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

机译:铂基化疗后高级浆液癌癌免疫相关基因对模型的开发与验证

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摘要

BackgroundHigh-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.MethodThe 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.ResultsA 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.ConclusionThe 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.
机译:背景高级浆液卵巢癌(HGSOC)是妇科癌症死亡的常见原因,几十年来的整体存活率并没有显着提高。需要可靠的生物标记来识别高风险的HGSOC,以协助选择和开发治疗方案。方法包括十个HGSOC队列,其合并为四个单独的群组,包括总共1,526个样品。我们使用免疫基因的相对表达来构建基因对基质,并且进行最小的绝对收缩和选择操作员回归以使用训练集来构建预后模型。培训集(363例)和三个验证集(251,354和558例)核实了该模型的预后。最后,确定了高低分数基团之间的免疫细胞浸润和基因富集途径的差异。在训练组中构建了HGSOC总存活率的预后模型,包括35个免疫基因相关基因对的数据和回归的数据系数。使用训练集成功进行HGSOC患者的风险分层,具有<0.001的Kaplan-Meier的p值。来自该模型的分数是Hgsoc的独立预后因子,并在不同的临床亚组中评价预后。此模型对于其他三种验证集也是成功的,并且Kaplan-Meier分析的结果具有统计学意义(P <0.05)。该模型还可以通过Hgsoc预测患者的无进展生存期以反映肿瘤生长状态。与低风险组中的高风险组中的M1巨噬细胞渗透水平降低(P <0.001)。最后,在低风险组中富集了免疫相关途径。结论基于免疫相关基因对的预后模型,该模型是用铂治疗的高级浆液癌癌的潜在预后标志物。该模型具有稳健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进行精密治疗的实际应用。

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