{"doi":"10.1007/s11306-021-01779-2","title":"Metabolomic and elemental profiling of human tissue in kidney cancer","abstract":"INTRODUCTION: Kidney cancer is one of the most frequently diagnosed and the most lethal urinary cancer. Despite advances in treatment, no specific biomarker is currently in use to guide therapeutic interventions. OBJECTIVES: Major aim of this work was to perform metabolomic and elemental profiling of human kidney cancer and normal tissue and to evaluate cancer biomarkers. METHODS: Metabolic and elemental profiling of tumor and adjacent normal human kidney tissue from 50 patients with kidney cancer was undertaken using three different analytical methods. RESULTS: Five potential tissue biomarkers of kidney cancer were identified and quantified using with high-resolution nuclear magnetic resonance spectroscopy. The contents of selected chemical elements in tissues was analyzed using inductively coupled plasma optical emission spectrometry. Eleven mass spectral features differentiating between kidney cancer and normal tissues were detected using silver-109 nanoparticle enhanced steel target laser desorption/ionization mass spectrometry. CONCLUSIONS: Our results, derived from the combination of ICP-OES, LDI MS and 1H NMR methods, suggest that tissue biomarkers identified herein appeared to have great potential for use in clinical prognosis and/or diagnosis of kidney cancer.","journal":"Metabolomics","year":2021,"id":165248,"datarank":0.8942013499747499,"base_score":3.6109179126442243,"endowment":3.6109179126442243,"self_citation_contribution":0.5416376868966337,"citation_network_contribution":0.3525636630781162,"self_endowment_contribution":0.5416376868966337,"citer_contribution":0.3525636630781162,"corpus_percentile":77.4348263324824,"corpus_rank":2918,"citation_count":36,"citer_count":20,"citers_with_citation_signal":17,"citers_with_endowment":17,"datacite_reuse_total":0,"is_dataset":true,"is_dataset_confidence":0.7636,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2021-01-01","fair_score":4.1667,"fair_percentile":4.891470498318557,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":226468,"name":"Valérie Copié","orcid":"0000-0002-2778-1463","position":1,"is_corresponding":false},{"id":344455,"name":"Brian Tripet","orcid":"0000-0002-8966-8714","position":2,"is_corresponding":false},{"id":688228,"name":"Leonardo Brandão Nogueira","orcid":"0000-0001-5108-2315","position":3,"is_corresponding":false},{"id":688229,"name":"Katiane de Oliveira Pinto Coelho Nogueira","orcid":"0000-0001-5495-2558","position":4,"is_corresponding":false},{"id":688230,"name":"Krzysztof Ossoliński","orcid":"0000-0002-2650-8326","position":5,"is_corresponding":false},{"id":688231,"name":"Adrian Arendowski","orcid":"0000-0002-8496-6800","position":6,"is_corresponding":false},{"id":688232,"name":"Tomasz Ruman","orcid":"0000-0002-9899-8627","position":7,"is_corresponding":false},{"id":688227,"name":"Joanna Nizioł","orcid":"0000-0002-4783-8615","position":0,"is_corresponding":true}],"reference_count":48,"raw_metadata":null,"created_at":"2026-07-18T23:45:36.425208Z","pmid":"33661419","pmcid":"PMC7932981","fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":11.1111,"fair_a":18.75,"fair_i":0.0,"fair_r":33.3333,"fair_zscore":-1.1986,"fair_rationale":{"fair_score":4.17,"has_llm":true,"taxonomy_version":"fair_taxonomy_v5","dimensions":{"F":{"name":"Findable","score":11.11,"criteria":[{"key":"f_dataset_pid","label":"Persistent identifier for the data","kind":"llm","weight":2.0,"fraction":0.0,"verdict":"no","evidence":"Data availability The data that support the findings of this study is available from the corresponding author upon reasonable request.","grounded":true,"rationale":"No persistent-identifier string or data URL occurs in the text; 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