Feature analysis of the tissue methylation profile in adenocarcinoma patients with pulmonary nodules on CT scan
10.3760/cma.j.cn114452-20240630-00343
- VernacularTitle:CT表现为结节的肺腺癌患者的组织甲基化特征分析
- Author:
Qiaomei GUO
1
;
Lihua QIAO
;
Lin WANG
;
Xueqing WANG
;
Fei WU
;
Xiaohui LIANG
;
Yuteng SUN
;
Jiatao LOU
Author Information
1. 上海市第一人民医院，上海交通大学医学院附属第一人民医院检验医学中心，上海200080
- Keywords:
Sarcoidosis, pulmonary;
Adenocarcinoma;
DNA Methylation
- From:
Chinese Journal of Laboratory Medicine
2024;47(11):1277-1285
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the tissue methylation features of adenocarcinoma patients presenting as pulmonary nodules on CT scans.Methods:A retrospective analysis was conducted on 70 adenocarcinoma patients with pulmonary nodules diagnosed at the Shanghai General Hospital from June 1, 2022 to January 20, 2024. Participants were assigned to two groups using the random number table, with 40 in the discovery group and 30 in the validation group. In the discovery group, tissue samples were analyzed using reduced representation bisulfite sequencing (RRBS) technology to compare the average methylation levels between cancer tissues and paired adjacent non-cancerous tissues. Differentially methylated regions (DMRs) were screened for analysis of their distribution across various genomic functional elements, and hierarchical clustering was plotted. GO and KEGG pathway enrichment analyses were further conducted on the DMRs. Subsequently, candidate DMRs associated with lung adenocarcinoma were validated using TCGA lung adenocarcinoma cohort and targeted bisulfite sequencing technology in the validation group. The comparison of methylation levels between groups was conducted using t-tests or non-parametric tests, while rates and composition ratios were analyzed using chi-square tests or Fisher′s exact test.Results:In discovery cohort, the average methylation level in cancer tissues was lower compared to adjacent normal tissues [(42.369±4.627) vs (44.370±4.046), t=?2.059, P=0.043]. A total of 37 995 DMRs were identified, including 16 889 upregulated regions and 21 106 downregulated regions, predominantly locating in promoter regions (48.917%), introns (36.457%), and exons (10.812%). The DMR clustering heatmap revealed two distinct clusters corresponding to cancer tissues and adjacent non-cancerous tissues. GO analysis showed that DMRs associated genes were mainly located in the cell membrane and nuclear chromatin, and were primarily involved in RNA polymerase Ⅱ-related transcription and regulation. KEGG pathway enrichment analysis indicated that DMRs associated genes were mainly involved in neuroactive ligand-receptor interaction, cancer pathways, calcium signaling pathway, cAMP signaling pathway, and MAPK signaling pathway. Validation in the TCGA cohort confirmed 11 potential characteristic DMRs. In the validation group, TBS confirmed that the methylation levels of DMRs associated with MIR10B, DMRTA2, HOPX, TFAP2B and MARCH11 in cancer tissues were significantly higher than those in adjacent non-cancerous tissues [11.200(4.305, 27.088) vs 2.650(1.298, 4.645), Z=?4.539, P<0.05; 18.610(13.600, 33.025) vs 8.675(5.488, 13.085), Z=?4.554, P<0.05; 17.600(2.183, 76.015) vs 1.085(0.898, 1.835), Z=?5.131, P<0.05; 5.250(3.220, 7.693) vs 3.495(2.165, 4.383), Z=?2.861, P<0.05; 11.515(7.525, 21.033) vs 7.830(5.518, 11.488), Z=?2.440, P<0.05 ], and the differences were statistically significant. Conclusions:Lung adenocarcinoma tissue exhibits different methylation patterns compared with adjacent normal lung tissue. The identified DMRs are involved in the regulation of several key pathways. Results from the TCGA cohort and an independent validation group support the potential diagnostic value of DMRs such as MIR10B, DMRTA2, HOPX, TFAP2B, and MARCH11 in lung adenocarcinoma, though their clinical application requires further validation.
