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.
Authors
- Hyun Myoung Yun
- Jee Ye Kim (ORCID: https://orcid.org/0000-0003-3936-4410)
- Won‐Ji Ryu (ORCID: https://orcid.org/0000-0002-6163-1354)
- Ja Seung Koo (ORCID: https://orcid.org/0000-0003-4546-4709)
- Geon-Uk Kim (ORCID: https://orcid.org/0000-0003-2983-3252)
- Seul‐Gi Kim (ORCID: https://orcid.org/0000-0003-1641-4059)
- Yumi Hwang
- Shinyoung Park (ORCID: https://orcid.org/0009-0006-3381-5910)
- 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
Institutions
- Kookmin University (KR)
- Yonsei University (KR)
- Kyung Hee University (KR)
- CHA University Bundang Medical Center (KR)
- Yonsei University Health System (KR)
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
Funders
- 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