- Open Access
Loss, mutation and deregulation of L3MBTL4 in breast cancers
Molecular Cancer volume 9, Article number: 213 (2010)
Many alterations are involved in mammary oncogenesis, including amplifications of oncogenes and losses of tumor suppressor genes (TSG). Losses may affect almost all chromosome arms and many TSGs remain to be identified.
We studied 307 primary breast tumors and 47 breast cancer cell lines by high resolution array comparative genomic hybridization (aCGH). We identified a region on 18p11.31 lost in about 20% of the tumors and 40% of the cell lines. The minimal common region of loss (Chr18:6,366,938-6,375,929 bp) targeted the L3MBTL4 gene. This gene was also targeted by breakage in one tumor and in two cell lines. We studied the exon sequence of L3MBTL4 in 180 primary tumor samples and 47 cell lines and found six missense and one nonsense heterozygous mutations. Compared with normal breast tissue, L3MBTL4 mRNA expression was downregulated in 73% of the tumors notably in luminal, ERBB2 and normal-like subtypes. Losses of the 18p11 region were associated with low L3MBTL4 expression level. Integrated analysis combining genome and gene expression profiles of the same tumors pointed to 14 other potential 18p TSG candidates. Downregulated expression of ZFP161, PPP4R1 and YES1 was correlated with luminal B molecular subtype. Low ZFP161 gene expression was associated with adverse clinical outcome.
We have identified L3MBTL4 as a potential TSG of chromosome arm 18p. The gene is targeted by deletion, breakage and mutations and its mRNA is downregulated in breast tumors. Additional 18p TSG candidates might explain the aggressive phenotype associated with the loss of 18p in breast tumors.
The development and progression of breast cancer is the result of the accumulation of genetic alterations such as amplification of oncogenes and deletions of tumor suppressor genes (TSG) in the epithelial cells of the mammary gland. Frequent deletions have been reported on chromosome arms 1p, 3p, 7q, 8p 9p, 16q and 17p but only few reports describe such deletions on chromosome arm 18p [1–3].
We profiled a series of 307 primary breast tumors and 47 breast cancer cell lines by using high resolution array comparative genomic hybridization (aCGH). We identified a region on 18p11.31 deleted in 25% of the tumors and 40% of the cell lines. We delineated a minimal common region of deletion that targeted the L3MBTL4 gene. The L3MBTL4 gene is one of the four human orthologs of Drosophila lethal (3) malignant brain tumor (l(3)mbt). L(3)mbt is a bona fide TSG in the fly [4, 5]. The L3MBTL4 protein contains three "malignant brain tumor" (MBT) domains. This domain of about 100 amino acid residues is conserved in protostomians and deuterostomians and often exists as repeats . The MBT domain binds methylated histone residues. The human genome contains several MBT-containing proteins, some of which have been linked to gene regulatory pathways and polycomb-mediated repression, and to cancer . L3MBTL1 is a TSG implicated in myeloid malignancies , and L3MBTL3 deregulation is associated with neuroblastoma .
To document the involvement of L3MBTL4 in breast cancer we searched for mutations by sequence analysis of 180 primary tumor samples and 47 cell lines. We found that, in addition to deletions, L3MBTL4 is targeted by mutations. Finally, we found that L3MBTL4 deletions correlate with low mRNA expression and with the presence of lymph node metastasis, high Scarf-Bloom-Richardson (SBR) grade and luminal B molecular subtype.
Our study is the first to identify a region on chromosome arm 18p likely to contain a putative TSG involved in breast oncogenesis, and to show that this TSG may be L3MBTL4. We did not exclude the existence of other potential 18p TSGs, some of which could explain the aggressive phenotype of breast tumors with 18p loss.
Samples and Methods
Tumor tissues were collected from 307 patients with primary adenocarcinoma who underwent initial surgery at the Institut Paoli-Calmettes (Marseille, France) between 1992 and 2004. Immediately after macroscopic examination of the surgery specimen by two pathologists, samples containing more than 60% of tumor cells were obtained, frozen in liquid nitrogen and stored at -80°C until nucleic acids extraction. The main histoclinical characteristics of tumors are listed in the Additional file 1, Table S1. Each patient gave written informed consent and the study was approved by our institutional review committee.
The 47 breast cell lines used in this study were BT-20, BT-483, HCC1937, CAMA-1, HCC38, HCC1500 , Hs 578T , BT-474, BT-549, HCC202, HCC1395, HCC1569, HCC1806, HCC1954, HCC2218, HME-1, MCF7, MDA-MB-134, MDA-MB-157, MDA-MB-175, MDA-MB-231, MDA-MB-361, MDA-MB-415, MDA-MB-436, MDA-MB-453, MDA-MB-468, SK-BR-3, SK-BR-7, T47 D, UACC-812, UACC-893, ZR-75-1, ZR-75-30 (ATTC, Manassas, VA), BrCa-Mz-01, BrCa-Mz-02 , SUM44, SUM52, SUM102, SUM149, SUM159, SUM185, SUM190, SUM206, SUM225, SUM229 , S68 (V. Catros, Rennes, France), and CAL51 . All cell lines were grown as recommended by their suppliers.
DNA and RNA extraction
DNA and RNA were extracted from frozen samples by using guanidium isothiocynanate and cesium chloride gradient, as previously described . DNA quality and RNA integrity were respectively controled on polyacrylamide gel electrophoresis and on Agilent Bioanalyzer (Agilent Technologies, Massy, France). DNA was also extracted from a normal area of paraffin-embedded T8584, T8847, T9193 and T8525 tissues.
Genome analysis by array-comparative genomic hybridization (aCGH)
Genome profiles were established on 307 tumors and 47 breast cancer cell lines by aCGH using 244K CGH Microarrays (Hu-244A, Agilent Technologies, Massy, France) as previously described . A pool of 13 normal male DNAs was used as reference. Scanning was done with Agilent Autofocus Dynamic Scanner (G2565BA, Agilent Technologies). Data analysis was done and visualized with CGH Analytics 3.4 software (Agilent Technologies). Extraction of data (log2 ratio) was done from CGH analytics, while normalized and filtered log2 ratio were obtained from "Feature extraction" software (Agilent Technologies). Data generated by probes mapped to × and Y chromosomes were eliminated. The final dataset contained 225,388 unique probes covering 22,509 genes and intergenic regions according to the hg17/NCBI human genome mapping database (build 35). Data were analyzed using circular binary segmentation (CBS)  as implemented in the DNA copy R/Bioconductor package  with default parameters to translate intensity measurements in regions of equal copy number, each region being defined by at least five consecutive probes. Thus, each probe was assigned a segment value referred to as its "smoothed" value.
We used a threshold value of |0.33| (log2 ratio) to define a copy number aberration (CNA) . Identification of copy number variations (CNV) was done using the regions published by McCarroll et al  which are stored in the Database of Genomic Variants (release v8) . To determine altered regions, we used the GISTIC algorithm , which computes for each genomic segment through the whole genome a score based on the frequency of CNA combined with its amplitude, with bootstrapping to calculate the significance level (p < 0.001). To establish significant association between CNA and categorical variables, Fisher's exact test was used. Gains and losses were handled separately.
Sequence analysis was done on 180 out of the 307 breast tumors and on the 47 breast cell lines after amplification of genomic DNA. Seventeen primers pairs were designed to amplify L3MBTL4 DNA by polymerase chain reaction (PCR) (Additional file 1, Table S2). PCR amplifications were done in a total volume of 25 μl PCR mix containing at least 10 ng template DNA, Taq buffer, 500 μmol of each deoxynucleotide triphosphate, 100 μmol of each primer and 1 unit of Hot Star Taq DNA polymerase (Qiagen, Courtaboeuf, France). PCR amplification conditions were as follows: 95°C 10 min and 95°C 30 sec, annealing T° 55°C 30 sec, 72°C 45 sec to to 1 min depending on PCR product length, 72°C 10 min, 35 cycles. PCR products were purified using Millipore plate MSNU030 (Millipore SAS, Molsheim, France). Aliquots (1 μl) of the purified PCR products were sequenced using Big Dye terminator v1.1 Cycling Sequencing Kit (Applied Biosystems, Courtaboeuf, France) including the forward or reverse primer. The sequencing products were purified through Multi-Screen-HV 96-well filter plates (Millipore, Billerica, MA, USA) preloaded with Sephadex G-50 (Sigma, St Louis, MO, USA). The reactions were run on the ABI 3130XL Genetic Analyser (Applied Biosystems, Courtaboeuf, France). The sequence data files were analyzed using the phred/phrap/consed software. All mutations were confirmed by a second round of PCR and sequencing reactions in both directions.
Quantitative real time reverse-transcribed PCR (qRT-PCR)
L3MBTL4 gene expression level was analyzed by qRT-PCR on a set of 52 out of the 307 tumors. Two μg of total RNA, treated beforehand with RNase-free DNase (Promega, France), was reverse-transcribed using the SuperScript II RT and 100 ng of randomhexamers (Invitrogen, France). PCR reactions were carried out in a LightCycler 2.0 instrument (Roche, Germany) in a final volume of 20 μl according to the supplier's recommendations using LightCycler FastStart DNA Master plus SYBR Green I Kit (Roche, Germany). L3MBTL4 primers, L3MBTL4-F (CTTGGAGCAAGCTGAAGAGG) and L3MBTL4-R (TGGAAAGGACTGATCCTTGG) (Sigma-Aldrich, Austria), were designed to anneal to exon 4 and exon 6, respectively. Primers for the control gene, GUSB, were GUSB-F (GAAAATATGTGGTTGGAGAGCT) and GUSB-R (CCGAGTGAAGATCCCCTTTTTA) (Sigma-Aldrich, Austria). The mean threshold cycle (Cp) was calculated for each gene and ΔCp was defined as ΔCp = Cp (GUSB) - Cp (L3MBTL4). The ΔCp was determined on two to six times for each sample and the mean calculated. The fold ratio of L3MBTL4 transcripts was calculated using the equation, fold ratio = 2ΔCp. Commercial pools of normal breast RNA (Clontech, Palo Alto, CA) were analyzed and used as control.
Gene expression profiling with DNA microarrays
A total of 229 tumors studied by aCGH, as well as 4 normal breast tissue samples, were profiled with Affymetrix U133 Plus 2.0 human oligonucleotide microarrays as previously described . Scanning was done with Affymetrix GeneArray scanner. Data were analyzed by 'Robust Multichip Average' (RMA) with the non-parametric quantile algorithm as normalization parameter in R/Bioconductor and associated packages . All probes were mapped based on their EntrezGeneID. When multiple probes were mapped to the same gene, the probe sets with an extension « at », next « s_at », and followed by all other extensions were preferentially kept. When several probe sets with the best extension were available, the one with the highest median value was retained.
The five molecular subtypes related to the intrinsic breast cancer tumor classification were determined using the single sample predictor (SSP) classifier  associated to 'Distance Weighted Discrimination' (DWD) as data set adjustment .
Prior statistical analyses L3MBTL4 expression level in samples was centered using its expression level in the 4 normal breast samples pooled. Over- and under-expression were defined using a two-fold threshold i.e. |1| in the log2 transformed data.
Comparative analyses of genome and expression data
To identify other potential 18p TSGs we compared the degree of CNA-driven RNA downregulation in 229 of the 307 samples by analyzing the genes common to the genome and expression platforms (aCGH Agilent Technologies and Affymetrix) and retained after filtering based on the expression level. Briefly, a potential TSG had to show a lower expression value in a sample with loss than in those without (Student t test) and an underexpression frequency overrepresented in samples with the loss (Fisher's exact test). For both tests significance level was 5% with a false discovery rate (FDR, ) less than 1%.
Correlations between L3MBTL4 CNA groups and histoclinical factors were calculated with the Fisher's exact test. Student's t test and one-way ANOVA test were used to evaluate association of L3MBTL4 gene expression level within histoclinical factors. Overall specific survival (OS) and metastasis-free survival (MFS) curves were estimated using the Kaplan-Meier method and statistical significance of pairwise comparisons was assessed using the log-rank test. OS and MFS follow-up times were measured from the date of diagnosis till death from breast cancer and till the first occurrence of distant metastases, respectively. All statistical tests were two-sided at the 5% level of significance. Statistical analysis was done using the survival package (version 2.30), in the R software (version 2.9.1).
Losses and breakages of 18p targets the L3MBTL4 gene at p11.31
Genome profiles of 307 primary breast tumors and 47 cancer cell lines were established by aCGH. GISTIC analysis showed that chromosome arm 18p was targeted by losses in more than 20% of tumor samples (Additional file 2, Figure S1). None of these losses were homozygous deletions. Profiles showed various sizes of losses (Figure 1A). In tumor T8700 loss within 18p11.31 (Figure 1A) spanned the L3MBTL4 gene only (Figure 1B). 18p losses including this region were found in 77 (25%) primary tumors and 19 (40%) cell lines.
Copy number transitions are likely to reflect DNA strand breakages that may lead to nonreciprocal translocations . L3MBTL4 was targeted by copy number transition in tumor T50115, and in the HCC38 (Figure 1C, D) and MDA-MB-453 cell lines. In T50115, the breakpoint was within the genome interval [ch18: 6,202,799-6,212,615], which contains L3MBTL4 exons 10 and 11. The resulting protein should be truncated of its C-terminal part starting from the second MBT motif. In HCC38 and MDA-MB-453 the breakpoints spanned genome intervals chr18: 6,009,803-6,020,061, (between exons 17 and 18) and chr18: 6,030,519-6,044,093 (including exon 16], respectively. These two breakages should generate a protein truncated of the sterile alpha motif (SAM) domain. None of these potential fusion transcripts involving the L3MBTL4 gene has been identified yet.
Thus, the L3MBTL4 gene is targeted by various genomic alterations, including loss and breakage, in a high proportion of breast cancers.
Features of tumors with L3MBTL4 loss
L3MBTL1, L3MBTL2 and L3MBTL3 paralogs were not targeted by deletion in our breast tumor set. We did not find any L3MBTL4 deletion among genome profiles similarly established in 80 colon cancers, 115 myeloid hematopoietic diseases and 53 sarcomas (data not shown). This suggests that L3MBTL4 loss occurs specifically in breast cancers.
Comparison of aCGH data in tumors with and without L3MBTL4 loss showed that L3MBTL4 loss was often found together with the loss of four 17q genes: ACCN1 (p = 2.5.10-5), RHOT1 (p = 8.3.10-5), PSMD11 (p = 1.3.10-4), and MYO1 D (p = 1.8.10-4) (Additional file 1, Table S3).
The 77 tumors with L3MBTL4 loss comprised 18 luminal A, 27 luminal B, 17 basal, 9 ERBB2, 2 normal-like (Table 1) and 4 non-informed tumors (Additional file 1, Table S4A). Among these, 42 (55%) showed loss of a regional part of chromosome 18p including the L3MBTL4 gene. They included 8 luminal A, 15 luminal B, 10 basal, 5 ERBB2, 1 normal-like and 3 non-informed tumors. The minimal commonly deleted region (CDR) including L3MBTL4 was defined for each molecular subtype as chr18:6,366,938-6,798,785 bp in luminal A (telomeric and centromeric limits were defined by tumors T11348 and T8683, respectively and noted [T11348-T8683]), chr18:3,784,366-6,202,799 bp in luminal B ([T9377-T50115]), chr18:6,285,396-6,375,929 bp in basal ([T5142cc-T8700]), chr18:3,732,722-6,168,500 bp in ERBB2 ([T9296]), chr18:5,520,302-8,628,361 bp in normal-like ([T12652]) and chr18:5,200,158-11,854,021 bp in non-informed tumors ([T6744-T12662]) (Additional file 1, Table S4A).
The 35 other cases showed a loss of L3MBTL4 as a consequence of the complete loss of the chromosome 18p. They included 10 luminal A, 12 luminal B, 7 basal, 4 ERBB2, 1 normal-like and 1 non-informed tumors. Interestingly, the complete loss of the chromosome 18p was associated with the luminal B molecular subtype (p < 0.05), as well as cancer in older women (>50 years old) (Additional file 1, Table S4B).
Taken together, a minimal 18p CDR, chr18:6,366,938-6,375,929 bp within the L3MBTL4 locus, was defined in 74 tumors (Additional file 1, Table S4A). In T9296, T50115 and T50136 the L3MBTL4 loss flanked this CDR at the telomeric and centromeric borders, respectively.
Comparison of clinical features between breast tumors with and without L3MBTL4 loss (Table 1) showed that L3MBTL4 loss was associated with the presence of lymph node metastases (p = 1.02 10-2), high SBR grade (p = 1.15 10-2) and luminal B molecular subtype defined by SSP classification  (p = 3.10-5). No impact on survival was noted.
L3MBTL4 is targeted by mutations
We searched for mutation in L3MBTL4 exons in 180 and 47 of the aCGH-profiled tumors and cell lines, respectively. Sequence analysis of the tumor samples identified 32 variants including 25 synonymous (23 p.Ileu570Ileu, 2 p.Val201Val), 6 missense (3 p.Ser123Asn, 1 p.Ser493Leu, 1 p.Glu560Lys, 1 p.Ile615Ser) and 1 nonsense (p.Tyr339X). In BT-483 cell line a missense (p.Arg96Gln) mutation was identified. Figure 2A shows two examples of mutation. The localization and nature of the mutations are shown in Figure 2B. The p.Ser123Asn substitution and the nonsense mutation were located in regions encoding the conserved MBT1 and MBT3 motifs, respectively. The nonsense mutation should generate a truncated L3MBTL4 protein without C2HC zinc finger and SAM domains. The p.Arg96Gln substitution in BT-483 should affect the MBT1 domain. The SAM motif was also targeted by the p.Glu560Lys substitution. We were able to show that the p.Ser123Asn and p.Tyr339X mutations found respectively in T8584, T8847 and T9193 and in T8525, were acquired (Figure 2A). We could not confirm that the other missense mutations are similarly somatic. However, they were not included as SNP or missenses in NCBI db SNP build 131 .
Counting only the 7 potentially deleterious mutations the frequency of such event would be 3.9% in tumor samples.
Two mutated (missense mutation) tumors (T9193 and T10003) were also deleted.
L3MBTL4 mRNA is downregulated in breast tumors
L3MBTL4 gene expression was measured using qRT-PCR in normal breast tissues and 52 breast tumor samples including 16 with a loss of the L3MBTL4 gene region (T7420, T8009, T8189, T8600, T8700, T9059, T9398, T9888, T9941, T11348, T11485, T11568, T10684, T12854, T13469, T13018), one mutated and deleted (T10003), and one mutated but not deleted (T8525). L3MBTL4 gene expression was quantified by comparison with the expression of the housekeeping GUS gene. Overall, tumor samples expressed a low level of L3MBTL4 mRNA as compared with normal breast tissue. L3MBTL4 mRNA level was decreased at least two-fold in all tumors with L3MBTL4 loss as well as in the mutated and non-deleted sample (Figure 3). Some non-deleted tumors also exhibited low L3MBTL4 mRNA level suggesting that L3MBTL4 downregulation could be attributed to several mechanisms including deletions but also regulation of transcription.
We also determined L3MBTL4 gene expression in 229 tumor samples and 4 NB samples by using Affymetrix microarrays. L3MBTL4 mRNA was downregulated (ratio T/NB <0.5) in 166 tumors (72%). Comparative analysis of these 229 samples identified a significant correlation (p = 5.05 10-4) between L3MBTL4 mRNA downregulation and gene loss (Figure 4A). Downregulation of L3MBTL4 mRNA was associated with luminal A, luminal B and ERBB2 molecular subtypes (p = 6.734 10-43).
Expression microarray profile revealed five genes (TTMA, PTPN2, NDC80, SLMO1 and TUBB6) coordinately deregulated with L3MBTL4 and also localized in an 18p region frequently lost in breast tumors, suggesting a common mechanism of deregulation of their expression, which might contribute to breast oncogenesis.
Correlations between L3MBTL4 microarray data and clinical features of 229 tumors are reported in the Additional file 1, Table S5. The lowest expression of L3MBTL4 was found in lobular tumors (p = 7,11.10-12) and in inflammatory breast cancers (p = 0.04) and was associated with the expression of estrogen receptor (ER) (p = 2,73.10-14), progesterone receptor (PR) (p = 3,11.10-13), ERBB2 (p = 7,73.10-14), SBR grade 2 (p = 1.49 104), lymph node metastasis (p = 3,39.10-5), P53 negativity (p = 0.0495) and low expression of Ki67 proliferative index (p = 19,61 10-5).
Sixty-four genes are targeted by 18p copy number losses in breast cancer
To identify other 18p genes targeted by copy number losses, a GISTIC analysis was done on the genome profiles of the 307 cases. Recurrent copy number losses targeted 64 genes within the 18p11.21-11.32 region (p < 1 × 10-5) (Additional file 2, Figure S1), including L3MBTL4 and the potential TSG EPB41L3/DAL1. This suggests that this 18p11 region probably hosts multiple TSGs.
Fourteen new 18p TSG candidates
To identify these other potential 18p11 TSGs we compared the degree of CNA-driven RNA downregulation in the 307 samples by analyzing the genes common to the genome and expression platforms (aCGH Agilent Technologies and Affymetrix) and retained after filtering based on the expression level. Sixty-three of the 64 were common. The gene expression of 14 genes (YES1, SMCHD1, LPIN2, MRCL3, MRCL2, ZFP161, RALBP1, PPP4R1, NAPG, AFG3L2, SPIRE1, CEP76, PTPN2 and SEH1L) was downregulated in relation with their copy number losses (p < 0.05) (Additional file 1, Table S6). We noted that EPB41L3/DAL1 and L3MBTL4 were not retained. The lowest expression of EPB41L3 in breast tumors was associated with the presence of lymph node metastases (p < 0.05), correlated with basal and luminal B molecular subtypes (p < 0.01) and showed clinical impact (Additional file 1, Table S7).
Among the 14 genes, the downregulated expressions of ZFP161, PPP4R1 and YES1 in breast tumors were correlated with the luminal B molecular subtype (p < 0.01). Interestingly, the downregulated expression of ZFP161 was correlated with a poor clinical outcome (5-years MFS, p = 1.7.10-3; 5-years OS, p = 1.6.10-3) (Additional file 1, Table S8).
L3MBTL4 gene alterations
Few works have reported the presence of TSGs on 18p for breast cancer [1, 2] and only EPB41L3/DAL1 has been identified as potential TSG involved in this neoplasm thus far. Our aCGH results provide a detailed view of the alterations of chromosome arm 18p in breast tumors. Losses at 18p11.31 occurred in 25% of tumors and the smallest common region of deletion targeted the L3MBTL4 locus and was also the site of breakages. The karyotype of the MDA-MB-453 cell line displays a der(18)t(7;18) . The L3MBTL4 breakpoint suggests involvement of this gene in this alteration. L3MBTL4 loss was associated with high grade and with lymph node metastasis. In agreement, an increased risk of relapse in patients with high risk breast cancer has been associated with 18p loss . L3MBTL4 loss was associated with the luminal B subtype, which is characterized by a poor prognosis. Interestingly, L3MBTL4 is centromeric and in close proximity to the loss of heterozygosity (LOH) region spanning EPB41L3 previously reported in non-small cell lung carcinomas , breast carcinomas , and meningiomas .
L3MBTL4 was targeted by point mutations in few cases. These mutations clustered in the vicinity of the MBT or SAM motifs. A study of L3MBTL1 has shown that a point mutation in the second MBT repeat motif affected the binding to H1K26me and H4K20me . We surmise that the nonsense mutation in the third MBT motif of L3MBTL4 may have similar functional implication.
In three tumors and in the BT-483 cell line L3MBTL4 mutations were associated with the loss of the other allele, suggesting a double-hit mechanism leading to complete loss-of-function of L3MBTL4 in these samples. We did not find homozygous mutations or deletions of L3MBTL4. However, we cannot exclude that in addition to these alterations, total inactivation could result from promoter hypermethylation of the other allele. The study of mRNA expression tended to confirm this.
L3MBTL4 loss of expression
Expression of L3MBTL4 level was decreased at least two-fold in 73% of breast cancer samples, particularly in tumors deleted at the L3MBTL4 locus since decreased expression correlated with genomic alteration. All the deleted tumors showed absence or decreased L3MBTL4 expression. Few cases displayed mRNA downregulation in the absence of loss suggesting that other mechanisms such as epigenetic repression play a role in the downregulation of L3MBTL4 in breast tumors.
L3MBTL4 downregulated expression was not found only in luminal B tumors but also in luminal A, luminal B, ERBB2 and normal-like cases. Only the basal subtype presented a normal expression of the gene, independently of loss. This suggests that L3MBTL4 does not play a TSG role in this subtype of breast cancer. Inactivation of other TSGs may explain 18p losses in basal breast cancers.
L3MBTL4 as a tumor suppressor gene
Our observations are in agreement with a previous study that suggested the presence of TSGs on 18p with a role in the genesis of breast cancer . There are several reasons to believe that L3MBTL4 is a good candidate TSG. First, it lies within the region of chromosome 18 that is frequently deleted in breast cancers; L3MBTL4 is also targeted by mutations and breakages and is dowregulated in tumors. Second, L3MBTL4 gene is a human homolog of Drosophila l(3)mbt, which functions as a TSG in fly. The loss-of-function generated by mutation of l(3)mbt causes brain tumors in Drosophila[4, 5]. Third, L3MBTL4 has three paralogs that are suspected to play a role in the etiology of certain types of cancer . L3MBTL1, a known transcriptional repressor , has been proposed as a TSG gene in myeloid malignancies associated with 20q deletion [8, 35, 36]. A recent study reported focal hemi- and homozygous deletions of L3MBTL2 and L3MBTL3 in medulloblastoma .
The four human L3MBTL proteins have MBT domains involved in transcriptional repression and chromatin remodeling. The MBT domain was originally identified in the Drosophila l(3)mbt protein  and binds methyl-lysine residues [37, 38], particularly and strongly H3K9me and H4K20me . The transcriptional repressor L3MBTL1 requires its three MBT domains for compacting chromatin and silencing . Although the exact biochemical properties and cellular functions of L3MBTL4 are unclear to date, the presence of MBT domains in L3MBTL4 suggests that it interacts with chromatin , may potentially bind methylated histone and thus play a role in transcriptional regulation of stem cell genes, oncogenes and tumor suppressors. Loss of this regulator may thus affect several breast cancer genes. Some of these genes may be part of the E2F/RB pathway. Indeed, the E2F/RB pathway is altered in luminal B cancers and L3MBTL proteins are known to regulate this pathway .
Taken together, our results suggest that aberrations targeting L3MBTL4 could confer to cancer cells specific advantages but do not exclude the role of other potential 18p candidates.
Other 18p TSG candidates
One of the potential 18p TSGs might be EPB41L3/DAL1, which is just telomeric to L3MBTL4, between the D18S59 and D18S452 markers. However, its expression was not correlated with that of L3MBTL4. We also identified 14 TSG candidates whose gene expression was downregulated in relation with their copy number losses. We noted that EPB41L3/DAL1 and L3MBTL4 were not included in the 14 suggesting that their downregulated gene expression is not only the consequence of their copy number loss but could result from other mechanisms of deregulation including epigenetic modifications. This is in agreement with study showing that the hypermethylation of EPB41L3/DAL1 was associated with its downregulation in lung cancer . Our EPB41L3/DAL1 expression data showed that its downregulation could be associated with an increased risk of relapse in patients with high risk breast cancer.
EPB41L3/DAL1 undergoes allelic losses in various cancers and in a significant proportion of ductal carcinomas in situ of the breast. The EPB41L3/DAL1 protein suppresses the growth of MCF7 breast cancer cells and increases attachment of these cells to a variety of extracellular matrices . Modulation of post-translational methylation may be an important mechanism through which EPB41L3/DAL1 affects tumor cell growth . EPB41L3/DAL1 plays a critical role in the suppression of lung tumor formation and metastasis . However, the role of EPB41L3/DAL1 as a TSG has yet to be validated in vivo. EPB41L3/DAL1 deficient mice are healthy and do not develop spontaneous tumors . Mutational screening failed to identify inactivating mutation of the EPB41L3/DAL1 gene .
Among the 14 other TSG candidates, except PTPN2/TCTP none has been so far associated with cancer. PTPN2/TCPTP codes for the T-cell protein tyrosine phosphatase (TCPTP) and is an important negative regulator of SFK, JAK1 and STAT3 signaling during the cell cycle . TCPTP suppresses the tumorigenicity of glioblastoma cells expressing a mutant epidermal growth factor receptor . CEP76 encodes a centrosomal protein controling centrosome duplication during cell division. Abnormal centrosome duplication contributes to mitotic failure, genome instability, aneuploidy, and cancer. Depletion of CEP76 drives the accumulation of centrosome intermediates in certain types of cancer cells . Only the downregulated expressions of ZFP161, PPP4R1 and YES1 were correlated with the luminal B subtype suggesting their potential involvement in the genesis of a particularly aggressive form of breast cancer with 18p loss. The downregulated expression of ZFP161 in breast tumors was correlated with a poor clinical evolution. ZFP161/ZF5 encodes a ubiquitously-expressed protein originally identified by its ability to bind and repress the murine Myc promoter [48, 49]. The protein contains an N-terminal POZ domain, which recruits cofactors to modulate transcription . ZFP161/ZF5 mediates both transcriptional activation and repression of cellular and viral promoters [48, 50, 51]. ZFP161 may compete with MYC-induced transcription .
PPP4R1 encodes the regulatory subunit of a ~125-kDa protein phosphatase. PPP4R1 interacts with PPP4C [53, 54] which is implicated in the regulation of histone acetylation, DNA damage checkpoint signaling, NFκB activation, and microtubule organization at centrosomes [55–59]. YES1 encodes a SRC-family kinase  and its tyrosine kinase activity has been shown to be elevated in colonic adenomas compared to its activity in adjacent normal mucosa . A number of studies have linked increased expression of YES in cancer with increased cell motility and tumor invasion [62, 63]. It is then surprising to find YES1 among the 18p TSG candidates. The downregulation of YES1 could be the consequence of its loss as a simple passenger of a larger region lost within 18p.
We have delineated a region of frequent loss in breast cancer on chromosome arm 18p. We have identified L3MBTL4 as the gene targeted by these losses. L3MBTL4 is also targeted by mutations and breakages. L3MBTL4 mRNA expression is low in non-basal breast tumors and in particular in tumors with loss of the gene. Alteration of L3MBTL4, coding for a regulator of epigenetic marks, is well in line with recent advances in cancer research [64, 65]. We have also pointed to other 18p TSG candidates including ZFP161, CEP76, PPP4R1 and PTPN2 whose involvement might explain the aggressive phenotype of breast tumors with 18p loss.
Tran Y, Benbatoul K, Gorse K, Rempel S, Futreal A, Green M, Newsham I: Novel regions of allelic deletion on chromosome 18p in tumors of the lung, brain and breast. Oncogene. 1998, 17: 3499-3505. 10.1038/sj.onc.1202258
Osborne RJ, Hamshere MG: A Genome-wide Map Showing Common Regions of Loss of Heterozygosity/AllelicImbalance in Breast Cancer. Cancer Res. 2000, 60: 3706-3712.
Kittiniyom K, Gorse KM, Dalbegue F, Lichy JH, Taubenberger JK, Newsham IF: Allelic loss on chromosome band 18p11.3 occurs early and reveals heterogeneity in breast cancer progression. Breast Cancer Res. 2001, 3: 192-198. 10.1186/bcr294
Gateff E, Löffler T, Wismar J: A temperature-sensitive brain tumor suppressor mutation of Drosophila melanogaster: developmental studies and molecular localization of the gene. Mech Dev. 1993, 41: 15-31. 10.1016/0925-4773(93)90052-Y
Wismar J, Löffler T, Habtemichael N, Vef O, Geissen M, Zirwes R, Altmeyer W, Sass H, Gateff E: The Drosophila melanogaster tumor suppressor gene lethal(3)malignant brain tumor encodes a proline-rich protein with a novel zinc finger. Mech Dev. 1995, 53: 141-154. 10.1016/0925-4773(95)00431-9
Wismar J: Molecular characterization of h-l(3)mbt-like: a new member of the human mbt family. FEBS Lett. 2001, 507: 119-121. 10.1016/S0014-5793(01)02959-3
Bonasio R, Lecona E, Reinberg D: MBT domain proteins in development and disease. Semin Cel Dev Biol. 2010, 21: 221-230. 10.1016/j.semcdb.2009.09.010.
Li J, Bench AJ, Piltz S, Vassiliou G, Baxter EJ, Ferguson-Smith AC, Green AR: L3mbtl, the mouse orthologue of the imprinted L3MBTL, displays a complex pattern of alternative splicing and escapes genomic imprinting. Genomics. 2005, 86: 489-494. 10.1016/j.ygeno.2005.06.012
Northcott PA, Nakahara Y, Wu X, Feuk L, Ellison DW, Croul S, Mack S, Kongkham PN, Peacock J, Dubuc A, Ra YS, Zilberberg K, McLeod J, Scherer SW, Sunil Rao J, Eberhart CG, Grajkowska W, Gillespie Y, Lach B, Grundy R, Pollack IF, Hamilton RL, Van Meter T, Carlotti CG, Boop F, Bigner D, Gilbertson RJ, Rutka JT, Taylor MD: Multiple recurrent genetic events converge on control of histone lysine methylation in medulloblastoma. Nat Genet. 2009, 41: 465-472. 10.1038/ng.336
Tomlinson GE, Chen TT, Stastny VA, Virmani AK, Spillman MA, Tonk V, Blum JL, Schneider NR, Wistuba II, Shay JW, Minna JD, Gazdar AF: Characterization of a breast cancer cell line derived from a germ-line BRCA1 mutation carrier. Cancer Res. 1998, 58: 3237-3242.
Hackett AJ, Smith HS, Springer EL, Owens RB, Nelson-Rees WA, Riggs JL, Gardner MB: Two syngeneic cell lines from human breast tissue: the aneuploid mammary epithelial (Hs578T) and the diploid myoepithelial (Hs578Bst) cell lines. J Natl Cancer Inst. 1977, 58: 1795-1806.
Möbus VJ, Moll R, Gerharz CD, Kieback DG, Merk O, Runnebaum IB, Linner S, Dreher L, Grill HJ, Kreienberg R: Differential characteristics of two new tumorigenic cell lines of human breast carcinoma origin. Int J Cancer. 1998, 77: 415-423. 10.1002/(SICI)1097-0215(19980729)77:3<415::AID-IJC18>3.0.CO;2-6
The University of Michigan Human Breast Cancer Cell Lines (SUM-LINES). http://www.cancer.med.umich.edu/breast_cell/Production/index.html
Gioanni J, Le François D, Zanghellini E, Mazeau C, Ettore F, Lambert JC, Schneider M, Dutrillaux B: Establishment and characterisation of a new tumorigenic cell line with a normal karyotype derived from a human breast adenocarcinoma. Br J Cancer. 1990, 62: 8-13.
Theillet C, Adelaïde J, Louason G, Bonnet-Dorion F, Jacquemier J, Adnane J, Longy M, Katsaros D, Sismondi P, Gaudray P, Birnbaum D: FGFRI and PLAT genes and DNA amplification at 8p12 in breast and ovarian cancers. Genes Chromosomes Cancer. 1993, 7: 219-226. 10.1002/gcc.2870070407
Adélaïde J, Finetti P, Bekhouche I, Repellini L, Geneix J, Sircoulomb F, Charafe-Jauffret E, Cervera N, Desplans J, Parzy D, Schoenmakers E, Viens P, Jacquemier J, Birnbaum D, Bertucci F, Chaffanet M: Integrated profiling of basal and luminal breast cancers. Cancer Res. 2007, 67: 11565-11575. 10.1158/0008-5472.CAN-07-2536
Olshen AB, Venkatraman ES, Lucito R, Wigler M: Circular binary segmentation for the analysis of array-based DNA copy number data. Biostatistics. 2004, 5: 557-572. 10.1093/biostatistics/kxh008
Irizarry RA, Hobbs B, Collin F, Beazer-Barclay YD, Antonellis KJ, Scherf U, Speed TP: Exploration, normalization, and summaries of high density oligonucleotide array probe level data. Biostatistics. 2003, 4: 249-264. 10.1093/biostatistics/4.2.249
McCarroll SA, Kuruvilla FG, Korn JM, Cawley S, Nemesh J, Wysoker A, Shapero MH, de Bakker PI, Maller JB, Kirby A, Elliott AL, Parkin M, Hubbell E, Webster T, Mei R, Veitch J, Collins PJ, Handsaker R, Lincoln S, Nizzari M, Blume J, Jones KW, Rava R, Daly MJ, Gabriel SB, Altshuler D: Integrated detection and population-genetic analysis of SNPs and copy number variation. Nat Genet. 2008, 40: 1166-1174. 10.1038/ng.238
Iafrate AJ, Feuk L, Rivera MN, Listewnik ML, Donahoe PK, Qi Y, Scherer SW, Lee C: Detection of large-scale variation in the human genome. Nat Genet. 2004, 36: 949-951. 10.1038/ng1416
Beroukhim R, Getz G, Nghiemphu L, Barretina J, Hsueh T, Linhart D, Vivanco I, Lee JC, Huang JH, Alexander S, Du J, Kau T, Thomas RK, Shah K, Soto H, Perner S, Prensner J, Debiasi RM, Demichelis F, Hatton C, Rubin MA, Garraway LA, Nelson SF, Liau L, Mischel PS, Cloughesy TF, Meyerson M, Golub TA, Lander ES, Mellinghoff IK, Sellers WR: Assessing the significance of chromosomal aberrations in cancer: methodology and application to glioma. Proc Natl Acad Sci USA. 2007, 104: 20007-200012. 10.1073/pnas.0710052104
Bertucci Finetti P, Cervera N, Charafe-Jauffret E, Mamessier E, Adélaïde J, Debono S, Houvenaeghel G, Maraninchi D, Viens P, Charpin C, Jacquemier J, Birnbaum D: Gene expression profiling shows medullary breast cancer is a subgroup of basal breast cancers. Cancer Res. 2006, 66: 4636-4644. 10.1158/0008-5472.CAN-06-0031
Hu Z, Fan C, Oh DS, Marron JS, He X, Qaqish BF, Livasy C, Carey LA, Reynolds E, Dressler L, Nobel A, Parker J, Ewend MG, Sawyer LR, Wu J, Liu Y, Nanda R, Tretiakova M, Ruiz Orrico A, Dreher D, Palazzo JP, Perreard L, Nelson E, Mone M, Hansen H, Mullins M, Quackenbush JF, Ellis MJ, Olopade OI, Bernard PS, Perou CM: The molecular portraits of breast tumors are conserved across microarray platforms. BMC Genomics. 2006, 7: 96- 10.1186/1471-2164-7-96
Benito M, Parker J, Du Q, Wu J, Xiang D, Perou CM, Marron JS: Adjustment of systematic microarray data biases. Bioinformatics. 2004, 20: 105-114. 10.1093/bioinformatics/btg385
Benjamini Y, Hochberg Y: Controlling the false discovery rate - a practical and powerful approach to multiple testing. J Roy Stat Soc B Met. 1995, 57: 289-300.
Snijders AM, Pinkel D, Albertson DG: Current status and future prospects of array-based comparative genomic hybridisation. Brief Funct Genomic Proteomic. 2003, 2: 37-45. 10.1093/bfgp/2.1.37
NCBI db SNP build 131 for human. http://www.ncbi.nlm.nih.gov/SNP
Charboneau AL, Singh V, Yu T, Newsham IF: Suppression of growth and increased cellular attachment after expression of DAL-1 in MCF-7 breast Cancer Cells. Int J Cancer. 2002, 100: 181-188. 10.1002/ijc.10470
Popovici C, Basset C, Bertucci F, Orsetti B, Adélaide J, Mozziconacci MJ, Conte N, Murati A, Ginestier C, Charafe-Jauffret E, Ethier SP, Lafage-Pochitaloff M, Theillet C, Birnbaum D, Chaffanet M: Reciprocal translocations in breast tumor cell lines: cloning of a t(3;20) that targets the FHIT gene. Genes Chromosomes Cancer. 2003, 35: 204-218. 10.1002/gcc.10107.
Climent J, Martinez-Climent JA, Blesa D, Garcia-Barchino MJ, Saez R, Sánchez-Izquierdo D, Azagra P, Lluch A, Garcia-Conde J: Genomic loss of 18p predicts an adverse clinical outcome in patients with high-risk breast cancer. Clin Cancer Res. 2002, 8: 3863-3869.
Gutmann DH, Donahoe J, Perry A, Lemke N, Gorse K, Kittiniyom K, Rempel SA, Gutierrez JA, Newsham IF: Loss of DAL-1, a protein 4.1-related tumor suppressor, is an important early event in the pathogenesis of meningiomas. Hum Mol Genet. 2000, 9: 1495-1500. 10.1093/hmg/9.10.1495
Trojer P, Li G, Sims RJ, Vaquero A, Kalakonda N, Boccuni P, Lee D, Erdjument-Bromage H, Tempst P, Nimer SD, Wang YH, Reinberg D: L3MBTL1, a histone-methylation-dependent chromatin lock. Cell. 2007, 129: 915-928. 10.1016/j.cell.2007.03.048
Kittiniyom K, Mastronardi M, Roemer M, Wells WA, Greenberg ER, Titus-Ernstoff L, Newsham IF: Allele-specific loss of heterozygosity at the DAL-1/4.1B (EPB41L3) tumor-suppressor gene locus in the absence of mutation. Genes Chromosomes Cancer. 2004, 40: 190-203. 10.1002/gcc.20034
Boccuni P, MacGrogan D, Scandura JM, Nimer SD: The human L(3)MBT polycomb group protein is a transcriptional repressor and interacts physically and functionally with TEL (ETV6). J Biol Chem. 2003, 278: 15412-15420. 10.1074/jbc.M300592200
Bench AJ, Li J, Huntly BJ, Delabesse E, Fourouclas N, Hunt AR, Deloukas P, Green AR: Characterization of the imprinted polycomb gene L3MBTL, a candidate 20q tumour suppressor gene, in patients with myeloid malignancies. Br J Haematol. 2004, 127: 509-518. 10.1111/j.1365-2141.2004.05278.x
MacGrogan D, Kalakonda N, Alvarez S, Scandura JM, Boccuni P, Johansson B, Nimer SD: Structural integrity and expression of the L3MBTL gene in normal and malignant hematopoietic cells. Genes Chromosomes Cancer. 2004, 41: 203-213. 10.1002/gcc.20087
Kim J, Daniel J, Espejo A, Lake A, Krishna M, Xia L, Zhang Y, Bedford MT: Tudor, MBT and chromo domains gauge the degree of lysine methylation. EMBO Rep. 2006, 7: 397-403.
Min J, Allali-Hassani A, Nady N, Qi C, Ouyang H, Liu Y, MacKenzie F, Vedadi M, Arrowsmith CH: L3MBTL1 recognition of mono- and dimethylated histones. Nat Struct Mol Biol. 2007, 14: 1229-1230. 10.1038/nsmb1340
Klymenko T, Papp B, Fischle W, Köcher T, Schelder M, Fritsch C, Wild B, Wilm M, Müller J: A Polycomb group protein complex with sequence-specific DNA-binding and selective methyl-lysine-binding activities. Genes Dev. 2006, 20: 1110-1122. 10.1101/gad.377406
Guo Y, Nady N, Qi C, Allali-Hassani A, Zhu H, Pan P, Adams-Cioaba MA, Amaya MF, Dong A, Vedadi M, Schapira M, Read RJ, Arrowsmith CH, Min J: Methylation-state-specific recognition of histones by the MBT repeat protein L3MBTL2. Nucleic Acids Res. 2009, 37: 2204-2210. 10.1093/nar/gkp086
Kikuchi S, Yamada D, Fukami T, Masuda M, Sakurai-Yageta M, Williams YN, Maruyama T, Asamura H, Matsuno Y, Onizuka M, Murakami Y: Promoter methylation of DAL-1/4.1B predicts poor prognosis in non-small cell lung cancer. Clin Cancer Res. 2005, 11: 2954-2961. 10.1158/1078-0432.CCR-04-2206
Singh V, Miranda TB, Jiang W, Frankel A, Roemer ME, Robb VA, Gutmann DH, Herschman HR, Clarke S, Newsham IF: DAL-1/4.1B tumor suppressor interacts with protein arginine N-methyltransferase 3 (PRMT3) and inhibits its ability to methylate substrates in vitro and in vivo. Oncogene. 2004, 23: 7761-7771. 10.1038/sj.onc.1208057
Yageta M, Kuramochi M, Masuda M, Fukami T, Fukuhara H, Maruyama T, Shibuya M, Murakami Y: Direct association of TSLC1 and DAL-1, two distinct tumor suppressor proteins in lung cancer. Cancer Res. 2002, 62: 5129-5133.
Yi C, McCarty JH, Troutman SA, Eckman MS, Bronson RT, Kissil JL: Loss of the putative tumor suppressor band 4.1B/Dal1 gene is dispensable for normal development and does not predispose to cancer. Mol Cell Biol. 2005, 25: 10052-10059. 10.1128/MCB.25.22.10052-10059.2005
Ibarra-Sanchez M, Simoncic PD, Nestel FR, Duplay P, Lapp WS, Tremblay ML: The T-cellprotein tyrosine phosphatase. Semin Immunol. 2000, 12: 379-386. 10.1006/smim.2000.0220
Klingler-Hoffmann M, Fodero-Tavoletti MT, Mishima K, Narita Y, Cavenee WK, Furnari FB, Huang HJ, Tiganis T: The protein tyrosine phosphatase TCPTP suppresses the tumorigenicity of glioblastoma cells expressing a mutant epidermal growth factor receptor. J Biol Chem. 2001, 276: 46313-46318. 10.1074/jbc.M106571200
Tsang WY, Spektor A, Vijayakumar S, Bista BR, Li J, Sanchez I, Duensing S, Dynlacht BD: Cep76, a centrosomal protein that specifically restrains centriole reduplication. Dev Cell. 2009, 16: 649-660. 10.1016/j.devcel.2009.03.004
Numoto M, Niwa O, Kaplan J, Wong KK, Merrell K, Kamiya K, Yanagihara K, Calame K: Transcriptional repressor ZF5 identifies a new conserved domain in zinc finger proteins. Nucleic Acids Res. 1993, 21: 3767-3775. 10.1093/nar/21.16.3767
Sobek-Klocke I, Disqué-Kochem C, Ronsiek M, Klocke R, Jockusch H, Breuning A, Ponstingl H, Rojas K, Overhauser J, Eichenlaub-Ritter U: The human gene ZFP161 on 18p11.21-pter encodes a putative c-myc repressor and is homologous to murine Zfp161 (Chr 17) and Zfp161-rs1 (X Chr). Genomics. 1997, 43: 156-64. 10.1006/geno.1997.4784
Kaplan J, Calame K: The ZiN/POZ domain of ZF5 is required for both transcriptional activation and repression. Nucleic Acids Res. 1997, 25: 1108-1116. 10.1093/nar/25.6.1108
Yokoro K, Yanagidani A, Obata T, Yamamoto S, Numoto M: Genomic cloning and characterization of the mouse POZ/zinc-finger protein ZF5. Biochem Biophys Res Commun. 1998, 246: 668-674. 10.1006/bbrc.1998.8675
Reymann S, Borlak J: Transcription profiling of lung adenocarcinomas of c-myc-transgenic mice: Identification of the c-myc regulatory gene network. BMC Syst Biol. 2008, 2: 46- 10.1186/1752-0509-2-46
Kloeker S, Wadzinski BE: Purification and identification of a novel subunit of protein serine/threonine phosphatase 4. J Biol Chem. 1999, 274: 5339-5347. 10.1074/jbc.274.9.5339
Wada T, Miyata T, Inagi R, Nangaku M, Wagatsuma M, Suzuki D, Wadzinski BE, Okubo K, Kurokawa K: Cloning and characterization of a novel subunit of protein serine/threonine phosphatase 4 from mesangial cells. J Am Soc Nephrol. 2001, 12: 2601-2608.
Zhou G, Mihindukulasuriya KA, MacCorkle-Chosnek RA, Van Hooser A, Hu MC, Brinkley BR, Tan TH: Protein phosphatase 4 is involved in tumor necrosis factor-alpha-induced activation of c-Jun N-terminal kinase. J Biol Chem. 2002, 277: 6391-6398. 10.1074/jbc.M107014200
Cohen PT, Philp A, Vázquez-Martin C: Protein phosphatase 4--from obscurity to vital functions. FEBS Lett. 2005, 579: 3278-3286. 10.1016/j.febslet.2005.04.070
Zhang X, Ozawa Y, Lee H, Wen YD, Tan TH, Wadzinski BE, Seto E: Histone deacetylase 3 (HDAC3) activity is regulated by interaction with protein serine/threonine phosphatase 4. Genes Dev. 2005, 19: 827-839. 10.1101/gad.1286005
Chowdhury D, Xu X, Zhong X, Ahmed F, Zhong J, Liao J, Dykxhoorn DM, Weinstock DM, Pfeifer GP, Lieberman JA: PP4-phosphatase complex dephosphorylates gamma-H2AX generated during DNA replication. Mol Cell. 2008, 31: 33-46. 10.1016/j.molcel.2008.05.016
Nakada S, Chen GI, Gingras A-C, Durocher D: PP4 is a gamma H2AX phosphatase required for recovery from the DNA damage checkpoint. EMBO Rep. 2008, 9: 1019-1026. Erratum in EMBO Rep, 2008, 9:1251., 10.1038/embor.2008.162
Thomas SM, Brugge JS: Cellular functions regulated by Src family kinases. Annu Rev Cell Dev Biol. 1997, 13: 513-609. 10.1146/annurev.cellbio.13.1.513
Pena SV, Melhem MF, Meisler AI, Cartwright CA: Elevated c-yes tyrosine kinase activity in premalignant lesions of the colon. Gastroenterology. 1995, 108: 117-124. 10.1016/0016-5085(95)90015-2
Barraclough J, Hodgkinson C, Hogg A, Dive C, Welman A: Increases in c-Yes expression level and activity promote motility but not proliferation of human colorectal carcinoma cells. Neoplasia. 2007, 9: 745-754. 10.1593/neo.07442
Kleber S, Sancho-Martinez I, Wiestler B, Beisel A, Gieffers C, Hill O, Thiemann M, Mueller W, Sykora J, Kuhn A, Schreglmann N, Letellier E, Zuliani C, Klussmann S, Teodorczyk M, Gröne HJ, Ganten TM, Sültmann H, Tüttenberg J, von Deimling A, Regnier-Vigouroux A, Herold-Mende C, Martin-Villalba A: Yes and PI3K bind CD95 to signal invasion of glioblastoma. Cancer Cell. 2008, 13: 235-248. 10.1016/j.ccr.2008.02.003
Van Haaften G, Dalgliesh GL, Davies H, Chen L, Bignell G, Greenman C, Edkins S, Hardy C, O'Meara S, Teague J, Butler A, Hinton J, Latimer C, Andrews J, Barthorpe S, Beare D, Buck G, Campbell PJ, Cole J, Forbes S, Jia M, Jones D, Kok CY, Leroy C, Lin ML, McBride DJ, Maddison M, Maquire S, McLay K, Menzies A, Mironenko T, Mulderrig L, Mudie L, Pleasance E, Shepherd R, Smith R, Stebbings L, Stephens P, Tang G, Tarpey PS, Turner R, Turrell K, Varian J, West S, Widaa S, Wray P, Collins VP, Ichimura K, Law S, Wong J, Yuen ST, Leung SY, Tonon G, DePinho RA, Tai YT, Anderson KC, Kahnoski RJ, Massie A, Khoo SK, Teh BT, Stratton MR, Futreal PA: Somatic mutations of the histone H3K27 demethylase gene UTX in human cancer. Nat Genet. 2009, 41: 521-523. 10.1038/ng.349
Figueroa ME, Lugthart S, Li Y, Erpelinck-Verschueren C, Deng X, Christos PJ, Schifano E, Booth J, van Putten W, Skrabanek L, Campagne F, Mazumdar M, Greally JM, Valk PJ, Löwenberg B, Delwel R, Melnick A: DNA methylation signatures identify biologically distinct subtypes in acute myeloid leukemia. Cancer Cell. 2010, 17: 13-27. 10.1016/j.ccr.2009.11.020
We are grateful to Drs. E. Charafe-Jauffret and J. Jacquemier for pathology data, to Pr. C. Chabannon for biobanking, to Dr. S. Olschwang for advices, and to the surgical department (Pr. G. Houvenaeghel). Frozen samples were provided by the IPC TumorBank (Authorization Number AC-2007-33). This work has been supported by Institut Paoli-Calmettes, Inserm, and grants from Ligue Nationale Contre Le Cancer (label DB) and Institut National du Cancer (Recherche translationnelle 2009).
The authors declare that they have no competing interests.
LAK and NC did sequence and qRT-PCR analyses, JA, IB, FS and AF aCGH experiments and analysis, PF and FB gene expression analysis, PV and SM supervised the study, DB and MC designed and supervised the study, LAK and MC wrote the manuscript. All authors read and approved the final manuscript.
Electronic supplementary material
Additional file 1:Supplementary Tables S1-S8. Table S1. Clinical and histological features of 307 breast tumor cases. Table S2. Primers used for L3MBTL4 sequence determination. Table S3. Association of genes with copy number alterations and L3MBTL4 genomic loss. Table S4A. The 77 tumors with L3MBTL4 loss and mutation. Table S4B. Correlations between clinical features of 305 BC and the loss of whole chromosome 18p. Table S5. Correlations between clinical features of 229 BC and L3MBTL4 gene expression. Table S6 - Other potential 18p TSG candidates. Table S7. Correlations between clinical features of 260 BC and EPB41L3 gene expression. Table S8. Correlations between clinical features of 260 BC and down regulated ZFP161 gene expression. (XLS 12 MB)
Additional file 2:Supplementary figure. Figure S1. The 18p is targeted by losses in breast cancer. On the top, combining the CNA frequency and gene copy number alterations level, the GISTIC algorithm plotted the score index observed in genomic profiles of 307 breast tumors as a function of chromosome 18 locations. The chromosome arm 18p was targeted by losses in more than 20% of tumor samples. The dotted line indicates the threshold of significance for the score. At the bottom, the figure shows only an 18p11.21-p11.32 region of 12.79 Mb including 64 loci as significant 18p losses (p < 10-5). L3MBTL4 and EPB41L3 are contained within this region. (TIFF 2 MB)
About this article
Cite this article
Addou-Klouche, L., Adélaïde, J., Finetti, P. et al. Loss, mutation and deregulation of L3MBTL4 in breast cancers. Mol Cancer 9, 213 (2010) doi:10.1186/1476-4598-9-213
- Tumor Suppressor Gene
- Molecular Subtype
- Malignant Brain Tumor
- Copy Number Aberration
- Copy Number Loss