Purpose: To gain insight into genomic and trancriptomic subtypes of ductal carcinomas in situ of the breast (DCIS).

Experimental Design: We did a combined phenotypic and genomic analysis of a series of 57 DCIS integrated with gene expression profile analysis for 26 of the 57 cases.

Results: Thirty-two DCIS exhibited a luminal phenotype; 21 were ERBB2 positive, and 4 were ERBB2/estrogen receptor (ER) negative with 1 harboring a bona fide basal-like phenotype. Based on a CGH analysis, genomic types were identified in this series of DCIS with the 1q gain/16q loss combination observed in 3 luminal DCIS, the mixed amplifier pattern including all ERBB2, 12 luminal and 2 ERBB2-/ER- DCIS, and the complex copy number alteration profile encompassing 14 luminal and 1 ERBB2-/ER- DCIS. Eight cases (8 of 57; 14%) presented a TP53 mutation, all being amplifiers. Unsupervised analysis of gene expression profiles of 26 of the 57 DCIS showed that luminal and ERBB2-amplified, ER-negative cases clustered separately. We further investigated the effect of high and low copy number changes on gene expression. Strikingly, amplicons but also low copy number changes especially on 1q, 8q, and 16q in DCIS regulated the expression of a subset of genes in a very similar way to that recently described in invasive ductal carcinomas.

Conclusions: These combined approaches show that the molecular heterogeneity of breast ductal carcinomas exists already in in situ lesions and further indicate that DCIS and invasive ductal carcinomas share genomic alterations with a similar effect on gene expression profile.

Ductal carcinoma in situ (DCIS) represents 15% to 20% of all newly diagnosed cases of breast cancer, and its incidence is increasing as a result of mammography screening (1).

DCIS correspond to a proliferation of malignant epithelial cells that spare the basal membrane with no stromal invasion. They can be classified into three categories (low-, intermediate-, and high-grade) according to nuclear grade, differentiation, and presence of central necrosis (2). However, this classification of DCIS is poorly reproducible among pathologists (3). Molecular studies, still based on a limited number of cases, have revealed some characteristics of high-grade DCIS, including the high frequency of ERBB2 overexpression, TP53 mutations, chromosomal 8p loss, and 1q gain (49). In contrast, positive estrogen receptors (ER), BCL2 expression, and 16q loss have been reported to characterize low-grade DCIS (1012).

Treatment, regardless of DCIS nuclear grade, is based on mastectomy or lumpectomy in combination with radiotherapy (1, 13). Factors known to be associated with a higher risk of recurrence are young age, positive margins, necrosis, and high nuclear grade (14, 15). Some emerging data suggest that ERBB2-amplified DCIS could present a higher risk of recurrence (16, 17).

Recent gene expression profiling studies have reported that consistent differences in expression of a subset of genes can be identified between low-grade and high-grade DCIS (1820). Interestingly, in situ lesions preferentially cluster with invasive lesions of the same grade, suggesting that DCIS are precursors of their similar grade invasive counterpart (20). In support of this hypothesis, DCIS and invasive components of the same tumors exhibit similar patterns of genetic alterations (4, 7).

Gene expression profile analysis classified invasive breast carcinomas into five groups: luminal A or B, basal like, ERBB2, and normal like carcinomas (21, 22). These analyses have led to the identification of specific immunophenotypic markers, which allow this classification to be used in clinical practice (23, 24). It is well-recognized that ERBB2 is up-regulated more frequently in DCIS than in invasive carcinomas (6). The identification of a basal-like entity is emerging with four recent studies describing DCIS lesions with this phenotype (18, 2527). It nevertheless remains to be determined whether basal-like DCIS show specific genomic/transcriptomic alterations.

Genomic profiles also provide criteria for a clinically relevant classification, as combined genomic and gene expression studies in invasive cancers have highlighted the prognostic effect of high level amplifications associated with gene overexpression at chromosome regions 8p12, 11q13, 17q12, and 20q13 independently of the previously described major gene expression classes. These cases are defined as amplifiers. Among nonamplifiers, one group with a good prognosis harbors few genetic alterations but recurrent 16q loss associated with 1q gain (1q/16q). Another group, which includes most of basal-like but also a subset of luminal cases, is characterized by numerous low-level copy number alterations (CNA; refs. 28, 29). In invasive breast cancer, this integrated genomic approach, based on genomic and transcriptomic data, is very promising to achieve better clinical management of patients.

In the present study, we analyzed the immunophenotype, the array CGH profiles, the TP53 gene sequence, and the gene expression profile of DCIS frozen samples. We identified DCIS subtypes according to the molecular classification described for invasive ductal carcinomas (IDC), allowing comparison of the genomic, transcriptomic, and phenotypic profiles of ERBB2, luminal, and basal-like DCIS. Finally, correlations of genomic and transcriptomic data were used to identify candidate genes, the altered expression of which may play a critical role in early breast carcinogenesis via copy number changes.

Selection of tumor samples. Fifty-seven DCIS of the breast were retrospectively selected from our tumor bank based on the availability of a frozen sample. Samples were collected on fresh surgical specimens by a pathologist within 1 hour after surgery from patients who underwent lumpectomy (n = 21) or mastectomy (n = 36), flash frozen in liquid nitrogen, and stored at −80°C. Experiments were done in agreement with the French Bioethics Law 2004-800 and the Ethics Charter from the French National Institute of Cancer. All samples were reviewed for histologic classification according to nuclear grade and classified as low, intermediate, and high nuclear grade (Table 1; ref. 2).

Table 1.

Pathologic characteristics and immunophenotype of the 57 DCIS

VariablesAll DCIS
ERBB2
Luminal A
ERBB2/ER
n = 57* (%)n = 21* (%)n = 32 (%)n = 4 (%)
Nuclear grade     
High 29 (51) 17 (81) 9 (28) 3 (75) 
Nonhigh 28 (49) 4 (19) 23 (72) 1 (25) 
Necrosis     
≥10% 36 (63) 18 (86) 16 (50) 2 (50) 
<10% 21 (37) 3 (14) 16 (50) 2 (50) 
ER     
34 (60) 2 (10) 32 (100) 
− 22 (40) 18 (90) 4 (100) 
PR     
29 (52) 2 (10) 26 (81) 1 (25) 
27 (48) 18 (90) 6 (19) 3 (75) 
ERBB2 (IHC)     
20 (36) 20 (100) 0 (0) 
− 36 (64) 32 (100) 4 (100) 
KRT8/18     
>50% 50 (89) 18 (90) 31 (97) 1 (25) 
≤50% 6 (11) 2 (10) 1 (3) 3 (75) 
KRT5/6     
≥5% 15 (27) 5 (25) 9 (28) 1 (25) 
<5% 41 (73) 15 (75) 23 (72) 3 (75) 
EGFR     
≥5% 6 (11) 3 (15) 2 (6) 1 (25) 
<5% 50 (89) 17 (85) 30 (94) 3 (75) 
VariablesAll DCIS
ERBB2
Luminal A
ERBB2/ER
n = 57* (%)n = 21* (%)n = 32 (%)n = 4 (%)
Nuclear grade     
High 29 (51) 17 (81) 9 (28) 3 (75) 
Nonhigh 28 (49) 4 (19) 23 (72) 1 (25) 
Necrosis     
≥10% 36 (63) 18 (86) 16 (50) 2 (50) 
<10% 21 (37) 3 (14) 16 (50) 2 (50) 
ER     
34 (60) 2 (10) 32 (100) 
− 22 (40) 18 (90) 4 (100) 
PR     
29 (52) 2 (10) 26 (81) 1 (25) 
27 (48) 18 (90) 6 (19) 3 (75) 
ERBB2 (IHC)     
20 (36) 20 (100) 0 (0) 
− 36 (64) 32 (100) 4 (100) 
KRT8/18     
>50% 50 (89) 18 (90) 31 (97) 1 (25) 
≤50% 6 (11) 2 (10) 1 (3) 3 (75) 
KRT5/6     
≥5% 15 (27) 5 (25) 9 (28) 1 (25) 
<5% 41 (73) 15 (75) 23 (72) 3 (75) 
EGFR     
≥5% 6 (11) 3 (15) 2 (6) 1 (25) 
<5% 50 (89) 17 (85) 30 (94) 3 (75) 

NOTE: Cases were considered positive for ER and PR using ≥10% of positive nuclei per carcinomatous duct and for ERBB2 with a cutoff of >60% of positive cells.

Abbreviations: EGFR, epidermal growth factor receptor; KRT, cytokeratin.

*

No fixed paraffin-embedded tissue sample was available for one case and immunophenotype was not assessed.

Nonhigh-grade tumors corresponded to 4 low-grade and 24 intermediate-grade DCIS.

IHC, ERBB2 status determined by immunohistochemistry.

DNA and RNA extractions. All tumor samples contained >50% of cancer cells, as assessed by H&E staining of histologic sections of the samples used for nucleic acid extraction. In this work, to avoid potential artifacts, which may due to DNA or RNA amplification of microdissected samples, we privileged the investigation of samples large enough to extract good quality nucleic acids without need for preamplification steps. DNA and RNA extractions were done using standard procedures as previously described (30). RNA quality control was checked on Agilent 2100 biolanalyzer (Agilent Technologies). Good quality RNA was obtained in a subset of 26 cases among these 57 cases.

Immunohistochemistry. Immunostaining was done according to previously published protocols (31). The expression of ER (clone 6F11; 1/200; Novocastra), progesterone receptor (PR; clone 1A6; 1/200; Novocastra), ERBB2 (clone CB11; 1/1,000; Novocastra), epidermal growth factor receptor (HER1; clone 31G7; 1/40; Zymed; Clinisciences), cytokeratin 5/6 (clone D5/16B4; 1/50; Dako), and cytokeratin 8/18 (clone DC10; 1/100; Zymed; Clinisciences) were evaluated. For each antibody, internal and external controls were included in the experiments.

TP53 sequencing. Exons 4 to 10 of TP53 were PCR amplified and bidirectionally sequenced using Big Dye Terminator chemistry (Applied Biosystems) with an ABI PRISM 3700 DNA Analyzer (primer sequences previously published in ref. 32).

Array CGH. The 3.5K BAC array together with experimental procedures used for hybridization and washing were as previously published (32). All BAC and PAC were verified by end sequencing before spotting.

Analysis of array CGH data. Data analysis was based on the normalized ratios of Cy5/Cy3 signals observed for each BAC clone that previously passed the flag assessment procedure (32, 33). For autosomal chromosomes, the status of each BAC locus was defined according to the VAMP (Vizualization and Analysis of Molecular Profiles) analysis procedure (34) using the GLAD (Gain and Loss Analysis of DNA) algorithm that, based on the Adaptive Weights Smoothing procedure, can be used to assign a status (gained, lost, or normal) to each chromosome region (33).

Regions of gain or loss and amplicons were defined as previously published (32). BACs known to harbor copy number variation in public databases (Database of Genomic variants)8

or identified in the laboratory by array CGH experiments using normal/normal DNAs hybridizations were excluded from the analysis.

Gene expression profile analysis. The DNA microarrays used in this study were the Human Genome U133 Set (HG-U133; Affymetrix), consisting of one GeneChip array (A) and containing almost 20,000 probe sets. Microarray data were simultaneously normalized using the GCRMA package version 1.1.4 in the R environment (R Development Core Team). Unsupervised hierarchical clustering of the tumor sample was done using the dChip software (35) with standard Pearson correlation as similarity measure and centroid as linkage criteria. Clustering was done on a subset of probe sets with an interquartile range of >2. Each probe set was preliminary standardized with respect to mean and SD. The comparison of mean gene expression between ERBB2-amplified and luminal DCIS was done using SAM (36) and Welch t tests. FDR for Welch t test was adjusted using the Benjamini-Hochberg corrections. Finally, for each probe set, the correlation with Cy5 to Cy3 ratios of the corresponding BAC clone was calculated using Pearson and Spearman correlation tests (for details see Supplementary Data 1).

Patient and tumor characteristics. Fifty-seven DCIS cases with no associated invasive component were analyzed. The median age of patients was 52.5 years (range, 30-79 years). All patients were treated according to established protocols: mastectomy (36 patients) or conservative surgery followed by radiation therapy (21 patients). The main tumor characteristics are indicated in Table 1. Twenty-nine cases (51%) were high nuclear grade, and 28 (49%) were nonhigh-grade, including 24 intermediate- and 4 low-grade tumors. For subsequent analyses, the intermediate and low nuclear grade DCIS cases were merged into a nonhigh-grade group. The immunophenotype of the 57 cases was determined to identify whether DCIS could be classified into subgroups previously identified in IDC: luminal ER-positive, ERBB2, basal-like triple-negative, and normal-like carcinomas (Table 1). Altogether, these markers were able to identify 32 luminal (ER positive) DCIS (most being nonhigh-grade group; 23 cases), 21 ERBB2 DCIS (most being ER negative; 18 ER-negative cases), and 17 of 21 being high nuclear grade, and finally 4 cases were ER and ERBB2 negative. Only one of these four ERBB2-negative/ER-negative DCIS was PR negative, expressed cytokeratin 5/6 basal cytokeratins and epidermal growth factor receptor, and could therefore be considered to be a bona fide basal-like DCIS (Fig. 1A).

Fig. 1.

Phenotypic and genomic analysis of DCIS. A, classification of the 57 DCIS according to the molecular subtypes previously identified for invasive breast carcinomas and their genomic status. *, three luminal DCIS and one ERBB2-negative, ER-negative DCIS presented a flat profile. B, examples of array CGH profiles from defined genomic status; B1, luminal with CNA; B2, luminal with 1q gain/16q loss profile; B3, luminal amplifier; B4, ERBB2 amplified; B5, triple-negative, basal-like amplifier with numerous CNA. C and D, frequencies of genome copy number gains and losses plotted as a function of genome location (C, luminal DCIS; D, ERBB2-amplified DCIS). Orange, gains; green, losses. From chromosome 1pter on the left to chromosome Xq on the right. Vertical lines, chromosome boundaries; vertical hemi-dashed lines, centromere locations. The BAC clones exhibiting significantly more frequent gains (red) or losses (green) between luminal (C) and ERBB2-amplified DCIS (D) are displayed underneath each frequency plot.

Fig. 1.

Phenotypic and genomic analysis of DCIS. A, classification of the 57 DCIS according to the molecular subtypes previously identified for invasive breast carcinomas and their genomic status. *, three luminal DCIS and one ERBB2-negative, ER-negative DCIS presented a flat profile. B, examples of array CGH profiles from defined genomic status; B1, luminal with CNA; B2, luminal with 1q gain/16q loss profile; B3, luminal amplifier; B4, ERBB2 amplified; B5, triple-negative, basal-like amplifier with numerous CNA. C and D, frequencies of genome copy number gains and losses plotted as a function of genome location (C, luminal DCIS; D, ERBB2-amplified DCIS). Orange, gains; green, losses. From chromosome 1pter on the left to chromosome Xq on the right. Vertical lines, chromosome boundaries; vertical hemi-dashed lines, centromere locations. The BAC clones exhibiting significantly more frequent gains (red) or losses (green) between luminal (C) and ERBB2-amplified DCIS (D) are displayed underneath each frequency plot.

Close modal

Genomic analysis. We then investigated the TP53 status and genomic profiles of these 57 DCIS lesions and their relationship with the three main phenotypic classes identified above. All samples were frozen DCIS lesions and comprised at least 50% of tumor cells. TP53 mutations were detected by direct sequencing of exons 4 to 11. Mutations were found in eight cases (14%) and corresponded to two frameshift, two splice site, two missense, and two stop mutations. These mutations were located in exon 5 (three cases); exon 6 (two cases); and exons 7, 8, and 9 (one case each). They occurred more frequently in high-grade DCIS (7 of 29; 24%) than in nonhigh-grade DCIS (1 of 28; 4%; P = 0.051) and significantly more frequently in ERBB2 (6 of 17; 35%) than in luminal and ERBB2-/ER- DCIS (2 of 36; 6%; P = 0.0047).

CNA (amplicons, gains, and losses) were identified using a one-megabase resolution BAC array. All samples but four exhibited altered profiles, indicating that the amount of stromal or other normal cells in the samples was not sufficient to mask copy number changes. Fifty-nine different amplicons were observed in the 57 DCIS (Supplementary Data 2). Fourteen amplicons were recurrent (observed in at least two tumors), including ERBB2 on chromosome 17q12, Cyclin D1 at 11q13, FGFR1 at 8p12, BMP7/BCAS1 at 20q13, but also five 17q amplicons distinct from ERBB2. Interestingly, the chromosomal localization of amplicons (distinct from ERBB2) differed between the ERBB2-amplified and the luminal DCIS groups, as half of the amplicons (13 of 26) of the ERBB2 group associated with ERBB2 were also localized on chromosome 17q, but only 5 of 29 amplicons of the luminal group were localized on this chromosome arm (P = 2.10−2).

The ERBB2 amplicon size differed from one tumor to another, ranging from 32.9 106 bp to 35.6 106 bp with a minimal common region of amplification located between 34.9 106 bp and 35.2 106 bp centered on the ERBB2 gene sequence but also containing other genes including STARD3, GRB7, and PERLD1.

Regions of gains and losses observed with a frequency of >20% in the luminal and ERBB2-amplified groups were identified. Common regions of gain were observed in both groups (Fig. 1C and D). They were located on chromosomes 1p, 1q, 5p, 7p, 7q, 8q, 14q, 16p, 19p, 19q, 17q, and 20q. Only one common and recurrent region of loss on 11q was identified. The ERBB2-amplified group presented specific regions of 3p, 4p, 4q, and 8p losses and 17q gains compared with the luminal group that presented specific regions of gains on 1q, 8p, and 17q and losses on 16q (Supplementary Data 3).

According to the criteria recently proposed by Fridlyand and Chin in 2006 (28, 29), DCIS cases could be classified into three categories: tumors characterized by the presence of amplicons (mixed amplifiers), tumors characterized by 1q gain and 16q loss (1q/16q group), and tumors with complex CNA. ERBB2-amplified DCIS never showed 16q loss. The luminal group exhibited genetic complexity with 12 cases classified as amplifiers, 3 cases harboring a 1q/16q profile, 14 cases exhibiting a complex pattern of CNA, and 3 cases characterized by a flat profile. Within the ERBB2-/ER-negative DCIS group, two belonged to the amplifier category with amplicons located on chromosomes 5p, 8p, and 22q, one harbored CNA and one case was charade rised by a flat profile (Fig. 1A and B).

Gene expression analysis. We also investigated transcriptomic differences between ERBB2-amplified and luminal DCIS. A subset of 26 cases for which good quality RNAs were available, including 9 ERBB2-amplified and 17 luminal DCIS, were analyzed on Affymetrix U133A. A total of 502 genes exhibited an interquartile range of >2 (Supplementary Data 4). These genes discriminated two major clusters of tumors mainly organized according to ERBB2 and hormonal receptor status rather than nuclear grade. One branch included most (8 of 9) ERBB2-amplified, ER-negative cases, and the other branch comprised all (17 of 17) luminal cases and one ERBB2-amplified, ER-negative/PR-positive case. As shown in Fig. 2, genes coamplified with ERBB2 (GRB7, PERLD1, and STARD3) and genes of the ER pathway (ESR1, GATA3, STC2, LIV1, IGF1R…) were major contributors of this clustering. The most discriminant genes between ERBB2-amplified and luminal DCIS (Welch and Sam tests results, P < 0.01) are indicated in Supplementary Data 5. Unsupervised and supervised analyses showed that genes involved in estrogens receptor pathways, extracellular matrix remodeling (syndecan, ezrin, …), immune response (TRBV19, …), antiapoptotic pathways, cell adhesion (CXCR4, syndecan, and ITGB6), or fatty acid metabolism (LDRL) were differentially expressed between the ERBB2-amplified and luminal groups (Fig. 2). Finally, genes encoding important signal transduction and transcription factors molecules were differentially expressed. FGFR2, RET, KIF5, and IGF1R were overexpressed in luminal cases, whereas ERBB2, GRB7, PTPRC were overexpressed in ERBB2-amplified cases.

Fig. 2.

Unsupervised hierarchical clustering of 26 DCIS tumors using intrinsically variable gene expression of 502 genes (interquartile range, >2). Each row represents a different tumor, and each column represents one of 502 genes used for this unsupervised clustering (orange, ERBB2 amplified; yellow, ERBB2 not amplified), indicating the genomic type (red, amplifiers; gray, CNA; green, 1q/16q; white flat profile). Cyan, ER or PR positive; dark blue, ER and PR. NG, nuclear grade; black, high-grade; gray, nonhigh-grade. The genes are divided into two main clusters. The first cluster (1) contains genes involved in fatty acid metabolism, extracellular matrix, and the ERBB2 amplicon. The second cluster (2) includes genes involved in apoptosis and ER signaling.

Fig. 2.

Unsupervised hierarchical clustering of 26 DCIS tumors using intrinsically variable gene expression of 502 genes (interquartile range, >2). Each row represents a different tumor, and each column represents one of 502 genes used for this unsupervised clustering (orange, ERBB2 amplified; yellow, ERBB2 not amplified), indicating the genomic type (red, amplifiers; gray, CNA; green, 1q/16q; white flat profile). Cyan, ER or PR positive; dark blue, ER and PR. NG, nuclear grade; black, high-grade; gray, nonhigh-grade. The genes are divided into two main clusters. The first cluster (1) contains genes involved in fatty acid metabolism, extracellular matrix, and the ERBB2 amplicon. The second cluster (2) includes genes involved in apoptosis and ER signaling.

Close modal

Interestingly, displaying genomic characteristics of tumors on the unsupervised cluster revealed that among the two branches of the luminal cluster, one was enriched in amplifiers distinct from the ERBB2 amplicon; the second was enriched in CNA (Fig. 2).

Genomic and transcriptomic correlations. Given the strong relationship between the genomic classification and the unsupervised clustering of gene expression profiles and to determine the effect of genomic changes on gene expression levels, we combined the analyses of the Affymetrix signals and array CGH ratios for the 26 DCIS analyzed with both approaches. Using the Pearson and Spearman correlation tests, we observed that the expression level of 416 genes was significantly correlated with the ratio of their corresponding BAC locus (372 BAC clones; Fig. 3). Correlations corresponding to amplicon were mostly located on 17q and corresponding to either the variable extent of the ERBB2 amplicon from one tumor to another or to other 17q amplicons, distinct from but co-occurring with ERBB2 (Supplementary Data 2). Other correlations due to amplicons mainly involved 8p (from 37 to 40 Mb), 11p12-p13 (from 34 to 36 Mb), 11q13 (from 69 to 78 Mb), and 20q13.32 (from 46 to 55 Mb; Supplementary Data 6). The main correlations due to low copy gains or losses were observed on chromosomes 1q, 8q, and 16q (Table 2; Supplementary Data 6). The analysis of genome expression correlations indicates that the amount of stromal or other normal cells in the samples was not sufficient to hamper the detection of a strong copy number effect upon gene expression.

Fig. 3.

Chromosomal localization of the most significant genome transcriptome correlations. The results of significant correlations according to Spearman and Pearson between probe sets and BAC loci are plotted as a function of genome location from chromosome 1pter to chromosome Xq.

Fig. 3.

Chromosomal localization of the most significant genome transcriptome correlations. The results of significant correlations according to Spearman and Pearson between probe sets and BAC loci are plotted as a function of genome location from chromosome 1pter to chromosome Xq.

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Table 2.

Genes showing significant expression copy number correlations and localized within regions discriminating ERBB2 and luminal DCIS

ChrCytobandStartlocusEndlocusGeneIDCorrelation coefficientCorrelation in IDC
q21.1 144150231 144356105 POLR3C 0.64 
q21.1 144150231 144356105 PEX11B 0.63 
q21.3 150870525 152158474 INTS3 0.68  
q21.3 149888549 150060705 MRPL9 0.7 
q23.1 154888337 155047911 MRPL24 0.76 
q23.1 154888337 155047911 ISG20L2 0.63 
q23.2 158452438 158743347 COPA 0.73 
q23.2 158452438 158743347 NCSTN 0.66 
q23.3 159044725 159381234 DEDD 0.75 
q23.3 159514689 160713118 DUSP12 0.68 
q23.3 159044725 159381234 PFDN2 0.66 
q23.3 159381234 159514689 PPOX 0.76 
q23.3 159381234 159514689 USP21 0.71 
q23.3 159381234 159514689 B4GALT3 0.7 
q23.3 159381234 159514689 NDUFS2 0.7 
q24.1 165426500 165600956 POU2F1 0.62  
q24.3 169943186 170838266 PIGC 0.77 
q24.3 169943186 170838266 KIAA0859 0.71 
q25.1 173402605 173547236 KIAA0040 0.63 
q25.1 173189878 173350442 CACYBP 0.62 
q25.3 180754428 181784986 LAMC2 0.74  
q25.3 179011386 180565371 STX6 0.72 
q32.1 204138581 204930767 IKBKE 0.82  
q32.1 203342491 203495694 RIPK5 0.75  
q32.1 202027575 202349129 ZC3H11A 0.76  
q32.1 205087762 205277242 C1orf116 0.67  
q32.1 203164295 203342491 RBBP5 0.75  
q32.1 203963475 204138581 NUCKS1 0.71  
q32.1 205277242 205431667 PFKFB2 0.67  
q32.3 210152024 210772193 NENF 0.64 
q41 219896304 221353763 MIA3 0.69  
q42.11 221568617 223326349 NVL 0.74 
q42.11 221568617 223326349 WDR26 0.74 
q42.13 227197070 228112708 NUP133 0.72 
q42.2 228271115 229195892 COG2 0.68  
q42.3 232853266 233928437 RBM34 0.71  
q42.3 232853266 233928437 TOMM20 0.72  
q42.3 232853266 233928437 ARID4B 0.65  
q43 234794031 243579104 HEATR1 0.83 
p23.1 8827798 9852904 TNKS 0.82 
p22 15734104 17364572 CNOT7 0.84  
p21.3 22230663 22882560 BIN3 0.78 
p21.2 24851358 26612249 PPP2R2A 0.81 
p21.2 24851358 26612249 BNIP3L 0.68 
p21.1 28844096 29353654 KIF13B 0.69  
p12 36836067 38260917 GPR124 0.87  
p12 36836067 38260917 ASH2L 0.81 
p12 36836067 38260917 BRF2 0.8 
p12 36836067 38260917 LSM1 0.8 
p12 36836067 38260917 BAG4 0.79 
p12 36836067 38260917 DDHD2 0.75 
p12 29507083 31056165 DCTN6 0.77  
p12 36836067 38260917 PROSC 0.69 
p12 29507083 31056165 PPP2CB 0.64  
p12 38335306 38425958 WHSC1L1 0.95 
p12 38335306 38425958 FGFR1 0.92 
p11.23 38497241 40010617 ADAM3A 0.79  
p11.21 40185770 41825747 GINS4 0.79  
p11.21 40185770 41825747 GOLGA7 0.73  
p11.21 42044320 42283104 AP3M2 0.67 
p11.21 42850482 43166289 FNTA 0.82 
p11.21 42287374 42449080 VDAC3 0.78 
p11.21 41825747 42044313 MYST3 0.77 
q11.23 55029042 55683872 TCEA1 0.75 
q11.23 54844920 55029042 ATP6V1H 0.73 
q12.1 58525613 59889959 LOC137886 0.74  
q12.1 61401378 61814156 RAB2A 0.66  
q21.11 74891351 76034750 TCEB1 0.67  
q21.13 81648505 82728066 PMP2 0.67  
q22.1 97062467 98198501 MTERFD1 0.81 
q22.1 97062467 98198501 UQCRB 0.82 
q22.1 97062467 98198501 PTDSS1 0.66 
q22.1 95496349 95679222 RAD54B 0.77 
q22.1 98198501 98375057 PGCP 0.74  
q22.2 98375057 99735538 HRSP12 0.74 
q22.2 100848701 102004873 POLR2K 0.74 
q22.2 100738763 100848701 VPS13B 0.7  
q22.3 103891151 104422933 ATP6V1C1 0.85 
q22.3 103891151 104422933 AZIN1 0.7 
q22.3 100848701 102004873 ANKRD46 0.7  
q22.3 102195771 103646239 ZNF706 0.84  
q23.2 110623681 110825964 EBAG9 0.76 
q24.11 117853649 118046959 RAD21 0.67 
q24.12 120401806 121248223 TAF2 0.73 
q24.13 124908744 126133308 TRMT12 0.84 
q24.13 124908744 126133308 RNF139 0.76 
q24.13 123977707 124708761 DERL1 0.77 
q24.13 124908744 126133308 SQLE 0.64 
q24.13 123977707 124708761 C8orf32 0.65 
q24.13 126133308 126334773 NSMCE2 0.74  
q24.22 131964334 133156759 KIAA0143 0.8 
q24.3 143909082 145536611 SIAHBP1 0.85 
q24.3 140031123 141603135 NIBP 0.83  
q24.3 143909082 145536611 EXOSC4 0.82 
q24.3 143909082 145536611 CYC1 0.8 
q24.3 143909082 145536611 GPAA1 0.73 
q24.3 143909082 145536611 SHARPIN 0.72  
q24.3 146133391  C8orf33 0.72 
q24.3 143909082 145536611 PYCRL 0.72 
q24.3 143909082 145536611 GRINA 0.71  
q24.3 143909082 145536611 SCRIB 0.68 
q24.3 143909082 145536611 PLEC1 0.68  
q24.3 143909082 145536611 ZNF696 0.68 
q24.3 143909082 145536611 ZC3H3 0.66 
q24.3 141603135 141808565 PTK2 0.79 
q24.3 146029133 146133391 ZNF7 0.71 
q24.3 143739886 143909082 C8orf55 0.69  
q24.3 146029133 146133391 ZNF16 0.66 
16 q12.1 46027393 46605539 PHKB 0.69 
16 q12.1 48832865 49022383 BRD7 0.74  
16 q13 56003087 56156112 COQ9 0.75  
16 q13 56003087 56156112 CIAPIN1 0.71  
16 q13 54836075 56003087 ARL2BP 0.68  
16 q21 56619483 57476831 CNOT1 0.83 
16 q21 56619483 57476831 GOT2 0.71 
16 q21 65020904 65209402 CKLF 0.64  
16 q22.1 65209402 65623027 APPBP1 0.75  
16 q22.1 65209402 65623027 FAM96B 0.65 
16 q22.1 67478745 69245806 AARS 0.72 
16 q22.1 67478745 69245806 DDX19A 0.72 
16 q22.1 67478745 69245806 SF3B3 0.72 
16 q22.1 67478745 69245806 WWP2 0.67 
16 q22.1 69245806 69419474 VAC14 0.7 
16 q22.3 69419474 71533759 KIAA0174 0.85 
16 q22.3 69419474 71533759 DHX38 0.71 
16 q22.3 71533759 74776431 PSMD7 0.8 
16 q22.3 71533759 74776431 RFWD3 0.72 
16 q23.1 71533759 74776431 KARS 0.79 
16 q23.1 71533759 74776431 ADAT1 0.73  
16 q23.1 71533759 74776431 WDR59 0.68  
16 q23.1 71533759 74776431 TERF2IP 0.64 
16 q23.2 79052806 80639519 ASCIZ 0.72 
16 q24.1 83335109 84444005 COX4NB 0.82 
16 q24.1 83335109 84444005 KIAA0182 0.71  
16 q24.1 83335109 84444005 COX4I1 0.69 
16 q24.1 83335109 84444005 ZDHHC7 0.69 
17 p13.3 2077107 3789432 ITGAE 0.8  
17 q11.2 24125209 25739938 ERAL1 0.66  
17 q11.2 24125209 25739938 FLOT2 0.75  
17 q11.2 22465093 23921490 IFT20 0.71  
17 q11.2 23991111 24125209 RPL23A 0.77  
17 q11.2 23926892 24057159 SUPT6H 0.76  
17 q11.2 27772588 27941694 PSMD11 0.76 
17 q11.2 23991111 24125209 C17orf63 0.76  
17 q11.2 23944011 24039852 SPAG5 0.75  
17 q11.2 23926892 24057159 SDF2 0.68  
17 q11.2 26430455 26574472 NF1 0.72  
17 q11.2 23991111 24125209 TRAF4 0.63  
17 q12 34434812 34987922 CRKRS 0.82  
17 q12 34434812 34987922 RPL19 0.85  
17 q12 34434812 34987922 PPARBP 0.71  
17 q12 34987922 35196413 GRB7 0.87 
17 q12 35246223 35393977 GSDML 0.87 
17 q12 34987922 35196413 PERLD1 0.86 
17 q12 34987922 35196413 STARD3 0.82 
17 q12 34987922 35196413 ERBB2 0.82 
17 q12 35246223 35393977 PSMD3 0.81 
17 q12 30384409 30599689 NLE1 0.76 
17 q12 34201212 34324738 CCDC49 0.75  
17 q12 30270215 30599689 LIG3 0.73 
17 q12 34201212 34324738 RPL23 0.71  
17 q12 34201212 34324738 PIP5K2B 0.68  
17 q12 34987922 35196413 PNMT 0.65 
17 q21.1 35465293 35659097 CASC3 0.66 
17 q21.1 35465293 35659097 THRA 0.66  
17 q21.2 35920386 37443438 SMARCE1 0.66 
17 q21.2 35682074 35839525 CDC6 0.81  
17 q21.2 35682074 35839525 WIPF2 0.75 
17 q21.2 35737736 35915957 RARA 0.71  
17 q21.2 35682074 35839525 TOP2A 0.7  
ChrCytobandStartlocusEndlocusGeneIDCorrelation coefficientCorrelation in IDC
q21.1 144150231 144356105 POLR3C 0.64 
q21.1 144150231 144356105 PEX11B 0.63 
q21.3 150870525 152158474 INTS3 0.68  
q21.3 149888549 150060705 MRPL9 0.7 
q23.1 154888337 155047911 MRPL24 0.76 
q23.1 154888337 155047911 ISG20L2 0.63 
q23.2 158452438 158743347 COPA 0.73 
q23.2 158452438 158743347 NCSTN 0.66 
q23.3 159044725 159381234 DEDD 0.75 
q23.3 159514689 160713118 DUSP12 0.68 
q23.3 159044725 159381234 PFDN2 0.66 
q23.3 159381234 159514689 PPOX 0.76 
q23.3 159381234 159514689 USP21 0.71 
q23.3 159381234 159514689 B4GALT3 0.7 
q23.3 159381234 159514689 NDUFS2 0.7 
q24.1 165426500 165600956 POU2F1 0.62  
q24.3 169943186 170838266 PIGC 0.77 
q24.3 169943186 170838266 KIAA0859 0.71 
q25.1 173402605 173547236 KIAA0040 0.63 
q25.1 173189878 173350442 CACYBP 0.62 
q25.3 180754428 181784986 LAMC2 0.74  
q25.3 179011386 180565371 STX6 0.72 
q32.1 204138581 204930767 IKBKE 0.82  
q32.1 203342491 203495694 RIPK5 0.75  
q32.1 202027575 202349129 ZC3H11A 0.76  
q32.1 205087762 205277242 C1orf116 0.67  
q32.1 203164295 203342491 RBBP5 0.75  
q32.1 203963475 204138581 NUCKS1 0.71  
q32.1 205277242 205431667 PFKFB2 0.67  
q32.3 210152024 210772193 NENF 0.64 
q41 219896304 221353763 MIA3 0.69  
q42.11 221568617 223326349 NVL 0.74 
q42.11 221568617 223326349 WDR26 0.74 
q42.13 227197070 228112708 NUP133 0.72 
q42.2 228271115 229195892 COG2 0.68  
q42.3 232853266 233928437 RBM34 0.71  
q42.3 232853266 233928437 TOMM20 0.72  
q42.3 232853266 233928437 ARID4B 0.65  
q43 234794031 243579104 HEATR1 0.83 
p23.1 8827798 9852904 TNKS 0.82 
p22 15734104 17364572 CNOT7 0.84  
p21.3 22230663 22882560 BIN3 0.78 
p21.2 24851358 26612249 PPP2R2A 0.81 
p21.2 24851358 26612249 BNIP3L 0.68 
p21.1 28844096 29353654 KIF13B 0.69  
p12 36836067 38260917 GPR124 0.87  
p12 36836067 38260917 ASH2L 0.81 
p12 36836067 38260917 BRF2 0.8 
p12 36836067 38260917 LSM1 0.8 
p12 36836067 38260917 BAG4 0.79 
p12 36836067 38260917 DDHD2 0.75 
p12 29507083 31056165 DCTN6 0.77  
p12 36836067 38260917 PROSC 0.69 
p12 29507083 31056165 PPP2CB 0.64  
p12 38335306 38425958 WHSC1L1 0.95 
p12 38335306 38425958 FGFR1 0.92 
p11.23 38497241 40010617 ADAM3A 0.79  
p11.21 40185770 41825747 GINS4 0.79  
p11.21 40185770 41825747 GOLGA7 0.73  
p11.21 42044320 42283104 AP3M2 0.67 
p11.21 42850482 43166289 FNTA 0.82 
p11.21 42287374 42449080 VDAC3 0.78 
p11.21 41825747 42044313 MYST3 0.77 
q11.23 55029042 55683872 TCEA1 0.75 
q11.23 54844920 55029042 ATP6V1H 0.73 
q12.1 58525613 59889959 LOC137886 0.74  
q12.1 61401378 61814156 RAB2A 0.66  
q21.11 74891351 76034750 TCEB1 0.67  
q21.13 81648505 82728066 PMP2 0.67  
q22.1 97062467 98198501 MTERFD1 0.81 
q22.1 97062467 98198501 UQCRB 0.82 
q22.1 97062467 98198501 PTDSS1 0.66 
q22.1 95496349 95679222 RAD54B 0.77 
q22.1 98198501 98375057 PGCP 0.74  
q22.2 98375057 99735538 HRSP12 0.74 
q22.2 100848701 102004873 POLR2K 0.74 
q22.2 100738763 100848701 VPS13B 0.7  
q22.3 103891151 104422933 ATP6V1C1 0.85 
q22.3 103891151 104422933 AZIN1 0.7 
q22.3 100848701 102004873 ANKRD46 0.7  
q22.3 102195771 103646239 ZNF706 0.84  
q23.2 110623681 110825964 EBAG9 0.76 
q24.11 117853649 118046959 RAD21 0.67 
q24.12 120401806 121248223 TAF2 0.73 
q24.13 124908744 126133308 TRMT12 0.84 
q24.13 124908744 126133308 RNF139 0.76 
q24.13 123977707 124708761 DERL1 0.77 
q24.13 124908744 126133308 SQLE 0.64 
q24.13 123977707 124708761 C8orf32 0.65 
q24.13 126133308 126334773 NSMCE2 0.74  
q24.22 131964334 133156759 KIAA0143 0.8 
q24.3 143909082 145536611 SIAHBP1 0.85 
q24.3 140031123 141603135 NIBP 0.83  
q24.3 143909082 145536611 EXOSC4 0.82 
q24.3 143909082 145536611 CYC1 0.8 
q24.3 143909082 145536611 GPAA1 0.73 
q24.3 143909082 145536611 SHARPIN 0.72  
q24.3 146133391  C8orf33 0.72 
q24.3 143909082 145536611 PYCRL 0.72 
q24.3 143909082 145536611 GRINA 0.71  
q24.3 143909082 145536611 SCRIB 0.68 
q24.3 143909082 145536611 PLEC1 0.68  
q24.3 143909082 145536611 ZNF696 0.68 
q24.3 143909082 145536611 ZC3H3 0.66 
q24.3 141603135 141808565 PTK2 0.79 
q24.3 146029133 146133391 ZNF7 0.71 
q24.3 143739886 143909082 C8orf55 0.69  
q24.3 146029133 146133391 ZNF16 0.66 
16 q12.1 46027393 46605539 PHKB 0.69 
16 q12.1 48832865 49022383 BRD7 0.74  
16 q13 56003087 56156112 COQ9 0.75  
16 q13 56003087 56156112 CIAPIN1 0.71  
16 q13 54836075 56003087 ARL2BP 0.68  
16 q21 56619483 57476831 CNOT1 0.83 
16 q21 56619483 57476831 GOT2 0.71 
16 q21 65020904 65209402 CKLF 0.64  
16 q22.1 65209402 65623027 APPBP1 0.75  
16 q22.1 65209402 65623027 FAM96B 0.65 
16 q22.1 67478745 69245806 AARS 0.72 
16 q22.1 67478745 69245806 DDX19A 0.72 
16 q22.1 67478745 69245806 SF3B3 0.72 
16 q22.1 67478745 69245806 WWP2 0.67 
16 q22.1 69245806 69419474 VAC14 0.7 
16 q22.3 69419474 71533759 KIAA0174 0.85 
16 q22.3 69419474 71533759 DHX38 0.71 
16 q22.3 71533759 74776431 PSMD7 0.8 
16 q22.3 71533759 74776431 RFWD3 0.72 
16 q23.1 71533759 74776431 KARS 0.79 
16 q23.1 71533759 74776431 ADAT1 0.73  
16 q23.1 71533759 74776431 WDR59 0.68  
16 q23.1 71533759 74776431 TERF2IP 0.64 
16 q23.2 79052806 80639519 ASCIZ 0.72 
16 q24.1 83335109 84444005 COX4NB 0.82 
16 q24.1 83335109 84444005 KIAA0182 0.71  
16 q24.1 83335109 84444005 COX4I1 0.69 
16 q24.1 83335109 84444005 ZDHHC7 0.69 
17 p13.3 2077107 3789432 ITGAE 0.8  
17 q11.2 24125209 25739938 ERAL1 0.66  
17 q11.2 24125209 25739938 FLOT2 0.75  
17 q11.2 22465093 23921490 IFT20 0.71  
17 q11.2 23991111 24125209 RPL23A 0.77  
17 q11.2 23926892 24057159 SUPT6H 0.76  
17 q11.2 27772588 27941694 PSMD11 0.76 
17 q11.2 23991111 24125209 C17orf63 0.76  
17 q11.2 23944011 24039852 SPAG5 0.75  
17 q11.2 23926892 24057159 SDF2 0.68  
17 q11.2 26430455 26574472 NF1 0.72  
17 q11.2 23991111 24125209 TRAF4 0.63  
17 q12 34434812 34987922 CRKRS 0.82  
17 q12 34434812 34987922 RPL19 0.85  
17 q12 34434812 34987922 PPARBP 0.71  
17 q12 34987922 35196413 GRB7 0.87 
17 q12 35246223 35393977 GSDML 0.87 
17 q12 34987922 35196413 PERLD1 0.86 
17 q12 34987922 35196413 STARD3 0.82 
17 q12 34987922 35196413 ERBB2 0.82 
17 q12 35246223 35393977 PSMD3 0.81 
17 q12 30384409 30599689 NLE1 0.76 
17 q12 34201212 34324738 CCDC49 0.75  
17 q12 30270215 30599689 LIG3 0.73 
17 q12 34201212 34324738 RPL23 0.71  
17 q12 34201212 34324738 PIP5K2B 0.68  
17 q12 34987922 35196413 PNMT 0.65 
17 q21.1 35465293 35659097 CASC3 0.66 
17 q21.1 35465293 35659097 THRA 0.66  
17 q21.2 35920386 37443438 SMARCE1 0.66 
17 q21.2 35682074 35839525 CDC6 0.81  
17 q21.2 35682074 35839525 WIPF2 0.75 
17 q21.2 35737736 35915957 RARA 0.71  
17 q21.2 35682074 35839525 TOP2A 0.7  

NOTE: The genes are ordered by chromosomes and are located in regions differentially gained or lost between ERBB2 and luminal DCIS (listed in Supplementary Data 3). The correlation coefficients (Pearson and Spearman) were considered significant when higher than 0.6 with a Benjamini-Hochberg corrected P value lower than 0.05. In case of multiple probe sets corresponding to one gene, the highest correlation coefficient is indicated. Similarly, for probe sets that matched with two flanking (backward and forward) BACs, the highest correlation coefficient is shown. The last column indicates the genes exhibiting expression copy number correlations in infiltrating ductal carcinomas (28). The complete list of genes exhibiting significant expression copy number correlations is provided in Supplementary Data 6.

Similar correlations have recently been described in IDC (28). Interestingly, when the lists of genes correlated with copy number changes in DCIS and IDC (28) were compared, we observed a strong overlap, as 204 of 416 (49%) genes that correlated with genomic status in DCIS were also shown to be correlated with genomic status in IDC. Strikingly, this overlap represented 103 of 170 genes (61%) within the genomic regions differentially altered between the ERBB2 and luminal DCIS groups (Table 2; Supplementary Data 3).

We report the first combined phenotypic, genomic, and transcriptomic analysis of a series of DCIS frozen samples. The most striking conclusions of this work are the high degree of phenotypic, genomic, and transcriptomic similarities between DCIS and IDC and high diversity of breast tumors existing already in situ early phase.

DCIS can be classified into the luminal, ERBB2, and basal-like groups previously described in IDC (21, 22). In our series of 57 DCIS, most tumors (56%) belonged to the luminal group based on ER expression and the absence of ERBB2 overexpression. The second group of tumors comprised ERBB2 overexpressing DCIS (37%) that were mostly high grade (81%) and ER negative/PR negative (90%) in agreement with previous reports showing that ERBB2 overexpression is rare in ER-positive DCIS (37). A third small group was composed of three triple-negative DCIS (5%) with only one case demonstrating a clear basal-like immunophenotype (2%) with positive staining for keratin 5/6 and epidermal growth factor receptor, confirming that the recently recognized basal-like DCIS group is a rare entity among pure DCIS (6-10% of cases; refs. 25, 26, 38, 39). This was also shown by a recent gene expression profile analysis of a series of DCIS (18).

When compared with the luminal group, the ERBB2-amplified cases presented a particular array CGH profile with more frequent 17q gains, 3p, 4p, 4q, and 8p losses. In contrast, the luminal DCIS group harbored significantly more frequent 16q losses. These observations refine previously published classic CGH data showing a significantly higher number of 17q gains in high nuclear grade DCIS (which correspond to most cases of our ERBB2-amplified, ER-negative group) and 16q losses in low-grade DCIS (which are represented in the present series by the luminal cases; refs. 4, 7, 11).

We also show that DCIS can be classified according to the genomic criteria recently proposed for IDC (28), as a first group of 34 tumors presented high-level amplification of genomic regions (amplifiers). All TP53 mutations were observed in this group. Remarkably, the recurrent amplicons of DCIS were located on 8p12 (FGFR1), 11q12 (Cyclin D1), 17q12 (ERBB2), and 20q13 (BMP7/BCAS1), corresponding also to the most frequent amplicons of IDC (28). Compared with other amplifier cases and as recently observed in IDC (28), half amplicons associated with ERBB2 were also located on chromosome 17q. In contrast, in the luminal group, only 17% of amplicons involved 17q. A second group comprised tumors with a 16q deletion associated with 1q gain but no additional CNA. All these cases presented a luminal phenotype. The last group comprised cases with more complex CNA. In this series, the three triple-negative DCIS did not present any recurrent genomic profile, but two were amplifiers including the bona fide basal-like DCIS, which also harbored a TP53 gene mutation.

Unsupervised analysis of gene expression profiles supports the observation that ERBB2-amplified and luminal DCIS constitute two distinct entities. Gene ontology analysis of the ERBB2 DCIS signature showed that the genes up-regulated in this group belonged to ERBB2 signal transduction pathways but also to fatty acid metabolism and other protein kinase and transmembrane signaling pathways. Genes down-regulated mainly belonged to apoptotic and ER regulation pathways. The list of genes differentially expressed between ERBB2 and luminal DCIS in this series was compared with the recently published list of genes that discriminate DCIS according to their differentiation status (18). Although the two comparisons were based on slightly different criteria, they both highlighted major genes involved in breast carcinogenesis such as ESR1, GRB7, and ERBB2. A link between the ERBB2 pathway and fatty acid metabolism has been previously reported in cell lines (40) and invasive breast carcinomas (41). The present study also showed that these pathways are activated right from the earliest stages of ERBB2-driven breast carcinogenesis. Interestingly, as reported in IDC (42, 43), overexpression of 17q12 genes STARD3, GRB7, and PERLD1 is also associated with ERBB2 overexpression in DCIS, which raises the question of their putative synergistic role during early breast carcinogenesis. Finally, Integrin β6, a receptor for fibronectin and cytotactin, is overexpressed in the ERBB2 DCIS group. Recent data have highlighted molecular interactions between ERBB2 receptors and integrin networks (41, 44). Moreover, experiments conducted with ITGB6 knockout mice indicate that ITGB6 may regulate transforming growth factor β and metalloprotease, in particular matrix metalloproteinase 12 expression (45). Further investigations are needed to understand the role of ITGB6 in ERBB2-amplified DCIS.

It is noteworthy that genes recently involved in angiogenesis or invasion such as SDC1 (syndecan; refs. 4648) or CXCR4 are up-regulated in ERBB2-positive in situ lesions (49). Reciprocally, FGFR2, a gene recently linked to in susceptibility locus in breast cancer (50, 51), is up-regulated in luminal DCIS.

The correlation between array CGH and expression data shows that amplifications but also more subtle copy number changes lead to modifications of the gene expression profile. Strikingly, a large part of the genes, for which a strong correlation between expression level and genomic status was observed, also exhibited a similar correlation in IDC (28), indicating that genome alterations have similar consequences on gene expression in both IDC and DCIS. In line with the data reported by Chin et al. (28), these results identify genes located in frequently altered regions in breast cancer, strongly influenced by copy number variations, and whose gene dosage effects may play a role in early phases of breast carcinogenesis. Two genes on chromosome 16 seem to be of particular interest: ASCIZ (ATM/ATR-substrate ChK2-interacting Zinc finger; ref. 52), which encodes a protein involved in lesion-specific Rad51 focus formation, a process that also involves BRCA1 and BRCA2, two master genes in breast carcinogenesis; and CNOT1, which encodes a member of the CCR4-NOT complex, a global regulator of transcription that may act as a repressor of endogenous estrogens target genes (53). Interestingly, CNOT7, another member of the CCR4-NOT complex, is regulated by gene copy number variation on chromosome 8p, a chromosome frequently altered in ERBB2 DCIS tumors. Based on these observation, the hypothesis of haploinsufficiency of the CCR4-NOT complex playing a role in early breast tumorigenesis may now be tested.

Altogether, these integrated genomic and transcriptomic data confirm previous results showing strong similarities between IDC and DCIS (20, 54). Although we cannot exclude the possibility that subtle genetic alterations that may have escaped detection in this study could also play a role in the evolution from DCIS to IDC, this study raises the hypothesis that the difference between DCIS and IDC is not based on specific genetic alterations or on their consequences on gene expression profile. Because a recent report suggested that a 35-gene expression classifier might distinguish IDC and DCIS (18), the role of epigenetic modifications in the progression from DCIS to IDC will need to be evaluated.

In conclusion, our data show that DCIS already displays the molecular diversity observed in IDC and, therefore, can be classified according to molecular criteria distinguishing ERBB2-amplified DCIS, usually high-grade, ER negative with frequent TP53 mutations, from luminal DCIS corresponding to low/intermediate-grade, ER positive with a very low rate of TP53 mutations. In our series, only three cases were classified as triple negative and only one was classified as basal-like DCIS, which confirms that this last entity is rare among DCIS. Further studies are needed to define whether a classification of DCIS based on molecular markers may help to more accurately define cases associated with a higher risk of recurrence. And finally, genomic/transcriptomic correlations represent a promising tool to identify new genes and pathways important in early breast carcinogenesis.

Grant support: Institut National de la Sante et de la Recherche Medicale, the Institut Curie (Programme Incitatif et Coopératif), and the Ligue Nationale contre le Cancer. Construction of the BAC array was supported by grants from the Carte d'Identité des Tumeurs program of the Ligue Nationale Contre le Cancer. Dr Anne Vincent-Salomon was supported by an “Interface Institut National de la Sante et de la Recherche Medicale” grant.

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Note: Supplementary data for this article are available at Clinical Cancer Research Online (http://clincancerres.aacrjournals.org/).

We thank Dr Paul Fréneaux for his constant support during our study, Céline Grassart for her excellent technical assistance, and Ingrid Lebigot and her team from the Institut Curie's tumor bank.

Members of the Breast Cancer Study group in addition to coauthors: Bernard Asselain, Alain Aurias, Emmanuel Barillot, Marc Bollet, François Campana, Paul Cottu, Patricia de Cremoux, Véronique Diéras, Laurent Mignot, Jean-Yves Pierga, Marie-France Poupon, Dominique Stoppa-Lyonnet, Anne Tardivon, Fabienne Thibault, and Pascale This.

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Supplementary data