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On-line Access: 2023-01-10

Received: 2022-05-09

Revision Accepted: 2022-08-30

Crosschecked: 2023-01-16

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Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Jiahang MO

Jiahang MO, https://orcid.org/0000-0002-2418-1745

Shunyi RUAN

Shunyi RUAN, https://orcid.org/0000-0003-0974-4463

Hua JIANG

Hua JIANG, https://orcid.org/0000-0002-5235-341X

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Journal of Zhejiang University SCIENCE B 2023 Vol.24 No.1 P.64-77

http://doi.org/10.1631/jzus.B2200272


A novel defined risk signature of endoplasmic reticulum stress-related genes for predicting the prognosis and immune infiltration status of ovarian cancer


Author(s):  Jiahang MO, Shunyi RUAN, Baicai YANG, Yunfeng JIN, Keyi LIU, Xukai LUO, Hua JIANG

Affiliation(s):  Obstetrics and Gynecology Hospital, Fudan University, Shanghai 200011, China; more

Corresponding email(s):   jianghua_fckyy@126.com

Key Words:  Ovarian cancer (OvCa), Endoplasmic reticulum (ER) stress, Risk signature, Prognosis, Immune infiltration


Jiahang MO, Shunyi RUAN, Baicai YANG, Yunfeng JIN, Keyi LIU, Xukai LUO, Hua JIANG. A novel defined risk signature of endoplasmic reticulum stress-related genes for predicting the prognosis and immune infiltration status of ovarian cancer[J]. Journal of Zhejiang University Science B, 2023, 24(1): 64-77.

@article{title="A novel defined risk signature of endoplasmic reticulum stress-related genes for predicting the prognosis and immune infiltration status of ovarian cancer",
author="Jiahang MO, Shunyi RUAN, Baicai YANG, Yunfeng JIN, Keyi LIU, Xukai LUO, Hua JIANG",
journal="Journal of Zhejiang University Science B",
volume="24",
number="1",
pages="64-77",
year="2023",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.B2200272"
}

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%T A novel defined risk signature of endoplasmic reticulum stress-related genes for predicting the prognosis and immune infiltration status of ovarian cancer
%A Jiahang MO
%A Shunyi RUAN
%A Baicai YANG
%A Yunfeng JIN
%A Keyi LIU
%A Xukai LUO
%A Hua JIANG
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%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.B2200272

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T1 - A novel defined risk signature of endoplasmic reticulum stress-related genes for predicting the prognosis and immune infiltration status of ovarian cancer
A1 - Jiahang MO
A1 - Shunyi RUAN
A1 - Baicai YANG
A1 - Yunfeng JIN
A1 - Keyi LIU
A1 - Xukai LUO
A1 - Hua JIANG
J0 - Journal of Zhejiang University Science B
VL - 24
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SP - 64
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PB - Zhejiang University Press & Springer
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DOI - 10.1631/jzus.B2200272


Abstract: 
endoplasmic reticulum (ER) stress, as an emerging hallmark feature of cancer, has a considerable impact on cell proliferation, metastasis, invasion, and chemotherapy resistance. ovarian cancer (OvCa) is one of the leading causes of cancer-related mortality across the world due to the late stage of disease at diagnosis. Studies have explored the influence of ER stress on OvCa in recent years, while the predictive role of ER stress-related genes in OvCa prognosis remains unexplored. Here, we enrolled 552 cases of ER stress-related genes involved in OvCa from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) cohorts for the screening of prognosis-related genes. The least absolute shrinkage and selection operator (LASSO) regression was applied to establish an ER stress-related risk signature based on the TCGA cohort. A seven-gene signature revealed a favorable predictive efficacy for the TCGA, International Cancer Genome Consortium (ICGC), and another GEO cohort (P<0.001, P<0.001, and P=0.04, respectively). Moreover, functional annotation indicated that this signature was enriched in cellular response and senescence, cytokines interaction, as well as multiple immune-associated terms. The immune infiltration profiles further delineated an immunologic unresponsive status in the high-risk group. In conclusion, ER stress-related genes are vital factors predicting the prognosis of OvCa, and possess great application potential in the clinic.

基于内质网应激相关基因构建新型风险模型用于卵巢癌预后及免疫浸润状态的预测

莫佳航1,2,阮顺毅3,杨柏财4,金云峰1,2,刘可一5,罗序楷1,姜桦1,2
1复旦大学附属妇产科医院,中国上海市,200011
2复旦大学附属妇产科医院上海市女性生殖内分泌相关疾病重点实验室,中国上海市,200011
3上海交通大学医学院附属第六人民医院肿瘤科,上海交通大学医学院,中国上海市,200233
4嘉兴学院附属妇幼保健院妇产科,中国嘉兴市,314050
5浙江大学医学院附属妇科医院病理科,中国杭州市,310006
目的:开发一种基于内质网应激相关基因的预后模型,可有效预测卵巢癌(OvCa)患者的总生存期和免疫浸润状态。
方法:首先从TCGA和GEO数据库下载了552例含有RNA测序及临床信息的OvCa病例数据;并从GeneCards中提取了785个被定义为内质网应激相关的基因。然后结合单因素Cox回归分析和LASSO回归分析建立基于内质网应激基因的预后模型。在TCGA队列训练后,我们又纳入两个外部数据集进行Kaplan-Meier生存分析和时间依赖性受试者工作特征曲线(ROC)分析验证了其预后预测的性能。此外,我们还进行了GO、KEGG和GSEA功能富集分析;应用CIBERSORT算法描绘了风险分组中免疫浸润状态差异。
创新点:OvCa是一种致死率极高的妇科恶性肿瘤,具有高度的侵袭性及肿瘤异质性。大量临床研究显示OvCa对免疫治疗的应答率极低,提示瘤内免疫浸润状态不佳。因此,需要开发更为可靠的基因标志物用于预测患者的预后和免疫浸润状态。研究显示,内质网应激相关通路与卵巢癌预后密切相关,但尚缺乏基于该通路相关基因的模型用以预测患者的临床预后。本研究基于内质网应激相关基因构建了一种新型风险模型,用于患者的预后风险分层和总体生存率预测。同时,基于对肿瘤免疫浸润状态评估,该风险模型提示内质网应激的选择性激活或可改善免疫治疗在OvCa中的疗效。
结论:本研究构建了由7个内质网应激相关基因构成的预后模型,可在训练集和验证集中有效区分高风险OvCa患者,并被证明为总生存期的独立预后因子。利用诺谟图进行基于该风险特征的生存率预测。后续分析显示高低风险人群存在内质网应激通路激活的分支差异。功能富集和免疫浸润分析表明该风险特征与肿瘤免疫应答状态密切相关。综上,基于内质网应激相关基因的预后模型是一种很有前景的工具,可进行风险分层、生存预测和免疫浸润状态的评估。

关键词:卵巢癌(OvCa);内质网应激;风险模型;预后;免疫浸润

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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