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Computer simulations and big data advance cancer immunotherapy

Speed read
  • Immunotherapy supercharges the body to combat cancer
  • Advanced computing at TACC simulates the effects of immunotherapy drugs
  • HPC helps scientists to design new and improved immunotherapies

The body has a natural way of fighting cancer – it's called the immune system, and it is tuned to defend our cells against outside infections and internal disorder. But occasionally, it needs a helping hand.

In recent decades, immunotherapy has become an important tool in treating a wide range of cancers, including breast cancer, melanoma and leukemia.

But alongside its successes, scientists have discovered that immunotherapy sometimes has powerful — even fatal — side-effects. 

Identifying patient-specific immune treatments

Not every immune therapy works the same on every patient. Differences in an individual's immune system may mean one treatment is more appropriate than another. Furthermore, tweaking one's system might heighten the efficacy of certain treatments.

This feature is part of a series of Texas Advanced Computing Center articles about how supercomputers are being used in the fight against cancer. Learn more in a <a href= 'https://www.tacc.utexas.edu/special-report/cancer'>TACC Special Report on Cancer.</a> Courtesy TACC.

Researchers from Wake Forest School of Medicine and Zhejiang University in China developed a novel mathematical model to explore the interactions between prostate tumors and common immunotherapy approaches, individually and in combination.

In a study published in Nature Scientific Reports, they used their model to predict how prostate cancer would react to four common immunotherapies.

The researchers incorporated data from animal studies into their complex mathematical models and simulated tumor responses to the treatments using the Stampede supercomputer at the Texas Advanced Computing Center (TACC).

"We do a lot of modeling which relies on millions of simulations," says Jing Su, a researcher at the Center for Bioinformatics and Systems Biology at Wake Forest School of Medicine and assistant professor in the Department of Diagnostic Radiology.

"To get a reliable result, we have to repeat each computation at least 100 times. We want to explore the combinations and effects and different conditions and their results."

TACC's high performance computing resources allowed the researchers to highlight a potential therapeutic strategy that may manage prostate tumor growth more effectively.

Designing more efficient clinical trials

Biological agents used in immunotherapy — including those that target a specific tumor pathway, aim for DNA repair, or stimulate the immune system to attack a tumor — function differently from radiation and chemotherapy.

Because traditional dose-finding designs are not suitable for trials of biological agents, novel designs that consider both the toxicity and efficacy of these agents are imperative.

Chunyan Cai, assistant professor of biostatistics at UT Health Science Center (UTHSC)'s McGovern Medical School, uses TACC systems to design new kinds of dose-finding trials for combinations of immunotherapies.

<strong>Plan of attack. </strong> Model construction for predicting treatment outcomes of prostate cancer. Courtesy Huiming Peng, Weiling Zhao, et al.

Writing in the Journal of the Royal Statistics Society Series C (Applied Statistics), Cai and her collaborators, Ying Yuan, and Yuan Ji, described efforts to identify biologically optimal dose combinations for agents that target the PI3K/AKT/mTOR signaling pathway, which has been associated with several genetic aberrations related to the promotion of cancer.

After 2,000 simulations on the Lonestar supercomputer for each of six proposed dose-finding designs, they discovered the optimal combination gives higher priority to trying new doses in the early stage of the trial. The best case also assigns patients to the most effective dose that is safe toward the end of the trial.

"Extensive simulation studies show that the design proposed has desirable operating characteristics in identifying the biologically optimal dose combination under various patterns of dose–toxicity and dose–efficacy relationships," Cai concludes.

Whether in support of population-level immune response studies, clinical dosing trials, or community-wide efforts, TACC's advanced computing resources are helping scientists put the immune system to work to better fight cancer.

Of course, there's much more to the story of fighting cancer with supercomputers. Read the full TACC article here.

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