Discovery of cancer common and specific driver gene sets

Abstract

Cancer is known as a disease mainly caused by gene alterations. Discovery of mutated driver pathways or gene sets is becoming an important step to understand molecular mechanisms of carcinogenesis. However, systematically investigating commonalities and specificities of driver gene sets among multiple cancer types is still a great challenge, but this investigation will undoubtedly benefit deciphering cancers and will be helpful for personalized therapy and precision medicine in cancer treatment. In this study, we propose two optimization models to de novo discover common driver gene sets among multiple cancer types (ComMDP) and specific driver gene sets of one certain or multiple cancer types to other cancers (SpeMDP), respectively. We first apply ComMDP and SpeMDP to simulated data to validate their efficiency. Then, we further apply these methods to 12 cancer types from The Cancer Genome Atlas (TCGA) and obtain several biologically meaningful driver pathways. As examples, we construct a common cancer pathway model for BRCA and OV, infer a complex driver pathway model for BRCA carcinogenesis based on common driver gene sets of BRCA with eight cancer types, and investigate specific driver pathways of the liquid cancer lymphoblastic acute myeloid leukemia (LAML) versus other solid cancer types. In these processes more candidate cancer genes are also found.

DriverFinder: A Gene Length-Based Network Method to Identify Cancer Driver Genes

“…With rapid advances in high-throughput sequencing technologies, some large-scale cancer genomics projects, such as The Cancer Genome Atlas (TCGA) [1] and International Cancer Genome Consortium (ICGC) [2], have produced different omics data including a rich dataset of whole-exome and RNA sequence data [3,4], which provides chances to allow us to accurately infer tumorspecific alterations [5] and help in precision medicine in cancers treatment [6,7]. However, many of genetic changes represent neutral variations that do not contribute to cancer development which are called passenger mutations [6,8].…”

Molecular and Cell Biological Considerations in the Initiation and Development of Sporadic Non-Hereditary Solid Cancers

“…It is a co-occurrence of common MDPs and individual-specific MDPs [74,78]. Hoadley et al [89] found similarity among driver gene sets across distinct cancer types.…”

“…According to Zhang and Zhang [78] genes (N= 2-11) necessary to convert a single normal cell into a cancer cell [77].…”

CDPath: Cooperative Driver Pathways Discovery Using Integer Linear Programming and Markov Clustering

“…Maximization of the weight function is defined as the maximum weight submatrix problem, which is originally solved by Markov Chain Monte Carlo (MCMC) method [12], and then addressed by an exact binary linear programming (BLP) model [13]. Zhang et al [14] proposed two optimization models to de novo separately discover common driver gene sets among multiple cancer types (ComMDP) and specific driver gene sets of a particular cancer (SpeMDP). However, these methods focus on single pathways or modules [12]- [14], they can not clarify how various cellular and physiological processes are coordinately altered during the initiation and progression of cancer.…”