ArticleOncology reports2019
The underlying molecular mechanism and potential drugs for treatment in papillary renal cell carcinoma: A study based on TCGA and Cmap datasets.
Article in Oncology reports, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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Who cites it
16 citing papers in PubMed, 26 citations in OpenAlex.
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- GARD: Genomic Data based Drug Repurposing in Head and Neck Cancer with Large Language Model Validation.bioRxiv : the preprint server for biology · 2026Article
- Construction of anti-tumor immune gene signature for HNSCC and identification of 4'-Hydroxywogonin as a potential immunotherapy combination drug.Cancer cell international · 2025Article
- Spatial single-cell maps reveal ST6GAL1 promoting ovarian cancer metastasis.Glycoconjugate journal · 2025Article
- Single-cell and genetic multi-omics analysis combined with experiments confirmed the signature and potential targets of cuproptosis in hepatocellular carcinoma.Frontiers in cell and developmental biology · 2023Article
- Panels of mRNAs and miRNAs for decoding molecular mechanisms of Renal Cell Carcinoma (RCC) subtypes utilizing Artificial Intelligence approaches.Scientific reports · 2022Article
- Identification of anthelmintic parbendazole as a therapeutic molecule for HNSCC through connectivity map-based drug repositioning.Acta pharmaceutica Sinica. B · 2022Article
- Identification of the Ferroptosis-Related Long Non-Coding RNAs Signature to Improve the Prognosis Prediction in Papillary Renal Cell Carcinoma.Frontiers in surgery · 2022Article
- Construction of an Immune-Autophagy Prognostic Model Based on ssGSEA Immune Scoring Algorithm Analysis and Prognostic Value Exploration of the Immune-Autophagy Gene in Endometrial Carcinoma (EC) Based on Bioinformatics.Journal of healthcare engineering · 2022Article
- Identification of immunization-related new prognostic biomarkers for papillary renal cell carcinoma by integrated bioinformatics analysis.BMC medical genomics · 2021Article
- Identification and validation of a prognostic signature and combination drug therapy for immunotherapy of head and neck squamous cell carcinoma.Computational and structural biotechnology journal · 2021Article
- RNA-Sequencing, Connectivity Mapping, and Molecular Docking to Investigate Ligand-Protein Binding for Potential Drug Candidates for the Treatment of Wilms Tumor.Medical science monitor : international medical journal of experimental and clinical research · 2020Article
- Development and Validation of Nine-RNA Binding Protein Signature Predicting Overall Survival for Kidney Renal Clear Cell Carcinoma.Frontiers in genetics · 2020Article
- Identification of a three-miRNA signature as a novel prognostic model for papillary renal cell carcinoma.Cancer cell international · 2020Article
- Underlying Mechanisms and Candidate Drugs for COVID-19 Based on the Connectivity Map Database.Frontiers in genetics · 2020Article
- The potential drug for treatment in pancreatic adenocarcinoma: a bioinformatical study based on distinct drug databases.Chinese medicine · 2020Article
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Authors and funding
7 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Papillary renal cell carcinoma (PRCC) accounts for 15‑20% of all kidney neoplasms and continually attracts attention due to the increase in the incidents in which it occurs. The molecular mechanism of PRCC remains unclear and the efficacy of drugs that treat PRCC lacks sufficient evidence in clinical trials. Therefore, it is necessary to investigate the underlying mechanism in the development of PRCC and identify additional potential anti‑PRCC drugs for its treatment. The differently expressed genes (DEGs) of PRCC were identified, followed by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses for functional annotation. Then, potential drugs for PRCC treatment were predicted by Connectivity Map (Cmap) based on DEGs. Furthermore, the latent function of query drugs in PRCC was explored by integrating drug‑target, drug‑pathway and drug‑protein interactions. In total, 627 genes were screened as DEGs, and these DEGs were annotated using KEGG pathway analyses and were clearly associated with the complement and coagulation cascades, amongst others. Then, 60 candidate drugs, as predicted based on DEGs, were obtained from the Cmap database. Vorinostat was considered as the most promising drug for detailed discussion. Following protein‑protein interaction (PPI) analysis and molecular docking, vorinostat was observed to interact with C3 and ANXN1 proteins, which are the upregulated hub genes and may serve as oncologic therapeutic targets in PRCC. Among the top 20 metabolic pathways, several significant pathways, such as complement and coagulation cascades and cell adhesion molecules, may greatly contribute to the development and progression of PRCC. Following the performance of the PPI network and molecular docking tests, vorinostat exhibited a considerable and promising application in PRCC treatment by targeting C3 and ANXN1.
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