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Norgard, R. J.

Publications and source records attributed to Norgard, R. J..

2 recordsLinked to original sources

Pancreatic cancer cachexia is mediated by PTHrP-driven disruption of adipose de novo lipogenesis

Pancreatic cancer patients have the highest rates and most severe forms of cancer cachexia, yet cachexia etiologies remain largely elusive, leading to a lack of effective intervening therapies. Parathyroid hormone-related protein (PTHrP) has been clinically implicated as a putative regulator of cachexia, with serum PTHrP levels correlating with increased weight loss in PDAC patients. Here we show that cachectic PDAC patients have high expression of tumor PTHrP and use a genetically engineered mouse model to functionally demonstrate that loss of PTHrP blocks cachectic wasting, dramatically extending overall survival. The re-expression of PTHrP in lowly cachectic models is sufficient to induce wasting and reduce survival in mice, which is reversed by the conditional deletion of the PTHrP receptor, Pth1r, in adipocytes. Mechanistically, tumor-derived PTHrP suppresses de novo lipogenesis in adipocytes, leading to a molecular rewiring of adipose depots to promote wasting in the cachectic state. Finally, the pharmacological disruption of the PTHrP-PTH1R signaling axis abrogates wasting, highlighting that a targeted disruption of tumor-adipose crosstalk is an effective means to limit cachexia. STATEMENT OF SIGNIFICANCEPancreatic ductal adenocarcinoma (PDAC) is the prototypical cancer type associated with cancer cachexia, a debilitating wasting syndrome marked by adipose tissue loss and muscle atrophy. Herein, we establish that PTHrP is a tumor-derived factor that facilitates cachexia by downregulating de novo lipogenesis in adipocytes and that blocking PTHrP is an effective means to limit wasting in preclinical mouse models.

cancer biology↗

Single-cell lineage and transcriptome reconstruction of metastatic cancer reveals selection of aggressive hybrid EMT states

Metastatic cancer remains largely incurable due to an incomplete understanding of how cancer cells disseminate throughout the body. However, tools for probing metastatic dissemination and associated molecular changes at high resolution are lacking. Here we present multiplexed, activatable, clonal, and subclonal GESTALT (macsGESTALT), an inducible lineage recorder with concurrent single cell readout of transcriptional and phylogenetic information. By integrating multiple copies of combined static barcodes and evolving CRISPR/Cas9 barcodes, macsGESTALT enables clonal tracing and subclonal phylogenetic reconstruction, respectively. High barcode editing and recovery rates produce deep lineage reconstructions, densely annotated with transcriptomic information. Applying macsGESTALT to a mouse model of metastatic pancreatic cancer, we reconstruct dissemination of tens-of-thousands of single cancer cells representing 95 clones and over 6,000 unique subclones across multiple distant sites, e.g. liver and lung metastases. Transcriptionally, cells exist along a continuum of epithelial-to-mesenchymal transition (EMT) in vivo with graded changes in associated signaling, metabolic, and regulatory processes. Lineage analysis reveals that from a majority of non-metastatic, highly epithelial clones, a single dominant clone that has progressed along EMT drives the majority of metastasis. Within this dominant clone a parallel process occurs, where a small number of aggressive subclones drive clonal outgrowth. By precisely mapping subclones along the EMT continuum, we find that size and dissemination gradually increase, peaking at late-hybrid EMT states but precipitously falling once subclones are highly mesenchymal. Late-hybrid EMT states are selected from a predominately epithelial ancestral pool, enabling rapid metastasis but also forcing extensive and continuous population bottlenecking. Notably, late-hybrid gene signatures are associated with decreased survival in human pancreatic cancer, while epithelial, early-hybrid, and highly mesenchymal states are not. Our findings illuminate features of metastasis and EMT with the potential for therapeutic exploitation. Ultimately, macsGESTALT provides a powerful, accessible tool for probing cancer and stem cell biology in vivo.

cancer biology↗