Project description:As the field of translational 'omics has progressed, refined classifiers at both genomic and proteomic levels have emerged to decipher the heterogeneity of breast cancer in a clinically-applicable way. The integration of 'omics knowledge at the DNA, RNA and protein levels is further expanding biologic understanding of breast cancer and opportunities for customized treatment, a particularly pressing need in clinically triple negative tumors. For this group of aggressive breast cancers, work from multiple groups has now validated at least four major biologically and clinically distinct omics-based subtypes. While to date most clinical trial designs have considered triple negative breast cancers as a single group, with an expanding arsenal of targeted therapies applicable to distinct biological pathways, survival benefits may be best realized by designing and analyzing clinical trials in the context of major molecular subtypes. While RNA-based classifiers are the most developed, proteomic classifiers proposed for triple negative breast cancer based on new technologies have the potential to more directly identify the most clinically-relevant biomarkers and therapeutic targets. Phospho-proteomic data further identify targetable signalling pathways in a unique subtype-specific manner. Single cell profiling of the tumor microenvironment represents a promising way to allow a better characterization of the heterogeneity of triple negative breast cancer which could be integrated in a spatially resolved context to build an ecosystem-based patient classification. Multi-omic data further allows in silico analysis of genetic and pharmacologic screens to map therapeutic vulnerabilities in a subtype-specific context. This review describes current knowledge about molecular subtyping of triple negative breast cancer, recent advances in omics-based genomics and proteomics diagnostics addressing the diversity of this disease, key advances made through single cell analysis approaches, and developments in treatments including targeted therapeutics being tested in major clinical trials.

Project description:Introduction: CHEK2 is a moderate penetrance breast cancer risk gene, whose truncating mutation 1100delC increases the risk about two fold. We pursued to investigate gene copy number aberrations and gene expression profiles that are typical for breast tumors of CHEK2 1100delC mutation carriers. Materials and methods: A total of 126 breast tumor tissue specimens including 32 samples from patients carrying CHEK2 1100delC were studied in array comparative genomic hybridization (aCGH) and gene expression experiments (GEX). After dimensionality reduction with CGHregions R package, CHEK2 1100delC associated regions in the aCGH data were detected by Wilcoxon rank sum test. Linear model was fitted to GEX data with R package limma. Genes whose expression levels were associated with CHEK2 1100delC mutation were detected by Bayesian method. Results: We discovered four lost and three gained CHEK2 1100delC related loci. These include losses of 1p13.3-31.3, 8p21.1-2, 8p23.1-2 and 17p12-13.1 as well as gains of 12q13.11-3, 16p13.3 and 19p13.3. Twenty-eight genes located on these regions showed differential expression between CHEK2 1100delC and other tumors nominating them as candidates for CHEK2 1100delC associated tumor progression drivers. These included CLCA1 on 1p22 as well as CALCOCO1, SBEM and LRP1 on 12q13. Altogether 188 genes were differentially expressed between CHEK2 1100delC and other tumors. Of these, 144 had elevated and 44 lowered expression levels. Our results suggest WNT pathway as a driver of tumorigenesis in breast tumors of CHEK2 1100delC mutation carriers and a role for the olfactory receptor protein family in cancer progression. Differences in the expression of the 188 CHEK2 1100delC associated genes divided breast tumor samples from three independent datasets into two groups that differed in their relapse-free survival time. Conclusions: We have shown that copy number aberrations of certain genomic regions are associated with CHEK2 mutation 1100delC. On these regions we have identified potential drivers of CHEK2 1100delC associated tumorigenesis, whose role in cancer progression is worth investigating. Furthermore, poorer survival related to the CHEK2 1100delC gene expression signature highlights pathways that are likely to have a role in the development of metastatic disease in carriers of CHEK2 1100delC mutation.

Dataset Information

Recurrent and pathological gene fusions in breast cancer: current advances in genomic discovery and clinical implications.

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Recurrent and pathological gene fusions in breast cancer: current advances in genomic discovery and clinical implications.

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