USF-LVHN SELECT
Programmatically Efficient Separation of Immune Infiltrate and Tumor Gene Expression Overlap Potentials in a Big Data Setting: FASLG Gene Expression-related Survival Distinctions.
Publication/Presentation Date
9-1-2025
Abstract
BACKGROUND/AIM: Typically expressed on T-cells and NK cells, FASLG induces apoptosis in target cells upon binding Fas. However, assessing potential FASLG expression in tumor cells with convenient genomics approaches has been challenging.
MATERIALS AND METHODS: This study applied a novel assessment of FASLG copy numbers (CNs) and gene expression levels, applicable to bulk exome and RNAseq files.
RESULTS: Analyses indicated high FASLG CN associated with worse survival outcomes. Interestingly, higher FASLG gene expression was found to be associated with better survival outcomes, which led to a determination of whether this result was due to FASLG expression from tumor-infiltrating lymphocytes (TILs) instead of cancer cells demonstrating the higher CNs. In fact, T-cell markers CD4 and CD8A highly correlated with FASLG expression, consistent with the hypothesis that the high FASLG expression was associated with the TILs. Subsequent analyses confirmed that CN increases led to increased gene expression in the genomic region of the FASLG gene, particularly with an assessment of the expression of the neighboring PRRC2C gene. In sum, FASLG CN assessments, even independently of a corresponding gene expression correlation, may provide important characterizations of tumor cells.
CONCLUSION: This study indicates that FASLG CN increases could represent a mechanism of tumor escape from TILs and a prognostic indicator; and tumor FASLG may be a suitable drug target for reducing tumor evasion of T-cells.
Volume
22
Issue
5
First Page
716
Last Page
724
ISSN
1790-6245
Published In/Presented At
Fletcher, E. A., Dabkowski, T. R., Varkhedi, M., & Blanck, G. (2025). Programmatically Efficient Separation of Immune Infiltrate and Tumor Gene Expression Overlap Potentials in a Big Data Setting: FASLG Gene Expression-related Survival Distinctions. Cancer genomics & proteomics, 22(5), 716–724. https://doi.org/10.21873/cgp.20531
Disciplines
Medical Education | Medicine and Health Sciences
PubMedID
40883027
Department(s)
USF-LVHN SELECT Program, USF-LVHN SELECT Program Students
Document Type
Article