Rob Miani joined the MMRF team as Chief Financial Officer in 2016. Most recently he was the Vice President of Finance and Corporate Controller of Aptuit, LLC, a global contract research organization providing integrated early discovery to mid-phase drug development services in the pharmaceutical industry. Rob has over 20 years of leadership experience in the private and public sectors, holding managerial positions in the renewable energy, private equity, Internet and technology industries, including Davenport Newberry, Oak Investment Partners and INT Media Group. He began his career with Arthur Anderson LLP in the Assurance and Business Advisory Services Division. Rob is a CPA and received his BS degree in Accounting from Fairfield University.
MMRF CoMMpass Study Data Featured at AACR 2019
The 2019 American Association for Cancer Research (AACR) meeting took place March 29 -April 3 in Atlanta. This gathering of over 20,000 cancer clinicians and researchers featured four presentations made possible by researchers using data from our CoMMpass Study, which is the largest genomic dataset in all of cancer. CoMMpass continues to be an invaluable resource for investigators to use to test new hypotheses and accelerate precision medicine treatments into the clinic for all myeloma patients. Below are summaries of the four CoMMpass Study presentations:
Analysis of CoMMpass genomic data has revealed 12 subtypes of myeloma. Myeloma also occurs more frequently in males and in African Americans. A group from the Translational Genomics Research Institute (TGen) analyzed the data from 607 CoMMpass patients to look at the contribution of variations in normal DNA sequences in this increase in incidence. They found
- Differences in gene expression associated with sex and ethnicity
- Differences in gene expression associated with overall myeloma patient survival
These differences are important because they provide further evidence of how understanding gene changes can help researchers develop targeted therapies that provide exactly the right treatment to each myeloma patient based on their type of myeloma.
Differences in gene expression in different myeloma patients has been associated with how well patients respond to certain treatments and how long patients may remain in remission. A group of Italian researchers led by Drs. Carolina Terragna and Michele Cavo examined the gene changes in 700 CoMMpass patients and found that the presence of 2 particular changes
- 13q loss (deletion)
- 1q gain (amplification)
may be sufficient to predict outcomes in MM patients . Patients who had both of these alterations spent less time in remission and their disease progressed faster, leading to poorer outcomes. The ability to predict which patients are at high risk to progress more quickly may enable patients with these alterations to be treated with more aggressive therapy at the outset of their disease, and may lead to improved outcomes.
Researchers at Emory University presented 2 important studies fueled by CoMMpass data. The first, led by Dr. Ben Barwick of Emory and co-authored by our own CSO, Dr. Daniel Auclair, described how a genetic change known as “DNA methylation” differs in myeloma cells compared to normal cells. He found that
- in myeloma cells, levels of DNA methylation are lower (only 41%) compared to normal blood cells (71%-89%).
- this “hypomethylation”, or reduced methylation, predicted poor outcomes for these patients.
Reduced methylation is often associated with myeloma cells growing faster, which can lead to shorter periods in remission. They also found that methylation levels differed in samples taken when patients were newly diagnosed compared to samples taken when the patient relapsed, and this again correlated with poor outcome. Differences in methylation between patients is yet another indication of how myeloma is different in every patient and how each patients treatment should be tailored for their specific type of myeloma.
The second Emory study, led by Dr. Sagar Lonial and others, looked into ways to determine which myeloma patients might benefit most from receiving venetoclax, a therapy which is already approved for use in other cancers and may be effective in myeloma patients with a t(11:14) translocation. They found that
- Patients whose myeloma cells were resistant to treatment with venetoclax had higher activity of a metabolic enzyme called SQR.
- Patients whose myeloma cells had lower activity of SQR were sensitive to the venetoclax treatment.
- Patients who were treated with Farydak, an approved therapy in myeloma, were also sensitive to venetoclax, because Farydak caused activity of SQR to decrease in their myeloma cells.
In this way, SQR was shown to be a “biomarker” for patients who are sensitive to venetoclax; in other words, a simple biological test would be able to determine SQR activity in patients, and therefore whether their myeloma might be sensitive to venetoclax, before giving them treatment.
As the leader in precision medicine in myeloma, we are proud that the data from our CoMMpass Study is helping researchers discover differences between the types of myeloma each patient has, and how these differences can help pinpoint effective therapies. Finding a cure for each and every patient will only happen by collecting as much patient data as possible, and making it freely available for researchers to examine, for clues on how myeloma cells grow and how to stop them. As the largest genomic dataset in all of cancer, our CoMMpass Study is providing the data necessary to do exactly that.
