A new study published in Cell Press reveals critical insights into the role of gamma-delta T cells across 33 cancer types, shedding light on their potential as clinical biomarkers and therapeutic targets in cancer treatment.
Led by a team of researchers at Moffitt Cancer Centre, this comprehensive analysis represents a significant advancement in the understanding of these unique immune cells and their implications for patient outcomes in cancer therapy.
Despite their minority status within the T cell community, gamma-delta T cells are increasingly recognised for their dual capability to engage both innate and adaptive immune responses.
Moffitt researchers, in collaboration with scientists at Dartmouth College and Duke University, utilised a novel computational algorithm to analyse the gamma-delta T-cell receptor landscape across 11,000 tumours, providing an extensive database that tracks cancer progression and responses to various treatments, particularly immunotherapy.
“It’s like finding a needle in a haystack,” said Xuefeng Wang, Ph.D., chair of Moffitt’s Biostatistics and Bioinformatics Department and the lead contact of the study.
“After two years of effort screening approximately 700 billion tumour RNA sequencing reads, our algorithm distilled 3.2 million gamma-delta T-cell reads, highly informative for the study of gamma-delta T-cell clones. Our findings suggest that the diversity and clonality of gamma-delta T cells can significantly impact patient survival and treatment efficacy.”
Key findings of the study include:
As the study evolves, researchers will expand the database by incorporating additional T-cell receptor repertoires and functional annotations, including single-cell RNA sequencing analyses.
This ongoing work aims to deepen our understanding of the functional roles of gamma-delta T cells in cancer and their interactions within the tumour microenvironment.
“This research not only expands our knowledge of gamma-delta T cells but also opens new avenues for therapeutic strategies,” Wang said.
“By understanding the specific roles of these cells in different cancers, we can better tailor treatments to improve patient outcomes.”
The Immuno-Oncology Programme and Biostatistics and Bioinformatics Shared Resources at Moffitt provided critical support and represent leading research expertise in computational immunology and personalised immunotherapy.
This study was supported by the National Institutes of Health (R01DE030493 and P20GM130454) and the National Cancer Institute (P30-CA076292).