Identification of an Individualized Prognostic Signature Based on the RWSR Model in Early-Stage Bladder Carcinoma

Identification of molecular subtypes and prognostic model to reveal immune infiltration and predict prognosis based on immunogenic cell death-related genes in lung adenocarcinoma

Immunogenic cell death (ICD) has been increasingly indicated to be related to caners. However, ICD's role in Lung adenocarcinoma (LUAD) is still not well investigated. Clinical data along with associated mRNA expression profiles from LUAD cases were collected in TCGA and GEO databases. 13 ICD-related genes were identified. Relations of ICD-related genes expression with prognosis of patients, tumor immune microenvironment (TIME) was analyzed. Then, candidate genes were identified and the prognostic signature were constructed. Afterwards, one nomogram incorporating those chosen clinical data together with risk scores were built. Finally, the effect of HSP90AA1, one gene of the prognostic signature, on LUAD cell were analyzed. Two clusters were identified, which were designated as the ICD-high or -low subtype according to ICD-related genes levels. ICD-high subgroup showed good prognosis, high immune cell infiltration degrees, and enhanced immune response signaling activity compared with ICD-low subtype. Moreover, we established and verified the risk signature based on ICD-related genes. High risk group predicted poor prognosis of LUAD independently and presented negative association with immune score and immune status. Furthermore, nomogram contributed to the accurate prediction of LUAD prognostic outcome. Finally, HSP90AA1 levels were remarkably elevated within tumor cells in comparison with healthy pulmonary epithelial cells. HSP90α, HSP90AA1 protein product, promoted growth, migration, and invasion of LUAD cells. Molecular subtypes and prognostic model were identified by incorporating ICD-related genes, and it was related to TIME and might be adopted for the accurate prediction of LUAD prognosis.

Genomic Alterations of Signaling and DNA Damage Repair Pathways in Non-Muscle Invasive Bladder Cancer

The aim of the study was to demonstrate the most common genetic alterations and evaluate possible targets involving phosphatidylinositol-3-OH kinase (PIK3)/AKT/mammalian target of rapamycin (mTOR) signaling and DNA damage repair (DDR) pathways for personalized treatment in patients with non-muscle invasive bladder cancer (NMIBC). Alterations of these pathways were observed in 89.5% and 100% of patients, respectively. Among them, BARD1 was more frequently altered in low/intermediate-risk cases, but PARP4 was more frequently affected in intermediate/high-risk patients. The possible target feasibility of BARD1 and PARP4 alterations should be evaluated for personalized treatment using PARP-inhibitors in NMIBC. It is important to detect high tumor mutation burden (TMB) in patients in terms of immunotherapy.

Identification and Validation of a Four-Gene Ferroptosis Signature for Predicting Overall Survival of Lung Squamous Cell Carcinoma

Background

Lung squamous cell carcinoma (LUSC) represents 30% of all non-small cell lung carcinoma. Targeted therapy is not sufficient for LUSC patients because of the low frequency of targeted-effective mutation in LUSC whereas immunotherapy offers more options for patients with LUSC. We explored a ferroptosis-related prognostic signature that can potentially assess the prognosis and immunotherapy efficacy of LUSC patients.

Methods

A total of 502 LUSC patients were downloaded from The Cancer Genome Atlas (TCGA). The external validation data were obtained from the Gene Expression Omnibus (GEO): GSE73403. Then, we identified the candidate genes and constructed the prognostic signature through the Cox survival regression analyses and least absolute shrinkage and selection operator (LASSO). Risk score plot, Kaplan–Meier curve, and ROC curve were used to assess the prognostic power and performance of the model. The CIBERSORT algorithm estimated the fraction of immune cell types. TIDE was utilized to predict the response to immunotherapy. IMvigor210 was used to explore the association between the risk scores and immunotherapy outcomes. A nomogram combined selected clinical characteristics, and the risk scores were constructed.

Results

We screened 132 differentially expressed ferroptosis-related genes. According to KEGG and GO pathway analyses, these genes were mainly engaged in the positive regulation of cytokine production, cytokine metabolic process, and oxidoreductase activity. We then constructed a prognostic model via LASSO regression. The proportions of CD8+ T cells, CD4+ activated T cells, and follicular helper T cells were significantly different between low-risk and high-risk groups. TIDE algorithm indicated that low-risk LUSC patients might profit more from immune checkpoint inhibitors. The predictive value of the ferroptosis gene model in immunotherapy response was further confirmed in IMvigor210. Finally, we combined the clinical characteristics with a LASSO regression model to construct a nomogram that could be easily applied in clinical practice.

Conclusion

We identified a prognostic model that provides an accurate and objective basis for guiding individualized treatment decisions for LUSC.