Nov. 30, 2018

The Paper of the Month for November 2018 is "Functional genomic landscape of acute myeloid leukaemia" published in Nature. This project was led by Jeffrey Tyner, Ph.D., associate professor of cell, developmental and cancer biology, OHSU School of Medicine, and researcher with the OHSU Knight Cancer Institute. Its authors include Dr. Brian Druker, Dr. Shannon McWeeney, Dr. Cristina Tognon, Daniel Bottomly, Dr. Beth Wilmot, Dr. Stephen Kurtz and others. (See full author list in the citation below.)

Acute myeloid leukemia, or AML, has a low survival rate: less than 25 percent of newly diagnosed patients survive beyond five years. Developing effective, targeted AML therapies has proved challenging because AML is not a single disease, but a disease of many types. Consequently, the standard of care has largely remained unchanged for the past 40 years.

To move the needle, a team of OHSU researchers and others around the country launched an ambitious project in 2013 to perform a truly comprehensive analysis of the disease. Five years and 672 patient samples later, the team has published the largest cancer dataset of its kind for AML.

Study design

The driving question behind the project was this: "What does the drug sensitivity profile look like for a large cohort of primary AML patient samples, and can we make predictions about genomic biomarkers of drug sensitivity?" said Dr. Tyner.

Broadly, the team sought to understand the genomic sequencing and molecular make-up of these samples, as well as information on how tumor cells respond to various drugs in laboratory screenings.

Unconnected prior studies had established the genomic landscape of AML, and Dr. Tyner and colleagues had previously developed a functional drug sensitivity test that they applied to primary samples from patients with various hematological malignancies, including AML.

"We wanted to apply this drug sensitivity test to a large cohort of AML patient samples while also determining the genetic subgroups to which each sample belonged," said Dr. Tyner. "By integrating data, we hoped to understand drug sensitivity profiles that are specific to certain genetic subsets of AML."

Deep in the data

The sheer amount of data garnered from these samples begged a logistical question: once you have all this data, how do you go about sharing it with the research community in a meaningful way? The study's co-corresponding author, Shannon McWeeney, Ph.D., and her team led the data coordination, analysis and modeling for the project. A major contribution to the study was their development of a new data visualization platform called Vizome.  

"The flood of high-throughput, multi-dimensional data has the potential to overwhelm scientists and clinicians, isolating them from knowledge discovery," Dr. McWeeney said. "This necessitates a new generation of scientific computing approaches and strategies to manage, integrate and visualize the data, fueling exploration. Vizome allows anyone to explore these data, ask questions, and start pursuing answers."

Clinical answers

Yet it's the specific clinical and functional information – including how tumor cells from 409 of the samples responded to 122 different targeted therapies – that sets this study apart from other datasets that have been published to date, Dr. Tyner said.

"We found many novel correlations of drug sensitivity with various genetic subsets of AML," he said. "It establishes a framework for which we can prioritize cutting-edge drugs and drug combinations for clinical testing in specific genetic subsets of AML."

He added, "When you have clinical information that is well integrated with research data, you can ask more questions of the data. Let's say a physician sees an AML patient with a particular gene mutation. With the lab screening information we have, our dataset can be useful to see if that particular gene mutation corresponds with certain drug sensitivities. We believe this dataset will help researchers and physicians solve those specific kinds of questions more easily."

True team effort

The OHSU team is quick to acknowledge the contributions of collaborators across the country. Representatives from 10* academic medical centers played key roles in collecting and analyzing the 672 samples of cancer cells from 562 patients. Pharmaceutical, biotech, and technology companies, 14 in total, also contributed to the effort, by supplying drugs for testing, collaborating on analyses, or facilitating data sharing.

Druker lab scientific director Cristina Tognon, Ph.D., was a co-first author on the paper and led coordination efforts among the various contributors. "The strength of the consortium really helped drive the project," Dr. Tognon said. "It took everyone working together to achieve this goal. We couldn't have done this alone."

Dr. Brian Druker, co-corresponding author, says this data could rapidly advance clinical trials evaluating potential AML treatments. "The real power comes when you start to integrate all that data, and we're just starting to scratch the surface of what we can do," Dr. Druker said. "The ability to analyze what drug worked, and why it worked, helps lay the foundation for planning clinical trials to test new therapies in the patients who are most likely to respond."

Dr. Druker says this study is a prime example of AML research underway as part of a multi-institution collaboration called the Beat AML initiative, sponsored by the Leukemia & Lymphoma Society, or LLS. The OHSU Knight Cancer Institute is one of several cancer institutes across the country partnering with LLS to seek new treatments for the disease.

"This paper shows the power of bringing together basic scientists, computationalists and clinicians to address a challenging and clinically significant problem," said Mary Heinricher, Ph.D., associate dean for basic research, OHSU School of Medicine.

Next steps for the project will feature three areas of focus. Researchers are planning clinical trials to test and hopefully validate predictions of drug sensitivity. The team will also undertake mechanistic work to understand why certain drugs work better in certain genetic backgrounds. Finally, researchers will continue to expand the sample cohort and test new drugs.

*Participating Academic Medical Centers

• University of Texas Southwestern Medical Center
• Huntsman Cancer Institute at the University of Utah
• Stanford University
• University of Colorado Cancer Center
• University of Miami Sylvester Comprehensive Cancer Center
• Fox Chase Cancer Center
• National Cancer Institute
• University of Florida
• The University of Kansas Cancer Center

Pictured above: OHSU researchers who contributed to the paper.

Citation

Tyner, JW, Tognon, CE, Bottomly, D, Wilmot, B, Kurtz, SE, Savage, SL, Long, N, Schultz, AR, Traer, E, Abel, M, Agarwal, A, Blucher, A, Borate, U, Bryant, J, Burke, R, Carlos, A, Carpenter, R, Carroll, J, Chang, BH, Coblentz, C, d'Almeida, A, Cook, R, Danilov, A, Dao, KT, Degnin, M, Devine, D, Dibb, J, Edwards, DKt, Eide, CA, English, I, Glover, J, Henson, R, Ho, H, Jemal, A, Johnson, K, Johnson, R, Junio, B, Kaempf, A, Leonard, J, Lin, C, Liu, SQ, Lo, P, Loriaux, MM, Luty, S, Macey, T, MacManiman, J, Martinez, J, Mori, M, Nelson, D, Nichols, C, Peters, J, Ramsdill, J, Rofelty, A, Schuff, R, Searles, R, Segerdell, E, Smith, RL, Spurgeon, SE, Sweeney, T, Thapa, A, Visser, C, Wagner, J, Watanabe-Smith, K, Werth, K, Wolf, J, White, L, Yates, A, Zhang, H, Cogle, CR, Collins, RH, Connolly, DC, Deininger, MW, Drusbosky, L, Hourigan, CS, Jordan, CT, Kropf, P, Lin, TL, Martinez, ME, Medeiros, BC, Pallapati, RR, Pollyea, DA, Swords, RT, Watts, JM, Weir, SJ, Wiest, DL, Winters, RM, McWeeney, SK &Druker, BJ. Functional genomic landscape of acute myeloid leukaemia. Nature. 562, 526-531 (2018). PMID 30333627

Resources

• Read the paper
• View the OHSU news announcement
  
• Visit the Tyner lab website
  
• Previous Papers of the Month