Journal: Endocrinology

Article Title: GLP-1 Receptor Expression Within the Human Heart

doi: 10.1210/en.2018-00004

Figure Lengend Snippet: Antibodies Used

Article Snippet: Immunoprecipitations were performed using 1 mg/mL of cell or tissue protein extract and 2 μg/mL of rabbit polyclonal anti-human GLP-1R antibody [Novus 19400002; Research Resource Identifier (RRID) AB_10004637 ; Bio-Techne, Oakville, ON, Canada] overnight at 4°C.

Techniques: Sequencing

Journal: Endocrinology

Article Title: GLP-1 Receptor Expression Within the Human Heart

doi: 10.1210/en.2018-00004

Figure Lengend Snippet: GLP1R mRNA transcript levels in the human heart are comparable to those in human pancreas and islets. (A) GLP1R mRNA levels were measured via qPCR analysis in multiple human tissues and in transfected BHK cells that express low levels of the human GLP-1R. For data represented without standard error bars, each single RNA sample was analyzed in duplicate; for isolates depicted with error bars, peripheral blood lymphocyte samples were analyzed in duplicate from two different sources, and at least three different samples were analyzed in duplicate by qPCR for RNAs from islet, bone marrow, left atria (LA), right atria (RA), left ventricle (LV), and right ventricle (RV). (B) qPCR analysis of GLP1R and tissue- or cell-type–specific gene expression in the indicated samples as confirmation of RNA/cDNA integrity. For (A) and (B), data are expressed as cycle threshold (Ct) values because none of the housekeeping genes examined (ACTB, GPI, PSMB4, CHMP2A, and EMC7) exhibited consistent expression levels in all tissues examined. Values are mean ± standard error (where appropriate); n = 1 to 3 samples per tissue. LA samples are from patients P01371, P01430, and P01504. RA samples are from patients P01262, P01371, and P01377. LV samples are from patients P01262, P01430, and P01371. RV samples are from patients P01262, P01371, and P01504 (see Supplemental Table 1 and Figure 4). Islet samples are from donors R177, R199, and R200 (see Supplemental Table 3). CA EC, coronary artery endothelial cells; CA SMC, coronary artery smooth muscle cells; PBL, peripheral blood lymphocytes; Card FB, cardiac fibroblasts.

Article Snippet: Immunoprecipitations were performed using 1 mg/mL of cell or tissue protein extract and 2 μg/mL of rabbit polyclonal anti-human GLP-1R antibody [Novus 19400002; Research Resource Identifier (RRID) AB_10004637 ; Bio-Techne, Oakville, ON, Canada] overnight at 4°C.

Techniques: Transfection, Expressing

Journal: Endocrinology

Article Title: GLP-1 Receptor Expression Within the Human Heart

doi: 10.1210/en.2018-00004

Figure Lengend Snippet: (A) Western blot analysis of whole cell or human islet tissue extracts using GLP-1R antibodies against the human GLP-1R, Mab 3F52, or polyclonal Novus. Molecular mass standards (kDa) are indicated in the center. Blots on the left contain whole cell extracts from BHK pcDNA3 (lane 1), BHK clone #12A (lane 2), BHK clone #13 (lane 3), BHK clone #27 (lane 4), and CFPAC-1 cells (lane 5). Blots on the right contain whole cell extracts from BHK clone #12A (lane 1) and whole tissue extracts from human islets #167 (lane 2), #177 (lane 3), #186 (lane 4), and 199 (lane 5). The blot on the far right was immunoblotted with Akt and Erk1/2 antibodies as loading controls. (B) Western blot analysis of whole cell or human cardiac tissue extracts analyzed using the indicated GLP-1R antibody. Molecular mass standards (kDa) are indicated in the center. Immunoblotting with Akt and Erk1/2 antibodies (bottom panels) was used as loading controls. In (A) and (B), the brackets indicate predicted migration positions of immunoreactive GLP-1R protein.

Article Snippet: Immunoprecipitations were performed using 1 mg/mL of cell or tissue protein extract and 2 μg/mL of rabbit polyclonal anti-human GLP-1R antibody [Novus 19400002; Research Resource Identifier (RRID) AB_10004637 ; Bio-Techne, Oakville, ON, Canada] overnight at 4°C.

Techniques: Western Blot, Migration

Journal: Endocrinology

Article Title: GLP-1 Receptor Expression Within the Human Heart

doi: 10.1210/en.2018-00004

Figure Lengend Snippet: (A) Whole cell/tissue extracts after immunoprecipitation (IP) and Western blotting with the indicated GLP-1R antibodies. Lanes 1 and 2 are whole cell extracts, and lanes 3 through 8 correspond to immunoprecipitated samples. Lane 1, BHK pcDNA3; lane 2, BHK clone #12A; lane 3, BHK clone #12A; lane 4, BHK clone #13; lane 5, human islet #167; lane 6, human islet #177; lane 7, human islet #186; and lane 8, human islet #199. Molecular mass standards (kDa) are indicated on the left. (B) Whole tissue extracts from human heart chamber samples after IP and Western blotting with the indicated GLP-1R antibodies. Molecular mass standards (kDa) are indicated on the far left and right of the blots. In (A) and (B), the brackets indicate predicted migration positions of immunoreactive GLP-1R protein.

Article Snippet: Immunoprecipitations were performed using 1 mg/mL of cell or tissue protein extract and 2 μg/mL of rabbit polyclonal anti-human GLP-1R antibody [Novus 19400002; Research Resource Identifier (RRID) AB_10004637 ; Bio-Techne, Oakville, ON, Canada] overnight at 4°C.

Techniques: Immunoprecipitation, Western Blot, Migration

Journal: Endocrinology

Article Title: GLP-1 Receptor Expression Within the Human Heart

doi: 10.1210/en.2018-00004

Figure Lengend Snippet: GLP-1R immunohistochemistry with Mab 3F52 does not detect GLP-1R–immunoreactive cells in human ventricular tissue. Immunostaining of hyperplastic human Brunner glands with isotype control antibody (A) and GLP-1R Mab 3F52 (B). The Novus 19400002 antibody did not reliably detect GLP-1R–immunopositive cells in sections containing human Brunner glands (data not shown). Immunostaining of human pancreas with isotype control antibody (C) and GLP-1R Mab 3F52 (D). (E–P) GLP-1R Mab 3F52 immunostaining of human cardiac tissues from individual subjects [(E) 193856; (F) 61704; (G) 70150; (H) 70847; (I) 81858; (J) 164011; (K) 116603; (L) 166469; (M) 179268; (N) 171263; (O) 182651; (P), 52411; see Supplemental Table 2].

Article Snippet: Immunoprecipitations were performed using 1 mg/mL of cell or tissue protein extract and 2 μg/mL of rabbit polyclonal anti-human GLP-1R antibody [Novus 19400002; Research Resource Identifier (RRID) AB_10004637 ; Bio-Techne, Oakville, ON, Canada] overnight at 4°C.

Techniques: Immunohistochemistry, Immunostaining

Journal: PLoS Computational Biology

Article Title: A systematic atlas of chaperome deregulation topologies across the human cancer landscape

doi: 10.1371/journal.pcbi.1005890

Figure Lengend Snippet: A. The human chaperome is a central PN functional arm in charge of maintaining the cellular folding environment. It comprises 332 chaperones and co-chaperones organized in 10 functional families . B. Pipeline involving (1) Gene Set Analysis (GSA), (2) Meta-PCA, a novel two-step principal component analysis (PCA)—based dimension reduction approach yielding M-scores for quantitative analysis of chaperome functional family expression changes across a compendium of TCGA solid cancer biopsy RNA-seq expression data, and (3) Polar Plots visualising contextual quantitative chaperome alterations. C. We connect 332 human chaperome genes (nodes) in a high-confidence literature-curated physical protein-protein interactome network (edges) and collapse nodes within functional families and edges between families into meta-nodes and meta-edges, respectively. The resulting optimized meta-networks serve as base-grid layout to enable interactome-guided chaperome landscape modeling. D. We use the meta-interactome-guided base grid layout (X-Y dimensions) and Meta-PCA derived M-scores, indicating cancer expression change (Z dimension), to chart 3-dimensional quantitative topographic chaperome maps. Heatmaps, polar plots, meta-networks and 3D topographic map visualisations are accessible through the Proteostasis Profiler (Pro 2 ) web-tool.

Article Snippet: Data not included in the manuscript or supporting information files is accessible as follows: The results published here are in part based upon data generated by the TCGA Research Network ( http://cancergenome.nih.gov ), available through the Broad Institute TCGA GDAC Firehose ( https://gdac.broadinstitute.org/ ).

Techniques: Functional Assay, Expressing, RNA Sequencing, Derivative Assay

Journal: PLoS Computational Biology

Article Title: A systematic atlas of chaperome deregulation topologies across the human cancer landscape

doi: 10.1371/journal.pcbi.1005890

Figure Lengend Snippet: Chaperome as compared to permutations of non-chaperome genes ( A ) and chaperome functional family (Level 2) ( B ) gene expression states in human cancer RNA-seq datasets from The Cancer Genome Atlas (TCGA) explored by Gene Set Analysis (GSA). Heatmaps indicate significance of up or down-regulation of cancer versus healthy gene expression as ∆GSA values in the interval [-1, +1], where ‘+1’ indicates significant upregulation (p value = 0), while ‘-1’ indicates significant downregulation (p value = 0). Chaperome functional families (B) are clustered by Euclidean distance (dendrograms). Bar graphs in A and B indicate functional family GSA group mean changes. Order of TCGA cancer groups (rows) in A is according to Euclidian distance of chaperome differential expression clustering (dendrogram) in B. Turquoise box highlights the human chaperome broken down into functional families in B. Yellow borders indicate marked clusters of chaperome functional family expression and separation of clusters I and II as separated by Euclidean distance clustering of TCGA cancer groups. TCGA cancer group acronyms: THYM (thymoma), ESCA (esophageal carcinoma), BRCA (breast invasive carcinoma), LUAD (lung adenocarcinoma), LUSC (lung squamous cell carcinoma), KICH (kidney chromophobe), STAD (stomach adenocarcinoma), CHOL (cholangiocarcinoma), LIHC (liver hepatocellular carcinoma), PRAD (prostate adenocarcinoma), HNSC (head and neck squamous cell carcinoma), KIRP (kidney renal papillary cell carcinoma), SARC (sarcoma), UCEC (uterine corpus endometrial carcinoma), BLCA (bladder urothelial carcinoma), PAAD (pancreatic adenocarcinoma), CESC (cervical squamous cell carcinoma and endocervical adenocarcinoma), GBM (glioblastoma multiforme), KIRC (kidney renal clear cell carcinoma), SKCM (skin cutaneous melanoma), PCPG (pheochromocytoma and paraganglioma), THCA (thyroid carcinoma).

Article Snippet: Data not included in the manuscript or supporting information files is accessible as follows: The results published here are in part based upon data generated by the TCGA Research Network ( http://cancergenome.nih.gov ), available through the Broad Institute TCGA GDAC Firehose ( https://gdac.broadinstitute.org/ ).

Techniques: Functional Assay, Gene Expression, RNA Sequencing, Quantitative Proteomics, Expressing

Journal: PLoS Computational Biology

Article Title: A systematic atlas of chaperome deregulation topologies across the human cancer landscape

doi: 10.1371/journal.pcbi.1005890

Figure Lengend Snippet: A. Heatmap indicates overall gene expression changes (∆GSA) of the human proteasome (43 genes, HGNC Family ID 690) throughout 22 TCGA solid cancers. Heatmap ∆GSA values are in the interval [-1, +1], where ‘+1’ indicates significant upregulation (p value = 0), while ‘-1’ indicates significant downregulation (p value = 0) as in . B. Heatmap highlights HSP60 gene level differential expression of TRiC/CCT complex subunits throughout 22 TCGA solid cancers. Heatmap indicates significance of up- or downregulation of gene expression ( t test) in cancer compared to matching healthy tissue (1—signed p value) in the interval [-1, +1], where ‘+1’ indicates significant upregulation (p value = 0), while ‘-1’ indicates significant downregulation (p value = 0). Blue highlights indicate Group 2 cancers (KICH, KIRC, KIRP, PCPG, and THCA).

Article Snippet: Data not included in the manuscript or supporting information files is accessible as follows: The results published here are in part based upon data generated by the TCGA Research Network ( http://cancergenome.nih.gov ), available through the Broad Institute TCGA GDAC Firehose ( https://gdac.broadinstitute.org/ ).

Techniques: Gene Expression, Quantitative Proteomics