<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Roller A</submitter><funding>F. Hoffmann-La Roche Ltd</funding><pagination>e008185</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11043740</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>12(4)</volume><pubmed_abstract>&lt;h4>Background&lt;/h4>The immune status of a patient's tumor microenvironment (TME) may guide therapeutic interventions with cancer immunotherapy and help identify potential resistance mechanisms. Currently, patients' immune status is mostly classified based on CD8+tumor-infiltrating lymphocytes. An unmet need exists for comparable and reliable precision immunophenotyping tools that would facilitate clinical treatment-relevant decision-making and the understanding of how to overcome resistance mechanisms.&lt;h4>Methods&lt;/h4>We systematically analyzed the CD8 immunophenotype of 2023 patients from 14 phase I-III clinical trials using immunohistochemistry (IHC) and additionally profiled gene expression by RNA-sequencing (RNA-seq). CD8 immunophenotypes were classified by pathologists into CD8-desert,</pubmed_abstract><journal>Journal for immunotherapy of cancer</journal><pubmed_title>Tumor-agnostic transcriptome-based classifier identifies spatial infiltration patterns of CD8+T cells in the tumor microenvironment and predicts clinical outcome in early-phase and late-phase clinical trials.</pubmed_title><pmcid>PMC11043740</pmcid><funding_grant_id>N/A</funding_grant_id><pubmed_authors>Cannarile MA</pubmed_authors><pubmed_authors>Serrano-Serrano ML</pubmed_authors><pubmed_authors>Valdeolivas A</pubmed_authors><pubmed_authors>Korski K</pubmed_authors><pubmed_authors>Davydov II</pubmed_authors><pubmed_authors>Staedler N</pubmed_authors><pubmed_authors>Dietmann G</pubmed_authors><pubmed_authors>Ferreira CS</pubmed_authors><pubmed_authors>Roller A</pubmed_authors><pubmed_authors>Heller A</pubmed_authors><pubmed_authors>Schwalie PC</pubmed_authors><pubmed_authors>Klaman I</pubmed_authors></additional><is_claimable>false</is_claimable><name>Tumor-agnostic transcriptome-based classifier identifies spatial infiltration patterns of CD8+T cells in the tumor microenvironment and predicts clinical outcome in early-phase and late-phase clinical trials.</name><description>&lt;h4>Background&lt;/h4>The immune status of a patient's tumor microenvironment (TME) may guide therapeutic interventions with cancer immunotherapy and help identify potential resistance mechanisms. Currently, patients' immune status is mostly classified based on CD8+tumor-infiltrating lymphocytes. An unmet need exists for comparable and reliable precision immunophenotyping tools that would facilitate clinical treatment-relevant decision-making and the understanding of how to overcome resistance mechanisms.&lt;h4>Methods&lt;/h4>We systematically analyzed the CD8 immunophenotype of 2023 patients from 14 phase I-III clinical trials using immunohistochemistry (IHC) and additionally profiled gene expression by RNA-sequencing (RNA-seq). CD8 immunophenotypes were classified by pathologists into CD8-desert,</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 Apr</publication><modification>2026-07-15T14:12:10.787Z</modification><creation>2026-07-06T03:08:42.188Z</creation></dates><accession>S-EPMC11043740</accession><cross_references><pubmed>38649280</pubmed><doi>10.1136/jitc-2023-008185</doi></cross_references></HashMap>