Essay titled precision immunotherapy received an award Michelson Prize for Philanthropy and Science in Immunology. his actor, Alexander Obradovicresearcher at the Columbia University Irving Medical Center (USA), proposes a customized approach that identifies cell-to-cell interactions associated with resistance to cancer treatment with immunotherapy using algorithms.
As Obradovic detailed in an article published this week in The science, “Over the past decade, cancer treatment has been revolutionized with the advent of inhibitory immunotherapy, as it activates antitumor immune responses extensively and independently of the mechanisms of tumor growth. However, many patients do not respond to such therapy and there are no reliable signs of therapeutic failure.
Cancer treatment with algorithms
For this reason, it offers more precise cancer immunotherapy tailored to each patient. This treatment and single cell RNA sequencing data will be combined with traditional anti-cancer drugs, using two algorithms developed by his team.
One determines protein activity (VIPER) and the other predicts drug sensitivity (ARACNe). The goal is to identify groups of cells associated with treatment resistance in different types of tumors.
“Given the large amount of missing data in single-cell RNA sequencing experiments, this is like solving a crossword puzzle,” Obradovic compares. “ARACNe is the dictionary that tells us which letters correspond to words, while VIPER is the one that solves the crossword by finding the right words, even if most of the letters are missing.”
Researcher explains SYNCHRONIZATION What algorithms “Helps distinguish between the immune characteristics of patients who respond to immunotherapy in two ways: first, the inference of protein activity allows a better identification of the various cell subtypes present in tumors, as well as regulatory protein markers of these subtypes.
Probabilistic biomarkers
He then points out: “You can determine the distinctive signature of each cell subtype and test its enrichment in large cohorts of patients who responded or did not respond to immunotherapy, determining for each cell type whether it was protective, deleterious or neutral. The informative cell type markers can then be used as new biomarkers to determine who will benefit the most from treatment.”
By identifying regulatory pathways active in cells associated with immunotherapy resistance, this approach offers targets for their elimination and could lead to the discovery of effective combination therapies.
The expert notes that “by identifying the regulatory pathways active in cells associated with immunotherapy resistance, this approach offers targets for killing these cells and therefore could lead to discovery of combination therapy effective in patients who do not respond to treatment.
To this should be added “ high throughput drug screeningwhich would allow us to quickly personalize and prioritize the best options for combining resistance mechanisms identified in a particular patient,” he emphasizes.
Obradovic says that the best hope for the future of his research “is to transfer expected discoveries about drug combinations to design of new clinical trials and patient care. In addition, he plans to study and integrate the immunological effects of radiotherapy into his approach.
Benefits of Combination Therapy
The expert also points out the benefits of this combination therapy: “A complete understanding of how each treatment option affects tumor cells and their surrounding immune cells can be used to identify resistance markers at an early stage. And thus target these markers with complementary initial therapies, both immunological and targeted.”
In addition, understanding immune dynamics which comes into play with chemotherapy And radiation therapy it will also serve to determine the timing of drug administration in order to take full advantage of any pro-inflammatory effects,” he concludes.
This article was first published on SYNCHRONIZATION
Source: Hiper Textual
