Abstract
Large-scale tumor genome sequencing projects have revealed a complex landscape of genomic mutations in multiple cancer types. A major goal of these projects is to characterize somatic mutations and discover cancer drivers, thereby providing important clues to uncover diagnostic or therapeutic targets for clinical treatment. However, distinguishing only a few somatic mutations from the majority of passenger mutations is still a major challenge facing the biological community. Fortunately, combining other functional features with mutations to predict cancer driver genes is an effective approach to solve the above problem. Protein lysine modifications are an important functional feature that regulates the development of cancer. Therefore, in this work, we have systematically analyzed somatic mutations on seven protein lysine modifications and identified several important drivers that are responsible for tumorigenesis. From published literature, we first collected more than 100,000 lysine modification sites for analysis. Another 1 million non-synonymous single nucleotide variants (SNVs) were then downloaded from TCGA and mapped to our collected lysine modification sites. To identify driver proteins that significantly altered lysine modifications, we further developed a hierarchical Bayesian model and applied the Markov Chain Monte Carlo (MCMC) method for testing. Strikingly, the coding sequences of 473 proteins were found to carry a higher mutation rate in lysine modification sites compared to other background regions. Hypergeometric tests also revealed that these gene products were enriched in known cancer drivers. Functional analysis suggested that mutations within the lysine modification regions possessed higher evolutionary conservation and deleteriousness. Furthermore, pathway enrichment showed that mutations on lysine modification sites mainly affected cancer related processes, such as cell cycle and RNA transport. Moreover, clinical studies also suggested that the driver proteins were significantly associated with patient survival, implying an opportunity to use lysine modifications as molecular markers in cancer diagnosis or treatment. By searching within protein-protein interaction networks using a random walk with restart (RWR) algorithm, we further identified a series of potential treatment agents and therapeutic targets for cancer related to lysine modifications. Collectively, this study reveals the functional importance of lysine modifications in cancer development and may benefit the discovery of novel mechanisms for cancer treatment.
Highlights
Somatic mutations have a crucial role in the regulation of cancer progression, and interpreting the functional consequences of somatic mutations on gene products will be essential for developing potential targets for cancer therapies
Of the 12 selected cancer types, we observed that uterine corpus endometrial carcinoma carried the largest number of lysine modification-related mutations in its samples, and more than 33.8% of the modification sites were mutated in this cancer type (Figure 1E)
These results demonstrated that abnormal lysine modification is a general mechanism of cancer cell regulation, implying its functional importance in different cancer types
Summary
Somatic mutations have a crucial role in the regulation of cancer progression, and interpreting the functional consequences of somatic mutations on gene products will be essential for developing potential targets for cancer therapies. Recent research has revealed that the ubiquitination of AR at position K311 is critical for its proper function, regulating both AR protein stability and AR transcriptional activity When such an ubiquitination site loses its function, the expression of over a thousand downstream genes will be altered, possibly leading to misregulation in chromatin organization, cellular adhesion, motility, and signal transduction (McClurg et al, 2016). In this regard, the annotation of known cancer mutations based on the effects on lysine modification and the discovery of novel lysine modification-related drivers may be important for providing potential guidance in the development of new therapeutic strategies and drugs for cancer patients
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