A new study published in Nature Medicine by researchers at The University of Texas MD Anderson Cancer Centre provides a better understanding of the tremendous diversity of T cell states and their relationships and activities within complex tumor microenvironments.
This pan-cancer single-cell T-cell atlas includes 27 single-cell RNA sequencing datasets, nine unique to MD Anderson, and covers 16 cancer types. It provides the most detailed picture of the heterogeneity of T cells present within the tumor microenvironment to date, demonstrating how their phenotypic states and the relative proportions of each state play a critical role in determining the efficacy of immunotherapy and the likelihood of potential adverse effects.
Linghua Wang, M.D., Ph.D. associate professor of Genomic Medicine, said, “This kind of large dataset and comprehensive pan-cancer analysis provides the opportunity to see things that aren’t visible when studying a single type of cancer or even a handful of cancer types, We hope these high-resolution maps, including the thoroughly characterized T cell states, are valuable resources for facilitating future T cell studies and biomarker discovery.”
The previously unknown T cell stress response state, or TSTR, was discovered in this work. Prior single-cell investigations frequently overlooked or dismissed these T cells as artifacts of tissue separation.
However, using the extensive data available, the researchers were able to identify these cells as a distinct group, distinct from other CD4+ or CD8+ T cell subsets, and to validate their existence in situ using TSTR cells, which are characterized by high heat shock gene expression and are seen at significantly higher fractions in both CD4+ and CD8+ T cells following immune checkpoint blockade therapy.
TSTR cells might be considered stressed-out’ T cells, and they appear less effective at fighting cancer, just as a stressed person may be less effective at their job. While both TSTR cells and tired T cells are dysfunctional, TSTR cells appear to follow a distinct differentiation path from exhausted T cells.
This new T cell state adds to their understanding of cancer’s complicated biology. It gives a possible target for future therapies.
Wang said, “The fact that these TSTR cells are found in many different types of tumors opens up a whole new world of possibilities that could have high translational potential, Investigating the mechanistic causes of stress response in T cells, understanding how these stressed T cells are induced in the tumor microenvironment, and learning how to stop or reverse this TSTR state could catalyze the development of more effective therapeutic strategies that may bring the benefit of immunotherapy to more cancer patients.”
This pan-cancer T cell atlas highlights big data’s ability to unravel the complex landscape of T cells within tumors, identifying seven subpopulations within the CD4+ regulatory subset, five within the CD4+ follicular helper T cell population, and eight states among proliferative T cells.
These findings highlight the enormous variability of T cell states within the tumor microenvironment and the need to learn more about how different conditions contribute to disease progression and immunotherapy response.
The researcher said, “There are still many questions left to answer. One of the limitations of this study is that we don’t have the corresponding T-cell receptor data for most of the datasets analyzed. We are not sure what triggers the TSTR state, and we don’t know from which T cell subset(s) they originate. It also is unclear whether these TSTR cells are specific to tumor cells and how they communicate with and influence other cells within the tumor microenvironment.”
The research team shared their T-cell atlas with the larger community via Single-Cell Research, a user-friendly, interactive web platform. The team created this portal to allow internal and external users to visualize and query the atlas without bioinformatics expertise.
The team created TCellMap, a tool that allows researchers to automatically label T cells from their datasets by aligning them with the high-resolution T cell maps established by this work.
Researchers hoped these materials would be helpful to scientists conducting in-depth analyses of T cells, leading to discoveries and ultimately improving T cell therapy tactics.
MD Anderson and the National Institutes of Health/National Cancer Institute funded this study.