Dataset Information

Clinicopathological and Molecular Prognostic Classifier for Intermediate/High-Risk Clear Cell Renal Cell Carcinoma.

ABSTRACT: The probability of tumor progression in intermediate/high-risk clear cell renal cell carcinoma (ccRCC) is highly variable, underlining the lack of predictive accuracy of the current clinicopathological factors. To develop an accurate prognostic classifier for these patients, we analyzed global gene expression patterns in 13 tissue samples from progressive and non-progressive ccRCC using Illumina Hi-seq 4000. Expression levels of 22 selected differentially expressed genes (DEG) were assessed by nCounter analysis in an independent series of 71 ccRCCs. A clinicopathological-molecular model for predicting tumor progression was developed and in silico validated in a total of 202 ccRCC patients using the TCGA cohort. A total of 1202 DEGs were found between progressive and non-progressive intermediate/high-risk ccRCC in RNAseq analysis, and seven of the 22 DEGs selected were validated by nCounter. Expression of HS6ST2, pT stage, tumor size, and ISUP grade were found to be independent prognostic factors for tumor progression. A risk score generated using these variables was able to distinguish patients at higher risk of tumor progression (HR 7.27; p < 0.001), consistent with the results obtained from the TCGA cohort (HR 2.74; p < 0.002). In summary, a combined prognostic algorithm was successfully developed and validated. This model may aid physicians to select high-risk patients for adjuvant therapy.

SUBMITTER: Roldan FL

PROVIDER: S-EPMC8699125 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature

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Clinicopathological and Molecular Prognostic Classifier for Intermediate/High-Risk Clear Cell Renal Cell Carcinoma.

Roldán Fiorella L FL Lozano Juan J JJ Ingelmo-Torres Mercedes M Carrasco Raquel R Díaz Esther E Ramirez-Backhaus Miguel M Rubio José J Reig Oscar O Alcaraz Antonio A Mengual Lourdes L Izquierdo Laura L

Cancers 20211217 24

The probability of tumor progression in intermediate/high-risk clear cell renal cell carcinoma (ccRCC) is highly variable, underlining the lack of predictive accuracy of the current clinicopathological factors. To develop an accurate prognostic classifier for these patients, we analyzed global gene expression patterns in 13 tissue samples from progressive and non-progressive ccRCC using Illumina Hi-seq 4000. Expression levels of 22 selected differentially expressed genes (DEG) were assessed by n ...[more]

PMID: 34944958

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Project description:BackgroundNecroptosis, a recently identified type of programmed necrotic cell death, is closely related to the tumorigenesis and development of cancer. However, it remains unclear whether necroptosis-associated long noncoding RNAs (lncRNAs) can be used to predict the prognosis of kidney renal clear cell carcinoma (KIRC). This work was designed to probe the possible prognostic worth of necroptosis-associated lncRNAs along with their impact on the tumor microenvironment (TME) in KIRC.MethodsThe Cancer Genome Atlas (TCGA) database was used to extract KIRC gene expression and clinicopathological data. Pearson correlation analysis was used to evaluate necroptosis-associated lncRNAs against 159 known necroptosis-associated genes. To define molecular subtypes, researchers used univariate Cox regression analysis and consensus clustering, as well as clinical significance, TME, and tumor immune cells in each molecular subtype. We develop the necroptosis-associated lncRNA prognostic model using univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) regression analysis. Patients were divided into high- and low-risk groups according to prognostic model. Moreover, comprehensive analyses, including prognostic value, gene set enrichment analysis (GSEA), immune infiltration, and immune checkpoint gene expression, were performed between the two risk groups. Finally, anticancer drug sensitivity analyses were employed for assessing associations for necroptosis-associated lncRNA expression profile and anticancer drug chemosensitivity.ResultsThrough univariate analysis, sixty-nine necroptosis-associated lncRNAs were found to have a significant relationship with KIRC prognosis. Two molecular clusters were identified, and significant differences were found with respect to clinicopathological features and prognosis. The segregation of patients into two risk groups was done by the constructed necroptosis-associated lncRNA model. The survival prognosis, clinical features, degree of immune cell infiltration, and expression of immune checkpoint genes of high-risk and low-risk groups were all shown to vary.ConclusionsOur study identified a model of necroptosis-associated lncRNA signature and revealed its prognostic role in KIRC. It is expected to provide a reference for the screening of KIRC prognostic markers and the evaluation of immune response.

Project description:Molecular mechanisms of progression of clear cell renal cell carcinoma (ccRCC) have been proven with recent genomic or transcriptional analyses. However, it is still difficult to apply these analyses to daily clinical practice owing to economical and practical issues. Here, we established a pathology-based, postoperative prognostic classification based on the well-validated transcriptional classifier, ClearCode34, in ccRCC. A total of 342 cases with available tissue were identified and randomly allocated into a discovery cohort (n = 138) and a validation cohort (n = 204). Levels of mRNA were quantified using a nCounter Digital Analyzer, and the ccA/ccB subtypes were determined. Histological and immunohistochemistry (IHC) analyses were subsequently performed to establish a pathology-based classification based on the mRNA levels. Finally, the prognostic ability of the new classifier was evaluated in both the discovery and validation cohorts. Of 138 cases in the discovery cohort, 78 (56.5%) and 60 (43.5%) were assigned to the ccA and ccB subtypes, respectively. Proangiogenic genes, neuropilin 1 (NRP1) and regulator of G protein signalling 5 (RGS5), were especially overexpressed in all ccRCC samples and were enriched in ccA-assigned tumours. Histologically, tumour necrosis and the sarcomatoid feature were associated with the ccB subtype. In IHC analyses, expression of NRP1, RGS5, and forkhead box M1 (FOXM1), an epithelial-mesenchymal transition-related factor, significantly correlated with the ccA/ccB subtypes. Combining these three IHC factors and tumour necrosis, we developed the IHC/histology-based classifier, which showed good concordance with the ClearCode34 classifier with an accuracy of 0.80. The established classification significantly stratified relapse-free, cancer-specific, and overall survival rates in both the discovery and validation cohorts. The novel molecular pathology classifier integrating NRP1, RGS5, FOXM1, and tumour necrosis may enable the stratification of oncological outcomes for patients with ccRCC undergoing resection surgery.

Dataset Information

Clinicopathological and Molecular Prognostic Classifier for Intermediate/High-Risk Clear Cell Renal Cell Carcinoma.

Publications

Clinicopathological and Molecular Prognostic Classifier for Intermediate/High-Risk Clear Cell Renal Cell Carcinoma.

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