Faculty Bibliography

BACKGROUND: Targeted therapies in renal cell carcinoma can have different effects on primary and metastatic tumors. To pave the way for predictive biomarker development, we assessed differences in expression of targets of currently approved drugs in matched primary and metastatic specimens from 34 patients. METHODS: Four cores from each site were embedded in tissue microarray blocks. Expression of B-Raf, C-Raf, cKIT, FGF-R1, HIF-2alpha, mTOR, PDGF-Rbeta, VEGF-R1, VEGF-R2, VEGF-R3, VEGF, VEGF-B, VEGF-C, VEGF-D, MEK1, and ERK1/2 was studied using a quantitative immunofluorescence method. RESULTS: No significant differences were observed in global expression levels in primary and metastatic renal cell carcinoma tumors, with the exception of MEK, which had higher expression in metastatic than primary specimens. Similarly, more ki67 positive cells were seen in metastatic specimens. Correlations between marker expression in primary and metastatic specimens were variable, with the lowest correlation seen for FGF-R1 and VEGF-D. There were no significant differences in the degree of heterogeneity in primary versus metastatic tumors. CONCLUSIONS: Expression of most of the studied markers was similar in primary and metastatic renal cell carcinoma tumors, suggesting that predictive biomarker testing for these markers can be conducted on either the primary or metastatic tumors for most markers.

Here, we show that apolipoprotein A1 (apoA1), the major protein component of high density lipoprotein (HDL), through both innate and adaptive immune processes, potently suppresses tumor growth and metastasis in multiple animal tumor models, including the aggressive B16F10L murine malignant melanoma model. Mice expressing the human apoA1 transgene (A1Tg) exhibited increased infiltration of CD11b(+) F4/80(+) macrophages with M1, anti-tumor phenotype, reduced tumor burden and metastasis, and enhanced survival. In contrast, apoA1-deficient (A1KO) mice showed markedly heightened tumor growth and reduced survival. Injection of human apoA1 into A1KO mice inoculated with tumor cells remarkably reduced both tumor growth and metastasis, enhanced survival, and promoted regression of both tumor and metastasis burden when administered following palpable tumor formation and metastasis development. Studies with apolipoprotein A2 revealed the anti-cancer therapeutic effect was specific to apoA1. In vitro studies ruled out substantial direct suppressive effects by apoA1 or HDL on tumor cells. Animal models defective in different aspects of immunity revealed both innate and adaptive arms of immunity contribute to complete apoA1 anti-tumor activity. This study reveals a potent immunomodulatory role for apoA1 in the tumor microenvironment, altering tumor-associated macrophages from a pro-tumor M2 to an anti-tumor M1 phenotype. Use of apoA1 to redirect in vivo elicited tumor-infiltrating macrophages toward tumor rejection may hold benefit as a potential cancer therapeutic.

Coronary artery disease, resulting from atherosclerosis, is the leading cause of death in the Western world. Most previous studies have subjected atherosclerotic arteries, a tissue of mixed cellular composition, to homogenization in order to identify the factors in plaque development, thereby obscuring information relevant to specific cell types. Because macrophage foam cells are critical mediators in atherosclerotic plaque advancement, we reasoned that performing gene analysis on those cells would provide specific insight in novel regulatory factors and potential therapeutic targets. We demonstrated for the first time in vascular biology that foam cell-specific RNA can be isolated by laser capture microdissection (LCM) of plaques. As expected, compared to whole tissue, a significant enrichment in foam cell-specific RNA transcripts was observed. Furthermore, because regression of atherosclerosis is a tantalizing clinical goal, we developed and reported a transplantation-based mouse model. This involved allowing plaques to form in apoE-/- mice and then changing the plaque's plasma environment from hyperlipidemia to normolipidemia. Under those conditions, rapid regression ensued in a process involving emigration of plaque foam cells to regional and systemic lymph nodes. Using LCM, we were able to show that under regression conditions, there was decreased expression in foam cells of inflammatory genes, but an up-regulation of cholesterol efflux genes. Interestingly, we also found that increased expression of chemokine receptor CCR7, a known factor in dendritic cell migration, was required for regression. In conclusion, the LCM methods described in this chapter, which have already lead to a number of striking findings, will likely further facilitate the study of cell type-specific gene expression in animal and human plaques during various stages of atherosclerosis, and after genetic, pharmacologic, and environmental perturbations.

Hyperlipidemia is a risk factor for various cardiovascular and metabolic disorders. Overproduction of lipoproteins, a process that is dependent on microsomal triglyceride transfer protein (MTP), can contribute to hyperlipidemia. We show that microRNA-30c (miR-30c) interacts with the 3' untranslated region of MTP mRNA and induces its degradation, leading to reductions in MTP activity and in apolipoprotein B (APOB) secretion. miR-30c also reduces lipid synthesis independently of MTP. Hepatic overexpression of miR-30c reduced hyperlipidemia in Western diet-fed mice by decreasing lipid synthesis and the secretion of triglyceride-rich ApoB-containing lipoproteins and decreased atherosclerosis in Apoe(-/-) mice. Furthermore, inhibition of hepatic miR-30c by anti-miR-30c increased hyperlipidemia and atherosclerosis. Therefore, miR-30c coordinately reduces lipid biosynthesis and lipoprotein secretion, thereby regulating hepatic and plasma lipid concentrations. Raising miR-30c levels might be useful in treating hyperlipidemias and associated disorders.

Researchers generating new genome-wide data in an exploratory sequencing study can gain biological insights by comparing their data with well-annotated data sets possessing similar genomic patterns. Data compression techniques are needed for efficient comparisons of a new genomic experiment with large repositories of publicly available profiles. Furthermore, data representations that allow comparisons of genomic signals from different platforms and across species enhance our ability to leverage these large repositories. Here, we present a signal processing approach that characterizes protein-chromatin interaction patterns at length scales of several kilobases. This allows us to efficiently compare numerous chromatin-immunoprecipitation sequencing (ChIP-seq) data sets consisting of many types of DNA-binding proteins collected from a variety of cells, conditions and organisms. Importantly, these interaction patterns broadly reflect the biological properties of the binding events. To generate these profiles, termed Arpeggio profiles, we applied harmonic deconvolution techniques to the autocorrelation profiles of the ChIP-seq signals. We used 806 publicly available ChIP-seq experiments and showed that Arpeggio profiles with similar spectral densities shared biological properties. Arpeggio profiles of ChIP-seq data sets revealed characteristics that are not easily detected by standard peak finders. They also allowed us to relate sequencing data sets from different genomes, experimental platforms and protocols. Arpeggio is freely available at http://sourceforge.net/p/arpeggio/wiki/Home/.

Connexins form a family of transmembrane proteins that consists of 20 members in humans and 21 members in mice. Six connexins assemble into a connexon that can function as a hemichannel or connexon that can dock to a connexon expressed by a neighbouring cell, thereby forming a gap junction channel. Such intercellular channels synchronize responses in multicellular organisms through direct exchange of ions, small metabolites, and other second messenger molecules between the cytoplasms of adjacent cells. Multiple connexins are expressed in the cardiovascular system. These connexins not only experience the different biomechanical forces within this system, but may also act as effector proteins in co-ordinating responses within groups of cells towards these forces. This review discusses recent insights regarding regulation of cardiovascular connexins by mechanical forces and junctions. It specifically addresses effects of (i) shear stress on endothelial connexins, (ii) hypertension on vascular connexins, and (iii) changes in afterload and the composition of myocardial mechanical junctions on cardiac connexins.

IMPORTANCE Crouzon syndrome with acanthosis nigricans is a distinct disorder caused by a mutation in the FGFR3 gene, featuring craniosynostosis, characteristic facial features, and atypical and extensive acanthosis nigricans. Other cutaneous findings have not been thoroughly described. OBSERVATIONS We report 6 cases and summarize the existing literature with regard to the cutaneous manifestations of this disorder. All patients have widespread, early-onset acanthosis nigricans. Patients often have prominent hypopigmented scars at surgical sites and nevi arising early in childhood. CONCLUSIONS AND RELEVANCE In addition to craniofacial malformations, Crouzon syndrome with acanthosis nigricans results in characteristic cutaneous findings.

Revealing the clonal composition of a single tumor is essential for identifying cell subpopulations with metastatic potential in primary tumors or with resistance to therapies in metastatic tumors. Sequencing technologies provide only an overview of the aggregate of numerous cells. Computational approaches to de-mix a collective signal composed of the aberrations of a mixed cell population of a tumor sample into its individual components are not available. We propose an evolutionary framework for deconvolving data from a single genome-wide experiment to infer the composition, abundance and evolutionary paths of the underlying cell subpopulations of a tumor. We have developed an algorithm (TrAp) for solving this mixture problem. In silico analyses show that TrAp correctly deconvolves mixed subpopulations when the number of subpopulations and the measurement errors are moderate. We demonstrate the applicability of the method using tumor karyotypes and somatic hypermutation data sets. We applied TrAp to Exome-Seq experiment of a renal cell carcinoma tumor sample and compared the mutational profile of the inferred subpopulations to the mutational profiles of single cells of the same tumor. Finally, we deconvolve sequencing data from eight acute myeloid leukemia patients and three distinct metastases of one melanoma patient to exhibit the evolutionary relationships of their subpopulations.