Joint Research Laboratory of the Hungarian Academy of Sciences and the Semmelweis University, Semmelweis University 1st Department of Pediatrics, Bokay u. 53-54, 1083, Budapest, Hungary.
Breast Cancer Res Treat. 2010 Oct;123(3):725-31. doi: 10.1007/s10549-009-0674-9. Epub 2009 Dec 18.
Validating prognostic or predictive candidate genes in appropriately powered breast cancer cohorts are of utmost interest. Our aim was to develop an online tool to draw survival plots, which can be used to assess the relevance of the expression levels of various genes on the clinical outcome both in untreated and treated breast cancer patients. A background database was established using gene expression data and survival information of 1,809 patients downloaded from GEO (Affymetrix HGU133A and HGU133+2 microarrays). The median relapse free survival is 6.43 years, 968/1,231 patients are estrogen-receptor (ER) positive, and 190/1,369 are lymph-node positive. After quality control and normalization only probes present on both Affymetrix platforms were retained (n = 22,277). In order to analyze the prognostic value of a particular gene, the cohorts are divided into two groups according to the median (or upper/lower quartile) expression of the gene. The two groups can be compared in terms of relapse free survival, overall survival, and distant metastasis free survival. A survival curve is displayed, and the hazard ratio with 95% confidence intervals and logrank P value are calculated and displayed. Additionally, three subgroups of patients can be assessed: systematically untreated patients, endocrine-treated ER positive patients, and patients with a distribution of clinical characteristics representative of those seen in general clinical practice in the US. Web address: www.kmplot.com . We used this integrative data analysis tool to confirm the prognostic power of the proliferation-related genes TOP2A and TOP2B, MKI67, CCND2, CCND3, CCNDE2, as well as CDKN1A, and TK2. We also validated the capability of microarrays to determine estrogen receptor status in 1,231 patients. The tool is highly valuable for the preliminary assessment of biomarkers, especially for research groups with limited bioinformatic resources.
验证具有预后或预测价值的候选基因在适当功率的乳腺癌队列中至关重要。我们的目的是开发一个在线工具来绘制生存图，可以用来评估各种基因的表达水平在未治疗和治疗的乳腺癌患者的临床结果上的相关性。使用从 GEO（Affymetrix HGU133A 和 HGU133+2 微阵列）下载的基因表达数据和生存信息建立了一个背景数据库。中位无复发生存期为 6.43 年，1231 例中有 968 例雌激素受体（ER）阳性，1369 例中有 190 例淋巴结阳性。经过质量控制和标准化，仅保留了两种 Affymetrix 平台上都存在的探针（n = 22277）。为了分析特定基因的预后价值，根据基因的中位数（或上/下四分位数）表达将队列分为两组。可以根据无复发生存率、总生存率和远处无转移生存率对两组进行比较。显示生存曲线，并计算和显示风险比和 95%置信区间和对数秩 P 值。此外，还可以评估三组患者：系统未治疗患者、内分泌治疗 ER 阳性患者和临床特征分布代表美国一般临床实践的患者。网址：www.kmplot.com。我们使用这种综合数据分析工具来确认与增殖相关的基因 TOP2A 和 TOP2B、MKI67、CCND2、CCND3、CCNDE2 以及 CDKN1A 和 TK2 的预后能力。我们还验证了微阵列在 1231 例患者中确定雌激素受体状态的能力。该工具对于生物标志物的初步评估非常有价值，特别是对于具有有限生物信息学资源的研究小组。
