Evidence map›Paper›PMID 42494981›Full record

ReviewMolecular therapy. Advances2026

The development of single-cell lineage tracing technology and its application in immunotherapy.

Jun Wang, Zhisen Li, Jia Chen, Huan Li, Fei Chen, Lei Tan, Xiaoge Chen, Song Liu, Wenfeng Zhang, Hongwei Shao

Abstract readReview
In one paragraph

Review in Molecular therapy. Advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Jun WangSchool of Life Sciences and Bio-pharmaceutics, the First Affiliated Hospital, Guangdong Pharmaceutical University, Guangzhou, People's Republic of China.
Zhisen LiSchool of Life Sciences and Bio-pharmaceutics, the First Affiliated Hospital, Guangdong Pharmaceutical University, Guangzhou, People's Republic of China.
Jia ChenSchool of Life Sciences and Bio-pharmaceutics, the First Affiliated Hospital, Guangdong Pharmaceutical University, Guangzhou, People's Republic of China.
Huan LiSchool of Life Sciences and Bio-pharmaceutics, the First Affiliated Hospital, Guangdong Pharmaceutical University, Guangzhou, People's Republic of China.
Fei ChenXianning Traditional Chinese Medicine Hospital, Xianning, People's Republic of China.
Lei TanSchool of Life Sciences and Bio-pharmaceutics, the First Affiliated Hospital, Guangdong Pharmaceutical University, Guangzhou, People's Republic of China.
Xiaoge ChenSchool of Life Sciences and Bio-pharmaceutics, the First Affiliated Hospital, Guangdong Pharmaceutical University, Guangzhou, People's Republic of China.
Song LiuSchool of Pharmacy & Clinical Pharmacy, Guangdong Pharmaceutical University, Guangzhou, People's Republic of China.
Wenfeng ZhangSchool of Life Sciences and Bio-pharmaceutics, the First Affiliated Hospital, Guangdong Pharmaceutical University, Guangzhou, People's Republic of China.
Hongwei ShaoSchool of Life Sciences and Bio-pharmaceutics, the First Affiliated Hospital, Guangdong Pharmaceutical University, Guangzhou, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immunotherapy stands as one of the most promising approaches in cancer treatment, with engineered T cell therapies, particularly chimeric antigen receptor T cell (CAR-T), leading the charge. However, relapse in some patients post-treatment suggests that research in this field remains incomplete. Tumor heterogeneity and the complexities of the immune microenvironment hinder a comprehensive understanding of the changes engineered T cells undergo once introduced into the human body. Single-cell lineage tracing (SCLT) technology facilitates the investigation of cellular development by monitoring the fate and differentiation of individual cells and their descendants within an organism. Employing methodologies such as CRISPR-based labeling and mitochondrial DNA tracking, SCLT allows for dynamic analysis of T cell clonal evolution, exhaustion mechanisms, and memory cell generation. This approach offers single-cell resolution data that contribute to resolving pertinent clinical challenges. This article provides a comprehensive review of recent developments and characteristics of the SCLT multi-omics approach. It elucidates the manner in which SCLT addresses the conventional constraints associated with spatiotemporal resolution and introduces a novel methodology for generating DNA barcodes to monitor CAR-T cells via CRISPR technology. These contributions offer valuable perspectives for the enhancement of cell therapy strategies.

Indexed as

CAR-TCRISPRimmunotherapylineage tracingscRNA-seq

Identifiers

PMID42494981
PMCPMC13392950

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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.