通过计算分析 P4HA3 在人类癌症中的致癌和抗肿瘤免疫作用。

IF 3.8 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Hong Yan Huang, Fu Wei Zhang, Jie Yu, Yan Hong Xiao, Di Zhu, XiaoLin Yi, XiaoHua Lin, Ming Jin, Hai Yun Jin, Yong Sheng Huang, Shu Wei Ren
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引用次数: 0

摘要

脯氨酰-4-羟化酶亚基α3(P4HA3)是一种三重螺旋胶原合成蛋白。P4HA3 在癌症发展中的作用尚不清楚,也缺乏对人类癌症的全面分析。本研究旨在探讨 P4HA3 表达与抗肿瘤免疫之间的关系及其在泛癌症中的预后价值。研究分析了TIMER2.0、GTEx、GEPIA2.0和TCGA数据库中P4HA3的表达。在 cBio Cancer Genomics Portal、TCGA、GSCA 和 TIMER2.0 中对 P4HA3 的遗传和 DNA 甲基化改变、生存分析和蛋白质共表达进行了分析。TIDE、XCELL、MCPCOUNTER和EPIC分析了P4HA3表达与免疫浸润的相关性。我们进行了EdU和transwell实验,以评估P4HA3对不同肿瘤的增殖、迁移和侵袭能力的影响。我们利用患者衍生异种移植(PDX)和皮下移植模型来探讨P4HA3与三阴性乳腺癌(TNBC)免疫疗法反应之间的相关性。进一步分析表明,P4HA3的表达与肿瘤微环境(TME)的细胞浸润相关。P4HA3的表达与细胞增殖标志物和上皮-间质转化(EMT)标志物呈正相关。此外,P4HA3的缺乏还能抑制肿瘤细胞的增殖、迁移和侵袭能力,促进PD-1/PD-L1抑制剂的抗肿瘤免疫治疗。通过对P4HA3的泛癌症分析,可以全面了解其在不同癌症中的致癌和预后作用,P4HA3的异常表达可以成为预测癌症患者免疫治疗效果的有用生物标志物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A computational analysis of the oncogenic and anti-tumor immunity role of P4HA3 in human cancers.

Prolyl-4-hydroxylase subunit alpha3 (P4HA3) is a triple helical procollagen synthesis protein. The role of P4HA3 in cancer development is not well known and lacks comprehensive analyses among human cancers. This study aimed to investigate the relationship between P4HA3 expression and anti-tumor immunity and its prognostic value in pan-cancer. P4HA3 expression was analyzed from TIMER2.0, GTEx, GEPIA2.0 and TCGA databases. Genetic and DNA methylation alterations, survival analysis and proteins co-expression analysis of P4HA3 in cBio Cancer Genomics Portal, TCGA, GSCA and TIMER2.0. The correlation between P4HA3 expression and immune infiltration was analyzed by TIDE, XCELL, MCPCOUNTER, and EPIC. We performed EdU and transwell experiments to evaluate the influence of P4HA3 on the proliferation, migration and invasion abilities of different tumors. Patients derived xenograft (PDX) and subcutaneous transplantation models were utilized to explore the correlation between P4HA3 and immunotherapy response in triple-negative breast cancer (TNBC). Among 33 types of cancers, P4HA3 had generally different expression between different tumors, further analysis showed that the expression of P4HA3 was correlated with the cells infiltration of the tumor microenvironment (TME). The expression of P4HA3 was positively with the cell proliferation markers and epithelial-mesenchymal transition (EMT) markers. Moreover, P4HA3 deficiency inhibited the proliferation, migration and invasion abilities of tumor cells, and promoted anti-tumor immunotherapy of PD-1/PD-L1 inhibitor. This pan-cancer analysis of P4HA3 provides a comprehensive understanding of its oncogenic and prognosis role in different cancers, P4HA3 abnormal expression could be a useful biomarker for predicting the effectiveness of immunotherapy in cancer patients.

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来源期刊
PLoS Computational Biology
PLoS Computational Biology BIOCHEMICAL RESEARCH METHODS-MATHEMATICAL & COMPUTATIONAL BIOLOGY
CiteScore
7.10
自引率
4.70%
发文量
820
审稿时长
2.5 months
期刊介绍: PLOS Computational Biology features works of exceptional significance that further our understanding of living systems at all scales—from molecules and cells, to patient populations and ecosystems—through the application of computational methods. Readers include life and computational scientists, who can take the important findings presented here to the next level of discovery. Research articles must be declared as belonging to a relevant section. More information about the sections can be found in the submission guidelines. Research articles should model aspects of biological systems, demonstrate both methodological and scientific novelty, and provide profound new biological insights. Generally, reliability and significance of biological discovery through computation should be validated and enriched by experimental studies. Inclusion of experimental validation is not required for publication, but should be referenced where possible. Inclusion of experimental validation of a modest biological discovery through computation does not render a manuscript suitable for PLOS Computational Biology. Research articles specifically designated as Methods papers should describe outstanding methods of exceptional importance that have been shown, or have the promise to provide new biological insights. The method must already be widely adopted, or have the promise of wide adoption by a broad community of users. Enhancements to existing published methods will only be considered if those enhancements bring exceptional new capabilities.
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