Proteogenomic decoding of chemotherapy resistance in patients with triple-negative breast cancer

BACKGROUND: The clinical utility of integrated proteogenomic biomarkers for predicting chemotherapy response in triple-negative breast cancer remains underexplored. We prospectively analyzed paired baseline and post-treatment tumor samples from 50 patients with stage II-III TNBC treated with anthracycline- and taxane-based neoadjuvant chemotherapy, integrating whole-exome sequencing, RNA sequencing, global proteomics, and phosphoproteomics. RESULTS: Non-negative matrix factorization clustering identifies five proteogenomic subtypes. The immune-enriched subtype demonstrates the highest pathologic complete response rate (55.6%), whereas no pathologic complete response was observed in the xenobiotic metabolism or epithelial-mesenchymal transition subtypes. Immune-related pathways are enriched in tumors with pathologic complete response, while epithelial-mesenchymal transition pathways are enriched in non-pathologic complete response tumors. The estrogen response pathway is selectively enriched in non-pathologic complete response tumors at the proteomic level and inversely correlated with immune activation. Post-translational modification and in vitro analyses suggest estrogen-linked GRK2 activation contributes to chemotherapy resistance. ITGB8 copy number loss is associated with higher pathologic complete response rates and immune activation, while non-pathologic complete response tumors of the immunomodulatory subtype show increased expression of AKR1C2 and ABCA13. Comparison of baseline and post-treatment tumors reveals AURKB pathway activation in residual disease, with Aurora B kinase inhibition synergizing with paclitaxel. A predictive model incorporating these biomarkers outperforms RNA-based models in predicting response. CONCLUSION: Integrative proteogenomic profiling enables robust prediction of chemotherapy resistance in triple-negative breast cancer and identifies actionable biomarkers providing a framework for advancing personalized therapeutic strategies.

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Publication Details

Journal
Genome biology
Published
2026-04-13
DOI
https://doi.org/10.1186/s13059-026-04053-7
Primary Topic
Advanced Proteomics Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Proteogenomic decoding of chemotherapy resistance in patients with triple-negative breast cancer

Hyun Myoung Yun, Jee Ye Kim, Won‐Ji Ryu, Ja Seung Koo et al.
Genome biology
Advanced Proteomics Techniques and Applications
article

Proteogenomic decoding of chemotherapy resistance in patients with triple-negative breast cancer

Hyun Myoung Yun, Jee Ye Kim, Won‐Ji Ryu, Ja Seung Koo, Geon-Uk Kim, Seul‐Gi Kim, Yumi Hwang, Shinyoung Park, Hyun Ju Han, Jong Bae Park, Min Hwan Kim, Seho Park, G. Kim, Heon Yung Gee, Seung Il Kim, Joohyuk Sohn, Min Hyoung Kim, Dong Yun Lee, Kyung-Hee Kim, Hyung Seok Park
article en

Abstract

BACKGROUND: The clinical utility of integrated proteogenomic biomarkers for predicting chemotherapy response in triple-negative breast cancer remains underexplored. We prospectively analyzed paired baseline and post-treatment tumor samples from 50 patients with stage II-III TNBC treated with anthracycline- and taxane-based neoadjuvant chemotherapy, integrating whole-exome sequencing, RNA sequencing, global proteomics, and phosphoproteomics. RESULTS: Non-negative matrix factorization clustering identifies five proteogenomic subtypes. The immune-enriched subtype demonstrates the highest pathologic complete response rate (55.6%), whereas no pathologic complete response was observed in the xenobiotic metabolism or epithelial-mesenchymal transition subtypes. Immune-related pathways are enriched in tumors with pathologic complete response, while epithelial-mesenchymal transition pathways are enriched in non-pathologic complete response tumors. The estrogen response pathway is selectively enriched in non-pathologic complete response tumors at the proteomic level and inversely correlated with immune activation. Post-translational modification and in vitro analyses suggest estrogen-linked GRK2 activation contributes to chemotherapy resistance. ITGB8 copy number loss is associated with higher pathologic complete response rates and immune activation, while non-pathologic complete response tumors of the immunomodulatory subtype show increased expression of AKR1C2 and ABCA13. Comparison of baseline and post-treatment tumors reveals AURKB pathway activation in residual disease, with Aurora B kinase inhibition synergizing with paclitaxel. A predictive model incorporating these biomarkers outperforms RNA-based models in predicting response. CONCLUSION: Integrative proteogenomic profiling enables robust prediction of chemotherapy resistance in triple-negative breast cancer and identifies actionable biomarkers providing a framework for advancing personalized therapeutic strategies.

Genome biologyVol. 27(1)
Kookmin University (KR), Yonsei University (KR), Kyung Hee University (KR), CHA University Bundang Medical Center (KR), Yonsei University Health System (KR)
Handok, National Research Foundation, National Cancer Center, Korea Health Industry Development Institute, National Research Foundation of Korea, Ministry of Science and ICT, South Korea, National Cancer Institute
Good health and well-being
Openalex Percentile: Top 25%
Advanced Proteomics Techniques and Applications
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