<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Klotzer KA</submitter><funding>NIDDK NIH HHS</funding><funding>NIA NIH HHS</funding><funding>Deutsche Forschungsgemeinschaft (German Research Foundation)</funding><funding>Österreichische Agentur für Internationale Mobilität und Kooperation in Bildung, Wissenschaft und Forschung (Austrian Agency for International Cooperation in Education and Research)</funding><funding>U.S. Department of Health &amp; Human Services | NIH | National Institute of Diabetes and Digestive and Kidney Diseases (National Institute of Diabetes &amp; Digestive &amp; Kidney Diseases)</funding><funding>Marshallplan-Jubiläumsstiftung (Austrian Marshall Plan Foundation)</funding><pagination>1922-1934</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC12415535</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>57(8)</volume><pubmed_abstract>The use of single-cell RNA sequencing in clinical and translational research is limited by the challenge of identifying cell-type-specific, targetable molecular changes in individual patients and cross-species differences. Here we created an integrated single-cell kidney atlas including over 1 million cells from 140 samples, defining more than 70 conserved cell states in human and rodent models. We developed CellSpectra, a computational tool that quantifies changes in gene expression coordination across cellular functions, which we applied to kidney and lung cancer data. This tool powers our patient-level single-cell functional profiling report, which highlights cell-type-specific changes in the coordination of pathway gene expression in individuals. Our cross-species atlas facilitates the selection of a rodent model that closely reflects the cellular and pathway-level signatures observed in patient samples, advancing the application of single-cell methodologies in clinical precision medicine. Finally, using experimental models, we demonstrate how our informatics approach can be applied for the potential selection of suitable therapeutics.</pubmed_abstract><journal>Nature genetics</journal><pubmed_title>Analysis of individual patient pathway coordination in a cross-species single-cell kidney atlas.</pubmed_title><pmcid>PMC12415535</pmcid><funding_grant_id>5R01DK105821-08</funding_grant_id><funding_grant_id>R01 DK087635</funding_grant_id><funding_grant_id>2R01DK076077-15</funding_grant_id><funding_grant_id>5R01DK132630-02</funding_grant_id><funding_grant_id>Marietta-Blau Grant</funding_grant_id><funding_grant_id>BA 6205/2-1</funding_grant_id><funding_grant_id>5R01DK087635-15</funding_grant_id><funding_grant_id>R01 DK076077</funding_grant_id><funding_grant_id>P50 DK114786</funding_grant_id><funding_grant_id>Austrian Marshall Plan Foundation scholarship</funding_grant_id><funding_grant_id>R01 DK105821</funding_grant_id><funding_grant_id>5P50DK114786-07</funding_grant_id><funding_grant_id>R01 DK132630</funding_grant_id><funding_grant_id>R56 AG081351</funding_grant_id><pubmed_authors>Liang X</pubmed_authors><pubmed_authors>Susztak K</pubmed_authors><pubmed_authors>Balzer MS</pubmed_authors><pubmed_authors>Hogan JJ</pubmed_authors><pubmed_authors>Eller K</pubmed_authors><pubmed_authors>Bloom RD</pubmed_authors><pubmed_authors>Abedini A</pubmed_authors><pubmed_authors>Zhang NR</pubmed_authors><pubmed_authors>Halmos B</pubmed_authors><pubmed_authors>Schuller M</pubmed_authors><pubmed_authors>Levinsohn J</pubmed_authors><pubmed_authors>Li S</pubmed_authors><pubmed_authors>Dumoulin B</pubmed_authors><pubmed_authors>Quinn G</pubmed_authors><pubmed_authors>Ha E</pubmed_authors><pubmed_authors>Klotzer KA</pubmed_authors></additional><is_claimable>false</is_claimable><name>Analysis of individual patient pathway coordination in a cross-species single-cell kidney atlas.</name><description>The use of single-cell RNA sequencing in clinical and translational research is limited by the challenge of identifying cell-type-specific, targetable molecular changes in individual patients and cross-species differences. Here we created an integrated single-cell kidney atlas including over 1 million cells from 140 samples, defining more than 70 conserved cell states in human and rodent models. We developed CellSpectra, a computational tool that quantifies changes in gene expression coordination across cellular functions, which we applied to kidney and lung cancer data. This tool powers our patient-level single-cell functional profiling report, which highlights cell-type-specific changes in the coordination of pathway gene expression in individuals. Our cross-species atlas facilitates the selection of a rodent model that closely reflects the cellular and pathway-level signatures observed in patient samples, advancing the application of single-cell methodologies in clinical precision medicine. Finally, using experimental models, we demonstrate how our informatics approach can be applied for the potential selection of suitable therapeutics.</description><dates><release>2025-01-01T00:00:00Z</release><publication>2025 Aug</publication><modification>2026-06-04T16:14:24.832Z</modification><creation>2026-05-13T14:24:11.845Z</creation></dates><accession>S-EPMC12415535</accession><cross_references><pubmed>40775269</pubmed><doi>10.1038/s41588-025-02285-0</doi></cross_references></HashMap>