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 intraâtumoral spatial heterogeneity in SCLC is crucial for improving patient outcomes and clinically relevant subtyping. In this study, a spatial whole transcriptomeâwide analysis of 25 SCLC patients at subâhistological resolution using GeoMx Digital Spatial Profiling technology is performed. This analysis deciphered intraâtumoral multiâregional heterogeneity, characterized by distinct molecular profiles, biological functions, immune features, and molecular subtypes within spatially localized histological regions. Connections between different transcriptâdefined intraâtumoral phenotypes and their impact on patient survival and therapeutic response are also established. Finally, a gene signature, termed ITHtyper, based on the prevalence of intraâtumoral heterogeneity levels, which enables patient risk stratification from bulk RNAâseq profiles is identified. The prognostic value of ITHtyper is rigorously validated in independent multicenter patient cohorts. This study introduces a preliminary tumorâcentric, regionally targeted spatial transcriptome resource that sheds light on previously unexplored intraâtumoral spatial heterogeneity in SCLC. These findings hold promise to improve tumor reclassification and facilitate the development of personalized treatments for SCLC patients.