The T Cell Immunoscore as a Reference for Biomarker Development Utilizing Real-World Data from Patients with Advanced Malignancies Treated with Immune Checkpoint Inhibitors

Islam Eljilany; Payman Ghasemi Saghand; James Chen; Aakrosh Ratan; Martin McCarter; John Carpten; Howard Colman; Alexandra P. Ikeguchi; Igor Puzanov; Susanne Arnold; Michelle Churchman; Patrick Hwu; Jose Conejo-Garcia; William S. Dalton; George J. Weiner; Issam M. El Naqa; Ahmad A. Tarhini

doi:10.3390/cancers15204913

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The T Cell Immunoscore as a Reference for Biomarker Development Utilizing Real-World Data from Patients with Advanced Malignancies Treated with Immune Checkpoint Inhibitors

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The T Cell Immunoscore as a Reference for Biomarker Development Utilizing Real-World Data from Patients with Advanced Malignancies Treated with Immune Checkpoint Inhibitors

Islam Eljilany, Payman Ghasemi Saghand, James Chen, Aakrosh Ratan, Martin McCarter, John Carpten, Howard Colman, Alexandra P. Ikeguchi, Igor Puzanov, Susanne Arnold, …

Cancers, Vol.15(20), 4913

10/10/2023

DOI: 10.3390/cancers15204913

PMCID: PMC10605389

PMID: 37894280

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Abstract

Background: We aimed to determine the prognostic value of an immunoscore reflecting CD3+ and CD8+ T cell density estimated from real-world transcriptomic data of a patient cohort with advanced malignancies treated with immune checkpoint inhibitors (ICIs) in an effort to validate a reference for future machine learning-based biomarker development. Methods: Transcriptomic data was collected under the Total Cancer Care Protocol (NCT03977402) Avatar® project. The real-world immunoscore for each patient was calculated based on the estimated densities of tumor CD3+ and CD8+ T cells utilizing CIBERSORTx and the LM22 gene signature matrix. Then, the immunoscore association with overall survival (OS) was estimated using Cox regression and analyzed using Kaplan–Meier curves. The OS predictions were assessed using Harrell’s concordance index (C-index). The Youden index was used to identify the optimal cut-off point. Statistical significance was assessed using the log-rank test. Results: Our study encompassed 522 patients with four cancer types. The median duration to death was 10.5 months for the 275 participants who encountered an event. For the entire cohort, the results demonstrated that transcriptomics-based immunoscore could significantly predict patients at risk of death (p-value < 0.001). Notably, patients with an intermediate–high immunoscore achieved better OS than those with a low immunoscore. In subgroup analysis, the prediction of OS was significant for melanoma and head and neck cancer patients but did not reach significance in the non-small cell lung cancer or renal cell carcinoma cohorts. Conclusions: Calculating CD3+ and CD8+ T cell immunoscore using real-world transcriptomic data represents a promising signature for estimating OS with ICIs and can be used as a reference for future machine learning-based biomarker development.

Details

Title: Subtitle: The T Cell Immunoscore as a Reference for Biomarker Development Utilizing Real-World Data from Patients with Advanced Malignancies Treated with Immune Checkpoint Inhibitors
Creators: Islam Eljilany - Moffitt Cancer Center
Payman Ghasemi Saghand - Moffitt Cancer Center
James Chen - The Ohio State University
Aakrosh Ratan - University of Virginia
Martin McCarter
John Carpten - USC Norris Comprehensive Cancer Center
Howard Colman - University of Utah
Alexandra P. Ikeguchi
Igor Puzanov - Roswell Park Cancer Institute
Susanne Arnold - University of Kentucky
Michelle Churchman
Patrick Hwu - Moffitt Cancer Center
Jose Conejo-Garcia - Moffitt Cancer Center
William S. Dalton
George J. Weiner - University of Iowa Health Care
Issam M. El Naqa - Moffitt Cancer Center
Ahmad A. Tarhini - Moffitt Cancer Center
Resource Type: Journal article
Publication Details: Cancers, Vol.15(20), 4913
DOI: 10.3390/cancers15204913
PMID: 37894280
PMCID: PMC10605389
NLM abbreviation: Cancers (Basel)
ISSN: 2072-6694
eISSN: 2072-6694
Grant note: name: ORIEN FOUNDATION, award: 69-21295-01-01; name: National Institute of Health, award: R01-CA233487, CA233487-05S1
Language: English
Date published: 10/10/2023
Academic Unit: Hematology, Oncology, and Blood & Marrow Transplantation; Pharmaceutical Sciences and Experimental Therapeutics; Internal Medicine
Record Identifier: 9984475075502771

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