<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Smelik M</submitter><funding>Cancerfonden (Swedish Cancer Society)</funding><funding>Vetenskapsrådet (Swedish Research Council)</funding><pagination>234</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11570627</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>4(1)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>Cancer screening tests are considered pivotal for early diagnosis and survival. However, the efficacy of these tests for improving survival has recently been questioned. This study aims to test if cancer screening could be improved by biomarkers in peripheral blood based on multi-omics data.&lt;h4>Methods&lt;/h4>We utilize multi-omics data from 500,000 participants in the UK Biobank. Machine learning is applied to search for proteins, metabolites, genetic variants, or clinical variables to diagnose cancers collectively and individually.&lt;h4>Results&lt;/h4>Here we show that the overall performance of the potential blood biomarkers do not outperform clinical variables for collective diagnosis. However, we observe promising results for individual cancers in close proximity to periphe</pubmed_abstract><journal>Communications medicine</journal><pubmed_title>Multiomics biomarkers were not superior to clinical variables for pan-cancer screening.</pubmed_title><pmcid>PMC11570627</pmcid><funding_grant_id>2019-01165</funding_grant_id><funding_grant_id>CAN 2017/411</funding_grant_id><pubmed_authors>Li X</pubmed_authors><pubmed_authors>Mahmud AF</pubmed_authors><pubmed_authors>Benson M</pubmed_authors><pubmed_authors>Smelik M</pubmed_authors><pubmed_authors>Mansour Aly D</pubmed_authors><pubmed_authors>Zhao Y</pubmed_authors><pubmed_authors>Sysoev O</pubmed_authors></additional><is_claimable>false</is_claimable><name>Multiomics biomarkers were not superior to clinical variables for pan-cancer screening.</name><description>&lt;h4>Background&lt;/h4>Cancer screening tests are considered pivotal for early diagnosis and survival. However, the efficacy of these tests for improving survival has recently been questioned. This study aims to test if cancer screening could be improved by biomarkers in peripheral blood based on multi-omics data.&lt;h4>Methods&lt;/h4>We utilize multi-omics data from 500,000 participants in the UK Biobank. Machine learning is applied to search for proteins, metabolites, genetic variants, or clinical variables to diagnose cancers collectively and individually.&lt;h4>Results&lt;/h4>Here we show that the overall performance of the potential blood biomarkers do not outperform clinical variables for collective diagnosis. However, we observe promising results for individual cancers in close proximity to periphe</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Nov</publication><modification>2025-04-04T00:47:58.884Z</modification><creation>2025-04-04T00:47:58.884Z</creation></dates><accession>S-EPMC11570627</accession><cross_references><pubmed>39551871</pubmed><doi>10.1038/s43856-024-00671-z</doi></cross_references></HashMap>