Decoding and engineering the tumor secretome for precision immunotherapy

Tumor-secreted factors are critical regulators of anti-tumor immunity. During cancer progression, malignant, immune, and stromal cells release diverse secreted molecules that collectively form the tumor secretome, which directs the tumor microenvironment (TME) toward immunosensitive or immunosuppressive states by regulating immune cell infiltration, activation, and exhaustion. Immune checkpoint blockade (ICB) therapies, such as anti–PD-1 and anti–CTLA-4 antibodies, have markedly improved survival in select cancers. Despite these successes, most malignancies remain resistant. Prior studies have shown that resistance to ICB is frequently associated with immunosuppressive TMEs driven by extrinsic signals. The tumor secretome therefore represents a promising therapeutic target for overcoming resistance, given its extracellular accessibility and amenability to antibody-based intervention. However, comprehensive and unbiased identification of immune dependencies within the tumor secretome remains a major challenge. Conventional high-throughput pooled genomic screens often fail to capture such dependencies, as surrounding unperturbed cells can compensate for the loss of secreted factors, thereby masking immune-related fitness effects. Our goal is to systematically identify tumor-secreted immune dependencies that act through non–cell-autonomous mechanisms in vivo and to translate these insights into therapeutic strategies. Here, we developed a high-throughput, clonal in vivo CRISPR screening platform. By engrafting single-cell–derived tumor clones in murine lungs and comparing guide representation across immune contexts, we identified genes essential for tumor immune evasion with CRISPR knockout screens. We extended this approach with CRISPR activation-based clonal screens targeting 580 highly expressed genes encoding secreted factors across most human cancer types. These screens were performed in three murine syngeneic cancer models, B16 (melanoma), KP (lung adenocarcinoma), and KPC (PDAC). Using appropriate cell-extrinsic positive controls and cell-intrinsic controls, we demonstrated that clonal screening robustly captures known immunomodulatory factors that are frequently overlooked in mixed-cell pooled screens. Applying this approach, we identified the tumor-associated tissue factor F3 as a previously unrecognized, broadly-acting driver of tumor progression across multiple cancer types. Ongoing studies focus on dissecting the mechanistic basis for the inhibitory role of F3 using spatial profiling of the tumor microenvironment and transcriptional analyses of tumor and immune cells. In parallel, we developed a strategy to selectively augment anti-tumor immunity within tumors. Using cancer-specific fusion transcripts as malignancy markers, we engineered reprogrammable RNA sensing systems (RADARS) that detect these transcripts and trigger expression of immune-stimulatory payloads. Given the inherent limitations of in vivo delivery, these payloads are designed to be secreted, allowing rare intracellular detection events to be amplified into microenvironment-wide immune responses. Together, these studies establish a unified framework for precision immunotherapy that integrates systematic discovery of immune-modulating secreted factors with programmable, tumor-specific immune activation. By identifying secreted immune dependencies that act non-cell-autonomously and pairing them with cancer-specific in vivo delivery designs, this work provides generalizable and tractable strategies to enhance therapeutic selectivity and efficacy across diverse cancer types.