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Do We Need to Realign Evidence-Based Versus Precision Medicine?

An interview with geneticist and pathologist Gabriel Bien-Willner, MD, PhD, FCAP, on why we need to change our outlook toward precision medicine in oncology.
Making a Career Choice
Gabe had always been deeply interested in genetics: “I found it fascinating, the ‘building blocks of our lives’ and, early on, I was particularly fascinated with the prospect of gene therapy—where at the time, in the mid-90s, it was thought that that was going to cure every disease. Of course, it didn’t turn out that way.” As he was considering medical schools, he decided to attend Baylor College of Medicine in Houston, Texas, because he believed that they had one of the best genetics departments in the world. Gabe completed both his medical training and his PhD in genetics and genomics at Baylor.

His initial work in genomics was with his mentor, James R. Lupski, MD, PhD, a member of the National Academy of Sciences, when they were presented with a patient who had been diagnosed with campomelic dysplasia. Gabe noted that campomelic dysplasia is “a very rare skeletal dysplasia that is typically caused by mutations in a gene called Sox9, and it ultimately became my thesis. Patients with mutations in the Sox9 gene develop skeletal dysplasia, because the gene is a transcription factor, meaning that it functions to turn on and off other genes and pathways in bone development. But,” he continued, “it is also important in sex development, so boys who have mutations in Sox9 can have sex reversal: they have XY [chromosomes], but their phenotype is female.” It was determined that this patient actually did not have any mutations of the Sox9 gene, so the patient was brought to their lab because they did work on chromosomal abnormalities and chromosomal rearrangements.

As Gabe explained, “It turned out that this patient had a translocation, meaning that the chromosomes are broken and then rearranged with other chromosomes about a million base pairs away from the Sox9 gene. So, I hypothesized that there were probably several enhancers or DNA elements that allow the proper activation of this transcription factor, Sox9, whose expression had to be maintained at a very steady level to function properly.  And so what was happening was that there were DNA elements upstream and downstream of this translocation breakpoint, and you were losing some of these elements—but not all of them, because the phenotype of this patient was not as severe as with others with mutations in this gene.”

Using novel computational methods and mouse models, Gabe was able to obtain evidence of rearrangements in these DNA elements—ie, enhancers—nearby. “One thing that concerned me was that I spent 4 years proving that there was an enhancer that was actually being activated by Hedgehog signaling, which was driving the expression of Sox9,” Gabe noted. [The hedgehog family of signaling molecules play a critical role in transmitting development signals.] “It took me 4 years to prove that there was 1 enhancer, but we speculated that there must be dozens of such regulators.” He believed that there had to be a way to determine where such enhancers were without the a priori knowledge he had in this case, ie, critical phenotypes and mouse models that gave him this evidence. “There had to be a way to figure out where these elements were. So that was my first foray into genomics,” Gabe explained.

“At the time, there was a very new technology that was just published by a group at the Sanger Institute that I thought could help me find these other elements.” This molecular cytogenetics team, led by Nigel Carter, DPhil, investigated methods to detect changes in the numbers of chromosomes and genes to learn more concerning the causes of particular inherited diseases in humans. Gabe explained that the new technology, called Chip on Chip, relied on using antibodies to capture proteins bound to the DNA elements of interest, which were then frozen. The “captured” DNA would then be hybridized against a microarray chip that included genomic regions of interest, in this case, the regions in Chromosome 17q. “When hybridized, you would see in the analysis where the DNA elements were located, therefore identifying all putative elements in a single experiment without bias.” However, he noted, the technology ultimately did not pan out for multiple reasons: “It wasn’t very scalable or reproducible, it didn’t really work very well at the time, but that was really the beginning of genomics and with DNA for me. And it was really essentially our first approach, not unlike microarray technology, to capture a lot of DNA or RNA information all at once, rather than in a very focused experiment like we’d always done in the past.”

He realized at the end of his PhD that folks who are geneticists tend to go into pediatrics to study the same kind of rare diseases that he was currently studying or perhaps internal medicine, but he found that he did not want to focus on very rare disease. Rather, he wanted to focus on common disease “and make an immediate impact in this space. My goal was to bring genetics and genomics into the clinical space. It always has been, and it still is.” He felt that the best way to accomplish this was in the cancer field through pathology. “There are 2 ways [to enter the field of cancer research]: one is through internal medicine and oncology, and the other is through pathology. Both pathologists and oncologists are experts in cancer, but they are experts in different ways. Oncologists are experts in the treatment of cancer, and pathologists are experts in the diagnosis of cancer, and they’re both experts in the biology of cancer.”

So that is the path that Gabe chose. When he became a resident, he decided to go to Washington University in St. Louis, known as one of the best training programs in this area. And right around that time, next-generation sequencing (NextGen Sequencing or NGS) was developed.  Also known as high-throughput sequencing, NGS enables researchers to sequence DNA and RNA much more quickly and inexpensively than Sanger sequencing, representing a paradigm shift that revolutionized the study of molecular biology and genomics. Gabe realized that this NextGen sequencing was a new method that would be transformative. “Even though the chemistry is almost essentially identical to Sanger sequencing,” he explained, “with NGS we’re turning a 2-dimensional process into a 3-dimensional one, where we can perform massively parallel sequencing and capture sufficient data, allowing us to draw conclusions independent of explicit a priori knowledge.” In addition to greatly reducing cost, it has dramatically increased the throughput of genomic sequencing, enabling simultaneous screening of thousands of genetic locations (loci) for disease-causing mutations. “Now we can sequence everything all at once if we want,” Gabe noted, “and figure out what you sequenced later.” 

Gabe subsequently decided to do a postdoc to learn NextGen sequencing in the lab of Robi Mitra, PhD, a new faculty member at Washington University’s Center for Genomic Sciences. While in the lab, Gabe learned computational methods and coding as well as how to use Unix (a multi-user computer operating system). As he emphasized, “To make sense of these data, you really had to create the software yourself, honestly: it really did not exist. If you needed to make some sort of analysis of NextGen sequencing results, you needed your own program to achieve this.” 

Gabe was influenced by the progress that was being made at Washington University, “including the launch of the Genomics and Pathology Services, where I believe we were the first academic institution to do a hybrid capture, a large gene panel with NextGen sequencing to capture this kind of information from patients. So, I got to be there for the development of that.”
Ultimately, he joined the faculty at Washington University, but did not stay there for long. Having multiple opportunities, he decided to enter industry and accepted a position as medical director for Molecular Health, which as noted previously, specializes in the development of analytic software and informatics approaches that are necessary to make sense of these complex data sets captured with NextGen sequencing.



 
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