A BIRC5High COD1Low Cancer Tissue Phenotype Indicates Poorer Prognosis of Metastatic Breast Cancer Patients.

IF 2.4 Q2 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Cancer Informatics Pub Date : 2022-06-14 eCollection Date: 2022-01-01 DOI:10.1177/11769351221096655
Yujie Bai, Feng Yuan, Jing Yu, Yibei Si, Yiwen Zheng, Dongqing Li
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引用次数: 1

Abstract

Extensive data research is helpful to find sensitive biomarkers for prognostic prediction of metastatic breast cancer. Through analyzing multiple GEO datasets, literature retrieval, and verified in GEPIA datasets, we identify BIRC5 (Baculoviral IAP repeat containing 5) and CDO1 (Cysteine dioxygenase type 1) as DEGs (differentially expressed genes) between breast tumor and normal tissue and DEGs between metastatic breast cancer and breast cancer in situ. Then, we performed a series of in silico studies on BIRC5 and CDO1 using online tools including the UALCAN, TIMER, TCGA-BRCA, LinkedOmics Kaplan-Meier Plotter, and an R script for analysis. To verify the association of 2 genes expression and patients' clinical data, we detected BIRC5 and CDO1 mRNA in the tissue of 48 breast cancer patients. The results showed the tumor with BIRC5high CDO1low expression generally indicated patients' shorter overall (OS) and relapse-free survival (RFS). Specifically, BIRC5 and CDO1 levels significantly affect OS or RFS in patients with Lymph node metastasis and molecular subtypes of TNBC (triple-negative breast cancer) and Luminal A. A BIRC5high tumor displayed a purer tumor purity and expressed more KIR receptors on NK cells while activating more FOXP3+CD25+ Treg cells. The CDO1low tumors infiltrated with more immunocytes leading to less tumor purity. In our verified experiment, BIRC5 mRNA level in patients with stage III and over was significantly higher than in patients with stage 0 to II, but there were no significant differences among molecular subtyping groups; TNBC tissue expressed lower CDO1 mRNA level than HER2+ and Luminal type cancer tissue. In conclusion, a BIRC5high CDO1low expression type in breast cancer tissue indicates a poorer prognosis of patients. The potential mechanism might be increased BIRC5 expression in cancer tissue is likely to accompany NK cells inhibition, activating more Treg cells, and lacking effective CD8+ T cells proliferation. Meanwhile, CDO1 level is positively related to more immunocytes infiltration.

Abstract Image

Abstract Image

Abstract Image

birc5高cod11低癌组织表型提示转移性乳腺癌患者预后较差
广泛的数据研究有助于寻找敏感的生物标志物来预测转移性乳腺癌的预后。通过对多个GEO数据集的分析、文献检索和GEPIA数据集的验证,我们确定BIRC5(杆状病毒IAP重复序列5)和CDO1(半胱氨酸双加氧酶1型)是乳腺肿瘤与正常组织之间、转移性乳腺癌与原位乳腺癌之间的差异表达基因。然后,我们使用在线工具,包括UALCAN, TIMER, TCGA-BRCA, LinkedOmics Kaplan-Meier绘图仪和R脚本,对BIRC5和CDO1进行了一系列的计算机研究。为了验证这两个基因的表达与患者临床资料的相关性,我们在48例乳腺癌患者的组织中检测了BIRC5和CDO1 mRNA。结果显示,birc5高cdo10低表达的肿瘤患者总体生存期(OS)和无复发生存期(RFS)较短。具体而言,BIRC5和CDO1水平显著影响淋巴结转移和TNBC(三阴性乳腺癌)和Luminal A分子亚型患者的OS或RFS。BIRC5高的肿瘤表现出更纯粹的肿瘤纯度,在NK细胞上表达更多的KIR受体,激活更多的FOXP3+CD25+ Treg细胞。CDO1low肿瘤浸润免疫细胞较多,肿瘤纯度较低。在我们验证的实验中,III期及以上患者BIRC5 mRNA水平显著高于0 ~ II期患者,但分子分型组间差异无统计学意义;TNBC组织CDO1 mRNA表达水平低于HER2+和Luminal型癌组织。综上所述,乳腺癌组织中birc5高cdo10低表达型患者预后较差。其潜在机制可能是癌组织中BIRC5表达增加可能伴随NK细胞抑制,激活更多Treg细胞,缺乏有效的CD8+ T细胞增殖。同时,CDO1水平与更多免疫细胞浸润呈正相关。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Cancer Informatics
Cancer Informatics Medicine-Oncology
CiteScore
3.00
自引率
5.00%
发文量
30
审稿时长
8 weeks
期刊介绍: The field of cancer research relies on advances in many other disciplines, including omics technology, mass spectrometry, radio imaging, computer science, and biostatistics. Cancer Informatics provides open access to peer-reviewed high-quality manuscripts reporting bioinformatics analysis of molecular genetics and/or clinical data pertaining to cancer, emphasizing the use of machine learning, artificial intelligence, statistical algorithms, advanced imaging techniques, data visualization, and high-throughput technologies. As the leading journal dedicated exclusively to the report of the use of computational methods in cancer research and practice, Cancer Informatics leverages methodological improvements in systems biology, genomics, proteomics, metabolomics, and molecular biochemistry into the fields of cancer detection, treatment, classification, risk-prediction, prevention, outcome, and modeling.
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