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Granger, J.

Publications and source records attributed to Granger, J..

2 recordsLinked to original sources

HCN channels sense temperature and determine heart rate responses to heat

Heart rate increases with heat, [1-3] constituting a fundamental physiological relationship in vertebrates. Each normal heartbeat is initiated by an action potential generated in a sinoatrial nodal pacemaker cell. Pacemaker cells are enriched with hyperpolarization activated cyclic nucleotide-gated ion channels (HCN) that deliver cell membrane depolarizing inward current that triggers action potentials. HCN channel current increases due to cAMP binding, a mechanism coupling adrenergic tone to physiological fight or flight heart rate acceleration. However, the mechanism(s) for heart rate response to thermal energy is unknown. We used thermodynamical and homology computational modeling, site-directed mutagenesis and mouse models to identify a concise motif on the S4-S5 linker of the cardiac pacemaker HCN4 channels (M407/Y409) that determines HCN4 current (If) and cardiac pacemaker cell responses to heat. This motif is required for heat sensing in cardiac pacemaker cells and in isolated hearts. In contrast, the cyclic nucleotide binding domain is not required for heat induced HCN4 current increases. However, a loss of function M407/Y409 motif mutation prevented normal heat and cAMP responses, suggesting that heat sensing machinery is essential for operating the cAMP allosteric pathway and is central to HCN4 modulation. The M407/Y409 motif is conserved across all HCN family members suggesting that HCN channels participate broadly in coupling heat to changes in cell membrane excitability.

physiology↗

Three-dimensional genomic mapping of human pancreatic tissue reveals striking multifocality and genetic heterogeneity in precancerous lesions

Pancreatic intraepithelial neoplasia (PanIN) is a precursor to pancreatic cancer and represents a critical opportunity for cancer interception. However, the number, size, shape, and connectivity of PanINs in human pancreatic tissue samples are largely unknown. In this study, we quantitatively assessed human PanINs using CODA, a novel machine-learning pipeline for 3D image analysis that generates quantifiable models of large pieces of human pancreas with single-cell resolution. Using a cohort of 38 large slabs of grossly normal human pancreas from surgical resection specimens, we identified striking multifocality of PanINs, with a mean burden of 13 spatially separate PanINs per cm3 of sampled tissue. Extrapolating this burden to the entire pancreas suggested a median of approximately 1000 PanINs in an entire pancreas. In order to better understand the clonal relationships within and between PanINs, we developed a pipeline for CODA-guided multi-region genomic analysis of PanINs, including targeted and whole exome sequencing. Multi-region assessment of 37 PanINs from eight additional human pancreatic tissue slabs revealed that almost all PanINs contained hotspot mutations in the oncogene KRAS, but no gene other than KRAS was altered in more than 20% of the analyzed PanINs. PanINs contained a mean of 13 somatic mutations per region when analyzed by whole exome sequencing. The majority of analyzed PanINs originated from independent clonal events, with distinct somatic mutation profiles between PanINs in the same tissue slab. A subset of the analyzed PanINs contained multiple KRAS mutations, suggesting a polyclonal origin even in PanINs that are contiguous by rigorous 3D assessment. This study leverages a novel 3D genomic mapping approach to describe, for the first time, the spatial and genetic multifocality of human PanINs, providing important insights into the initiation and progression of pancreatic neoplasia.

cancer biology↗