NVIDIA awards $400,000 to two cancer research institutions to drive computing treatment programs
NVIDIA (Chinese name NVIDIA), founded in January 1993, is a computer graphics chip manufacturer with more than half of the computer-independent graphics cards using NVIDIA chips. Now, NVIDIA is an artificial intelligence computing company that has already penetrated its business into supercomputing chips, artificial intelligence, deep learning and autonomous driving.
Recently, the NVIDIA “Calculation Therapy†project team awarded $400,000 in prize money to two cancer research institutes for a close combat with cancer – the most appropriate description for two pioneering research teams on the front line of cancer research. . A group of NVIDIA employees, with the support of researchers from the National Cancer Institute, selected the two award-winning groups from 20 proposals worldwide.
One of them is led by Seungchan Kim, a team of translational genomics research institutes in Phoenix, Arizona. Their goal is to understand why some cancer cells respond to treatment, while others do not. Their findings will drive the development of cancer differentiation therapy.
Another team, led by Andrés Cisneros of the University of North Texas, is looking for related variants that can trigger abnormal changes in repairing DNA damage proteins. These variants are likely to be key factors in the diagnosis of cancer. The two teams studied ways to fight cancer from the most fundamental aspects of human biology by using accelerated computing.
Each of the above two teams, each team receives a $200,000 grant from the NVIDIA Foundation to further explore how to create newer and more targeted treatments. The NVIDIA Foundation is a charity led by NVIDIA employees and these two bonuses are part of the Foundation's "Calculation Therapy" program. The program is designed to support projects that use parallel computing to make breakthroughs in cancer diagnosis and treatment.
Fight cancer and break down cells
Researchers at the Translation Genomics Institute discuss data analysis tools - EDDY
Kim and his team's research can lead to precise treatment of cancer, such as treatment of certain cells in a patient's tumor.
To this end, they created a GPU-accelerated data analysis tool that allows them to examine in detail how cancer cells' DNA controls protein production and how these proteins interact with each other and with other molecules. By using this tool, researchers can find differences between different cell populations in the same tumor.
This research means that in the future, individualized treatments for cancer patients can be brought to the treatment of different parts of the tumor by using different drugs.
Kim said: "There may be subpopulations of cells that only respond to component A, and another subgroup only responds to component B."
This tool, called EDDY-GPU (EDDY is an acronym for Differential Dependency Assessment), allows researchers to quickly analyze data from a large number of tumor cells. In contrast, the early CPU-based EDDY analysis failed to complete the analysis of 4754 samples in two months.
Kim said: "If you have a cancer patient hanging a line, for the results of the treatment, you must not wait for a moment."
He wants to use the "Calculation Therapy" project to improve his algorithm to get faster analysis.
Kim and his team also plan to do a trial with the University of California in San Francisco. They took tissue samples from two brain cancer patients, performed detailed analysis of the patient's tumors, suggested therapies, and further investigated the therapies through patient-derived models.
Fight cancer and repair "repair protein"
DNA is often destroyed by ultraviolet light, carcinogens and other substances in cigarettes. Fortunately, human-made DNA repair proteins often solve the problem of DNA damage.
But sometimes DNA repair proteins themselves divide or mutate. Andres Cisneros of the University of North Texas and his team brought together a large amount of data from the National Institutes of Health to look for cancer-related DNA repair protein variants.
After finding these variations, the researchers used GPU-accelerated computer simulations to find out how these variations alter DNA repair proteins and their functions.
Cisneros said, "If we know that mutations affect these proteins and are related to cancer, researchers can use this information to repair these proteins, or use drugs or other treatments to treat them."
The larger goal of Cisneros is to find more biomarkers that indicate signs of a particular type of cancer. The team has found mutations associated with several cancers, including biomarkers for prostate cancer in African Americans.
Scientists are using genetic data to identify the risks and treatments of certain cancers. For example, surgeons can detect high-risk mutations in breast cancer, while testing for estrogen and progesterone receptors can help doctors determine which treatments are more effective.
By finding more biomarkers, Cisneros can provide new diagnostic tools for more types of cancer. In addition, his DNA repair protein mutation analysis can help scientists develop more personalized genetic anticancer therapies.
NVIDIA has been working on cancer research
The "Calculation Therapy" project can be said to be one of NVIDIA's efforts to parallelize research in cancer. In fact, NVIDIA has been paying attention to the treatment of cancer. Last month, NVIDIA reached a new collaboration with the National Cancer Institute and the Department of Energy to develop an artificial intelligence framework to accelerate cancer research. This new framework is called the "Cancer Distributed Learning Environment", referred to as CANDLE. NVIDIA said it will try to achieve the goal of the "Cancer Moonshot" program announced by Obama earlier this year, which will take 10 years to complete a cancer study in five years.
NVIDIA said its engineers and computer scientists will work with cancer researchers to develop and improve the artificial intelligence framework. CANDLE will focus on three major cancer research projects:
The first is to raise scientists' understanding of the understanding of gene signatures in DNA and RNA to help them predict which treatments will work for patients;
Second is the simulation process that accelerates protein interactions (which plays an important role in the formation of early cancer);
Finally, it will sort out millions of cancer patient data to build a comprehensive database for monitoring cancer metastasis and recurrence. In order to protect the privacy of patients, this process will be carried out under semi-supervised.
NVIDIA founder and CEO Huang Renxun said: "GPU deep learning has provided us with a new tool to deal with major challenges. So far, even the most powerful supercomputers are too complicated in this regard. Through cancer with the United States In collaboration with the Institute and the Department of Energy, we have created this artificial intelligence supercomputing platform for cancer research."
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