Abstract PS4-02-03: Tumor-educated platelet RNA captures treatment-induced transcriptomic changes and predicts response in luminal breast cancer

Abstract Background: Tumor-educated platelets (TEPs) store cancer-related mRNAs and tolerate routine manipulation, providing a stable and minimally invasive window into disease biology. We wondered whether serial TEPs-RNA profiling reflects therapy-induced changes and predicts response in Luminal (HR+/HER2) breast cancer. Methods: In a prospective luminal cohort (n = 12), platelet-rich plasma was collected at diagnosis (T0), post-neoadjuvant therapy (T1) and post-surgery (TF). Fifty-five immune, proliferative and endocrine genes were quantified by RT-qPCR. Data were analysed with PLS-DA, limma differential expression, Spearman correlation with tumour shrinkage, and logistic regression for nodal status. Results: PLS-DA cleanly separated T0, T1 and TF, indicating stepwise transcriptomic re-programming. Twenty genes differed between T0 vs T1 and T0 vs TF (FDR < 0.05); five differed between T1 vs TF. Higher post-neoadjuvant IKBKG and VDR correlated with greater tumour reduction (r ≈ -0.6, p < 0.01). A two-gene model (CACNA2D1 + IKBKG) classified axillary involvement with 85% accuracy. A baseline five-gene signature (ADRB2, IL13, CACNA2D1, MET, ERBB2) was identified that distinguishes patients who achieved pathological complete response (pCR), showing an AUC of 0.87 and clear segregation in hierarchical clustering. Enrichment analysis revealed pathways related to cell cycle control, DNA repair, and p53 regulation, highlighting biological processes associated with treatment response. Conclusions: Sequential TEPs-RNA profiling reflects molecular effects of therapy and surgery and yields baseline biomarkers of complete response in luminal breast cancer. Platelet RNA warrants prospective validation as an accessible complement to tissue-based assays for personalized treatment. Citation Format: I. URDANIBIA, A. VELASCO, G. RODRIGUEZ, N. TUSET, A. GASOL, S. MORALES. Tumor-educated platelet RNA captures treatment-induced transcriptomic changes and predicts response in luminal breast cancer. [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS4-02-03.

Authors

Institutions

Publication Details

Journal
Clinical Cancer Research
Published
2026-02-17
DOI
https://doi.org/10.1158/1557-3265.sabcs25-ps4-02-03
Primary Topic
Extracellular vesicles in disease
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Abstract PS4-02-03: Tumor-educated platelet RNA captures treatment-induced transcriptomic changes and predicts response in luminal breast cancer

Ariadna Gasol, G. RODRIGUEZ, N. TUSET, I. URDANIBIA et al.
Clinical Cancer Research
Extracellular vesicles in disease
article

Abstract PS4-02-03: Tumor-educated platelet RNA captures treatment-induced transcriptomic changes and predicts response in luminal breast cancer

Ariadna Gasol, G. RODRIGUEZ, N. TUSET, I. URDANIBIA, A. VELASCO, S. MORALES
article en

Abstract

Abstract Background: Tumor-educated platelets (TEPs) store cancer-related mRNAs and tolerate routine manipulation, providing a stable and minimally invasive window into disease biology. We wondered whether serial TEPs-RNA profiling reflects therapy-induced changes and predicts response in Luminal (HR+/HER2) breast cancer. Methods: In a prospective luminal cohort (n = 12), platelet-rich plasma was collected at diagnosis (T0), post-neoadjuvant therapy (T1) and post-surgery (TF). Fifty-five immune, proliferative and endocrine genes were quantified by RT-qPCR. Data were analysed with PLS-DA, limma differential expression, Spearman correlation with tumour shrinkage, and logistic regression for nodal status. Results: PLS-DA cleanly separated T0, T1 and TF, indicating stepwise transcriptomic re-programming. Twenty genes differed between T0 vs T1 and T0 vs TF (FDR < 0.05); five differed between T1 vs TF. Higher post-neoadjuvant IKBKG and VDR correlated with greater tumour reduction (r ≈ -0.6, p < 0.01). A two-gene model (CACNA2D1 + IKBKG) classified axillary involvement with 85% accuracy. A baseline five-gene signature (ADRB2, IL13, CACNA2D1, MET, ERBB2) was identified that distinguishes patients who achieved pathological complete response (pCR), showing an AUC of 0.87 and clear segregation in hierarchical clustering. Enrichment analysis revealed pathways related to cell cycle control, DNA repair, and p53 regulation, highlighting biological processes associated with treatment response. Conclusions: Sequential TEPs-RNA profiling reflects molecular effects of therapy and surgery and yields baseline biomarkers of complete response in luminal breast cancer. Platelet RNA warrants prospective validation as an accessible complement to tissue-based assays for personalized treatment. Citation Format: I. URDANIBIA, A. VELASCO, G. RODRIGUEZ, N. TUSET, A. GASOL, S. MORALES. Tumor-educated platelet RNA captures treatment-induced transcriptomic changes and predicts response in luminal breast cancer. [abstract]. In: Proceedings of the San Antonio Breast Cancer Symposium 2025; 2025 Dec 9-12; San Antonio, TX. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(4 Suppl):Abstract nr PS4-02-03.

Clinical Cancer ResearchVol. 32(4_Supplement)
Universitat de Lleida (ES), Hospital Universitari Arnau de Vilanova (ES), Hospital Arnau de Vilanova (ES), Instituto de Investigación Biomédica de Lleida (ES)
Openalex Percentile: Top 52%
Extracellular vesicles in disease
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.