So much as science is an art, it is really an art of seeing and hearing nature in its most minute form in any setting, big or small. Sometimes nature gives us clues in the many meticulous observations noted by scientists. Other times, the absence of any expected phenomenon can be just as enlightening to the researcher. This would be especially true for cancer researchers who have observed many types of pediatric and adult cancers that seem to occur spontaneously without any genetic alterations in their DNA! This event has been recently referred to as the dark matter of the cancer genome and is an indicator of how much we have yet to learn. But the knowledge we have accumulated over the past 40 years of human genetics is quite vast (see Figure 1) and has led to some staggering advancements in the war against cancer. This article will attempt to accumulate some of what we have learned in recent years, thanks to staggering advancements in next generation of sequencing (NGS).
Figure 1. Major Events in a decade of cancer genomics.
Image Description: (Dark blue) Major advances in massively parallel sequencing platforms and targeted enrichment technologies; (black) major large-scale projects designed to catalog genomic variations of normal human individuals; (red) milestones in cancer genomics;
ACRONYMN KEY: (dbSNP) Database of single nucleotide polymorphism; (HapMap) haplotype map of the human genome; (ENCODE) Encyclopedia of DNA Elements; (COSMIC) Catalog of Somatic Mutations in Cancer; (TCGA) The Cancer Genome Atlas; (GA) genome analyzer; (CRC) colorectal carcinoma; (WES) whole-exome sequencing; (ICGC) International Cancer Genome Consortium; (TSP) tumor sequencing project; (AML) acute myeloid leukemia; (WGS) whole-genome sequencing; (OSCC) ovarian small cell carcinoma. Image Published by Cold Spring Harbor Laboratory Press ©2013.
While the formation of tumors in many types of cancer appears to be driven by a single driver gene, most human cancers have genetic alterations within a much larger set of cancer genes. Across all cancers, genomic studies have identified hundreds of cancer driver genes, and the number continues to grow. Developing a gene therapy for cancer that can target specificaly mutated genes is a great challenge, principally impractical due to the difficulty of targeting genes, and still yet unproven without the compliment of stem cells to guide them to their target. Currently, all the known driver genes of cancer are classified into one or more of twelve core signaling pathways . An article published last year in the journal Science, advocates for the development of therapies that can broadly target downstream mediators, regulators, or key points in the disfunctional pathways.
Figure 2. Mutation Rates Across Cancer
Image/Research by: Mike Lawrence, Broad Institute of Harvard and MIT.
The exact mechanism of how tumors form in patients who do not display any genetic changes are not well understood, but it is now assumed that errors in the epigenetic instructions of developmental programs controlling transcription, metabolism, and chromatin remodeling lead to disruptions in genetic and cellular processes [2,3]. Genome-wide sequencing has helped to illuminate this important issue by shedding light on how the average rate of mutation between adult and pediatric cancers differs.
Research has shown that most pediatric tumors typically have anywhere from 0.1 to 0.2 mutations per mega base pair (Mb). Most adult cancers will have approximately 1 and 2 mutations per Mb, tenfold more than pediatric cancers, but is consistent with accumulated mutations within affected tissues across a lifetime . Adult tumors with a mutation frequency above 2 Mb, typically result from exposing one tissue type to known mutagens for long periods of time, notably UV radiation and tobacco leaf products. Also, adult cancers can have a mutation rate of 10 mutations per Mb, or higher, that usually seem to appear because of mutations that either hinder the DNA repair mechanism or completely silences the mismatched repair genes . Exceptional cases have shown tumors with mutation frequencies as high as 100 per Mb, or greater, and always seem to appear within the exonuclease domain of POLE, which codes for one of two DNA replication enzymes used by cells . Through the power of NGS we know, in particular, MLH1 is a key gene responsible for detecting errors in replication .
These mutation patterns are important because they may have exciting implications for the ways doctors diagnose and ultimately treat adult and pediatric cancers. Many types of pediatric cancers are reported to have a low rate of mutation, so DNA sequencing may be a less reliable means to understand the disease. Instead, clinicians say monitoring the symptoms from the gene expression data is more beneficial to the patient . Adult cancers with mutation rates greater than one mutation per Mb are seen as more likely to be driven by a mutation(s) in the genomic DNA, and is the main reason why DNA sequencing will continue to be a highly useful diagnostic tool.
Figure 3.Â Gene Archictecture of Cancer Risk
Image from: Cancer Genetics Overview, ©2014. http://www.cancer.gov/cancertopics/
A recent report in the Journal Nature, quite paradoxically, noted that cancers with the highest rate of mutation, with greater than 100 mutations per Mb, may have a better prognosis and, thus, need less aggressive therapy than their lower-rate counterparts . While the reason for this isn't clearly understood at the moment, two possibilities have been proposed. The first is that having an elevated mutation rate leads to a bigger immune response, enhanced by virtue of the many types of mutated proteins generated over a lifetime. The other possibility of having such a high mutation rate is that normal routine functions essential for cell survival become impaired. This causes the cells to die at a rate fast enough to make the formation of tumors not possible (see Figure 3) .
Mutation Frequency Leading to Breakthroughs in Many Cancers
Another pattern that emerged after the completion of the first whole-exome screening, in colon and breast cancers, is that one to three genes have repeat mutations in more than 20% of the tumors, later proven to be true for all cancers . The shoulder you see on the distribution map shows several genes that appear in about 10-20% of tumors . Then, finally it the long tail on the graph depicts gene mutations that appear with decreasing frequency in different types of cancer (see Figure 4).
Figure 4. Distribution of Mutation Frequencies
(This graph depicts the general finding of a low relative risk associated with common, low-penetrance genetic variants, such as single-nucleotide polymorphisms identified in genome-wide association studies, and a higher relative risk associated with rare, high-penetrance genetic variants, such as mutations in the BRCA1/ BRCA2 genes associated with hereditary breast and ovarian cancer and the mismatch repair genes associated with Lynch syndrome. Image/Caption courtesy of: http://www.cancer.gov/cancertopics/).
These lower frequency genes are another important clue helping us to better understand how tumors form. It's possible they code for a redundant mutation within a single signaling pathway, which could add to our understanding of how that pathway is used by the cancer cell. They can also reveal new pathways or processes, or how known genes are being affected. If the mutation driving the cancer happens to be within a downstream gene, well, that's just to illustrate the complexity of applying gene therapy, since typically it targets a specific pathway.
The ways in which we apply gene therapy going forward will become increasingly important since redundant mutations that occur within key pathways are an increasingly observed phenomenon in cancer genomes, which has also been revealed after decades of exome or genomic sequencing .
NOTABLE ORGANIZATIONS / USEFUL WEBSITESÂ
The Cancer Genome Atlas (TCGA), http://cancergenome.nih.gov/
the International Cancer Genome Consortium (ICGC)
the Cancer Genome Project, http://sanger.ac.uk/genetics/CGP/
Therapeutically Applicable Research to Generate Effective Treatments (TARGET), http://target.cancer.gov/
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