Despite recent advances in the use of immunotherapy, only a minority of patients with small cell lung cancer (SCLC) respond to immune checkpoint blockade (ICB). Here, we show that targeting the DNA damage response (DDR) proteins PARP and checkpoint kinase 1 (CHK1) signifi cantly increased protein and surface expression of PD-L1. PARP or CHK1 inhibition remarkably potentiated the antitumor effect of PD-L1 blockade and augmented cytotoxic T-cell infi ltration in multiple immunocompetent SCLC in vivo models. CD8 + T-cell depletion reversed the antitumor effect, demonstrating the role of CD8 + T cells in combined DDR-PD-L1 blockade in SCLC. We further demonstrate that DDR inhibition activated the STING/TBK1/IRF3 innate immune pathway, leading to increased levels of chemokines such as CXCL10 and CCL5 that induced activation and function of cytotoxic T lymphocytes. Knockdown of cGAS and STING successfully reversed the antitumor effect of combined inhibition of DDR and PD-L1. Our results defi ne previously unrecognized innate immune pathway-mediated immunomodulatory functions of DDR proteins and provide a rationale for combining PARP/CHK1 inhibitors and immunotherapies in SCLC. SIGNIFICANCE: Our results defi ne previously unrecognized immunomodulatory functions of DDR inhibitors and suggest that adding PARP or CHK1 inhibitors to ICB may enhance treatment effi cacy in patients with SCLC. Furthermore, our study supports a role of innate immune STING pathway in DDR-mediated antitumor immunity in SCLC.

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Crucial transitions in cancer-including tumor initiation, local expansion, metastasis, and therapeutic resistance-involve complex interactions between cells within the dynamic tumor ecosystem. Transformative single-cell genomics technologies and spatial multiplex in situ methods now provide an opportunity to interrogate this complexity at unprecedented resolution. The Human Tumor Atlas Network (HTAN), part of the National Cancer Institute (NCI) Cancer Moonshot Initiative, will establish a clinical, experimental, computational, and organizational framework to generate informative and accessible three-dimensional atlases of cancer transitions for a diverse set of tumor types. This effort complements both ongoing efforts to map healthy organs and previous largescale cancer genomics approaches focused on bulk sequencing at a single point in time. Generating single-cell, multiparametric, longitudinal atlases and integrating them with clinical outcomes should help identify novel predictive biomarkers and features as well as therapeutically relevant cell types, cell states, and cellular interactions across transitions. The resulting tumor atlases should have a profound impact on our understanding of cancer biology and have the potential to improve cancer detection, prevention, and therapeutic discovery for better precision-medicine treatments of cancer patients and those at risk for cancer.Cancer forms and progresses through a series of critical transitions-from pre-malignant to malignant states, from locally contained to metastatic disease, and from treatment-responsive to treatment-resistant tumors (Figure 1). Although specifics differ across tumor types and patients, all transitions involve complex dynamic interactions between diverse pre-malignant, malignant, and non-malignant cells (e.g., stroma cells and immune cells), often organized in specific patterns within the tumor

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