Dissertations and Theses (Open Access)
Author ORCID Identifier
0000-0003-4276-8774
Graduation Date
Summer 8-13-2026
Degree Name
Master of Science (MS)
School Name
The University of Texas School of Biomedical Informatics at Houston
Advisory Committee
Sachet Shukla, PhD
Abstract
Multiple myeloma (MM) remains an incurable plasma cell malignancy, with relapse driven by persistent chemotherapy-resistant cells and residual disease following treatment. Although immunotherapies have transformed MM care, their success depends on identifying tumor-specific antigens that can be safely targeted. While aberrant genomic structural variation and transcriptional dysregulation are increasingly recognized as sources of novel antigens in MM, the HLA-presented antigenic landscape of MM remains incompletely characterized, particularly for non-canonical, structurally-derived peptides, and long-read transcriptome-informed immunopeptidomic data specific to MM remain scarce.
We established an integrated antigen discovery platform combining long-read RNA sequencing (Iso-Seq) with mass spectrometry-based HLA immunoprecipitation and immunopeptidomics to define the antigenic repertoire of MM. A panel of six MM cell lines (ANBL-6, ALMC-1, MM.1S, NCI-H929, LP-1, and U266) was selected for both transcriptomic fidelity to primary patient tumors and diversity of HLA-A/-B/-C genotype, and HLA class I/II expression was confirmed by flow cytometry prior to profiling. Across this cohort, the integrated pipeline identified 1,255 candidate HLA-presented peptides mapping to 891 unique underlying genes, of which only a small minority (approximately 7%) have previously characterized, gene-level roles in MM, MGUS, or smoldering MM, indicating that this platform captures a substantially broader antigen repertoire than approaches restricted to known MM driver genes. HLA typing across an expanded 25-cell-line panel further identified HLA-A03:01 and HLA-A30:01 as “super-alleles” anchoring a disproportionate share of candidate peptides, with HLA-A*30:01 of particular translational interest given its association with elevated risk of progression from MGUS to MM. Candidate peptides were additionally evaluated for sharing across other tumor types and for feasibility using an in-house-optimized immunoprecipitation protocol, validated by western blot confirmation of MHC class I capture.
Together, this work provides one of the largest combined long-read transcriptomic and immunopeptidomic datasets generated for MM to date, establishing a comprehensive resource of candidate MM antigens and a rationale for both personalized and shared HLA-super-allele–based vaccine strategies. This platform lays the groundwork for the rational development of next-generation immunotherapies, including mRNA vaccines and T-cell receptor (TCR)-based approaches, aimed at intercepting disease in high-risk precursor states and preventing relapse in patients with multiple myeloma.
Recommended Citation
Albittar, Aya, "Antigen Discovery in Multiple Myeloma Using Integrated Long-Read Transcriptomics and Immunopeptidomics" (2026). Dissertations and Theses (Open Access). 79.
https://digitalcommons.library.tmc.edu/uthshis_dissertations/79
Keywords
Cancer Vaccines, immunotherapy, Multiple myeloma, T-cells based therapies