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Biology subjects

Olsen, K. S.

Publications and source records attributed to Olsen, K. S..

3 recordsLinked to original sources

Shared Graft Versus Leukemia Minor Histocompatibility Antigens in DISCOVeRY-BMT

T cell responses to minor histocompatibility antigens (mHAs) mediate graft versus leukemia (GvL) effects and graft versus host disease (GvHD) in allogeneic hematopoietic cell transplant (alloHCT). Therapies that boost T cell responses improve the efficacy of alloHCT; however, these have been limited by concurrent increases in the incidence and severity of GvHD. mHAs with expression restricted to hematopoietic tissue (GvL mHAs) are attractive targets for driving GvL without causing GvHD. Prior work to identify mHAs has focused on a small set of mHAs or population-level SNP association studies. We report here the discovery of a large set of novel GvL mHAs based on predicted peptide immunogenicity, restriction of expression to hematopoietic tissue or GvHD target organs, and degree of sharing among donor-recipient pairs (DRPs) in the DISCOVeRY-BMT dataset of 3231 alloHCT DRPs. The total number of predicted mHAs and count within each class of predicted mHAs significantly differed by recipient genomic ancestry group, with European American>Hispanic>African American for each. The number of mHAs also differed markedly by HLA allele, even among alleles of the same gene. From the pool of predicted mHAs, we identified the smallest sets of GvL mHAs needed to cover 100% of DRPs with a given HLA allele. We then used mass spectrometry to search for high population frequency mHAs for three common HLA alleles. We validated a total of 24 novel predicted GvL mHAs that cumulatively are found within 98.8%, 60.7%, and 78.9% of DRPs within DISCOVeRY-BMT that express HLA-A*02:01, HLA-B*35:01, and HLA-C*07:02 respectively. We also confirmed in vivo immunogenicity of one example novel mHA via coculture of healthy human CD8 T cells with mHA-pulsed dendritic cells. This work demonstrates that identification of shared mHAs is a feasible and promising technique for expanding mHA-targeting immunotherapeutics to larger numbers of patients.

cancer biology↗

SARS-CoV-2 peptide vaccine elicits T-cell responses in mice but does not protect against infection or disease

We vaccinated BALB/c mice with peptides derived from the SARS-CoV-2 proteome selected in silico to elicit T-cell responses and/or B-cell responses against linear epitopes. These peptides were administered in combination with either of two adjuvants, poly(I:C) and the STING agonist BI-1387466. Antibody responses against predicted linear epitopes were not observed but both adjuvants consistently elicited T-cell responses to the same peptides, which were primarily from the set chosen for predicted T-cell immunogenicity. The magnitude of T-cell responses was significantly higher with BI-1387466 compared with poly(I:C). Neither adjuvant group, however, provided any protection against infection with the murine adapted virus SARS-CoV-2-MA10 or from disease following infection. In light of more recent evidence for protection from severe disease mediated by CD8+ T-cells, we suspect that the epitopes selected for vaccination were not presented by infected murine cells.

immunology↗

Building Applications For Interactive Data Exploration In Systems Biology

As the systems biology community generates and collects data at an unprecedented rate, there is a growing need for interactive data exploration tools to explore the datasets. These tools need to combine advanced statistical analyses, relevant knowledge from biological databases, and interactive visualizations in an application with clear user interfaces. To answer specific research questions tools must provide specialized user interfaces and visualizations. While these are application-specific, the underlying components of a data analysis tool can be shared and reused later. Application developers can therefore compose applications of reusable services rather than implementing a single monolithic application from the ground up for each project.\n\nOur approach for developing data exploration applications in systems biology builds on the microservice architecture. Microservice architectures separates an application into smaller components that communicate using language-agnostic protocols. We show that this design is suitable in bioinformatics applications where applications often use different tools, written in different languages, by different research groups. Packaging each service in a software container enables re-use and sharing of key components between applications, reducing development, deployment, and maintenance time.\n\nWe demonstrate the viability of our approach through a web application, MIxT blood-tumor, for exploring and comparing transcriptional profiles from blood and tumor samples in breast cancer patients. The application integrates advanced statistical software, up-to-date information from biological databases, and modern data visualization libraries.\n\nThe web application for exploring transcriptional profiles, MIxT, is online at mixt-blood-tumor.bci.mcgill.ca and open-sourced at github.com/fjukstad/mixt. Packages to build the supporting microservices are open-sourced as a part of Kvik at github.com/fjukstad/kvik.

bioinformatics↗