br Of the top anticorrelations low expression of PIGR and
Of the 10 top anticorrelations, low expression of PIGR and SPATA18 in LUAD was associated with poor survival. The polymeric immunoglobulin receptor (the PIGR gene product) pIgR plays an important role in protecting small airways of the lung from airborne antigens and microorganisms (Richmond et al., 2016); PIGR /- mice develop chronic obstructive pulmonary disease (COMP)-like pathology with age and persistent activation of innate immune response to the lung microbiome (Richmond et al., 2016). Loss of PIGR is an early event in lung tumorigenesis (Ocak et al., 2012), and it is plausible that the association of low PIGR with high mutation rates we observe reflects a role for the ensuing inflammation in mutagenesis, in part through the release of ROS and reactive nitrogen intermediates (Grivennikov et al., 2010). The product of SPATA18, usually referred to as Mieap, is a target of TP53 and has a role in mitochondria. In lung adenocarcinoma Mieap evidently cooperates with BNIP3 and an activated-truncated form of VDAC1 to achieve HIF-dependent cellular 740 Y-P and fitness to hypoxia conditions through mitochondrial hyperfusion (Brahimi-Horn et al., 2015), as well as in mitochondrial regenera-tion that entail reduction of ROS buildup (Miyamoto et al., 2011; Nakamura et al., 2012). Thus, our analyses support the concept that SPATA18 downregulation would increase mutation loads through the Warburg effect.
4.2.2. Positive correlations
The clearest insight implicating functional connections between gene expression and mutation was the finding that the top 10 strongest co-correlations identified genes highly overexpressed in most, if not all, tumor types, with high expression being linked to poor survival. The association of these genes with the cell cycle is supported by prior analyses of TCGA data sets (Buccitelli et al., 2017; Peng et al., 2015), and is in line with the idea that tumorigenesis is sustained by hyperactivity in cell growth and cell division. The transcription factor V-Myb avian myeloblastosis viral oncogene homolog-like 2 (the product of MYBL2) plays a critical role in cell cycle progression, cell survival and cell proliferations (Musa et al., 2017), by activating many genes including CENPA, KIF2C and KIFC1. Our survival analyses add to the number of tumor types in
Please cite this article as: Bacolla, A et al., Cancer mutational burden is shaped by G4 DNA, replication stress and mitochondrial dysfunction, Progress in Biophysics and Molecular Biology, https://doi.org/10.1016/j.pbiomolbio.2019.03.004
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which MYBL2 overexpression has been associated with decreased survival (reviewed in (Musa et al., 2017)). A causal association be-tween MYBL2 expression and mutation loads has recently been reported, and involves transactivation of the APOBEC3B gene (Chou et al., 2017) whose product (apolipoprotein B mRNA cytosine deaminase, A3B) generates ectopic C > U > T transitions and genomic hypermutation when overproduced (Burns et al., 2013).
The strong correlation of the SDH accessory factor SDHAF3 with mutations was of particular interest since a germline c.157T > C (p.Phe53Leu) substitution in this gene was recently associated with increased prevalence of familiar and sporadic pheochromocytoma and paraganglioma, which are characteristic of SDH-deficiency (Dwight et al., 2017). Mechanistically, SDHAF3 plays an indispens-able role, together with the other 3 accessory factors (SDHAF1,2,4), in the maturation of the SDH complex, by promoting the insertion of FeeS clusters into the SDHB subunit and by protecting the SDH complex from superoxide-related oxidative damage (Dwight et al., 2017; Na et al., 2014). The fundamental importance of FeeS clusters and control of superoxide support the observed connections of the SDHB subunit with mutational load (Fuss et al., 2015; Perry et al., 2010). Under low concentrations of SDHAF3, or any other SDH component, SDH activity is expected to decrease, resulting in high levels of ROS, the Warburg effect (Tseng et al., 2018) and an accu-mulation of succinate, a competitive inhibitor of a large number of a-ketoglutarate-dependent enzymes (Xiao et al., 2012). Succinate buildup would then lead to activation of the HIF-1a pathway (Laurenti and Tennant, 2016), a hypermethylator phenotype (Aldera and Govender, 2018), and a suppression of the homologous recombination DNA repair pathway (Sulkowski et al., 2018). Thus, anticorrelation between SDHAF3 expression and mutations may stem from SDH deficiency.
Our clustering results are intriguing, both from a tumor classi-fication perspective and from a mechanistic standpoint. The clus-tering encompassing KICH, LUAD, PRAD and LGG is centered on cell cycle, DNA replication and DNA repair genes, and the positive correlations with mutations likely arise from replication stress (Hamperl and Cimprich, 2016; Hills and Diffley, 2014; Kotsantis et al., 2016; Macheret and Halazonetis, 2015), excessive DNA damage (such as A3B activation) and its escape from repair. The second cluster comprising STAD, THCA and CHOL revolves on genes coding for complexes I e V of the mitochondrial respiratory chain. One electron oxidation and charge transfer reactions in DNA are suggested to promote base substitutions (Bacolla et al., 2013; Suarez-Villagran et al., 2018; Temiz et al., 2015). Thus, we propose that the association of mitochondrial gene expression with muta-tions likely stems from direct damage to DNA by increased ROS and other oxidants. Thus, our analysis implicates cell cycle/DNA repair and mitochondrial dysfunction as two main branches through which gene expression is linked to somatic mutation in cancer.