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Calycosin (Caly), a flavonoid compound, demonstrates a variety of beneficial properties. However, the specific mechanisms behind Caly's anticancer effects remain largely unexplored. Network pharmacology was used to explore the potential targets of Caly in renal cancer. Additionally, RNA-seq sequencing was used to detect changes in genes in renal cancer cells after Caly treatment. Validation was carried out through quantitative reverse transcription-PCR and Western blot analysis. The luciferase reporter assay was applied to pinpoint the interaction site between MAZ and HAS2. Furthermore, the immunoprecipitation assay was utilized to examine the ubiquitination and degradation of MAZ. In vivo experiments using cell line-derived xenograft mouse models were performed to assess Calycosin's impact on cancer growth. Network pharmacology research suggests Caly plays a role in promoting apoptosis and inhibiting cell adhesion in renal cancer. In vitro, Caly has been observed to suppress proliferation, colony formation, and metastasis of renal cancer cells while also triggering apoptosis. Additionally, it appears to diminish hyaluronic acid synthesis by downregulating HAS2 expression. MAZ is identified as a transcriptional regulator of HAS2 expression. Calycosin further facilitates the degradation of MAZ via the ubiquitin-proteasome pathway. Notably, Caly demonstrates efficacy in reducing the growth of renal cell carcinoma xenograft tumors in vivo. Our findings indicate that Caly suppresses the proliferation, metastasis, and progression of renal cell carcinoma through its action on the MAZ/HAS2 signaling pathway. Thus, Caly represents a promising therapeutic candidate for the treatment of renal cell carcinoma.
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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.
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MicroRNAs , Neoplasias Urológicas , Humanos , RNA Circular/genética , RNA Circular/metabolismo , MicroRNAs/genética , MicroRNAs/metabolismo , Biomarcadores/metabolismo , Biossíntese de Proteínas , Neoplasias Urológicas/diagnóstico , Neoplasias Urológicas/genéticaRESUMO
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.
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Neoplasias do Córtex Suprarrenal/patologia , Carcinoma Adrenocortical/patologia , Biomarcadores Tumorais/genética , Biologia Computacional/métodos , Regulação Neoplásica da Expressão Gênica , Modelos Estatísticos , Microambiente Tumoral , Neoplasias do Córtex Suprarrenal/genética , Neoplasias do Córtex Suprarrenal/metabolismo , Carcinoma Adrenocortical/genética , Carcinoma Adrenocortical/metabolismo , Idoso , Biomarcadores Tumorais/metabolismo , Feminino , Seguimentos , Perfilação da Expressão Gênica , Humanos , Masculino , Prognóstico , Estudos Retrospectivos , Taxa de SobrevidaRESUMO
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.
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Carcinoma de Células Renais/genética , Glucose-6-Fosfatase/genética , Neoplasias Renais/genética , Transcriptoma/genética , Biomarcadores Tumorais/genética , Carcinoma de Células Renais/patologia , Estudos de Coortes , Progressão da Doença , Feminino , Regulação Neoplásica da Expressão Gênica/genética , Humanos , Rim/patologia , Neoplasias Renais/patologia , Masculino , Prognóstico , Microambiente Tumoral/imunologiaRESUMO
BACKGROUND: Growing evidence has demonstrated immune reactivity as a confirmed important carcinogenesis and therapy efficacy for clear cell renal cell carcinoma (ccRCC). Aquaporin 9 (AQP9) is involved in many immune-related signals; however, its role in ccRCC remains to be elucidated. This study investigated AQP9 expression in tumor tissues and defined the prognostic value in ccRCC patients. METHODS: A total of 913 ccRCC patients with available RNA-sequence data from the Cancer Genome Atlas (TCGA) database and Fudan University Shanghai Cancer Center (FUSCC) were consecutively recruited in analyses. Differential transcriptional and proteome expression profiles were obtained and validated using multiple datasets. A partial likelihood test from Cox regression analysis was developed to address the influence of independent factors on progression-free survival (PFS) and overall survival (OS). The Kaplan-Meier method and log-rank test were performed to assess survival. Receiver operating characteristic (ROC) curves were used to describe binary classifier value of AQP9 using area under the curve (AUC) score. Functional enrichment analyses and immune infiltration analysis were used to describe significantly involved hallmark pathways of hub genes. RESULTS: Significantly elevated transcriptional and proteomic AQP9 expressions were found in ccRCC samples. Increased AQP9 mRNA expression was significantly associated with advanced clinicopathological parameters and correlated with shorter PFS and OS in TCGA and FUSCC cohorts (p < 0.001). ROC curves suggested the significant diagnostic and prognostic ability of AQP9 (PFS, AUC = 0.823; OS, AUC = 0.828). Functional annotations indicated that AQP9 is involved in the most significant hallmarks including complement, coagulation, IL6/JAK-STAT3, inflammatory response and TNF-alpha signaling pathways. CONCLUSION: Our study revealed that elevated AQP9 expression was significantly correlated with aggressive progression, poor survival and immune infiltrations in ccRCC patients, and we validated its prognostic value in a real-world cohort. These data suggest that AQP9 may act as an oncogene and a promising prognostic marker in ccRCC.
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Aquaporinas/genética , Biomarcadores Tumorais/genética , Carcinoma de Células Renais/genética , Neoplasias Renais/genética , Idoso , Aquaporinas/metabolismo , Biomarcadores Tumorais/metabolismo , Carcinoma de Células Renais/metabolismo , Carcinoma de Células Renais/patologia , Estudos de Coortes , Feminino , Regulação Neoplásica da Expressão Gênica , Humanos , Estimativa de Kaplan-Meier , Neoplasias Renais/metabolismo , Neoplasias Renais/patologia , Masculino , Pessoa de Meia-Idade , Prognóstico , Intervalo Livre de Progressão , Mapas de Interação de Proteínas , RNA Mensageiro/genética , RNA Mensageiro/metabolismo , Transdução de Sinais , Pesquisa Translacional Biomédica , Regulação para CimaRESUMO
BACKGROUND This study aimed to evaluate the factors associated with a survival benefit for patients with metastatic renal cell carcinoma (mRCC) treated with sunitinib, with and without cytoreductive nephrectomy (CN). MATERIAL AND METHODS This retrospective clinical study included 118 patients with mRCC who were treated with CN and sunitinib (CN-sunitinib) (N=70) and with sunitinib-alone (N=48). Categorical clinicopathological variables were compared with hypothesis tests using contingency tables and a chi-squared test. Independent indicators for progression-free survival (PFS) and overall survival (OS) were analyzed with univariate and multivariate Cox regression models. The Kaplan-Meier method and log-rank test were used to evaluate patient survival. RESULTS The median PFS and OS for the 118 patients were 8.38 and 15.48 months, respectively. There were no significant differences between the CN-sunitinib group and the sunitinib-alone group for either PFS (7.2 months vs. 11.6 months; P=0.525) or OS (16.7 months vs. 15.2 months; P=0.839). Stratification of patients based on clinicopathological characteristics showed that CN was significantly associated with reduced PFS and OS for patients with lymph node metastasis (PFS, P<0.001; OS, P<0.001) and high International Metastatic Renal Cell Carcinoma Database Consortium (IMDC) risk scores (PFS, P=0.003; OS, P=0.011). However, CN was associated with a significant survival benefit for patients with low levels of serum C-reactive protein (CRP<10 mg/L) (PFS, P=0.026; OS, P=0.007). CONCLUSIONS Sunitinib-alone without CN improved the survival of patients with mRCC who had high IMDC risk scores or lymph node metastasis. CN and sunitinib resulted in significantly improved survival in patients with low serum CRP.
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Proteína C-Reativa/metabolismo , Carcinoma de Células Renais/tratamento farmacológico , Sunitinibe/farmacologia , Adulto , Idoso , Antineoplásicos/uso terapêutico , Proteína C-Reativa/análise , Carcinoma de Células Renais/metabolismo , Carcinoma de Células Renais/cirurgia , China , Procedimentos Cirúrgicos de Citorredução/métodos , Intervalo Livre de Doença , Feminino , Humanos , Indóis/uso terapêutico , Estimativa de Kaplan-Meier , Neoplasias Renais/patologia , Masculino , Pessoa de Meia-Idade , Nefrectomia/métodos , Intervalo Livre de Progressão , Modelos de Riscos Proporcionais , Pirróis/uso terapêutico , Estudos Retrospectivos , Sunitinibe/metabolismo , Resultado do TratamentoRESUMO
BACKGROUND The serine peptidase inhibitor Kazal type 13 (SPINK13) gene has tumor suppressor activity, but its role in renal cell carcinoma (RCC) remains unknown. This study aimed to investigate mRNA expression of SPINK13 in clear cell renal cell carcinoma (CCRCC) in human tissue and to use bioinformatics data to investigate the role of SPINK13 expression as a clinicopathological and prognostic biomarker for patients with CCRCC. MATERIAL AND METHODS Patients with CCRCC (N=533) with available RNA sequence data from The Cancer Genome Atlas (TCGA)-CCRCC database were analyzed with patients who had a tissue diagnosis of CCRCC (N=305) at the Fudan University Shanghai Cancer Center (FUSCC). Differential transcriptional and proteome expression profiles were obtained from the ONCOMINE cancer microarray database, TCGA, and the Human Protein Atlas (HPA) database. Quantitative reverse transcription-polymerase chain reaction (RT-qPCR) measured SPINK13 mRNA expression in 305 samples of CCRCC tissue from the FUSCC. The effects of clinicopathological parameters on progression-free survival (PFS) and overall survival (OS) were analyzed using the Kaplan-Meier and log-rank test. RESULTS Transcriptional and proteome expression of SPINK13 were significantly increased CCRCC tissue samples. Increased SPINK13 mRNA expression was significantly associated with reduced PFS and OS in 838 patients with CCRCC patients from the two independent cohorts, the FUSCC and the TCGA-CCRCC cohorts (p<0.01). Gene set enrichment analysis (GSEA) showed that SPINK13 expression was involved in complement, apical junction, epithelial-mesenchymal transition (EMT), glycolysis, hypoxia, and inflammation signaling pathways. CONCLUSIONS Increased expression of SPINK13 was associated with poor prognosis in patients with CCRCC.
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Carcinoma de Células Renais/metabolismo , Neoplasias Renais/metabolismo , Inibidores de Serinopeptidase do Tipo Kazal/metabolismo , Adulto , Idoso , Biomarcadores Tumorais/genética , Biomarcadores Tumorais/metabolismo , Carcinoma de Células Renais/genética , Carcinoma de Células Renais/patologia , Proliferação de Células/fisiologia , Biologia Computacional , Bases de Dados Genéticas , Intervalo Livre de Doença , Transição Epitelial-Mesenquimal , Feminino , Humanos , Estimativa de Kaplan-Meier , Neoplasias Renais/genética , Neoplasias Renais/patologia , Masculino , Pessoa de Meia-Idade , Prognóstico , Inibidores de Serinopeptidase do Tipo Kazal/genéticaRESUMO
BACKGROUND: The association of prostate cancer antigen 3 (PCA3) polymorphism (SNP, rs544190G>A) with metastatic prostate cancer in European descent has been reported. Our aim of the current study was to re-validate the effect of PCA3 polymorphism on prostate cancer risk in an Eastern Chinese population and then estimate possible genetic discrepancies among population. MATERIALS AND METHODS: Taqman assay was employed to determine genotype of SNP rs544190 in 1015 ethnic Han Chinese patients with prostate cancer and 1032 cancerfree controls. Simultaneously, odds ratios (OR) and 95% confidence intervals (95%CI) for risk relationship were calculated by logistic regression models. RESULTS: The statistically significant relationship between PCA3 rs544190G>A and higher prostate cancer risk was not found. Stratification analysis revealed that there was no remarkable association of rs544190 variant AG/AA genotype with prostate cancer risk in every subgroup, except for patients with Gleason score ≤7(3+4). CONCLUSION: Although the results demonstrated that SNP rs544190 was not involved in prostate cancer risk in Eastern Chinese descent, unlike in European population, these might have clinical implications on prostate cancer heterogeneity around the World. To validate these findings, well-designed studies with different ethnic populations are warranted.
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Antígenos de Neoplasias/genética , Povo Asiático/genética , Polimorfismo de Nucleotídeo Único/genética , Neoplasias da Próstata/genética , Medição de Risco/métodos , Idoso , Estudos de Casos e Controles , China , Expressão Gênica , Estudos de Associação Genética , Genótipo , Humanos , Modelos Logísticos , Masculino , Gradação de Tumores , Estadiamento de Neoplasias , Neoplasias da Próstata/etnologia , Neoplasias da Próstata/patologia , Fatores de Risco , Fumar/efeitos adversosRESUMO
BACKGROUND: Artificial Intelligence(AI)-based solutions for Gleason grading hold promise for pathologists, while image quality inconsistency, continuous data integration needs, and limited generalizability hinder their adoption and scalability. METHODS: We present a comprehensive digital pathology workflow for AI-assisted Gleason grading. It incorporates A!MagQC (image quality control), A!HistoClouds (cloud-based annotation), Pathologist-AI Interaction (PAI) for continuous model improvement, Trained on Akoya-scanned images only, the model utilizes color augmentation and image appearance migration to address scanner variations. We evaluate it on Whole Slide Images (WSI) from another five scanners and conduct validations with pathologists to assess AI efficacy and PAI. RESULTS: Our model achieves an average F1 score of 0.80 on annotations and 0.71 Quadratic Weighted Kappa on WSIs for Akoya-scanned images. Applying our generalization solution increases the average F1 score for Gleason pattern detection from 0.73 to 0.88 on images from other scanners. The model accelerates Gleason scoring time by 43% while maintaining accuracy. Additionally, PAI improve annotation efficiency by 2.5 times and led to further improvements in model performance. CONCLUSIONS: This pipeline represents a notable advancement in AI-assisted Gleason grading for improved consistency, accuracy, and efficiency. Unlike previous methods limited by scanner specificity, our model achieves outstanding performance across diverse scanners. This improvement paves the way for its seamless integration into clinical workflows.
Gleason grading is a well-accepted diagnostic standard to assess the severity of prostate cancer in patients' tissue samples, based on how abnormal the cells in their prostate tumor look under a microscope. This process can be complex and time-consuming. We explore how artificial intelligence (AI) can help pathologists perform Gleason grading more efficiently and consistently. We build an AI-based system which automatically checks image quality, standardizes the appearance of images from different equipment, learns from pathologists' feedback, and constantly improves model performance. Testing shows that our approach achieves consistent results across different equipment and improves efficiency of the grading process. With further testing and implementation in the clinic, our approach could potentially improve prostate cancer diagnosis and management.
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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.
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Carcinoma de Células Renais , Neoplasias Renais , Proteogenômica , Humanos , Carcinoma de Células Renais/tratamento farmacológico , Carcinoma de Células Renais/genética , Carcinoma de Células Renais/patologia , Sunitinibe/uso terapêutico , Neoplasias Renais/tratamento farmacológico , Neoplasias Renais/genética , Neoplasias Renais/patologia , Proteômica , Inibidores de Proteínas Quinases/farmacologia , Inibidores de Proteínas Quinases/uso terapêutico , Serina-Treonina Quinases TOR/genética , Microambiente TumoralRESUMO
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.
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Carcinoma de Células de Transição , Neoplasias da Bexiga Urinária , Humanos , Carcinoma de Células de Transição/diagnóstico , Proteômica , Metástase Linfática , MúsculosRESUMO
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.
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Carcinoma de Células Renais , Neoplasias Renais , Biomarcadores , Carcinoma de Células Renais/genética , Carcinoma de Células Renais/terapia , China , Regulação Neoplásica da Expressão Gênica , Humanos , Fatores Imunológicos , Imunoterapia , Neoplasias Renais/genética , Prognóstico , Microambiente Tumoral/genéticaRESUMO
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.
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Carcinoma de Células Renais , Neoplasias Renais , Proteogenômica , Biomarcadores Tumorais/genética , Biomarcadores Tumorais/metabolismo , Carcinoma de Células Renais/patologia , China , Feminino , Humanos , Neoplasias Renais/patologia , MasculinoRESUMO
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.
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Carcinoma de Células Renais , Neoplasias Renais , Microftalmia , Proteogenômica , Humanos , Carcinoma de Células Renais/patologia , Fatores de Transcrição/genética , Microftalmia/genética , Proteômica , Neoplasias Renais/patologia , Fatores de Transcrição de Zíper de Leucina e Hélice-Alça-Hélix Básicos/genética , Translocação GenéticaRESUMO
BACKGROUND: Multiplex urine-based assay emerged outperforms single biomarker (e.g., prostate-specific antigen, PSA) for predicting prostate cancer (CaP), whereas its combined mode has to be fully optimized. Our aim is to determine whether a strategy of combining gene-based, protein-based, metabolite-based with positive, negative makers in urine could optimize a multiplex model for detecting CaP. METHODS: Using quantitative PCR, Western blot, and liquid chromatography-mass spectrometry, expression patterns of PCA3, TMPRSS2: ERG, Annexin A3, Sarcosine, and urine PSA were evaluated in urine samples from 86 untreated patients with CaP and 45 patients with no evidence of malignancy. Multivariate logistic regression analysis was used to generate a final model and receiver-operating characteristic (ROC) analysis and special bootstrap software to assess diagnostic performance of tested variables. RESULTS: The expression patterns of PCA3, TMPRSS2: ERG, Annexin A3, Sarcosine, and a panel including these biomarkers were significant predictors of CaP both in patients with PSA 4-10 ng/ml and in all patients (all P < 0.05). Employing ROC analysis, the area under the curves of the panel in these both cohorts were 0.840 and 0.856, respectively, which outperform that of any single biomarker (PCA3: 0.733 and 0.739; TMPRSS2: ERG: 0.720 and 0.732; Annexin A3: 0.716 and 0.728; Sarcosine: 0.659 and 0.665, respectively). CONCLUSIONS: Compared with single biomarker, the multiplex model including PCA3, TMPRSS2: ERG, Annexin A3 and Sarcosine adds even more to the diagnostic performance for predicting CaP. Further validation experiments and optimization for the strategy of constructing this model are warranted.
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Antígenos de Neoplasias/urina , Biomarcadores Tumorais/urina , Detecção Precoce de Câncer/métodos , Neoplasias da Próstata/diagnóstico , Antígenos de Neoplasias/genética , Área Sob a Curva , Biomarcadores Tumorais/análise , Biomarcadores Tumorais/genética , Western Blotting , Cromatografia Líquida de Alta Pressão , Humanos , Masculino , Espectrometria de Massas , Modelos Teóricos , Reação em Cadeia da Polimerase , Valor Preditivo dos Testes , Neoplasias da Próstata/urina , Curva ROC , Urinálise/métodosRESUMO
More and more studies have revealed that the level of serum prostate specific antigen(PSA) has little value for early diagnosis of prostate cancer (PCa). For example, negative prostate biopsies are as high as 70%-80% for patients with serum PSA ranging between 4 ng/mL and 10 ng/mL. However, the negative results cannot exclude the existence of cancer. In the studies of the early diagnosis of PCa, investigators focused on seeking biomarkers that have higher sensitivity and specificity. Recently, PSA derivatives, HPC1, PCA3, TMPRSS2: ETS, GSTP1, AMACR, GOLPH2, EPCA, sarcosine, and the combination of multiple biomarkers are widely discussed. In this article, we have reviewed their recent development and the prospective value of the combination of multiple biomarkers, which may be helpful for the early diagnosis and the prognostic monitoring of patients with PCa.
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Biomarcadores Tumorais/metabolismo , Neoplasias da Próstata/diagnóstico , Neoplasias da Próstata/metabolismo , Antígenos de Neoplasias/metabolismo , Diagnóstico Precoce , Endorribonucleases/metabolismo , Glutationa S-Transferase pi/metabolismo , Humanos , Masculino , Proteínas de Membrana/metabolismo , Proteínas de Fusão Oncogênica/metabolismo , Antígeno Prostático Específico/metabolismo , Racemases e Epimerases/metabolismo , Sarcosina/metabolismoRESUMO
OBJECTIVES: To analyze the clinical and pathological informations of metastatic prostate cancer patients to find the predictive factors of the survival. METHODS: To filter 364 cases of metastatic prostate cancer in the 940 cases of prostate cancer that were treated in Cancer Hospital Fudan University in Shanghai from March 1998 to June 2009, the cases had hormonal therapy and full clinical and pathological records. All the 364 cases were followed up and the clinical and pathological informations were analyzed, to find the predictive factors that related to the prognosis. Statistic software SPSS 15.0 was used for analysis. Cumulative survival was analyzed by the method of Kaplan-Meier. Cox regression was used for univariate and multivariate analysis. Log-rank method was used for the significance test. RESULTS: The last follow-up date was 30th June 2009 and the median follow-up time was 24 months. At the final follow-up, 240 cases were alive, 109 cases were dead and 15 cases were lost to follow up. The median survival time of metastatic prostate cancer was 64 months, and the one-year, two-year, three-year, four-year, five-year survival rate was 92%, 78%, 66%, 60%, 54%. The univariate analysis indicated that Gleason score (P = 0.033), clinical stage (P < 0.001), the effectiveness of hormonal therapy (P < 0.001), the prostate specific antigen (PSA) nadir during hormonal therapy (P < 0.001) and the time from the start of hormonal therapy to the PSA nadir (P = 0.002) were predictive factors for the survival time of metastatic prostate cancer. The multivariate analysis indicated that the PSA nadir during hormonal therapy (P < 0.001) and the time from the start of hormonal therapy to the PSA nadir (P < 0.001) were independent factors that predict the survival time of metastatic prostate cancer. CONCLUSION: The PSA nadir during hormonal therapy and the time from the start of hormonal therapy to the PSA nadir are independent factors that predict the survival time of metastatic prostate cancer.
Assuntos
Neoplasias da Próstata/terapia , Adulto , Idoso , Idoso de 80 Anos ou mais , Seguimentos , Humanos , Estimativa de Kaplan-Meier , Masculino , Pessoa de Meia-Idade , Prognóstico , Modelos de Riscos Proporcionais , Estudos RetrospectivosRESUMO
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.
Assuntos
Biomarcadores Tumorais , Carcinoma de Células Renais/genética , Carcinoma de Células Renais/mortalidade , Transição Epitelial-Mesenquimal/genética , Neoplasias Renais/genética , Neoplasias Renais/mortalidade , Carcinoma de Células Renais/patologia , Biologia Computacional/métodos , Bases de Dados Genéticas , Feminino , Perfilação da Expressão Gênica , Regulação Neoplásica da Expressão Gênica , Redes Reguladoras de Genes , Humanos , Neoplasias Renais/patologia , Masculino , Anotação de Sequência Molecular , Gradação de Tumores , Estadiamento de Neoplasias , Prognóstico , Curva ROC , Reprodutibilidade dos Testes , Microambiente Tumoral/genéticaRESUMO
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.