LaBahn Pancreatic Cancer Program, Division of Hematology and Oncology, Medical College of Wisconsin (MCW), Milwaukee, Wisconsin.
BostonGene Corporation, Waltham, Massachusetts.
Gastroenterology. 2024 May;166(5):859-871.e3. doi: 10.1053/j.gastro.2024.01.028. Epub 2024 Jan 25.
BACKGROUND & AIMS: 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.
A transcriptomic profiling platform for TME classification based on functional gene signatures was applied to 14 publicly available PDAC datasets (n = 1657) 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.
TME classification using transcriptomic profiling identified 4 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 with the F and D subtypes. Most 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. In addition, distinct TMEs with potential therapeutic implications were identified in treatment-naive primary tumors compared with tumors that underwent neoadjuvant therapy.
This novel approach defines a distinct subgroup of PADC 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.
胰腺导管腺癌（PDAC）复杂的肿瘤微环境（TME）阻碍了针对靶向治疗和免疫调节策略的可靠预测生物标志物的发展。全面描述 TME 对于推进 PDAC 的精准治疗是必要的。
应用基于功能基因特征的 TME 分类转录组分析平台，对 14 个公开的 PDAC 数据集（n=1657）进行分析，并在具有 PDAC 临床注释的独立患者队列（n=79）中进行验证。使用无监督聚类识别出四个不同的亚型，并进行评估以评估预测和预后效用。
使用转录组分析进行 TME 分类，根据其 TME 免疫组成，识别出 4 种具有生物学差异的亚型：免疫富集（IE）；免疫富集伴纤维化（IE/F）；纤维化（F）；和免疫耗竭（D）。与 F 和 D 亚型相比，IE 和 IE/F 亚型表现出更有利的预后和对免疫治疗的潜在反应能力。大多数肺转移和肝转移分别为 IE 和 D 亚型，表明克隆表型和免疫微环境在制定个性化治疗策略中的作用。此外，与接受新辅助治疗的肿瘤相比，在未经治疗的原发性肿瘤中发现了具有潜在治疗意义的不同 TME。
这种新方法定义了一个独特的 PDAC 患者亚组，可能受益于基于其 TME 亚型的免疫治疗策略，并为选择患者参加前瞻性临床试验提供了框架，以研究 PDAC 中的精准免疫治疗。此外，这种基于转录组的 TME 分类方法的预测效用和实际临床应用将加速 PDAC 精准医学的发展。
