Although uterine serous carcinoma (USC) represents a small proportion of all uterine cancer cases, patients with this aggressive subtype typically have high rates of chemotherapy resistance and disease recurrence that collectively result in a disproportionately high death rate. The goal of this study was to provide a deeper view of the tumor microenvironment of this poorly characterized uterine cancer variant through multi-region microsampling and quantitative proteomics. Tumor epithelium, tumor-involved stroma, and whole “bulk” tissue were harvested by laser microdissection (LMD) from spatially resolved levels from nine USC patient tumor specimens and underwent proteomic analysis by mass spectrometry and reverse phase protein arrays, as well as transcriptomic analysis by RNA-sequencing for one patient’s tumor. LMD enriched cell subpopulations demonstrated varying degrees of relatedness, indicating substantial intratumor heterogeneity emphasizing the necessity for enrichment of cellular subpopulations prior to molecular analysis. Known prognostic biomarkers were quantified with stable levels in both LMD enriched tumor and stroma, which were shown to be highly variable in bulk tissue. These USC data were further used in a comparative analysis with a data generated from another serous gynecologic malignancy, high grade serous ovarian carcinoma, and have been added to our publicly available data analysis tool, the Heterogeneity Analysis Portal ( https://lmdomics.org/ ). Here we identified extensive three-dimensional heterogeneity within the USC tumor microenvironment, with disease-relevant biomarkers present in both the tumor and the stroma. These data underscore the critical need for upfront enrichment of cellular subpopulations from tissue specimens for spatial proteogenomic analysis.

中文翻译：

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通过多区域微采样绘制子宫浆液性癌三维肿瘤内蛋白质组异质性

尽管子宫浆液性癌 (USC) 在所有子宫癌病例中只占一小部分，但这种侵袭性亚型的患者通常具有较高的化疗耐药率和疾病复发率，这共同导致了不成比例的高死亡率。本研究的目的是通过多区域微采样和定量蛋白质组学，更深入地了解这种特征不明的子宫癌变体的肿瘤微环境。通过激光显微切割 (LMD) 从 9 名南加州大学患者肿瘤标本的空间分辨水平上收获肿瘤上皮、肿瘤相关基质和整个“大块”组织，并通过质谱和反相蛋白阵列进行蛋白质组分析以及转录组分析通过对一名患者的肿瘤进行 RNA 测序。LMD 富集的细胞亚群表现出不同程度的相关性，表明肿瘤内存在显着的异质性，强调了在分子分析之前富集细胞亚群的必要性。已知的预后生物标志物在富含 LMD 的肿瘤和基质中均以稳定水平进行量化，而这些标志物在大块组织中表现出高度可变性。这些 USC 数据进一步用于与另一种浆液性妇科恶性肿瘤（高级别浆液性卵巢癌）生成的数据进行比较分析，并已添加到我们公开的数据分析工具异质性分析门户 (https://lmdomics.org) / ）。在这里，我们发现了南加州大学肿瘤微环境中广泛的三维异质性，肿瘤和基质中都存在与疾病相关的生物标志物。这些数据强调了从组织样本中预先富集细胞亚群以进行空间蛋白质组分析的迫切需要。