{Reference Type}: Journal Article
{Title}: Elucidating immune-related gene transcriptional programs via factorization of large-scale RNA-profiles.
{Author}: He S;Gubin MM;Rafei H;Basar R;Dede M;Jiang X;Liang Q;Tan Y;Kim K;Gillison ML;Rezvani K;Peng W;Haymaker C;Hernandez S;Solis LM;Mohanty V;Chen K;
{Journal}: iScience
{Volume}: 27
{Issue}: 6
{Year}: 2024 Jun 21
{Factor}: 6.107
{DOI}: 10.1016/j.isci.2024.110096
{Abstract}: Recent developments in immunotherapy, including immune checkpoint blockade (ICB) and adoptive cell therapy (ACT), have encountered challenges such as immune-related adverse events and resistance, especially in solid tumors. To advance the field, a deeper understanding of the molecular mechanisms behind treatment responses and resistance is essential. However, the lack of functionally characterized immune-related gene sets has limited data-driven immunological research. To address this gap, we adopted non-negative matrix factorization on 83 human bulk RNA sequencing (RNA-seq) datasets and constructed 28 immune-specific gene sets. After rigorous immunologist-led manual annotations and orthogonal validations across immunological contexts and functional omics data, we demonstrated that these gene sets can be applied to refine pan-cancer immune subtypes, improve ICB response prediction and functionally annotate spatial transcriptomic data. These functional gene sets, informing diverse immune states, will advance our understanding of immunology and cancer research.