DOCSLIB.ORG

Downregulation of GNA14 in Hepatocellular Carcinoma Indicates an Unfavorable Prognosis

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Downregulation of GNA14 in Hepatocellular Carcinoma Indicates an Unfavorable Prognosis ONCOLOGY LETTERS 20: 165-172, 2020 Downregulation of GNA14 in hepatocellular carcinoma indicates an unfavorable prognosis TAO YU1*, SIYU LU2* and WENJING XIE2 Departments of 1Medical Oncology and 2Anesthesiology, Xuzhou Municipal Hospital Affiliated to Xuzhou Medical University, Xuzhou, Jiangsu 221000, P.R. China Received August 2, 2019; Accepted March 5, 2020 DOI: 10.3892/ol.2020.11538 Abstract. Guanine nucleotide-binding protein subunit α14 In conclusion, low GNA14 expression may be a novel biomarker (GNA14) knockdown was demonstrated to inhibit the prolifera- for diagnosis and prognosis prediction for patients with HCC. tion of endometrial carcinoma cells in a recent study; however, its role in hepatocellular carcinoma (HCC) is unknown. In Introduction the present study, the clinical significance of GNA14 in HCC was assessed using a dataset of patients with HCC from The Liver cancer was the second leading cause of cancer-asso- Cancer Genome Atlas database. The Integrative Molecular ciated mortality worldwide in 2015 (1). Patients with HCC Database of Hepatocellular Carcinoma and Oncomine data- have no noticeable symptoms, making an accurate diagnosis bases were also used to identify the expression levels of GNA14 challenging; therefore, effective and efficient treatment of in HCC tissues. The association between GNA14 expression HCC should be available at a much earlier stage, and novel levels and clinicopathological features was assessed using the biomarkers are required to improve earlier diagnosis of HCC Wilcoxon signed-rank test and logistic regression analysis. and guide clinical management (2,3). Kaplan-Meier curves and Cox regression analysis were applied HCC is associated with increased expression levels of to evaluate the independent risk factors for clinical outcomes. α-fetoprotein (AFP) (4). AFP is a serum glycoprotein that has The present study determined GNA14 DNA methylation levels been widely used as a conventional biomarker for HCC (5). and tumor‑infiltrating immune cells, as well as used Gene Set However, the expression levels of AFP remain normal in >30% Enrichment Analysis (GSEA) in HCC. GNA14 mRNA expres- of patients with HCC at the time of diagnosis. In addition, sion levels were lower in HCC compared with normal tissues. relatively low AFP expression levels have been identified in Downregulation of GNA14 in HCC was significantly associated approximately 30% of HCC (5). Although AFP is often used with tumor grade, clinical stage and T stage. Furthermore, low in combination with ultrasound for an accurate diagnosis of expression of GNA14 was an independent predictor for survival HCC, novel biomarkers may improve the diagnostic accuracy outcomes. GNA14 expression levels were partially correlated and detection rates (6,7). with the infiltration of B cells and macrophages. Additionally, Guanine nucleotide-binding protein subunit α (GNA) GSEA analysis revealed that the expression levels of GNA14 is a member of the guanine nucleotide-binding (G protein) were associated with multiple signaling pathways, such as family that serve as modulators or transducers in miscel- translation, DNA replication, and homologous recombination. laneous transmembrane signaling systems (8,9). Mutations in G protein subunits α14 (GNA14), αQ (GNAQ) and α11, are involved in ~50% of cherry hemangiomas and cherry-like hemangiomas, and pathological and molecular studies have demonstrated common functions of GNA14 mutations in Correspondence to: Dr Wenjing Xie, Department of vascular neoplasms (10). In addition, GNA14 silencing has Anesthesiology, Xuzhou Municipal Hospital Affiliated to been demonstrated to impair the proliferation of endometrial Xuzhou Medical University, 9 Zhongshan North Road, Xuzhou, carcinoma cells by enhancing apoptosis and inducing cell Jiangsu 221000, P.R. China cycle arrest (11). Additionally, somatic activating mutations in E-mail: [email protected] GNA14 induce the activation of the MAPK signaling pathway Abbreviations: HCC, hepatocellular carcinoma; TCGA, The and contribute to the occurrence and development of congen- Cancer Genome Atlas; GNA14, guanine nucleotide-binding protein ital and sporadic vascular tumors, providing novel insight into subunit α14; TIICs, tumor-infiltrating immune cells the underlying mechanisms of carcinogenesis (12). The present study investigated the prognostic value of *Contributed equally GNA14 expression levels in HCC according using data from The Cancer Genome Atlas (TCGA). Additionally, biological Key words: GNA14, HCC, prognostic marker, TCGA processes and signaling pathways associated with GNA14 that may be involved in the molecular pathogenesis of HCC were identified based on the Gene Set Enrichment Analysis (GSEA) 166 YU et al: GNA14 AND HEPATOCELLULAR CARCINOMA analysis. Overall, the present study aimed to explore the role Table I. The clinicopathological characteristics of 377 patients of GNA14 in HCC. with hepatocellular carcinoma. Materials and methods Characteristic n % Data sources. RNA‑sequencing (RNA‑seq) data (workflow Age at diagnosis, years (range) 61 (16-81) type, htseq-counts) and matching clinical data of 377 patients Sex were obtained from the Genomic Data Commons data Female 122 32.4 portal (https://portal.gdc.cancer.gov/) in June 2019, including Male 255 67.6 information from TCGA database and the Therapeutically Grade Applicable Research to Generate Effective Treatments G1 39 15.4 program. The clinicopathological characteristics included age, G2 124 49.0 sex, histological grade, clinical stage, T, N and M staging (13). G3 82 32.4 According to a previous study (14), the processing of data and G4 8 3.2 further analysis were conducted to explore the associations Clinical stage between GNA14 expression levels and clinicopathological I 125 51.9 characteristics in HCC. An unpaired t-test was performed to II 60 24.9 analyze the difference between tumor and normal samples. III 55 22.8 IV 1 0.4 Integrative Molecular Database of Hepatocellular Carcinoma (HCCDB) analysis. The HCCDB (http://lifeome. T stage net/database/hccdb/) (15) is an integrated molecular database T1 128 50.4 of HCC with 15 HCC gene expression datasets including T2 65 25.6 3,917 samples. The HCCDB includes 13 datasets from the T3 54 21.3 Gene Expression Omnibus database and 2 RNA-seq datasets T4 7 2.8 from TCGA liver hepatocellular carcinoma (LIHC) and the N stage International Cancer Genome Consortium (ICGC) databases N0 177 69.7 to explore the expression levels of GNA14 mRNA in HCC. N1 1 0.4 Nx 76 29.9 Oncomine database analysis. Oncomine is a cancer micro- M stage array database (oncomine.org/) containing 715 datasets and M0 186 72.9 86,733 cancer samples (16). In the present study, Oncomine was M1 1 0.4 used to further assess the expression levels of GNA14 in HCC and Mx 68 26.7 adjacent normal tissue. The parameters were set as fold-change ≥2 and P<0.05, and the top 10% of ranked genes were exhibited. DNA methylation level of GNA14. The DNA methylation levels Statistical analysis. Statistical analysis was performed using of GNA14 were analyzed using the Methylation in Human R software version 3.6.0 (http://www.R-project.org/) (20), Cancer database (MethHC) (methhc.mbc.nctu.edu.tw/) (17), R studio software version 1.2.5019 (21) and GraphPad a comprehensive database of DNA methylation and gene Prism version 8.0 software (GraphPad Software, Inc.) for expression in human cancer. Unpaired t-tests were performed data processing and analysis. All data were represented as to analyze the difference between tumor and normal samples. mean ± standard deviation (SD). According to the median value of GNA14 expression levels in HCC tissues, patients were Tumor Immune Estimation Resource (TIMER) database divided into low and high GNA14 expression groups. Survival analysis. A systematic assessment of the correlation between analysis was conducted by the Kaplan-Meier method. Wilcoxon different immune cells, such as B cells, CD4+ T cells, CD8+ signed-rank test and log regression were used to analyze the T cells, neutrophils, macrophages, and dendritic cells, and association of clinicopathological characteristics and GNA14 GNA14 expression levels across different types of cancer expression levels. The univariate and multivariate Cox propor- were performed using the TIMER database (https://cistrome. tional hazards model was performed to evaluate the prognostic shinyapps.io/timer/) (18). value of GNA14 expression. Receiver operating characteristic (ROC) curves were constructed using log-rank tests to evaluate GSEA. Gene set enrichment analysis (GSEA) was conducted the diagnostic value of GNA14 expression in HCC. P<0.05 was using c2.cp.kegg.v6.0.symbols.gmt as a reference gene set considered to indicate a statistically significant difference. (software.broadinstitute.org/gsea/) (19). A list of genes was obtained from GSEA to account for the survival differences Results in patients with differential expression levels of GNA14. Gene set permutations were analyzed 1,000 times. In addition, Patient characteristics. Clinical and RNA-seq data of the normalized enrichment score, normalized P-value and 377 patients with primary HCC, including 377 HCC and 50 false discovery rate (FDR) q value were applied to filter the adjacent normal tissues, were obtained from TCGA database correlative pathways. and are listed in Table I. Of the 377 patients, 122 (32.4%) ONCOLOGY LETTERS 20: 165-172, 2020 167 Figure 1. Differential expressions of GNA14 evaluated using the TIMER, HCCDB and Oncomine databases for HCC. (A)
Load more

Recommended publications
  • Multi-Functionality of Proteins Involved in GPCR and G Protein Signaling: Making Sense of Structure–Function Continuum with In
    Cellular and Molecular Life Sciences (2019) 76:4461–4492 https://doi.org/10.1007/s00018-019-03276-1 Cellular andMolecular Life Sciences REVIEW Multi‑functionality of proteins involved in GPCR and G protein signaling: making sense of structure–function continuum with intrinsic disorder‑based proteoforms Alexander V. Fonin1 · April L. Darling2 · Irina M. Kuznetsova1 · Konstantin K. Turoverov1,3 · Vladimir N. Uversky2,4 Received: 5 August 2019 / Revised: 5 August 2019 / Accepted: 12 August 2019 / Published online: 19 August 2019 © Springer Nature Switzerland AG 2019 Abstract GPCR–G protein signaling system recognizes a multitude of extracellular ligands and triggers a variety of intracellular signal- ing cascades in response. In humans, this system includes more than 800 various GPCRs and a large set of heterotrimeric G proteins. Complexity of this system goes far beyond a multitude of pair-wise ligand–GPCR and GPCR–G protein interactions. In fact, one GPCR can recognize more than one extracellular signal and interact with more than one G protein. Furthermore, one ligand can activate more than one GPCR, and multiple GPCRs can couple to the same G protein. This defnes an intricate multifunctionality of this important signaling system. Here, we show that the multifunctionality of GPCR–G protein system represents an illustrative example of the protein structure–function continuum, where structures of the involved proteins represent a complex mosaic of diferently folded regions (foldons, non-foldons, unfoldons, semi-foldons, and inducible foldons). The functionality of resulting highly dynamic conformational ensembles is fne-tuned by various post-translational modifcations and alternative splicing, and such ensembles can undergo dramatic changes at interaction with their specifc partners.
    [Show full text]
  • Gα15 in Early Onset of Pancreatic Ductal Adenocarcinoma Giulio Innamorati1,7*, Thomas M
    www.nature.com/scientificreports OPEN Gα15 in early onset of pancreatic ductal adenocarcinoma Giulio Innamorati1,7*, Thomas M. Wilkie2,7, Giorgio Malpeli1, Salvatore Paiella1, Silvia Grasso1, Borislav Rusev3, Biagio Eugenio Leone4, Maria Teresa Valenti5, Luca dalle Carbonare5, Samuele Cheri6, Alice Giacomazzi1, Marco Zanotto1, Vanessa Guardini1, Michela Deiana6, Donato Zipeto6, Michela Serena6, Marco Parenti4, Francesca Guzzi4, Rita Teresa Lawlor3, Giovanni Malerba6, Antonio Mori6, Giuseppe Malleo1, Luca Giacomello1, Roberto Salvia1,8 & Claudio Bassi1,8 The GNA15 gene is ectopically expressed in human pancreatic ductal adenocarcinoma cancer cells. The encoded Gα15 protein can promiscuously redirect GPCR signaling toward pathways with oncogenic potential. We sought to describe the distribution of GNA15 in adenocarcinoma from human pancreatic specimens and to analyze the mechanism driving abnormal expression and the consequences on signaling and clinical follow-up. We detected GNA15 expression in pre-neoplastic pancreatic lesions and throughout progression. The analysis of biological data sets, primary and xenografted human tumor samples, and clinical follow-up shows that elevated expression is associated with poor prognosis for GNA15, but not any other GNA gene. Demethylation of the 5′ GNA15 promoter region was associated with ectopic expression of Gα15 in pancreatic neoplastic cells, but not in adjacent dysplastic or non-transformed tissue. Down-modulation of Gα15 by shRNA or CRISPR/Cas9 afected oncogenic signaling, and reduced adenocarcimoma cell motility and invasiveness. We conclude that de novo expression of wild-type GNA15 characterizes transformed pancreatic cells. The methylation pattern of GNA15 changes in preneoplastic lesions coincident with the release a transcriptional blockade that allows ectopic expression to persist throughout PDAC progression.
    [Show full text]
  • Downregulation of Carnitine Acyl-Carnitine Translocase by Mirnas
    Page 1 of 288 Diabetes 1 Downregulation of Carnitine acyl-carnitine translocase by miRNAs 132 and 212 amplifies glucose-stimulated insulin secretion Mufaddal S. Soni1, Mary E. Rabaglia1, Sushant Bhatnagar1, Jin Shang2, Olga Ilkayeva3, Randall Mynatt4, Yun-Ping Zhou2, Eric E. Schadt6, Nancy A.Thornberry2, Deborah M. Muoio5, Mark P. Keller1 and Alan D. Attie1 From the 1Department of Biochemistry, University of Wisconsin, Madison, Wisconsin; 2Department of Metabolic Disorders-Diabetes, Merck Research Laboratories, Rahway, New Jersey; 3Sarah W. Stedman Nutrition and Metabolism Center, Duke Institute of Molecular Physiology, 5Departments of Medicine and Pharmacology and Cancer Biology, Durham, North Carolina. 4Pennington Biomedical Research Center, Louisiana State University system, Baton Rouge, Louisiana; 6Institute for Genomics and Multiscale Biology, Mount Sinai School of Medicine, New York, New York. Corresponding author Alan D. Attie, 543A Biochemistry Addition, 433 Babcock Drive, Department of Biochemistry, University of Wisconsin-Madison, Madison, Wisconsin, (608) 262-1372 (Ph), (608) 263-9608 (fax), [email protected]. Running Title: Fatty acyl-carnitines enhance insulin secretion Abstract word count: 163 Main text Word count: 3960 Number of tables: 0 Number of figures: 5 Diabetes Publish Ahead of Print, published online June 26, 2014 Diabetes Page 2 of 288 2 ABSTRACT We previously demonstrated that micro-RNAs 132 and 212 are differentially upregulated in response to obesity in two mouse strains that differ in their susceptibility to obesity-induced diabetes. Here we show the overexpression of micro-RNAs 132 and 212 enhances insulin secretion (IS) in response to glucose and other secretagogues including non-fuel stimuli. We determined that carnitine acyl-carnitine translocase (CACT, Slc25a20) is a direct target of these miRNAs.
    [Show full text]
  • Table S1. 103 Ferroptosis-Related Genes Retrieved from the Genecards
    Table S1. 103 ferroptosis-related genes retrieved from the GeneCards. Gene Symbol Description Category GPX4 Glutathione Peroxidase 4 Protein Coding AIFM2 Apoptosis Inducing Factor Mitochondria Associated 2 Protein Coding TP53 Tumor Protein P53 Protein Coding ACSL4 Acyl-CoA Synthetase Long Chain Family Member 4 Protein Coding SLC7A11 Solute Carrier Family 7 Member 11 Protein Coding VDAC2 Voltage Dependent Anion Channel 2 Protein Coding VDAC3 Voltage Dependent Anion Channel 3 Protein Coding ATG5 Autophagy Related 5 Protein Coding ATG7 Autophagy Related 7 Protein Coding NCOA4 Nuclear Receptor Coactivator 4 Protein Coding HMOX1 Heme Oxygenase 1 Protein Coding SLC3A2 Solute Carrier Family 3 Member 2 Protein Coding ALOX15 Arachidonate 15-Lipoxygenase Protein Coding BECN1 Beclin 1 Protein Coding PRKAA1 Protein Kinase AMP-Activated Catalytic Subunit Alpha 1 Protein Coding SAT1 Spermidine/Spermine N1-Acetyltransferase 1 Protein Coding NF2 Neurofibromin 2 Protein Coding YAP1 Yes1 Associated Transcriptional Regulator Protein Coding FTH1 Ferritin Heavy Chain 1 Protein Coding TF Transferrin Protein Coding TFRC Transferrin Receptor Protein Coding FTL Ferritin Light Chain Protein Coding CYBB Cytochrome B-245 Beta Chain Protein Coding GSS Glutathione Synthetase Protein Coding CP Ceruloplasmin Protein Coding PRNP Prion Protein Protein Coding SLC11A2 Solute Carrier Family 11 Member 2 Protein Coding SLC40A1 Solute Carrier Family 40 Member 1 Protein Coding STEAP3 STEAP3 Metalloreductase Protein Coding ACSL1 Acyl-CoA Synthetase Long Chain Family Member 1 Protein
    [Show full text]
  • High Frequency of GNA14, GNAQ, and GNA11 Mutations In
    Modern Pathology (2019) 32:1657–1665 https://doi.org/10.1038/s41379-019-0284-y ARTICLE High frequency of GNA14, GNAQ, and GNA11 mutations in cherry hemangioma: a histopathological and molecular study of 85 cases indicating GNA14 as the most commonly mutated gene in vascular neoplasms 1,2 1,2 1,2 2 2 2 Jau-Yu Liau ● Jen-Chieh Lee ● Jia-Huei Tsai ● Chih-Chi Chen ● Yung-Chuan Chung ● Ying-Hao Wang Received: 18 February 2019 / Revised: 1 April 2019 / Accepted: 1 April 2019 / Published online: 12 June 2019 © United States & Canadian Academy of Pathology 2019 Abstract Cherry hemangioma is the most common hemangioma in adult life. Neoplastic and non-neoplastic theories had both been proposed for its pathogenesis, but its nature is still poorly understood. We noted a significant subset of anastomosing hemangiomas and congenital hemangiomas harbored a population of small capillaries surrounded by a perivascular hyaline layer, reminiscent of the vessels seen in cherry hemangioma. Both anastomosing hemangioma and congenital hemangioma harbor recurrent mutations in exon 5 of GNAQ and its paralogues. In this study, we analyzed 68 cherry hemangiomas and 17 1234567890();,: 1234567890();,: cherry hemangioma-like hemangiomas exhibiting additional non-classical features including markedly dilated, cavernous vessels, and/or a deep component extending to the deep dermis. By Sanger sequencing, GNAQ, GNA11, and GNA14 exon 5 mutations were identified in 12, 4, and 32 cherry hemangiomas, respectively, and 5, 3, and 3 cherry hemangioma-like hemangiomas, respectively. MassARRAY analysis detected mutations (including exon 2 GNAQG48V mutations) in additional 8 cherry hemangiomas and 3 cherry hemangioma-like hemangiomas.
    [Show full text]
  • Whole Genome Landscapes of Uveal Melanoma Show an Ultraviolet Radiation Signature in Iris Tumours
    ARTICLE https://doi.org/10.1038/s41467-020-16276-8 OPEN Whole genome landscapes of uveal melanoma show an ultraviolet radiation signature in iris tumours Peter A. Johansson1,20, Kelly Brooks1,20, Felicity Newell1, Jane M. Palmer 1, James S. Wilmott2,3, Antonia L. Pritchard1,4, Natasa Broit1,5, Scott Wood1, Matteo S. Carlino2, Conrad Leonard1, Lambros T. Koufariotis1, Vaishnavi Nathan 1,5, Aaron B. Beasley 6, Madeleine Howlie1, Rebecca Dawson1, Helen Rizos 2,7, Chris W. Schmidt 1,8, Georgina V. Long2,9, Hayley Hamilton1,10, Jens F. Kiilgaard 11, Timothy Isaacs12,13,14, Elin S. Gray 6,13, Olivia J. Rolfe10, John J. Park7, Andrew Stark10, Graham J. Mann2,15,16, 1234567890():,; Richard A. Scolyer 2,3,17, John V. Pearson1, Nicolas van Baren18, Nicola Waddell 1, Karin W. Wadt 19, ✉ Lindsay A. McGrath 10, Sunil K. Warrier10, William Glasson10 & Nicholas K. Hayward 1 Uveal melanoma (UM) is the most common intraocular tumour in adults and despite surgical or radiation treatment of primary tumours, ~50% of patients progress to metastatic disease. Therapeutic options for metastatic UM are limited, with clinical trials having little impact. Here we perform whole-genome sequencing (WGS) of 103 UM from all sites of the uveal tract (choroid, ciliary body, iris). While most UM have low tumour mutation burden (TMB), two subsets with high TMB are seen; one driven by germline MBD4 mutation, and another by ultraviolet radiation (UVR) exposure, which is restricted to iris UM. All but one tumour have a known UM driver gene mutation (GNAQ, GNA11, BAP1, PLCB4, CYSLTR2, SF3B1, EIF1AX).
    [Show full text]
  • Rare TERT Promoter Mutations Present in Benign and Malignant Cutaneous Vascular Tumors
    Article Rare TERT Promoter Mutations Present in Benign and Malignant Cutaneous Vascular Tumors Philipp Jansen 1,* , Georg Christian Lodde 1, Anne Zaremba 1, Carl Maximilian Thielmann 1 , Johanna Matull 1, Hansgeorg Müller 2, Inga Möller 1, Antje Sucker 1, Stefan Esser 1, Jörg Schaller 3, Dirk Schadendorf 1, Thomas Mentzel 4, Eva Hadaschik 1 and Klaus Georg Griewank 1,5,* 1 Department of Dermatology, University Hospital Essen, University Duisburg-Essen and German Cancer Consortium (DKTK), 45147 Essen, Germany; [email protected] (G.C.L.); [email protected] (A.Z.); [email protected] (C.M.T.); [email protected] (J.M.); [email protected] (I.M.); [email protected] (A.S.); [email protected] (S.E.); [email protected] (D.S.); [email protected] (E.H.) 2 Dermatohistologie am Stachus, 80331 München, Germany; [email protected] 3 Dermatopathologie Duisburg, 47166 Duisburg, Germany; [email protected] 4 MVZ Dermatopathologie Friedrichshafen, Bodensee, 88048 Friedrichshafen, Germany; [email protected] 5 Dermatopathologie bei Mainz, 55268 Nieder-Olm, Germany * Correspondence: [email protected] (P.J.); [email protected] (K.G.G.); Tel.: +49-201-723-4700 (P.J.); +49-201-723-4700 (K.G.G.) Abstract: Mutations in the promoter of the telomerase reverse transcriptase (TERT) gene have been described as the most common hot-spot mutations in different solid tumors. High frequencies of TERT Citation: Jansen, P.; Lodde, G.C.; promoter mutations have been reported to occur in tumors arising in tissues with low rates of self- Zaremba, A.; Thielmann, C.M.; renewal.
    [Show full text]
  • Selectivity Determinants of GPCR–G-Protein Binding Tilman Flock1,2, Alexander S
    ARTICLE doi:10.1038/nature22070 Selectivity determinants of GPCR–G-protein binding Tilman Flock1,2, Alexander S. Hauser3, Nadia Lund3, David E. Gloriam3, Santhanam Balaji1 & M. Madan Babu1 The selective coupling of G-protein-coupled receptors (GPCRs) to specific G proteins is critical to trigger the appropriate physiological response. However, the determinants of selective binding have remained elusive. Here we reveal the existence of a selectivity barcode (that is, patterns of amino acids) on each of the 16 human G proteins that is recognized by distinct regions on the approximately 800 human receptors. Although universally conserved positions in the barcode allow the receptors to bind and activate G proteins in a similar manner, different receptors recognize the unique positions of the G-protein barcode through distinct residues, like multiple keys (receptors) opening the same lock (G protein) using non-identical cuts. Considering the evolutionary history of GPCRs allows the identification of these selectivity- determining residues. These findings lay the foundation for understanding the molecular basis of coupling selectivity within individual receptors and G proteins. Membrane protein receptors trigger the appropriate cellular response GPCR and Gα protein repertoires to extracellular stimuli by selective interaction with cytosolic adaptor Understanding how GPCRs and Gα proteins evolve could pro- proteins. In humans, GPCRs form the largest family of receptors, with vide insights into the constraints underlying selective coupling. over 800 members1–3. Although GPCRs bind a staggering number of The genomes of unicellular sister groups of metazoans (diverged natural ligands (~1,000), they primarily couple to only four major Gα ~900 million years ago) encode a small number of genes for the GPCR– families encoded by 16 human genes3,4.
    [Show full text]
  • Phosphodiesterase Inhibitors Revert Axonal Dystrophy in Friedreich's
    Phosphodiesterase inhibitors revert axonal dystrophy in Friedreich’s ataxia mouse model. Belén Mollá*,†, Diana C. Muñoz-Lasso‡,§, Pablo Calap*,‡,§,¶, Angel Fernandez-Vilata||, María de la Iglesia-Vaya||,#,8, Federico V. Pallardó*,‡,§,**, Maria Dolores Moltó¶,**,††, Francesc Palau*,‡‡,§§,¶¶, Pilar González-Cabo*,‡,§,††,¶¶,|| || * CIBER de Enfermedades Raras (CIBERER), Valencia, Spain † Instituto de Biomedicina de Valencia (IBV), CSIC, Valencia 46010, Spain ‡ Department of Physiology, Faculty of Medicine and Dentistry. University of Valencia, Valencia 46010, Spain § Associated Unit for rare diseases INCLIVA-CIPF ¶ Department of Genetics, University of Valencia, Campus of Burjassot, 46100 Valencia, Spain. || Brain Connectivity Laboratory. Joint unit FISABIO & Prince Felipe Research Centre (CIPF), Valencia 46012, Spain # Regional Ministry of Health in Valencia, Hospital Sagunto (CEIB-CSUSP), Valencia, Spain ** CIBER de Salud Mental (CIBERSAM), Valencia, Spain. †† Biomedical Research Institute INCLIVA, 46010 Valencia, Spain ‡‡ Institut de Recerca Sant Joan de Déu and Department of Genetic & Molecular Medicine and IPER, Hospital Sant Joan de Déu, Barcelona 08950, Spain §§ Department of Pediatrics, University of Barcelona School of Medicine, Barcelona, Spain ¶¶ Equally contributed || || corresponding author: Pilar González Cabo; [email protected] Facultad de Medicina y Odontología Avda. Blasco Ibañez, 1515 46010 Valencia, Spain. Tel. 0034 963395036 ABSTRACT: Friedreich’s ataxia (FRDA) is a neurodegenerative disorder caused by an unstable GAA repeat
    [Show full text]
  • (A) Information on Patients Whose Tumors Were Used for Establishing PDX Models
    A B Figure S1 PDX models used in this study. (A) Information on patients whose tumors were used for establishing PDX models. (B) H&E images of PDX tumors with large field-of-view. Scale bar, 100 µm. Figure S2. Information for chemotherapy treatments on PXO and PDX models (A) Information of combination treatments on PXOs (B) Doses and schedules for treatments on PDX mouse models. (C) Dose- dependent responses to single regent treatments in PXOs. Figure S3. Comparing responses classification in vitro and in vivo (A) Treatments on Panc286 PXO and PDX models. (B) Goodness of fit for Jenkins break classification. Figure S4: Mass spectrometric analysis of N-glycans in PDX and PDO of Panc030. The structures and compositions of glycans were illustrated on top of peaks of corresponding m/z values. Figure S5 Immunoblot of Vglut2 proteins in EVs from patient plasma. EVs from 15 µl of plasma were input per lane. A2M CP HIST1H3I NUTF2 RSF1 AAK1 CPD HIST1H3J NXN RSU1 AARS CPE HIST1H4A OAF RTCB ABAT CPNE1 HIST1H4B OGA RTRAF ABCA7 CPOX HIST1H4C OGDH RUFY3 ABHD10 CPS1 HIST1H4D OGN RUVBL1 ABHD14B CPSF2 HIST1H4E OLA1 RUVBL2 ABI1 CPSF6 HIST1H4F OLFML3 RYR3 ACAA1 CPXM1 HIST1H4H OPTN S100A1 ACAA2 CRABP2 HIST1H4I OSGEP S100A10 ACACA CRMP1 HIST1H4J OSTF1 S100A11 ACAT1 CRTAP HIST1H4K OTUB1 S100A12 ACAT2 CRYM HIST1H4L OXCT1 S100A14 ACLY CRYZ HIST2H2AC P3H1 S100A16 ACO1 CS HIST2H2BE P4HB S100A2 ACO2 CSAD HIST2H3A PA2G4 S100A4 ACOT7 CSE1L HIST2H3C PABPC1 S100A6 ACSF2 CSH1 HIST2H3D PACSIN2 S100A7 ACTB CSNK2A1 HIST2H3PS2 PAFAH1B1 S100A7A ACTC1 CSNK2B HIST2H4A PAFAH1B2
    [Show full text]
  • GPCR Signaling As a Paradigm
    Oncogene (2019) 38:6491–6506 https://doi.org/10.1038/s41388-019-0895-2 ARTICLE Rare, functional, somatic variants in gene families linked to cancer genes: GPCR signaling as a paradigm 1,2 3,4 3,4 5 1,2 Francesco Raimondi ● Asuka Inoue ● Francois M. N. Kadji ● Ni Shuai ● Juan-Carlos Gonzalez ● 1,2 6 6 5 3,4 7 Gurdeep Singh ● Alicia Alonso de la Vega ● Rocio Sotillo ● Bernd Fischer ● Junken Aoki ● J. Silvio Gutkind ● Robert B. Russell 1,2 Received: 24 September 2018 / Revised: 4 March 2019 / Accepted: 8 April 2019 / Published online: 23 July 2019 © The Author(s) 2019. This article is published with open access Abstract Oncodriver genes are usually identified when mutations recur in multiple tumours. Different drivers often converge in the activation or repression of key cancer-relevant pathways. However, as many pathways contain multiple members of the same gene family, individual mutations might be overlooked, as each family member would necessarily have a lower mutation frequency and thus not identified as significant in any one-gene-at-a-time analysis. Here, we looked for mutated, functional sequence positions in gene families that were mutually exclusive (in patients) with another gene in the same pathway, which fi 1234567890();,: 1234567890();,: identi ed both known and new candidate oncodrivers. For instance, many inactivating mutations in multiple G-protein (particularly Gi/o) coupled receptors, are mutually exclusive with Gαs oncogenic activating mutations, both of which ultimately enhance cAMP signalling. By integrating transcriptomics and interaction data, we show that the Gs pathway is upregulated in multiple cancer types, even those lacking known GNAS activating mutations.
    [Show full text]
  • The Emerging Mutational Landscape of G Proteins and G-Protein-Coupled
    ANALYSIS The emerging mutational landscape of G proteins and G‑protein‑coupled receptors in cancer Morgan O’Hayre1, José Vázquez-Prado2, Irina Kufareva3, Eric W. Stawiski4,5, Tracy M. Handel3, Somasekar Seshagiri4 and J. Silvio Gutkind1 Abstract | Aberrant expression and activity of G proteins and G-protein-coupled receptors (GPCRs) are frequently associated with tumorigenesis. Deep sequencing studies show that 4.2% of tumours carry activating mutations in GNAS (encoding Gαs), and that oncogenic activating mutations in genes encoding Gαq family members (GNAQ or GNA11) are present in ~66% and ~6% of melanomas arising in the eye and skin, respectively. Furthermore, nearly 20% of human tumours harbour mutations in GPCRs. Many human cancer-associated viruses also express constitutively active viral GPCRs. These studies indicate that G proteins, GPCRs and their linked signalling circuitry represent novel therapeutic targets for cancer prevention and treatment. The G-protein-coupled receptor (GPCR) family of proteins G protein and GPCR signalling comprises approximately 4% of the encoded human genes: The widely accepted model for GPCR activation involves 1Oral and Pharyngeal Cancer Branch, Dental and with over 800 members, it is the largest family of cell- the binding of an agonist ligand at the extracellular side Craniofacial Research, surface receptors involved in signal transduction. These of the receptor, which induces a conformational change in National Institutes of Health, proteins are characterized by a seven-transmembrane the receptor and alters the position of its transmembrane Bethesda, Maryland 20892, domain structure with an extracellular amino terminus helices and intracellular loops. In this active conforma- USA. and an intracellular carboxyl terminus.
    [Show full text]