In March 2011, Covance’s Seattle-based Genomics Laboratory (CGL) collaborated with the Institute for Systems Biology (ISB), also based in Seattle, to collectively unravel the complex regulation of gene expression in Glioblastoma Multiforme (GBM), one of the most common and aggressive forms of brain cancer. By applying Covance’s expertise in genomics and next-generation sequencing (NGS) with ISB’s expertise in complex genomics networks, the researchers’ goal is to gain a greater understanding of GBM. Since joining forces, CGL and ISB have made significant headway towards elucidating the genetic mechanisms behind GBM.
Although considerable efforts have been applied to unravel the complicated genetic background of GBM – the most common and malignant of all gliomas − it still has an average survival time of a little more than one year after diagnosis. Currently, the best available therapy for treating GBM consists of surgery, radiation, and chemotherapy. However, the survival time for those inflicted with GBM remains low due to its highly invasive and infiltrative nature, which makes complete eradication of the tumor via surgical resection challenging.
Over the past year, researchers from CGL and ISB have been studying the genetic differences within GBM and working on finding molecular targets that may enable researchers to select the right drug for the right patient. Since the ability to resolve complex regulatory networks requires reproducible, high-quality data, the researchers have been utilizing next-generation sequencing (NGS), which provides them an important dataset to investigate tumor heterogeneity and find targets for patient stratification and/or therapeutics. NGS technology, which is digital in nature and has a larger dynamic range compared to microarrays, has revolutionized the field of genomics by allowing investigation of the genomic aberrations associated with different cancers and other various diseases.
In February 2012, CGL and ISB researchers presented a preliminary results poster entitled “Optimizing Therapeutic Outcomes for Gliobastima Multiforme Leveraging Whole Exome Sequencing,” detailing their use of variant analysis data to identify variants that could effectively stratify GBM patients for response to the chemotherapy drug temozolomide (TMZ). Currently, the standard of care for GBM includes surgical resection followed by chemotherapy using TMZ.
However, treatment with TMZ is often problematic because the tumor generally recurs and is then resistant to the drug.
MGMT promoter methylation has been identified as a predictive biomarker of response to TMZ, but is not widely used due to lack of precision. For the study, researchers from CGL and ISB hypothesized that variants in MGMT, other methytranferases, mismatch repair or exclision repair genes and their respective causal networks could be useful in stratifying patients for response to TMZ. They then sought to identify variants that could effectively stratify GBM patients for TMZ response using variant analysis data. Following are their preliminary findings:
- Ingenuity Variant Analysis using RNA-Sequencing and Exome-Sequencing data provides markers to stratify response to TMZ therapy in GBM. These markers are being further validated.
- RNA-Sequencing data provides additional information by pinpointing expressed Single Nucelotide Variations (SNVs) missed in exome analysis.
- In addition to variant analysis, researchers used RNA-Sequencing data to identify gene signatures that can be used for patient stratification in GBM. The results of these analyses are presented in a separate paper.
The full poster can be viewed here.
All of the studies currently being conducted by CGL and ISB, and associated new discoveries, will lead to entirely new approaches to treat brain cancer. As the researchers integrate various datasets to look at all of the important aspects of GBM etiology, they are working to define how each plays a role in regulating different networks. By mining these networks, they will be able to identify gene signatures associated with different cell sub-types associated with GBM, which will be useful to identify and isolate different types of tumor-initiating cells from patients and target them for therapeutics. Those biomarkers can then be used in the clinic by physicians for personalized medicine.
Once all of the research is finished, the results of the analysis, along with the raw data, will be released to public databases and submitted for publication in a peer-reviewed scientific journal.
Click here for more info on Covance’s Genomics Laboratory.
Anup Madan, Ph.D., is Principal Scientist and Genomics/Sequencing Team Leader, Covance Genomics Laboratory. Anup played a key role in the sequencing of the human genome and made significant contributions to understanding the etiology of brain tumors. Anup received his Ph.D. in Biochemical Genetics from the Tata Institute of Fundamental Research in Mumbai, India and has been published in numerous peer-reviewed journals.
Sergey Stepaniants, Ph.D., is Head of Computational Biology, Covance Genomics Laboratory. Sergey received his M.S. from the Moscow Institute for Physics and Technology and his Ph.D. from the University of Rhode Island. Sergey has more than 15 years experience in genomics and genetics data analysis, focusing on biomarker/target discovery in pre-clinical and clinical experiments. Sergey has also been published in numerous peer-reviewed journals.