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Single-cell technologies have elucidated mechanisms responsible for immune checkpoint inhibitor (ICI) response, but are not amenable to a clinical diagnostic setting. In contrast, bulk RNA sequencing (RNA-seq) is now routine for research and clinical applications. Our workflow uses transcription factor (TF)-directed co-expression networks (regulons) inferred from single-cell RNA-seq data to deconvolute immune functional states from bulk RNA-seq data. Regulons preserve the phenotypic variation in CD45+ immune cells from metastatic melanoma samples (n=19, discovery dataset) treated with ICIs, despite reducing dimensionality by > 100-fold. Four cell states, termed exhausted T cells, monocyte lineage cells, memory T cells, and B cells were associated with therapy response; and were characterized by differentially active and cell-state specific regulons. Clustering of bulk RNA-seq melanoma samples from four independent studies (n=209, validation dataset) according to regulon-inferred scores identified four groups with significantly different response outcomes (p < 0.001). An intercellular link was established between exhausted T cells and monocyte lineage cells, whereby their cell numbers were correlated, and exhausted T cells predicted prognosis as a function of monocyte lineage cell number. The ligand–receptor expression analysis suggested that monocyte lineage cells drive exhausted T cells into terminal exhaustion through programs that regulate antigen presentation, chronic inflammation, and negative co-stimulation. Together, our results demonstrate how regulon-based characterization of cell states provide robust and functionally informative markers that can deconvolve bulk RNA-seq data to identify ICI responders.

The DNA damage response (DDR) and epithelial-to-mesenchymal transition (EMT) are two crucial cellular programs in cancer biology. While the DDR orchestrates cell cycle progression, DNA repair and cell death, EMT promotes invasiveness, cellular plasticity and intratumor heterogeneity. Therapeutic targeting of EMT transcription factors, such as ZEB1, remains challenging, but tumor-promoting DDR alterations elicit specific vulnerabilities. Using multi-omics, inhibitors and high-content microscopy, we discover a chemoresistant ZEB1 high expressing sub-population (ZEB1hi) with co-rewired cell cycle progression and proficient DDR across tumor entities. ZEB1 stimulates accelerated S-phase entry via CDK6, inflicting endogenous DNA replication stress. However, DDR buildups involving constitutive MRE11-dependent fork resection allow homeostatic cycling and enrichment of ZEB1hi cells during TGFβ-induced EMT and chemotherapy. Thus, ZEB1 promotes G1/S transition to launch a progressive DDR benefitting stress tolerance, which concurrently manifests a targetable vulnerability in chemoresistant ZEB1hi cells. Our study thus highlights the translationally relevant intercept of the DDR and EMT.&nbsp