An extensive study conducted at the Terasaki Institute for Biomedical Innovation (TIBI) has revealed a connection between increased populations of tissue-resident memory T cells (TRM) and improved survival outcomes for melanoma patients. The data gathered from this study not only could be utilized to develop a predictive machine learning model based on TRM for melanoma prognosis but could also provide insight into the potential role TRM cells play in the tumor immune microenvironment. This information could help in the development of more effective and personalized anti-tumor immunotherapeutic treatments for cancer patients by guiding treatment regimens.
The tumor immune microenvironment (TIME) is a complex and dynamic interplay between tumor cells, various immune cells, and other cellular and non-cellular components in and around the tumor. TRM cells are a special type of immune cell that can be found in peripheral tissues and many different cancer types. Due to their presence and functional characteristics in the TIME, there has been a growing interest in studying TRM cells and their impact on patient survival. It is important to determine whether the presence and abundance of TRM cells in cancer patients correlate with better patient prognosis, as previous studies on this relationship have produced conflicting results.
The TIBI research team aimed to address this issue by utilizing data from single-cell RNA sequencing (scRNA-seq) technology to obtain a comprehensive genetic profile of individual cells. By generating gene signatures based on this profile, the team was able to identify 11 distinct gene signatures that were highly correlated with TRM abundance in melanoma patients. These gene signatures also showed a strong association with patient survival outcomes. Additional studies revealed positive correlations between TRM abundance and the presence of multiple anti-tumor immune cells, immune pathways, and regulatory genes in the melanoma TIME, suggesting that TRM cells play a critical role in immunomodulation and influencing patient outcomes.
The data from the analysis allowed the TIBI researchers to develop a high-precision TRM-derived risk scoring system to classify melanoma patients into high- and low-risk prognostic categories. This innovative approach could potentially improve the assessment of cancer patients’ response to immunotherapeutic drugs and lead to more tailored and effective treatment plans. According to Ali Khademhosseini, TIBI’s Director and CEO, the team’s findings may help refine the understanding of cancer patients’ responses to immunotherapy, which could ultimately enhance patient outcomes. The study was supported by grants from the National Institutes of Health (NIH) and the Cancer Prevention Research Institute of Texas (CPRIT).
