Splicing mutation analysis reveals previously unrecognized pathways in lymph node-invasive breast cancer

Abstract

Somatic mutations reported in large-scale breast cancer (BC) sequencing studies primarily consist of protein coding mutations. mRNA splicing mutation analyses have been limited in scope, despite their prevalence in Mendelian genetic disorders. We predicted splicing mutations in 442 BC tumour and matched normal exomes from The Cancer Genome Atlas Consortium (TCGA). These splicing defects were validated by abnormal expression changes in these tumours. Of the 5,206 putative mutations identified, exon skipping, leaky or cryptic splicing was confirmed for 988 variants. Pathway enrichment analysis of the mutated genes revealed mutations in 9 NCAM1-related pathways, which were significantly increased in samples with evidence of lymph node metastasis, but not in lymph node-negative tumours. We suggest that comprehensive reporting of DNA sequencing data should include non-trivial splicing analyses to avoid missing clinically-significant deleterious splicing mutations, which may reveal novel mutated pathways present in genetic disorders.

Genomic signatures for paclitaxel and gemcitabine resistance in breast cancer derived by machine learning

“…Multi‐gene analytical approaches have previously been successful in deriving prognostic gene signatures for metastatic risk stratification (Oncotype DX™, MammaPrint ® ), subtypes (PAM50), and efforts have been made to predict chemotherapy resistance (Hess et al., 2006; Hatzis et al., 2011). Given the complexity of genomic changes and the fundamental biological differences among the intrinsic subtypes of breast cancer (Cancer Genome Atlas Network, 2012; Dorman et al., 2014), this approach has advantages over analysis of isolated genes. Reasonable gene signatures associated with breast cancer outcome can be obtained by chance alone (Venet et al., 2011), however our results show that such signatures are especially rare.…”

“…biological differences among the intrinsic subtypes of breast cancer (Cancer Genome Atlas Network, 2012;Dorman et al, 2014), this approach has advantages over analysis of isolated genes. Reasonable gene signatures associated with breast cancer outcome can be obtained by chance alone (Venet et al, 2011), however our results show that such signatures are especially rare.…”

Aberrant RNA splicing in cancer; expression changes and driver mutations of splicing factor genes

“…However, in a separate study of breast cancers, extensive aberrant splicing associated with splice site mutations of the target genes was found. 77 These seemingly conflicting results highlight the need for continued efforts to elucidate the genome-wide aberrant splicing patterns in cancer.…”

SomaticTP53Mutations in the Era of Genome Sequencing

“…Genome-wide splicing mutation analysis has identified TP53 as the gene most commonly affected by splicing mutation in BC (continued) (B, top) Codon distribution of mutations (missense, nonsense, and indels) in the coding sequence of TP53, based on mutation data derived from integrated genomic studies compiled in the Whole Genomes Resource (v73) of the COSMIC mutation database (cancer.sanger.ac.uk/cosmic/signatures), showing the position of major hotspots (.2% of all mutations) and mini hotspots (1%-2% of all mutations). (Bottom) Codon distribution of missense and nonsense mutations based on studies using conventional targeted sequencing approaches and compiled from the International Agency for Research on Cancer (IARC) TP53 mutation database (version R.13, 2008(version R.13, [Olivier et al 2010 (Dorman et al 2014). However, significant somatic variations occur in TP53 introns at sites other than those implicated in splice junctions, which are not covered in many conventional or exome-sequencing programs and thus are not reported in mutation databases.…”