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

IF 12.3 1区 生物学 Q1 Agricultural and Biological Sciences
Dong Ki Lee, Min Hwan Kim, Yumi Hwang, Seul-Gi Kim, Won-Ji Ryu, Geon-Uk Kim, Hyun Myoung Yun, Shinyoung Park, Jeong Dong Lee, Hyun Ju Han, Gun Min Kim, Kyung-Hee Kim, Jong Bae Park, Min Jung Kim, Ja Seung Koo, Jee Ye Kim, Hyung Seok Park, Seung Il Kim, Heon Yung Gee, Seho Park, Joohyuk Sohn
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引用次数: 0

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.

三阴性乳腺癌患者化疗耐药的蛋白质基因组解码。
背景:综合蛋白质基因组生物标志物在预测三阴性乳腺癌化疗反应中的临床应用仍未得到充分探索。我们前瞻性地分析了50例接受蒽环类和紫杉烷为基础的新辅助化疗的II-III期TNBC患者的基线和治疗后肿瘤样本,整合了全外显子组测序、RNA测序、全局蛋白质组学和磷蛋白质组学。结果:非负矩阵因子聚类鉴定出5种蛋白质基因组亚型。免疫富集亚型表现出最高的病理完全缓解率(55.6%),而在异种代谢或上皮-间质转化亚型中没有观察到病理完全缓解。免疫相关通路在病理完全应答的肿瘤中丰富,而上皮-间质转化通路在非病理完全应答的肿瘤中丰富。在蛋白质组学水平上,雌激素反应通路在非病理性完全反应肿瘤中选择性富集,与免疫激活呈负相关。翻译后修饰和体外分析表明,雌激素相关的GRK2激活有助于化疗耐药。ITGB8拷贝数丢失与较高的病理性完全缓解率和免疫激活相关,而免疫调节亚型的非病理性完全缓解肿瘤显示AKR1C2和ABCA13的表达增加。基线和治疗后肿瘤的比较显示,残留疾病中AURKB通路激活,Aurora B激酶抑制与紫杉醇协同作用。结合这些生物标志物的预测模型在预测反应方面优于基于rna的模型。结论:综合蛋白质基因组分析能够预测三阴性乳腺癌的化疗耐药性,并确定可操作的生物标志物,为推进个性化治疗策略提供框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Genome Biology
Genome Biology BIOTECHNOLOGY & APPLIED MICROBIOLOGY-GENETICS & HEREDITY
CiteScore
25.50
自引率
3.30%
发文量
0
审稿时长
14 weeks
期刊介绍: Genome Biology is a leading research journal that focuses on the study of biology and biomedicine from a genomic and post-genomic standpoint. The journal consistently publishes outstanding research across various areas within these fields. With an impressive impact factor of 12.3 (2022), Genome Biology has earned its place as the 3rd highest-ranked research journal in the Genetics and Heredity category, according to Thomson Reuters. Additionally, it is ranked 2nd among research journals in the Biotechnology and Applied Microbiology category. It is important to note that Genome Biology is the top-ranking open access journal in this category. In summary, Genome Biology sets a high standard for scientific publications in the field, showcasing cutting-edge research and earning recognition among its peers.
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