Publications by authors named "Jacks T"

Tumor progression is driven by dynamic interactions between cancer cells and their surrounding microenvironment. Investigating the spatiotemporal evolution of tumors can provide crucial insights into how intrinsic changes within cancer cells and extrinsic alterations in the microenvironment cooperate to drive different stages of tumor progression. Here, we integrate high-resolution spatial transcriptomics and evolving lineage tracing technologies to elucidate how tumor expansion, plasticity, and metastasis co-evolve with microenvironmental remodeling in a -driven mouse model of lung adenocarcinoma.

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In combination with cell-intrinsic properties, interactions in the tumor microenvironment modulate therapeutic response. We leveraged single-cell spatial transcriptomics to dissect the remodeling of multicellular neighborhoods and cell-cell interactions in human pancreatic cancer associated with neoadjuvant chemotherapy and radiotherapy. We developed spatially constrained optimal transport interaction analysis (SCOTIA), an optimal transport model with a cost function that includes both spatial distance and ligand-receptor gene expression.

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Anticancer immunity is predicated on leukocyte migration into tumors. Once recruited, leukocytes undergo substantial reprogramming to adapt to the tumor microenvironment. A major challenge in the field is distinguishing recently recruited from resident leukocytes in tumors.

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Here, we define a future of cancer team science adopting "radical collaboration"-in which six "Hallmarks of Cancer Collaboration" are utilized to propel cancer teams to reach new levels of productivity and impact in the modern era. This commentary establishes a playbook for cancer team science that can be readily adopted by others.

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Tumors comprise a complex ecosystem consisting of many cell types that communicate through secreted factors. Targeting these intercellular signaling networks remains an important challenge in cancer research. Cardiotrophin-like cytokine factor 1 (CLCF1) is an interleukin-6 (IL-6) family member secreted by cancer-associated fibroblasts (CAFs) that binds to ciliary neurotrophic factor receptor (CNTFR), promoting tumor growth in lung and liver cancer.

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A hallmark of cancer is the avoidance of immune destruction. This process has been primarily investigated in locally advanced or metastatic cancer; however, much less is known about how pre-malignant or early invasive tumours evade immune detection. Here, to understand this process in early colorectal cancers (CRCs), we investigated how naive colon cancer organoids that were engineered in vitro to harbour Apc-null, Kras and Trp53-null (AKP) mutations adapted to the in vivo native colonic environment.

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The human blood system is maintained through the differentiation and massive amplification of a limited number of long-lived haematopoietic stem cells (HSCs). Perturbations to this process underlie diverse diseases, but the clonal contributions to human haematopoiesis and how this changes with age remain incompletely understood. Although recent insights have emerged from barcoding studies in model systems, simultaneous detection of cell states and phylogenies from natural barcodes in humans remains challenging.

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Although low-dose computed tomography screening improves lung cancer survival in at-risk groups, inequality remains in lung cancer diagnosis due to limited access to and high costs of medical imaging infrastructure. We designed a needleless and imaging-free platform, termed PATROL (point-of-care aerosolizable nanosensors with tumor-responsive oligonucleotide barcodes), to reduce resource disparities for early detection of lung cancer. PATROL formulates a set of DNA-barcoded, activity-based nanosensors (ABNs) into an inhalable format.

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DNA mismatch repair deficiency (MMRd) is associated with a high tumor mutational burden (TMB) and sensitivity to immune checkpoint blockade (ICB) therapy. Nevertheless, most MMRd tumors do not durably respond to ICB and critical questions remain about immunosurveillance and TMB in these tumors. In the present study, we developed autochthonous mouse models of MMRd lung and colon cancer.

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In combination with cell intrinsic properties, interactions in the tumor microenvironment modulate therapeutic response. We leveraged high-plex single-cell spatial transcriptomics to dissect the remodeling of multicellular neighborhoods and cell-cell interactions in human pancreatic cancer associated with specific malignant subtypes and neoadjuvant chemotherapy/radiotherapy. We developed Spatially Constrained Optimal Transport Interaction Analysis (SCOTIA), an optimal transport model with a cost function that includes both spatial distance and ligand-receptor gene expression.

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Genetically engineered mouse models only capture a small fraction of the genetic lesions that drive human cancer. Current CRISPR-Cas9 models can expand this fraction but are limited by their reliance on error-prone DNA repair. Here we develop a system for in vivo prime editing by encoding a Cre-inducible prime editor in the mouse germline.

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Lymphocytes are key for immune surveillance of tumors, but our understanding of the spatial organization and physical interactions that facilitate lymphocyte anti-cancer functions is limited. We used multiplexed imaging, quantitative spatial analysis, and machine learning to create high-definition maps of lung tumors from a Kras/Trp53-mutant mouse model and human resections. Networks of interacting lymphocytes ("lymphonets") emerged as a distinctive feature of the anti-cancer immune response.

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A complete understanding of how exposure to environmental substances promotes cancer formation is lacking. More than 70 years ago, tumorigenesis was proposed to occur in a two-step process: an initiating step that induces mutations in healthy cells, followed by a promoter step that triggers cancer development. Here we propose that environmental particulate matter measuring ≤2.

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Diverse processes in cancer are mediated by enzymes, which most proximally exert their function through their activity. High-fidelity methods to profile enzyme activity are therefore critical to understanding and targeting the pathological roles of enzymes in cancer. Here, we present an integrated set of methods for measuring specific protease activities across scales, and deploy these methods to study treatment response in an autochthonous model of Alk-mutant lung cancer.

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Article Synopsis
  • * Current mouse models for LUAD are effective but slow and complicated, while cell line models are quick but don't fully represent disease progression.
  • * New organoid technologies are promising for studying LUAD, and this research has optimized conditions to create organoids from murine alveolar type 2 cells that closely mimic the disease, providing a powerful new model for future investigations.
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New highly-multiplexed imaging technologies have enabled the study of tissues in unprecedented detail. These methods are increasingly being applied to understand how cancer cells and immune response change during tumor development, progression, and metastasis, as well as following treatment. Yet, existing analysis approaches focus on investigating small tissue samples on a per-cell basis, not taking into account the spatial proximity of cells, which indicates cell-cell interaction and specific biological processes in the larger cancer microenvironment.

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Article Synopsis
  • Pancreatic ductal adenocarcinoma (PDAC) is a deadly cancer with limited treatment options, and current methods for understanding its molecular characteristics are inadequate.
  • Researchers used advanced techniques, including single-nucleus RNA sequencing and digital spatial profiling, to analyze 43 PDAC tumors, revealing key cellular subtypes and their interactions.
  • They identified new malignant cell programs linked to poor outcomes and established three distinct multicellular communities, providing insights that could improve patient stratification in clinical trials and guide targeted therapies.
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Immunosurveillance of cancer requires the presentation of peptide antigens on major histocompatibility complex class I (MHC-I) molecules. Current approaches to profiling of MHC-I-associated peptides, collectively known as the immunopeptidome, are limited to in vitro investigation or bulk tumour lysates, which limits our understanding of cancer-specific patterns of antigen presentation in vivo. To overcome these limitations, we engineered an inducible affinity tag into the mouse MHC-I gene (H2-K1) and targeted this allele to the KrasTrp53 mouse model (KP/KStrep).

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Tumor evolution is driven by the progressive acquisition of genetic and epigenetic alterations that enable uncontrolled growth and expansion to neighboring and distal tissues. The study of phylogenetic relationships between cancer cells provides key insights into these processes. Here, we introduced an evolving lineage-tracing system with a single-cell RNA-seq readout into a mouse model of Kras;Trp53(KP)-driven lung adenocarcinoma and tracked tumor evolution from single-transformed cells to metastatic tumors at unprecedented resolution.

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With increasing attention on the essential roles of the tumour microenvironment in recent years, the nervous system has emerged as a novel and crucial facilitator of cancer growth. In this Review, we describe the foundational, translational, and clinical advances illustrating how nerves contribute to tumour proliferation, stress adaptation, immunomodulation, metastasis, electrical hyperactivity and seizures, and neuropathic pain. Collectively, this expanding knowledge base reveals multiple therapeutic avenues for cancer neuroscience that warrant further exploration in clinical studies.

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The GATA4 transcription factor acts as a master regulator of development of multiple tissues. GATA4 also acts in a distinct capacity to control a stress-inducible pro-inflammatory secretory program that is associated with senescence, a potent tumor suppression mechanism, but also operates in non-senescent contexts such as tumorigenesis. This secretory pathway is composed of chemokines, cytokines, growth factors, and proteases.

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The state and behaviour of a cell can be influenced by both genetic and environmental factors. In particular, tumour progression is determined by underlying genetic aberrations as well as the makeup of the tumour microenvironment. Quantifying the contributions of these factors requires new technologies that can accurately measure the spatial location of genomic sequence together with phenotypic readouts.

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Prognostically relevant RNA expression states exist in pancreatic ductal adenocarcinoma (PDAC), but our understanding of their drivers, stability, and relationship to therapeutic response is limited. To examine these attributes systematically, we profiled metastatic biopsies and matched organoid models at single-cell resolution. In vivo, we identify a new intermediate PDAC transcriptional cell state and uncover distinct site- and state-specific tumor microenvironments (TMEs).

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