Development and validation of the Immune Profile Score (IPS), a novel multiomic algorithmic assay for stratifying outcomes in a real-world cohort of patients with advanced solid cancer treated with immune checkpoint inhibitors
Background Immune checkpoint inhibitors (ICIs) have transformed the oncology treatment landscape. Despite substantial improvements for some patients, the majority do not benefit from ICIs, indicating a need for predictive biomarkers to better inform treatment decisions.Methods A de-identified pan-ca...
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BMJ Publishing Group
2025-05-01
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| Series: | Journal for ImmunoTherapy of Cancer |
| Online Access: | https://jitc.bmj.com/content/13/5/e011363.full |
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| author | Yan Liu Matthew Zibelman Timothy Chan Justin Guinney Douglas Adkins Ezra E W Cohen Michelle M Stein Halla Nimeiri Sandip P Patel Alia D Zander Rossin Erbe Ailin Jin Sayantoni Mukhopadhyay Ben Terdich Mario G Rosasco Nirali Patel Chithra Sangli Timothy Taxter Seung Won Hyun Brett M Mahon A Kate Sasser Michelle A Ting-Lin Kyle A Beauchamp |
| author_facet | Yan Liu Matthew Zibelman Timothy Chan Justin Guinney Douglas Adkins Ezra E W Cohen Michelle M Stein Halla Nimeiri Sandip P Patel Alia D Zander Rossin Erbe Ailin Jin Sayantoni Mukhopadhyay Ben Terdich Mario G Rosasco Nirali Patel Chithra Sangli Timothy Taxter Seung Won Hyun Brett M Mahon A Kate Sasser Michelle A Ting-Lin Kyle A Beauchamp |
| author_sort | Yan Liu |
| collection | DOAJ |
| description | Background Immune checkpoint inhibitors (ICIs) have transformed the oncology treatment landscape. Despite substantial improvements for some patients, the majority do not benefit from ICIs, indicating a need for predictive biomarkers to better inform treatment decisions.Methods A de-identified pan-cancer cohort from the Tempus multimodal real-world database was used for the development and validation of the Immune Profile Score (IPS) algorithm leveraging Tempus xT (648 gene DNA panel) and xR (RNA sequencing) (N=1,707 development cohort; N=1,600 validation cohort). The cohort consisted of patients with advanced stage cancer with solid tumor carcinomas across 16 cancer types treated with any ICI-containing regimen as the first or second line of therapy. The IPS model was developed using a machine learning framework that includes tumor mutational burden (TMB) and 11 RNA-based biomarkers as features.Results IPS-High patients demonstrated significantly longer overall survival (OS) compared with IPS-Low patients (HR=0.45, 90% CI (0.40 to 0.52)). IPS was consistently prognostic in programmed death-ligand 1 (PD-L1) (positive/negative), TMB (High/Low), microsatellite status (microsatellite instability (MSI)-High), and regimen (ICI only/ICI+other) subgroups. Additionally, IPS remained significant in multivariable models controlling for TMB, MSI, and PD-L1, with IPS HRs of 0.49 (90% CI 0.42 to 0.56), 0.47 (90% CI 0.41 to 0.53), and 0.45 (90% CI 0.38 to 0.53), respectively. In an exploratory predictive utility analysis of the subset of patients (n=345) receiving first-line chemotherapy (CT) and second-line ICI, there was no significant effect of IPS for time to next treatment on CT in L1 (HR=1.06 (90% CI 0.88 to 1.29)). However, there was a significant effect of IPS for OS on ICI in L2 (HR=0.63 (90% CI 0.49 to 0.82)). A test of interaction was statistically significant (p<0.01).Conclusions Our results demonstrate that IPS is a generalizable multiomic biomarker that can be widely used clinically as a prognosticator of ICI-based regimens. |
| format | Article |
| id | doaj-art-dc3827e5d9c94348bab3f0e2c41c774c |
| institution | OA Journals |
| issn | 2051-1426 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | BMJ Publishing Group |
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| series | Journal for ImmunoTherapy of Cancer |
| spelling | doaj-art-dc3827e5d9c94348bab3f0e2c41c774c2025-08-20T02:07:23ZengBMJ Publishing GroupJournal for ImmunoTherapy of Cancer2051-14262025-05-0113510.1136/jitc-2024-011363Development and validation of the Immune Profile Score (IPS), a novel multiomic algorithmic assay for stratifying outcomes in a real-world cohort of patients with advanced solid cancer treated with immune checkpoint inhibitorsYan Liu0Matthew Zibelman1Timothy Chan2Justin Guinney3Douglas Adkins4Ezra E W Cohen5Michelle M Stein6Halla Nimeiri7Sandip P Patel8Alia D Zander9Rossin Erbe10Ailin Jin11Sayantoni Mukhopadhyay12Ben Terdich13Mario G Rosasco14Nirali Patel15Chithra Sangli16Timothy Taxter17Seung Won Hyun18Brett M Mahon19A Kate Sasser20Michelle A Ting-Lin21Kyle A Beauchamp22Tempus AI Inc, Chicago, Illinois, USAFox Chase Cancer Center, Philadelphia, Pennsylvania, USACenter for Immunotherapy and Precision Immuno-oncology, Cleveland Clinic, Cleveland, Ohio, USATempus AI Inc, Chicago, Illinois, USAWashington Univ, St. Louis, Missouri, USATempus AI Inc, Chicago, Illinois, USATempus AI Inc, Chicago, Illinois, USATempus AI Inc, Chicago, Illinois, USAUCSD Moores Cancer Center, La Jolla, California, USATempus AI Inc, Chicago, Illinois, USATempus AI Inc, Chicago, Illinois, USATempus AI Inc, Chicago, Illinois, USATempus AI Inc, Chicago, Illinois, USATempus AI Inc, Chicago, Illinois, USATempus AI Inc, Chicago, Illinois, USATempus AI Inc, Chicago, Illinois, USATempus AI Inc, Chicago, Illinois, USATempus AI Inc, Chicago, Illinois, USATempus AI Inc, Chicago, Illinois, USATempus AI Inc, Chicago, Illinois, USATempus AI Inc, Chicago, Illinois, USATempus AI Inc, Chicago, Illinois, USATempus AI Inc, Chicago, Illinois, USABackground Immune checkpoint inhibitors (ICIs) have transformed the oncology treatment landscape. Despite substantial improvements for some patients, the majority do not benefit from ICIs, indicating a need for predictive biomarkers to better inform treatment decisions.Methods A de-identified pan-cancer cohort from the Tempus multimodal real-world database was used for the development and validation of the Immune Profile Score (IPS) algorithm leveraging Tempus xT (648 gene DNA panel) and xR (RNA sequencing) (N=1,707 development cohort; N=1,600 validation cohort). The cohort consisted of patients with advanced stage cancer with solid tumor carcinomas across 16 cancer types treated with any ICI-containing regimen as the first or second line of therapy. The IPS model was developed using a machine learning framework that includes tumor mutational burden (TMB) and 11 RNA-based biomarkers as features.Results IPS-High patients demonstrated significantly longer overall survival (OS) compared with IPS-Low patients (HR=0.45, 90% CI (0.40 to 0.52)). IPS was consistently prognostic in programmed death-ligand 1 (PD-L1) (positive/negative), TMB (High/Low), microsatellite status (microsatellite instability (MSI)-High), and regimen (ICI only/ICI+other) subgroups. Additionally, IPS remained significant in multivariable models controlling for TMB, MSI, and PD-L1, with IPS HRs of 0.49 (90% CI 0.42 to 0.56), 0.47 (90% CI 0.41 to 0.53), and 0.45 (90% CI 0.38 to 0.53), respectively. In an exploratory predictive utility analysis of the subset of patients (n=345) receiving first-line chemotherapy (CT) and second-line ICI, there was no significant effect of IPS for time to next treatment on CT in L1 (HR=1.06 (90% CI 0.88 to 1.29)). However, there was a significant effect of IPS for OS on ICI in L2 (HR=0.63 (90% CI 0.49 to 0.82)). A test of interaction was statistically significant (p<0.01).Conclusions Our results demonstrate that IPS is a generalizable multiomic biomarker that can be widely used clinically as a prognosticator of ICI-based regimens.https://jitc.bmj.com/content/13/5/e011363.full |
| spellingShingle | Yan Liu Matthew Zibelman Timothy Chan Justin Guinney Douglas Adkins Ezra E W Cohen Michelle M Stein Halla Nimeiri Sandip P Patel Alia D Zander Rossin Erbe Ailin Jin Sayantoni Mukhopadhyay Ben Terdich Mario G Rosasco Nirali Patel Chithra Sangli Timothy Taxter Seung Won Hyun Brett M Mahon A Kate Sasser Michelle A Ting-Lin Kyle A Beauchamp Development and validation of the Immune Profile Score (IPS), a novel multiomic algorithmic assay for stratifying outcomes in a real-world cohort of patients with advanced solid cancer treated with immune checkpoint inhibitors Journal for ImmunoTherapy of Cancer |
| title | Development and validation of the Immune Profile Score (IPS), a novel multiomic algorithmic assay for stratifying outcomes in a real-world cohort of patients with advanced solid cancer treated with immune checkpoint inhibitors |
| title_full | Development and validation of the Immune Profile Score (IPS), a novel multiomic algorithmic assay for stratifying outcomes in a real-world cohort of patients with advanced solid cancer treated with immune checkpoint inhibitors |
| title_fullStr | Development and validation of the Immune Profile Score (IPS), a novel multiomic algorithmic assay for stratifying outcomes in a real-world cohort of patients with advanced solid cancer treated with immune checkpoint inhibitors |
| title_full_unstemmed | Development and validation of the Immune Profile Score (IPS), a novel multiomic algorithmic assay for stratifying outcomes in a real-world cohort of patients with advanced solid cancer treated with immune checkpoint inhibitors |
| title_short | Development and validation of the Immune Profile Score (IPS), a novel multiomic algorithmic assay for stratifying outcomes in a real-world cohort of patients with advanced solid cancer treated with immune checkpoint inhibitors |
| title_sort | development and validation of the immune profile score ips a novel multiomic algorithmic assay for stratifying outcomes in a real world cohort of patients with advanced solid cancer treated with immune checkpoint inhibitors |
| url | https://jitc.bmj.com/content/13/5/e011363.full |
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