Department of Urology, Federal Armed Forces Hospital, Hamburg, Germany.
BJU Int. 2012 Jul;110(2 Pt 2):E14-20. doi: 10.1111/j.1464-410X.2011.10778.x. Epub 2012 Jan 13.
Treatment options for testis cancer depend on the histological subtype as well as on the clinical stage. An accurate staging is essential for correct treatment. The 'golden standard' for staging purposes is CT, but occult metastasis cannot be detected with this method. Currently, parameters such as primary tumour size, vessel invasion or invasion of the rete testis are used for predicting occult metastasis. Last year the association of these parameters with metastasis could not be validated in a new independent cohort. Gene expression analysis in testis cancer allowed discrimination between the different histological subtypes (seminoma and non-seminoma) as well as testis cancer and normal testis tissue. In a two-stage study design we (i) screened the whole genome (using human whole genome microarrays) for candidate genes associated with the metastatic stage in seminoma and (ii) validated and quantified gene expression of our candidate genes (real-time quantitative polymerase chain reaction) on another independent group. Gene expression measurements of two of our candidate genes (dopamine receptor D1 [DRD1] and family with sequence similarity 71, member F2 [FAM71F2]) examined in primary testis cancers made it possible to discriminate the metastasis status in seminoma. The discriminative ability of the genes exceeded the predictive significance of currently used histological/pathological parameters. Based on gene expression analysis the present study provides suggestions for improved individual decision making either in favour of early adjuvant therapy or increased surveillance.
To evaluate the usefulness of gene expression profiling for predicting metastatic status in testicular seminoma at the time of first diagnosis compared with established clinical and pathological parameters.
Total RNA was isolated from testicular tumours of metastasized patients (12 patients, clinical stage IIa-III), non-metastasized patients (40, clinical stage I) and adjacent 'normal' tissue (n = 36). The RNA was then converted into cDNA and real-time quantitative polymerase chain reaction was run on 94 candidate genes selected from previous work. Normalised gene expression of these genes and histological variables, e.g. tumour size and rete testis infiltration, were analysed using logistic regression analysis.
Expression of two genes (dopamine receptor D1 [DRD1] and family with sequence similarity 71, member F2 [FAM71F2], P = 0.005 and 0.024 in separate analysis and P = 0.004 and 0.016 when combining both genes, respectively) made it possible to significantly discriminate the metastasis status. Concordance increased from 77.9% (DRD1) and 72.3% (FAM71F2) in separate analysis and up to 87.7% when combining both genes in one model. Only primary tumour size in separate analysis (continuous or categorical with tumour size >6 cm) was significantly associated with metastasis (P = 0.039/P = 0.02), but concordance was lower (61%). When we combined tumour size with our two genes in one model there was no further statistical improvement or increased concordance.
Based on gene expression analysis our study provides suggestions for improved individual decision making either in favour of early adjuvant therapy or increased surveillance.
评估基因表达谱分析在预测睾丸精原细胞瘤首次诊断时的转移状态方面的作用，与现有的临床和病理参数相比。
从转移性患者（12 例，临床分期 IIa-III）、非转移性患者（40 例，临床分期 I）和相邻“正常”组织（n = 36）的睾丸肿瘤中分离总 RNA。然后将 RNA 转化为 cDNA，并对从先前工作中选择的 94 个候选基因进行实时定量聚合酶链反应。使用逻辑回归分析对这些基因的归一化基因表达和组织学变量（例如肿瘤大小和 rete testis 浸润）进行分析。
两种基因（多巴胺受体 D1[DRD1]和家族与序列相似性 71，成员 F2[FAM71F2]）的表达使得能够显著区分转移状态。在单独分析中，一致性分别增加到 77.9%（DRD1）和 72.3%（FAM71F2），当将两个基因合并到一个模型中时，一致性增加到 87.7%。仅在单独分析中，原发性肿瘤大小（连续或分类，肿瘤大小>6cm）与转移显著相关（P=0.039/P=0.02），但一致性较低（61%）。当我们将肿瘤大小与我们的两个基因结合到一个模型中时，没有进一步的统计改善或一致性增加。
基于基因表达分析，我们的研究为改善个体决策提供了建议，无论是赞成早期辅助治疗还是增加监测。
