Cancer can evade the immune system without necessarily exhausting the T cells meant to destroy it. Research into multiple myeloma is revealing why that distinction matters—and how studying human immune cells directly can challenge conclusions drawn from animal models. Balint of SciAnts_Streams speaks with Dr. David Glass, a postdoctoral researcher in the Vaccine and Infectious Disease Division at Fred Hutch Cancer Center, about the molecular mechanisms governing cancer immunity, vaccine responses, and long-term immunological memory.
Dr. Glass discusses his team's investigation of T-cell behavior in multiple myeloma. By analyzing patient samples collected before, during, and after treatment, researchers found evidence inconsistent with the hypothesis that T-cell exhaustion was the principal explanation for the absent anti-tumor response. Their findings redirect attention toward how tumors avoid immune recognition and whether the surrounding tissue environment prevents immune cells from effectively engaging cancer cells.
The interview examines how spatial transcriptomics is helping researchers investigate these questions by measuring gene expression while preserving each cell's location within tissue. This allows scientists to study the relationship between tumor cells, T cells, and other immune populations, including the possibility that oxygen-depleted, nutrient-poor tumor environments interfere with immune activity.
The discussion also moves into vaccine immunology, particularly the challenge of developing durable protection against HIV. Dr. Glass explains how researchers analyze blood, lymph node, and bone marrow samples to identify immune-cell populations associated with stronger, longer-lasting responses. Single-cell sequencing and computational analysis can reveal how B-cell lineages evolve after vaccination, producing increasingly diverse antibodies and establishing immunological memory.
A recurring theme is the difference between using artificial intelligence to make predictions and using computational models to discover biology. Dr. Glass emphasizes interpretable machine learning, independent validation, and careful experimental design as essential safeguards against overfitting and misleading correlations.
The conversation also examines B-cell diversity, camelid-derived antibodies, immune checkpoint therapies, publicly shared biological datasets, and the growing ability to measure RNA, proteins, epigenetic states, and glycan modifications within individual cells.
The deeper scientific question is not simply whether an immune response works, but which cells, molecular signals, and tissue conditions determine its success. Those mechanisms may inform both future cancer immunotherapies and vaccines designed to provide more durable protection against infectious disease.
Recorded: 9/16/2026
Relevant Links
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Dr. David Glass
Google Scholar: https://scholar.google.com/citations?user=yIAmk24AAAAJ&hl=en&oi=ao
Fred Hutch Cancer Center
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