br cancer driving genes Sondka et
>700 cancer-driving genes (Sondka et al., 2018). Despite the dif-ferences in these estimates, these studies point to the vast reper-toire of targets available to the cell for tumor initiation and progression. In addition to the gene expression profiles, BafilomycinA1 remodeling is also altered in cancer, which modulates genome-wide enhancer sequences to either upregulate or repress genes (Chen et al., 2018). Such genomic alterations are seen not only in adult but also in pediatric tumors (Grobner et al., 2018; Ma et al., 2018), implicating DNA mutations and epigenetic changes in steering a normal cell into a malignant phenotype. Somatic muta-tions in driver genes are often instigated by predisposing germline variants, such as in BRCA1 and BRCA2, and impinge on 8 major cellular processes, with alterations in genes involved in maintain-ing genome integrity, such as the Fanconi anemia pathway, and in 10 signaling pathways (RTK/RAS, Nrf2, PI3K, TGFb, Wnt, Myc, TP53, cell cycle, Hippo, Notch) as being among the most commonly altered (Chae et al., 2016; Ding et al., 2018; Sanchez-Vega et al.,
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
2 A. Bacolla et al. / Progress in Biophysics and Molecular Biology xxx (xxxx) xxx
Abbreviations LAML acute myeloid leukemia
LGG brain lower grade glioma COSMIC Catalogue Of Somatic Mutations In Cancer LIHC liver hepatocellular carcinoma TCGA The Cancer Genome Atlas LUAD lung adenocarcinoma GRCh38/hg38 Genome Reference Consortium Human Build 38 LUSC lung squamous cell carcinoma
(GRCh38/hg38) MESO mesothelioma ACC adrenocortical carcinoma OV ovarian serous cystadenocarcinoma BLCA bladder urothelial carcinoma PAAD pancreatic adenocarcinoma BRCA breast invasive carcinoma PCPG pheochromocytoma and paraganglioma CESC cervical squamous cell carcinoma and endocervical PRAD prostate adenocarcinoma
adenocarcinoma READ rectum adenocarcinoma CHOL cholangiocarcinoma SARC sarcoma COAD colon adenocarcinoma SKCM skin cutaneous melanoma DLBC lymphoid neoplasm diffuse large B-cell lymphoma STAD stomach adenocarcinoma ESCA esophageal carcinoma TGCT testicular germ cell tumors GBM glioblastoma multiforme THCA thyroid carcinoma HNSC head and neck squamous cell carcinoma THYM thymoma KICH kidney chromophobe UCEC uterine corpus endometrial carcinoma KIRC kidney renal clear cell carcinoma UCS uterine carcinosarcoma KIRP kidney renal papillary cell carcinoma UVM uveal melanoma
Elucidating the mechanisms through which mutations arise is central to understanding and strategically targeting tumorigenesis. By extracting patterns of base changes in cancer genomes, ~30 distinct signatures have been catalogued (Forbes et al., 2015), which inform on molecular processes likely to lead to mutations from either extrinsic (ultraviolet light, smoking, chemicals) or intrinsic (APOBEC misediting, DNA repair deficiencies, defective polymerase ε) sources (Alexandrov et al., 2013; Helleday et al., 2014). Patterns of base substitutions have also been associated with direct damage to DNA bases by oxidants (Bacolla et al., 2013; Temiz et al., 2015), such as reactive oxygen and nitrogen species (ROS and RNS respectively) (Turrens, 2003), which rise in tumor cells following glucose deprivation, deregulation of the mitochon-drial electron transport chain and other organelles (endoplasmic reticulum, lysosomes and peroxisomes) (Gorlach et al., 2015; Panieri and Santoro, 2016).
In addition, recent research suggests that mutation loads arise as a secondary effect from oncogene-dependent transcriptional stimulation of transcription factors, which then activate genes responsible for uncontrolled replication (Kotsantis et al., 2016). This sustained proliferation contributes to a condition referred to as “replication stress”, a potent inducer of genomic instability (Hills and Diffley, 2014; Macheret and Halazonetis, 2015; Zheng et al., 2016) triggered by a buildup of ssDNA from RPA depletion (Toledo et al., 2017), the accumulation of DNA secondary structures, R-loops, collisions between replication and transcription (Hamperl and Cimprich, 2016; Wang and Vasquez, 2017), and other factors. Indeed, the formation of non-B DNA structures, such as cruciforms, triplexes, G4 structures and Z-DNA, has been reported to contribute in genomic instability (Bacolla et al., 2016; Georgakopoulos-Soares et al., 2018; Zhao et al., 2018), possibly following nuclease cleavage (Zhao et al., 2018) or replication fork collapse (Wang and Vasquez, 2017). In view of the relationships between non-B DNA-structure formation and impaired transcription and replication, we reasoned it would seem sensible to further explore the roles of DNA structure impacting transcription and of transcription profiling in cancer mutational loads.