Ge Jiachen, Cai Jianping, Zhang Gaolei, Li Deyu, Tao Lianyuan
Department of Hepatobiliary Surgery, Henan Provincial People's Hospital, People's Hospital of Zhengzhou University, Zhengzhou, 450003, People's Republic of China.
Laboratory of Gene Regulation and Signal Transduction, Departments of Pharmacology and Pathology, School of Medicine, University of California, San Diego, La Jolla, CA, USA.
J Transl Med. 2025 Jul 4;23(1):741. doi: 10.1186/s12967-025-06711-z.
Pancreatic cancer (PC) represents a highly heterogeneous malignancy with poor prognosis, where precise molecular subtyping facilitates comprehensive understanding of disease progression.
Transcriptomic, methylation, and mutational data from 168 PC samples were integrated. The molecular subtypes were established and validated across 13 independent cohorts utilizing ten distinct classification methods. Prognostic genes were identified to construct predictive models through various machine learning approaches. Following the identification of A2ML1 as a key gene, its expression profile was detected using RT-qPCR, western blotting, and immunohistochemistry. We subsequently conducted functional experiments to elucidate the mechanism of A2ML1 in promoting PC progression.
Through multi-omics integration, we classified PC into two molecular subtypes with distinct prognostic outcomes. Pathway enrichment analysis revealed subtype-specific characteristics, subsequently validated in external cohorts. Using 23 prognostic genes, we developed and validated a prognostic signature through 101 machine learning algorithms and their combinations, with ridge regression demonstrating optimal performance. This signature demonstrated superior accuracy compared to multiple published signatures. The risk scores showed significant correlations with drug sensitivity, clinical characteristics, and patient outcomes. We further validated that A2ML1 expression was significantly elevated in PC tissues compared to normal counterparts. A2ML1 promoted PC progression through downregulation of LZTR1 expression and subsequent activation of the KRAS/MAPK pathway, ultimately driving epithelial-mesenchymal transition (EMT).
In this study, we uncovered molecular basal-like subtype of PC and developed a prognostic signature using ridge regression. A2ML1 was identified as a crucial regulator of EMT in PC progression.
胰腺癌（PC）是一种高度异质性的恶性肿瘤，预后较差，精确的分子亚型划分有助于全面了解疾病进展。
整合了168份PC样本的转录组、甲基化和突变数据。利用十种不同的分类方法在13个独立队列中建立并验证了分子亚型。通过各种机器学习方法鉴定预后基因以构建预测模型。在将A2ML1鉴定为关键基因后，使用RT-qPCR、蛋白质免疫印迹和免疫组织化学检测其表达谱。随后我们进行了功能实验以阐明A2ML1促进PC进展的机制。
通过多组学整合，我们将PC分为两种具有不同预后结果的分子亚型。通路富集分析揭示了亚型特异性特征，随后在外部队列中得到验证。利用23个预后基因，我们通过101种机器学习算法及其组合开发并验证了一种预后特征，其中岭回归表现最佳。与多个已发表的特征相比，该特征显示出更高的准确性。风险评分与药物敏感性、临床特征和患者预后显著相关。我们进一步验证了与正常组织相比，A2ML1在PC组织中的表达显著升高。A2ML1通过下调LZTR1表达并随后激活KRAS/MAPK通路促进PC进展，最终驱动上皮-间质转化（EMT）。
在本研究中，我们发现了PC的分子基底样亚型，并使用岭回归开发了一种预后特征。A2ML1被确定为PC进展中EMT的关键调节因子。
