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Jacks, T.

Publications and source records attributed to Jacks, T..

25 records · Page 2Linked to original sources

Measuring kinetics and metastatic propensity of CTCs by blood exchange between mice

Existing pre-clinical methods for acquiring dissemination kinetics of rare circulating tumor cells (CTCs) en route to forming metastases have not been capable of providing a direct measure of CTC intravasation rate and subsequent half-life in the circulation. Here, we demonstrate an approach for measuring endogenous CTC kinetics by continuously exchanging CTC-containing blood over several hours between un-anesthetized, tumor-bearing mice and healthy, tumor-free counterparts. By tracking CTC transfer rates using an autochthonous small cell lung cancer model, we extrapolated half-life times in the circulation of 50-100 seconds and intravasation rates between 4,000 and 27,000 CTCs/hour - an average daily shedding rate equivalent to [~]0.07% of the total number of primary tumor cells in the lung. Additionally, transfer of 1-2% of daily-shed CTCs from late-stage tumor-bearing mice generated macrometastases in healthy recipient mice. We envision that our technique will help further elucidate the role of CTCs and the rate-limiting steps in metastasis.

cancer biology↗

Dissecting cell type-specific metabolism in pancreatic ductal adenocarcinoma

Tumors are composed of many different cell types including cancer cells, fibroblasts, and immune cells. Dissecting functional metabolic differences between various cell types within a mixed population can be limited by the rapid turnover of metabolites relative to the time needed to isolate cells. To overcome this challenge, we traced isotope-labeled nutrients into macromolecules that turn over more slowly than metabolites. This approach was used to assess differences between cancer cell and fibroblast metabolism in pancreatic cancer organoid-fibroblast co-cultures and in pancreatic tumors. In these contexts, we find pancreatic cancer cells exhibit increased pyruvate carboxylation relative to fibroblasts, and that this flux depends on both pyruvate carboxylase and malic enzyme 1 activity. Consequently, expression of both enzymes in cancer cells is necessary for organoid and tumor growth, demonstrating that dissecting the metabolism of specific cell populations within heterogeneous systems can identify dependencies that may not be evident from studying isolated cells in culture or bulk tumor tissue.

cancer biology↗

Spatially-Resolved Live Cell Tagging and Isolation Using Protected Photoactivatable Cell Dyes

Whether cultured in vitro or part of a complex tissue in vivo, a cells phenotype and function are significantly influenced by dynamic interactions with its microenvironment. To explicitly examine how a cells spatiotemporal activity impacts its behavior, we developed and validated a strategy termed SPACECAT--Spatially PhotoActivatable Color Encoded Cell Address Tags--to annotate, track, and isolate specific cells in a non-destructive, viability-preserving manner. In SPACECAT, a biological sample is immersed in a photocaged fluorescent molecule, and cells within a location of interest are labeled for further study by uncaging that molecule with user-patterned near-UV light. SPACECAT offers high spatial precision and temporal stability across diverse cell and tissue types, and is compatible with common downstream assays, including flow cytometry and single-cell RNA-Seq. Illustratively, we leveraged this approach in patient-derived intestinal organoids, a spatially complex system less amenable to genetic manipulations, to select for crypt-like regions enriched in stem-like and actively mitotic cells. Moreover, we demonstrate its applicability and utility on ex vivo tissue sections from four healthy organs and an autochthonous lung tumor model, uncovering spatially-biased gene expression patterns among immune cell subsets and identifying rare myeloid phenotypes enriched around tumor/healthy border regions. In sum, our method provides a minimally invasive and broadly applicable approach to link cellular spatiotemporal features and/or behavioral phenotypes with diverse downstream assays, enabling fundamental insights into the connections between tissue microenvironments and biological (dys)function.

systems biology↗

NINJA: an inducible genetic model for creating neoantigens in vivo

Mouse models with inducible neoantigens have been historically difficult to generate because of leaky expression of antigens in the thymus, which causes central tolerance in developing CD8 and CD4 T cells. Attempts to resolve this problem using existing genetic tools have been unsuccessful. We developed the iNversion INducible Joined neoAntigen (NINJA) mouse model that uses RNA splicing, DNA recombination, and three levels of regulation to prevent neoantigen leakiness and allow tight control over the induction of neoantigen expression. We describe the development of these genetic tools and their use for obtaining tumor cell lines with inducible neoantigen expression. Moreover, we show that the genetic regulation in NINJA mice bypasses central and peripheral tolerance mechanisms and allows for robust endogenous CD8 and CD4 T cells responses upon neoantigen induction in peripheral tissues. Thus, NINJA fills a long-standing gap in the field and will enable studies of how T cells respond to defined neoantigens in the context of peripheral tolerance, autoimmune diseases, and developing tumors.

immunology↗

Microenvironmental adaptations drive obesity-associated pancreatic cancer

Obesity is a major modifiable risk factor for pancreatic ductal adenocarcinoma (PDAC), yet how and when obesity contributes to PDAC progression is not well understood. Leveraging an autochthonous mouse model, we demonstrate a causal and reversible role for obesity in early PDAC progression, showing that obesity markedly enhances tumorigenesis, while genetic or dietary induction of weight loss intercepts cancer development. Bulk and single cell molecular analyses of human and murine samples define microenvironmental consequences of obesity that promote tumor development rather than new driver gene mutations. We observe increased inflammation and fibrosis and also provide evidence for significant pancreatic islet cell adaptation in obesity-associated tumors. Specifically, we identify aberrant islet beta cell expression of the peptide hormone cholecystokinin (CCK) in tumors as an adaptive response to obesity. Furthermore, beta cell CCK expression promotes oncogenic Kras-driven pancreatic ductal tumorigenesis. Our studies argue that PDAC progression is driven by local obesity-associated changes in the tumor microenvironment - rather than systemic effects - and implicate endocrine-exocrine signaling beyond insulin in PDAC development. Furthermore, our demonstration that these obesity-associated adaptations are reversible supports the use of anti-obesity strategies to intercept PDAC early during progression.

cancer biology↗

Longitudinal single cell profiling of regulatory T cells identifies IL-33 as a driver of tumor immunosuppression

Regulatory T cells (Tregs) can impair anti-tumor immune responses and are associated with poor prognosis in multiple cancer types. Tregs in human tumors span diverse transcriptional states distinct from those of peripheral Tregs, but their contribution to tumor development remains unknown. Here, we used single cell RNA-Seq to longitudinally profile conventional CD4+ T cells (Tconv) and Tregs in a genetic mouse model of lung adenocarcinoma. Tissue-infiltrating and peripheral CD4+ T cells differed, highlighting divergent pathways of activation during tumorigenesis. Longitudinal shifts in Treg heterogeneity suggested increased terminal differentiation and stabilization of an effector phenotype over time. In particular, effector Tregs had enhanced expression of the interleukin 33 receptor ST2. Treg-specific deletion of ST2 reduced effector Tregs, increased infiltration of CD8+ T cells into tumors, and decreased tumor burden. Our study shows that ST2 plays a critical role in Treg-mediated immunosuppression in cancer, highlighting new potential paths for therapeutic intervention.

cancer biology↗

Noninvasive lung cancer detection via pulmonary protease profiling

Lung cancer is the leading cause of cancer-related death and patients most commonly present with incurable metastatic disease. National guidelines recommend screening for high-risk patients with low-dose computed tomography (LDCT), but this approach has limitations including high false positive rates. Activity-based nanosensors (ABNs) detect dysregulated proteases in vivo and release a reporter to provide a urinary readout of disease activity. Here, we demonstrate the translational potential of ABNs by coupling ABN multiplexing with intrapulmonary delivery to detect early-stage lung cancer in an immunocompetent, genetically engineered mouse model (GEMM). The design of the multiplexed panel of sensors was informed by comparative transcriptomic analysis of human and mouse lung adenocarcinoma data sets and in vitro cleavage assays with recombinant candidate proteases. When employed in a Kras and Trp53 mutant lung adenocarcinoma mouse model, this approach confirmed the role of metalloproteases in lung cancer and enabled accurate early detection of disease, with 92% sensitivity and 100% specificity.

cancer biology↗