title: Integrating the multiple dimensions of genomic and epigenomic landscapes of cancer.
abstract: Advances in high-throughput, genome-wide profiling technologies have allowed for an unprecedented view of the cancer genome landscape. Specifically, high-density microarrays and sequencing-based strategies have been widely utilized to identify genetic (such as gene dosage, allelic status, and mutations in gene sequence) and epigenetic (such as DNA methylation, histone modification, and microRNA) aberrations in cancer. Although the application of these profiling technologies in unidimensional analyses has been instrumental in cancer gene discovery, genes affected by low-frequency events are often overlooked. The integrative approach of analyzing parallel dimensions has enabled the identification of (a) genes that are often disrupted by multiple mechanisms but at low frequencies by any one mechanism and (b) pathways that are often disrupted at multiple components but at low frequencies at individual components. These benefits of using an integrative approach illustrate the concept that the whole is greater than the sum of its parts. As efforts have now turned toward parallel and integrative multidimensional approaches for studying the cancer genome landscape in hopes of obtaining a more insightful understanding of the key genes and pathways driving cancer cells, this review describes key findings disseminating from such high-throughput, integrative analyses, including contributions to our understanding of causative genetic events in cancer cell biology.
authors.affiliation: Genetics Unit - Department of Integrative Oncology, British Columbia Cancer Research Centre, Vancouver, BC, Canada. rchari@bccrc.ca
authors.forename: Raj
authors.initials: R
authors.lastname: Chari
authors.forename: Kelsie L
authors.initials: KL
authors.lastname: Thu
authors.forename: Ian M
authors.initials: IM
authors.lastname: Wilson
authors.forename: William W
authors.initials: WW
authors.lastname: Lockwood
authors.forename: Kim M
authors.initials: KM
authors.lastname: Lonergan
authors.forename: Bradley P
authors.initials: BP
authors.lastname: Coe
authors.forename: Chad A
authors.initials: CA
authors.lastname: Malloff
authors.forename: Adi F
authors.initials: AF
authors.lastname: Gazdar
authors.forename: Stephen
authors.initials: S
authors.lastname: Lam
authors.forename: Cathie
authors.initials: C
authors.lastname: Garnis
authors.forename: Calum E
authors.initials: CE
authors.lastname: MacAulay
authors.forename: Carlos E
authors.initials: CE
authors.lastname: Alvarez
authors.forename: Wan L
authors.initials: WL
authors.lastname: Lam
mesh_terms: D000818:Animals; D044127:Epigenesis, Genetic / Q000235:genetics / Q000502:physiology*; D020869:Gene Expression Profiling / Q000379:methods; D023281:Genomics / Q000379:methods* / Q000639:trends; D057166:High-Throughput Screening Assays / Q000379:methods; D006801:Humans; D008954:Models, Biological; D009369:Neoplasms / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods; D015398:Signal Transduction / Q000235:genetics; D018511:Systems Integration