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蛋白质基因组学分析剖析了具有预后相关性的早发性乳腺癌患者。

Proteogenomic analysis dissects early-onset breast cancer patients with prognostic relevance.

作者信息

Yoon Kyong-Ah, Kim Youngwook, Jung So-Youn, Ryu Jin-Sun, Kim Kyung-Hee, Lee Eun-Gyeong, Chae Heejung, Kwon Youngmee, Kim Jaegil, Park Jong Bae, Kong Sun-Young

机构信息

Department of Biochemistry, College of Veterinary Medicine, Konkuk University, Seoul, Korea.

Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea.

出版信息

Exp Mol Med. 2024 Nov;56(11):2382-2394. doi: 10.1038/s12276-024-01332-w. Epub 2024 Nov 1.

Abstract

Early-onset breast cancer is known for its aggressive clinical characteristics and high prevalence in East Asian countries, but a comprehensive understanding of its molecular features is still lacking. In this study, we conducted a proteogenomic analysis of 126 treatment-naïve primary tumor tissues obtained from Korean patients with young breast cancer (YBC) aged ≤40 years. By integrating genomic, transcriptomic, and proteomic data, we identified five distinct functional subgroups that accurately represented the clinical characteristics and biological behaviors of patients with YBC. Our integrated approach could be used to determine the proteogenomic status of HER2, enhancing its clinical significance and prognostic value. Furthermore, we present a proteome-based homologous recombination deficiency (HRD) analysis that has the potential to overcome the limitations of conventional genomic HRD tests, facilitating the identification of new patient groups requiring targeted HR deficiency treatments. Additionally, we demonstrated that protein-RNA correlations can be used to predict the late recurrence of hormone receptor-positive breast cancer. Within each molecular subtype of breast cancer, we identified functionally significant protein groups whose differential abundance was closely correlated with the clinical progression of breast cancer. Furthermore, we derived a recurrence predictive index capable of predicting late recurrence, specifically in luminal subtypes, which plays a crucial role in guiding decisions on treatment durations for YBC patients. These findings improve the stratification and clinical implications for patients with YBC by contributing to the optimal adjuvant treatment and duration for favorable clinical outcomes.

摘要

早发性乳腺癌以其侵袭性临床特征和在东亚国家的高患病率而闻名,但对其分子特征仍缺乏全面了解。在本研究中,我们对126例来自年龄≤40岁的韩国年轻乳腺癌(YBC)患者的未经治疗的原发性肿瘤组织进行了蛋白质基因组分析。通过整合基因组、转录组和蛋白质组数据,我们确定了五个不同的功能亚组,它们准确地代表了YBC患者的临床特征和生物学行为。我们的综合方法可用于确定HER2的蛋白质基因组状态,增强其临床意义和预后价值。此外,我们提出了一种基于蛋白质组的同源重组缺陷(HRD)分析方法,该方法有可能克服传统基因组HRD检测的局限性,有助于识别需要靶向HR缺陷治疗的新患者群体。此外,我们证明蛋白质-RNA相关性可用于预测激素受体阳性乳腺癌的晚期复发。在乳腺癌的每个分子亚型中,我们确定了功能上重要的蛋白质组,其丰度差异与乳腺癌的临床进展密切相关。此外,我们得出了一个复发预测指数,能够预测晚期复发,特别是在管腔亚型中,这在指导YBC患者的治疗持续时间决策中起着关键作用。这些发现通过有助于优化辅助治疗和持续时间以获得良好的临床结果,改善了YBC患者的分层和临床意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9a1a/11612404/6e0500841252/12276_2024_1332_Fig1_HTML.jpg

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