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通过二次谐波产生显微镜和质谱法评估高级别浆液性卵巢癌早期前体病变中的胶原蛋白变化

Evaluation of Collagen Alterations in Early Precursor Lesions of High Grade Serous Ovarian Cancer by Second Harmonic Generation Microscopy and Mass Spectrometry.

作者信息

Gant Kristal L, Jambor Alexander N, Li Zihui, Rentchler Eric C, Weisman Paul, Li Lingjun, Patankar Manish S, Campagnola Paul J

机构信息

Department of Obstetrics and Gynecology, University of Wisconsin-Madison, Madison, WI 53706, USA.

Department of Biomedical Engineering, University of Wisconsin-Madison, Madison, WI 53706, USA.

出版信息

Cancers (Basel). 2021 Jun 4;13(11):2794. doi: 10.3390/cancers13112794.

Abstract

The collagen architecture in high grade serous ovarian cancer (HGSOC) is highly remodeled compared to the normal ovary and the fallopian tubes (FT). We previously used Second Harmonic Generation (SHG) microscopy and machine learning to classify the changes in collagen fiber morphology occurring in serous tubal intraepithelial carcinoma (STIC) lesions that are concurrent with HGSOC. We now extend these studies to examine collagen remodeling in pure p53 signatures, STICs and normal regions in tissues that have no concurrent HGSOC. This is an important distinction as high-grade disease can result in distant collagen changes through a field effect mechanism. We trained a linear discriminant model based on SHG texture and image features as a classifier to discriminate the tissue groups. We additionally performed mass spectrometry analysis of normal and HGSOC tissues to associate the differential expression of collagen isoforms with collagen fiber morphology alterations. We quantified the differences in the collagen architecture between normal tissue and the precursors with good classification accuracy. Through proteomic analysis, we identified the downregulation of single α-chains including those for Col I and III, where these results are consistent with our previous SHG-based supramolecular analyses. This work provides new insights into ECM remodeling in early ovarian cancer and suggests the combined use of SHG microscopy and mass spectrometry as a new diagnostic/prognostic approach.

摘要

与正常卵巢和输卵管相比,高级别浆液性卵巢癌(HGSOC)中的胶原蛋白结构发生了高度重塑。我们之前使用二次谐波产生(SHG)显微镜和机器学习对与HGSOC同时发生的浆液性输卵管上皮内癌(STIC)病变中胶原蛋白纤维形态的变化进行分类。我们现在扩展这些研究,以检查在没有并发HGSOC的组织中,纯p53特征、STIC和正常区域的胶原蛋白重塑情况。这是一个重要的区别,因为高级别疾病可通过场效应机制导致远处的胶原蛋白变化。我们基于SHG纹理和图像特征训练了一个线性判别模型作为分类器,以区分组织组。我们还对正常组织和HGSOC组织进行了质谱分析,将胶原蛋白亚型的差异表达与胶原蛋白纤维形态改变相关联。我们以良好的分类准确性量化了正常组织与前体之间胶原蛋白结构的差异。通过蛋白质组学分析,我们确定了包括I型和III型胶原蛋白在内的单个α链的下调,这些结果与我们之前基于SHG的超分子分析一致。这项工作为早期卵巢癌的细胞外基质重塑提供了新的见解,并建议将SHG显微镜和质谱联用作为一种新的诊断/预后方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ed9a/8200041/1bd58417110c/cancers-13-02794-g001.jpg

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