Molecular insights from genome and systems biology are influencing how cancer is diagnosed and treated.,We critically evaluate big data challenges in precision medicine.,The melanoma research community has identified distinct subtypes involving chronic sun-induced damage and the mitogen-activated protein kinase driver pathway.,In addition, despite low mutation burden, non-genomic mitogen-activated protein kinase melanoma drivers are found in membrane receptors, metabolism, or epigenetic signaling with the ability to bypass central mitogen-activated protein kinase molecules and activating a similar program of mitogenic effectors.,Mutation hotspots, structural modeling, UV signature, and genomic as well as non-genomic mechanisms of disease initiation and progression are taken into consideration to identify resistance mutations and novel drug targets.,A comprehensive precision medicine profile of a malignant melanoma patient illustrates future rational drug targeting strategies.,Network analysis emphasizes an important role of epigenetic and metabolic master regulators in oncogenesis.,Co-occurrence of driver mutations in signaling, metabolic, and epigenetic factors highlights how cumulative alterations of our genomes and epigenomes progressively lead to uncontrolled cell proliferation.,Precision insights have the ability to identify independent molecular pathways suitable for drug targeting.,Synergistic treatment combinations of orthogonal modalities including immunotherapy, mitogen-activated protein kinase inhibitors, epigenetic inhibitors, and metabolic inhibitors have the potential to overcome immune evasion, side effects, and drug resistance.
We characterized the mutational landscape of human skin cutaneous melanoma (SKCM) using data obtained from The Cancer Genome Atlas (TCGA) project.,We analyzed next-generation sequencing data of somatic copy number alterations and somatic mutations in 303 metastatic melanomas.,We were able to confirm preeminent drivers of melanoma as well as identify new melanoma genes.,The TCGA SKCM study confirmed a dominance of somatic BRAF mutations in 50% of patients.,The mutational burden of melanoma patients is an order of magnitude higher than of other TCGA cohorts.,A multi-step filter enriched somatic mutations while accounting for recurrence, conservation, and basal rate.,Thus, this filter can serve as a paradigm for analysis of genome-wide next-generation sequencing data of large cohorts with a high mutational burden.,Analysis of TCGA melanoma data using such a multi-step filter discovered novel and statistically significant potential melanoma driver genes.,In the context of the Pan-Cancer study we report a detailed analysis of the mutational landscape of BRAF and other drivers across cancer tissues.,Integrated analysis of somatic mutations, somatic copy number alterations, low pass copy numbers, and gene expression of the melanogenesis pathway shows coordination of proliferative events by Gs-protein and cyclin signaling at a systems level.