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铂类化疗后高级别浆液性卵巢癌免疫相关基因对模型的开发与验证

Development and Validation of an Immune-Related Gene-Pair Model of High-Grade Serous Ovarian Cancer After Platinum-Based Chemotherapy.

作者信息

Lin Jiaxing, Xu Xiao, Sun Dan, Li Tianren

机构信息

Department of Urology, The First Hospital of China Medical University, Shenyang, China.

Department of Pediatric Intensive Care Unit, The Shengjing Hospital of China Medical University, Shenyang, China.

出版信息

Front Oncol. 2021 Feb 10;10:626555. doi: 10.3389/fonc.2020.626555. eCollection 2020.

Abstract

BACKGROUND

High-grade serous ovarian cancer (HGSOC) is a common cause of death from gynecological cancer, with an overall survival rate that has not significantly improved in decades. Reliable bio-markers are needed to identify high-risk HGSOC to assist in the selection and development of treatment options.

METHOD

The study included ten HGSOC cohorts, which were merged into four separate cohorts including a total of 1,526 samples. We used the relative expression of immune genes to construct the gene-pair matrix, and the least absolute shrinkage and selection operator regression was performed to build the prognosis model using the training set. The prognosis of the model was verified in the training set (363 cases) and three validation sets (of 251, 354, and 558 cases). Finally, the differences in immune cell infiltration and gene enrichment pathways between high and low score groups were identified.

RESULTS

A prognosis model of HGSOC overall survival rate was constructed in the training set, and included data for 35 immune gene-related gene pairs and the regression coefficients. The risk stratification of HGSOC patients was successfully performed using the training set, with a p-value of Kaplan-Meier of < 0.001. A score from this model is an independent prognostic factor of HGSOC, and prognosis was evaluated in different clinical subgroups. This model was also successful for the other three validation sets, and the results of Kaplan-Meier analysis were statistically significant (p < 0.05). The model can also predict patient progression-free survival with HGSOC to reflect tumor growth status. There was a lower infiltration level of M1 macrophages in the high-risk group compared to that in the low-risk group (p < 0.001). Finally, the immune-related pathways were enriched in the low-risk group.

CONCLUSION

The prognostic model based on immune-related gene pairs developed is a potential prognostic marker for high-grade serous ovarian cancer treated with platinum. The model has robust prognostic ability and wide applicability. More prospective studies will be needed to assess the practical application of this model for precision therapy.

摘要

背景

高级别浆液性卵巢癌(HGSOC)是妇科癌症常见的死亡原因,其总体生存率在数十年间并未显著提高。需要可靠的生物标志物来识别高危HGSOC,以协助治疗方案的选择和制定。

方法

该研究纳入了10个HGSOC队列,这些队列被合并为4个独立队列,共1526个样本。我们使用免疫基因的相对表达构建基因对矩阵,并使用训练集通过最小绝对收缩和选择算子回归构建预后模型。该模型的预后在训练集(363例)和3个验证集(分别为251例、354例和558例)中得到验证。最后,确定了高分和低分两组之间免疫细胞浸润和基因富集途径的差异。

结果

在训练集中构建了HGSOC总体生存率的预后模型,该模型包含35个免疫基因相关基因对的数据及回归系数。使用训练集成功地对HGSOC患者进行了风险分层,Kaplan-Meier检验的p值<0.001。该模型的评分是HGSOC的独立预后因素,并在不同临床亚组中评估了预后。该模型在其他3个验证集中也取得成功,Kaplan-Meier分析结果具有统计学意义(p<0.05)。该模型还可以预测HGSOC患者的无进展生存期,以反映肿瘤生长状态。高危组中M1巨噬细胞的浸润水平低于低危组(p<0.001)。最后,免疫相关途径在低危组中富集。

结论

基于免疫相关基因对开发的预后模型是铂类治疗的高级别浆液性卵巢癌潜在的预后标志物。该模型具有强大的预后能力和广泛的适用性。需要更多的前瞻性研究来评估该模型在精准治疗中的实际应用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/42ee/7928280/1ddf4213692b/fonc-10-626555-g001.jpg

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