School of Biomedical Engineering, National Clinical Research Center for Ocular Diseases, Eye Hospital, Wenzhou Medical University, Wenzhou, 325027, P. R. China.
Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100021, P. R. China.
Adv Sci (Weinh). 2024 Aug;11(31):e2402716. doi: 10.1002/advs.202402716. Epub 2024 Jun 19.
Small cell lung cancer (SCLC) is a highly aggressive malignancy characterized by rapid growth and early metastasis and is susceptible to treatment resistance and recurrence. Understanding the intra-tumoral spatial heterogeneity in SCLC is crucial for improving patient outcomes and clinically relevant subtyping. In this study, a spatial whole transcriptome-wide analysis of 25 SCLC patients at sub-histological resolution using GeoMx Digital Spatial Profiling technology is performed. This analysis deciphered intra-tumoral multi-regional heterogeneity, characterized by distinct molecular profiles, biological functions, immune features, and molecular subtypes within spatially localized histological regions. Connections between different transcript-defined intra-tumoral phenotypes and their impact on patient survival and therapeutic response are also established. Finally, a gene signature, termed ITHtyper, based on the prevalence of intra-tumoral heterogeneity levels, which enables patient risk stratification from bulk RNA-seq profiles is identified. The prognostic value of ITHtyper is rigorously validated in independent multicenter patient cohorts. This study introduces a preliminary tumor-centric, regionally targeted spatial transcriptome resource that sheds light on previously unexplored intra-tumoral spatial heterogeneity in SCLC. These findings hold promise to improve tumor reclassification and facilitate the development of personalized treatments for SCLC patients.
小细胞肺癌(SCLC)是一种高度侵袭性的恶性肿瘤,其特征为快速生长和早期转移,并且容易产生治疗抵抗和复发。了解 SCLC 中的肿瘤内空间异质性对于改善患者预后和进行临床相关的亚型分类至关重要。在这项研究中,使用 GeoMx 数字空间解析技术,对 25 名 SCLC 患者进行了亚组织学分辨率的空间全转录组分析。该分析揭示了肿瘤内多区域异质性,其特征为不同的分子谱、生物学功能、免疫特征和分子亚型在空间定位的组织学区域中存在。还建立了不同转录定义的肿瘤内表型之间的联系及其对患者生存和治疗反应的影响。最后,确定了一种基于肿瘤内异质性水平普遍性的基因特征,称为 ITHtyper,它可以根据批量 RNA-seq 图谱对患者进行风险分层。ITHtyper 的预后价值在独立的多中心患者队列中得到了严格验证。本研究介绍了一种初步的以肿瘤为中心、区域性靶向的空间转录组资源,揭示了之前未被探索的 SCLC 肿瘤内空间异质性。这些发现有望改善肿瘤重新分类,并促进为 SCLC 患者制定个性化治疗方案。