Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

At a glance: The STEP trials

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.
ADVANCED SEARCH
Log in
Top
BMC Cancer
Published in: BMC Cancer 1/2012

Open Access 01-12-2012 | Research article

The application of nonsense-mediated mRNA decay inhibition to the identification of breast cancer susceptibility genes

Authors: Julie K Johnson, Nic Waddell, Georgia Chenevix-Trench, kConFab Investigators

Published in: BMC Cancer | Issue 1/2012

Login to get access

Abstract

Background

Identification of novel, highly penetrant, breast cancer susceptibility genes will require the application of additional strategies beyond that of traditional linkage and candidate gene approaches. Approximately one-third of inherited genetic diseases, including breast cancer susceptibility, are caused by frameshift or nonsense mutations that truncate the protein product [1]. Transcripts harbouring premature termination codons are selectively and rapidly degraded by the nonsense-mediated mRNA decay (NMD) pathway. Blocking the NMD pathway in any given cell will stabilise these mutant transcripts, which can then be detected using gene expression microarrays. This technique, known as gene identification by nonsense-mediated mRNA decay inhibition (GINI), has proved successful in identifying sporadic nonsense mutations involved in many different cancer types. However, the approach has not yet been applied to identify germline mutations involved in breast cancer. We therefore attempted to use GINI on lymphoblastoid cell lines (LCLs) from multiple-case, non- BRCA1/2 breast cancer families in order to identify additional high-risk breast cancer susceptibility genes.

Methods

We applied GINI to a total of 24 LCLs, established from breast-cancer affected and unaffected women from three multiple-case non-BRCA1/2 breast cancer families. We then used Illumina gene expression microarrays to identify transcripts stabilised by the NMD inhibition.

Results

The expression profiling identified a total of eight candidate genes from these three families. One gene, PPARGC1A, was a candidate in two separate families. We performed semi-quantitative real-time reverse transcriptase PCR of all candidate genes but only PPARGC1A showed successful validation by being stabilised in individuals with breast cancer but not in many unaffected members of the same family. Sanger sequencing of all coding and splice site regions of PPARGC1A did not reveal any protein truncating mutations. Haplotype analysis using short tandem repeat microsatellite markers did not indicate the presence of a haplotype around PPARGC1A which segregated with disease in the family.

Conclusions

The application of the GINI method to LCLs to identify transcripts harbouring germline truncating mutations is challenging due to a number of factors related to cell type, microarray sensitivity and variations in NMD efficiency.
Appendix
Available only for authorised users
Literature
1.
Frischmeyer PA, Dietz HC: Nonsense-mediated mRNA decay in health and disease. Human Molecular Genetics. 1999, 8: 1893-1900. 10.1093/hmg/8.10.1893.CrossRefPubMed
2.
3.
Ponder BA, Antoniou A, Dunning A, Easton DF, Pharoah PD: Polygenic inherited predisposition to breast cancer. Cold Spring Harb Symp Quant Biol. 2005, 70: 35-41. 10.1101/sqb.2005.70.029.CrossRefPubMed
4.
5.
Antoniou A, Pharoah PD, Narod S, Risch HA, Eyfjord JE, Hopper JL, Loman N, Olsson H, Johannsson O, Borg A, et al: Average risks of breast and ovarian cancer associated with BRCA1 or BRCA2 mutations detected in case Series unselected for family history: a combined analysis of 22 studies. Am J Hum Genet. 2003, 72: 1117-1130. 10.1086/375033.CrossRefPubMedPubMedCentral
6.
Serova OM, Mazoyer S, Puget N, Dubois V, Tonin P, Shugart YY, Goldgar D, Narod SA, Lynch HT, Lenoir GM: Mutations in BRCA1 and BRCA2 in breast cancer families: are there more breast cancer-susceptibility genes?. Am J Hum Genet. 1997, 60: 486-495.PubMedPubMedCentral
7.
Schubert EL, Lee MK, Mefford HC, Argonza RH, Morrow JE, Hull J, Dann JL, King MC: BRCA2 in American families with four or more cases of breast or ovarian cancer: recurrent and novel mutations, variableexpression, penetrance, and the possibility of families whose cancer is not attributable to BRCA1 or BRCA2. Am J Hum Genet. 1997, 60: 1031-1040.PubMedPubMedCentral
8.
Peto J, Collins N, Barfoot R, Seal S, Warren W, Rahman N, Easton DF, Evans C, Deacon J, Stratton MR: Prevalence of BRCA1 and BRCA2 gene mutations in patients with early-onset breast cancer. J Natl Cancer Inst. 1999, 91: 943-949. 10.1093/jnci/91.11.943.CrossRefPubMed
9.
Ford D, Easton DF, Stratton M, Narod S, Goldgar D, Devilee P, Bishop DT, Weber B, Lenoir G, Chang-Claude J, et al: Genetic heterogeneity and penetrance analysis of the BRCA1 and BRCA2 genes in breast cancer families. The Breast Cancer Linkage Consortium. American Journal of Human Genetics. 1998, 62: 676-689. 10.1086/301749.CrossRefPubMedPubMedCentral
10.
Claus EB, Schildkraut J, Iversen ES, Berry D, Parmigiani G: Effect of BRCA1 and BRCA2 on the association between breast cancer risk and family history. J Natl Cancer Inst. 1998, 90: 1824-1829. 10.1093/jnci/90.23.1824.CrossRefPubMed
11.
Peto J, Mack TM: High constant incidence in twins and other relatives of women with breast cancer. Nat Genet. 2000, 26: 411-414. 10.1038/82533.CrossRefPubMed
12.
Lichtenstein P, Holm NV, Verkasalo PK, Iliadou A, Kaprio J, Koskenvuo M, Pukkala E, Skytthe A, Hemminki K: Environmental and heritable factors in the causation of cancer–analyses of cohorts of twins from Sweden, Denmark, and Finland. N Engl J Med. 2000, 343: 78-85. 10.1056/NEJM200007133430201.CrossRefPubMed
13.
Antoniou AC, Pharoah PD, McMullan G, Day NE, Stratton MR, Peto J, Ponder BJ, Easton DF: A comprehensive model for familial breast cancer incorporating BRCA1, BRCA2 and other genes. Br J Cancer. 2002, 86: 76-83. 10.1038/sj.bjc.6600008.CrossRefPubMedPubMedCentral
14.
Smith P, McGuffog L, Easton DF, Mann GJ, Pupo GM, Newman B, Chenevix-Trench G, Szabo C, Southey M, Investigators kConFab, et al: A genome wide linkage search for breast cancer susceptibility genes.Genes. Chromosomes and Cancer. 2006, 45: 646-655.CrossRef
15.
Rosa-Rosa JM, Pita G, Urioste M, Llort G, Brunet J, Lazaro C, Blanco I, Ramon y Cajal T, Diez O, de la Hoya M, et al: Genome-wide linkage scan reveals three putative breast-cancer-susceptibility loci. Am J Hum Genet. 2009, 84: 115-122. 10.1016/j.ajhg.2008.12.013.CrossRefPubMedPubMedCentral
16.
Gonzalez-Neira A, Rosa-Rosa JM, Osorio A, Gonzalez E, Southey M, Sinilnikova O, Lynch H, Oldenburg RA, van Asperen CJ, Hoogerbrugge N, et al: Genomewide high-density SNP linkage analysis of non-BRCA1/2 breast cancer families identifies various candidate regions and has greater power than microsatellite studies. BMC Genomics. 2007, 8: 299-10.1186/1471-2164-8-299.CrossRefPubMedPubMedCentral
17.
Rosa-Rosa JM, Pita G, Gonzalez-Neira A, Milne RL, Fernandez V, Ruivenkamp C, van Asperen CJ, Devilee P, Benitez J: A 7 Mb region within 11q13 may contain a high penetrance gene for breast cancer. Breast Cancer Res Treat. 2009, 118: 151-159. 10.1007/s10549-009-0317-1.CrossRefPubMed
18.
Noensie EN, Dietz HC: A strategy for disease gene identification through nonsense-mediated mRNA decay inhibition. Nature Biotechnology. 2001, 19: 434-439. 10.1038/88099.CrossRefPubMed
19.
Ionov Y, Nowak N, Perucho M, Markowitz S, Cowell JK: Manipulation of nonsense mediated decay identifies gene mutations in colon cancer Cells with microsatellite instability Oncogene. 2004, 23: 639-645.PubMed
20.
Maquat LE: Nonsense-mediated mRNA decay in mammals. Journal of Cell Science. 2005, 118: 1773-1776. 10.1242/jcs.01701.CrossRefPubMed
21.
Wolf M, Edgren H, Muggerud A, Kilpinen S, Huusko P, Sorlie T, Mousses S, Kallioniemi O: NMD microarray analysis for rapid genome-wide screen of mutated genes in cancer. Cell Oncology. 2005, 27: 169-173.
22.
Khajavi M, Inoue K, Lupski JR: Nonsense-mediated mRNA decay modulates clinical outcome of genetic disease. European Journal of Human Genetics. 2006, 14: 1074-1081. 10.1038/sj.ejhg.5201649.CrossRefPubMed
23.
Ivanov I, Lo KC, Hawthorn L, Cowell JK, Ionov Y: Identifying candidate colon cancer tumor suppressor genes using inhibition of nonsense-mediated mRNA decay in colon cancer cells. Oncogene. 2007, 26: 2873-2884. 10.1038/sj.onc.1210098.CrossRefPubMed
24.
El-Bchiri J, Guilloux A, Dartigues P, Loire E, Mercier D, Buhard O, Sobhani I, de la Grange P, Auboeuf D, Praz F, et al: Nonsense-mediated mRNA decay impacts MSI-driven carcinogenesis and anti-tumor immunity in colorectal cancers. PLoS ONE. 2008, 3: e2583-10.1371/journal.pone.0002583.CrossRefPubMedPubMedCentral
25.
Huusko P, Ponciano-Jackson D, Wolf M, Kiefer JA, Azorsa DO, Tuzmen S, Weaver D, Robbins C, Moses T, Allinen M, et al: Nonsense-mediated decay microarray analysis identifies mutations of EPHB2 in human prostate cancer. Nature Genetics. 2004, 36: 979-983. 10.1038/ng1408.CrossRefPubMed
26.
Rossi MR, Hawthorn L, Platt J, Burkhardt T, Cowell JK, Ionov Y: Identification of inactivating mutations in the JAK1, SYNJ2, and CLPTM1 genes in prostate cancer cells using inhibition of nonsensemediated decay and microarray analysis. Cancer Genetics and Cytogenetics. 2005, 161: 97-103. 10.1016/j.cancergencyto.2005.02.006.CrossRefPubMed
27.
Bloethner S, Mould A, Stark M, Hayward NK: Identification of ARHGEF17, DENND2D, FGFR3, and RB1 mutations in melanoma by inhibition of nonsense-mediated mRNA decay. Genes Chromosomes Cancer. 2008, 47: 1076-1085. 10.1002/gcc.20598.CrossRefPubMed
28.
Pinyol M, Bea S, Pla L, Ribrag V, Bosq J, Rosenwald A, Campo E, Jares P: Inactivation of RB1 in mantle-cell lymphoma detected by nonsensemediated mRNA decay pathway inhibition and microarray analysis. Blood. 2007, 109: 5422-5429. 10.1182/blood-2006-11-057208.CrossRefPubMed
29.
Duns G, van den Berg E, van Duivenbode I, Osinga J, Hollema H, Hofstra RM, Kok K: Histone methyltransferase gene SETD2 is a novel tumor suppressor gene in clear cell renal cell carcinoma. Cancer Res. 2010, 70: 4287-4291. 10.1158/0008-5472.CAN-10-0120.CrossRefPubMed
30.
Evans DG, Eccles DM, Rahman N, Young K, Bulman M, Amir E, Shenton A, Howell A, Lalloo F: A new scoring system for the chances of identifying a BRCA1/2 mutation outperforms existing models including BRCAPRO. J Med Genet. 2004, 41: 474-480. 10.1136/jmg.2003.017996.CrossRefPubMedPubMedCentral
31.
Evans DG, Lalloo F, Wallace A, Rahman N: Update on the Manchester Scoring System for BRCA1 and BRCA2 testing. J Med Genet. 2005, 42: e39-10.1136/jmg.2005.031989.CrossRefPubMedPubMedCentral
32.
Du P, Kibbe WA, Lin SM: lumi: a pipeline for processing Illumina microarray. Bioinformatics. 2008, 24: 1547-1548. 10.1093/bioinformatics/btn224.CrossRefPubMed
33.
Edgar R, Domrachev M, Lash AE: Gene Expression Omnibus: NCBI gene expression and hybridization array data repository. Nucleic Acids Res. 2002, 30: 207-210. 10.1093/nar/30.1.207.CrossRefPubMedPubMedCentral
34.
Smyth GK: Linear models and empirical bayes methods for assessing differential expression in microarray experiments. Stat Appl Genet Mol Biol. 2003, 3: :Article3.
35.
Desmet FO, Hamroun D, Lalande M, Collod-Beroud G, Claustres M, Beroud C: Human Splicing Finder: an online bioinformatics tool to predict splicing signals. Nucleic Acids Res. 2009, 37: e67-10.1093/nar/gkp215.CrossRefPubMedPubMedCentral
36.
Esterbauer H, Oberkofler H, Krempler F, Patsch W: Human peroxisome proliferator activated receptor gamma coactivator 1 (PPARGC1) gene: cDNA sequence, genomic organization, chromosomal localization, and tissue expression. Genomics. 1999, 62: 98-102. 10.1006/geno.1999.5977.CrossRefPubMed
37.
Knutti D, Kaul A, Kralli A: A tissue-specific coactivator of steroid receptors, identified in a functional genetic screen. Mol Cell Biol. 2000, 20: 2411-2422. 10.1128/MCB.20.7.2411-2422.2000.CrossRefPubMedPubMedCentral
38.
Wu Z, Puigserver P, Andersson U, Zhang C, Adelmant G, Mootha V, Troy A, Cinti S, Lowell B, Scarpulla RC, Spiegelman BM: Mechanisms controlling mitochondrial biogenesis and respiration through the thermogenic coactivator PGC-1. Cell. 1999, 98: 115-124. 10.1016/S0092-8674(00)80611-X.CrossRefPubMed
39.
St-Pierre J, Lin J, Krauss S, Tarr PT, Yang R, Newgard CB, Spiegelman BM: Bioenergetic analysis of peroxisome proliferator-activated receptor gamma coactivators 1alpha and 1beta (PGC-1alpha and PGC-1beta) in muscle cells. J Biol Chem. 2003, 278: 26597-26603. 10.1074/jbc.M301850200.CrossRefPubMed
40.
Kressler D, Schreiber SN, Knutti D, Kralli A: The PGC-1-related protein PERC is a selective coactivator of estrogen receptor alpha. J Biol Chem. 2002, 277: 13918-13925. 10.1074/jbc.M201134200.CrossRefPubMed
41.
Tcherepanova I, Puigserver P, Norris JD, Spiegelman BM, McDonnell DP: Modulation of estrogen receptor-alpha transcriptional activity by the coactivator PGC-1. J Biol Chem. 2000, 275: 16302-16308. 10.1074/jbc.M001364200.CrossRefPubMed
42.
Platet N, Cathiard AM, Gleizes M, Garcia M: Estrogens and their receptors in breast cancer progression: a dual role in cancer proliferation and invasion. Crit Rev Oncol Hematol. 2004, 51: 55-67. 10.1016/j.critrevonc.2004.02.001.CrossRefPubMed
43.
Anderson E: The role of oestrogen and progesterone receptors in human mammary development and tumorigenesis. Breast Cancer Res. 2002, 4: 197-201. 10.1186/bcr452.CrossRefPubMedPubMedCentral
44.
Roger P, Daures JP, Maudelonde T, Pignodel C, Gleizes M, Chapelle J, Marty-Double C, Baldet P, Mares P, Laffargue F, Rochefort H: Dissociated overexpression of cathepsin D and estrogen receptor alpha in preinvasive mammary tumors. Hum Pathol. 2000, 31: 593-600. 10.1053/hp.2000.6687.CrossRefPubMed
45.
Osborne CK: Steroid hormone receptors in breast cancer management. Breast Cancer Res Treat. 1998, 51: 227-238. 10.1023/A:1006132427948.CrossRefPubMed
46.
Ali S, Coombes RC: Estrogen receptor alpha in human breast cancer: occurrence and significance. J Mammary Gland Biol Neoplasia. 2000, 5: 271-281. 10.1023/A:1009594727358.CrossRefPubMed
47.
Wirtenberger M, Tchatchou S, Hemminki K, Schmutzhard J, Sutter C, Schmutzler RK, Meindl A, Wappenschmidt B, Kiechle M, Arnold N, et al: Associations of genetic variants in the estrogen receptor coactivators PPARGC1A, PPARGC1B and EP300 with familial breast cancer. Carcinogenesis. 2006, 27: 2201-2208. 10.1093/carcin/bgl067.CrossRefPubMed
48.
Shi J, Hu Z, Pabon K, Scotto KW: Caffeine regulates alternative splicing in a subset of cancer-associated genes: a role for SC35. Mol Cell Biol. 2008, 28: 883-895. 10.1128/MCB.01345-07.CrossRefPubMed
49.
Yu L, Coelho JE, Zhang X, Fu Y, Tillman A, Karaoz U, Fredholm BB, Weng Z, Chen JF: Uncovering multiple molecular targets for caffeine using a drug target validation strategy combining A 2A receptor knockout mice with microarray profiling. Physiol Genomics. 2009, 37: 199-210. 10.1152/physiolgenomics.90353.2008.CrossRefPubMedPubMedCentral
50.
Jeganathan D, Fox MF, Young JM, Yates JR, Osborne JP, Povey S: Nonsense-mediated RNA decay in the TSC1 gene suggests a useful tool pre- and post-positional cloning. Hum Genet. 2002, 111: 555-565. 10.1007/s00439-002-0821-4.CrossRefPubMed
51.
Cheng J, Maquat LE: Nonsense codons can reduce the abundance of nuclear mRNA without affecting the abundance of pre-mRNA or the halflife of cytoplasmic mRNA. Mol Cell Biol. 1993, 13: 1892-1902.CrossRefPubMedPubMedCentral
52.
Mendell JT, Ap Rhys CMJ, Dietz HC: Separable roles for rent1/hUpf1 in altered splicing and decay of nonsense transcripts. Science. 2002, 298: 419-422. 10.1126/science.1074428.CrossRefPubMed
53.
Mendell JT, Sharifi NA, Meyers JL, Martinez-Murillo F, Dietz HC: Nonsense surveillance regulates expression of diverse classes of mammalian transcripts and mutes genomic noise. Nature Genetics. 2004, 36: 1073-1078. 10.1038/ng1429.CrossRefPubMed
54.
Shin N, You KT, Lee H, Kim WK, Song M, Choi HJ, Rhee H, Nam SW, Kim H: Identification of frequently mutated genes with relevance to nonsense mediated mRNA decay in the high microsatellite instability cancers. Int J Cancer. 2010, 128: 2872-2880.CrossRefPubMed
55.
Mattila H, Schindler M, Isotalo J, Ikonen T, Vihinen M, Oja H, Tammela TL, Wahlfors T, Schleutker J: NMD and microRNA expression profiling of the HPCX1 locus reveal MAGEC1 as a candidate prostate cancer predisposition gene. BMC Cancer. 2011, 11: 327-10.1186/1471-2407-11-327.CrossRefPubMedPubMedCentral
56.
Linde L, Boelz S, Neu-Yilik G, Kulozik AE, Kerem B: The efficiency of nonsense-mediated mRNA decay is an inherent character and varies among different cells. Eur J Hum Genet. 2007, 15: 1156-1162. 10.1038/sj.ejhg.5201889.CrossRefPubMed
57.
Resta N, Susca FC, Di Giacomo MC, Stella A, Bukvic N, Bagnulo R, Simone C, Guanti G: A homozygous frameshift mutation in the ESCO2 gene: evidence of intertissue and interindividual variation in Nmd efficiency. J Cell Physiol. 2006, 209: 67-73. 10.1002/jcp.20708.CrossRefPubMed
58.
Bahassi el M, Penner CG, Robbins SB, Tichy E, Feliciano E, Yin M, Liang L, Deng L, Tischfield JA, Stambrook PJ: The breast cancer susceptibility allele CHEK2*1100delC promotes genomic instability in a knock-in mouse model. Mutat Res. 2007, 616: 201-209. 10.1016/j.mrfmmm.2006.11.025.CrossRefPubMed
59.
Zetoune AB, Fontaniere S, Magnin D, Anczukow O, Buisson M, Zhang CX, Mazoyer S: Comparison of nonsense-mediated mRNA decay efficiency in various murine tissues. BMC Genet. 2008, 9: 83-CrossRefPubMedPubMedCentral
60.
Viegas MH, Gehring NH, Breit S, Hentze MW, Kulozik AE: The abundance of RNPS1, a protein component of the exon junction complex, can determine the variability in efficiency of the Nonsense Mediated Decay pathway. Nucleic Acids Res. 2007, 35: 4542-4551. 10.1093/nar/gkm461.CrossRefPubMedPubMedCentral
61.
Buffart TE, Tijssen M, El-Bchiri J, Duval A, van de Wiel MA, Ylstra B, Meijer GA, Carvalho B: NMD inhibition fails to identify tumour suppressor genes in microsatellite stable gastric cancer cell lines. BMC Med Genomics. 2009, 2: 39-10.1186/1755-8794-2-39.CrossRefPubMedPubMedCentral
62.
Kunnev D, Ivanov I, Ionov Y: Par-3 partitioning defective 3 homolog (C. elegans) and androgen-induced prostate proliferative shutoff associated protein genes are mutationally inactivated in prostate cancer cells. BMC Cancer. 2009, 9: 318-10.1186/1471-2407-9-318.CrossRefPubMedPubMedCentral
63.
Hamaguchi I, Ooka A, Brun A, Richter J, Dahl N, Karlsson S: Gene transfer improves erythroid development in ribosomal protein S19-deficient Diamond-Blackfan anemia. Blood. 2002, 100: 2724-2731. 10.1182/blood.V100.8.2724.CrossRefPubMed
Metadata
Title
The application of nonsense-mediated mRNA decay inhibition to the identification of breast cancer susceptibility genes
Authors
Julie K Johnson
Nic Waddell
Georgia Chenevix-Trench
kConFab Investigators
Publication date
01-12-2012
Publisher
BioMed Central
Published in
BMC Cancer / Issue 1/2012
Electronic ISSN: 1471-2407
DOI
https://doi.org/10.1186/1471-2407-12-246

Other articles of this Issue 1/2012

BMC Cancer 1/2012 Go to the issue

Research article

Penetration of anticancer drugs through tumour tissue as a function of cellular packing density and interstitial fluid pressure and its modification by bortezomib

Study protocol

Tri-Modality therapy with I-125 brachytherapy, external beam radiation therapy, and short- or long-term hormone therapy for high-risk localized prostate cancer (TRIP): study protocol for a phase III, multicenter, randomized, controlled trial

Study protocol

Physiological and neurophysiological determinants of postcancer fatigue: design of a randomized controlled trial

Research article

Mammographic density and inter-observer variability of pathologic evaluation of core biopsies among women with mammographic abnormalities

Research article

Overexpression of SERBP1 (Plasminogen activator inhibitor 1 RNA binding protein) in human breast cancer is correlated with favourable prognosis

Research article

DNA methylation regulates expression of VEGF-R2 (KDR) and VEGF-R3 (FLT4)
Webinar | 19-02-2024 | 17:30 (CET)

Keynote webinar | Spotlight on antibody–drug conjugates in cancer

Watch now

Antibody–drug conjugates (ADCs) are novel agents that have shown promise across multiple tumor types. Explore the current landscape of ADCs in breast and lung cancer with our experts, and gain insights into the mechanism of action, key clinical trials data, existing challenges, and future directions.

Dr. Véronique Diéras
Prof. Fabrice Barlesi
Developed by: Springer Medicine
Image Credits