Evan Rosenbaum, Fiona Ehrich, Mohammad Yosofvand, Martina Bradic, Jasme Lee, Mathew Adamow, Sujana Movva, Ciara M Kelly, Viswatej Avutu, Lauren B Banks, Jason E Chan, Ping Chi, Mark A Dickson, Mrinal M Gounder, Mary L Keohan, Robert G Maki, Damon R Reed, Paige Fuentes, Paige Collins, Rhoena Desir, Allison Reiner, Oleg Baranov, Konstantin Chernyshov, Nikita Kotlov, Ajay Subramanian, Everett J Moding, Li-Xuan Qin, Phillip Wong, William D Tap, Cristina R Antonescu, Katherine S Panageas, Ronglai Shen, Sandra P D'Angelo
{"title":"Association of Circulating T Cell and Tumor Microenvironment Profiles with Immune Checkpoint Blockade Outcomes in Sarcoma.","authors":"Evan Rosenbaum, Fiona Ehrich, Mohammad Yosofvand, Martina Bradic, Jasme Lee, Mathew Adamow, Sujana Movva, Ciara M Kelly, Viswatej Avutu, Lauren B Banks, Jason E Chan, Ping Chi, Mark A Dickson, Mrinal M Gounder, Mary L Keohan, Robert G Maki, Damon R Reed, Paige Fuentes, Paige Collins, Rhoena Desir, Allison Reiner, Oleg Baranov, Konstantin Chernyshov, Nikita Kotlov, Ajay Subramanian, Everett J Moding, Li-Xuan Qin, Phillip Wong, William D Tap, Cristina R Antonescu, Katherine S Panageas, Ronglai Shen, Sandra P D'Angelo","doi":"10.1158/1078-0432.CCR-25-3419","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>Immune checkpoint blockade (ICB) benefits only a subset of patients with sarcoma. Biomarkers of response and resistance are needed to help guide patient selection.</p><p><strong>Experimental design: </strong>We analyzed peripheral blood and tumor samples from patients with sarcoma treated in five ICB-based clinical trials. Baseline peripheral blood mononuclear cells (PBMC) underwent 11-color flow cytometry to define T-cell immunotypes. Baseline tumor tissue underwent RNA sequencing (RNA-seq) to classify tumors into four tumor microenvironment (TME) subtypes using consensus clustering of 29 functional gene expression signatures. Associations between immune features and clinical outcomes were assessed. A deep learning model was applied to baseline hematoxylin and eosin (H&E) slides to detect and quantify lymphoid aggregates in patients with available RNA-seq.</p><p><strong>Results: </strong>Among 178 patients with PBMC available for analysis, a proliferative (PRO) circulating T-cell immunotype was associated with poorer overall survival (OS) than lymphocyte-activation gene 3 (LAG)- or LAG+ immunotypes. RNA-seq from 67 tumors identified an immune-enriched/nonfibrotic TME subtype associated with a higher response rate, longer progression-free survival, and longer OS compared with immune-enriched/fibrotic, immune-depleted, and fibrotic subtypes. Automated analysis of 48 baseline H&E slides identified lymphoid aggregates in five tumors; four were classified as immune-enriched and two of these responded to ICB.</p><p><strong>Conclusions: </strong>Patients with sarcoma and a PRO circulating T-cell immunotype had inferior outcomes to ICB, whereas those with an immune-enriched/nonfibrotic TME had superior outcomes. Automated analysis of H&E slides showed promise in identifying patients with an immune-enriched TME. These findings support the use of a multimodal approach to identify predictors of response to immunotherapy in sarcoma.</p>","PeriodicalId":10279,"journal":{"name":"Clinical Cancer Research","volume":" ","pages":"1777-1789"},"PeriodicalIF":10.2000,"publicationDate":"2026-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13014529/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Cancer Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1158/1078-0432.CCR-25-3419","RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ONCOLOGY","Score":null,"Total":0}
引用次数: 0
Abstract
Purpose: Immune checkpoint blockade (ICB) benefits only a subset of patients with sarcoma. Biomarkers of response and resistance are needed to help guide patient selection.
Experimental design: We analyzed peripheral blood and tumor samples from patients with sarcoma treated in five ICB-based clinical trials. Baseline peripheral blood mononuclear cells (PBMC) underwent 11-color flow cytometry to define T-cell immunotypes. Baseline tumor tissue underwent RNA sequencing (RNA-seq) to classify tumors into four tumor microenvironment (TME) subtypes using consensus clustering of 29 functional gene expression signatures. Associations between immune features and clinical outcomes were assessed. A deep learning model was applied to baseline hematoxylin and eosin (H&E) slides to detect and quantify lymphoid aggregates in patients with available RNA-seq.
Results: Among 178 patients with PBMC available for analysis, a proliferative (PRO) circulating T-cell immunotype was associated with poorer overall survival (OS) than lymphocyte-activation gene 3 (LAG)- or LAG+ immunotypes. RNA-seq from 67 tumors identified an immune-enriched/nonfibrotic TME subtype associated with a higher response rate, longer progression-free survival, and longer OS compared with immune-enriched/fibrotic, immune-depleted, and fibrotic subtypes. Automated analysis of 48 baseline H&E slides identified lymphoid aggregates in five tumors; four were classified as immune-enriched and two of these responded to ICB.
Conclusions: Patients with sarcoma and a PRO circulating T-cell immunotype had inferior outcomes to ICB, whereas those with an immune-enriched/nonfibrotic TME had superior outcomes. Automated analysis of H&E slides showed promise in identifying patients with an immune-enriched TME. These findings support the use of a multimodal approach to identify predictors of response to immunotherapy in sarcoma.
期刊介绍:
Clinical Cancer Research is a journal focusing on groundbreaking research in cancer, specifically in the areas where the laboratory and the clinic intersect. Our primary interest lies in clinical trials that investigate novel treatments, accompanied by research on pharmacology, molecular alterations, and biomarkers that can predict response or resistance to these treatments. Furthermore, we prioritize laboratory and animal studies that explore new drugs and targeted agents with the potential to advance to clinical trials. We also encourage research on targetable mechanisms of cancer development, progression, and metastasis.