Imatinib in digestive system pan-cancer. In conclusion, the prognostic model of HRlncRNAs showed a promising clinical prediction value and may provide a useful reference for the diagnosis and treatment of the digestive system tumors.

Effect and Safety of Therapeutic Regimens for Patients With Germline BRCA Mutation-Associated Breast Cancer: A Network Meta-Analysis.

PURPOSE: Breast cancer type 1 susceptibility (BRCA) mutations not only increase breast cancer (BC) risk but also result in poor survival and prognosis for BC patients. This study will analyze the effect and safety of therapeutic regimens for the treatment of BC patients with germline BRCA (gBRCA) mutations by network meta-analysis. METHODS: Public databases were searched from inception to 29 April 2021. Frequentist network meta-analysis was conducted to analyze the benefit of chemotherapy and targeted drug-related strategies. RESULTS: Seventeen articles were included in the analysis. For progression-free survival (PFS), olaparib (hazard ratio (HR): 0.58; 95% confidence interval (CI): 0.43 - 0.79), platinum (HR: 0.45; 95% CI: 0.22 - 0.89), and talazoparib (HR: 0.54; 95% CI: 0.41 - 0.71) were significantly better than platinum-free chemotherapy (Chemo). The results based on indirect comparisons showed that veliparib (Vel) + platinum + Chemo was also significantly better than Chemo (HR: 0.37; 95% CI: 0.20 - 0.69). For overall survival (OS), olaparib was significantly better than Chemo only in the population who did not receive prior chemotherapy. For pathologic complete response (pCR), bevacizumab+Chemo had a significant advantage over platinum agents (OR: 3.64; 95% CI: 1.07 - 12.39). Olaparib and talazoparib both showed significantly higher objective response rates (ORRs) than Chemo. CONCLUSION: The PFS results suggested that olaparib, talazoparib, and Vel+platinum agent+Chemo were ideal regimens for overall, TNBC, and advanced BC patients with gBRCA mutations. Whether PARPis are suitable for patients with gBRCA mutations who have received prior platinum therapy still needs to be clarified.

Expression and prognosis of CDC45 in cervical cancer based on the GEO database.

Cervical cancer is one of the most common malignant tumors in women, and its morbidity and mortality are increasing year by year worldwide. Therefore, an urgent and challenging task is to identify potential biomarkers for cervical cancer. This study aims to identify the hub genes based on the GEO database and then validate their prognostic values in cervical cancer by multiple databases. By analysis, we obtained 83 co-expressed differential genes from the GEO database (GSE63514, GSE67522 and GSE39001). GO and KEGG enrichment analysis showed that these 83 co-expressed it mainly involved differential genes in DNA replication, cell division, cell cycle, etc.. The PPI network was constructed and top 10 genes with protein-protein interaction were selected. Then, we validated ten genes using some databases such as TCGA, GTEx and oncomine. Survival analysis demonstrated significant differences in CDC45, RFC4, TOP2A. Differential expression analysis showed that these genes were highly expressed in cervical cancer tissues. Furthermore, univariate and multivariate cox regression analysis indicated that CDC45 and clinical stage IV were independent prognostic factors for cervical cancer. In addition, the HPA database validated the protein expression level of CDC45 in cervical cancer. Further studies investigated the relationship between CDC45 and tumor-infiltrating immune cells via CIBERSORT. Finally, gene set enrichment analysis (GSEA) showed CDC45 related genes were mainly enriched in cell cycle, chromosome, catalytic activity acting on DNA, etc. These results suggested CDC45 may be a potential biomarker associated with the prognosis of cervical cancer.