Literature DB >> 24662924

Frequent MYC coamplification and DNA hypomethylation of multiple genes on 8q in 8p11-p12-amplified breast carcinomas.

T Z Parris1, A Kovács2, S Hajizadeh2, S Nemes3, M Semaan1, M Levin1, P Karlsson1, K Helou1.   

Abstract

Genetic and epigenetic (DNA methylation, histone modifications, microRNA expression) crosstalk promotes inactivation of tumor suppressor genes or activation of oncogenes by gene loss/hypermethylation or duplications/hypomethylation, respectively. The 8p11-p12 chromosomal region is a hotspot for genomic aberrations (chromosomal rearrangements, amplifications and deletions) in several cancer forms, including breast carcinoma where amplification has been associated with increased proliferation rates and reduced patient survival. Here, an integrative genomics screen (DNA copy number, transcriptional and DNA methylation profiling) performed in 229 primary invasive breast carcinomas identified substantial coamplification of the 8p11-p12 genomic region and the MYC oncogene (8q24.21), as well as aberrant methylation and transcriptional patterns for several genes spanning the 8q12.1-q24.22 genomic region (ENPP2, FABP5, IMPAD1, NDRG1, PLEKHF2, RRM2B, SQLE, TAF2, TATDN1, TRPS1, VPS13B). Taken together, our findings suggest that MYC activity and aberrant DNA methylation may also have a pivotal role in the aggressive tumor phenotype frequently observed in breast carcinomas harboring 8p11-p12 regional amplification.

Entities:  

Year:  2014        PMID: 24662924      PMCID: PMC4038389          DOI: 10.1038/oncsis.2014.8

Source DB:  PubMed          Journal:  Oncogenesis        ISSN: 2157-9024            Impact factor:   7.485


Introduction

Genomic instability and epigenetic modulations, that is, DNA methylation, histone modifications, microRNA expression, contribute to the neoplastic phenotype by deregulating key gene functions that permit cells to bypass regulatory mechanisms controlling and maintaining normal cellular physiology.[1] Recently, genetic and epigenetic crosstalk has shown to be one of several major driving forces behind tumor initiation and progression.[2, 3, 4, 5, 6] However, DNA methylation is considered by some to be a secondary event which locks genes in their inactive/active states only after gene silencing/activation has been achieved by other means.[7, 8, 9, 10] Several well-characterized DNA regions have been investigated extensively in breast cancer for their role in genetic modulations, interactions in molecular pathways and association with unfavorable clinical outcome. These include the 8p11-p12, 8q24 (MYC), 11q13 (CCND1), 17q12 (ERBB2, GRB7, STARD3) and 20q13 (ZNF217, MYBL2, STK6) amplicons, some of which have become major molecular targets for breast cancer treatment. Regional amplification of the 8p11-p12 genomic region is a common genetic event in solid tumors, for example, breast carcinoma,[11, 12, 13] pleuropulmonary blastoma,[14] lung cancer and esophageal squamous cell carcinomas,[15, 16, 17, 18] urinary bladder cancer,[19, 20] osteosarcoma[21] and pancreatic adenocarcinoma.[17] In breast cancer cell lines, the initiation site and structure of the 8p11-p12 DNA rearrangement involved different mechanisms of gene activation, thereby resulting in the activation of different combinations of candidate genes.[22] To further define the role, 8p11-p12 regional amplification may have on breast cancer pathophysiology, we examined genome-wide copy number alterations, DNA methylation patterns and transcriptional changes in 229 primary invasive breast tumors. Here, we demonstrate that ∼50% of 8p11-p12-amplified tumors also harbor MYC amplification, as well as, hypomethylation of genes located in close proximity to the MYC gene.

Results and discussion

Amplification of the 8p11-p12 genomic region is a common genetic event in breast carcinoma with clinical implications. To assess aberrant transcriptional and DNA methylation patterns in invasive breast carcinomas harboring the 8p11-p12 amplicon, an integrative analysis was performed using DNA copy number, DNA methylation and transcriptome data from 229 primary invasive breast cancer samples previously presented in our work,[23, 24] including our own unpublished data. The DNA copy number analysis using array-comparative genomic hybridization data showed recurrent copy number alterations on chromosome bands 8p11-p12 in 83 tumors (36%), including 47/83 high-level gains/amplifications, 20/83 low-level gains and 16/83 heterozygous losses. Copy number alterations were confirmed using a set of overlapping BAC clones building a contig over the 8p11-p12 genomic region. On average, there was a five-fold increase in the number of amplifications observed in lesions containing the 8p11-p12 amplicon compared with those lacking the amplicon (P=1.8E−13). In general, amplification of the 8p11-p12 genomic region was predominantly coamplified with 1q, 8q, 11q, 12p, 16p, 17q or 20q, but also occurred as the sole region of amplification in two cases. Notably, 53% (n=24) of 8p11-p12-amplified tumors were coamplified with the MYC gene, whereas only 20% (n=9) and 18% (n=8) were coamplified with the CCND1 and ERBB2 genes, respectively (Figure 1). Extensive research has been carried out on the coamplification of 8p11-p12 and CCND1, but few studies have investigated 8p11-p12 and MYC interactions.[22, 25]
Figure 1

Array-CGH genomic profiles showing recurrent DNA amplification of the 8p11-p12 genomic region in breast carcinoma. The top panel shows focal amplification (log2 ratio>0.5) of the 8p11-p12 region in two breast tumors. Black dots depict BAC clones spanning chromosome 8 for tumor 8931 and gray dots for tumor 9493. The bottom panel shows amplification of the 8p11-p12 and 8q regions. Black dots depict BAC clones spanning chromosome 8 for tumor 11248 and gray dots for tumor 8138. The x-axis shows chromosome 8 from the 8p telomere to the 8q telomere. The y-axis shows the log2 ratio value for each BAC clone (tumor gDNA versus normal control gDNA).

In accordance with published studies, genetic aberrations of the 8p11-p12 region (gain, loss and amplification; P=5.0E−6), including amplification (P=4.0E−5) or loss (P=0.005), were associated with reduced overall survival rates.[26] Conversely, genomic gain was not indicative of unfavorable patient outcome (P=0.08). The amplicon was most prevalent in tumors of large pathologic size (P=0.0002), high genomic grade index status (P=0.0004) and high S-phase fraction (P=0.002; Table 1). There was no significant difference in histologic type, axillary lymph node status, estrogen/progesterone receptor status, human epidermal growth factor receptor 2 (HER2)/neu receptor status, triple negative status or molecular breast cancer subtype. These findings are consistent with previous reports showing high cell proliferation (high Ki-67) and high tumor grade in breast carcinomas harboring the 8p11-p12 amplicon. However, Gelsi–Boyer et al. [26] did not find a connection with amplification and tumor size. Recently, several studies have found an association between the luminal B molecular subtype and DNA amplification of two genes (ZNF703 and FGFR1) within the 8p11-p12 amplicon. Interestingly, tumors harboring these genetic alterations were also resistant to endocrine therapy.[27, 28, 29, 30] However, we show that ∼80% of the breast tumors analyzed here were luminal B subtype/estrogen receptor-positive regardless of 8p11-p12 amplicon status. Furthermore, ZNF703 was generally upregulated in breast carcinomas, particularly in estrogen receptor-positive tumors, compared with normal breast tissue.[24] Functional studies have provided additional evidence for biological effects in vitro and in vivo using small-interfering RNA-mediated knockdown of candidate genes within the 8p11-p12 genomic region.[27, 28, 29, 30, 31, 32, 33] Eight genes (BAG4, C8orf4, DDHD2, ERLIN2, LSM1, PPAPDC1B, WHSC1L1 and ZNF703) have thereby emerged as targets with oncogenic potential.
Table 1

Correlation between 8p11-p12 DNA amplification and clinicopathological features in breast carcinoma

CharacteristicsNumber of tumors (%)
 Total tumors (n=229)Neutral DNA dosagea (n=71)DNA amplificationa (n=45)P-value
Age
 Mean596060 
 Range30–8837–7930–88 
     
Histologic type   0.7
 Ductal136 (59)52 (73)21 (47) 
 Lobular22 (10)7 (10)4 (9) 
 Other26 (11)12 (17)3 (7) 
 Not available45 (20)0 (0)17 (38) 
     
Axillary lymph node status   0.2
 pN082 (36)38 (54)12 (27) 
 pN184 (37)33 (46)19 (42) 
 Not available63 (28)0 (0)14 (31) 
     
Pathologic tumor size   0.0002
 pT151 (22)22 (31)4 (9) 
 pT289 (39)35 (49)12 (27) 
 pT351 (22)11 (15)20 (44) 
 pT46 (3)3 (4)0 (0) 
 Not available32 (14)0 (0)9 (20) 
     
S-phase fraction   0.002
 ⩽6.1112 (49)59 (83)18 (40) 
 >6.169 (30)12 (17)16 (36) 
 Not available48 (21)0 (0)11 (24) 
     
GGI status   0.0004
 Low45 (20)31 (44)6 (13) 
 High73 (32)26 (37)29 (64) 
 Not available111 (48)14 (20)10 (22) 
     
Estrogen receptor   0.8
 Negative60 (26)14 (20)10 (22) 
 Positive166 (72)57 (80)34 (76) 
 Not available3 (1)0 (0)1 (2) 
     
Progesterone receptor   0.7
 Negative108 (47)31 (44)21 (47) 
 Positive118 (52)40 (56)23 (51) 
 Not available3 (1)0 (0)1 (2) 
     
HER2/neu status   0.6
 Negative199 (87)61 (86)37 (82) 
 Positive30 (13)10 (14)8 (18) 
 Not available0 (0)0 (0)0 (0) 
     
Triple negative status   1.0
 Yes41 (18)9 (13)5 (11) 
 No186 (81)62 (87)39 (87) 
 Not available2 (1)0 (0)1 (2) 
     
Subtype   0.9
 Luminal subtype A2 (1)1 (1)0 (0) 
 Luminal subtype B/HER2-101 (44)47 (66)31 (69) 
 Luminal subtype B/HER2+13 (6)8 (11)4 (9) 
 HER2/ER-18 (8)10 (14)5 (11) 
 Basal-like16 (7)5 (7)5 (11) 
 Normal-like0 (0)0 (0)0 (0) 
 Not available79 (34)0 (0)0 (0) 

Abbreviations: GGI status, genomic grade index; HER2, human epidermal growth factor receptor 2.

P-values were calculated using the Fisher's exact test (neutral DNA dosage versus DNA amplification).

Tumor specimens included in the analysis with both array-CGH and gene expression microarray data are available.

To delineate whether aberrant methylation patterns may also has a role in the evolution of breast tumors harboring the 8p11-p12 amplicon, we performed genome-wide DNA methylation analysis on 22/229 tumors (11 tumors harboring the amplicon and 11 tumors lacking the amplicon) using the 450k Infinium Methylation Beadchip (Illumina Inc., San Diego, CA, USA). Of the 382 815 cytosine sites remaining after filtering, ⩽1% (n=2066) were differentially methylated in tumors harboring the 8p11-p12 amplicon compared with samples lacking the amplicon. Eighty-nine percent of aberrantly-methylated cytosine sites were hypermethylated (n=1847) and 11% (n=219) of sites were hypomethylated. The promoter regions (200 and 1500 bp upstream transcriptional start sites, 5′ untranslated region and the first exon) were tightly linked with hypermethylation (n=352 sites, 92%), whereas fewer methylation events occurred further downstream in the body of genes and at the 3′ untranslated region region. The highest number of aberrantly-methylated cytosine sites surrounded CpG islands (n=408) with fewer sites found in the CpG shores (up to 2 kb from CpG islands, n=172) and shelves (2–4 kb from CpG islands, n= 48). The majority of aberrant methylation patterns occurred within genes and intergenic regions, whereas few microRNA transcripts were found (Figure 2). We found that differential methylation occurred on all chromosomes including the X chromosome in 8p11-p12-amplified tumors, where hypermethylation ranged from 72–98% and the highest hypomethylation rates were found on chromosomes 8 and 9 with 28% and 24%, respectively.
Figure 2

DNA methylation patterns in 8p11-p12-amplified tumors. The distribution of aberrant methylation (hyper- and hypomethylation, Q<0.05) and gene expression patterns (downregulation and upregulation, Q<0.01) among the 2066 differentially-methylated cytosine sites in 8p11-p12-amplified tumors. Transcripts were categorized into functional genomic regions (promoter region (between 200 and 1500 bp upstream of transcriptional start sites, 5′ untranslated region, first exon), gene body and 3′ untranslated region region) and regions surrounding CpG islands (CpG islands, 2 kb from CpG islands (CpG shores) and 2–4 kb from CpG islands (CpG shelves)).

Few of the methylation events resulted in aberrant gene expression patterns in 8p11-p12-amplified tumors (n=61, 4.5% of aberrantly-methylated coding RNAs), although disparate methylation-transcriptional patterns were observed for 23/61 genes (38%); 20/23 genes were hypermethylated and overexpressed and 3/23 genes were hypomethylated and underexpressed (Table 2). Univariate Cox regression analysis showed that aberrant transcriptional patterns for 47/61 genes influenced overall survival rates. In addition, only one gene located at 8p11-p12 showed differential methylation and gene expression patterns, that is, BRF2 was hypermethylated but overexpressed owing to BRF2 gene amplification in 7/11 cases. Gene Ontology enrichment analysis of the genes with aberrant DNA methylation and gene expression patterns revealed several cancer-related processes, for example, cell differentiation, DNA replication, cell migration and cell adhesion (Table 3).
Table 2

Differentially-methylated genes in 8p11-p12-amplified breast tumors

Gene symbolChromosomeDelta beta valueaGene expression (n=22)bGene expression (n=150)cCox coefficient (n=150)dCox P-value (n=150)dDNA copy number 8p11-p12-amplified tumors (n=11)e amplification/loss/normalDNA copy number 8p11-p12 nonamplified tumors (n=11)f amplification/loss/normal
BAMBI10p12.1HypomethylatedOverexpressed  NS0/0/110/0/11
CXCL1210q11.21Hypermethylated Underexpressed−0.4983.76E−050/0/110/0/11
HTRA110q26.13Hypermethylated Underexpressed−0.4001.57E−04  
CRYAB;HSPB211q23.1HypermethylatedUnderexpressedUnderexpressed NS0/4/70/0/11
PTHLH12p11.22HypermethylatedUnderexpressedUnderexpressed NS1/0/100/0/11
HOXC1312q13.13Hypermethylated Overexpressed0.3973.96E−040/1/100/0/11
PABPC313q12.13Hypermethylated Overexpressed0.6431.12E−060/4/70/0/11
TRAPPC6B14q21.1Hypermethylated Overexpressed0.8661.80E−050/2/90/0/11
BMP414q22.2Hypermethylated Underexpressed−0.3790.0010/3/80/0/11
BATF14q24.3Hypomethylated Underexpressed−0.5020.0020/4/70/0/11
ELL315q15.3Hypomethylated Overexpressed0.4320.0090/0/110/0/11
SEPHS216p11.2Hypomethylated Overexpressed0.4950.0030/0/110/0/11
SPN16p11.2Hypermethylated Overexpressed0.2540.0640/0/110/0/11
SPAG917q21.33HypermethylatedOverexpressedOverexpressed0.6280.0001/0/100/0/11
DHX4017q23.1HypermethylatedOverexpressed 0.5990.0042/0/90/0/11
CCDC4717q23.3Hypomethylated Overexpressed0.6710.001  
ICAM217q23.3HypermethylatedUnderexpressedUnderexpressed−0.4410.0121/0/100/0/11
CYGB17q25.1HypermethylatedUnderexpressed −0.4330.0130/0/110/0/11
NFIX19p13.2HypermethylatedUnderexpressed −0.2890.0230/0/110/0/11
NFIC19p13.3HypermethylatedUnderexpressed  NS0/1/100/0/11
CACNG619q13.42HypermethylatedOverexpressed  NS0/0/110/0/11
PHGDH1p12HypermethylatedUnderexpressed 0.3130.0020/0/110/0/11
CHI3L21p13.3Hypermethylated Underexpressed NS0/0/110/0/11
COL11A11p21.1HypermethylatedOverexpressed  NS0/1/100/0/11
AGL1p21.2HypomethylatedOverexpressedOverexpressed0.3370.0130/1/100/0/11
PODN1p32.3Hypermethylated Underexpressed−0.3660.0010/2/90/0/11
MMP23A;MMP23B1p36.33Hypermethylated Underexpressed−0.4150.0030/1/100/0/11
MMP23B1p36.33Hypermethylated Underexpressed−0.4150.0030/1/100/0/11
EXOC81q42.2HypomethylatedOverexpressedOverexpressed0.7342.58E−051/1/90/0/11
SYCP220q13.33HypomethylatedOverexpressedOverexpressed0.4473.15E−052/0/90/0/11
GREB12p25.1HypomethylatedOverexpressed −0.2680.0500/2/90/1/10
C2orf402q12.2HypermethylatedUnderexpressedUnderexpressed−0.2680.005  
SATB22q33.1HypermethylatedOverexpressed  NS0/0/110/0/11
KIF1A2q37.3HypermethylatedOverexpressed  NS0/0/110/0/11
TF3q22.1HypermethylatedUnderexpressed  NS0/1/100/0/11
TAPT14p15.32Hypomethylated Overexpressed NS  
SORBS24q35.1HypomethylatedUnderexpressedUnderexpressed−0.3260.004  
PIK3R15q13.1Hypermethylated Overexpressed0.5363.96E−040/0/110/0/11
CARTPT5q13.2HypermethylatedUnderexpressed  NS  
PCSK15q15HypermethylatedUnderexpressed −0.3260.0020/1/100/0/11
PAM5q21.1HypermethylatedUnderexpressedUnderexpressed−0.3400.0240/0/110/0/11
DMXL15q23.1HypermethylatedOverexpressedOverexpressed0.6209.99E−060/0/110/0/11
H2AFY5q31.1HypermethylatedOverexpressedOverexpressed0.8313.15E−070/0/110/0/11
DOCK25q35.1Hypomethylated Underexpressed NS0/0/110/0/11
SCGB3A15q35.3HypermethylatedUnderexpressed −0.2400.0010/0/110/0/11
USP496p21.1Hypermethylated Overexpressed0.3100.0311/0/100/0/11
SCAND36p22.1HypermethylatedOverexpressed 0.4920.015  
ID46p22.3Hypermethylated Overexpressed0.4921.95E−050/0/110/0/11
RARS2;ORC3L6q15Hypomethylated Overexpressed0.8221.85E−052/1/80/0/11
LRP116q25.1Hypomethylated Overexpressed0.6383.05E−040/1/100/0/11
C7orf28A7p22.1Hypomethylated Overexpressed0.7751.85E−050/0/110/0/11
LFNG7p22.3Hypermethylated Underexpressed−0.6684.55E−060/0/110/0/11
PON37q21.3HypermethylatedUnderexpressedUnderexpressed−0.3053.19E−051/0/100/0/11
NRCAM7q31.1Hypomethylated Overexpressed0.3360.0240/0/110/0/11
NDUFA57q31.32Hypermethylated Overexpressed0.7711.48E−040/1/100/0/11
LEP7q32.1Hypermethylated Overexpressed0.3570.0030/0/110/0/11
RARRES27q36.1Hypermethylated Underexpressed−0.2720.0200/0/110/0/11
BRF28p11.23HypermethylatedOverexpressedOverexpressed NS7/2/20/0/11
IMPAD18q12.1HypomethylatedOverexpressedOverexpressed1.0672.70E−07  
FABP58q21.13Hypermethylated Overexpressed NS1/0/100/0/11
PLEKHF28q22.1HypomethylatedOverexpressedOverexpressed0.3934.47E−043/0/80/0/11
VPS13B8q22.2Hypomethylated Overexpressed0.8787.06E−06  
RRM2B8q22.3HypomethylatedOverexpressedOverexpressed0.4520.0013/0/80/0/11
TRPS18q23.3HypermethylatedOverexpressedOverexpressed0.3200.0086/0/50/0/11
TRPS18q23.3HypomethylatedOverexpressedOverexpressed0.3200.0086/0/50/0/11
ENPP28q24.12HypermethylatedUnderexpressedUnderexpressed−0.2580.0172/0/90/0/11
TAF28q24.12Hypomethylated Overexpressed1.1641.34E−062/0/90/0/11
SQLE8q24.13HypomethylatedOverexpressedOverexpressed0.5662.95E−072/0/90/0/11
TATDN18q24.13HypomethylatedOverexpressedOverexpressed0.7832.89E−065/0/60/0/11
NDRG18q24.22Hypomethylated Overexpressed0.8435.03E−112/1/80/0/11
WDR44Xq24Hypomethylated Overexpressed0.9374.75E−063/0/80/0/11

Abbreviation: NS, not statistically significant.

Genes not correlating between DNA methylation and transcriptional patterns are shown in bold text.

Delta beta value (8p11-p12-amplified tumors versus nonamplified tumors) >0.14 are indicated by hypermethylation and <−0.14 are indicated by hypomethylation; Bonferroni adjusted P-value P<0.05.

Gene expression microarray log2 ratio for the 22 tumors (8p11–p12-amplified tumors versus nonamplified tumors) >0.58 are indicated by overexpression and <−0.58 are indicated by underexpression.

Gene expression microarray log2 ratio for the 150 tumors (8p11-p12-amplified tumors versus nonamplified tumors) > 0.58 are indicated by overexpression and < −0.58 are indicated by underexpression.

Univariate Cox proportional hazard regression models using the gene expression data for the 150 tumors and overall survival rates.

Array-CGH log2 ratio thresholds set at ⩾+0.5, −0.2 and between +0.5 and −0.2 for amplification, loss and normal copy number, respectively.

Array-CGH log2 ratio thresholds set at ⩾+0.5, –0.2 and between +0.5 and −0.2 for amplification, loss and normal copy number, respectively.

Table 3

Significantly enriched Gene Ontology (GO) terms identified by integrated DNA methylation and expression profiling in 8p11-p12-amplified breast tumors

CategoryGO termP-valueGene count
Biological process
 GO:0032099Negative regulation of appetite8.32E−052
 GO:0045671Negative regulation of osteoclast differentiation2.48E−042
 GO:0045060Negative thymic T-cell selection2.48E−042
 GO:0008343Adult feeding behavior4.93E−042
 GO:0006935Chemotaxis0.002034
 GO:0007281Germ cell development0.0028712
 GO:0006260DNA replication0.0032364
 GO:0007420Brain development0.0033233
 GO:0030335Positive regulation of cell migration0.0070462
 GO:0006366Transcription from RNA polymerase II promoter0.0145313
 GO:0016337Cell-cell adhesion0.0306512
 GO:0008544Epidermis development0.0428612
    
Molecular function
 GO:0043169Cation binding0.0115692
 GO:0008083Growth factor activity0.0131733
 GO:0001104RNA polymerase II transcription factor activity0.0138423
 GO:0005179Hormone activity0.0217682
 GO:0004252Serine-type endopeptidase activity0.0302473
 GO:0006351Transcription regulator activity0.0386152
    
Cellular component
 GO:0005615Extracellular space3.46E−0510
 GO:0005576Extracellular region2.89E−0417
 GO:0043005Neuron projection0.0028712
 GO:0009897External side of plasma membrane0.0795132
 GO:0005634Nucleus0.08134422
 GO:0005794Golgi apparatus0.083466
 GO:0005768Endosome0.0961522
 GO:0005578Proteinaceous extracellular matrix0.1071123
 GO:0005737Cytoplasm0.3359319
Interestingly, 11 genes spanning the 8q12.1-q24.22 genomic region were differentially methylated and expressed, of which nine genes (IMPAD1, NDRG1, PLEKHF2, RRM2B, SQLE, TAF2, TATDN1, TRPS1, VPS13B) were hypomethylated and overexpressed, the ENPP2 gene was hypermethylated and underexpressed and the FABP5 gene was hypermethylated but overexpressed. As the 11 genes were also coamplified with the 8p11-p12 region in at least one tumor specimen, we examined whether DNA copy number, DNA methylation or both had an impact on gene expression (Figure 3). We found that hypomethylation alone frequently enhanced gene expression patterns. However, hypomethylation and DNA amplification of the same transcript further enhanced expression levels. These findings suggest that genes in the 8q region are frequently targeted by more than one mechanism for activation in breast tumors harboring 8p11-p12 amplification. Consequently, ENPP2 was the only example showing lower expression levels when hypermethylated (at four different cytosine sites in the promoter region) despite amplification of the gene in 2/11 samples harboring the 8p11-p12 amplicon. These results indicate that aberrant methylation patterns may be a secondary event to further lock genes in their inactive or active states only after they have already been silenced or activated by other means.[7, 8, 9, 10] The ENPP2 gene was an exception to this phenomenon because hypermethylation occurred at four different cytosine sites in the promoter region of the gene, resulting in lower transcriptional levels despite amplification of the gene in 2/11 samples harboring the 8p11-p12 amplicon. However, 8/11 genes (FABP5, NDRG1, PLEKHF2, RRM2B, SQLE, TAF2, TATDN1, TRPS1) may not be distinctive of 8p11-p12 amplification as they were also differentially regulated in MYC coamplified tumors.
Figure 3

The effect of aberrant DNA copy number and DNA methylation on gene expression. Box plots showing the relationship between DNA copy number (CNA), methylation status and gene expression for three candidate genes (ENPP2, SQLE and SYCP2) in 22 tumor samples. X-axis, methylation and CNA status; Y-axis, gene expression signal intensity.

Several of the aberrantly-methylated genes spanning the 8q arm have been previously associated with cancer-related processes. In addition to gene amplification shown in the present study, VPS13B frameshift mutations have also been identified in gastric and colorectal cancers, as well as TRPS1-LASP1, PLEC1-ENPP2 and TATDN1-GSDMB fusion genes in breast carcinoma.[34, 35, 36] Recently, gain of TRPS1, TATDN1 and SQLE DNA copy numbers in estrogen receptor-positive, ERBB2-amplified breast tumors have been reported, and elevated SQLE levels were associated with distant metastasis-free survival.[37, 38, 39] TRPS1, a transcription factor that belongs to the GATA gene family, in which, protein expression is inhibited by androgens via the androgen receptor in prostate cancer and demonstrates high expression levels in both normal breast and tumor tissue. In breast tumors, TRPS1 expression is associated with ER, PgR, GATA3, HER2/neu expression and favorable clinical outcome.[40, 41] Elevated NDRG1 protein levels have been associated with shorter disease-free and overall survival, cell differentiation and breast cancer progression.[42, 43, 44] In contrast, Han et al.[45] demonstrated that NDRG1 methylation in breast cancer is associated with a more aggressive phenotype. Interestingly, substantial NDRG1 phosphorylation is found in Akt inhibitor-resistant breast cancer cell lines, which can be reversed by the mTORC1/2 inhibitor, MLN0128, in breast cancer xenograft models.[46, 47] p53-mediated induction of DNA damage-associated genes, such as RRM2B, can promote resistance of cancer cells to genotoxic therapy, which can be prevented by inhibiting histone deacetylases that can in turn inhibit ataxia telangiectasia-mutated kinase and p53 activation and their downstream targets.[48, 49, 50] The TAF2 gene is involved in general transcription processes and is the DNA binding component of the transcription factor II D transcription factor complex.[51] In summary, we have identified the enrichment of MYC amplification and hypomethylation of genes on cytoband 8q in 8p11-p12-amplified tumors. These findings indicate that the aggressive phenotype observed in invasive breast tumors harboring the 8p11-p12 amplicon may not only be a consequence of altered activity of amplified genes in the genomic region, but also a result of MYC coamplification and aberrant DNA methylation patterns on chromosome 8q.

Materials and methods

Tumor specimens

Primary invasive breast carcinoma specimens (n=229) corresponding to 185 patients diagnosed from 1988–1999 were obtained from the fresh-frozen tumor bank at the Sahlgrenska University Hospital Oncology Lab in accordance with the Declaration of Helsinki and approved by the Medical Faculty Research Ethics Committee (Gothenburg, Sweden). The 229 cases were compiled from three independent array-comparative genomic hybridization microarray datasets, including two published (138/229 tumors) and one unpublished (91/229 tumors) studies.[23, 24] The clinicopathological features of the 229 cases are shown in Table 1. Each tumor specimen was assessed for the presence of malignant cells using May–Grünwald Giemsa staining (Chemicon International, Temecula, CA, USA) on touch preparations. Highly representative specimens containing >70% neoplastic cell content were included in the microarray and fluorescence in situ hybridization analyses.

Genomic and transcriptome profiling

Genomic profiling of the tumor specimens was performed using whole-genome tiling 38K array-comparative genomic hybridization microarrays, as previously described.[23, 24] Data preprocessing, normalization and data analysis were performed as previously described using log2 ratio thresholds set at +0.2, ⩾+0.5, −0.2 and ⩽−1.0 for low-level gain, high-level gain/amplification, heterozygous loss and homozygous deletion (henceforth referred to as gain, amplification, loss and deletion), respectively.[24] Total RNA samples from 150/229 tumor specimens were isolated and profiled using Illumina HumanHT-12 Beadchips (Illumina Inc.) as previously described.[24] Enriched gene ontology terms associated with differentially regulated genes were set to P<0.05, analyzed further using the gene ontology database (http://www.geneontology.org). The dataset was stratified into the molecular breast cancer subtypes using the five centroids (normal-like, basal-like, luminal subtype A, luminal subtype B and human epidermal growth factor receptor 2/estrogen receptor-negative (HER2/ER−)) and genomic grade index (high, low), as previously described.[52, 53, 54] Luminal subtype B was further stratified according HER2 status as determined by array-comparative genomic hybridization; HER2+ was set to log2 ratio ⩾+0.5 and HER2− was set to log2 ratio <+0.5.[55] Univariate Cox proportional hazard models were calculated for statistically significant genes using overall survival.

Fluorescence in situ hybridization

Probe labeling and hybridization were performed as described elsewhere[56] using locus-specific bacterial artificial chromosome (BAC; BACPAC Resources, Oakland, CA, USA) probes to verify gene amplification. Dual-color fluorescence in situ hybridization was performed on touchprint and metaphase preparations using cohybridized biotin-16-deoxyuridine triphosphate (dUTP) and dioxigenin-11-dUTP-labeled probes. Analysis was performed using a Leica DMRA2 fluorescent microscope (Leica, Wetzler, Germany) equipped with an ORCA Hamamatsu CCD (charged-couple devices) camera (Hamamatsu City, Japan) and filter cubes specific for fluorescein isothiocyanate, Rhodamine and ultraviolet for DAPI visualization. Digitalized black and white images were acquired using the Leica CW4000 software package (Leica).

DNA methylation profiling

In total, 22/229 tumor samples harboring (n=11) or lacking the 8p11-p12 amplicon (n=11) were profiled using Illumina Infinium Human Methylation 450 Beadchips (Illumina Inc) according to the manufacturer's instructions. The estimated methylation level for specific cytosine sites (average beta) was calculated as a ratio between the intensities of methylated and unmethylated alleles and ranged from 0 (null methylated) to 1 (completely methylated). Delta beta values were calculated using (average beta values8p11–p12-amplified tumors–average beta values8p11-p12 nonamplified tumors). Cytosine sites located on the Y chromosome or containing single-nucleotide polymorphisms were removed. Differential DNA methylation was determined using the IMA package in R/Bioconductor (Bioconductor, FHCRC, Seattle, WA, USA) with thresholds set at: ⩾±0.14 delta beta value and Bonferroni adjusted at P<0.05.[57]
  57 in total

1.  High-resolution genomic profiling to predict 10-year overall survival in node-negative breast cancer.

Authors:  Elin Möllerström; Ulla Delle; Anna Danielsson; Toshima Parris; Björn Olsson; Per Karlsson; Khalil Helou
Journal:  Cancer Genet Cytogenet       Date:  2010-04-15

Review 2.  Structural bioinformatics of the general transcription factor TFIID.

Authors:  Maja Malkowska; Katarzyna Kokoszynska; Leszek Rychlewski; Lucjan Wyrwicz
Journal:  Biochimie       Date:  2012-11-09       Impact factor: 4.079

Review 3.  Aberrant DNA methylation as a cancer-inducing mechanism.

Authors:  Manel Esteller
Journal:  Annu Rev Pharmacol Toxicol       Date:  2005       Impact factor: 13.820

4.  FGFRI and PLAT genes and DNA amplification at 8p12 in breast and ovarian cancers.

Authors:  C Theillet; J Adelaide; G Louason; F Bonnet-Dorion; J Jacquemier; J Adnane; M Longy; D Katsaros; P Sismondi; P Gaudray
Journal:  Genes Chromosomes Cancer       Date:  1993-08       Impact factor: 5.006

Review 5.  Epigenetics and cancer.

Authors:  Anders H Lund; Maarten van Lohuizen
Journal:  Genes Dev       Date:  2004-10-01       Impact factor: 11.361

6.  Invasive micropapillary carcinoma of the breast is associated with chromosome 8 abnormalities detected by comparative genomic hybridization.

Authors:  Ann D Thor; Clarence Eng; Sandy Devries; Michael Paterakos; William G Watkin; Susan Edgerton; Dan H Moore; Joan Etzell; Frederic M Waldman
Journal:  Hum Pathol       Date:  2002-06       Impact factor: 3.466

7.  ZNF703 gene amplification at 8p12 specifies luminal B breast cancer.

Authors:  Fabrice Sircoulomb; Nathalie Nicolas; Anthony Ferrari; Pascal Finetti; Ismahane Bekhouche; Estelle Rousselet; Aurélie Lonigro; José Adélaïde; Emilie Baudelet; Séverine Esteyriès; Julien Wicinski; Stéphane Audebert; Emmanuelle Charafe-Jauffret; Jocelyne Jacquemier; Marc Lopez; Jean-Paul Borg; Christos Sotiriou; Cornel Popovici; François Bertucci; Daniel Birnbaum; Max Chaffanet; Christophe Ginestier
Journal:  EMBO Mol Med       Date:  2011-02-15       Impact factor: 12.137

Review 8.  Epigenetics in breast cancer: what's new?

Authors:  Yi Huang; Shweta Nayak; Rachel Jankowitz; Nancy E Davidson; Steffi Oesterreich
Journal:  Breast Cancer Res       Date:  2011-11-01       Impact factor: 6.466

9.  Investigational drug MLN0128, a novel TORC1/2 inhibitor, demonstrates potent oral antitumor activity in human breast cancer xenograft models.

Authors:  Yesim Gökmen-Polar; Yi Liu; Rachel A Toroni; Kerry L Sanders; Rutika Mehta; Sunil Badve; Christian Rommel; George W Sledge
Journal:  Breast Cancer Res Treat       Date:  2012-10-21       Impact factor: 4.624

10.  Aberrant NDRG1 methylation associated with its decreased expression and clinicopathological significance in breast cancer.

Authors:  Lin-Lin Han; Lin Hou; Ming-Jin Zhou; Zhong-liang Ma; Dong-Liang Lin; Li Wu; Yin-lin Ge
Journal:  J Biomed Sci       Date:  2013-07-30       Impact factor: 8.410

View more
  29 in total

Review 1.  Lipids and cancer: Emerging roles in pathogenesis, diagnosis and therapeutic intervention.

Authors:  Lisa M Butler; Ylenia Perone; Jonas Dehairs; Leslie E Lupien; Vincent de Laat; Ali Talebi; Massimo Loda; William B Kinlaw; Johannes V Swinnen
Journal:  Adv Drug Deliv Rev       Date:  2020-07-23       Impact factor: 15.470

2.  High-Resolution Bisulfite-Sequencing of Peripheral Blood DNA Methylation in Early-Onset and Familial Risk Breast Cancer Patients.

Authors:  Justin Chen; Maria K Haanpää; Joshua J Gruber; Natalie Jäger; James M Ford; Michael P Snyder
Journal:  Clin Cancer Res       Date:  2019-06-07       Impact factor: 12.531

3.  Squalene epoxidase (SQLE) promotes the growth and migration of the hepatocellular carcinoma cells.

Authors:  Zhenghui Sui; Jiahua Zhou; Zhangjun Cheng; Penhua Lu
Journal:  Tumour Biol       Date:  2015-03-19

4.  TRPS1 gene alterations in human subependymoma.

Authors:  Sascha B Fischer; Michelle Attenhofer; Sakir H Gultekin; Donald A Ross; Karl Heinimann
Journal:  J Neurooncol       Date:  2017-05-20       Impact factor: 4.130

Review 5.  Sulfation pathways from red to green.

Authors:  Süleyman Günal; Rebecca Hardman; Stanislav Kopriva; Jonathan Wolf Mueller
Journal:  J Biol Chem       Date:  2019-07-02       Impact factor: 5.157

6.  Missing-in-Metastasis regulates cell motility and invasion via PTPδ-mediated changes in SRC activity.

Authors:  Fauzia Chaudhary; Robert Lucito; Nicholas K Tonks
Journal:  Biochem J       Date:  2015-01-01       Impact factor: 3.857

Review 7.  Cholesterol Metabolic Reprogramming in Cancer and Its Pharmacological Modulation as Therapeutic Strategy.

Authors:  Isabella Giacomini; Federico Gianfanti; Maria Andrea Desbats; Genny Orso; Massimiliano Berretta; Tommaso Prayer-Galetti; Eugenio Ragazzi; Veronica Cocetta
Journal:  Front Oncol       Date:  2021-05-24       Impact factor: 6.244

8.  Progression risk assessments of individual non-invasive gastric neoplasms by genomic copy-number profile and mucin phenotype.

Authors:  Diem Thi-Ngoc Vo; Takahisa Nakayama; Hiroto Yamamoto; Ken-ichi Mukaisho; Takanori Hattori; Hiroyuki Sugihara
Journal:  BMC Med Genomics       Date:  2015-02-18       Impact factor: 3.063

9.  Cholesterol biosynthesis pathway as a novel mechanism of resistance to estrogen deprivation in estrogen receptor-positive breast cancer.

Authors:  Nikiana Simigdala; Qiong Gao; Sunil Pancholi; Hanne Roberg-Larsen; Marketa Zvelebil; Ricardo Ribas; Elizabeth Folkerd; Andrew Thompson; Amandeep Bhamra; Mitch Dowsett; Lesley-Ann Martin
Journal:  Breast Cancer Res       Date:  2016-06-01       Impact factor: 6.466

10.  Squalene epoxidase is a bona fide oncogene by amplification with clinical relevance in breast cancer.

Authors:  David N Brown; Irene Caffa; Gabriella Cirmena; Daniela Piras; Anna Garuti; Maurizio Gallo; Saverio Alberti; Alessio Nencioni; Alberto Ballestrero; Gabriele Zoppoli
Journal:  Sci Rep       Date:  2016-01-18       Impact factor: 4.379

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.