Evidence map›Paper›PMID 40754872›Full record

ArticleCurrent cancer drug targets2025

Single-Cell Transcriptomics: Technical Advances, Applications and Challenges in Cancer Drug Discovery.

Yueying Yang, Lingyu Meng, Teng Zhang, Jianjun Tan

Abstract read
In one paragraph

Article in Current cancer drug targets, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

4 authors.

Yueying YangDepartment of Biomedical Engineering, School of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China.
Lingyu MengDepartment of Biomedical Engineering, School of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China.
Teng ZhangDepartment of Biomedical Engineering, School of Chemistry and Life Science, Beijing University of Technology, Beijing 100124, China.
Jianjun TanBeijing International Science and Technology Cooperation Base for Intelligent Physiological Measure-ment and Clinical Transformation, Beijing 100124, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With advancements in technology, single-cell RNA sequencing has emerged as a power-ful tool in cancer drug discovery. This technique enables the construction of gene expression profiles at the individual cell level, offering detailed insights into cellular heterogeneity and molecular path-ways involved in tumor development. It enables researchers to gain a deeper understanding of tumor heterogeneity. Researchers can study cell subpopulations and gene expression patterns. This under-standing helps in identifying potential drug targets. Additionally, it aids in predicting therapeutic responses. This high-resolution gene expression analysis provides a new perspective and oppor-tunity for cancer drug development, which is expected to accelerate the discovery and development process of new anti-cancer drugs. This article provides a comprehensive overview of the basic pro-cesses and developmental trajectory of single-cell RNA sequencing technology, with a particular emphasis on its applications in various aspects of cancer drug discovery. It also addresses the chal-lenges faced by single-cell RNA sequencing and potential future directions. This review aims to enhance readers' understanding of single-cell sequencing, inspire new ideas for oncology drug de-velopment, and support the translation of clinical research into practice, ultimately enabling physi-cians to design more precise and personalized treatment strategies.

Indexed as

cancer drug discoverydrug resistance.heterogeneitySingle-cell RNA sequencingtarget identificationtumor microenvironment

Identifiers

PMID40754872
PMCPMC13681292

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.