000169200 001__ 169200
000169200 005__ 20260223164759.0
000169200 0247_ $$2doi$$a10.1016/j.isci.2026.114751
000169200 0248_ $$2sideral$$a148289
000169200 037__ $$aART-2026-148289
000169200 041__ $$aeng
000169200 100__ $$aHermoso-Durán, Sonia
000169200 245__ $$aIntegrating thermal liquid biopsy, clinical data, and mass spectrometry for early diagnosis and biomarker discovery in colorectal cancer
000169200 260__ $$c2026
000169200 5060_ $$aAccess copy available to the general public$$fUnrestricted
000169200 5203_ $$aEarly detection of colorectal cancer is essential to improving survival, where yet current diagnostic tools show limited performance. This study aimed to enhance diagnostic accuracy by integrating clinical variables with thermogram profiles obtained through serum-based thermal liquid biopsy and analyzed using machine learning models. We evaluated 328 patients with colorectal cancer and 355 symptomatic individuals with non-organ-specific cancer signs but negative diagnostic evaluations, to reproduce clinically relevant decision settings. The combined model showed improved classification performance compared with the use of clinical variables alone, particularly in patients with early-stage disease. In addition, proteomic analysis of samples stratified by thermogram patterns identified proteins associated with survival, including fibrinogen-like protein 1, supporting the biological relevance of these thermodynamic profiles. Together, these findings indicate that integrating serum thermogram information with routine clinical data can modestly strengthen diagnostic assessment and help identify biologically meaningful patient subgroups, offering a promising non-invasive colorectal
000169200 536__ $$9info:eu-repo/grantAgreement/ES/DGA/B08-24R$$9info:eu-repo/grantAgreement/ES/DGA/B25-23R$$9info:eu-repo/grantAgreement/ES/ISCIII-FIS/FI19-00146$$9info:eu-repo/grantAgreement/ES/ISCIII/PI20-00661$$9info:eu-repo/grantAgreement/ES/ISCIII/PI21-00394$$9info:eu-repo/grantAgreement/ES/MICINN/AEI/PID2021-127296OB-I00$$9info:eu-repo/grantAgreement/ES/MICIU/JDC2023-052992-I
000169200 540__ $$9info:eu-repo/semantics/openAccess$$aby-nc$$uhttps://creativecommons.org/licenses/by-nc/4.0/deed.es
000169200 655_4 $$ainfo:eu-repo/semantics/article$$vinfo:eu-repo/semantics/publishedVersion
000169200 700__ $$0(orcid)0000-0003-1885-4365$$aOrtega-Alarcón, David
000169200 700__ $$aJohansen, Astrid Z.
000169200 700__ $$aMcKay, Mattew J.
000169200 700__ $$aJohansen, Julia S.
000169200 700__ $$0(orcid)0000-0002-1232-6310$$aVega, Sonia
000169200 700__ $$aFeltoft, Claus L.
000169200 700__ $$aDolin, Troels Gammeltoft
000169200 700__ $$aLykke, Jakob
000169200 700__ $$aFraunhoffer, Nicolas
000169200 700__ $$aSánchez-Gracia, Oscar
000169200 700__ $$aGarrido, Pablo F.
000169200 700__ $$0(orcid)0000-0001-5932-2889$$aLanas, Ángel$$uUniversidad de Zaragoza
000169200 700__ $$aMolloy, Mark P.
000169200 700__ $$0(orcid)0000-0001-5702-4538$$aVelázquez-Campoy, Adrian$$uUniversidad de Zaragoza
000169200 700__ $$0(orcid)0000-0001-5664-1729$$aAbian, Olga$$uUniversidad de Zaragoza
000169200 7102_ $$11007$$2610$$aUniversidad de Zaragoza$$bDpto. Medicina, Psiqu. y Derm.$$cArea Medicina
000169200 7102_ $$11002$$2060$$aUniversidad de Zaragoza$$bDpto. Bioq.Biolog.Mol. Celular$$cÁrea Bioquímica y Biolog.Mole.
000169200 773__ $$g29, 2 (2026), 114751 [17 pp.]$$piScience$$tISCIENCE$$x2589-0042
000169200 8564_ $$s4229999$$uhttps://zaguan.unizar.es/record/169200/files/texto_completo.pdf$$yVersión publicada
000169200 8564_ $$s1205049$$uhttps://zaguan.unizar.es/record/169200/files/texto_completo.jpg?subformat=icon$$xicon$$yVersión publicada
000169200 909CO $$ooai:zaguan.unizar.es:169200$$particulos$$pdriver
000169200 951__ $$a2026-02-23-14:54:23
000169200 980__ $$aARTICLE