Evidence map›Paper›PMID 41775434›Full record

ReviewJournal for immunotherapy of cancer2026

TCR sequencing in cancer immunology and immunotherapy: what, when, where, why, and how.

Yohei Nose, Igor Figueiredo, Kevin Tuballes, Diane Marie Del Valle, Tina Ruth Gonsalves, Ruiwei Guo, Giorgio Ioannou, Rafael Cabal, Edgar Gonzalez-Kozlova, Sacha Gnjatic

Abstract readReview
In one paragraph

Review in Journal for immunotherapy of cancer, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
  5. Review
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

10 authors.

Yohei NoseImmunology and Immunotherapy, Icahn School of Medicine at Mount Sinai, New York, New York, USA.ORCID http://orcid.org/0000-0003-1973-9035
Igor FigueiredoImmunology and Immunotherapy, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Kevin TuballesImmunology and Immunotherapy, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Diane Marie Del ValleImmunology and Immunotherapy, Icahn School of Medicine at Mount Sinai, New York, New York, USA.ORCID http://orcid.org/0000-0001-6983-5362
Tina Ruth GonsalvesImmunology and Immunotherapy, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Ruiwei GuoImmunology and Immunotherapy, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Giorgio IoannouImmunology and Immunotherapy, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Rafael CabalImmunology and Immunotherapy, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Edgar Gonzalez-KozlovaImmunology and Immunotherapy, Icahn School of Medicine at Mount Sinai, New York, New York, USA.
Sacha GnjaticImmunology and Immunotherapy, Icahn School of Medicine at Mount Sinai, New York, New York, USA sacha.gnjatic@mssm.edu.

Funding

THE TISCH CANCER INSTITUTE - CANCER CENTER SUPPORT GRANTP30CA196521 · NCI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Ramon E Parsons · 2015 to 2026
$35.4M
High-Dimensional Immune Monitoring of NCI-Supported Immunotherapy TrialsU24CA224319 · NCI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Sacha Gnjatic, Seunghee Kim-Schulze · 2017 to 2026
$21.5M
Targeting the Chemokine System to Sensitize Tumors to ImmunotherapyP01CA234212 · NCI · ROSWELL PARK CANCER INSTITUTE CORP · PI KALINSKI, PAWEL · 2020 to 2024
$10.1M
Characterizing and predicting colitis in immune checkpoint blockade-treated cancer patientsU01DK124165 · NIDDK · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI COLOMBEL, JEAN-FREDERIC, FAITH, JEREMIAH JAMES · 2020 to 2024
$2.9M
NCI NIH HHS P01 CA234212NCI NIH HHS P30 CA196521NCI NIH HHS U24 CA224319NIDDK NIH HHS U01 DK124165
6 · The paper itself

Abstract

T-cell receptors (TCRs) are generated through somatic recombination of variable (V), diversity (D), and joining (J) gene segments, resulting in an extraordinarily diverse receptor repertoire that is essential for immune surveillance and host defense. TCR sequencing (TCR-seq) has emerged as a powerful tool for comprehensive characterization of the adaptive immune repertoire, offering deep insights into T-cell diversity, antigen specificity, and clonal dynamics.TCR-seq enables the tracking of T-cell clones across both temporal and spatial dimensions. From a longitudinal perspective, it allows for the monitoring of clonal dynamics before and after therapeutic interventions or over the course of disease progression. Temporal shifts in clonal composition can reveal the persistence, contraction, or expansion of specific T-cell populations, thereby providing valuable information on the durability of immune responses and the efficacy of treatments. From a spatial standpoint, TCR-seq facilitates comparative analyses of repertoires across distinct anatomical compartments, including tumors, blood, and lymph nodes. Such analyses yield insights into tissue-specific immune responses, T-cell trafficking, and infiltration patterns. Moreover, the ability to track antigen-specific T-cell clones enables the visualization and quantification of tumor-specific immune responses. Advances in spatial TCR-seq now integrate spatial context with clonal identity and repertoire diversity, further illuminating complex immune architecture within tissue microenvironments. Nonetheless, despite the development of various approaches for antigen specificity prediction, further advances are needed to improve their accuracy and generalizability.A wide range of TCR-seq platforms are currently available, including DNA-based and RNA-based protocols, short-read and long-read sequencing technologies, and bulk and single-cell approaches. Each method presents unique advantages in terms of resolution, throughput, cost, and biological relevance. For instance, DNA-based TCR-seq is well suited for longitudinal tracking of clonal populations, whereas RNA-based approaches are advantageous for detecting actively transcribed, antigen-responsive clones. Short-read sequencing offers high-throughput capabilities, while long-read and paired-chain sequencing provide comprehensive structural and functional information on TCRs. Additionally, computational methods, including machine learning algorithms and motif-based clustering, are increasingly employed to infer antigen specificity directly from TCR-seq data.In this review, we examine the current landscape of TCR-seq through the lenses of what, when, where, why, and how, highlighting recent technological developments and emerging applications that are shaping the field of immune repertoire analysis.

Indexed as

ImmunotherapyNeoplasmsReceptors, Antigen, T-CellAnimalsHumansT-LymphocytesReceptors, Antigen, T-CellBiomarkerImmune Checkpoint InhibitorNext generation sequencing - NGST cellT cell Receptor - TCR

Identifiers

PMID41775434
PMCPMC12958967

What OpenQuestion holds

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LicenceCC BY-NC
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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.