The Lampe laboratory investigates the control of cell growth both at the cell biological/ mechanistic level and through cancer biomarker discovery. We study the cell biology connecting gap junctions and intercellular communication (GJIC) with the control of cell growth, the cell cycle and, how the relationship is disrupted during carcinogenesis.
The Lampe laboratory investigates the kinases and pathways that regulate gap junction function during development, epidermal wounding, cardiac ischemia and cancinogenesis. Gap junctions allow diffusion of small molecules (<1000 MW) between adjacent cells via matched cell-to-cell membrane channels. Cell-cell communication via these channels is known to play an important role in the control of cell proliferation, embryonic development, cell differentiation, and the regulation of differentiated function in post-mitotic cells. Vertebrate gap junctions are composed of proteins derived from the connexin gene family, and our results indicate that gap junction formation and degradation are highly regulated via protein kinases at various stages of the assembly process and the cell cycle.
Ongoing studies include determination of the cellular localization of different connexin phosphorylation events and the specific serine substrates that are phosphorylated within connexins at different stages of the cell cycle. Thus, we attempt to link the activation of specific kinases to phosphorylation on a particular residue within the connexin protein and to connexin function in tissue including skin and heart. Our data indicates that kinases such as PKA, PKC, CK1, cdc2/cyclinB, MAP-K, Akt and others regulate specific steps of gap junction protein export, assembly, channel gating and degradation. To perform these studies of gap junction function, we utilize a variety of cell, molecular and biochemical techniques including super resolution microscopy, tracer microinjection and GFP chimeras to monitor gap junctions in living cells.
The Lampe laboratory performs studies to find blood tests or protein biomarkers that can indicate if and where a person has cancer and if it is present how to best treat it. Specifically, we are working to find early detection, recurrence or response biomarkers of colon, breast, pancreas and lung cancer. Useful biomarkers can allow doctors to find and treat cancer earlier and better saving lives, reducing costs and allowing for “personalized or precision medicine” where the treatment is specific for each person’s disease. Although in the past we have used a variety of mass spectrometry methods, currently our primary approach is to utilize high density antibody arrays to determine proteomic, glycoproteomic and auto-autoantibody markers of disease. We are especially interested in markers where the level of a protein, the level of its glycosylation or whether autoantibodies are produced to it can yield multi-dimensional information on each protein. We consider specific proteins that show consistent cancer-specific changes in 2 or 3 of these measurements to be “hybrid markers”. We hypothesize these markers will suffer less variation between different individuals since one component can act to “standardize” the other measurement.
Our approach to biomarker discovery is unique in several ways. Our discovery arrays contain over 3000 antibodies printed in triplicate giving us reliable and highly consistent data. The fact that we assay proteomic, glycomic and autoantibody changes gives us broad coverage of potential biomarkers. We can screen hundreds of samples in a week reducing false positives. For early detection, we have utilized large pre-diagnostic sample sets from screening cohorts (WHI, CHS, PLCO) reducing the chance that potential early detection biomarkers are not simply related to inflammation or disease burden. We validate in similar sized sample sets and the high denisty of the arrays allow us to retain hundreds of candidate biomarkers. Thus, we do not spend the time to develop individual assays until biomarkers have passed multiple validation steps and their utility is more clear reducing costs and prioritizing effort.