Multi-dimensional characterization of immunological profiles in small cell lung cancer uncovers clinically relevant immune subtypes with distinct prognoses and therapeutic vulnerabilities

免疫系统 医学 亚型 肿瘤科 疾病 CXCL9型 肺癌 免疫分型 免疫学 趋化因子 内科学 抗原 趋化因子受体 计算机科学 程序设计语言
作者
Lin Yang,Zicheng Zhang,Jiyan Dong,Yibo Zhang,Zijian Yang,Yiying Guo,Xujie Sun,Junling Li,Puyuan Xing,Jianming Ying,Meng Zhou
出处
期刊:Pharmacological Research [Elsevier BV]
卷期号:194: 106844-106844 被引量:18
标识
DOI:10.1016/j.phrs.2023.106844
摘要

Small-cell lung cancer (SCLC) is generally considered a 'homogenous' disease, with little documented inter-tumor heterogeneity in treatment guidance or prognosis evaluation. The precise identification of clinically relevant molecular subtypes remains incomplete and their translation into clinical practice is limited. In this retrospective cohort study, we comprehensively characterized the immune microenvironment in SCLC by integrating transcriptional and protein profiling of formalin-fixation-and-paraffin-embedded (FFPE) samples from 29 patients. We identified two distinct disease subtypes: immune-enriched (IE-subtype) and immune-deprived (ID-subtype), displaying heterogeneity in immunological, biological, and clinical features. The IE-subtype was characterized by abundant immune infiltrate and elevated levels of interferon-alpha/gamma (IFNα/IFNγ) and inflammatory response, while the ID-subtype featured a complete lack of immune infiltration and a more proliferative phenotype. These two immune subtypes are associated with clinical benefits in SCLC patients treated with adjuvant therapy, with the IE-subtype exhibiting a more favorable response leading to improved survival and reduced disease recurrence risk. Additionally, we identified and validated a personalized prognosticator of immunophenotyping, the CCL5/CXCL9 chemokine index (CCI), using machine learning. The CCI demonstrated superior predictive abilities for prognosis and clinical benefits in SCLC patients, validated in our institute immunohistochemistry cohort and multicenter bulk transcriptomic data cohorts. In conclusion, our study provides a comprehensive and multi-dimensional characterization of the immune architecture of SCLC using clinical FFPE samples and proposes a new immune subtyping conceptual framework enabling risk stratification and the appropriate selection of individualized therapy.
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