Bai Kaisong, Zhao Tong, Li Yilong, Li Xinjian, Zhang Zhantian, Du Zuchao, Wang Zimin, Xu Yan, Sun Bei, Bai Xuewei
Department of General Surgery, The First Affiliated Hospital of Harbin Medical University, Harbin, China.
Key Laboratory of Hepatosplenic Surgery, Ministry of Education, Harbin, China.
Front Genet. 2021 Sep 9;12:747270. doi: 10.3389/fgene.2021.747270. eCollection 2021.
Pancreatic adenocarcinoma (PAAD) is one of the deadliest malignancies and mortality for PAAD have remained increasing under the conditions of substantial improvements in mortality for other major cancers. Although multiple of studies exists on PAAD, few studies have dissected the oncogenic mechanisms of PAAD based on genomic variation. In this study, we integrated somatic mutation data and gene expression profiles obtained by high-throughput sequencing to characterize the pathogenesis of PAAD. The mutation profile containing 182 samples with 25,470 somatic mutations was obtained from The Cancer Genome Atlas (TCGA). The mutation landscape was generated and somatic mutations in PAAD were found to have preference for mutation location. The combination of mutation matrix and gene expression profiles identified 31 driver genes that were closely associated with tumor cell invasion and apoptosis. Co-expression networks were constructed based on 461 genes significantly associated with driver genes and the hub gene FAM133A in the network was identified to be associated with tumor metastasis. Further, the cascade relationship of somatic mutation-Long non-coding RNA (lncRNA)-microRNA (miRNA) was constructed to reveal a new mechanism for the involvement of mutations in post-transcriptional regulation. We have also identified prognostic markers that are significantly associated with overall survival (OS) of PAAD patients and constructed a risk score model to identify patients' survival risk. In summary, our study revealed the pathogenic mechanisms and prognostic markers of PAAD providing theoretical support for the development of precision medicine.
胰腺腺癌（PAAD）是最致命的恶性肿瘤之一，在其他主要癌症死亡率大幅改善的情况下，PAAD的死亡率仍在上升。尽管对PAAD已有多项研究，但基于基因组变异剖析PAAD致癌机制的研究却很少。在本研究中，我们整合了通过高通量测序获得的体细胞突变数据和基因表达谱，以表征PAAD的发病机制。从癌症基因组图谱（TCGA）获得了包含182个样本、25470个体细胞突变的突变谱。生成了突变图谱，发现PAAD中的体细胞突变对突变位置有偏好。突变矩阵与基因表达谱的结合确定了31个与肿瘤细胞侵袭和凋亡密切相关的驱动基因。基于与驱动基因显著相关的461个基因构建了共表达网络，并确定网络中的枢纽基因FAM133A与肿瘤转移相关。此外，构建了体细胞突变-长链非编码RNA（lncRNA）-微小RNA（miRNA）的级联关系，以揭示突变参与转录后调控的新机制。我们还确定了与PAAD患者总生存期（OS）显著相关的预后标志物，并构建了风险评分模型以识别患者的生存风险。总之，我们的研究揭示了PAAD的致病机制和预后标志物，为精准医学的发展提供了理论支持。
