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通过整合转录组学和代谢组学分析来表征NTPCR在上皮性卵巢癌中的潜在作用

Characterization of the Potential Role of NTPCR in Epithelial Ovarian Cancer by Integrating Transcriptomic and Metabolomic Analysis.

作者信息

Shang Hongkai, Zhang Huizhi, Ren Ziyao, Zhao Hongjiang, Zhang Zhifen, Tong Jinyi

机构信息

Department of the Fourth Clinical Medical College, Zhejiang Chinese Medical University, Hangzhou, China.

Department of Gynecology, Hangzhou First People's Hospital, Hangzhou, China.

出版信息

Front Genet. 2021 Sep 1;12:695245. doi: 10.3389/fgene.2021.695245. eCollection 2021.

DOI:10.3389/fgene.2021.695245
PMID:34539736
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8442909/
Abstract

BACKGROUND

Epithelial ovarian carcinoma (EOC) is a malignant tumor with high motility in women. Our previous study found that dysregulated nucleoside-triphosphatase cancer-related (NTPCR) was associated with the prognosis of EOC patients, and thus, this present study attempted to explore the potential roles of NTPCR in disease progression.

METHODS

Expressed level of NTPCR was investigated in EOC tissues by RT-qPCR and Western blot analysis. NTPCR shRNA and overexpression vector were generated and transfected into OVCAR-3 or SKOV3 cells to detect the effect of NTPCR on cell proliferation, cell cycle, cell migration, and invasion. Transcriptomic sequencing and metabolite profiling analysis were performed in shNTPCR groups to identify transcriptome or metabolite alteration that might contribute to EOC. Finally, we searched the overlapped signaling pathways correlated with differential metabolites and differentially expressed genes (DEGs) by integrating analysis.

RESULTS

Comparing para-cancerous tissues, we found that NTPCR is highly expressed in cancer tissues ( < 0.05). Overexpression of NTPCR inhibited cell proliferation, migration, and invasion and reduced the proportion of S- and G2/M-phase cells, while downregulation of NTPCR showed the opposite results. RNA sequencing analysis demonstrated cohorts of DEGs were identified in shNTPCR samples. Protein-protein interaction networks were constructed for DEGs. STAT1 (degree = 43) and OAS2 (degree = 36) were identified as hub genes in the network. Several miRNAs together with target genes were predicted to be crucial genes related to disease progression, including , , , , , and . We also screened the differential metabolites from shNTPCR samples, including 22 upregulated and 22 downregulated metabolites. By integrating transcriptomics and metabolomics analysis, eight overlapped pathways were correlated with these DEGs and differential metabolites, such as primary bile acid biosynthesis, protein digestion, and absorption, pentose, and glucuronate interconversions.

CONCLUSION

NTPCR might serve as a tumor suppressor in EOC progression. Our results demonstrated that DEGs and differential metabolites were mainly related to several signaling pathways, which might be a crucial role in the progression of NTPCR regulation of EOC.

摘要

背景

上皮性卵巢癌(EOC)是女性中具有高迁移性的恶性肿瘤。我们之前的研究发现,癌症相关的核苷三磷酸酶(NTPCR)失调与EOC患者的预后相关,因此,本研究试图探讨NTPCR在疾病进展中的潜在作用。

方法

通过RT-qPCR和蛋白质免疫印迹分析研究EOC组织中NTPCR的表达水平。构建NTPCR短发夹RNA(shRNA)和过表达载体,并转染到OVCAR-3或SKOV3细胞中,以检测NTPCR对细胞增殖、细胞周期、细胞迁移和侵袭的影响。在shNTPCR组中进行转录组测序和代谢物谱分析,以鉴定可能导致EOC的转录组或代谢物改变。最后,通过整合分析搜索与差异代谢物和差异表达基因(DEG)相关的重叠信号通路。

结果

与癌旁组织相比,我们发现NTPCR在癌组织中高表达(<0.05)。NTPCR的过表达抑制细胞增殖、迁移和侵袭,并降低S期和G2/M期细胞的比例,而NTPCR的下调则显示相反的结果。RNA测序分析表明,在shNTPCR样本中鉴定出了DEG队列。构建了DEG的蛋白质-蛋白质相互作用网络。STAT1(度=43)和OAS2(度=36)被确定为网络中的枢纽基因。预测了几个与靶基因相关的微小RNA(miRNA)是与疾病进展相关的关键基因,包括、、、、、和。我们还从shNTPCR样本中筛选出差异代谢物,包括22种上调代谢物和22种下调代谢物。通过整合转录组学和代谢组学分析,八个重叠通路与这些DEG和差异代谢物相关,如初级胆汁酸生物合成、蛋白质消化和吸收、戊糖和葡糖醛酸相互转化。

结论

NTPCR可能在EOC进展中作为肿瘤抑制因子发挥作用。我们的结果表明,DEG和差异代谢物主要与几个信号通路相关,这可能在NTPCR调节EOC的进展中起关键作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a9a/8442909/639bb9754609/fgene-12-695245-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a9a/8442909/f2b749afba80/fgene-12-695245-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a9a/8442909/97189d5b63d7/fgene-12-695245-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a9a/8442909/a9efaf2ca0f9/fgene-12-695245-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a9a/8442909/331e96f737d0/fgene-12-695245-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a9a/8442909/11e1b42d3287/fgene-12-695245-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a9a/8442909/639bb9754609/fgene-12-695245-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a9a/8442909/f2b749afba80/fgene-12-695245-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a9a/8442909/97189d5b63d7/fgene-12-695245-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a9a/8442909/a9efaf2ca0f9/fgene-12-695245-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a9a/8442909/331e96f737d0/fgene-12-695245-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a9a/8442909/11e1b42d3287/fgene-12-695245-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3a9a/8442909/639bb9754609/fgene-12-695245-g006.jpg

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