斯坦福大学医学院

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal human cancers and shows resistance to any therapeutic strategy used. Here we tested small-molecule inhibitors targeting chromatin regulators as possible therapeutic agents in PDAC. We show that JQ1, an inhibitor of the bromodomain and extraterminal (BET) family of proteins, suppresses PDAC development in mice by inhibiting both MYC activity and inflammatory signals. The histone deacetylase (HDAC) inhibitor SAHA synergizes with JQ1 to augment cell death and more potently suppress advanced PDAC. Finally, using a CRISPR-Cas9-based method for gene editing directly in the mouse adult pancreas, we show that de-repression of p57 (also known as KIP2 or CDKN1C) upon combined BET and HDAC inhibition is required for the induction of combination therapy-induced cell death in PDAC. SAHA is approved for human use, and molecules similar to JQ1 are being tested in clinical trials. Thus, these studies identify a promising epigenetic-based therapeutic strategy that may be rapidly implemented in fatal human tumors.

Diverse fusions of echinoderm microtubule-associated protein-like 4 (EML4) and anaplastic lymphoma kinase (ALK) are oncogenic drivers in lung adenocarcinoma. EML4-ALK variants have distinct breakpoints within EML4, but their functional differences remain poorly understood. In this study, we use somatic genome editing to generate autochthonous mouse models of EML4-ALK-driven lung tumors and show that variant 3 (V3) is more oncogenic than variant 1 (V1). By using multiplexed genome editing and quantifying the effects of 29 putative tumor-suppressor genes on V1- and V3-driven lung cancer growth, we show that many tumor-suppressor genes have variant-specific effects on tumorigenesis. Pharmacogenomic analyses further suggest that tumor genotype can influence therapeutic responses. Analysis of human EML4-ALK-positive lung cancers also identified variant-specific differences in their genomic landscapes. These findings suggest that EML4-ALK variants behave more like distinct oncogenes than a uniform entity and highlight the dramatic impact of oncogenic fusion partner proteins and coincident tumor-suppressor gene alterations on the biology of oncogenic fusion-driven cancers. SIGNIFICANCE:EML4-ALK-driven lung cancer is treated as a uniform disease despite the presence of distinct fusion variants in patients. Our findings show that EML4-ALK variants are functionally distinct, which may have implications for the treatment of this cancer type and highlights the need to consider differences among variants of other oncogenic fusions.

Spatial proteomics enables high-resolution mapping of protein expression and can transform our understanding of biology and disease. However, major challenges remain for clinical translation, including cost, complexity and scalability. Here we present H&E to protein expression (HEX), an AI model designed to computationally generate spatial proteomics profiles from standard histopathology slides. Trained and validated on 819,000 histopathology image tiles with matched protein expression from 382 tumor samples, HEX accurately predicts the expression of 40 biomarkers encompassing immune, structural and functional programs. HEX demonstrates substantial performance gains over alternative methods for protein expression prediction from H&E images. We develop a multimodal data integration approach that combines the original H&E image and AI-derived virtual spatial proteomics to enhance outcome prediction. Applied to six independent non-small-cell lung cancer cohorts totaling 2,298 patients, HEX-enabled multimodal integration improved prognostic accuracy by 22% and immunotherapy response prediction by 24-39% compared with conventional clinicopathological and molecular biomarkers. Biological interpretation revealed spatially organized tumor-immune niches predictive of therapeutic response, including the co-localization of T helper cells and cytotoxic T cells in responders, and immunosuppressive tumor-associated macrophage and neutrophil aggregates in non-responders. HEX provides a low-cost and scalable approach to study spatial biology and enables the discovery and clinical translation of interpretable biomarkers for precision medicine.

Tissue-resident immunity mediates host defense against pathogens and enables rapid adaptive memory responses. However, the study of tissue-resident immunity is hindered by a singular lack of experimental systems allowing pathogenic epithelial infection amidst the full spectrum of endogenous immune subsets. Particularly in lung, differing notions of transient versus sustained residency of tissue-resident memory T cells (TRM) have questioned the extent to which recall immunity to respiratory pathogens occurs locally or in concert with secondary lymphoid organs. We thus generated long-term adult human distal lung organoids from intact tissue fragments in 3D air-liquid interface (ALI) culture that co-preserved epithelial and stromal architecture alongside endogenous lung-resident immune cells (T, B, NK, myeloid). The organoid T cells exhibited persistent cytokine-assisted maintenance, expressed residency and memory markers, and preserved T cell receptor (TCR) repertoires of cognate fresh tissue. SARS-CoV-2 vigorously infected the organoid lung epithelium, stimulated inflammatory cytokine production, and crucially, induced widespread SARS-CoV-2-specific, tissue-resident T cell responses. Our studies introduce a robust adult human lung organoid experimental system containing a physiologic air interface and diverse resident immune subsets, demonstrate the organ-autonomous sufficiency of lung pathogen memory T cell responses, distinct from secondary lymphoid tissue, and provide a platform to investigate tissue-resident immunity in health and disease.