What usually comes to mind when we think about DNA is this thin strand of molecules with which the granite framework of life is clothed, but it is the main event to us. The story of DNA naturally appeals to the imagination; decades of research crack open an ages old code giving us the ability to regulate genetic disorders and destabilize tumor cells is a rare opportunity, to say the least. What has added to the level of wonder are new insights that are revealing, for the first time, exactly how drug resistance develops in targeted therapies, the signaling pathways involved in gene regulation, and other fundamental insights that shed light into the pathogenesis of cancer.
What usually comes to mind when we think about DNA is this thin strand of molecules with which the granite framework of life is clothed, but it is the main event to us. The story of DNA naturally appeals to the imagination; decades of research crack open an ages old code giving us the ability to regulate genetic disorders and destabilize tumor cells is a rare opportunity, to say the least. What has added to the level of wonder are new insights that are revealing, for the first time, exactly how drug resistance develops in targeted therapies, the signaling pathways involved in gene regulation, and other fundamental insights that shed light into the pathogenesis of cancer. Some of the more recent advances have happened - in large part - thanks to simultaneous advancements in computing analysis and the gene sequencing technique known as next generation sequencing (NGS). Both advancements have allowed researchers to create a comprehensive directory of genes involved in cancer pathogenesis.
New technology is driving the field to move from sequencing single genes using the Sanger method, toward integrating the mammothly massive paired-end sequencing, which researchers say is powerful enough to open innovations in the ways we target genes and how we analyze the information. Large-scale sequencing is the only technology that can reconstruct all the changes that occur in any given tumor [1,2].
Recent Advances In Cancer Biology
Studies on cancer genomes have greatly improved our understanding of how genes drive cancer. Studies of genes have revealed their mechanisms of action, and, in some cases, places a new context around well-understood signaling pathways. In many cases, genes that drive the progress of one type of cancer are involved with other cancers too. This led to the general suggestion, in clinical circles, that cancer may develop according to a particular group of driver genes as opposed to a particular organ site [3].
For example, gene NF1, first discovered in neurofibromatosis and also involved in pediatric myeloid neoplasms, was identified as a significantly mutated gene in glioblastoma multiforme [4]. Sometimes such genes are already targets of therapies, and their use against other cancers in clinical trials is straightforward [5]. Yet it lends credence to the importance for researchers to identify and understand cancer genes in the context of other cancer types.
The strong new ethic in cancer biology is that, in many cases, the genes that drive the development of one type of cancer are involved in causing other cancers too. This genetic heterogeneity, as it's known, is one of the main obstacles preventing researchers from discovering reliable, new cancer biomarkers and adds to the complexity of applying gene therapies in treatment plans, since they usually target a specific gene pathway. Nonetheless, DNA sequencing is important, if not crucial, since it often leads to the discovery of new actionable mutations, which can help researchers, stake the path on where the road to the cure should lead.
Novel Discoveries from Sequencing
The frequency of point mutations varies among patients with different cancers. At the low end range of point mutations are pediatric cancers with approximately 0.1 to 0.2 mutations per megabase pairs (Mb) of DNA, followed by adult renal cell carcinoma, adult leukemia and other solid tumors. Some patients surprisingly have none! This absence of any genetic alterations was recently referred to as the "dark matter" of the cancer genome [6].
So while not all mechanisms are clearly understood, the current consensus points to the disruption of normal developmental transcritption due to errors in the epigenetic programming [7]. Combining the genome-wide epigenetic profiles with transcriptional profiles could help shed light on this important issue.
Every single individual has a new and unique variation in the sequence of their DNA. Cancer researchers should be prepared to sequence the patient's normal genome, as well as, the tumor in order to clearly detect the somatic variation leading to cancer.
Identifying single nucleotide variants is the specialty of one sequencing technique, the power of the whole-exome sequencing (WES) is paving new boulevards of research creating lists of genes that were not previously associated with cancer (see Supplemental Table 1).
Other newer emerging technologies such as desktop sequencers and targeted gene capture is making NGS both feasible and affordable for the clinical cancer researcher.
Today, researchers have a set of choices when it comes to their approach to next-generation sequencing (NGS), techniques that include: whole-genome sequencing (WGS), whole-exome sequencing (WES), whole-transcriptome sequencing (RNA-seq), and amplicon-based deep sequencing, which can be flexibly adapted given your study goals (see Figure 1).
Image courtesy of: http://www.cancer.gov/newscenter/newsfromnci
Figure 1. Strategies for next-generation sequencing of cancer.
Image courtesy of: Nature Reviews Drug Discovery. 2013.
<http://www.nature.com/nrd/journal/v12/n5/full/nrd3979.html>
Whole-Genome Sequencing Sequencing the complete DNA sequence of an organisms genome is an effective way to identify mutations in the coding and non-coding regions of DNA, including small point substitutions and large structural rearrangements. Whole-Genome Sequencing (WGS) helps to characterize this spectrum of mutations across entire genomes. Read-coverage information can be used to infer DNA copy-number alterations, as well as the variant allelic faction information, e.g., the relative number of reads harboring a variant allele. WGS can also be used to infer the architecture of tumors. The paired read library brought about by WGS enables sensitive detection of structural rearrangements on the largest scales. WGS studies require (approximately) 60-fold redundancy of the tumor genome for adequate sensitivity, along with 30-fold redundancy of the normal genome. This translates to a total of 270 billion bases of DNA needed to characterize one tumor! Although the whole-genome sequence has been reported on a number of tumors already, it's still far from being routine, owing much to the high cost and massive data needed for processing and storage [8,9]. Whole-Exome Sequencing The introduction of whole-exome sequencing (WES) enabled an understanding of the coding exons in the genome targets that comprise a mere 1% of the entire genome. When compared with WGS, WES has the advantage of having being cheaper to run and you'll have an easier time managing the data. WES can be done for all genes, or for a select gene panel using NGS technologies. WES was the preferred method used by researchers in order to sift through multiple varieties of tumors collected from more than 100 patients between 2004 and 2013. (http://www.sanger.ac.uk/genetics/CGP/cosmic/papers/). WES also recently identified a new subgroup (10%) of endometrial cancer with an unusually high mutation rate (more than 100 mutations per Mb) [10]. Transcriptome Sequencing (RNA sequencing, or RNAseq) WGS and WES have been augmented by RNA-seq to explore alterations to the transcriptome. RNA-seq quantifies gene expression and can detect alternative splicing patterns, enriched isoforms, and transcribed fusion genes. Transcriptome sequencing can also express somatic mutations including any imbalances with their partner allele [11]. Gene Panel Sequencing To be widely used as a diagnostic tool in clinical laboratories, the ideal sequencing instrument will need to be rapid, simple, flexible, widely accessible, and affordable. It must also have excellent sensitivity and accuracy. In 2010, a semiconductor chip--based sequencing technology was developed and commercialized by Ion Torrent, a division of Life Technologies, Inc. It utilizes a small semiconductor chip to detect released hydrogen ions emitted during DNA polymerization. Using this technology, the AmpliSeq panel also allows for flexible design and sensitive detection of point mutations on targeted regions (L. Wang & D.A. Wheeler, unpublished data). Although the technology is still at the beginning of its developmental roadmap, it has been a pivotal technology that is rapidly advancing the output and accuracy of NGS over the past 3 years [12]. RNA Splicing Machinery Functional tests of the commonly recurrent mutation sites in U2AF1 demonstrated that they promote enhanced splicing and exon skipping in reporter assays in vitro. The findings implicate abnormalities of messenger RNA splicing in the pathogenesis of myelodysplastic syndrome and other human cancers [13]. This presents one of the most perplexing contributors to the biology of cancer because it's not clear exactly why RNA splicing defects seem to preferentially affect myeloid neoplasms and, also, why RNA splicing is impaired, which could potentially impact the expression of every gene in the cell, and would specifically contribute to cancer. FUTURE GLIMPSES Taken together, these findings reveal how the use of advanced NGS technologies is enabling researchers to obtain an in-depth understanding of cancer biology and to identify numerous new diagnostic, prognostic, and actionable biomarkers for managing cancer. Today, we know that cancer is far more complicated than imagined in 1973 with the discovery of the Philadelphia chromosome. While we are making dramatic inroads in the fight against cancer, the war on cancer is still being waged.Supplemental Table 1. New Cancer Genes Discovered by NGS
Image reprint permission of: OncLive, 2014. <http://www.onclive.com/>.
SOURCES Image (top) courtesy of: Thinkstock [1] Meyerson M, Gabriel S, Getz G. 2010. Advances in understanding cancer genomes through second-generation sequencing. Nature Reviews Genetics. 11:685-96. [2] Mwenifumbo JC, Marra MA. 2013. Cancer genome-sequencing study design. Nature Review Genetics. 14:321-32. [3,5,7] Simon R, Roychowdhury S. Implementing personalized cancer genomics in clinical trials. Nature Reviews Drug Discovery. 2013. 12:358-69. [4] Cancer Genome Atlas Res. NETW. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature. 2008. 455:1061-68. [6,9] Vogelstein B, Papdopoulos N, Velculescu VE, et al. 2013. Cancer genome landscapes. Science. 339:1546-58. [7,8,11,12] Garraway LA, Lander ES. 2013. Lessons from the cancer genome. Cell. 153:17-37. [10] The sequencing data came from TCGA Genome Data Analysis Center (https://confluence.broadinstitute.org/display/GDAC/Home). [13] Graubert T, Shen D, Ding L, et al. Recurrent mutations in the U2AF1 splicing factor in myelodysplastic syndromes. Nature Genetics. Dec 11, 2011; 44(1): 53-57.