Use of DNA–Damaging Agents and RNA Pooling to Assess Expression Profiles Associated with and Mutation Status in Familial Breast Cancer Patients

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A large number of rare sequence variants of unknown clinical significance have been identified in the breast cancer susceptibility genes, BRCA1 and BRCA2. Laboratory-based methods that can distinguish between carriers of pathogenic mutations and non-carriers are likely to have utility for the classification of these sequence variants. To identify predictors of pathogenic mutation status in familial breast cancer patients, we explored the use of gene expression arrays to assess the effect of two DNA–damaging agents (irradiation and mitomycin C) on cellular response in relation to BRCA1 and BRCA2 mutation status. A range of regimes was used to treat 27 lymphoblastoid cell-lines (LCLs) derived from affected women in high-risk breast cancer families (nine BRCA1, nine BRCA2, and nine non-BRCA1/2 or BRCAX individuals) and nine LCLs from healthy individuals. Using an RNA–pooling strategy, we found that treating LCLs with 1.2 µM mitomycin C and measuring the gene expression profiles 1 hour post-treatment had the greatest potential to discriminate BRCA1, BRCA2, and BRCAX mutation status. A classifier was built using the expression profile of nine QRT–PCR validated genes that were associated with BRCA1, BRCA2, and BRCAX status in RNA pools. These nine genes could distinguish BRCA1 from BRCA2 carriers with 83% accuracy in individual samples, but three-way analysis for BRCA1, BRCA2, and BRCAX had a maximum of 59% prediction accuracy. Our results suggest that, compared to BRCA1 and BRCA2 mutation carriers, non-BRCA1/2 (BRCAX) individuals are genetically heterogeneous. This study also demonstrates the effectiveness of RNA pools to compare the expression profiles of cell-lines from BRCA1, BRCA2, and BRCAX cases after treatment with irradiation and mitomycin C as a method to prioritize treatment regimes for detailed downstream expression analysis.

Vyšlo v časopise: Use of DNA–Damaging Agents and RNA Pooling to Assess Expression Profiles Associated with and Mutation Status in Familial Breast Cancer Patients. PLoS Genet 6(2): e32767. doi:10.1371/journal.pgen.1000850
Kategorie: Research Article
prolekare.web.journal.doi_sk: https://doi.org/10.1371/journal.pgen.1000850

Souhrn

Zdroje

1. PerouCM

SorlieT

EisenMB

van de RijnM

JeffreySS

2000 Molecular portraits of human breast tumours. Nature 406 747 752

2. SorlieT

PerouCM

TibshiraniR

AasT

GeislerS

2001 Gene expression patterns of breast carcinomas distinguish tumor subclasses with clinical implications. Proc Natl Acad Sci U S A 98 10869 10874

3. SorlieT

TibshiraniR

ParkerJ

HastieT

MarronJS

2003 Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci U S A 100 8418 8423

4. WeigeltB

HuZ

HeX

LivasyC

CareyLA

2005 Molecular portraits and 70-gene prognosis signature are preserved throughout the metastatic process of breast cancer. Cancer Res 65 9155 9158

5. FinakG

BertosN

PepinF

SadekovaS

SouleimanovaM

2008 Stromal gene expression predicts clinical outcome in breast cancer. Nat Med 14 518 527

6. HedenfalkI

DugganD

ChenY

RadmacherM

BittnerM

2001 Gene-expression profiles in hereditary breast cancer. N Engl J Med 344 539 548

7. Kote-JaraiZ

WilliamsRD

CattiniN

CopelandM

GiddingsI

2004 Gene expression profiling after radiation-induced DNA damage is strongly predictive of BRCA1 mutation carrier status. Clin Cancer Res 10 958 963

8. Kote-JaraiZ

MatthewsL

OsorioA

ShanleyS

GiddingsI

2006 Accurate prediction of BRCA1 and BRCA2 heterozygous genotype using expression profiling after induced DNA damage. Clin Cancer Res 12 3896 3901

9. WaddellN

Ten HaafA

MarshA

JohnsonJ

WalkerLC

2008 BRCA1 and BRCA2 missense variants of high and low clinical significance influence lymphoblastoid cell line post-irradiation gene expression. PLoS Genet 4 e1000080 doi:10.1371/journal.pgen.1000080

10. CheungVG

ConlinLK

WeberTM

ArcaroM

JenKY

2003 Natural variation in human gene expression assessed in lymphoblastoid cells. Nat Genet 33 422 425

11. CorreaCR

CheungVG

2004 Genetic variation in radiation-induced expression phenotypes. Am J Hum Genet 75 885 890

12. WaddellN

JonnalagaddaJ

MarshA

GristS

JenkinsM

2006 Characterization of the breast cancer associated ATM 7271T>G (V2424G) mutation by gene expression profiling. Genes Chromosomes Cancer 45 1169 1181

13. SmirnovDA

MorleyM

ShinE

SpielmanRS

CheungVG

2009 Genetic analysis of radiation-induced changes in human gene expression. Nature 459 587 591

14. AgrawalD

ChenT

IrbyR

QuackenbushJ

ChambersAF

2002 Osteopontin identified as lead marker of colon cancer progression, using pooled sample expression profiling. J Natl Cancer Inst 94 513 521

15. EnardW

KhaitovichP

KloseJ

ZollnerS

HeissigF

2002 Intra- and interspecific variation in primate gene expression patterns. Science 296 340 343

16. SmithP

McGuffogL

EastonDF

MannGJ

PupoGM

2006 A genome wide linkage search for breast cancer susceptibility genes. Genes Chromosomes Cancer 45 646 655

17. HedenfalkI

RingnerM

Ben-DorA

YakhiniZ

ChenY

2003 Molecular classification of familial non-BRCA1/BRCA2 breast cancer. Proc Natl Acad Sci U S A 100 2532 2537

18. WaddellN

ArnoldJ

CocciardiS

da SilvaL

MarshA

2009 Subtypes of familial breast tumours revealed by expression and copy number profiling. Breast Cancer Res Treat

19. ShihJH

MichalowskaAM

DobbinK

YeY

QiuTH

2004 Effects of pooling mRNA in microarray class comparisons. Bioinformatics 20 3318 3325

20. ZhangW

CarriquiryA

NettletonD

DekkersJC

2007 Pooling mRNA in microarray experiments and its effect on power. Bioinformatics 23 1217 1224

21. KendziorskiCM

ZhangY

LanH

AttieAD

2003 The efficiency of pooling mRNA in microarray experiments. Biostatistics 4 465 477

22. PengX

WoodCL

BlalockEM

ChenKC

LandfieldPW

2003 Statistical implications of pooling RNA samples for microarray experiments. BMC Bioinformatics 4 26

23. KendziorskiC

IrizarryRA

ChenKS

HaagJD

GouldMN

2005 On the utility of pooling biological samples in microarray experiments. Proc Natl Acad Sci U S A 102 4252 4257

24. HowlettNG

TaniguchiT

DurkinSG

D'AndreaAD

GloverTW

2005 The Fanconi anemia pathway is required for the DNA replication stress response and for the regulation of common fragile site stability. Hum Mol Genet 14 693 701

25. GuilloufC

VitJP

RosselliF

2000 Loss of the Fanconi anemia group C protein activity results in an inability to activate caspase-3 after ionizing radiation. Biochimie 82 51 58

26. ManjuK

MuralikrishnaB

ParnaikVK

2006 Expression of disease-causing lamin A mutants impairs the formation of DNA repair foci. J Cell Sci 119 2704 2714

27. WangW

2007 Emergence of a DNA-damage response network consisting of Fanconi anaemia and BRCA proteins. Nat Rev Genet 8 735 748

28. WalkerLC

WaddellN

Ten HaafA

GrimmondS

SpurdleAB

2008 Use of expression data and the CGEMS genome-wide breast cancer association study to identify genes that may modify risk in BRCA1/2 mutation carriers. Breast Cancer Res Treat 112 229 236

29. MelchorL

HonradoE

HuangJ

AlvarezS

NaylorTL

2007 Estrogen receptor status could modulate the genomic pattern in familial and sporadic breast cancer. Clin Cancer Res 13 7305 7313

30. JoosseSA

van BeersEH

TielenIH

HorlingsH

PeterseJL

2009 Prediction of BRCA1-association in hereditary non-BRCA1/2 breast carcinomas with array-CGH. Breast Cancer Res Treat 116 479 489

31. StefanssonOA

JonassonJG

JohannssonOT

OlafsdottirK

SteinarsdottirM

2009 Genomic profiling of breast tumours in relation to BRCA abnormalities and phenotypes. Breast Cancer Res 11 R47

32. MannGJ

ThorneH

BalleineRL

ButowPN

ClarkeCL

2006 Analysis of cancer risk and BRCA1 and BRCA2 mutation prevalence in the kConFab familial breast cancer resource. Breast Cancer Res 8 R12

33. WarrenM

LordCJ

MasabandaJ

GriffinD

AshworthA

2003 Phenotypic effects of heterozygosity for a BRCA2 mutation. Hum Mol Genet 12 2645 2656

34. ArnoldK

KimMK

FrerkK

EdlerL

SavelyevaL

2006 Lower level of BRCA2 protein in heterozygous mutation carriers is correlated with an increase in DNA double strand breaks and an impaired DSB repair. Cancer Lett 243 90 100

35. KornEL

TroendleJF

McShaneLM

SimonR

2004 Controlling the number of false discoveries: Application to high dimensional genomic data. J Stat Plan Infer 124 379 378

36. KornEL

LiMC

McShaneLM

SimonR

2007 An investigation of two multivariate permutation methods for controlling the false discovery proportion. Stat Med 26 4428 4440

37. DudoitS

FridlyandF