Evidence map›Paper›PMID 41482355›Full record

ArticleCancer genomics & proteomics

Comparative Transcriptomic Analysis Identifies Predictive Biomarkers of Pathological Complete Response in Triple-negative Breast Cancer.

Fang-Ming Chen, Chung-Liang Li, Mei-Ren Pan, Yun-Cian Huang, Li-Ju Huang, Sin-Hua Moi, Shu-Jyuan Chang, Ping-Fu Yang, Chieh-Ni Kao, Jung-Yu Kan and 7 more

Abstract readComparative Study
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer genomics & proteomics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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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

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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

17 authors.

Fang-Ming Chen *Division of Breast Oncology and Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan, R.O.C.
Chung-Liang Li *Division of Breast Oncology and Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan, R.O.C.
Mei-Ren PanGraduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan, R.O.C.
Yun-Cian HuangGraduate Institute of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan, R.O.C.
Li-Ju HuangDepartment of Medical Research and Development, Kaohsiung Municipal Ta-Tung Hospital, Kaohsiung, Taiwan, R.O.C.
Sin-Hua MoiGraduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan, R.O.C.
Shu-Jyuan ChangGraduate Institute of Clinical Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan, R.O.C.
Ping-Fu YangDivision of Breast Oncology and Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan, R.O.C.
Chieh-Ni KaoDivision of Breast Oncology and Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan, R.O.C.
Jung-Yu KanDivision of Breast Oncology and Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan, R.O.C.
Li-Kun KoDivision of Breast Oncology and Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan, R.O.C.
Hidenobu TakahashiDivision of Breast Oncology and Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan, R.O.C.
Chia-Yu KuoDivision of Breast Oncology and Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan, R.O.C.
Shen-Liang ShihDivision of Breast Oncology and Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan, R.O.C.
Ming-Feng HouDivision of Breast Oncology and Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan, R.O.C.
Yi-Hsiung LinCenter for Lipid Biosciences, Department of Medical Research, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan, R.O.C.
Chi-Wen LuoDivision of Breast Oncology and Surgery, Department of Surgery, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan, R.O.C.; cwlo0623@gmail.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

aimPathologic complete response (pCR) to neoadjuvant chemotherapy (NACT) is a strong prognostic indicator in triple-negative breast cancer (TNBC). However, reliable predictive biomarkers for pCR remain limited. This study aimed to identify gene expression signatures associated with pCR in TNBC to facilitate more precise treatment stratification. MATERIALS AND

methodsTumor samples from 16 TNBC patients treated with NAC at the Kaohsiung Medical University Hospital (KMUH) were analyzed, including 5 pCR and 11 non-pCR cases. RNA sequencing (RNA-seq) was performed, and differentially expressed genes (DEGs) were identified using DESeq2 (|log

resultsIn the KMUH cohort, 175 DEGs were identified, including 146 up-regulated and 29 down-regulated genes in non-pCR tumors. Fifteen DEGs demonstrated consistent differential expression patterns between KMUH and TCGA datasets, showing enrichment in pCR samples. These genes may serve as predictive biomarkers for NAC response. Notably, several of these genes are potentially druggable, suggesting opportunities for targeted therapy in chemoresistant TNBC.

conclusionWe identified and validated a 15 gene signature associated with pCR in TNBC across independent cohorts. These findings offer a promising basis for improving patient stratification, guiding treatment decisions, and developing targeted therapies for NAC-resistant TNBC.

Indexed as

Biomarkers, TumorGene Expression ProfilingTranscriptomeTriple Negative Breast NeoplasmsAdultAgedFemaleGene Expression Regulation, NeoplasticHumansMiddle AgedNeoadjuvant TherapyPrognosisBiomarkers, Tumorbiomarkergene expression signatureneoadjuvant chemotherapypathological complete responseTriple-negative breast cancer

Identifiers

PMID41482355
PMCPMC12758711

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LicenceCC BY-NC-ND
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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.