State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Dongfengdong Road 651, Guangzhou 510060, China.
Pharm-X Center, Engineering Research Center of Cell & Therapeutic Antibody, Ministry of Education, School of Pharmacy, Shanghai Jiao Tong University, Dongchuan Road 800, Shanghai 200240, China.
Int J Mol Sci. 2022 Apr 26;23(9):4792. doi: 10.3390/ijms23094792.
Pancreatic cancer is a highly fatal disease and an increasing common cause of cancer mortality. Mounting evidence now indicates that molecular heterogeneity in pancreatic cancer significantly impacts its clinical features. However, the dynamic nature of gene expression pattern makes it difficult to rely solely on gene expression alterations to estimate disease status. By contrast, biological networks tend to be more stable over time under different situations. In this study, we used a gene interaction network from a new point of view to explore the subtypes of pancreatic cancer based on individual-specific edge perturbations calculated by relative gene expression value. Our study shows that pancreatic cancer patients from the TCGA database could be separated into four subtypes based on gene interaction perturbations at the individual level. The new network-based subtypes of pancreatic cancer exhibited substantial heterogeneity in many aspects, including prognosis, phenotypic traits, genetic mutations, the abundance of infiltrating immune cell, and predictive therapeutic efficacy (chemosensitivity and immunotherapy efficacy). The new network-based subtypes were closely related to previous reported molecular subtypes of pancreatic cancer. This work helps us to better understand the heterogeneity and mechanisms of pancreatic cancer from a network perspective.
胰腺癌是一种高度致命的疾病，也是癌症死亡率不断上升的常见原因。越来越多的证据表明，胰腺癌中的分子异质性显著影响其临床特征。然而，基因表达模式的动态性质使得仅依赖基因表达改变来估计疾病状态变得困难。相比之下，生物网络在不同情况下往往更稳定。在这项研究中，我们从一个新的角度使用基因相互作用网络，基于通过相对基因表达值计算的个体特异性边缘扰动，来探索基于个体的胰腺癌亚型。我们的研究表明，基于个体水平基因相互作用扰动，来自 TCGA 数据库的胰腺癌患者可以分为四个亚型。基于基因相互作用的胰腺癌新型网络亚型在许多方面表现出显著的异质性，包括预后、表型特征、遗传突变、浸润免疫细胞的丰度以及预测治疗效果（化疗敏感性和免疫治疗效果）。新的基于网络的亚型与先前报道的胰腺癌分子亚型密切相关。这项工作有助于我们从网络角度更好地理解胰腺癌的异质性和机制。
