Proteogenomics of clear cell renal cell carcinoma response to tyrosine kinase inhibitor.

The tyrosine kinase inhibitor (TKI) Sunitinib is one the therapies approved for advanced renal cell carcinoma. Here, we undertake proteogenomic profiling of 115 tumors from patients with clear cell renal cell carcinoma (ccRCC) undergoing Sunitinib treatment and reveal the molecular basis of differential clinical outcomes with TKI therapy. We find that chromosome 7q gain-induced mTOR signaling activation is associated with poor therapeutic outcomes with Sunitinib treatment, whereas the aristolochic acid signature and VHL mutation synergistically caused enhanced glycolysis is correlated with better prognosis. The proteomic and phosphoproteomic analysis further highlights the responsibility of mTOR signaling for non-response to Sunitinib. Immune landscape characterization reveals diverse tumor microenvironment subsets in ccRCC. Finally, we construct a multi-omics classifier that can detect responder and non-responder patients (receiver operating characteristic-area under the curve, 0.98). Our study highlights associations between ccRCC molecular characteristics and the response to TKI, which can facilitate future improvement of therapeutic responses.

The function and mechanisms of action of circular RNAs in Urologic Cancer.

Kidney, bladder, and prostate cancer are the three major tumor types of the urologic system that seriously threaten human health. Circular RNAs (CircRNAs), special non-coding RNAs with a stabile structure and a unique back-splicing loop-forming ability, have received recent scientific attention. CircRNAs are widely distributed within the body, with important biologic functions such as sponges for microRNAs, as RNA binding proteins, and as templates for regulation of transcription and protein translation. The abnormal expression of circRNAs in vivo is significantly associated with the development of urologic tumors. CircRNAs have now emerged as potential biomarkers for the diagnosis and prognosis of urologic tumors, as well as targets for the development of new therapies. Although we have gained a better understanding of circRNA, there are still many questions to be answered. In this review, we summarize the properties of circRNAs and detail their function, focusing on the effects of circRNA on proliferation, metastasis, apoptosis, metabolism, and drug resistance in kidney, bladder, and prostate cancers.

Proteogenomic characterization of MiT family translocation renal cell carcinoma.

Microphthalmia transcription factor (MiT) family translocation renal cell carcinoma (tRCC) is a rare type of kidney cancer, which is not well characterized. Here we show the comprehensive proteogenomic analysis of tRCC tumors and normal adjacent tissues to elucidate the molecular landscape of this disease. Our study reveals that defective DNA repair plays an important role in tRCC carcinogenesis and progression. Metabolic processes are markedly dysregulated at both the mRNA and protein levels. Proteomic and phosphoproteome data identify mTOR signaling pathway as a potential therapeutic target. Moreover, molecular subtyping and immune infiltration analysis characterize the inter-tumoral heterogeneity of tRCC. Multi-omic integration reveals the dysregulation of cellular processes affected by genomic alterations, including oxidative phosphorylation, autophagy, transcription factor activity, and proteasome function. This study represents a comprehensive proteogenomic analysis of tRCC, providing valuable insights into its biological mechanisms, disease diagnosis, and prognostication.

The expression and prognostic value of transporter 1, ATP binding cassette subfamily B member in clear cell renal cell cancer with experimental validation.

Transporter associated with antigen processing 1(TAP1) serves as a protein to transport antigenic peptides from the surface of the endoplasmic reticulum to the lumen of the endoplasmic reticulum when the antigens are presented by major histocompatibility complex type I (MHC-I), which has been identified to play a critical role in antigen presentation in innate immunity. In tumors, the role of TAP1 seems to remain controversial. On the one hand, given the role of TAP1 in antigen presentation, it is indicated that high TAP1 expression corresponds to the emergence of more neoantigens epitopes that facilitate the recognition for phagocytes, T cells and other cells. On the other hand, the genetic ablation of transporter associated with antigen processing (TAP) results in the presentation of new class I-restricted epitopes encoded in house-keeping products. Opposite result has been revealed by studies in other tumors suggest, which implies a more complex function of TAP1. Therefore, it's significant to clarify the role of TAP1 in clear cell renal cell carcinoma (ccRCC). In this study, we found the elevated expression levels in mRNA and protein of TAP1 in ccRCC tissues, which indicated a relatively worse prognosis. Transwell assay and Scratch assay in vitro demonstrated the promotive role of TAP1 in ccRCC migration as well as a significant role in metastasis. And the increased expression of TAP1 resulted in more immune cells infiltrated in cancer tissues. TAP1 was also demonstrated to be related to immune regulator genes, as gene set enrichment analysis (GSEA) indicated its significant role in immune regulation. The results of CancerSEA indicated the positive association of the high-level TAP1 expression with epithelial-mesenchymal transition (EMT) and the inverse association with Cell Cycle. The effective drugs were also predicted based on TAP1 expression, of which the high level was indeed associated with resistance to multiple drugs, but some effective drugs still identified based on high TAP1 expression. According to the analysis of various databases, the role of TAP1 in ccRCC was explored, especially in relationship of TAP1 with tumor microenvironment. These results indicate that TAP1 can serve as a potential target for treatment of ccRCC.

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.

A proteogenomic analysis of clear cell renal cell carcinoma in a Chinese population.

Clear cell renal cell carcinoma (ccRCC) is a common and aggressive subtype of renal cancer. Here we conduct a comprehensive proteogenomic analysis of 232 tumor and adjacent non-tumor tissue pairs from Chinese ccRCC patients. By comparing with tumor adjacent tissues, we find that ccRCC shows extensive metabolic dysregulation and an enhanced immune response. Molecular subtyping classifies ccRCC tumors into three subtypes (GP1-3), among which the most aggressive GP1 exhibits the strongest immune phenotype, increased metastasis, and metabolic imbalance, linking the multi-omics-derived phenotypes to clinical outcomes of ccRCC. Nicotinamide N-methyltransferase (NNMT), a one-carbon metabolic enzyme, is identified as a potential marker of ccRCC and a drug target for GP1. We demonstrate that NNMT induces DNA-dependent protein kinase catalytic subunit (DNA-PKcs) homocysteinylation, increases DNA repair, and promotes ccRCC tumor growth. This study provides insights into the biological underpinnings and prognosis assessment of ccRCC, revealing targetable metabolic vulnerabilities.

Identification of prognostic biomarkers in papillary renal cell carcinoma and PTTG1 may serve as a biomarker for predicting immunotherapy response.

OBJECTIVE: This study aims to identify potential prognostic and therapeutic biomarkers in papillary renal cell carcinoma (pRCC). METHODS: Two microarray datasets were downloaded from the Gene Expression Omnibus (GEO) database and differentially expressed genes (DEGs) were identified. The protein-protein interaction (PPI) networks and functional annotations of DEGs were established. Survival analysis was utilized to evaluate the prognostic significance of the DEGs and the association between the expression level of candidate biomarkers and various tumour-infiltrating immune cells was explored. The role of PTTG1 in tumour microenvironments (TME) was further explored using Single-cell RNA-seq and its prognostic and therapeutic significance was validated in Fudan University Shanghai Cancer Centre (FUSCC) cohort. RESULTS: Eight genes, including BUB1B, CCNB1, CCNB2, MAD2L1, TTK, CDC20, PTTG1, and MCM were found to be negatively associated with patients' prognosis. The expression level of PTTG1 was found to be significantly associated with lymphocytes, immunomodulators, and chemokine in the TCGA cohort. Single-cell RNA-seq information indicated that PTTG1 was strongly associated with the proliferation of T cells. In the FUSCC cohort, the expression level of PTTG1 was also statistically significant for both progression-free survival (PFS) and overall survival (OS) prediction (HR = 2.683, p < .001; HR = 2.673, p = .001). And higher expression level of PTTG1 was significantly associated with immune checkpoint blockade (ICB) response in the FUSCC cohort (χ2=3.99, p < .05). CONCLUSIONS: Eight genes were identified as a prognostic biomarker and the expression level of PTTG1 was also found to serve as a potential predictor for ICB response in pRCC patients.Key messages:Eight genes, including BUB1B, CCNB1, CCNB2, MAD2L1, TTK, CDC20, PTTG1, and MCM were found to be negatively associated with pRCC patients' prognosis.Expression level of PTTG1 was significantly associated with tumour microenvironment including lymphocytes, immunomodulators, and chemokines.Higher expression level of PTTG1 was significantly associated with immune checkpoint blockade (ICB) response in FUSCC cohort.

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.

Survival in Metastatic Renal Cell Carcinoma Patients Treated With Sunitinib With or Without Cryoablation.

BACKGROUND: Percutaneous cryoablation (PCA) has emerged as an alternative to extirpative management of small renal masses in select patients. In recent years, the use of targeted therapies has become mainstream, while the role of PCA in treating primary tumor is not well established among patients with metastatic renal cell carcinoma (mRCC). We sought to evaluate how mRCC patients react to PCA in combination with sunitinib. METHODS: We retrospectively identified patients with mRCC (primary tumor diameter ≤ 7 cm) treated with sunitinib between 2013 and 2019. These patients were categorized by initial treatment (cryoablation followed by sunitinib versus sunitinib only). Oncological outcomes and rate of adverse events were compared. RESULTS: Of the 178 patients analyzed, 65 underwent PCA prior to sunitinib. The median overall survival (OS) in the PCA-sunitinib group was 31.7 months (95% CI; 26.1-37.3), better than the sunitinib-only group, which reported a median OS of 19.8 months (95% CI; 17.1-22.4) (p < 0.001). The median progression-free survival (PFS) in patients treated with PCA-sunitinib versus sunitinib alone was 13.8 months (95% CI; 10.0-17.6) versus 7.2 months (95% CI: 6.1-8.3) (p < 0.005). No significant differences in adverse events were observed (p > 0.05). CONCLUSIONS: PCA combined with sunitinib is associated with better survival outcomes than sunitinib alone in patients with mRCC. Careful patient selection remains warranted. These results should inform future prospective trials.

Hexokinase 3 dysfunction promotes tumorigenesis and immune escape by upregulating monocyte/macrophage infiltration into the clear cell renal cell carcinoma microenvironment.

Purpose: This study aimed to identify the potential prognostic role of HK3 and provide clues about glycolysis and the microenvironmental characteristics of ccRCC. Methods: Based on the Cancer Genome Atlas (TCGA, n = 533) and Gene expression omnibus (GEO) (n = 127) databases, real-world (n = 377) ccRCC cohorts, and approximately 15,000 cancer samples, the prognostic value and immune implications of HK3 were identified. The functional effects of HK3 in ccRCC were analyzed in silico and in vitro. Results: The large-scale findings suggested a significantly higher HK3 expression in ccRCC tissues and the predictive efficacy of HK3 for tumor progression and a poor prognosis. Next, the subgroup survival and Cox regression analyses showed that HK3 serves as a promising and independent predictive marker for the prognosis and survival of patients with ccRCC from bioinformatic databases and real-world cohorts. Subsequently, we found that HK3 could be used to modulate glycolysis and the malignant behaviors of ccRCC cells. The comprehensive results suggested that HK3 is highly correlated with the abundance of immune cells, and specifically stimulates the infiltration of monocytes/macrophages presenting surface markers, regulates the immune checkpoint molecules PD-1 and CTLA-4 of exhaustive T cells, restrains the immune escape of tumor cells, and prompts the immune-rejection microenvironment of ccRCC. Conclusion: In conclusion, the large-scale data first revealed that HK3 could affect glycolysis, promote malignant biologic processes, and predict the aggressive progression of ccRCC. HK3 may stimulate the abundance of infiltrating monocytes/macrophages presenting surface markers and regulate the key molecular subgroups of immune checkpoint molecules of exhaustive T cells, thus inducing the microenvironmental characteristics of active anti-tumor immune responses.

Construction of a robust prognostic model for adult adrenocortical carcinoma: Results from bioinformatics and real-world data.

This study aims to construct a robust prognostic model for adult adrenocortical carcinoma (ACC) by large-scale multiomics analysis and real-world data. The RPPA data, gene expression profiles and clinical information of adult ACC patients were obtained from The Cancer Proteome Atlas (TCPA), Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Integrated prognosis-related proteins (IPRPs) model was constructed. Immunohistochemistry was used to validate the prognostic value of the IPRPs model in Fudan University Shanghai Cancer Center (FUSCC) cohort. 76 ACC cases from TCGA and 22 ACC cases from GSE10927 in NCBI's GEO database with full data for clinical information and gene expression were utilized to validate the effectiveness of the IPRPs model. Higher FASN (P = .039), FIBRONECTIN (P < .001), TFRC (P < .001), TSC1 (P < .001) expression indicated significantly worse overall survival for adult ACC patients. Risk assessment suggested significantly a strong predictive capacity of IPRPs model for poor overall survival (P < .05). IPRPs model showed a little stronger ability for predicting prognosis than Ki-67 protein in FUSCC cohort (P = .003, HR = 3.947; P = .005, HR = 3.787). In external validation of IPRPs model using gene expression data, IPRPs model showed strong ability for predicting prognosis in TCGA cohort (P = .005, HR = 3.061) and it exhibited best ability for predicting prognosis in GSE10927 cohort (P = .0898, HR = 2.318). This research constructed IPRPs model for predicting adult ACC patients' prognosis using proteomic data, gene expression data and real-world data and this prognostic model showed stronger predictive value than other biomarkers (Ki-67, Beta-catenin, etc) in multi-cohorts.

Identification and validation of novel metastasis-related signatures of clear cell renal cell carcinoma using gene expression databases.

Patients with clear cell renal cell carcinoma (ccRCC) typically face aggressive disease progression when metastasis occurs. Here, we screened and identified differentially expressed genes in three microarray datasets from the Gene Expression Omnibus database. We identified 112 differentially expressed genes with functional enrichment as candidate prognostic biomarkers. Lasso Cox regression suggested 10 significant oncogenic hub genes involved in earlier recurrence and poor prognosis of ccRCC. Receiver operating characteristic curves validated the specificity and sensitivity of the Cox regression penalty used to predict prognosis. The area under the curve indexes of the integrated genes scores were 0.758 and 0.772 for overall and disease-free survival, respectively. The prognostic values of ADAMTS9, C1S, DPYSL3, H2AFX, MINA, PLOD2, RUNX1, SLC19A1, TPX2, and TRIB3 were validated through an analysis of 10 hub genes in 380 patients with ccRCC from a real-world cohort. The expression levels of were of high prognostic value for predicting metastatic potential. These findings will likely significantly contribute to our understanding of the underlying mechanisms of ccRCC, which will enhance efforts to optimize therapy.

Large-scale transcriptome profiles reveal robust 20-signatures metabolic prediction models and novel role of G6PC in clear cell renal cell carcinoma.

Clear cell renal cell carcinoma (ccRCC) is the most common and highly malignant pathological type of kidney cancer. We sought to establish a metabolic signature to improve post-operative risk stratification and identify novel targets in the prediction models for ccRCC patients. A total of 58 metabolic differential expressed genes (MDEGs) were identified with significant prognostic value. LASSO regression analysis constructed 20-mRNA signatures models, metabolic prediction models (MPMs), in ccRCC patients from two cohorts. Risk score of MPMs significantly predicts prognosis for ccRCC patients in TCGA (P < 0.001, HR = 3.131, AUC = 0.768) and CPTAC cohorts (P = 0.046, HR = 2.893, AUC = 0.777). In addition, G6PC, a hub gene in PPI network of MPMs, shows significantly prognostic value in 718 ccRCC patients from multiply cohorts. Next, G6Pase was detected high expressed in normal kidney tissues than ccRCC tissues. It suggested that low G6Pase expression significantly correlated with poor prognosis (P < 0.0001, HR = 0.316) and aggressive progression (P < 0.0001, HR = 0.414) in 322 ccRCC patients from FUSCC cohort. Meanwhile, promoter methylation level of G6PC was significantly higher in ccRCC samples with aggressive progression status. G6PC significantly participates in abnormal immune infiltration of ccRCC microenvironment, showing significantly negative association with check-point immune signatures, dendritic cells, Th1 cells, etc. In conclusion, this study first provided the opportunity to comprehensively elucidate the prognostic MDEGs landscape, established novel prognostic model MPMs using large-scale ccRCC transcriptome data and identified G6PC as potential prognostic target in 1,040 ccRCC patients from multiply cohorts. These finding could assist in managing risk assessment and shed valuable insights into treatment strategies of ccRCC.

Development and validation of a robust multigene signature as an aid to predict early relapse in stage I-III clear cell and papillary renal cell cancer.

Background and objectives: Multi-gene signature can be used as prognostic indicator in many types of cancer, but the association with early-relapse in patients with stage I-III clear cell and papillary renal cell cancer (RCC) is unknown. We aim to establish a mRNAs signature for improving prediction of early-relapse in patients with stage I-III clear cell and papillary RCC. Methods: The data of 610 patients with stage I-III RCC from The Cancer Genome Atlas (TCGA) and 270 patients from Fudan University Shanghai Cancer Center (FUSCC) were extracted. Propensity score matching analysis, linear models for microarray data VOOM method, least absolute shrinkage and selection operation Cox regression modeling analysis was conducted in turn for selecting multi-mRNA signature. Survival differences were assessed by Kaplan-Meier estimate and compared using log-rank test. Multivariable Cox regression and time-dependent receiver operating characteristic curves were used to evaluate the association of mRNAs signature with relapse-free survival (RFS). Results: Seventeen mRNAs were identified to constitute the early-relapse signature. Among patients with stage I-III RCC, those with high-risk score calculated from 17 mRNAs signature showed shorter RFS than those with low-risk score, both in TCGA discovery and internal validation sets, and in FUSCC discovery and internal validation sets (all p < 0.05). In multivariable Cox regression analysis, the 17 mRNAs signature remained an independent prognostic factor both in TCGA discovery (HR 2.43, 95%CI 1.98-2.96) and internal validation sets (HR 1.66, 95%CI 1.19-2.30), and FUSCC discovery (HR 1.28, 95%CI 1.13-1.43) and internal validation sets (HR 1.65, 95%CI 1.11-2.48). Additionally, the 17 mRNAs signature achieved a higher accuracy for RFS estimation beyond clinical indicator. Conclusion: The 17 mRNAs signature could classify stage I-III RCC patients into low- or high-risk of early-relapse, and will help to guide interventions to optimize survival outcomes.

Prognostic value of epithelial-mesenchymal transition markers in clear cell renal cell carcinoma.

Epithelial-to-mesenchymal transition (EMT) is important in tumor invasiveness and metastasis. We aimed to determine prognostic value of six key EMT markers (CDH1, CDH2, SNAI1, SNAI2, VIM, TWIST1) in clear cell renal cell carcinoma (ccRCC). A total of 533 ccRCC patients with RNASeq data from The Cancer Genome Atlas (TCGA) cohort were included for analysis. Gene expression of these EMT markers was compared between tumor and normal tissues based on Oncomine database and TCGA cohort. Their correlations with progression-free survival (PFS) and overall survival (OS) were also examined in both TCGA cohort and FUSCC (Fudan University Shanghai Cancer Center) cohort. Cox proportional hazards regression model and Kaplan-Meier plot were used to assess the relative factors. Functional enrichment analyses were utilized to describe biologic function annotations and significantly involved hallmarks pathways of each gene. We found that Epithelial marker, CDH1 expression was lower, while mesenchymal markers (CDH2, SNAI1, VIM, TWIST1) expression was higher in ccRCC primary tumors. In the TCGA cohort, we found that patients with higher expression of VIM, TWIST1 or lower expression of CDH1 had worse prognosis. Further, in the FUSCC cohort, we confirmed the predictive ability of mesenchymal markers and epithelial marker expression in PFS and OS of ccRCC patients. After generating Cox regression models, EMT markers (CDH1, SNAI1, VIM, and TWIST1) were independent prognostic factors of both PFS and OS in ccRCC patients. Our preliminary EMT prediction model can facilitate further screening of EMT biomarkers and cast a better understanding of EMT gene function in ccRCC.

Prognostic implication and functional annotations of Rad50 expression in patients with prostate cancer.

Increasing evidence has shown that Rad50, a protein involved in the DNA damage repair process, significantly correlated with tumor prognosis. This study focused on Rad50 expression in tumor samples and its prognostic value for patients with prostate cancer (PCa). In this study, significantly elevated Rad50 expression in PCa tissues compared to normal tissues (P < .01). Five independent Oncomine databases validated significant differential expression of Rad50 (P < .001). Hence, 80 patients with PCa from Fudan University Shanghai Cancer Center (FUSCC) and 351 patients with PCa with available protein expression data from The Cancer Genome Atlas (TCGA) were included to investigate the survival benefit. Univariate and multivariate Cox regression analyses were performed to investigate the significance of clinicopathological factors on disease-free survival (DFS) and overall survival (OS). Kaplan-Meier analysis indicated that elevated Rad50 protein expression levels significantly correlated with unfavorable DFS (P = .005) in the FUSCC cohort and poorer OS (P = .04) in TCGA cohort. Furthermore, coregulation analysis of proteins indicated that 76 coregulated proteins were associated with Rad50, while 11 most highly involved hub proteins, including Rad50, MRE11A, DUT, POLR3A, MCM3AP, RECQL, PNPT1, RANBP3, DDX1, SNRPB, and UGN, were significantly coregulated in the protein-protein interaction network. Functional enrichment analysis consecutively indicated significant functions and signaling pathways including DNA replication, spliceosome, DNA geometric change, homologous recombination, and G2M checkpoint. This study first reveals that elevated Rad50 expression is significantly associated with aggressive progression and poor survival for patients with PCa. Together, these data suggest that Rad50 may act as an oncoprotein, guide the molecular diagnosis, and may shed light on novel individual therapeutic strategies for progressive PCa patients.

Inactivation of the AMPK-GATA3-ECHS1 Pathway Induces Fatty Acid Synthesis That Promotes Clear Cell Renal Cell Carcinoma Growth.

The tumorigenic role and underlying mechanisms of lipid accumulation, commonly observed in many cancers, remain insufficiently understood. In this study, we identified an AMP-activated protein kinase (AMPK)-GATA-binding protein 3 (GATA3)-enoyl-CoA hydratase short-chain 1 (ECHS1) pathway that induces lipid accumulation and promotes cell proliferation in clear cell renal cell carcinoma (ccRCC). Decreased expression of ECHS1, which is responsible for inactivation of fatty acid (FA) oxidation and activation of de novo FA synthesis, positively associated with ccRCC progression and predicted poor patient survival. Mechanistically, ECHS1 downregulation induced FA and branched-chain amino acid (BCAA) accumulation, which inhibited AMPK-promoted expression of GATA3, a transcriptional activator of ECHS1. BCAA accumulation induced activation of mTORC1 and de novo FA synthesis, and promoted cell proliferation. Furthermore, GATA3 expression phenocopied ECHS1 in predicting ccRCC progression and patient survival. The AMPK-GATA3-ECHS1 pathway may offer new therapeutic approaches and prognostic assessment for ccRCC in the clinic. SIGNIFICANCE: These findings uncover molecular mechanisms underlying lipid accumulation in ccRCC, suggesting the AMPK-GATA3-ECHS1 pathway as a potential therapeutic target and prognostic biomarker.

The Prognostic Value of Programmed Death-Ligand 1 in a Chinese Cohort With Clear Cell Renal Cell Carcinoma.

Objective: To investigate the association between tumor PD-L1 expression and patient survival to determine whether PD-L1 represents an independent prognostic feature for patients with non-metastatic clear cell renal cell carcinoma (RCC). Patients and Methods: The tissue bank of the Fudan University Shanghai Cancer Center was queried to identity tissue samples of patients treated with radical nephrectomy, for non-metastatic sporadic clear cell RCC (ccRCC) between 2008 and 2015. Real-time polymerase chain reaction and immunohistochemistry staining was performed to detect the expression level of PD-L1 in paired cancer tissue and paracancerous tissue. Results: Three-hundred-and-thirty patients were enrolled in this study, with a mean age of 55.0 years at surgery and a mean tumor size of 5.2 cm. Two-hundred-and-forty-two (73.3%) and 88 (26.7%) patients showed a high and low expression of PD-L1 mRNA, respectively, while 254 patients had positive PD-L1 immunohistochemistry staining. Two-hundred-and-ninety-two patients had consistent results for mRNA and the PD-L1 protein based on these different detection methods. Patients with high PD-L1 expression were more likely to exhibit adverse pathologic features including an advanced T stage (P = 0.002) and lymph node metastasis (P = 0.044). The Kaplan-Meier curves of PFS and OS stratified by PD-L1 expression had a statistically significant difference. PD-L1 expression maintained a significant predictive role for PFS and OS in the multivariate cox model. Conclusions: Our data suggests that PD-L1 correlates with prognosis in RCC and targeting the PD-1/PD-L1 pathway should be considered in the treatment of RCC patients.

Genetic variants in RTEL1 influencing telomere length are associated with prostate cancer risk.

Telomere length measured in lymphocytes has been evaluated as a potential biomarker for prostate cancer (PCa) risk. Identifying genetic variants that affect telomere length and testing their association with disease could clarify any causal role. We therefore investigated associations between genetic variants in three telomere length-related genes and PCa risk in a case-control study. The influence of these variants on the leukocyte telomere lengths was then appraised by real-time PCR. RTEL1 rs2297441 [odds ratio (OR): 1.23; 95% confidence interval (CI): 1.03-1.46, P = 0.021] and rs3208008 (OR: 1.23; 95% CI: 1.03-1.46) were associated with PCa risk. These two risk single nucleotide polymorphisms (SNPs) (OR: 0.59; 95% CI: 0.39-0.89, P = 0.012 and OR: 0.58; 95% CI: 0.38-0.87, P = 0.009, respectively) and another SNP PARP1 rs1136410 (OR: 1.53; 95% CI: 1.01-2.31, P = 0.043) were also associated with leukocyte telomere length. These findings support that genetic determinants of telomere length may influence PCa risk.