2023 World Conference on Lung Cancer (Posters)-P2.13. Spatially Resolved Transcriptomics deciphers Inter- and Intra-Tumor Heterogeneity of Small Cell Lung Cancer

P2.13. Spatially Resolved Transcriptomics deciphers Inter- and Intra-Tumor Heterogeneity of Small Cell Lung Cancer - PDF(Abstract)

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Small cell lung cancer (SCLC) is a highly heterogeneous cancer with aggressive progression and poor prognosis. In this study, researchers aimed to define and decipher the inter- and intra-tumor heterogeneity (ITH) of SCLC and its clinical relevance. They used digital spatial profiling (DSP) to quantify the whole transcriptomes of SCLC tumors and calculated their ITH scores using the Deviating gene Expression Profiling Tumor Heterogeneity algorithm (DEPTH) at the RNA level. They also evaluated immune infiltration from RNA expression data using deconvoluted algorithms and validated it with immunochemistry. <br /><br />The study found that SCLC tumors could be classified into two distinct subtypes: high heterogeneity-complex (HC) and medium-low heterogeneity (ML). These subtypes showed significant variations in CD8 T cell infiltration and multiple biological properties. They also had significant differences in overall survival and disease-free survival, with MLs having a good prognosis and HCs showing a poor prognosis. <br /><br />The researchers developed a machine learning model called THIM to determine tumor heterogeneity and facilitate prognostic stratification. This model accurately predicted the therapeutic response and survival of SCLC patients. It was validated across multiple cohorts of SCLC patients. <br /><br />Overall, this study provides insight into the inter- and intra-tumor heterogeneity of SCLC and proposes a new heterogeneity-oriented subtyping framework for improving risk stratification and molecular classification. This framework has the potential to guide postoperative management of limited-stage SCLC patients and assess immunotherapy efficacy in advanced stage patients.

Asset Subtitle

xujie Sun

Meta Tag

Speaker xujie Sun

Topic SCLC & Neuroendocrine Tumors: Biomarkers & Radiomics

Keywords

Small cell lung cancer

SCLC

heterogeneity

aggressive progression

poor prognosis

digital spatial profiling

whole transcriptomes

ITH scores

immune infiltration

machine learning model