Data from T-cell Receptor Profiling of Blood to Detect Lung Cancer

<div>Abstract<p>The blood T-cell receptor (TCR) repertoire broadly reflects current and lifetime immune responses against infectious pathogens and cancer, but the circulating T-cell repertoire remains a largely untapped resource for cancer biomarker studies due to repertoire complexity and limited profiling data. In this study, we investigated the use of blood TCR sequencing for the early detection of lung cancer. We sequenced the leukocyte fraction of peripheral blood from 633 individuals divided into a case–control cohort (<i>n</i> = 511) and a lung cancer screening cohort (<i>n</i> = 122), representing more than 12.6 million unique clonotypes. Based on the TCR repertoires in these individuals, we devised a Tumor Immune Lymphocyte Score (TILS) using either TCR specificity groups (TILS-A) or highly recurrent “public” TCR clonotypes (TILS-B) capable of detecting lung cancer. TILS-A consisted of 125 TCR specificity groups that outperformed the TILS-B classifier of 49 public, TCRβ-Vβ–defined clonotypes for cancer detection. TILS classifiers (TILS-A and TILS-B) provided predictive value after accounting for age, smoking status, and nodule size in the lung cancer screening cohort and improved cancer prediction for individuals with indeterminate lung cancer risk. In the subgroup analysis, TILS-A was associated with lung cancer in both early- and late-stage disease, had improved accuracy when accounting for HLA status, and was validated in an external dataset studying lung cancer initiation. Collectively, these data suggest that profiles of the circulating T-cell response can provide value for lung cancer detection and support its use as a diagnostic tool.</p></div>

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Publication Details

Published
2025-09-02
DOI
https://doi.org/10.1158/2326-6066.c.8011999
Primary Topic
Monoclonal and Polyclonal Antibodies Research
Type
article
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article

Data from T-cell Receptor Profiling of Blood to Detect Lung Cancer

Diane Tseng, A. McGarry Houghton, Jianhong Cao, Lorna G. Nolan et al.
Monoclonal and Polyclonal Antibodies Research
article

Data from T-cell Receptor Profiling of Blood to Detect Lung Cancer

Diane Tseng, A. McGarry Houghton, Jianhong Cao, Lorna G. Nolan, Mason Lai, Shin‐Heng Chiou, Pamela Y. Yang, Koshlan Mayer-Blackwell, Maria T. Søgaard, Sudhakar Pipavath, Evan W. Newell, Wei Wu, Kyle K. Payne, Viswam S. Nair, Sarah Gibbs
article en

Abstract

<div>Abstract<p>The blood T-cell receptor (TCR) repertoire broadly reflects current and lifetime immune responses against infectious pathogens and cancer, but the circulating T-cell repertoire remains a largely untapped resource for cancer biomarker studies due to repertoire complexity and limited profiling data. In this study, we investigated the use of blood TCR sequencing for the early detection of lung cancer. We sequenced the leukocyte fraction of peripheral blood from 633 individuals divided into a case–control cohort (<i>n</i> = 511) and a lung cancer screening cohort (<i>n</i> = 122), representing more than 12.6 million unique clonotypes. Based on the TCR repertoires in these individuals, we devised a Tumor Immune Lymphocyte Score (TILS) using either TCR specificity groups (TILS-A) or highly recurrent “public” TCR clonotypes (TILS-B) capable of detecting lung cancer. TILS-A consisted of 125 TCR specificity groups that outperformed the TILS-B classifier of 49 public, TCRβ-Vβ–defined clonotypes for cancer detection. TILS classifiers (TILS-A and TILS-B) provided predictive value after accounting for age, smoking status, and nodule size in the lung cancer screening cohort and improved cancer prediction for individuals with indeterminate lung cancer risk. In the subgroup analysis, TILS-A was associated with lung cancer in both early- and late-stage disease, had improved accuracy when accounting for HLA status, and was validated in an external dataset studying lung cancer initiation. Collectively, these data suggest that profiles of the circulating T-cell response can provide value for lung cancer detection and support its use as a diagnostic tool.</p></div>

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Monoclonal and Polyclonal Antibodies Research
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