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Proteomic landscape of multi-layered breast cancer internal tumor heterogeneity

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NIAID Data Ecosystem2026-05-02 收录
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https://www.omicsdi.org/dataset/pride/PXD024190
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Breast cancer often presents with a high degree of intratumor heterogeneity, resulting in therapy resistance and tumor relapse. Here, we investigated spatial intratumor heterogeneity by integrating histopathological analyses and mass spectrometry-based proteomics. Using multilayered heterogeneity scoring, we identified the proteomic determinants of tumor heterogeneity and associated them with clinical and functional tumor characteristics. We found that molecular subtypes present lower heterogeneity with higher tumor grade, and demonstrate distinct subtype-specific profiles. However, even homogeneous tumors present high degrees of proteomic diversity, associated with proliferative and immune processes. Interestingly, tumor regions from molecularly-heterogeneous tumors, irrespective of their molecular subtype showed high proteomic similarity with enriched glutathione metabolism and proline biosynthesis pathways. Taken together the proteomic analyses revealed the association of internal tumor heterogeneity with cancer progression and immune selection, which can serve as a platform to decipher mechanisms underlying cancer evolution and therapy resistance.

乳腺癌通常具有高度的瘤内异质性(intratumor heterogeneity),这往往会导致治疗耐药与肿瘤复发。本研究通过整合组织病理学分析与基于质谱的蛋白质组学(mass spectrometry-based proteomics),对空间维度下的瘤内异质性展开探究。研究采用多层异质性评分方法,鉴定出肿瘤异质性的蛋白质组学决定因素,并将其与肿瘤的临床及功能特征建立关联。我们发现,肿瘤分级越高的分子亚型(molecular subtypes),其异质性越低,且各亚型展现出独特的亚型特异性特征谱。然而,即便为均质的肿瘤,仍存在高度的蛋白质组学多样性,该多样性与肿瘤增殖及免疫过程密切相关。值得注意的是,源自分子异质性肿瘤的不同区域,无论其所属的分子亚型为何,均表现出高度的蛋白质组学相似性,且富集了谷胱甘肽代谢(glutathione metabolism)与脯氨酸生物合成通路(proline biosynthesis pathways)。综合上述蛋白质组学分析结果,本研究揭示了肿瘤内部异质性与癌症进展及免疫选择之间的关联,该研究可作为解析癌症演化与治疗耐药机制的研究平台。
创建时间:
2025-08-10
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