Evidence map›Paper›PMID 37093316›Full record

ArticleMedical oncology (Northwood, London, England)2023

Classification of triple-negative breast cancer based on pathway enrichment levels.

Qian Liu, Xiaosheng Wang

Abstract read
PubMed Publisher
In one paragraph

Article in Medical oncology (Northwood, London, England), 2023. 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
1.2field-weighted citation impact, top 20% of its field
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, 5 citations in OpenAlex.

  1. Article
  2. Review
  3. Single-Cell RNA-Sequencing: Opening New Horizons for Breast Cancer Research.International journal of molecular sciences · 2024
    Review
  4. Review
  5. 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

2 authors at 1 institution in 1 country.

Qian LiuBiomedical Informatics Research Lab, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 211198, China.
Xiaosheng WangBiomedical Informatics Research Lab, School of Basic Medicine and Clinical Pharmacy, China Pharmaceutical University, Nanjing, 211198, China. xiaosheng.wang@cpu.edu.cn.ORCID http://orcid.org/0000-0002-7199-7093
China Pharmaceutical University · CN

Funding

China Pharmaceutical University 3150120001
6 · The paper itself

Abstract

Triple-negative breast cancer (TNBC) is highly heterogeneous in the stromal and immune microenvironment, genome integrity, oncogenic signatures, and metabolic processes. However, a classification of TNBC by combining these features remains lacking. Here we classified TNBC based on the enrichment levels of 14 pathways related to immune, stromal, oncogenic and metabolic signatures by unsupervised clustering. In three bulk tumor transcriptome datasets and a single cell RNA-Seq (scRNA-seq) dataset, we consistently identified four TNBC subtypes: Imm-E, Str-E, DR-E, and Met-E. Imm-E displayed the strongest immune signatures, the lowest intratumor heterogeneity (ITH), the highest global methylation levels, the lowest tumor purity, and the best prognosis. Str-E showed the strongest stromal signatures and TGF-β signaling. DR-E had the highest DNA repair activity, cell cycle activity, and genomic instability. Met-E demonstrated the strongest hormone metabolism and signaling, the highest ITH, the lowest genomic instability, and the worst prognosis. The subtyping of TNBC provides novel insights into tumor biology and clinical implications for this disease.

Indexed as

Triple Negative Breast NeoplasmsGenomic InstabilityHumansPrognosisTranscriptomeTumor MicroenvironmentClassificationGenomic instabilityImmune signaturesPathway enrichment analysisPrognostic risk scoringTriple-negative breast cancer

Identifiers

PMID37093316
OpenAlexW4366819763

What OpenQuestion holds

Textmetadata
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.