Functional enrichment analysis of LYSET and identification of related hub gene signatures as novel biomarkers to predict prognosis and immune infiltration status of clear cell renal cell carcinoma.

The latest research shows that the lysosomal enzyme trafficking factor (LYSET) encoded by TMEM251 is a key regulator of the amino acid metabolism reprogramming (AAMR) and related pathways significantly correlate with the progression of some tumors. The purpose of this study was to explore the potential pathways of the TMEM251 in clear cell renal cell carcinoma (ccRCC) and establish related predictive models based on the hub genes in these pathways for prognosis and tumor immune microenvironment (TIME). We obtained mRNA expression data and clinical information of ccRCC samples from The Cancer Genome Atlas (TCGA), E-MATE-1980, and immunotherapy cohorts. Single-cell sequencing data (GSE152938) were downloaded from the Gene Expression Omnibus (GEO) database. We explored biological pathways of the LYSET by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of TMEM251-coexpression genes. The correlation of LYSET-related pathways with the prognosis was conducted by Gene Set Variation Analysis (GSVA) and unsupervised cluster analysis. The least absolute shrinkage and selection operator (LASSO) and Cox regression were used to identify hub prognostic genes and construct the risk score. Immune infiltration analysis was conducted by CIBERSORTx and Tumor Immune Estimation Resource (TIMER) databases. The predictive value of the risk score and hub prognostic genes on immunotherapy responsiveness was analyzed through the tumor mutation burden (TMB) score, immune checkpoint expression, and survival analysis. Immunohistochemistry (IHC) was finally used to verify the expressions of hub prognostic genes. The TMEM251 was found to be significantly correlated with some AAMR pathways. AAGAB, ENTR1, SCYL2, and WDR72 in LYSET-related pathways were finally identified to construct a risk score model. Immune infiltration analysis showed that LYSET-related gene signatures significantly influenced the infiltration of some vital immune cells such as CD4 + cells, NK cells, M2 macrophages, and so on. In addition, the constructed risk score was found to be positively correlated with TMB and some common immune checkpoint expressions. Different predictive values of these signatures for Nivolumab therapy responsiveness were also uncovered in immunotherapy cohorts. Finally, based on single-cell sequencing analysis, the TMEM251 and the hub gene signatures were found to be expressed in tumor cells and some immune cells. Interestingly, IHC verification showed a potential dual role of four hub genes in ccRCC progression. The novel predictive biomarkers we built may benefit clinical decision-making for ccRCC. Our study may provide some evidence that LYSET-related gene signatures could be novel potential targets for treating ccRCC and improving immunotherapy efficacy. Our nomogram might be beneficial to clinical choices, but the results need more experimental verifications in the future.

Chen Y ，He J ，Jin T ，Zhang Y ，Ou Y ... -  《-》

PBRM1 mutation and WDR72 expression as potential combinatorial biomarker for predicting the response to Nivolumab in patients with ccRCC: a tumor marker prognostic study.

Chang Q ，Sun J ，Zhao S ，Li L ，Zhang N ，Yan L ，Fan Y ，Liu J ... -  《Aging-US》

Identification and verification of a novel anoikis-related gene signature with prognostic significance in clear cell renal cell carcinoma.

Clear cell renal cell carcinomas (ccRCCs) are the most common form of renal cancer in the world. The loss of extracellular matrix (ECM) stimulates cell apoptosis, known as anoikis. A resistance to anoikis in cancer cells is believed to contribute to tumor malignancy, particularly metastasis; however, the potential influence of anoikis on the prognosis of ccRCC patients is not fully understood. In this study, anoikis-related genes (ARGs) with discrepant expression were selected from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. The anoikis-related gene signature (ARS) was built using a combination of the univariate Cox and least absolute shrinkage and selection operator (LASSO) analyses. ARS was also evaluated for their prognostic value. We explored the tumor microenvironment and enrichment pathways between different clusters of ccRCC. We also examined differences in clinical characteristics, immune cell infiltration and drug sensitivity between the high- and low-risk sets. In addition, we utilized three external databases and quantitative real-time polymerase chain reaction (qRT-PCR) to validate the expression and prognosis of ARGs. Eight ARGs (PLAUR, HMCN1, CDKN2A, BID, GLI2, PLG, PRKCQ and IRF6) were identified as anoikis-related prognostic factors. According to Kaplan-Meier (KM) analysis, ccRCC patients with high-risk ARGs have a worse prognosis. The risk score was found to be a significant independent prognostic indicator. According to tumor microenvironment (TME) scores, stromal score, immune score, and estimated score of the high-risk group were superior to those of the low-risk group. There were significant differences between the two groups regarding the amount of infiltrated immune cells, immune checkpoint expression as well as drug sensitivity. A nomogram was constructed using ccRCC clinical features and risk scores. The signature and the nomogram both performed well in predicting overall survival (OS) for ccRCC patients. According to a decision curve analysis (DCA), clinical treatment options for patients with ccRCC could be improved using this model. The results of validation from external databases and qRT-PCR were basically agreement with findings in TCGA and GEO databases. The ARS serving as biomarkers may provide an important reference for individual therapy of ccRCC patients.

He Z ，Gu Y ，Yang H ，Fu Q ，Zhao M ，Xie Y ，Liu Y ，Du W ... -  《-》

Identification and validation of prognostic and tumor microenvironment characteristics of necroptosis index and BIRC3 in clear cell renal cell carcinoma.

Wei K ，Zhang X ，Yang D 《PeerJ》

Immune regulation and prognosis indicating ability of a newly constructed multi-genes containing signature in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common renal malignancy, although newly developing targeted therapy and immunotherapy have been showing promising effects in clinical treatment, the effective biomarkers for immune response prediction are still lacking. The study is to construct a gene signature according to ccRCC immune cells infiltration landscape, thus aiding clinical prediction of patients response to immunotherapy. Firstly, ccRCC transcriptome expression profiles from Gene Expression Omnibus (GEO) database as well as immune related genes information from IMMPORT database were combine applied to identify the differently expressed meanwhile immune related candidate genes in ccRCC comparing to normal control samples. Then, based on protein-protein interaction network (PPI) and following module analysis of the candidate genes, a hub gene cluster was further identified for survival analysis. Further, LASSO analysis was applied to construct a signature which was in succession assessed with Kaplan-Meier survival, Cox regression and ROC curve analysis. Moreover, ccRCC patients were divided as high and low-risk groups based on the gene signature followed by the difference estimation of immune treatment response and exploration of related immune cells infiltration by TIDE and Cibersort analysis respectively among the two groups of patients. Based on GEO and IMMPORT databases, a total of 269 differently expressed meanwhile immune related genes in ccRCC were identified, further PPI network and module analysis of the 269 genes highlighted a 46 genes cluster. Next step, Kaplan-Meier and Cox regression analysis of the 46 genes identified 4 genes that were supported to be independent prognosis indicators, and a gene signature was constructed based on the 4 genes. Furthermore, after assessing its prognosis indicating ability by both Kaplan-Meier and Cox regression analysis, immune relation of the signature was evaluated including its association with environment immune score, Immune checkpoint inhibitors expression as well as immune cells infiltration. Together, immune predicting ability of the signature was preliminary explored. Based on ccRCC genes expression profiles and multiple bioinformatic analysis, a 4 genes containing signature was constructed and the immune regulation of the signature was preliminary explored. Although more detailed experiments and clinical trials are needed before potential clinical use of the signature, the results shall provide meaningful insight into further ccRCC immune researches.

Gui Z ，Du J ，Wu N ，Shen N ，Yang Z ，Yang H ，Wang X ，Zhao N ，Zeng Z ，Wei R ，Ma W ，Wang C ... -  《BMC CANCER》