Transcriptomic-Based Microenvironment Classification Reveals Precision Medicine Strategies for Pancreatic Ductal Adenocarcinoma

转录组 免疫疗法 免疫系统 精密医学 胰腺癌 胰腺导管腺癌 肿瘤科 个性化医疗 基因表达谱 肿瘤微环境 腺癌 内科学 生物信息学 医学 生物 免疫学 癌症 病理 基因 基因表达 生物化学
作者
Ben George,Olga Kudryashova,Andrey Kravets,Samih Z Thalji,Subramaniam Malarkannan,Razelle Kurzrock,E. F. Chernyavskaya,Mariia Gusakova,Dmitry Kravchenko,Dmitry Tychinin,Egor V. Savin,Lolita Alekseeva,Anna Butusova,A. Bagaev,Nara Shin,Jessica H. Brown,Isha Sethi,Dandan Wang,Bradley Taylor,Thomas McFall
出处
期刊:Gastroenterology [Elsevier BV]
卷期号:166 (5): 859-871.e3 被引量:10
标识
DOI:10.1053/j.gastro.2024.01.028
摘要

Background The complex tumor microenvironment (TME) of pancreatic ductal adenocarcinoma (PDAC) has hindered the development of reliable predictive biomarkers for targeted therapy and immunomodulatory strategies. A comprehensive characterization of the TME is necessary to advance precision therapeutics in PDAC. Methods A transcriptomic profiling platform for TME classification based on functional gene signatures (Fges) was applied to 14 publicly available PDAC datasets (n = 1,657) and validated in a clinically annotated independent cohort of patients with PDAC (n = 79). Four distinct subtypes were identified using unsupervised clustering and assessed to evaluate predictive and prognostic utility. Results TME classification using transcriptomic profiling identified four biologically distinct subtypes based on their TME immune composition: immune enriched (IE); immune enriched, fibrotic (IE/F); fibrotic (F); and immune depleted (D). The IE and IE/F subtypes demonstrated a more favorable prognosis and potential for response to immunotherapy compared to the F and D subtypes. The majority of lung metastases and liver metastases were subtypes IE and D, respectively, indicating the role of clonal phenotype and immune milieu in developing personalized therapeutic strategies. Additionally, distinct TMEs with potential therapeutic implications were identified in treatment-naive primary tumors compared with tumors that underwent neoadjuvant therapy. Conclusions This novel approach defines a distinct subgroup of PDAC patients that may benefit from immunotherapeutic strategies based on their TME subtype and provides a framework to select patients for prospective clinical trials investigating precision immunotherapy in PDAC. Further, the predictive utility and real-world clinical applicability espoused by this transcriptomic-based TME classification approach will accelerate the advancement of precision medicine in PDAC.
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