Research Department of Haematology, UCL Cancer Institute, University College London, London, UK.
PILAR Research Network, London, UK.
Pharmacogenomics J. 2021 Jun;21(3):390-401. doi: 10.1038/s41397-021-00217-9. Epub 2021 Mar 17.
Certain breast and ovarian cancers are characterised by high levels of chromosomal instability. We established a suite of eleven SNP array-based signatures of various forms of chromosomal instability. To understand what biological mechanisms might underpin these signatures, we generated and assembled genetic-feature data including allele-specific expression, fusion genes, gene expression, methylation, somatic coding mutations and protein expression. For each signature, we extracted a compendium of significantly associated genetic features using machine learning. We established an association between subchromosomal allelic imbalance-based measures and DNA repair genes. Numerical chromosomal instability and chromothripsis were found to have distinct genetic associations but shared a relationship to mitotic processes, while whole-genome doubling was characterised by TP53 mutation, and high AURKA and GINS1 expression. Furthermore, we identified two genetically distinct forms of tandem duplicator phenotypes. These findings identify potentially novel genomic targets for validation and drug development for specific subsets of breast and ovarian cancer.
某些乳腺癌和卵巢癌的特点是染色体不稳定性高。我们建立了一套基于 SNP 芯片的各种形式染色体不稳定性的特征签名。为了了解哪些生物学机制可能是这些特征的基础,我们生成并整合了包括等位基因特异性表达、融合基因、基因表达、甲基化、体细胞编码突变和蛋白质表达在内的遗传特征数据。对于每个特征签名,我们使用机器学习提取了一套与之显著相关的遗传特征。我们发现亚染色体等位基因失衡的指标与 DNA 修复基因之间存在关联。我们发现,染色体数目不稳定性和染色体重排具有不同的遗传关联,但都与有丝分裂过程有关,而全基因组加倍则与 TP53 突变和 AURKA 和 GINS1 表达升高有关。此外,我们还鉴定了两种具有不同遗传特征的串联重复表型。这些发现为特定乳腺癌和卵巢癌亚组的验证和药物开发确定了潜在的新的基因组靶标。