Identification of prognostic and therapeutic biomarkers in type 2 papillary renal cell carcinoma.

BACKGROUND: Papillary renal cell carcinoma (PRCC) can be divided into type 1 (PRCC1) and type 2 (PRCC2) and PRCC2 share a more invasive phenotype and worse prognosis. This study aims to identify potential prognostic and therapeutic biomarkers in PRCC2. METHODS: A cohort from The Cancer Genome Atlas and two datasets from Gene Expression Omnibus were examined. Common differentially expressed genes (DEGs) were screened and potential biomarkers were explored by using Kaplan-Meier method and cox regression analysis. Functional enrichment analysis was utilized to evaluate the potential biological functions. Tumor infiltrating immune cells were estimated by CIBERSORT algorithm. Ninety-two PRCC2 samples from Fudan University Shanghai Cancer Center were obtained, and immunostaining was performed to validate prognostic and therapeutic significance of the potential biomarker. RESULTS: PRCC2 has worse overall survival and shares distinct molecular characteristics from PRCC1. There was significant higher expression level of Targeting protein for Xklp2 (TPX2) in PRCC2 compared with normal tissues. Higher expression level of TPX2 was significantly associated with worse overall survival in PRCC2 and kinesin family genes expression were found significantly elevated in high risk PRCC2. Abundance of tumor infiltrating M1 macrophage was significantly higher in PRCC2 and it was also associated with worse overall survival. In the FUSCC cohort, higher TPX2 expression was significantly correlated with worse overall and progression-free survival. Retrospective analysis indicated that mTOR inhibitor (everolimus) had greater efficacy in the high-risk group than in the low-risk group (overall response rate: 28.6% vs. 16.7%) and that everolimus had greater efficacy than sunitinib in the high-risk group (overall response rate: 28.6% vs. 20%). CONCLUSIONS: TPX2 was a prognostic and therapeutic biomarker in PRCC2. Higher abundance of tumor infiltrating M1 macrophage was significantly associated with worse overall survival in PRCC2. mTOR inhibitors may have good efficacy in patients with high-risk PRCC2.

The Inflammasomes Adaptor Protein PYCARD Is a Potential Pyroptosis Biomarker Related to Immune Response and Prognosis in Clear Cell Renal Cell Carcinoma.

PYCARD is a protein engaged in inflammation, pyroptosis, and apoptosis. However, the function of PYCARD in human cancers remains unclear. The objective of our study was to explore PYCARD expression and prognostic value in human cancers. Public databases were used to assess PYCARD expression and prognostic value. The TISIDB database was used to explore the associations between PYCARD expression and different immune subtypes. The correlations between PYCARD expression and ICP genes, MMR genes, MSI, and TMB were also investigated. The immunotherapy response was assessed using the TIDE database. Single-cell RNA databases evaluated the PYCARD expression of immune cells. External datasets and immunohistochemical staining were conducted to validate PYCARD expression and prognostic value. The results showed that PYCARD expression varied in several cancers and was associated with prognosis, immune-related genes, published biomarkers, and immunotherapy response. Of note, PYCARD expression was upregulated in renal cancers with high diagnostic ability. Upregulation of PYCARD was correlated with worse prognosis in KIRC and external validation cohorts. In conclusion, PYCARD demonstrated strong correlations with prognosis, immune response, and disease progression in pan-cancer analysis. In ccRCC, PYCARD might serve as a biomarker for diagnosis and therapeutic target-boosting immunotherapy response.

Large-Scale Proteomics Data Reveal Integrated Prognosis-Related Protein Signatures and Role of SMAD4 and RAD50 in Prognosis and Immune Infiltrations of Prostate Cancer Microenvironment.

As prostate cancer (PCa) is one of the most commonly diagnosed cancer worldwide, identifying potential prognostic biomarkers is crucial. In this study, the survival information, gene expression, and protein expression data of 344 PCa cases were collected from the Cancer Proteome Atlas (TCPA) and the Cancer Genome Atlas (TCGA) to investigate the potential prognostic biomarkers. The integrated prognosis-related proteins (IPRPs) model was constructed based on the risk score of each patients using machine-learning algorithm. IPRPs model suggested that Elevated RAD50 expression (p = 0.016) and down-regulated SMAD4 expression (p = 0.017) were significantly correlated with unfavorable outcomes for PCa patients. Immunohistochemical (IHC) staining and western blot (WB) analysis revealed significant differential expression of SMAD4 and RAD50 protein between tumor and normal tissues in validation cohort. According to the overall IHC score, patients with low SMAD4 (p < 0.0001) expression and high RAD50 expression (p = 0.0001) were significantly correlated with poor outcomes. Besides, expression of SMAD4 showed significantly negative correlation with most immune checkpoint molecules, and the low SMAD4 expression group exhibited significantly high levels of LAG3 (p < 0.05), TGFß (p < 0.001), and PD-L1 (p < 0.05) compared with the high SMAD4 expression group in the validation cohort. Patients with low SMAD4 expression had significantly higher infiltration of memory B cells (p = 0.002), CD8 + T cells (p < 0.001), regulatory T cells (p = 0.006), M2-type macrophages (p < 0.001), and significantly lower infiltration of naïve B cells (p = 0.002), plasma cells (p < 0.001), resting memory CD4 + T cells (p < 0.001) and eosinophils (p = 0.045). Candidate proteins were mainly involved in antigen processing and presentation, stem cell differentiation, and type I interferon pathways. Supplementary Information: The online version contains supplementary material available at 10.1007/s43657-022-00070-1.