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首页> 外文期刊>EBioMedicine >Generation of in situ sequencing based OncoMaps to spatially resolve gene expression profiles of diagnostic and prognostic markers in breast cancer
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Generation of in situ sequencing based OncoMaps to spatially resolve gene expression profiles of diagnostic and prognostic markers in breast cancer

机译：基于OncoMaps的原位测序可在空间上解析乳腺癌诊断和预后标志物的基因表达谱

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Background Gene expression analysis of breast cancer largely relies on homogenized tissue samples. Due to the high degree of cellular and molecular heterogeneity of tumor tissues, bulk tissue-based analytical approaches can only provide very limited system-level information about different signaling mechanisms and cellular interactions within the complex tissue context. Methods We describe an analytical approach using in situ sequencing (ISS), enabling highly multiplexed, spatially and morphologically resolved gene expression profiling. Ninety-one genes including prognostic and predictive marker profiles, as well as genes involved in specific cellular pathways were mapped within whole breast cancer tissue sections, covering luminal A/B-like, HER2-positive and triple negative tumors. Finally, all these features were combined and assembled into a molecular-morphological OncoMap for each tumor tissue. Findings Our in situ approach spatially revealed intratumoral heterogeneity with regard to tumor subtype as well as to the OncotypeDX recurrence score and even uncovered areas of minor cellular subpopulations. Since ISS-resolved molecular profiles are linked to their histological context, a deeper analysis of the core and periphery of tumor foci enabled identification of specific gene expression patterns associated with these morphologically relevant regions. Interpretation ISS generated OncoMaps represent useful tools to extend our general understanding of the biological processes behind tumor progression and can further support the identification of novel therapeutical targets as well as refine tumor diagnostics. Fund Swedish Cancerfonden, UCAN, Vetenskapsr?det, Cancer Genomics Netherlands, Iris, Stig och Gerry Castenb?cks Stiftelse, BRECT, PCM Program, King Gustaf V Jubilee Fund, BRO, KI and Stockholm County Council, Alice Wallenberg Foundation.
机译：背景技术乳腺癌的基因表达分析主要依赖于均质化的组织样品。由于肿瘤组织在细胞和分子方面的高度异质性，基于大组织的分析方法只能提供有关复杂组织环境中不同信号传导机制和细胞相互作用的非常有限的系统级信息。方法我们描述了一种使用原位测序（ISS）的分析方法，可实现高度复用的，在空间和形态上解析的基因表达谱。在整个乳腺癌组织切片中标出了包括预后和预测性标志物特征在内的91个基因以及参与特定细胞途径的基因，涵盖了管腔A / B样，HER2阳性和三阴性肿瘤。最后，将所有这些特征组合并组装到每个肿瘤组织的分子形态OncoMap中。研究结果我们的原位研究方法在空间上揭示了肿瘤内亚型，肿瘤亚型以及OncotypeDX复发评分甚至未发现的次要细胞亚群的肿瘤内异质性。由于ISS解析的分子图谱与其组织学背景相关，因此对肿瘤灶核心和外围的更深入分析使得能够鉴定与这些形态相关区域相关的特定基因表达模式。解释ISS生成的OncoMaps代表了有用的工具，可以扩展我们对肿瘤进展背后的生物学过程的一般理解，并且可以进一步支持鉴定新的治疗靶标并完善肿瘤诊断。瑞典瑞典癌症基金会，UCAN，Vetenskapsr？det，荷兰癌症基因组学，艾里斯，斯蒂格·盖里·卡斯滕贝克·史蒂芬瑟基金会，BRECT，PCM计划，古斯塔夫五世国王纪念基金会，BRO，KI和斯德哥尔摩县议会，爱丽丝·沃伦伯格基金会。

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