Evidence map›Paper›PMID 40143733›Full record

ArticleInternational journal of surgery (London, England)2025

Identification of biomarkers of shrinkage modes after neoadjuvant therapy in HER-2 positive breast cancer.

Zhao Bi, Yue Zhang, Xian-Rang Song, Wen-Hao Zheng, Peng Chen, Peng-Fei Qiu, Yan-Bing Liu, Yong-Jin Lu, Xing-Guo Song, Yong-Sheng Wang

Abstract read
In one paragraph

Article in International journal of surgery (London, England), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

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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

4 citing papers in PubMed.

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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

10 authors.

Zhao BiShandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China.
Yue ZhangShanghai Pudong New Area Center for Disease Control and Prevention, Shanghai, People's Republic of China.
Xian-Rang SongShandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China.
Wen-Hao ZhengRizhao Central Hospital, Rizhao, Shandong, People's Republic of China.
Peng ChenShandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China.
Peng-Fei QiuShandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China.
Yan-Bing LiuShandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China.
Yong-Jin LuShandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China.
Xing-Guo SongShandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China.
Yong-Sheng WangShandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeA nomogram to predict shrinkage modes after neoadjuvant therapy (NAT) was constructed in HER-2 positive (HER2+) breast cancer. The value and mechanism of targeting long noncoding RNA (lncRNA) as efficacy prediction biomarker was also evaluated.

methodsAll enrolled patients received six cycles of chemotherapy (Docetaxel + Carboplatin) and anti-HER-2 dual-targeted therapy (Trastuzumab + Pertuzumab) before surgery. According to pathological three-dimensional (3D) models of residual tumor from 71 HER2+ patients, shrinkage modes were divided into concentric shrinkage mode (CSM) and non-CSM (NCSM). LncRNAs in core biopsy tissues in the CSM and NCSM groups were selected by microarray and validated by RT-PCR. A nomogram was constructed to predict shrinkage modes after NAT in combination with clinical-pathological and transcriptome signatures. Cell proliferation was used CCK-8 and colony formation assay. PAPIS Kit was used to perform nuclear and cytoplasmic separation. The cell drug resistance assays were to explore the value of paclitaxel. The ChIRP-MS assay was to search RNA-binding proteins and verified by WB. Cell cycle analysis was carried out by flow cytometry.

resultsIndependent predictors of NCSM were lymph nodes downstaging after NAT, mammographic malignant calcification, hormone receptor expression, and RUVBL1-AS1 expression. A nomogram was constructed in combination with these predictors, which showed an area under the curve of 0.883, supporting the predictive power of the method. Overexpression of RUVBL1-AS1 inhibited HER2+ cells proliferation. Overexpression of RUVBL1-AS1 increased the number of cells in G1/S phase and decreased that of cells in G2 phase. RUVBL1-AS1 increased paclitaxel resistance and downregulated VCP expression. RUVBL1-AS1 affects cell cycle progression by downregulating VCP, resulting in the reduction of cells in G2/M phase, thereby weakening the sensitivity to paclitaxel.

conclusionThe nomogram could accurately predict shrinkage modes after NAT, and may help guide the individualized selection of breast conserving surgery candidates after NAT. RUVBL1-AS1 might be a promising therapeutic target of paclitaxel-based chemotherapy inHER2+ breast cancer.

Indexed as

Antineoplastic Combined Chemotherapy ProtocolsBiomarkers, TumorBreast NeoplasmsErb-b2 Receptor Tyrosine KinasesNeoadjuvant TherapyAdultAntibodies, Monoclonal, HumanizedCarboplatinDocetaxelFemaleHumansMiddle AgedNomogramsRNA, Long NoncodingTrastuzumabAntibodies, Monoclonal, HumanizedBiomarkers, TumorCarboplatinDocetaxelERBB2 protein, humanErb-b2 Receptor Tyrosine KinasespertuzumabRNA, Long NoncodingTrastuzumabbreast cancerneoadjuvant therapynomogramRUVBL1-AS1shrinkage modes

Identifiers

PMID40143733
PMCPMC12165485

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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.