ArticleOncotarget2017
Identifying biomarkers of papillary renal cell carcinoma associated with pathological stage by weighted gene co-expression network analysis.
Article in Oncotarget, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed, 33 citations in OpenAlex.
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- Cross-Platform Synaptic Network Analysis of Human Entorhinal Cortex Identifies TWF2 as a Modulator of Dendritic Spine Length.The Journal of neuroscience : the official journal of the Society for Neuroscience · 2023Article
- Identification of Four Novel Prognostic Biomarkers and Construction of Two Nomograms in Adrenocortical Carcinoma: A Multi-Omics Data StudyFrontiers in molecular biosciences · 2022Article
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- Pan-cancer analysis of pathway-based gene expression pattern at the individual level reveals biomarkers of clinical prognosis.Cell reports methods · 2021Article
- Identification of Core Genes Related to Progression and Prognosis of Hepatocellular Carcinoma and Small-Molecule Drug Predication.Frontiers in genetics · 2021Article
- Identification and Validation of a Novel Prognosis Prediction Model in Adrenocortical Carcinoma by Integrative Bioinformatics Analysis, Statistics, and Machine Learning.Frontiers in cell and developmental biology · 2021Article
- Correlating Transcriptional Networks to Papillary Renal Cell Carcinoma Survival: A Large-Scale Coexpression Analysis and Clinical Validation.Oncology research · 2020Article
- Large-scale proteomic analysis of Alzheimer's disease brain and cerebrospinal fluid reveals early changes in energy metabolism associated with microglia and astrocyte activation.Nature medicine · 2020Article
- Identification of pancreatic cancer type related factors by Weighted Gene Co-Expression Network Analysis.Medical oncology (Northwood, London, England) · 2020Article
- A deep learning and similarity-based hierarchical clustering approach for pathological stage prediction of papillary renal cell carcinoma.Computational and structural biotechnology journal · 2020Article
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- Three novel hub genes and their clinical significance in clear cell renal cell carcinoma.Journal of Cancer · 2019Article
- Co-expression network analysis identified KIF2C in association with progression and prognosis in lung adenocarcinoma.Cancer biomarkers : section A of Disease markers · 2019Article
- Novel Biomarkers Associated With Progression and Prognosis of Bladder Cancer Identified by Co-expression Analysis.Frontiers in oncology · 2019Article
- Integrated analysis of long noncoding RNA associated-competing endogenous RNA as prognostic biomarkers in clear cell renal carcinoma.Cancer science · 2018Article
- Identifying miRNA and gene modules of colon cancer associated with pathological stage by weighted gene co-expression network analysis.OncoTargets and therapy · 2018Article
- Identifying a Novel BiomarkerJournal of Cancer · 2018Article
- Identification of Biomarkers Associated With Pathological Stage and Prognosis of Clear Cell Renal Cell Carcinoma by Co-expression Network Analysis.Frontiers in physiology · 2018Article
Corrections and comments
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Authors and funding
10 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Although papillary renal cell carcinoma (PRCC) accounts for 10%-15% of renal cell carcinoma (RCC), no predictive molecular biomarker is currently applicable to guiding disease stage of PRCC patients. The mRNASeq data of PRCC and adjacent normal tissue in The Cancer Genome Atlas was analyzed to identify 1148 differentially expressed genes, on which weighted gene co-expression network analysis was performed. Then 11 co-expressed gene modules were identified. The highest association was found between blue module and pathological stage (r = 0.45) by Pearson's correlation analysis. Functional enrichment analysis revealed that biological processes of blue module focused on nuclear division, cell cycle phase, and spindle (all P < 1e-10). All 40 hub genes in blue module can distinguish localized (pathological stage I, II) from non-localized (pathological stage III, IV) PRCC (P < 0.01). A good molecular biomarker for pathological stage of RCC must be a prognostic gene in clinical practice. Survival analysis was performed to reversely validate if hub genes were associated with pathological stage. Survival analysis unveiled that all hub genes were associated with patient prognosis (P < 0.01).The validation cohort GSE2748 verified that 30 hub genes can differentiate localized from non-localized PRCC (P < 0.01), and 18 hub genes are prognosis-associated (P < 0.01).ROC curve indicated that the 17 hub genes exhibited excellent diagnostic efficiency for localized and non-localized PRCC (AUC > 0.7). These hub genes may serve as a biomarker and help to distinguish different pathological stages for PRCC patients.
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