Evidence map›Paper›PMID 40684046›Full record

ArticleNPJ precision oncology2025

Circulating T-cell receptor repertoire for cancer early detection.

Yilong Li, Michelle Nahas, Dennis Stephens, Kate Froburg, Emma Hintz, Devin Champagne, Amaneet Lochab, Markus Brown, Jasper Braun, María Antonia Fortuño and 16 more

Abstract read
In one paragraph

Article in NPJ precision oncology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

26 authors.

Yilong Li *Serum Detect, Inc, Newton, MA, USA.
Michelle Nahas *Serum Detect, Inc, Newton, MA, USA.
Dennis StephensSerum Detect, Inc, Newton, MA, USA.
Kate FroburgSerum Detect, Inc, Newton, MA, USA.
Emma HintzSerum Detect, Inc, Newton, MA, USA.
Devin ChampagneSerum Detect, Inc, Newton, MA, USA.
Amaneet LochabSerum Detect, Inc, Newton, MA, USA.
Markus BrownSerum Detect, Inc, Newton, MA, USA.
Jasper BraunSerum Detect, Inc, Newton, MA, USA.
María Antonia FortuñoClínica Universidad de Navarra Cancer Center, Pamplona, Spain.
María-Del-Mar OcónClínica Universidad de Navarra Cancer Center, Pamplona, Spain.
Andrea PasquierClínica Universidad de Navarra Cancer Center, Pamplona, Spain.
Inés Luque-VázquezClínica Universidad de Navarra Cancer Center, Pamplona, Spain.
Hita MoudgalyaRush University Medical Center Department of Anatomy & Cell Biology, Chicago, IL, USA.
Sophie KivlehanDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
Iliana GjeciDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
Stephanie L KorleDivision of Thoracic Surgery, Brigham and Women's Hospital, Boston, MA, USA.
Arantza CampoPulmonary Department, Clínica Universidad de Navarra, Madrid, Spain.
Maria RodriguezThoracic Surgery Department, Clínica Universidad de Navarra, Madrid, Spain.
Christopher W SederRush University Medical Center Department of Cardiovascular and Thoracic Surgery, Chicago, IL, USA.
Patrick H LizotteDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA.
Raphael BuenoDivision of Thoracic Surgery, Brigham and Women's Hospital, Boston, MA, USA.
Jeffrey A BorgiaRush University Medical Center Department of Anatomy & Cell Biology, Chicago, IL, USA.
Luis M SeijoClínica Universidad de Navarra Cancer Center, Pamplona, Spain. lseijo@unav.es.
Luis M MontuengaClínica Universidad de Navarra Cancer Center, Pamplona, Spain. lmontuenga@unav.es.
Roman YelenskySerum Detect, Inc, Newton, MA, USA. roman@serumdetect.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Liquid biopsy is a promising non-invasive technology that is capable of diagnosing cancer. However, current ctDNA-based approaches detect only a minority of early-stage disease. We set out to improve the sensitivity of liquid biopsy by harnessing tumor recognition by T cells through the sequencing of the circulating T-cell receptor repertoire. We studied a cohort of 463 patients with lung cancer (86% stage I) and 587 subjects without cancer using gDNA extracted from blood buffy coats. We performed TCR β chain sequencing to yield a median of 113,571 TCR clonotypes per sample and built a TCR sequence similarity graph to cluster clonotypes into TCR repertoire functional units (RFUs). The TCR frequencies of RFUs were tested for association with cancer status and RFUs with a statistically significant association were combined into a cancer score using a support vector machine model. The model was evaluated by 10-fold cross-validation and compared with a ctDNA panel of 237 mutation hotspots in 154 lung cancer driver genes and 17 cancer related protein biomarkers in 85 subjects. We identified 327 cancer-associated TCR RFUs with a false discovery rate (FDR) ≤ 0.1, including 157 enriched in cancer samples and 170 enriched in controls. Levels of 247/327 (76%) RFUs were correlated with the presence of an HLA allele at FDR ≤ 0.1 and tumor-infiltrating lymphocyte TCRs from multiple RFUs bound HLA presented tumor antigen peptides, suggesting antigen recognition as a driver of the cancer-RFU associations found. The RFU cancer score detected nearly 50% of stage I lung cancers at a specificity of 80% and boosted the sensitivity by up to 20 percentage points when added to ctDNA and circulating proteins in a multi-analyte cancer screening test. Overall, we show that circulating TCR repertoire functional unit analysis can complement established analytes to improve liquid biopsy sensitivity for early-stage cancer.

Identifiers

PMID40684046
PMCPMC12276287

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.