Evidence map›Paper›PMID 40734705›Full record

ArticleCancer informatics2025

Single-Cell Sequence and Machine Learning Identify a CD79A+B Cells-Related Transcriptional Signature for Predicting Clinical Outcomes and Immune Microenvironment in Breast Cancer.

Haihong Hu, Wendi Zhan, Hongxia Zhu, Bo Hao, Ting Yan, Jingdi Zhang, Siyu Wang, Taolan Zhang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

8 authors.

Haihong HuDepartment of Pharmacy, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hunan, China.ORCID https://orcid.org/0000-0003-1799-864X
Wendi ZhanDepartment of Pharmacy, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hunan, China.
Hongxia ZhuDepartment of Pharmacy, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hunan, China.
Bo HaoDepartment of Pharmacy, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hunan, China.
Ting YanDepartment of Breast and Thyroid Surgery, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hunan, China.
Jingdi ZhangDepartment of Pharmacy, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hunan, China.
Siyu WangDepartment of Medical Oncology, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hunan, China.
Taolan ZhangDepartment of Pharmacy, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hunan, China.ORCID https://orcid.org/0000-0002-0049-128X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: The aim of this study was to investigate the role and mechanism of CD79A Methods: Single-cell RNA sequencing and bulk RNA sequencing analysis were combined to annotate breast cancer cell subtypes, perform cell communication and trajectory analysis. CD79A-related signature was constructed by LASSO and multivariate Cox analysis. CD79A Results: There were communication relationships between CD79A Conclusion: This study comprehensively explored the heterogeneity of CD79A

Indexed as

breast cancerbulk RNA sequencingCD79A+ B cellsprognostic risk signaturesingle-cell RNA sequencingtumor immune environment

Identifiers

PMID40734705
PMCPMC12304643

What Socratic holds

Textmetadata
LicenceCC BY-NC
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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 Socratic graph.