Evidence map›Paper›PMID 31534839›Full record

ArticlePeerJ2019

Network-based approach to identify biomarkers predicting response and prognosis for HER2-negative breast cancer treatment with taxane-anthracycline neoadjuvant chemotherapy.

Cui Jiang, Shuo Wu, Lei Jiang, Zhichao Gao, Xiaorui Li, Yangyang Duan, Na Li, Tao Sun

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in PeerJ, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing 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

9 citing papers in PubMed.

  1. Article
  2. Apelin/APJ: Another Player in the Cancer Biology Network.International journal of molecular sciences · 2025
    Review
  3. Article
  4. Article
  5. Article
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  7. Article
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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.

Cui JiangDepartment of Medical Oncology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, Liaoning, China.
Shuo WuDepartment of Medical Oncology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, Liaoning, China.
Lei JiangDepartment of Medical Oncology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, Liaoning, China.
Zhichao GaoDepartment of Medical Oncology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, Liaoning, China.
Xiaorui LiDepartment of Medical Oncology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, Liaoning, China.
Yangyang DuanDepartment of Medical Oncology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, Liaoning, China.
Na LiInstitute of Translational Medicine, China Medical University, Shenyang, Liaoning, China.
Tao SunDepartment of Medical Oncology, Cancer Hospital of China Medical University, Liaoning Cancer Hospital and Institute, Shenyang, Liaoning, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aims to identify effective gene networks and biomarkers to predict response and prognosis for HER2-negative breast cancer patients who received sequential taxane-anthracycline neoadjuvant chemotherapy. MATERIALS AND

methodsTranscriptome data of training dataset including 310 HER2-negative breast cancer who received taxane-anthracycline treatment and an independent validation set with 198 samples were analyzed by weighted gene co-expression network analysis (WGCNA) approach in R language. Gene ontology (GO) terms and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis were performed for the selected genes. Module-clinical trait relationships were analyzed to explore the genes and pathways that associated with clinicopathological parameters. Log-rank tests and COX regression were used to identify the prognosis-related genes.

resultsWe found a significant correlation of an expression module with distant relapse-free survival (HR = 0.213, 95% CI [0.131-0.347],

conclusionWe used WGCNA approach to reveal a gene network that regulate HER2-negative breast cancer treatment with taxane-anthracycline neoadjuvant chemotherapy, which enriched in pathways of estrogen signaling, apelin signaling, cAMP signaling, the PPAR signaling pathway and fatty acid metabolism. In addition, genes of CA12, FOXA1, MLPH, XBP1, GATA3 and MAGED2 might serve as novel biomarkers predicting chemotherapeutic response and prognosis for HER2-negative breast cancer.

Indexed as

Breast cancerNeoadjuvant chemotherapyPrognosisResponseWGCNA

Identifiers

PMID31534839
PMCPMC6730536

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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.