Clinical-grade RAS inhibitors raise an unresolved question as to whether KRAS alleles impose constraints on adaptive resistance that can be exploited therapeutically. Using daraxonrasib (RMC-6236), a multi-selective RAS(ON) inhibitor, we compared resistance mechanisms between KRASG12D and KRASG12R, mutants with fundamentally different RAS network dynamics. Daraxonrasib inhibited KRASMUT primarily through steric occlusion of effector binding, while engaging RASWT only modestly (~20%). KRASG12R was marked by its inability to transactivate RASWT, and daraxonrasib resistant KRASG12R PDAC cells utilized EGFR/RASWT-GTP signaling as the dominant adaptive route. In contrast, KRASG12D resistance arose through retained KRASG12D-GTP signaling, with a decrease of cyclophilin A (CypA) protein, the binding partner required for daraxonrasib activity. The shift from KRASG12R dependence to EGFR/RASWT dependence conferred sensitivity to trametinib. As clinical confirmation, a KRASG12R PDAC patient who progressed after 10 months on daraxonrasib showed intratumoral EGFR/RASWT activation, and rapid 3D-bioprinted patient-derived tumoroid modeling predicted sensitivity to trametinib-based combination therapy. Despite the aggressive disease trajectory and lack of response to the two immediately preceding lines of therapy, sixth-line trametinib-based combination therapy achieved approximately 5 months of disease control, and this patient ultimately achieved 40 months of overall survival, far exceeding the 8-12 month median for metastatic PDAC. Collectively, these data establish a framework in which allele-specific RAS network topology dictates the adaptive resistance landscape, enabling rational selection of targeted therapies with meaningful clinical benefit in metastatic PDAC.

Neutrophil extracellular traps (NETs) have recently emerged as key modulators of cancer progression and metastasis. However, a more comprehensive understanding of the underlying mechanisms could help identify effective strategies to prevent and treat NET-mediated metastasis. Here, we observed a marked accumulation of intratumoral NETs in metastatic primary lung adenocarcinoma (LUAD). Tumor cells with elevated CXCL2 expression not only recruited neutrophils via interactions with CXCR2 but also facilitated NET formation. In turn, NET-derived DNA (NET-DNA), through specific DNA motifs, directly bound to the extracellular domain of integrin β1 (ITGB1), thereby activating FAK signaling and promoting invasion and metastasis. NET-DNA was capable of enhancing CXCL2 expression through MAPK-ELK1, thereby establishing a positive feedback loop that maintained continuous neutrophil recruitment and NET formation. In both in vitro and in vivo models, targeting either NETs or ITGB1-FAK signaling significantly inhibited LUAD metastasis. These findings suggest that the CXCL2-NET-ITGB1-FAK signaling axis plays a pivotal role in driving NET-mediated metastasis, which provides a rationale for targeting this signaling pathway to inhibit LUAD metastasis.

KRAS mutations occur in over 90% of pancreatic ductal adenocarcinomas (PDACs). Despite recent advances in targeting oncogenic KRAS, tumors eventually acquire resistance. A more comprehensive understanding of the mechanisms connecting KRAS signaling to tumor progression could facilitate the development of effective therapies to improve the treatment of KRAS-driven malignancies. Here, we dissected how oncogenic KRAS reprograms post-transcriptional regulation in PDAC. Oncogenic KRAS altered AGO2 phosphorylation at tyrosine 393, expanded the miRNA-mRNA interaction network, and impaired both mRNA destabilization and translational repression. Mapping endogenous miRNA-mRNA interactions using AGO2 chimeric eCLIP combined with genome-wide measurements of mRNA stability and translational efficiency using SLAM-seq and Ribo-eCLIP revealed that miRNA targets in KRAS-mutant cells exhibited increased stability and translational efficiency, even when cognate miRNA levels were unchanged. The rewiring enriched pro-tumorigenic transcripts involved in GTPase signaling, autophagy, and metabolism, and it was accompanied by the assembly of enlarged, static processing bodies (P-bodies) in cell lines, mouse models, and patient tumors, an effect that could be reversed by inhibiting oncogenic KRAS. Expression of a phospho-mimetic AGO2 Y393E reproduced the effects of oncogenic KRAS, while a phospho-deficient AGO2 Y393A blocked them. These findings identify a mechanistically distinct post-transcriptional effector arm of KRAS signaling, link AGO2 Y393 phosphorylation to both silencing dysfunction and condensate remodeling, and reveal opportunities to target RNA regulation in PDAC.

Immune checkpoint blockade (ICB) has revolutionized cancer treatment, yet its efficacy in gastrointestinal malignancies is often limited by an immunosuppressive tumor microenvironment. In this study, we identified phospholipase C beta 1 (PLCβ1) as a central driver of pathogenesis and ICB resistance in gastrointestinal cancer. Unlike classical oncogenes, PLCβ1 promoted tumor progression by fostering immune evasion rather than directly enhancing intrinsic tumor cell survival. Mechanistically, PLCβ1 interacted with ERC1, promoting its ubiquitin-proteasomal degradation. ERC1 destabilization suppressed NF-κB-dependent transcriptional activation of MHC-I, thereby impairing antigen presentation. Upstream, the YAP1 complex served as a direct transcriptional activator of PLCβ1, and pharmacological disruption of this pathway using the YAP inhibitor effectively restored MHC-I expression. Expression PLCβ1 was associated with reduced responsiveness to immunotherapy in patients, and combining the YAP inhibitor with anti-PD-1 therapy elicited synergistic antitumor responses in both syngeneic mice and patient-derived xenografts. Collectively, these findings uncover the YAP1-PLCβ1-MHC-I axis as a critical mechanism of immune escape and propose combinatorial YAP inhibition as a promising strategy to sensitize gastrointestinal tumors to immunotherapy.

Exercise induces a variety of changes in the tumor microenvironment with beneficial effects in several tumor types. However, a better understanding of the clinical effects of exercise and mediating mechanisms is needed to maximize the utility of exercise for patients. In this study, we analyzed tumors from pancreatic ductal adenocarcinoma (PDAC) patients in the PancFit trial and identified an exercise induced reduction in cells expressing alpha smooth muscle actin (αSMA). Interrogation of changes in tumor stromal composition with exercise in a murine PDAC model revealed a microbially-influenced reduction in αSMA+ cells and IL6 expressing inflammatory cancer associated fibroblasts (iCAFs). Cholic acid, a microbial bile acid, was increased in both patients and murine models with exercise, as a potential mediator of exercise induced reduction in iCAFs. Consistent with these findings, patients that exercised more also exhibited fewer iCAFs and lower tumor IL6 expression, supporting a stromal remodeling effect of physical activity. In summary, this study demonstrates that the anti-tumor effect of exercise includes stromal remodeling which is impacted by microbial metabolites.

The immune system can eradicate cancer, but various immunosuppressive mechanisms active within a tumor curb this beneficial response. However, unraveling the effects of multimodal interactions between tumor and immune cells and their contributions to tumor control using an experimental approach alone is time- and resource-intensive. To identify the critical immunological features associated with tumor control and escape, we built a mechanistic, structurally identifiable mathematical model of the interactions between CD8+ T cells, regulatory T cells (Tregs), dendritic cells, and tumor cells deeply rooted in current biological concepts. The model captured Treg accrual occurring after checkpoint blockade immunotherapy. After successfully fitting the mathematical model to experimental data from an immunogenic melanoma mouse model with acquired resistance to PD-1 immunotherapy and ensuring that the model was practically identifiable, hundreds of parameter sets were generated, each of which fit the data well and represented a unique 'virtual mouse' to capture variability across individuals. The model indicated that the initial tumor and immune conditions instruct cancer control or progression and that optimal initial ratios of immune cells exist that result in improved tumor control. The model further predicted that the Treg influx into the tumor is a key determinant of resistance to PD-1 immunotherapy. Experimental studies validated all these predictions from the model. Overall, this integrated approach of modeling and experimental validation identified crucial determinants of resistance to PD-1 immunotherapy and can be used to guide the development of more effective therapeutic strategies.

Spatial transcriptomic analyses provide spatially resolved gene expression data that can provide insights into complex biological processes. However, current spatial transcriptomics approaches remain financially prohibitive and restricted in resolution, scalability, and gene coverage, limiting broader adoption for large-scale studies. Here, we developed CarHE (contrastive alignment of gene expression for hematoxylin and eosin images), a multimodal pretraining framework that infers high-dimensional spatial transcriptomic profiles from routine H&E-stained slides. By using contrastive learning to align cell type-specific transcriptomic information with histological features, CarHE achieved high prediction accuracy across evaluated datasets and spatial transcriptomics platforms. CarHE approximated spatially organized pathological microenvironment features consistent with tertiary lymphoid structure (TLS)-associated regions in breast cancer, lung cancer, melanoma, and clear cell renal cell carcinoma. Additionally, CarHE inferred approximated 3D spatial transcriptomic context from 2D images, providing more informative neighborhood context than 2D visualization. In a cohort of 880 lung cancer patients, CarHE-derived features were associated with disease-free survival and outperformed current approaches. Overall, CarHE provides a cost-effective and scalable framework for H&E-based spatial inference, supporting further validation toward translational research applications.

The development and validation of prognostic and predictive biomarkers in breast cancer is limited by the availability of well-annotated datasets linking tumor molecular features to treatment response and survival outcomes. To address this need, we generated an extensive mouse models dataset comprised of 26 immunocompetent mammary tumor models spanning diverse genetic backgrounds, epithelial-mesenchymal states, the basal-luminal axis, and distinct immune microenvironments. For each model, survival was measured under no treatment, immune checkpoint inhibition (ICI), and carboplatin/paclitaxel chemotherapy, and RNA-sequencing was performed on baseline tumors and on 7-day on-treatment samples for both regimens. Baseline murine tumor gene expression features were used to train a machine learning Elastic Net model that predicted survival outcomes on multiple human breast cancer datasets with performance comparable to that of existing prognostic assays. Models trained for ICI benefit, using either the untreated or 7-day ICI treated samples, predicted ICI benefit on human ICI treated datasets, with the 7-day treated tumor model showing better performance. A predictor of carboplatin/paclitaxel response developed from the murine mammary tumor data performed well in mice but did not generalize to human chemotherapy cohorts. Finally, comparison of multiple computational approaches, including XGBoost, random forests, and support vector regression, showed that all methods successfully predicted survival outcomes, with Elastic Net offering the best performance and interpretability. These results indicate conserved cancer biology between mouse and human tumors for prognosis and ICI response and establish a large preclinical dataset with linked phenotypic and genomic data as a resource for biomarker discovery.

KRAS mutations are a major driver of pancreatic ductal adenocarcinoma (PDAC). RASA2, a RAS GTPase-activating protein, modulates KRAS protein levels in wild-type contexts, suggesting it could play a potential role in PDAC. Here, we systematically investigated the biological function and molecular mechanisms of RASA2 in PDAC. Integrative analyses of multiple datasets and clinical samples demonstrated that RASA2 was consistently upregulated in KRAS-mutant PDAC and significantly associated with poor prognosis and metastatic progression. Gain- and loss-of-function studies revealed that RASA2 markedly enhanced PDAC cell migration and invasion in both KRAS-mutant and KRAS-wild-type models, suggesting that its pro-metastatic activity is largely independent of KRAS mutational status. Transcriptomic and mechanistic analyses revealed that RASA2 activated GLI1 through a TGFβ2-dependent, non-canonical Hedgehog pathway. Mechanistically, RASA2 interacted with RTF1 to promote H2BK120 ubiquitination at the TGFB2 promoter, thereby enhancing TGFβ2 transcription and activating downstream GLI1 signaling. Pharmacological inhibition of TGFβ signaling or genetic silencing of GLI1 effectively suppressed RASA2-driven migratory, invasive, and metastatic phenotypes in vitro and in vivo. Collectively, these findings reveal a mechanism by which RASA2-dependent epigenetic and transcriptional reprogramming promotes metastatic progression and nominate the RASA2- TGFβ2-GLI1 axis as a potential therapeutic target in PDAC.

Mutant KRAS inhibition has revolutionized the treatment of lung adenocarcinoma. Unfortunately, responses to this form of targeted therapy are often of limited duration because of the development of resistance. Targeted protein degradation, including using PROTACs (PROteolysis-TArgeting Chimeras), presents an alternative approach to targeting oncogenic drivers in cancer. In this issue of Cancer Research, Martín and colleagues developed a dTAG-KRASG12V syngeneic mouse model that allows for the study of the effects of degrading the KRASG12V oncoprotein in vivo. The authors discovered that degrading the KRASG12V oncoprotein leads to regression of the resulting lung adenocarcinoma tumors. Most of the regression was based on cancer cell-intrinsic responses, although the tumor microenvironment also underwent substantial remodeling. Despite the initial efficacy of the treatment, the authors found that prolonged PROTAC KRAS degrader treatment eventually resulted in relapse. Resistance to PROTAC treatment seemed to be driven by dysregulation of the ubiquitin-proteasome system that is required for the activity of the PROTAC degraders. Despite developing resistance to the PROTAC degraders, the resulting tumors were still dependent on the KRAS oncoprotein, meaning that they were still sensitive to conventional KRAS inhibitors. Thus, PROTACs that degrade the KRAS oncoprotein are a promising modality for the treatment of lung adenocarcinomas. Resistance to PROTACs may differ from conventional KRAS inhibitors, suggesting potential strategies for overcoming such resistance. See related article by Martín et al., p. 4115.

The Tn antigen, a truncated O-glycan, is frequently elevated in pancreatic ductal adenocarcinoma (PDAC). Multiple therapeutic approaches targeting Tn have been developed, but they have not demonstrated clear efficacy signals in early phase clinical studies. Improving Tn-targeted strategies in PDAC will require both overcoming the immunosuppressive tumor microenvironment and defining pathways by which truncated O-glycans promote growth and immune evasion. Here, we showed that Tn reshapes the tumor immune landscape of PDAC. Expression of Tn antigen on PDAC cells enhanced proliferation in vitro and tumor growth in vivo. Tn expression remodeled the immune microenvironment, skewing tumor-associated macrophages toward M2-like phenotypes, reducing cross-presenting dendritic cells, and expanding myeloid-derived suppressor cells (MDSCs). Single-cell RNA sequencing confirmed expansion of MDSCs and downregulation of antigen processing and presentation in the immune cell infiltrate of Tn+ tumors. Tumor-intrinsic transcriptomic analyses revealed activation of TNF-α/NF-κB signaling and induction of IL-34, a cytokine linked to monocyte survival and differentiation in Tn antigen expressing tumors. Additionally, high Tn expression in both organoids derived from pancreatic cancer patients and in PDAC mouse models was associated with increased IL-34 expression. Genetic deletion of Il34 in PDAC cells attenuated Tn-driven tumorigenesis and reduced MDSC infiltration, while recombinant IL-34 promoted myeloid cell differentiation and proliferation in vitro. Together, these findings establish a glyco-immune-cytokine axis in which truncated O-glycans contribute to IL-34-mediated immunosuppression, providing mechanistic insight and potential therapeutic targets in PDAC.

Fasting-mimicking diets (FMD) have been reported to increase the anti-tumor efficacy in preclinical studies in various cancers. FMD can impact the tumor microenvironment (TME), and elucidating the mechanisms and cells mediating the effects of FMD may uncover combination treatment strategies. Here, we performed single-cell transcriptomic sequencing to characterize the TME changes induced by FMD intervention in a mouse model of spontaneous breast cancer. The sequencing data indicated that FMD suppressed tumor cell stemness, promoted apoptosis, and increased the infiltration of innate and adaptive immune cells, especially natural killer (NK) cells and effector CD8+T cells. Importantly, FMD induced phenotypic reprogramming of cancer-associated fibroblasts (CAFs), leading to a decrease in the immunosuppressive inflammatory CAF (iCAF) subset. Mechanistically, FMD decreased platelet-derived growth factor C (PDGFC) secretion in tumor cells by reducing glucose and inhibiting glycolysis to reprogram CAFs. PDGFC increased activation of the JAK/STAT3 pathway, which induced iCAF differentiation. Combining FMD with PDGFR inhibitors increased the efficacy of anti-PD-L1 immunotherapy in vivo. Overall, this study reveals a mechanism of metabolic-immune rewiring through which FMD suppresses tumor progression, providing preliminary evidence for the potential of combination FMD-based strategies in breast cancer treatment.

Prostate cancer (PCa) frequently metastasizes to bone, marking incurable disease. This progression is driven by an immunologically cold bone tumor microenvironment that fosters resistance to therapy. To define the mechanisms underlying this uniquely immunosuppressive niche, we applied spatial single cell analyses across primary tumors and metastatic sites. Bone metastases showed marked suppression of tumor-intrinsic type I interferon (IFN-I) signaling and loss of antigen presentation, features that were strongly associated with reduced bone metastasis-free survival. Tumor-intrinsic IFN-I expression correlated with memory T cell infiltration, whereas the bone myeloid compartment was enriched for protumor macrophages and showed reduced dendritic cell (DC) activation and antigen presentation. Digital spatial profiling of matched tumors revealed a broad loss of IFN-I-regulated immunostimulatory and checkpoint molecules. Notably, B7-H3, a putative negative regulator of IFN-I, was highly expressed in bone metastases and inversely associated with antigen presentation. These findings define bone-specific mechanisms of immune resistance and highlight therapeutic vulnerabilities that could inform precision therapeutic strategies for PCa.

High levels of immune suppression are a common intrinsic mechanism of resistance in metastatic breast cancer that calls for developing immunotherapeutic combinations to broaden treatment responses. Histone deacetylase (HDAC) inhibitors can sensitize tumors to dual checkpoint inhibition in patients. Here, we investigated the tumor microenvironment (TME) of breast metastases by combining experimental and clinical data with theory to elucidate the mechanism of response to treatment with the HDAC inhibitor entinostat combined with anti-PD-1 and anti-CTLA-4. Knowledge-guided subclustering of single-cell RNA-sequencing (scRNA-seq) data and cell circuit analyses from murine breast-to-lung metastases identified 39 cell states and salient interactions, of which myeloid, T cell, and B cell subpopulations were most affected. Analyses of patient biopsies and blood via spatial proteomics and flow cytometry corroborated the preclinical findings, showing increased T cell and B cell activation, mature tertiary lymphoid structures, and increased CD8+ T cell-macrophage distances in responders to entinostat + nivolumab + ipilimumab. Combination treatment increased immunoglobulin production in patients and mice, and murine studies demonstrated increased tumor-targeting IgG and implicated B cells as necessary for treatment response. Inhibition of the ICAM1 and IFNγ pathways in myeloid cells partially recapitulated treatment effects on CD8+ T cells observed via scRNA-seq. Mathematical modeling of tumor-immune dynamics implicated simultaneous modulation of multiple TME interactions as required for response to the combination treatment. Overall, this study identifies lymphoid and myeloid cell contributions to response to treatment with HDAC inhibitors and immune checkpoint blockade, providing a framework for discovering interactions driving responses in complex TMEs.