de Souza Jorge E S, Fonseca André F, Valieris Renan, Carraro Dirce M, Wang Jean Y J, Kolodner Richard D, de Souza Sandro J
Institute of Bioinformatics and Biotechnology, São Paulo, Brazil; Center for Cell Therapy and Regional Blood Center, Department of Clinical Medicine, Faculty of Medicine, University of São Paulo, Ribeirão Preto, Brazil; International Research Center, CIPE/AC Camargo Cancer Center, São Paulo, Brazil.
Institute of Bioinformatics and Biotechnology, São Paulo, Brazil; Brain Institute, UFRN, Natal, Brazil.
PLoS One. 2014 Apr 7;9(4):e94147. doi: 10.1371/journal.pone.0094147. eCollection 2014.
A new method, which allows for the identification and prioritization of predicted cancer genes for future analysis, is presented. This method generates a gene-specific score called the "S-Score" by incorporating data from different types of analysis including mutation screening, methylation status, copy-number variation and expression profiling. The method was applied to the data from The Cancer Genome Atlas and allowed the identification of known and potentially new oncogenes and tumor suppressors associated with different clinical features including shortest term of survival in ovarian cancer patients and hormonal subtypes in breast cancer patients. Furthermore, for the first time a genome-wide search for genes that behave as oncogenes and tumor suppressors in different tumor types was performed. We envisage that the S-score can be used as a standard method for the identification and prioritization of cancer genes for follow-up studies.
本文提出了一种新方法，该方法可对预测的癌症基因进行识别并确定其优先级，以便未来进行分析。此方法通过整合来自不同类型分析的数据，包括突变筛查、甲基化状态、拷贝数变异和表达谱分析，生成一种名为“S评分”的基因特异性评分。该方法应用于来自癌症基因组图谱的数据，能够识别与不同临床特征相关的已知和潜在新的癌基因及肿瘤抑制基因，这些临床特征包括卵巢癌患者的最短生存期以及乳腺癌患者的激素亚型。此外，首次在全基因组范围内搜索在不同肿瘤类型中表现为癌基因和肿瘤抑制基因的基因。我们设想，S评分可作为一种标准方法，用于识别癌症基因并确定其优先级，以供后续研究使用。
