Somatic gene mutations in cancers occur randomly but a significant unresolved question is how selective mutations are retained. Retention is in part determined by fitness traits such as overcoming barriers to proliferation or immune surveillance that confer an adaptation to the tumor microenvironment. Our proposal tests a new idea on fitness traits and adaptation contributing to retention of gene mutations in cancers. This new idea is based on the conserved trait of most cancers having a higher intracellular pH (pHi 7.5-7.6) than normal cells (pHi 7.1-7.2). We predict that selective somatic mutations confer gain or loss of pH sensing that provides an adaptive advantage to the higher pHi of cancers. To limit the scope and risk of testing this new idea we will focus on Arg>His mutations in cancers with the prediction that these mutations encode a gain of pH sensing. Our specific hypothesis is that increased pHi in cancers confers an adaptive advantage for retention of selective arginine to histidine mutations. Our preliminary analysis reveals a higher incidence of Arg>His mutations than expected from codon bias, including CpG mutational effects. Our prediction on gain of pH sensing by Arg>His mutations is based on histidine having a pKa near neutral in solution and hence can be protonated at the pHi of normal cells and uncharged at the higher pHi of cancer cells. In contrast, because Arg has a pKa ~12 it likely remains charged at the pHi of normal and cancer cells.
In Aim 1 we test evolutionary forces for retention of histidine mutations by using bioinformatics approaches. We will develop novel bioinformatics techniques for ranking Arg>His somatic mutations, and characterize the historical and contemporaneous evolutionary forces operating at these positions to quantify mutational biases and determine the extent to which pKa altering His mutations are retained in cancers relative to what would be expected across evolutionary timescales.
In Aim 2 we experimentally test recurring Arg>His candidate mutations for gain of pH sensing. We will determine pH-dependent functions of wild type and mutant proteins in vitro and in normal and transformed clonal cells. We also will computationally predict pKa's of mutated histidines and arginines and test pH-dependent conformational changes in protein structure using molecular dynamics simulations. To our knowledge mutations in cancers conferring pH sensing, such as p53-R273H, one of the most commonly occurring mutations we will test, has not been reported, nor has the retention of somatic mutations relative to the higher pHi of cancers. If correct, our hypothesis would generate a substantial new view on why some somatic mutations in cancers are retained. Additionally, successfully confirming our hypothesis would be compelling for future studies to test His>Arg mutations for loss of pH-sensing, and mutations involving tyrosine, serine and threonine residues that have pKa's near neutral when phosphorylated. Hence, our findings could be applied broadly and have substantial impact on therapeutic strategies to target pH dependence of mutations driving cancers.

Public Health Relevance

Most somatic mutations in cancers are random but selective mutations are often retained because they confer a fitness trait to the cancer cell or tumor microenvironment. We will test a new idea that histidine mutations can generate changes in protein pH sensing to confer a fitness trait adapted to the higher intracellular pH of cancer cells Our expected outcome is a substantial new view on why some somatic mutations are retained. Moreover, our hypothesis could be applied broadly to substantially impact new therapeutic approaches to limit progression of cancers from different tissue origins and genetic backgrounds.

National Institute of Health (NIH)
Exploratory/Developmental Grants (R21)
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Special Emphasis Panel (ZCA1)
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Okano, Paul
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University of California San Francisco
Anatomy/Cell Biology
Schools of Dentistry/Oral Hygn
San Francisco
United States
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Szpiech, Zachary A; Hernandez, Ryan D (2014) selscan: an efficient multithreaded program to perform EHH-based scans for positive selection. Mol Biol Evol 31:2824-7
Uricchio, Lawrence H; Hernandez, Ryan D (2014) Robust forward simulations of recurrent hitchhiking. Genetics 197:221-36