Martins Filipe C, Santiago Ines de, Trinh Anne, Xian Jian, Guo Anne, Sayal Karen, Jimenez-Linan Mercedes, Deen Suha, Driver Kristy, Mack Marie, Aslop Jennifer, Pharoah Paul D, Markowetz Florian, Brenton James D
Genome Biol. 2014 Dec 17;15(12):526. doi: 10.1186/s13059-014-0526-8.
TP53 and BRCA1/2 mutations are the main drivers in high-grade serous ovarian carcinoma (HGSOC). We hypothesise that combining tissue phenotypes from image analysis of tumour sections with genomic profiles could reveal other significant driver events.
Automatic estimates of stromal content combined with genomic analysis of TCGA HGSOC tumours show that stroma strongly biases estimates of PTEN expression. Tumour-specific PTEN expression was tested in two independent cohorts using tissue microarrays containing 521 cases of HGSOC. PTEN loss or downregulation occurred in 77% of the first cohort by immunofluorescence and 52% of the validation group by immunohistochemistry, and is associated with worse survival in a multivariate Cox-regression model adjusted for study site, age, stage and grade. Reanalysis of TCGA data shows that hemizygous loss of PTEN is common (36%) and expression of PTEN and expression of androgen receptor are positively associated. Low androgen receptor expression was associated with reduced survival in data from TCGA and immunohistochemical analysis of the first cohort.
PTEN loss is a common event in HGSOC and defines a subgroup with significantly worse prognosis, suggesting the rational use of drugs to target PI3K and androgen receptor pathways for HGSOC. This work shows that integrative approaches combining tissue phenotypes from images with genomic analysis can resolve confounding effects of tissue heterogeneity and should be used to identify new drivers in other cancers.
TP53和BRCA1/2突变是高级别浆液性卵巢癌(HGSOC)的主要驱动因素。我们假设,将肿瘤切片图像分析的组织表型与基因组图谱相结合,可能会揭示其他重要的驱动事件。
对TCGA HGSOC肿瘤的基质含量进行自动估计并结合基因组分析表明,基质对PTEN表达的估计有很大偏差。使用包含521例HGSOC病例的组织芯片在两个独立队列中检测肿瘤特异性PTEN表达。通过免疫荧光检测,第一个队列中77%的病例出现PTEN缺失或下调,通过免疫组织化学检测,验证组中这一比例为52%,并且在针对研究地点、年龄、分期和分级进行调整的多变量Cox回归模型中,PTEN缺失或下调与较差的生存率相关。对TCGA数据的重新分析表明,PTEN半合子缺失很常见(36%),并且PTEN表达与雄激素受体表达呈正相关。在TCGA数据以及第一个队列的免疫组织化学分析中,低雄激素受体表达与生存率降低相关。
PTEN缺失是HGSOC中的常见事件,并且定义了一个预后明显更差的亚组,这表明针对HGSOC合理使用靶向PI3K和雄激素受体途径的药物。这项工作表明,将图像中的组织表型与基因组分析相结合的综合方法可以解决组织异质性的混杂效应,并且应用于识别其他癌症中的新驱动因素。