research 44 research 45 BamQuery: a proteogenomic tool to explore the immunopeptidome and prioritize actionable tumor antigens. Grégory Ehx, in close collaboration with several Canadian teams, has developed a computer program that enables the discovery of optimal targets for producing anti-cancer vaccines. The results obtained with this program indicate that many targets currently under investigation to create this type of vaccine could trigger autoimmune reactions. Despite significant recent advances, cancer remains one of the leading causes of mortality in Belgium. Among these recent advances, immunotherapy is a strategy based on the ability of immune cells to recognize and eliminate tumor cells. Given their versatility and impressive effectiveness during the COVID-19 pandemic, messenger RNA vaccines offer a promising new avenue for immunotherapy for many cancers. However, their implementation requires the ability to identify vaccine targets, known as MHC-I antigens, that are specific to cancer cells (tumor-specific antigens, or TSA). This is the problem that Grégory Ehx, an FNRS postdoctoral researcher, and his Canadian colleagues tackled by creating their software, BamQuery. Currently, the discovery of TSAs relies on a technique called mass spectrometry, which analyzes all the antigens of tumor cells. It is then necessary to identify which regions of the genome generated these antigens and compare the expression of these regions between tumor cells and healthy cells. This comparison finally reveals which antigens derive from genomic regions exclusively expressed by cancer cells, qualifying them Cancer Grégory Ehx as TSAs and selecting them as vaccine targets. However, current approaches too often overlook an important aspect: multiple different genomic regions can generate the same antigen! Therefore, it is essential to consider all of these regions when comparing tumor and normal cells. This is precisely what BamQuery does; it allows for a simultaneous study of the expression of all genomic regions capable of generating a given antigen. Using BamQuery and an extensive dataset comprising thousands of healthy tissues and cancer samples, researchers investigated the tumor specificity of numerous TSAs reported in previous publications. The researchers discovered that a concerning number of these TSAs (ranging from 6 to 100% depending on the considered publication) were actually expressed in one or several healthy tissues. Consequently, they could potentially trigger undesirable autoimmune reactions if targeted by immunotherapy. This mainly resulted from the fact that, in general, studies describing TSAs fail to identify all genomic regions capable of producing them. Therefore, utilizing BamQuery to verify the safety of these antigens could prevent the occurrence of several potentially lethal side effects in future clinical studies involving vaccination against TSAs. Finally, the researchers explored their program’s ability to discover and select TSAs during exploratory analyses of cancer antigens. To do this, they analyzed approximately 7000 antigens from nonHodgkin lymphoma cells, the most common form of blood cancer in adults. After comparing healthy and maignant cells using BamQuery, the researchers identified sixty-seven TSAs, of which eleven were highly shared among patients with this disease. Furthermore, the expression of these TSAs was associated with evident immune responses in patients, suggesting that vaccination would enhance these responses and could potentially lead to cancer elimination. These TSAs are thus promising targets for developing a vaccine against this type of lymphoma. Eager to maximize the sharing of their tool, the researchers made their program completely accessible and created a web portal https:// bamquery.iric.ca/ for testing potential vaccine targets. In doing so, they hope to accelerate progress in vaccine discovery. BamQuery: a proteogenomic tool to explore the immunopeptidome and prioritize actionable tumor antigens. Cuevas MVR, Hardy MP, Larouche JD, Apavaloaei A, Kina E, Vincent K, Gendron P, Laverdure JP, Durette C, Thibault P, Lemieux S, Perreault C, Ehx G. Genome Biol. 2023 Aug 15;24(1):188. doi: 10.1186/s13059-023-03029-1. Reference
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