Laboratory of Theoretical Biophysics, School of Physical Science and Technology, Inner Mongolia University, Hohhot 010021, China.
Laboratory of Theoretical Biophysics, School of Physical Science and Technology, Inner Mongolia University, Hohhot 010021, China; The State Key Laboratory of Reproductive Regulation and Breeding of Grassland Livestock, Inner Mongolia University, Hohhot 010070, China.
Biochim Biophys Acta Gene Regul Mech. 2022 Aug;1865(6):194841. doi: 10.1016/j.bbagrm.2022.194841. Epub 2022 Jul 5.
Abnormal DNA methylation can alter the gene expression to promote or inhibit tumorigenesis in colon adenocarcinoma (COAD). However, the finding important genes and key sites of abnormal DNA methylation which result in the occurrence of COAD is still an eventful task. Here, we studied the effects of DNA methylation in the 12 types of genomic features on the changes of gene expression in COAD, the 10 important COAD-related genes and the key abnormal DNA methylation sites were identified. The effects of important genes on the prognosis were verified by survival analysis. Moreover, it was shown that the important genes were participated in cancer pathways and were hub genes in a co-expression network. Based on the DNA methylation levels in the ten sites, the least diversity increment algorithm for predicting tumor tissues and normal tissues in seventeen cancer types are proposed. The better results are obtained in jackknife test. For example, the predictive accuracies are 94.17 %, 91.28 %, 89.04 % and 88.89 %, respectively, for COAD, rectum adenocarcinoma, pancreatic adenocarcinoma and cholangiocarcinoma. Finally, by computing enrichment score of infiltrating immunocytes and the activity of immune pathways, we found that the genes are highly correlated with immune microenvironment.
异常的 DNA 甲基化可以改变基因表达，促进或抑制结肠腺癌 (COAD) 的肿瘤发生。然而，发现导致 COAD 发生的重要基因和异常 DNA 甲基化的关键位点仍然是一项艰巨的任务。在这里，我们研究了 DNA 甲基化在 12 种基因组特征上对 COAD 中基因表达变化的影响，确定了 10 个重要的 COAD 相关基因和关键的异常 DNA 甲基化位点。通过生存分析验证了重要基因对预后的影响。此外，结果表明，这些重要基因参与了癌症通路，并在共表达网络中是枢纽基因。基于这 10 个位点的 DNA 甲基化水平，提出了一种用于预测 17 种癌症类型中肿瘤组织和正常组织的最小多样性增量算法。在 jackknife 测试中获得了更好的结果。例如，对于 COAD、直肠腺癌、胰腺腺癌和胆管癌，预测准确率分别为 94.17%、91.28%、89.04%和 88.89%。最后，通过计算浸润免疫细胞的富集评分和免疫通路的活性，我们发现这些基因与免疫微环境高度相关。
