Posted in: Healthcare

Brainiacs: Applying Watson for Genomics to better understand brain tumors

This spring I was invited to a global meeting about cancer research – how tumor data should be gathered, integrated and interpreted.  It brought together specialists from medicine, biology, chemistry, mathematics and computer science for an extensive multi-disciplinary exploration. On the long trans-Atlantic flight back, to distract myself, I casually pulled out a movie from the in-flight entertainment with an intriguing title, “Collateral Beauty.”  To my great surprise, the movie touched on cancer- it was about the devastating effect on the hapless family of a glioblastoma multiforme (GBM) victim.  A gut-wrenching account.

GBM strikes indiscriminately and more frequently than one would imagine[1]. About a hundred thousand cases of brain tumors are diagnosed a year in the US, and a quarter of these are gliomas, or tumors of the supportive tissue of the brain. They account for 75 percent of all malignant tumors, and nearly 50 percent of the gliomas are GBMs. GBMs are usually highly malignant and grow aggressively, invading surrounding tissues. Our team in IBM Research set out to explore the potential for applying machine learning and data science to better understand and predict this disease.

Researchers prepare tissue samples for whole genome sequencing at The Rockefeller University, where clinical researcher Robert Darnell, MD, PhD, led a study with the New York Genome Center and IBM to analyze complex genomic data from state-of-the-art DNA sequencing of whole genomes. The findings were published in the July 11, 2017 issue of Neurology® Genetics, an official journal of the American Academy of Neurology. (Photo Credit: Epic Creative)

Would analyzing more genes give us a more complete view of the patient? In this case, is more really ‘more’? That’s the question we investigated in our paper published in Neurology Genetics this month: one of the results of our collaborative effort with New York Genome Center and other specialists [2].  Current commercially available genomic testing (called “assays”) target a small panel of a patient’s genes. We extended this analysis to a patient’s entire genome, as well as other omic-assays, such as proteomics (the study of proteins) that included whole genome expression (i.e., RNA or ribonucleic acid) data. We found that this indeed results in identifying more variants of their individual genome that can be potentially targeted for therapy by an oncologist.

Next we asked, does a machine-based (algorithm) analysis of this multi-modal, whole genome data hold a candle to a crack team of human bioinformaticians and cancer oncologists, in terms of accuracy and quality of analytics? We used a research version of Watson for Genomics at the time and demonstrated that it does! It was able to cut the time for accurate genomic data interpretation from 160 expert human hours to 10 minutes, opening the door for the possibility of scaling this highly specialized analytics.

Currently we are extending this work to a larger set of GBM patients and extending to other cancers, while we continuously improve the underpinning algorithms. Now we are also setting our sights on understanding the genomic basis of other complex phenomena such as resistance and response to therapy and immunotherapy.

 

Sources

[1] American Brain Tumor Association, “Glioblastoma” http://www.abta.org/about-us/news/brain-tumor-statistics/

http://www.abta.org/brain-tumor-information/types-of-tumors/glioblastoma.html

[2] Comparing sequencing assays and human-machine analyses in actionable genomics for glioblastoma, Neurology Genetics, 2017.

Comments

  1. Samaresh says:

    Wonderful work. On the frontier of human knowledge. Kudos

  2. Saroj Parida, MD says:

    What a wonderful venture you are on! Genomics and proteomics hold the key not only to finding possible cure for cancer but to many other chronic recalcitrant illneses: auto-immune, collagen-vascular, connective tissue diseases etc., just to name a few. Glioblastoma multiforme (GBM), being the most aggressive cancer in the brain, is the ideal one to study, in terms of time-span for looking at effectiveness of experimental treatments.
    As we dig deeper and deeper into the sub-atomic world of quantum medicine, we will find infinite possibilities. We will begin to appreciate how intricately balanced nature is. It will be a marvel to behold. Just imagine this: There are 10,000 chemical reactions taking place in each of the 50 trillion cells in the human body. And, if one of these chemical reactions goes awry, one is prone to devastating illnesses like cancer. Also, one quantum unit in the human body is 1/10 million size of an atomic particle. We are only scratching the surface of this marvel. It will be an unending process of satisfying one’s intellectual curiosity, but the beauty is that there is nothing better than the endeavor to find out who we are and how we function and “dysfunction.”
    Great work! Thank you so much for sharing!

Add Comment

Your email address will not be published. Required fields are marked *

Laxmi Parida

Manager, Computational Genomics, IBM Research