FUME-TCRseq Enables Sensitive and Accurate Sequencing of the T-cell Receptor from Limited Input of Degraded RNA

Sep 22, 2026

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FUME-TCRseq delivers a robust RNA-based TCR sequencing method for samples with low-quality, degraded nucleic acids, including formalin-fixed paraffin-embedded tissue. It adds unique molecular identifiers to each cDNA molecule to correct sequencing errors and PCR bias. Benchmarked on colorectal and head-and-neck cancer RNA, it shows strong concordance with existing methods, detects more clonotypes, reduces library preparation time, and lowers cost. High sensitivity enables quantitative analysis of small cell numbers from archival sections and spatially resolved profiling across tumor invasive transitions and subclones.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages10

Reading Time25 min

AccessFree to download

Abstract

Significance

Introduction

TCR biology and sequencing challenges

FUME-TCRseq Enables Sensitive and Accurate Sequencing of the T-cell Receptor from Limited Input of Degraded RNA Ann-Marie Baker1,2, Gayathri Nageswaran3, Pablo Nenclares4, Tahel Ronel1,2,3, Kane Smith1,2, Christopher Kimberley2, Miangela M. Lacl5, Shreerang Bhide4,6, Kevin J. Harrington4, Alan Melcher4,7, Manuel Rodriguez-Justo8, Benny Chain3, and Trevor A. Graham1,2 ABSTRACT ◥ Genomic analysis of the T-cell receptor (TCR) reveals the strength, breadth, and clonal dynamics of the adaptive immune response to pathogens or cancer. The diversity of the TCR repertoire, however, means that sequencing is technically challenging, particularly for samples with low-quality, degraded nucleic acids. Here, we developed and validated FUME-TCRseq, a robust and sensitive RNA-based TCR sequencing methodology that is suitable for formalin-ﬁxed parafﬁn-embedded samples and low amounts of input material. FUME-TCRseq incorporates unique molecular identiﬁers into each molecule of cDNA, allowing correction for sequencing errors and PCR bias. Using RNA extracted from colorectal and head and neck cancers to benchmark the accuracy and sensitivity of FUME-TCRseq against existing methods demonstrated excellent concordance between the datasets. Furthermore, FUME-TCRseq detected more clonotypes than a commercial RNA-based alternative, with shorter library preparation time and signiﬁcantly lower cost. The high sensitivity and the ability to sequence RNA of poor quality and limited amount enabled quantitative analysis of small numbers of cells from archival tissue sections, which is not possible with other methods. Spatially resolved FUME-TCRseq analysis of colorectal cancers using macrodissected archival samples revealed the shifting T-cell landscapes at the transition to an invasive phenotype and between tumor subclones containing distinct driver alterations. In summary, FUME-TCRseq represents an accurate, sensitive, and low-cost tool for the characterization of T-cell repertoires, particularly in samples with low-quality RNA that have not been accessible using existing methodology. Signiﬁcance: FUME-TCRseq is a TCR sequencing methodology that supports sensitive and spatially resolved detection of TCR clones in archival clinical specimens, which can facilitate longitudinal tracking of immune responses through disease course and treatment. Introduction T cells are critical drivers of the adaptive immune response, whose antigen speciﬁcity is determined by the highly diverse T-cell receptor (TCR) sequence. High throughput sequencing and analysis of the TCR repertoire have emerged as powerful tools for proﬁling T-cell responses to pathogens or cancer, or indeed to host tissues in 1Centre for Evolution and Cancer, Institute of Cancer Research, London, United Kingdom. 2Centre for Genomics and Computational Biology, Barts Cancer Institute, Queen Mary University of London, London, United Kingdom. 3Division of Infection and Immunity, University College London, London, United Kingdom. 4Division of Radiotherapy and Imaging, Institute of Cancer Research, London, United Kingdom. 5Department of Pathology, University Medical Center Utrecht, Utrecht, the Netherlands. 6Head and Neck Unit, The Royal Marsden Hospital NHS Trust, London, United Kingdom. 7Division of Breast Cancer Research, Institute of Cancer Research, London, United Kingdom. 8Department of Histopathology, UCL Hospitals NHS Trust, London, United Kingdom. B. Chain and T.A. Graham have contributed equally as the co-senior authors to this article. Corresponding Author: Ann-Marie Baker, Centre for Evolution and Cancer, Institute of Cancer Research, 15 Cotswold Road, Belmont, Sutton, Surrey, SM2 5NG, UK. E-mail: [annie.baker@icr.ac.uk](annie.baker@icr.ac.uk) [Cancer Res 2024](Cancer Res 2024);[84:1560](84:1560)–[9](9) doi: 10.1158/0008-5472 . CAN-23-3340 This open access article is distributed under the Creative Commons Attribution 4. 0 International (CC BY 4 . 0) license. 􀀂2024The

FAQs

What problem does FUME-TCRseq address?

It addresses technically challenging T-cell receptor sequencing when input nucleic acids are low in quantity and degraded, including archival formalin-fixed paraffin-embedded samples.

How does FUME-TCRseq improve accuracy?

It incorporates unique molecular identifiers into each cDNA molecule, enabling correction for sequencing errors and PCR bias.

What benefits does FUME-TCRseq provide compared with a commercial RNA-based method?

It detects more clonotypes, requires shorter library preparation time, and has significantly lower cost while maintaining excellent concordance with benchmark datasets.

Sep 22, 2026

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