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.
Spatial Transcriptome-Wide Profiling of Small Cell Lung Cancer Reveals Intra-Tumoral Molecular and Subtype Heterogeneity.
小细胞肺癌的空间转录组分析揭示了肿瘤内分子和亚型异质性
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作者:Zhang Zicheng, Sun Xujie, Liu Yutao, Zhang Yibo, Yang Zijian, Dong Jiyan, Wang Nan, Ying Jianming, Zhou Meng, Yang Lin
| 期刊: | Advanced Science | 影响因子: | 14.100 |
| 时间: | 2024 | 起止号: | 2024 Aug;11(31):e2402716 |
| doi: | 10.1002/advs.202402716 | 研究方向: | 肿瘤 |
| 疾病类型: | 肺癌 | ||
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