Genomic Instability and Mutations

2019 John A. Catanzaro

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Introduction

Genomic instability is a hallmark of cancer cells primarily effecting cell division. This is not a single gene event, there are multiple genes that initiate, control and regulate tumor suppressor function and cell division. Surveillance is a key control integrated in many multi-functions and mechanisms including DNA damage checkpoint, DNA repair machinery and mitotic checkpoint. I will be elaborating on the stages of DNA surveillance and repair and demonstrate how defects in the regulation of any of these mechanisms often results in genomic instability, which predisposes the cell to malignant transformation.

Genomic Stability

Genomic stability is essential in cell maintenance and integrity. Errors in DNA replication, endogenous genotoxic stress such as reactive oxygen species (ROS) from cellular metabolism, and exogenous carcinogen insults; for example, ultraviolet light, ionizing radiation or DNA damaging chemicals are just some of the elements that create DNA replication breaks. It is established that tumor cells are inherently unstable in comparison to normal cells. Tumor initiation and progression results from the altercations of DNA replication. The genomic instability provides individuals a shorter cell cycle and/or an advantage of bypassing intracellular and immunological control systems. DNA alteration give cancerous cells a growth advantage and are selectively malignantly transformed cells.

Genomic instability includes variations of increased frequencies of base pair mutation, microsatellite instability (MSI) and chromosome number or structure changes, which is also called chromosome instability (CIN)(Al-Sohaily et al. 2012, Roschke and Kirsch 2010).

Frequency of Base Pair Mutations

Loss of functional DNA repair genes is a key feature of base pair mutations found in hereditary cancers. For example, hereditary MYH-associated polyposis, biallelic germline mutations in MYH, a DNA base excision repair (BER) gene, results in increased G•C to T•A transversion frequencies and cancer (Al-Tassan et al. 2002).

Cancer is a multi-factorial process, however, cancer cell mutation load, tumor initiation and progression through genomic instability has obvious relation to loss of gene function as seen in mutator phenotypes and relation to oncogene initiation and induced DNA replication stress.

Microsatellite Instability

Microsatellites (MSI) are nucleotide repeats, repetitive motifs of 1 to 6 nucleotides, scattering widespread the human genome (Ellegren 2004). MSI has been detected in many solid malignancies. Colorectal, stomach, endometrial, ovarian cancer and various solid tumors demonstrate MSI patterns. MSI is also observed in non small cell lung cancer but the prognosis with this pattern is poor.

“Microsatellite integrity in the genome is believed to be maintained by the mismatch repair (MMR) system, which corrects single base mismatches and insertion-deletion loops on the nascent DNA strand (Kunkel 1995). It is generally accepted that MSI is largely attributable to the failure of repairing insertion-deletion loops arising from replication slippage (Genschel et al. 1998).” Yao Y, Dai W. Genomic Instability and Cancer. J Carcinog Mutagen. 2014;5:1000165.

Chromosomal Instability (CIN)

This feature of cancer cell mutation and tumor progression has been studied for many decades as a hallmark feature, however, there is much uncertainty in its relation to early process or final transformation process in cancer evolution. Chromosomal instability is a manifest of genome instability with complexities that require careful attention to individual gene control features specific to the cancer cell mutation, tumor microenvironment and surrounding moiety. Karyotypic features are often misleading at best. WES and genome analysis are essential in identifying key cancer specific expressed features but these are not fool proof. Careful integrated analytics featuring immunogenetic and immunocentric engineering are innovations that can process and matriculate vast data sets and algorithms.

DNA Checkpoint and Repair Mechanisms

The p53 network is known as a crucial induction pathway involved in cancer defense. Activated p53 induces programmed cell death (apoptosis) or senescence as a last attempt to avoid possible malignant transformation when the damage is too severe and beyond repair. It is known to halt cancer cell proliferation and the propagation of DNA damage and can also initiate DNA repair mechanisms. This system detects oncogenic stress and initiates defense and regulatory immune sequences to prevent further high grade mutation, tumor progression and proliferation.

DNA damage predisposes normal cells and transforms into cancer cell mutations with expression of antigenic determinants related to cancer cell life cycle initiation and survival. Therefore, there are multiple conserved pathways within cells that respond to such errors by recruiting DNA repair processes or initiating apoptosis. The mechanisms of DNA repair is closely coupled with the DNA damage response (DDR), which involves the recruitment and localization within distinct nuclear foci of DNA damage sensors, mediators, transducers and effector proteins (Polo and Jackson 2011).

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DNA Repair Pathways

There are several key repair pathways and I will give brief attention and leave it to you to further explore.

  • NER: The nucleotide excision repair (NER) involves more than 25 proteins that function to replace modified nucleotides with the correct ones (Mitchell et al. 2003).
  • BER: The base excision repair (BER) mechanism is based on replacement of the modified bases via deamination, methylation, and oxidation with the correct ones (Lindahl 1974).
  • MMR: The mismatch repair (MMR) system especially functions in removing base mismatches formed by exogenous and endogenous agents that cause base deamination, oxidation, and methylation.
  • DSBR: DNA double strand breaks are repaired by the DNA double strand break repair (DSBR) system. There are two major DSB repair pathways, one is called nonhomologous end joining (NHEJ), in which broken DNA strand ends are ligated by specific ligase enzymes; the other is called homologous repair (HR).
  • GGR: GGR pathway functions by repairing nearly all damaged sites in the whole genome. This pathway is in the NER schema.
  • TCR: TCR is solely involved in removal of the lesions that block the transcription of the constitutively expressed genes (Tornaletti and Hanawalt, 1999). This pathway is in the NER schema.
  • DAR: Differentiation-associated repair (DAR) also part of the NER schema. (Nouspikel et al. 2006)
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An immunocentric model considers and engineers for a better adaptive model realizing that genetic stability at best is configured for an optimal cost-benefit relationship; meaning natural selection is not expected to have produced the best genetic stability available in the human body, but only the best compromise of DNA repair and the cost of these systems. In tissues where proliferation rates are critical, such as the colon epithelium, any repair mechanism that delays cell division might be disadvantageous for the function of that organ. The model proposed by Breivik and Gaudernack postulates that in some tissues during some conditions, the cost of DNA repair might exceed the cost of errors (Breivik and Gaudernack 1999, 2004).

Mitotic Controls

“Surveillance mechanisms termed checkpoints that monitor completion of essential molecular and cellular processes of one stage before entering another. The mitotic checkpoint monitors the completion of bi-orientation attachment of spindle microtubules to all condensed chromosomes before initiation of nuclear division during mitosis. A number of conserved proteins have been identified and characterized that are required for the checkpoint function. These proteins include Bub1, Bub3; Mad1, Mad2 and Mad3 (Cahill et al. 1998, Hoyt et al. 1991, Li R. and Murray 1991, Olesen et al. 2001, Weiss and Winey 1996).” https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4274643/

Telomere Maintenance

Cancer cells and tumor cells exhibit a high rate of telomere loss even with high levels of telomerase. A critical feature of the spontaneous telomere loss in cancer cell lines is that it occurs at a low enough frequency so that the cells do not die. Telomere loss contributes to chromosome instability and tumor cell progression (Fouladi et al. 2000, Lo et al. 2002, Sabatier et al. 2005). Cancer cells and tumors at high proliferation rate can successfully maintain the length of their telomeres, most often through the expression of telomerase,

DNA Methylation and Histone Modification

Epigenetic change alone is enough to dramatically alter functional proteins in genome integrity maintenance. Hypermethylation and/or hypomethylation of promoter or first exon of cancer related genes (tumor suppressor genes or oncogenes) may mimic the effect of mutations. Inflammatory mediation has a profound effect on expressed hypermethylation and / or hypomethylation and can induce both proliferative and regressive effects on cancer cell bearing expressed related antigens and in the tumor microenvironment.

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This side by side comparison demonstrates the effects of both hypermethylation and hypomethylation in normal and cancer cells. Transcription activation and inactivation are key effects on exon stability.

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Summary

Genomic instability and expressed mutations of cancer related molecular proteins and protein segments provide expansive precision profiling of the controls briefly discussed in this article. The Cancer Hallmark Analytic and Immunocentric model integrates and networks the pivotal multi-functions in the cancer evolution, adaptation and defense schema.

Patient Analysis using Cancer Hallmark Analytics and Immunocentrics profiles key multifunctions:

  1. Patient Extrinsic / Intrinsic Risk Index (EIRI)
  2. WES Patient / Cancer / Tumor (WESCT)
  3. Telomere Integrity (TI)
  4. Cancer Cell Mutation Rate (CCMR)
  5. Cancer Cell Migration Load (CCML)
  6. Cancer Cell Proliferation Index (CCPI)
  7. Tumor Mutation Rate (TMR)
  8. Tumor Migration Load (TML)
  9. Tumor Proliferation Index (TPI)
  10. Inflammation / Immune Cell Stress (IICS)
  11. Cancer Cell / Tumor Antigen Mapping (CCTAM)
  12. Patient HLA Matched Immunogenic Mapping (HLA-MIM)
  13. Precision Immunogenic Vaccine Mapping (PIVM)
  14. Patient Product Development Schema (PPDS)
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Cancer Hallmark Analytics

Development of a patient-centered immunocentric model requires network integration. In molecular science, we spark off of brilliant minds doing brilliant work. In short, this system is an innovation that takes the patient’s medical historical data, identifies risk related to cancer type and rates the risk, acquires the patient cancer sample liquid or solid biopsy (blood, saliva, tumor, urine, etc) and moves downstream to analysis and product development within weeks of first acquiring the sample.

John A. Catanzaro is CEO of Neo7logix, a bioscience company that designs precision and personalized treatment designs. www.neo7logix.com

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