Evidence map›Paper›PMID 41179682›Full record

ArticleFrontiers in oncology2025

Integrating single-cell transcriptomics and whole-genome CRISPR CAS9 screen identifies a cell cluster associated with tumor dependency in triple-negative breast cancer.

Su Liu, Shuo Wang, Guixin Wang, Yingxi Li, Zhigang Zhao, Yao Tian, Junming Cao

Abstract read
In one paragraph

Article in Frontiers in oncology, 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

7 authors.

Su Liu *Department of Hematology, Tianjin Medical University Cancer Institute and Hospital, Tianjin Cancer Hospital Airport Hospital, National Clinical Research Center for Cancer, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, Tianjin, China.
Shuo Wangthe First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Guixin Wangthe First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.
Yingxi LiHealth Science Center, Ningbo University, Ningbo, Zhejiang, China.
Zhigang ZhaoDepartment of Medical Oncology, Tianjin First Central Hospital, School of Medicine, Nankai University, Tianjin, China.
Yao TianDepartment of Thoracic Surgery, The Affiliated LiHuiLi Hospital of Ningbo University, Ningbo, Zhejiang, China.
Junming Caothe First Department of Breast Cancer, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Triple-negative breast cancer (TNBC) is the most aggressive breast cancer subtype; however, clinically approved prognostic biomarkers and therapeutic options remain limited. This study aimed to investigate tumor dependency genes to identify novel therapeutic targets for TNBC. Methods: Tumor dependency genes for TNBC were identified using the The Cancer Dependency Map (DEPMAP) database. The TCGA-BRCA dataset was utilized to analyze the expression, survival associations, and pathway enrichment of these genes. Single-cell datasets were employed to explore cellular trajectories and biological functions within tumor dependency gene-associated cell subpopulations. Genomic sequencing was used to investigate the somatic mutational landscape influencing the infiltration abundance of the tumor dependency-associated subpopulation. The METABRIC dataset assessed the impact of the tumor dependency-associated subpopulation on radiotherapy, chemotherapy, and combination therapy outcomes. Potential drugs were identified using the Connectivity Map (CMAP). Colony formation experiment and the CCK-8 experiment were performed to validate the biological function of gene. Results: Four tumor dependency genes (TDGs) were identified. These genes were highly expressed in TNBC and associated with poor prognosis. Enrichment analysis revealed their significant involvement in cell cycle-related pathways. Single-cell analysis demonstrated that the tumor dependency-associated subpopulation (TDAS), defined by these four genes, resided at the differentiation terminus of epithelial/tumor cells and was linked to energy metabolism and cell proliferation pathways. Crucially, patients with high TDAS infiltration abundance were found to be unsuitable for surgery alone and should receive combined radiotherapy or chemotherapy. Potential therapeutic agents targeting the TDAS were screened. And Conclusion: This study identifies four potential TNBC biomarkers for assessing TDAS abundance, providing novel insights and strategies for personalized TNBC treatment.

Indexed as

cell proliferationCRISPR-Cas9ScRNA-seqtriple-negative breast cancertumor dependency

Identifiers

PMID41179682
PMCPMC12575124

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.