Elucidating immune-related gene transcriptional programs via factorization of large-scale RNA-profiles

Shan He, Matthew M. Gubin, Hind Rafei, Rafet Basar, Merve Dede, Xianli Jiang, Qingnan Liang, Yukun Tan, Kunhee Kim, Maura L. Gillison, Katayoun Rezvani, Weiyi Peng, Cara Haymaker, Sharia Hernandez, Luisa M. Solis, Vakul Mohanty, Ken Chen

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish (US)
Article number110096
JournaliScience
Volume27
Issue number6
DOIs
StatePublished - Jun 21 2024

Keywords

  • Bioinformatics
  • Cancer
  • Expression study
  • Immunity
  • Molecular network
  • Transcriptomics

ASJC Scopus subject areas

  • General

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