Center of Reproductive Medicine, Shengjing Hospital of China Medical University, Shenyang, China.
Key Laboratory of Reproductive Dysfunction Diseases and Fertility Remodeling of Liaoning Province, Shenyang, China.
Hereditas. 2022 Mar 18;159(1):17. doi: 10.1186/s41065-022-00222-3.
With a lack of specific symptoms, ovarian cancer (OV) is often diagnosed at an advanced stage. This coupled with inadequate prognostic indicators and treatments with limited therapeutic effect make OV the deadliest type of gynecological tumor. Recent research indicates that N6-methyladenosine (m6A) and long-chain non-coding RNA (lncRNA) play important roles in the prognosis of OV and the efficacy of immunotherapy.
Using the Cancer Genome Atlas (TCGA) OV-related data set and the expression profiles of 21 m6A-related genes, we identified two m6A subtypes, and the differentially expressed genes between the two. Based on the differentially expressed lncRNAs in the two m6A subtypes and the lncRNAs co-expressed with the 21 m6A-related genes, single-factor cox and LASSO regression were used to further isolate the 13 major lncRNAs. Finally, multi-factor cox regression was used to construct a m6A-related lncRNA risk score model for OV, with good performance in patient prognosis. Using risk score, OV tumor samples are divided into with high- and low-score groups. We explored the differences in clinical characteristics, tumor mutational burden, and tumor immune cell infiltration between the two groups, and evaluated the risk score's ability to predict the benefit of immunotherapy.
Our m6A-based lncRNA risk model could be used to predict the prognosis and immunotherapy response of future OV patients.
由于缺乏特异性症状,卵巢癌(OV)常常在晚期才被诊断出来。再加上预后指标不足和治疗效果有限,使得 OV 成为妇科肿瘤中最致命的类型。最近的研究表明,N6-甲基腺苷(m6A)和长链非编码 RNA(lncRNA)在 OV 的预后和免疫治疗疗效中发挥着重要作用。
利用癌症基因组图谱(TCGA)OV 相关数据集和 21 个 m6A 相关基因的表达谱,我们鉴定出了两种 m6A 亚型,以及两种亚型之间差异表达的基因。基于两种 m6A 亚型中差异表达的 lncRNA 以及与 21 个 m6A 相关基因共表达的 lncRNA,采用单因素 cox 和 LASSO 回归进一步分离出 13 个主要的 lncRNA。最后,采用多因素 cox 回归构建了 OV 的 m6A 相关 lncRNA 风险评分模型,对患者预后有较好的预测性能。利用风险评分,OV 肿瘤样本被分为高分组和低分组。我们探讨了两组之间临床特征、肿瘤突变负担和肿瘤免疫细胞浸润的差异,并评估了风险评分预测免疫治疗获益的能力。
我们基于 m6A 的 lncRNA 风险模型可用于预测未来 OV 患者的预后和免疫治疗反应。