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The purpose of this study is to comprehensively investigate the function and prognostic value of PPAR-targeted genes in BLCA.\nMETHODS: The RNA sequencing data and clinical information of BLCA patients were acquired from The Cancer Genome Atlas (TCGA). The differentially expressed PPAR-targeted genes were investigated. Cox analysis and least absolute shrinkage and selection operator (LASSO) analysis were performed for screening prognostic PPAR-targeted genes and constructing the prognostic PPAR signature and then validated by GSE13507 cohort and GSE32894 cohort. A nomogram was constructed to predict the outcomes of BLCA patients in combination with PPAR signature and clinical factors. Gene set enrichment analysis (GSEA) and immune cell infiltration were implemented to explore the molecular characteristics of the signature. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to predict the chemotherapy responses of the prognostic signature. The candidate small molecule drugs targeting PPAR-targeted genes were screened by the CMAP database.\nRESULTS: We constructed and validated the prognostic signature comprising of 4 PPAR-targeted genes (CPT1B, CALR, AHNAK, and FADS2), which was an independent prognostic biomarker in BLCA patients. A nomogram based on the signature and clinical factors was established in the TCGA set, and the calibration plots displayed the excellent predictive capacity. GSEA analysis indicated that PPAR signature was implicated in multiple oncogenic signaling pathways and correlated with tumor immune cell infiltration. Patients in the high-risk groups showed greater sensitivity to chemotherapy than those in the low-risk groups. Moreover, 11 candidate small molecule drugs were identified for the treatment of BLCA.\nCONCLUSION: We constructed and validated a novel PPAR signature, which showed the excellent performance in predicting prognosis and chemotherapy sensitivity of BLCA patients.","package_hash":"17828c25bd8086fb15f7b217ff998cd52c2ec8c8754fae77017f8443efc4e972","plan_hash":null,"plan_version":null,"first_receipt_at":"2026-11-04T07:03:23+00:00","decided_at":null,"days_open":5,"intake":{"method":"sci_import","source_name":"PPAR research","source_identifier":"pmid:35027921","source_url":null,"corpus_record_id":"pmid:35027921","recorded_by":"Journal Editor","ingested_at":"2026-11-04T07:03:23+00:00"},"lineage":{"relationship":"original","parent":null,"descendants":[]}},"source_text":{"held":false,"kind":"abstract","what_the_kind_means":"only the abstract was read","characters":null,"sha256":null,"intact":null,"note":"The hash is of the text as it arrived. 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The purpose of this study is to comprehensively investigate the function and prognostic value of PPAR-targeted genes in BLCA.\\nMETHODS: The RNA sequencing data and clinical information of BLCA patients were acquired from The Cancer Genome Atlas (TCGA). The differentially expressed PPAR-targeted genes were investigated. Cox analysis and least absolute shrinkage and selection operator (LASSO) analysis were performed for screening prognostic PPAR-targeted genes and constructing the prognostic PPAR signature and then validated by GSE13507 cohort and GSE32894 cohort. A nomogram was constructed to predict the outcomes of BLCA patients in combination with PPAR signature and clinical factors. Gene set enrichment analysis (GSEA) and immune cell infiltration were implemented to explore the molecular characteristics of the signature. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to predict the chemotherapy responses of the prognostic signature. 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METHODS: The RNA sequencing data and clinical information of BLCA patien\"\n   ],\n   \"order_basis\": \"paper_text_order:415\",\n   \"id\": \"assay:1\"\n  },\n  {\n   \"role\": \"analysis\",\n   \"definition_id\": \"survival_analysis\",\n   \"definition_version\": \"f2132e96ae6c7a4e\",\n   \"definition_digest\": null,\n   \"required_operations\": [\n    \"cox_ph\"\n   ],\n   \"support_state\": \"supported\",\n   \"source_hashes\": {\n    \"dsl_catalogue\": \"f2132e96ae6c7a4e\"\n   },\n   \"confidence\": 1.0,\n   \"evidence\": [\n    \"The differential expression analysis was conducted with the edgeR package in R software (version R 3.6.1).\"\n   ],\n   \"order_basis\": \"consumes_earlier_output\",\n   \"id\": \"assay:2\"\n  }\n ]\n}\n","document":{"sci_version":"1.2","schema":"https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json","id":"pmid:35027921","kind":"science-record","revision":5,"content_hash":"sha256:a63979991c40bb01ef19a7869b34502e4d8f9e3fed4e292fd11e80009e6e6c51","created_at":"2026-11-01T17:36:44Z","updated_at":"2026-11-01T22:48:14Z","generator":{"name":"corpus-assay-engine","run_id":"reading-sci-2026-11-01"},"paper":{"state":"complete","title":"Identification of a Novel PPAR Signature for Predicting Prognosis, Immune Microenvironment, and Chemotherapy Response in Bladder Cancer.","doi":"10.1155/2021/7056506","pmid":"35027921","authors":["Ke Zhu","Wen Deng","Hui Deng","Xiaoqiang Liu","Gongxian Wang","Bin Fu"],"journal":"PPAR research","year":2021,"abstract":"BACKGROUND: Mounting evidence has confirmed that peroxisome proliferator-activated receptors (PPARs) played a crucial role in the development and progression of bladder cancer (BLCA). The purpose of this study is to comprehensively investigate the function and prognostic value of PPAR-targeted genes in BLCA.\nMETHODS: The RNA sequencing data and clinical information of BLCA patients were acquired from The Cancer Genome Atlas (TCGA). The differentially expressed PPAR-targeted genes were investigated. Cox analysis and least absolute shrinkage and selection operator (LASSO) analysis were performed for screening prognostic PPAR-targeted genes and constructing the prognostic PPAR signature and then validated by GSE13507 cohort and GSE32894 cohort. A nomogram was constructed to predict the outcomes of BLCA patients in combination with PPAR signature and clinical factors. Gene set enrichment analysis (GSEA) and immune cell infiltration were implemented to explore the molecular characteristics of the signature. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to predict the chemotherapy responses of the prognostic signature. The candidate small molecule drugs targeting PPAR-targeted genes were screened by the CMAP database.\nRESULTS: We constructed and validated the prognostic signature comprising of 4 PPAR-targeted genes (CPT1B, CALR, AHNAK, and FADS2), which was an independent prognostic biomarker in BLCA patients. A nomogram based on the signature and clinical factors was established in the TCGA set, and the calibration plots displayed the excellent predictive capacity. GSEA analysis indicated that PPAR signature was implicated in multiple oncogenic signaling pathways and correlated with tumor immune cell infiltration. Patients in the high-risk groups showed greater sensitivity to chemotherapy than those in the low-risk groups. Moreover, 11 candidate small molecule drugs were identified for the treatment of BLCA.\nCONCLUSION: We constructed and validated a novel PPAR signature, which showed the excellent performance in predicting prognosis and chemotherapy sensitivity of BLCA patients.","claims":[{"id":"claim-method","statement":"The differential expression analysis was conducted with the edgeR package in R software (version R 3.6.1).","kind":"methodological","target":null,"evidence":[{"asset":"source:pmid:35027921","locator":"sections[4] \"2.2. Identification of Differentially Expressed PPAR Genes\" paragraph 2","quote":"The differential expression analysis was conducted with the edgeR package in R software (version R 3.6.1)."}],"state":"complete"},{"id":"claim-data-access","statement":"The RNA-sequencing data and clinical characteristic information of patients with BLCA were acquired from the TCGA database (https://gdc-portal.nci.nih.gov/). 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