We analysed whole genome sequences of 560 breast cancers to advance understanding of the driver mutations conferring clonal advantage and the mutational processes generating somatic mutations. 93 protein-coding cancer genes carried likely driver mutations. Some non-coding regions exhibited high mutation frequencies but most have distinctive structural features probably causing elevated mutation rates and do not harbour driver mutations. Mutational signature analysis was extended to genome rearrangements and revealed 12 base substitution and six rearrangement signatures. Three rearrangement signatures, characterised by tandem duplications or deletions, appear associated with defective homologous recombination based DNA repair: one with deficient BRCA1 function; another with deficient BRCA1 or BRCA2 function; the cause of the third is unknown. This analysis of all classes of somatic mutation across exons, introns and intergenic regions highlights the repertoire of cancer genes and mutational processes operative, and progresses towards a comprehensive account of the somatic genetic basis of breast cancer.

Technological advances have led to the introduction of next-generation sequencing (NGS) platforms in cancer investigation. NGS allows massive parallel sequencing that affords maximal tumor genomic assessment. NGS approaches are different, and concern DNA and RNA analysis. DNA sequencing includes whole-genome, whole-exome, and targeted sequencing, which focuses on a selection of genes of interest for a specific disease. RNA sequencing facilitates the detection of alternative gene-spliced transcripts, posttranscriptional modifications, gene fusion, mutations/single-nucleotide polymorphisms, small and long noncoding RNAs, and changes in gene expression. Most applications are in the cancer research field, but lately NGS technology has been revolutionizing cancer molecular diagnostics, due to the many advantages it offers compared to traditional methods. There is greater knowledge on solid cancer diagnostics, and recent interest has been shown also in the field of hematologic cancer. In this review, we report the latest data on NGS diagnostic/predictive clinical applications in solid and hematologic cancers. Moreover, since the amount of NGS data produced is very large and their interpretation is very complex, we briefly discuss two bioinformatic aspects, variant-calling accuracy and copy-number variation detection, which are gaining a lot of importance in cancer-diagnostic assessment.

Purpose:In an effort to additionally determine the global patterns of CpG island hypermethylation in sporadic breast cancer, we searched for aberrant promoter methylation at 10 gene loci in 54 primary breast cancer and 10 breast benign lesions.Experimental Design: Genomic DNA sodium bisulfate converted from benign and malignant tissues was used as template in methyl-specific PCR for BRCA1, p16, ESR1, GSTP1, TR␤1, RAR␤2, HIC1, APC, CCND2, and CDH1 genes.Results: The majority of the breast cancer (85%) showed aberrant methylation in at least 1 of the loci tested with half of them displaying 3 or more methylated genes.The highest frequency of aberrant promoter methylation was found for HIC1 (48%) followed by ESR1 (46%), and CDH1 (39%). Similar methylation frequencies were detected for breast benign lesions with the exception of the CDH1 gene (P ‫؍‬ 0.02). The analysis of methylation distribution indicates a statistically significant association between methylation of the ESR1 promoter, and methylation at CDH1, TR␤1, GSTP1, and CCND2 loci (P < 0.03). Methylated status of the BRCA1 promoter was inversely correlated with methylation at the RAR␤2 locus (P < 0.03).Conclusions: Our results suggest a nonrandom distribution for promoter hypermethylation in sporadic breast cancer, with tumor subsets characterized by aberrant methylation of specific cancer-related genes. These breast cancer subgroups may represent separate biological entities with potential differences in sensitivity to therapy, occurrence of metastasis, and overall prognosis.

A recent comprehensive whole genome analysis of a large breast cancer cohort was used to link known and novel drivers and substitution signatures to the transcriptome of 266 cases. Here, we validate that subtypespecific aberrations show concordant expression changes for, for example, TP53, PIK3CA, PTEN, CCND1 and CDH1. We find that CCND3 expression levels do not correlate with amplification, while increased GATA3 expression in mutant GATA3 cancers suggests GATA3 is an oncogene. In luminal cases the total number of substitutions, irrespective of type, associates with cell cycle gene expression and adverse outcome, whereas the number of mutations of signatures 3 and 13 associates with immune-response specific gene expression, increased numbers of tumour-infiltrating lymphocytes and better outcome. Thus, while earlier reports imply that the sheer number of somatic aberrations could trigger an immune-response, our data suggests that substitutions of a particular type are more effective in doing so than others.