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鉴定与自噬相关的基因特征,用于预测宫颈癌患者的生存情况。

Identification of an autophagy-related gene signature for survival prediction in patients with cervical cancer.

机构信息

Department of Pancreatic Surgery, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430022, China.

NHC Key Laboratory of Hormones and Development, Tianjin Institute of Endocrinology, Tianjin Medical University Chu Hsien-I Memorial Hospital, Tianjin, 300070, China.

出版信息

J Ovarian Res. 2020 Nov 7;13(1):131. doi: 10.1186/s13048-020-00730-8.

DOI:10.1186/s13048-020-00730-8
PMID:33160404
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7648936/
Abstract

Cervical cancer is one of the most common female malignancy that occurs worldwide and is reported to cause over 300,000 deaths in 2018. Autophagy controls the survival and death of cancerous cells by regulating the degradation process of cytoplasm and cellular organelle. In the present study, the differentially expressed autophagy-related genes (ARGs) between healthy and cancerous cervical tissues (squamous cell neoplasms) were obtained using data from GTEx and The Cancer Genome Atlas (TCGA) database. The functionalities of the differentially expressed ARGs were analyzed using Gene Ontology (GO) as well as the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Next, we conducted univariate Cox regression assay and obtained 12 ARGs that were associated with the prognosis of cervical cancer patients. We carried out a multivariate Cox regression analysis and developed six ARG-related prognostic signature for the survival prediction of patients with squamous cell cervical cancer (Risk score = - 0.63ATG3-0.42BCL2 + 0.85CD46-0.38IFNG+ 0.23NAMPT+ 0.82TM9SF1). Following the calculation of risk score using the signature, the patients were divided into high and low-risk groups according to the median value. Kaplan-Meier curve demonstrated that patients with a high-risk score tend to have a poor prognosis (P < 0.001). The value for area under the curves corresponding to the receiver operating characteristic (ROC) was 0.740. As observed, the expression of IFNG was negatively associated with lymph node metastasis (P = 0.026), while a high-risk score was significantly associated with increased age (P = 0.008). To further validate the prognostic signature, we carried out a permutation test and confirmed the performance of the risk score. In conclusion, our study developed six ARG-related prognostic signature for patients with squamous cell cervical cancer, which might help in improving the prognostic predictions of such patients.

摘要

宫颈癌是全球最常见的女性恶性肿瘤之一,据报道,2018 年导致超过 30 万人死亡。自噬通过调节细胞质和细胞器的降解过程来控制癌细胞的存活和死亡。在本研究中,使用 GTEx 和癌症基因组图谱 (TCGA) 数据库的数据获得了健康和癌性宫颈组织(鳞状细胞肿瘤)之间差异表达的自噬相关基因 (ARGs)。使用基因本体论 (GO) 以及京都基因与基因组百科全书 (KEGG) 数据库分析差异表达的 ARG 的功能。接下来,我们进行了单变量 Cox 回归分析,并获得了 12 个与宫颈癌患者预后相关的 ARG。我们进行了多变量 Cox 回归分析,并为鳞状细胞宫颈癌患者的生存预测开发了六个 ARG 相关的预后标志(风险评分= -0.63ATG3-0.42BCL2+0.85CD46-0.38IFNG+0.23NAMPT+0.82TM9SF1)。使用该标志计算风险评分后,根据中位数将患者分为高风险组和低风险组。Kaplan-Meier 曲线表明,高风险评分的患者预后较差(P<0.001)。对应接收器操作特征 (ROC) 的曲线下面积的值为 0.740。正如观察到的,IFNG 的表达与淋巴结转移呈负相关(P=0.026),而高风险评分与年龄增加显著相关(P=0.008)。为了进一步验证预后标志,我们进行了置换检验并确认了风险评分的性能。总之,我们的研究为鳞状细胞宫颈癌患者开发了六个 ARG 相关的预后标志,这可能有助于改善这些患者的预后预测。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e386/7648936/fbd0ca91fdfc/13048_2020_730_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e386/7648936/246cff1a1c20/13048_2020_730_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e386/7648936/0fe474f6c975/13048_2020_730_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e386/7648936/6a0e10f1c734/13048_2020_730_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e386/7648936/49f3663703cf/13048_2020_730_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e386/7648936/f959af01a086/13048_2020_730_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e386/7648936/fbd0ca91fdfc/13048_2020_730_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e386/7648936/246cff1a1c20/13048_2020_730_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e386/7648936/0fe474f6c975/13048_2020_730_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e386/7648936/6a0e10f1c734/13048_2020_730_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e386/7648936/49f3663703cf/13048_2020_730_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e386/7648936/f959af01a086/13048_2020_730_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/e386/7648936/fbd0ca91fdfc/13048_2020_730_Fig6_HTML.jpg

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