Evidence map›Paper›PMID 41408017›Full record

ArticleClinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico2026

Bayesian selection of lipidome dynamics features for a K-nearest neighbors (KNN) classifier model of tumor response in patients with advanced gastrointestinal adenocarcinoma undergoing systemic treatment.

Vicente Valentí, Javier Ramos, Laura Fernández-Sénder, Óscar Villuendas, Begoña Rodríguez, Eugenia Sopena, Marta Peña, Carlos Alonso-Villaverde

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Article in Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Vicente Valentí *Medical Oncology Department, Hospital Sant Pau i Santa Tecla, Rambla Vella 14, 43003, Tarragona, Spain. vvalenti@xarxatecla.cat.ORCID http://orcid.org/0000-0002-2963-7713
Javier RamosMedical Oncology Department, Hospital Comarcal Baix Penedès, El Vendrell, Spain.ORCID http://orcid.org/0000-0002-0918-5895
Laura Fernández-SénderInternal Medicine Department, Hospital Sant Pau i Santa Tecla, Tarragona, Spain.ORCID http://orcid.org/0000-0002-3796-3017
Óscar VilluendasClinical Laboratory, Hospital Sant Pau i Santa Tecla, Tarragona, Spain.ORCID http://orcid.org/0000-0002-8788-4624
Begoña RodríguezPharmacy Department, Hospital Sant Pau i Santa Tecla, Tarragona, Spain.
Eugenia SopenaInternal Medicine Department, Hospital Sant Pau i Santa Tecla, Tarragona, Spain.ORCID http://orcid.org/0009-0003-2100-6209
Marta PeñaQuality Direction, Hospital Sant Pau i Santa Tecla, Tarragona, Spain.
Carlos Alonso-Villaverde *Internal Medicine Department, Hospital Sant Pau i Santa Tecla, Tarragona, Spain.ORCID http://orcid.org/0000-0001-8278-8388

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDysregulated lipid metabolism is common in patients with gastrointestinal (GI) cancer. This study investigated the ability of plasma lipidome variation during systemic treatment to classify GI cancer patients according to tumor response.

methodsNon-targeted plasma lipidomics with LC-qTOF mass spectrometry was conducted in patients with advanced GI adenocarcinomas before and after three months of systemic standard-of-care antitumor treatment. Bayesian ANOVA with repeated measures and an uninformative prior was used to screen for analytes whose before-and-after variation could be associated with tumor response. Suitable candidates with a Bayes Factor (BF) > 7 for the interaction were used to train a KNN model to classify patients as responders (PR + CR) vs. non-responders (PD + SD) according to RECIST 1.1 criteria.

resultsThirty patients were included (18 colorectal, 6 gastric, 6 biliopancreatic). The cohort included 10 responders (all partial responses, 33%) and 20 non-responders (14 stable disease, 6 progressive disease). Plasma lipidomics identified 262 analytes on 10 lipid species: phosphatidylcholines (PCs), non-polar and polar lyso-PCs, sphingomyelins, lysophosphatidylethanolamines, cholesterol esters, acylglycerides, fatty acids, hormones, and bile acids. An increase in abundance after treatment of five PCs (PC32:2, PC33:2, PC36:2, PC36:5, PC38:5) was associated with tumor response (BF > 7 for interaction). After excluding collinear PCs (retaining PC32:2, PC33:2, PC36:2), a KNN model (optimized: k = 7, Manhattan distance, inverse weighting, LOOCV) achieved consistent performance over 20 runs (mean ± SD): AUC 0.86 ± 0.23; Precision 0.76 ± 0.17; Recall 0.81 ± 0.15; F1 score 0.80 ± 0.13; MCC 0.66 ± 0.23. None of the other nine lipid classes contributed more than one analyte with a BF > 7 for the interaction with tumor response.

conclusionsTumor response is associated with variations in plasma lipidome in patients with advanced GI cancer. The plasma abundance of PCs increased after treatment in responder patients, suggesting that further investigation may be warranted on PCs as a potential biomarker.

Indexed as

AdenocarcinomaGastrointestinal NeoplasmsLipidomicsLipidsAdultAgedBayes TheoremFemaleHumansLipid MetabolismMaleMiddle AgedLipidsBayesian statisticsGastrointestinal cancerKNNLipidomicsMachine learning

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.