Deciphering glutamine metabolism patterns for malignancy and tumor microenvironment in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer characterized by metabolic reprogramming. Glutamine metabolism is pivotal in metabolic reprogramming, contributing to the significant heterogeneity observed in ccRCC. Consequently, developing prognostic markers associated with glutamine metabolism could enhance personalized treatment strategies for ccRCC patients. This study obtained RNA sequencing and clinical data from 763 ccRCC cases sourced from multiple databases. Consensus clustering of 74 glutamine metabolism related genes (GMRGs)- profiles stratified the patients into three clusters, each of which exhibited distinct prognosis, tumor microenvironment, and biological characteristics. Then, six genes (SMTNL2, MIOX, TMEM27, SLC16A12, HRH2, and SAA1) were identified by machine-learning algorithms to develop a predictive signature related to glutamine metabolism, termed as GMRScore. The GMRScore showed significant differences in clinical prognosis, expression profile of immune checkpoints, abundance of immune cells, and immunotherapy response of ccRCC patients. Besides, the nomogram incorporating the GMRScore and clinical features showed strong predictive performance in prognosis of ccRCC patients. ALDH18A1, one of the GRMGs, exhibited elevated expression level in ccRCC and was related to markedly poorer prognosis in the integrated cohort, validated by proteomic profiling of 232 ccRCC samples from Fudan University Shanghai Cancer Center (FUSCC). Conducting western blotting, CCK-8, transwell, and flow cytometry assays, we found the knockdown of ALDH18A1 in ccRCC significantly promoted apoptosis and inhibited proliferation, invasion, and epithelial-mesenchymal transition (EMT) in two human ccRCC cell lines (786-O and 769-P). In conclusion, we developed a glutamine metabolism-related prognostic signature in ccRCC, which is tightly linked to the tumor immune microenvironment and immunotherapy response, potentially facilitating precision therapy for ccRCC patients. Additionally, this study revealed the key role of ALDH18A1 in promoting ccRCC progression for the first time.

Construction of cuproptosis signature based on bioinformatics and experimental validation in clear cell renal cell carcinoma.

BACKGROUND: Cuproptosis was defined as a novel nonapoptotic cell death pathway and its potential function in clear cell renal cell carcinoma (ccRCC) remains unclear. METHODS: We obtained gene expression profiles, somatic mutation and corresponding clinical information of 881 ccRCC samples from 3 cohorts including the cancer genome atlas cohort, GSE29609 cohort and CheckMate 025 cohort. As described in the latest published article, we enrolled 16 genes as cuproptosis-related genes (CRGs). We explored the expression level, variants and copy number variation of the CRGs. Univariate and multi-variate regression were utilized to assess the prognostic significance of the CRGs. Non-negative matrix factorization was used to identify potential subgroup and gene set variation analysis was used to explore the potential biological functions. CIBERSORT, ESTIMATE algorithm and single sample gene set enrichment analysis were used to evaluate the tumor microenvironment. In vitro experiments including CCK-8, transwell and wound healing assays were utilized to explore the potential biological function of DLAT in ccRCC. RESULTS: We found that except for CDKN2A, the CRGs were positively associated with patients' OS. Cuproptosis cluster, cuproptosis gene cluster and cuproptosis score were established, respectively, and higher cuproptosis score was significantly associated with a worse OS in ccRCC (p < 0.001). The area under the receiver operating characteristic curve of the cuproptosis-related nomogram at 1 year, 3 years, 5 years was 0.858, 0.821 and 0.78, respectively. In addition, we found that the cuproptosis score was positively associated with PDCD1, CTLA4 expression level, thus the cuproptosis score may also reflect the dysfunction of tumor infiltrating immune cells. In vitro experiments indicated that overexpression of DLAT could inhibited the migration and proliferation ability of ccRCC cells. CONCLUSION: Our findings identify a novel cuproptosis-related signature and the cuproptosis characteristics may influence the anti-tumor immunity though complex regulating networks, and thus cuproptosis may play a role in developing novel therapeutic target of ccRCC.

Protein Arginine Methyltransferases Refine the Classification of Clear Cell Renal Cell Carcinoma with Distinct Prognosis and Tumor Microenvironment Characteristics.

Background: Clear cell renal cell carcinoma (ccRCC) is an aggressive urological cancer that originates from the proximal tubular epithelium. As one of the most common post-translational modification, protein arginine methylation plays a pivotal role in various cancer-associated biological functions, especially in cancer immunity. Therefore, constructing a protein arginine methylation-related prognostic signature would be beneficial in guiding better personalized clinical management for patients with ccRCC. Methods: Based on the multi-omics profiling of the expression levels of eight protein arginine methyltransferases (PRMTs) in 763 ccRCC samples (from TCGA, CPTAC, EMBL, and ICGC databases), we established a scoring system with machine-learning algorithms to quantify the modification patterns on clinical and immunological characterizations of individual ccRCC patient, which was termed as PRMTScore. Moreover, we utilized two external clinical cohorts receiving immunotherapy (n=302) to validate the reliability of the PRMTScore system. Multiplex immunohistochemistry (mIHC) was performed to characterize the cellular composition of 30 paired ccRCC samples. The proteomic profiling of 232 ccRCC samples obtained from Fudan University Shanghai Cancer Center (FUSCC) was analyzed to validate the protein expression of PRMT5 in ccRCC. Finally, CCK-8, transwell, and wound healing assays were conducted to elucidate the role of PRMT5 in ccRCC in vitro. Results: A total of 763 ccRCC patients with available multi-omics profiling were stratified into two clusters (PRMTCluster A and B) with distinctive prognosis, genomic alterations, tumor microenvironment (TME) characteristics, and fundamental biological mechanisms. Subsequently, protein arginine methylation-related prognostic signature (PRMTScore) was constructed and consisted of SLC16A12, HRH2, F2RL3, and SAA1. The PRMTScore showed remarkable differences in outcomes, immune and stromal fractions, expressions of immune checkpoints, the abundance of immune cells, and immunotherapy response in ccRCC patients. Additionally, preliminary insights unveiled the tumor-suppressive role of PRMT5 in ccRCC, and the signal of PRMT5low significantly predicted aggressive prognosis and the high abundance of PD1+ CD8+ cells in ccRCC. Conclusion: We constructed a PRMTScore system, which showed the potent ability to assess the prognosis, TME characteristics, and immunotherapy response for patients with ccRCC. Moreover, this is the first study to propose that PRMT5 acts as a cancer suppressor in ccRCC.

Plasma proteomic profiling discovers molecular features associated with upper tract urothelial carcinoma.

Upper tract urothelial carcinoma (UTUC) is often diagnosed late and exhibits poor prognosis. Limited data are available on potential non-invasive biomarkers for disease monitoring. Here, we investigate the proteomic profile of plasma in 362 UTUC patients and 239 healthy controls. We present an integrated tissue-plasma proteomic approach to infer the signature proteins for identifying patients with muscle-invasive UTUC. We discover a protein panel that reflects lymph node metastasis, which is of interest in identifying UTUC patients with high risk and poor prognosis. We also identify a ten-protein classifier and establish a progression clock predicting progression-free survival of UTUC patients. Finally, we further validate the signature proteins by parallel reaction monitoring assay in an independent cohort. Collectively, this study portrays the plasma proteomic landscape of a UTUC cohort and provides a valuable resource for further biological and diagnostic research in UTUC.

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.

Special issue "The advance of solid tumor research in China": Multi-omics analysis based on 1311 clear cell renal cell carcinoma samples identifies a glycolysis signature associated with prognosis and treatment response.

In clear cell renal cell carcinoma (ccRCC), glycolysis is enhanced mainly because of the increased expression of key enzymes in glycolysis. Hence, the discovery of new molecular biomarkers for glycolysis may help guide and establish a precise system of diagnosis and treatment for ccRCC. Expression profiles of 1079 tumor samples of ccRCC patients (including 311 patients treated with everolimus or nivolumab) were downloaded from public databases. Proteomic profiles of 232 ccRCC samples were obtained from Fudan University Shanghai Cancer Center (FUSCC). Biological changes, tumor microenvironment and prognostic differences were explored between samples with various glycolysis characteristics. There were significant differences in CD8+ effector T cells, epithelial-to-mesenchymal transition and pan-fibroblast TGFb between the Low and High glyScore groups. The tumor mutation burden of the Low glyScore group was lower than that of the High glyScore group. And higher glyScore was significantly associated with worse overall survival (OS) in 768 ccRCC patients (P < .0001). External validation in FUSCC cohort also indicated that glyScore was of strong ability for predicting OS (P < .05). GlyScore may serve as a biomarker for predicting everolimus response in ccRCC patients due to its significant associations with progression-free survival (PFS). And glyScore may also predict overall survival in patients treated with nivolumab. We calculated the glyScore in ccRCC and the defined glyScore was of strong ability for predicting OS. In addition, glyScore may also serve as a biomarker for predicting PFS in patients treated with everolimus and could predict OS in patients treated with nivolumab.

A novel amino acid metabolism-related gene risk signature for predicting prognosis in clear cell renal cell carcinoma.

Background: Renal cancer is one of the most lethal cancers because of its atypical symptoms and metastatic potential. The metabolism of amino acids and their derivatives is essential for cancer cell survival and proliferation. Thus, the construction of the amino acid metabolism-related risk signature might enhance the accuracy of the prognostic model and shed light on the treatments of renal cancers. Methods: RNA expression and clinical data were downloaded from Santa Cruz (UCSC) Xena, GEO, and ArrayExpress databases. The "DESeq2" package identified the differentially expressed genes. Univariate COX analysis selected prognostic genes related to the metabolism of amino acids. Patients were divided into two clusters using the "ConsensusClusterPlus" package, and the CIBERSORT, ESTIMATE methods were explored to assess the immune infiltrations. The LASSO regression analysis constructed a risk model which was evaluated the prediction accuracy in two independent cohorts. The genomic alterations and drug sensitivity of 18-LASSO-genes were assessed. The differentially expressed genes between two clusters were used to perform functional enrichment analysis and weighted gene co-expression network analysis (WGCNA). Furthermore, external validation of TMEM72 expression was conducted in the FUSCC cohort containing 33 ccRCC patients. Results: The amino acid metabolism-related genes had significant correlations with prognosis. The patients in Cluster A demonstrated better survival, lower Treg cell proportion, higher ESTIMATE scores, and higher cuproptosis-related gene expressions. Amino acid metabolism-related genes with prognostic values were used to construct a risk model and patients in the low risk group were associated with improved outcomes. The Area Under Curve of the risk model was 0.801, 0.777, and 0.767 at the first, second, and third year respectively. The external validation cohort confirmed the stable prognostic value of the risk model. WGCNA identified four gene modules correlated with immune cell infiltrations and cuproptosis. We found that TMEM72 was downregulated in tumors by using TCGA, GEO datasets (p<0.001) and the FUSCC cohort (p=0.002). Conclusion: Our study firstly constructed an 18 amino acid metabolism related signature to predict the prognosis in clear cell renal cell carcinoma. We also identified four potential gene modules potentially correlated with cuproptosis and identified TMEM72 downregulation in ccRCC which deserved further studies.

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.

Stabilization of Notch1 and ß-catenin in response to ER- breast cancer-specific up-regulation of PSAT1 mediates distant metastasis.

Breast cancer has the highest incidence in women worldwide, with a mortality rate second only to lung cancer. Distant metastasis is the major cause of breast cancer-induced death. While upregulation of phosphoserine aminotransferase 1 (PSAT1) has been reported in several cancer types, its specific roles in breast cancer and potential involvement in distant metastasis remain unclear. In our study, PSAT1 was upregulated in metastatic breast cancer and promoted distant metastasis both in vitro and in vivo. Data obtained from transwell and wound healing, colony, sphere assays and detection of various malignant phenotypic markers showed that PSAT1 mediates distant metastasis by promoting invasion, migration, proliferation, anti-apoptosis, stemness and angiogenesis in breast cancer cells. Mechanistically, PSAT1 activated Notch and ß-catenin signaling pathways, leading to enhanced distant metastasis. The clinical relevance of PSAT1 in breast cancer was additionally investigated, which revealed associations of poorer patient prognosis with high PSAT1 mRNA and protein expression. In summary, PSAT1 is a critical molecular regulator of distant metastasis that may effectively serve as a marker of poor prognosis in breast cancer.

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.