Single-cell-based identification of drug synergy with immunotherapy via tumor microenvironment remodeling

Identifying effective therapeutic drugs in the intricate tumor microenvironment (TME) is challenging, further complicated by the lack of a systematic framework for analyzing TME perturbations in response to therapeutic interventions.

To address this, we established the single-cell RNA sequencing repository of immunomodulatory drugs resource and used the L1000 platform for unbiased screening of 739 immune-modulating compounds across various cancers.

Drug responses in mouse model revealed 12 distinct meta-programs associated with TME remodeling, enriched in biological processes such as antigen presentation, tissue repair, and salt stress response. Notably, myeloid-derived suppressor cells were markedly reduced in responsive TMEs compared with other cell types, underscoring their key immunosuppressive role. We developed an MP scoring algorithm to quantify TME responsiveness, which successfully identified allopurinol-a gout medication-as a potent enhancer of anti-programmed cell death protein-1 therapy. This combination led to significant tumor-free outcomes (4/6) in vivo.

This work provides a robust framework for assessing TME remodeling that uncovers genes and compounds that significantly modulate immunotherapeutic efficacy.