Faster and more precise information about how best to treat cancer patients should be possible thanks to a $200,000 Compute the Cure grant announced today from the NVIDIA Foundation to the Translational Genomics Research Institute (TGen).
The grant will help TGen accelerate the computer processing of transcriptomes from thousands of cells gleaned from patient tumor samples, using a complex computational algorithm. Transcriptomes are all the messenger RNA (mRNA) molecules expressed from an individual’s genes. This process will advance the practice of precision medicine by quickly informing doctors with the best options for attacking each individual patient’s cancer.
“When you analyze actual patient data, your goal is to help physicians better understand treatment options, providing these answers to the doctors as soon as you possibly can. There is a lot at stake for our patients, and time is critical,” said Dr. Seungchan Kim, an Associate Professor and head of TGen’s Biocomputing Unit.
Specifically, the grant will enable TGen to perfect its prototype statistical analysis tool called EDDY (evaluation of differential dependency), reducing its analysis turn-around from months to days. By simultaneously sequencing the mRNAs of thousands of individual cancer cells from the same tumor, it will help physicians understand why some cancer cells respond to treatment, and some don’t, leading to more precisely targeted therapeutics.
“We can actually separate all these individual cells and then look in more fine detail at how each cell responds to each compound,” Dr. Kim said. “With that information we can propose which treatment might be best for each patient. You might have to use more than one compound to get all the tumor cells.”
According to TGen’s project proposal, single-cell RNA sequencing addresses several shortcomings of the traditional averaging of RNA expression from multiple cells. In isolating the specific genetic profile of individual cells, subtle changes in biological behavior are brought into sharp focus, enabling new research directions such as microevolution, dynamic RNA processes and the biological mechanisms involved in rare diseases.
The challenge for researchers is that each cell contains billions of pieces of genetic information. Initial attempts to simultaneously analyze thousands of tumor cells proved time consuming.
Using a CPU — a central processing unit, which is designed to conduct many different tasks — EDDY ran for two months and was still not able to complete the analysis of an initial batch of more than 4,700 samples, even using hundreds of CPUs simultaneously.
However, using a GPU — a graphics processing unit created by NVIDIA, which is designed to accomplish simple tasks but in massive parallel computing units — researchers anticipate EDDY will be able to analyze thousands of samples in a matter of days.
Working with the University of California San Francisco, TGen will apply this GPU-accelerated process to a study of brain cancer patients, analyzing their tumors, proposing therapies and monitoring the results.
“That is the promise of this grant proposal,” said Dr. Harshil Dhruv, an Assistant Professor in TGen’s Cancer and Cell Biology Division. “With the GPU, we can speed up the computation significantly, process the patient data within a few days, and give that information back to the oncologists so they can make an informed decision about how best to help the patient.”
Compute the Cure is the NVIDIA Foundation’s philanthropic initiative to fund computational efforts to advance cancer research, diagnostics and treatment, support non-profits that provide patient care and support services, and engage its employees in fundraising activities. Through this initiative, the NVIDIA Foundation has donated nearly $3 million to cancer causes since 2011.
The award to TGen was selected by a group of NVIDIA employees, with the support of researchers at the National Cancer Institute, from among nearly 20 proposals submitted from across the globe.
“Advanced computation is indispensable to the search for cancer cures, so we’re supporting researchers who embrace this view, like TGen’s Dr. Kim. We’re impressed with his novel use of single-cell transcriptomic profiling, the broad experience of his research team, and the potential of his GPU-accelerated analysis method to advance the clinical practice of precision medicine in cancer,” said John Montrym, chief architect at NVIDIA, and an NVIDIA Foundation Compute the Cure review committee member.
Source – TGen