A long noncoding RNA-based serum signature predicts ado-trastuzumab emtansine (T-DM1) treatment benefit in HER2+ metastatic breast cancer patients: a multicenter cohort study

Ado-trastuzumab is considered a standard treatment for patients with HER2+ metastatic breast cancer (mBC). Current clinical practices do not reliably predict therapeutic outcomes for patients who are refractory to therapy. Long noncoding RNAs (lncRNAs) are emerging as critical regulators of gene expression and therapeutic resistance, and the use of lncRNAs as tumor biomarkers is becoming more common in other diseases. However, whether they may also be used to predict therapy response in HER2+ mBC is unclear. Using lncRNA microarray profiling, we identified 23 differentially expressed lncRNAs in the serum of HER2+ mBC patients with unique responses to trastuzumab-emtansine (T-DM1). Following RT-PCR validation and machine learning-based selection in the training cohort, four lncRNAs were selected to construct the signature panel and used for T-DM1 response prediction. This four-lncRNA signature classifies patients into high- and low-risk groups and significantly and distinctively predicts patient survival. Importantly, identical outcomes were obtained from the two validation cohorts, confirming that the signature accurately predicts the T-DM1 response of HER2+ mBC patients. Integrative analysis demonstrated that this four-lncRNA signature is primarily released by immune and tumor cells and is correlated with immune activity. Our findings indicate that the four-lncRNA signature is a potentially promising biomarker for predicting T-DM1 treatment outcome, as it may reliably predict the T-DM1 treatment response in HER2+ mBC.

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Publication Details

Journal
Cell Death Discovery
Published
2025-09-09
DOI
https://doi.org/10.1038/s41420-025-02701-8
Citations
1
Primary Topic
Cancer-related molecular mechanisms research
Type
article
Field-Weighted Citation Impact
0.94
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article

A long noncoding RNA-based serum signature predicts ado-trastuzumab emtansine (T-DM1) treatment benefit in HER2+ metastatic breast cancer patients: a multicenter cohort study

Ahmed Gad, Asma Tulbah, Abdelilah Aboussekhra, Layla Al-Harbi et al.
1 citations
Cell Death Discovery
Cancer-related molecular mechanisms research
0.94
article

A long noncoding RNA-based serum signature predicts ado-trastuzumab emtansine (T-DM1) treatment benefit in HER2+ metastatic breast cancer patients: a multicenter cohort study

Ahmed Gad, Asma Tulbah, Abdelilah Aboussekhra, Layla Al-Harbi, Taher Al‐Tweigeri, Sana Bouakez Héla Najjar, Shafat Ujjahan, Syed S. Islam, S Aljohani
article en
1 citations

Abstract

Ado-trastuzumab is considered a standard treatment for patients with HER2+ metastatic breast cancer (mBC). Current clinical practices do not reliably predict therapeutic outcomes for patients who are refractory to therapy. Long noncoding RNAs (lncRNAs) are emerging as critical regulators of gene expression and therapeutic resistance, and the use of lncRNAs as tumor biomarkers is becoming more common in other diseases. However, whether they may also be used to predict therapy response in HER2+ mBC is unclear. Using lncRNA microarray profiling, we identified 23 differentially expressed lncRNAs in the serum of HER2+ mBC patients with unique responses to trastuzumab-emtansine (T-DM1). Following RT-PCR validation and machine learning-based selection in the training cohort, four lncRNAs were selected to construct the signature panel and used for T-DM1 response prediction. This four-lncRNA signature classifies patients into high- and low-risk groups and significantly and distinctively predicts patient survival. Importantly, identical outcomes were obtained from the two validation cohorts, confirming that the signature accurately predicts the T-DM1 response of HER2+ mBC patients. Integrative analysis demonstrated that this four-lncRNA signature is primarily released by immune and tumor cells and is correlated with immune activity. Our findings indicate that the four-lncRNA signature is a potentially promising biomarker for predicting T-DM1 treatment outcome, as it may reliably predict the T-DM1 treatment response in HER2+ mBC.

Cell Death DiscoveryVol. 11(1)
Alfaisal University (SA), King Faisal Specialist Hospital & Research Centre (SA), Chattagram Maa-O-Shishu Hospital Medical College (BD)
Openalex Percentile: Top 21%
Cancer-related molecular mechanisms research
0.94
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