A new tumor immunology computational tool created by USF medical student Boris Chobrutskiy may help improve the predictability and precision of cancer immune therapies. He is first author of a study recently reported in Oncogene.
3D-rendered illustration of T-cells of the immune system attacking growing cancer cells
In the last decade, several immunotherapy drugs have been approved that rev up the patient’s own immune system to selectively combat cancer. These revolutionary anticancer treatments have shown remarkable potential to prolong the lives of those with malignant melanoma, advanced lung cancers and other types of cancers – but not all patients benefit equally. Their widespread use has been limited by unpredictable response rates and autoimmune side effects, including occasional life-threatening inflammatory damage.
Researchers at the USF Health Morsani College of Medicine’s Department of Molecular Medicine study the complex interplay between tumors and immune cells. They wanted to better understand apparently contradictory reports about the positive and negative effects of immune response in low-grade gliomas (LGG), brain tumors that grow slowly but are deadly.
So, they used the federal genomics database The Cancer Genome Atlas and a sophisticated computational method developed by third-year USF Health medical student Boris Chobrutskiy to determine the chemical match (complementarity) between a type of immune cell known as T lymphocytes (T-cells) and tumor-specific antigens. In particular, they delved into how well patient-specific T lymphocyte receptors matched abnormal proteins (antigens) of the patient’s LGG tumor cells. These tumor antigens flag the immune system to recognize and attack the tumor cells as “non-self” invaders so they do not grow uncontrollably.
Based on Chobrutskiy’s chemical complementarity scoring system, the researchers found that patient survival rates significantly increased when LGG-associated immune cell receptors (specifically the amino acid sequences of complementarity-determining region-3, or CDR3) were a good match with the cancer’s mutated protein, a tumor antigen known as the isocitrate dehydrogenase-1 (IDH1) mutant. Of 100 patient cases scoring high matches, 80% of the patients were living more than five years following diagnosis. Conversely, for 158 patient cases with poor or no discernable matches, only 30% survived beyond five years.
The USF Health study, with Chobrutskiy as lead author, was reported recently in the high-impact journal Oncogene. The paper’s senior author George Blanck, PhD, USF Health professor of molecular medicine, said Chobrutskiy’s latest publication is “a potential game changer” for developing next-generation tumor immunology tools. It is the medical student’s 16th peer-reviewed article with faculty mentor Dr. Blanck and other co-authors in the molecular medicine group.
Third-year USF Health medical student Boris Chobrutskiy with research mentor George Blanck, PhD, a professor of molecular medicine
“Boris’s big accomplishment — both a thought success and a computer programming success — was figuring out how to track down matches between the mutant protein in the cancer and the receptor on the T-cells (lymphocytes). “It’s like finding two matching needles from two different haystacks,” Dr. Blanck said. “He was able to bring the chemistry of what’s happening in the body (with cancer-immune cell interactions) into the computer.”
Computational models like the one created by Chobrutskiy could improve the reliability of prognoses for LGG and other cancers — that is, the ability to predict whether existing checkpoint inhibitors or other cancer immune therapies will benefit a patient, Dr. Blanck said. “That could save a lot of patients from a potentially harsh reaction to an immunotherapy that does nothing for them.”
Clinicians already know that the absence of an IDH1 mutation represents a poor prognosis for LGG. However, the USF Health researchers suggest, a scoring system like Chobrutskiy’s, that can distinguish how effectively the immune receptors complement the IDH1 mutants, adds prognostic value and may help guide therapy for those patients who do carry the mutation.
Ultimately, advanced technologies characterizing cancer immunity could also be used to develop more precise therapies to kill targeted tumor cells while sparing healthy cells, preventing the extensive inflammation caused by an immune system in overdrive, Chobrutskiy said. “It’s an opportunity to personalize treatment for both a patient’s cancer with its unique mutations that drive tumor growth, and for the patient’s particular lymphocyte (T cell) repertoire.
Unlike other immune cells with largely genetically identical receptors, every mature lymphocyte has a unique receptor on its cell membrane. When an antigen invades the body, normally only those lymphocytes with receptors that best fit the contours of that particular antigen mount the immune response. This receptor diversity enables the lymphocyte to recognize and bind hopefully at least one antigen, whether the invading pathogen is a bacteria, virus, or cancer cell.
Chobrutskiy harnessed the power of Big Data and created an algorithm to track down matches between the mutant protein in the cancer and the receptor on the immune cells. “It’s like finding two matching needles from two different haystacks,” Dr. Blanck says.
Since we have so many unique lymphoctyes and no two tumors are alike, “you really need a computer tool to sift through all the data and do the chemistry and math calculations to figure out the best matches,” said Chobrutskiy, who does computer programming as a hobby. “Finding the matches (between immune receptors and tumor mutants) in the laboratory would be way too expensive and time-consuming with such a large number of samples.”
The USF Health researchers will next test their hypothesis that patients with LGG who respond well to checkpoint inhibitor drugs will be those with highly specific binding interactions, or the “best fits,” between their immune cell receptors and tumor mutants.
“We know that their immune systems are already poised to go, whereas in the patient with no match, it doesn’t matter how well the T-cell works or how much you ‘uninhibit’ the T-cell,” Dr. Blanck said. “There’s nothing for the T-cell to do, because without a match even a boosted immune system cannot get rid of the cancer.”
The study was supported in part by USF Research Computing and MCOM Research, Innovation & Scholarly Endeavors fellowships.
-Photos by Freddie Coleman, USF Health Communications and Marketing
