How can identical twins, with the same genetic makeup, experience different diseases? Scientists believe this is due to epigenetic marks or chemical tags that play a role in controlling the activities of genes. The study of the epigenetic landscape has already generated recent breakthroughs in the detection, treatment and prognosis of many diseases, including cancer.
These breakthroughs are due in part to large-scale mapping efforts of cancer genomes coupled with the rapidly dropping costs of high-throughput next-generation sequencing technologies. Identification of mutations and epigenetic analysis are the next frontier for finding reliable biomarkers and developing targeted therapies.
Next-generation sequencing platforms are particularly powerful for mutational and epigenetic studies due to their ability to quickly analyze the entire genome through multiple methods of sequencing, such as DNA, RNA, miRNA, whole genome, exome, targeted, ChIP-Seq, methylome and epigenome. As a result, researchers obtain comprehensive, clinically relevant data sets.
With these resulting data, computational biologists can mine both open source data sets along with data sets from clinical trials to narrow down options for prospective biomarkers.
Capitalizing on the increased sensitivity of the platforms, Covance Genomics Laboratory has proven experience with the development of custom panels for personalized medicine. High-throughput assays are now cheaper to run and boast a shorter turnaround time, in some cases as little as one day.
CGL recently developed a mutation detection panel for p53, a well-known tumor suppressor protein that is involved in preventing cancer. In this specific project, CGL faced the difficult task of analyzing thousands of bases in a tumor genome to determine mutational analysis of the gene p53 in treated samples.
Using next-generation sequencing, CGL provided a quick turnaround time of five days for this assay for specific treatment requiring known mutational status of p53. Previous “traditional methods” were not as robust and did not have enough of the required coverage that next-generation sequencing provides. The resulting data can be used to include or exclude patients from a clinical trial. Additionally, this assay has the potential for future clinical diagnostics.
Identifying mutations and stratifying diseases
As this new era of mapping individual heterogeneity and diseases is explored, panels must be developed to identify the genes and epigenetic markers associated with diseases and corresponding drug treatments.
Traditionally, biomarker detection would start with identifying mutations associated with the cancer, because different mutations could be targeted with specific drugs. To stratify the disease, epigenetic information can very specifically characterize a disease to suggest a course of action.
Once a tumor is stratified genomically, researchers can obtain a better understanding of which gene mutations program certain molecular subtypes. Certain genes may have active roles in controlling cell growth, while others can have a more indirect role in the disease by modulating the activity of other genes. Knowing the biological basis of a tumor’s variability by identifying multiple mutations can indicate its genetic heterogeneity or lack thereof.
Diagnostic Potential – Screening for Genetic Variations and Epigenetic Markers
Beyond basic research and preclinical development, one could imagine the impact of personalized panels in patient care. Suppose that, with a sample of blood, patients could be screened for genetic variations and epigenetic markers, such as methylations. Recent research already shows this proof of principle by capturing and sequencing DNA from plasma as an alternative or a complementary approach to identifying mutations with invasive biopsies.
In healthy patients, personalized panels could spur early preventative action to promote healthy lifestyle changes. Or with presented diseases, physicians could identify the markers or mutations associated with the relapse to recommend targeted medicines, better predict survival rates or further study the affects of previous treatments.
For these advancements to progress from discovery to the clinic, CGL’s genomics experts can harness the knowledge and expertise within the larger Covance network. With worldwide access to laboratories and clinical samples, CGL can deliver critical patient data—from tumor samples to results. An additional partnership with Ingenuity Systems allows Covance Genomics Laboratory to manage, analyze and easily share large data sets with clients.
Starting with very low input samples, CGL is able to offer high-resolution mutation analysis and RNA sequencing with the quality and reproducibility of its CLIA-certified laboratory.
Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA. Muhammed Murtaza, Sarah-Jane Dawson, Dana W. Y. Tsui, Davina Gale, Tim Forshew, et al. Nature 497, 108-112 doi:10.1038/nature12065
Muhammed Murtaza, Sarah-Jane Dawson, Dana W. Y. Tsui, Davina Gale, Tim Forshew, et al. Non-invasive analysis of acquired resistance to cancer therapy by sequencing of plasma DNA. Nature 2013 May 2;497(108-112). Doi: 10.1038/nature 12065. Epub 2013 Apr 7.