Evidence map›Paper›PMID 39727934›Full record

ArticleCurrent issues in molecular biology2024

SPP1 mRNA Expression Is Associated with M2 Macrophage Infiltration and Poor Prognosis in Triple-Negative Breast Cancer.

Yu-Chia Chen, Chia-Ching Chen, Rong-Fu Chen, Hsin-Hung Chen, Po-Ming Chen

Abstract read
In one paragraph

Article in Current issues in molecular biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Trial
  2. Article
  3. Article
  4. Article
  5. IGLC3Frontiers in immunology · 2026
    Article
  6. Article
  7. Article
  8. 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

5 authors.

Yu-Chia ChenDivision of General Surgery, Department of Surgery, Kaohsiung Veterans General Hospital, Kaohsiung 813414, Taiwan.
Chia-Ching ChenDepartment of Emergency Medicine, Chang Bing Show Chwan Memorial Hospital, Changhua 505, Taiwan.ORCID 0000-0002-0898-8696
Rong-Fu ChenDivision of Plastic Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung 807, Taiwan.ORCID 0000-0001-7529-5390
Hsin-Hung ChenDepartment of Medical Education and Research, Kaohsiung Veterans General Hospital, No. 386, Dazhong 1st Road, Zuoying District, Kaohsiung 813414, Taiwan.ORCID 0000-0002-5662-5945
Po-Ming ChenResearch Assistant Center, Show Chwan Memorial Hospital, No. 542, Section 1, Zhongshan Road, Changhua 500, Taiwan.ORCID 0000-0002-0824-9615

Funding

Show Chwan Memorial Hospital SRD-112007
6 · The paper itself

Abstract

(1): Triple-negative breast cancer (TNBC) is an especially aggressive form of breast cancer defined by a poor prognosis and a lack of effective treatment options. There is a pressing need for validated predictive and prognostic biomarkers to assist in making treatment decisions and improve the prognostic accuracy for patients with this challenging disease. (2): We analyzed the RNA-seq data from three TNBC tissue samples alongside their corresponding normal tissues. Gene set enrichment analysis (GSEA) identified potential pathways. Additionally, we examined SPP1 mRNA expression datasets available in the Kaplan-Meier plotter and investigated the SPP1 protein expression patterns in our own tissue microarray cohort via immunohistochemistry. (3): The results revealed that genes associated with the Toll-like receptor signaling pathway showed a significant increase in activity in TNBC tissues when compared to normal breast tissues. Furthermore,

Indexed as

prognosisSPP1triple-negative breast cancer

Identifiers

PMID39727934
PMCPMC11674533

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.