Chen Guansheng, Li Wenjing, Guo Jiayi, Liu Lingyu, Wang Yongjun
Department of Gynecology and Obstetrics, Beijing Jishuitan Hospital, Capital Medical University, Beijing, China.
Cancer Med. 2025 Feb;14(3):e70634. doi: 10.1002/cam4.70634.
BACKGROUND: Ovarian cancer (OC) is a prevalent malignant tumor in the field of gynecology, exhibiting the third highest incidence rate and the highest mortality rate among gynecological tumors. Chromatin remodeling accomplishes specific chromatin condensation at distinct genomic loci and plays an essential role in epigenetic regulation associated with various processes related to cancer development. METHODS: Differentially expressed genes (DEGs) between OC and control samples were screened from The Cancer Genome Atlas (TCGA) and Genotype-Tissue Expression (GTEx) databases, combined with chromatin remodeling-related genes (CRRGs) obtained from the GeneCards database to identify differentially expressed CRRGs (DECRRGs). Enrichment analysis and protein-protein interaction (PPI) network were performed on the DECRRGs. Prognostic genes of OC were screened using univariate Cox and least absolute shrinkage and selection operator (Lasso) analyses. A risk model based on prognostic genes was developed, and the survival probability of OC patients in different risk groups was analyzed by Kaplan-Meier (KM) curve. Finally, the expression levels of prognostic genes were validated by quantitative real-time polymerase chain reaction (qRT-PCR) and western blotting. RESULTS: In total, 7 potential prognostic genes associated with the progression of OC patients were obtained, including ARID1B, ATRX, CHRAC1, HDAC1, INO80, MBD2, and SS18. Based on the expression level of prognostic genes, OC patients were divided into high-risk group and low-risk group. Survival analysis indicated that patients classified into the high-risk group had higher mortality rates, which enables this prediction model to be utilized as an independent predictor of OC. Immunocorrelation analysis showed that low-risk patients were more likely to benefit from immunotherapy. CONCLUSION: In this study, we have identified 7 prognostic genes, including ARID1B, ATRX, CHRAC1, HDAC1, INO80, MBD2, and SS18. Overall, our findings provided a foundation for further comprehension of the potential molecular mechanisms underlying OC pathogenesis and progression.
背景:卵巢癌(OC)是妇科领域中一种常见的恶性肿瘤,在妇科肿瘤中发病率排名第三,死亡率最高。染色质重塑在不同的基因组位点实现特定的染色质浓缩,并在与癌症发展相关的各种过程的表观遗传调控中发挥重要作用。 方法:从癌症基因组图谱(TCGA)和基因型-组织表达(GTEx)数据库中筛选OC与对照样本之间的差异表达基因(DEG),并结合从基因卡片数据库获得的染色质重塑相关基因(CRRG),以鉴定差异表达的CRRG(DECRRG)。对DECRRG进行富集分析和蛋白质-蛋白质相互作用(PPI)网络分析。使用单变量Cox分析和最小绝对收缩和选择算子(Lasso)分析筛选OC的预后基因。基于预后基因建立风险模型,并通过Kaplan-Meier(KM)曲线分析不同风险组OC患者的生存概率。最后,通过定量实时聚合酶链反应(qRT-PCR)和蛋白质免疫印迹法验证预后基因的表达水平。 结果:总共获得了7个与OC患者病情进展相关的潜在预后基因,包括ARID1B、ATRX、CHRAC1、HDAC1、INO80、MBD2和SS18。根据预后基因的表达水平,将OC患者分为高风险组和低风险组。生存分析表明,分类为高风险组的患者死亡率较高,这使得该预测模型可作为OC的独立预测指标。免疫相关性分析表明,低风险患者更有可能从免疫治疗中获益。 结论:在本研究中,我们鉴定了7个预后基因,包括ARID1B、ATRX、CHRAC1、HDAC1、INO¬80、MBD2和SS18。总体而言,我们的研究结果为进一步理解OC发病机制和病情进展的潜在分子机制提供了基础。
BMC Cancer. 2024-4-23
Biochem Biophys Res Commun. 2024-11-12
Transl Lung Cancer Res. 2023-12-26
Int J Mol Sci. 2024-1-2
J Natl Compr Canc Netw. 2023-2
Int J Mol Sci. 2022-11-8
Nat Rev Cancer. 2022-11