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Critical Reviews™ in Eukaryotic Gene Expression

年間 6 号発行

ISSN 印刷: 1045-4403

ISSN オンライン: 2162-6502

The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) IF: 1.6 To calculate the five year Impact Factor, citations are counted in 2017 to the previous five years and divided by the source items published in the previous five years. 2017 Journal Citation Reports (Clarivate Analytics, 2018) 5-Year IF: 2.2 The Immediacy Index is the average number of times an article is cited in the year it is published. The journal Immediacy Index indicates how quickly articles in a journal are cited. Immediacy Index: 0.3 The Eigenfactor score, developed by Jevin West and Carl Bergstrom at the University of Washington, is a rating of the total importance of a scientific journal. Journals are rated according to the number of incoming citations, with citations from highly ranked journals weighted to make a larger contribution to the eigenfactor than those from poorly ranked journals. Eigenfactor: 0.00058 The Journal Citation Indicator (JCI) is a single measurement of the field-normalized citation impact of journals in the Web of Science Core Collection across disciplines. The key words here are that the metric is normalized and cross-disciplinary. JCI: 0.33 SJR: 0.345 SNIP: 0.46 CiteScore™:: 2.5 H-Index: 67

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Identification of Hub Genes in Gastric Cancer with High Heterogeneity Based on Weighted Gene Co-Expression Network

巻 30, 発行 2, 2020, pp. 101-109
DOI: 10.1615/CritRevEukaryotGeneExpr.2020028305
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要約

Intra-tumor heterogeneity (ITH) plays an important role in the therapeutic resistance and prognosis of gastric cancer (GC), but there are no effective methods to detect it. The purpose of this study was to apply the mutant-allele tumor heterogeneity (MATH) algorithm to reveal the relationship between ITH and clinical features, and to use weighted gene co-expression network analysis (WGCNA) to search hub genes. The whole exome sequencing data with tumor mutations, RNA-seq, and clinical data were obtained from The Cancer Genome Atlas database. We calculated the MATH values and further investigated their relationships with clinical features and key genes screened out from molecular classification published by Nature. The WGCNA method was applied to discover hub genes within the high ITH cases. We found that MATH values were related to grade classification (P < 0.05). Our study also showed a "high MATH" group with a higher TP53 percentage (P < 0.001), whereas PIK3CA and RHOA had the opposite results (P = 0.004; P = 0.031). Using WGCNA, we found that red module, black module, and brown module were enriched in spliceosome, ribosome, and butanoate metabolism, and their hub genes were PSMD1, RPS23, and FAM84B, respectively. Together, these results demonstrate that in the high MATH group, represented as high heterogeneity, there was a higher frequency of TP53 mutation, and RHOA and PIK3CA tended to appear in the low heterogeneity group. PSMD1, RPS23, and FAM84B were the hub genes in high heterogeneity GC. They were related to the pathology and prognosis of patients.

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によって引用された
  1. Wang Shuang, Tian Jun, Wang Jianzhong, Liu Sizhu, Ke Lianwei, Shang Chaojiang, Yang Jichun, Wang Lin, Identification of the Biomarkers and Pathological Process of Heterotopic Ossification: Weighted Gene Co-Expression Network Analysis, Frontiers in Endocrinology, 11, 2020. Crossref

  2. Liu Lihua, Liu Aihua, Dong Jun, Zuo Zhongfu, Liu Xuezheng, Proteasome 26S subunit, non-ATPase 1 (PSMD1) facilitated the progression of lung adenocarcinoma by the de-ubiquitination and stability of PTEN-induced kinase 1 (PINK1), Experimental Cell Research, 413, 2, 2022. Crossref

  3. Yang Yan, Dai Daofeng, Jin Wen, Huang Yingying, Zhang Yingzi, Chen Yiran, Wang Wankun, Lin Wu, Chen Xiangliu, Zhang Jing, Wang Haohao, Zhang Haibin, Teng Lisong, Microbiota and metabolites alterations in proximal and distal gastric cancer patients, Journal of Translational Medicine, 20, 1, 2022. Crossref

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