Abstract
ANRIL, a long noncoding RNA (lncRNA), has recently been reported to have a direct role in recruiting polycomb repressive complexes PRC2 and PRC1 to regulate the expression of the p15/CDKN2B-p16/CDKN2A-p14/ARF gene cluster. Expression analysis of ANRIL, EZH2, SUZ12, EED, JARID2, CBX7, BMI1, p16, p15, and p14/ARF genes was evaluated in a large cohort of invasive breast carcinomas (IBC, n = 456) by qRT-PCR and immunohistochemistry (IHC) was performed on CBX7, EZH2, p14, p15, p16, H3K27me3, and H3K27ac. We observed significant overexpression in IBCs of ANRIL (19.7%) and EZH2 (77.0%) and an underexpression of CBX7 (39.7%). Correlations were identified between these genes, their expression patterns, and several classical clinical and pathologic parameters, molecular subtypes, and patient outcomes, as well as with proliferation, epithelial–mesenchymal transition, and breast cancer stem cell markers. Multivariate analysis revealed that combined EZH2/CBX7 status is an independent prognostic factor (P = 0.001). In addition, several miRNAs negatively associated with CBX7 underexpression and EZH2 overexpression. These data demonstrate a complex pattern of interactions between lncRNA ANRIL, several miRNAs, PRC2/PRC1 subunits, and p15/CDKN2B-p16/CDKN2A-p14/ARF locus and suggest that their expression should be considered together to evaluate antitumoral drugs, in particular the BET bromodomain inhibitors.
Implications: This study suggests that the global pattern of expression rather than expression of individual family members should be taken into account when defining functionality of repressive Polycomb complexes and therapeutic targeting potential. Mol Cancer Res; 14(7); 623–33. ©2016 AACR.
This article is featured in Highlights of This Issue, p. 587
Introduction
Invasive breast carcinomas (IBC) are highly heterogeneous tumors, and triple-negative subtype (TNC) remains a major cause of death in women. Although more than 90% of breast tumors are clinically localized, about 50% of them relapse within 5 years. Thus, identification of new prognostic factors and potential targeted therapies is crucial to improve outcome of patients with IBC.
Changes in the epigenetic landscape, including histone modifications, DNA methylation, and noncoding RNAs (ncRNA,) altered expression are now considered as a new hallmark of cancer (1). Polycomb repressive complexes (PRC) play important roles in chromatin remodeling and inhibition of transcription, suppressor genes silencing, and interconnection with major signaling pathways (2). Polycomb group protein subunits are essential regulators of embryonic stem cell pluripotency and early developmental cell fate decisions that are often deregulated in cancer. Two multiprotein complexes, PRC2 and PRC1, act concertedly and sequentially in transcriptional repression via two distinct histone modifications, trimethylation of lysine 27 on histone H3 (H3K27me3) and monoubiquitination of histone H2A (H2AK119ub). PRC2 contains mainly four subunits (EZH2, SUZ12, EED, and JARID2) and is involved in initiation of silencing by catalyzing methylation of histone H3 (3). PRC1 also comprises mainly four subunits (BMI1, PHC, CBX7, and RING1) and is implicated in maintenance of silencing by catalyzing monoubiquitination of histone H2A (ref. 4; Supplementary Fig. S1).
PRC2 and PRC1 have been described to interact with long noncoding RNAs (lncRNA). LncRNAs are defined by a length ranged from 200 bp to 100 kbp and their number is in constant increase: 48,680 lncRNAs are at present identified (5–7). LncRNAs are important regulators coordinating expression of protein-coding genes nearby (cis-regulation) or at distance (trans-regulation). LncRNAs function as guide, tethers, scaffolds, and decoys and their mechanisms of action are located at epigenetics, translational, and posttranslational levels (8). Accumulating data suggest that deregulation of lncRNAs is pivotal in cancer initiation, progression, and metastatic spread. Among important lncRNAs deregulated in cancer, ANRIL (antisense noncoding RNA in the INK4 locus) is encoded in the chromosome 9p21 region (9) and has been reported to have a direct role in recruiting PRC2 and PRC1 complexes to specific loci and in repressing gene expression (10). ANRIL is transcribed as a 3.8-kb lncRNA in the opposite direction from the p15/CDKN2B-p16/CDKN2A-p14/ARF gene cluster. Common disease genome-wide association studies (GWAS) have identified the ANRIL gene as a shared genetic susceptibility locus to coronary disease, intracranial aneurysm, type 2 diabetes, and numerous cancers (11). Increased ANRIL expression levels were observed in prostate carcinomas and involved in repression of the CDKN2B/CDKN2A/ARF gene cluster in cis by directly binding to PRC complexes (10). EZH2 (PRC2) and CBX7 (PRC1) act as transcriptional repressors of many genes and are particularly implicated in silencing via ANRIL of the CDKN2B/CDKN2A/ARF locus (12). However, the functional role and underlying mechanism of action of ANRIL in breast carcinogenesis still remain unclear (13).
The aim of the present study was to analyze at RNA and protein levels, the ribonucleoproteic network composed of the lncRNA ANRIL, the two polycomb complexes PRC2/PRC1, and the downstream CDKN2B/CDKN2A/ARF gene cluster, as well as several miRNAs targeting PRC units, in IBCs and to evaluate their clinical significance.
Materials and Methods
Patients and samples
Samples of 456 primary unilateral invasive primary breast tumors excised from women managed at Institut Curie (Saint-Cloud, France) from 1978 to 2008 have been analyzed. All patients cared in our institution before 2007 were informed that their tumor samples might be used for scientific purposes and had the opportunity to decline. Since 2007, patients treated in our institution have given their approval by signed informed consent. This study was approved by the local ethics committee (Breast Group of Rene Huguenin Hospital). Samples were immediately stored in liquid nitrogen until RNA extraction. A tumor sample was considered suitable for this study if the proportion of tumor cells exceeded 70%. The patients (mean age, 61.7 years; range, 31–91 years) all met the following criteria: primary unilateral nonmetastatic breast carcinoma for which complete clinical, histologic, and biologic data were available; no radiotherapy or chemotherapy before surgery; and full follow-up at Institut Curie. Treatment consisted of modified radical mastectomy in 283 cases (63.9%) and breast-conserving surgery plus locoregional radiotherapy in 160 cases (36.1%). The patients had a physical examination and routine chest radiography every 3 months for 2 years and then annually. Mammograms were done annually. Adjuvant therapy was administered to 369 patients, consisting of chemotherapy alone in 91 cases, hormone therapy alone in 176 cases, and both treatments in 102 cases. The histologic type and the number of positive axillary nodes were established at the time of surgery. The malignancy of infiltrating carcinomas was scored according to Scarff Bloom Richardson (SBR) histoprognostic system. Estrogen receptor (ERα), progesterone receptor (PR), and human EGF receptor 2 (ERBB2) status was determined at the protein level by using biochemical methods [dextran-coated charcoal method, enzyme immunoassay, or immunohistochemistry (IHC)] and confirmed by real-time quantitative RT-PCR assays (14, 15). The population was divided into 4 groups according to HR (ERα and PR) and ERBB2 status, as follows: two luminal subtypes [HR+ (ERα+ or PR+)/ERBB2+ (n = 54)] and [HR+ (ERα+ or PR+)/ERBB2− (n = 290)]; an ERBB2+ subtype [HR− (ERα− and PR−)/ERBB2+ (n = 45)]; and a triple-negative subtype [HR− (ERα− and PR−)/ERBB2− (n = 69)]. Standard prognostic factors are shown in Supplementary Table S1. Patients (n = 169) developed metastasis during a median follow-up of 8.9 years (range, 6 months to 29 years). Ten specimens of adjacent normal breast tissue from patients with breast cancer (n = 7) and normal breast tissue from women undergoing cosmetic breast surgery (n = 3) were used as sources of normal RNA.
RNA extraction
Total RNA was extracted from breast tumor samples by using acid-phenol guanidium as previously described (16). RNA quality was determined by electrophoresis through agarose gels, staining with ethidium bromide, and visualization of the 18S and 28S RNA bands under ultraviolet light.
Real-time RT-PCR
LncRNA and protein-coding genes expression analysis.
ANRIL, EZH2, SUZ12, EED, JARID2, CBX7, BMI1, P16/CDKN2A, P15/CDKN2B, and P14/ARF gene mRNA expression levels were quantified by using real time RT-PCR in a retrospective series of 456 well-characterized tumors. Quantitative values were obtained from the cycle number (Ct value) at which the increase in the fluorescence signal associated with exponential growth of PCR products started to be detected by the laser detector of the ABI Prism 7900 Sequence Detection System (Perkin-Elmer Applied Biosystems), using PE Biosystems analysis software according to the manufacturer's manuals. The precise amount of total RNA added to each reaction mix (based on optical density) and its quality (i.e., lack of extensive degradation) are both difficult to assess. We therefore also quantified transcripts of the TBP gene (Genbank accession: NM_003194) encoding the TATA box–binding protein (a component of the DNA-binding protein complex TFIID) as an endogenous RNA control and normalized each sample on the basis of its TBP content. We selected TBP as an endogenous control because the prevalence of its transcripts is moderate and because there are no known TBP retropseudogenes (retropseudogenes lead to coamplification of contaminating genomic DNA and thus interfere with RT-PCR, despite the use of primers in separate exons; ref. 14). Results, expressed as N-fold differences in target gene expression relative to the TBP gene and termed "Ntarget," were determined as Ntarget = 2ΔCt_sample, where the ΔCt value of the sample was determined by subtracting the average Ct value of the target gene from the average Ct value of the TBP gene. The Ntarget values of the samples were subsequently normalized such that the median of the Ntarget values for the 10 normal breast tissues was 1. The primers for TBP, ANRIL, and the 9 protein-coding genes were chosen with the assistance of the Oligo 6.0 program (National Biosciences). We scanned the dbEST and nr databases to confirm the total gene specificity of the nucleotide sequences chosen for the primers and the absence of SNPs. To avoid amplification of contaminating gDNA, 1 of the 2 primers was placed at the junction between 2 exons or on 2 different exons. Agarose gel electrophoresis was used to verify the specificity of PCR amplicons. The conditions of cDNA synthesis and PCR were as described (17).
miRNAs expression analysis.
miRNAs were isolated with the RNA extraction procedure used for the protein-coding transcripts (total RNA extraction). Reverse transcription was performed with the QIAGEN miScript Reverse Transcription Kit, according to the manufacturer's protocol (QIAGEN, GmbH). Specific miRNAs were quantified by real-time PCR with the QIAGEN miScript SYBR Green PCR Kit (QIAGEN). The small nucleolar RNU44 was used as an internal control. The relative expression level of each miRNA, expressed as N-fold difference in target miRNA expression relative to RNU44, and termed “Ntarget”, was calculated as follows: Ntarget = 2ΔCt_sample. The ΔCt value of a given sample was determined by subtracting the Ct value of the target miRNA from the Ct value of RNU44. The Ntarget values of the samples were subsequently normalized so that the median Ntarget value of samples with low level of EZH2 and CBX7 transcripts was 1.
IHC
We performed IHC assay by using CBX7 (Novus, polyclonal, rabbit, NBP1-79042, 1/250, pH6), EZH2 (Novocastra, monoclonal mouse, 6A10, 1/100, pH6), p15 (Abcam, polyclonal, rabbit, ab53034, 1/50, pH6), p16 (CINtec p16, Ventana 705-4713, mouse, monoclonal, E6H4 prediluted, 1 μg/mL), H3K27me2/3 [Abcam, anti-histone H3 (di- + tri-methyl K27), ab6147, mouse, monoclonal, 1/200, pH6], and H3K27ac [Abcam, ab 4729, Rabbit polyclonal to Histone H3 (acetyl K27), 1/400, pH6] antibodies in a series of 80 IBCs. Paraffin-embedded tissue blocks, obtained at the time of the initial diagnosis, were retrieved from the archives of the Department of Biopathology, Institut Curie. Sections of 3 μm were cut with a microtome from the paraffin-embedded tissue blocks of normal breast tissue, preinvasive lesions, and IBCs. Tissue sections were deparaffinized and rehydrated through a series of xylene and ethanol washes. Briefly, key figures included: (i) antigen retrieval in 0.1 mol/L citrate buffer, pH 6 (Biocare) in a pressure cooker (4 minutes); (ii) blocking of endogenous peroxidase activity by immersing sections in 3% hydrogen peroxide in methanol for 15 minutes and subsequently rinsing them in water and PBS; (iii) incubation with primary antibodies against the targeted antigen; (iv) immunodetection with a biotin-conjugated secondary antibody formulation that recognizes rabbit and mouse immunoglobulins, followed by peroxidase-labeled streptavidin and linking with a rabbit biotinylated antibody against mouse immunoglobulin G (DAKO SA); and (v) chromogenic revelation with AEC and counterstaining with Mayer's hematoxylin. All immunostaining was processed by using a DAKO automated immunostaining device. The specificity of the antibodies was confirmed by doing IHC studies with the same protocol on paraffin-embedded human tissue sections containing lymphocytes. A semiquantitative histologic score (H-score = intensity × frequency) was performed (score 0 = negative staining, score 1 = weak staining, score 2 = moderate staining, score 3 = strong staining).
Statistical analysis
The distributions of target mRNA levels were characterized by their median values and ranges. Relationships between mRNA levels of the different target genes and between mRNA (and protein) levels and clinical parameters were identified by using nonparametric tests, namely, the χ2 test (relation between 2 qualitative parameters), the Mann–Whitney U test (relation between 1 qualitative and 1 quantitative parameter), and the Spearman rank correlation test (relation between 2 quantitative parameters). Differences were considered significant at confidence levels greater than 95% (P < 0.05). Metastasis-free survival (MFS) was determined as the interval between initial diagnosis and detection of the first metastasis. Survival distributions were estimated by the Kaplan–Meier method, and the significance of differences between survival rates was ascertained with the log-rank test. The Cox proportional hazards regression model was used to assess prognostic significance, and the results are presented as HRs and 95% confidence intervals (CI). Hierarchical clustering was performed with GenANOVA software (18).
Results
ANRIL and EZH2 are upregulated, whereas CBX7 is downregulated in IBCs
We measured mRNA levels of the lncRNA ANRIL and 6 genes belonging to the two repressive polycomb PRC2 and PRC1 complexes (PRC2: EZH2, SUZ12, EED, and JARID2; PRC1: BMI1 and CBX7) in a series of 456 patients with unilateral invasive breast tumors and in a series of 10 normal breast tissues (including adjacent normal breast tissue from patients with breast cancer and normal breast tissue from women undergoing cosmetic breast surgery) by using quantitative RT-PCR assays (Table 1). We did not observe significant differences concerning the expression profiles of the 7 genes tested between the adjacent normal breast tissue from patients with breast cancer (7 samples) and normal breast tissue from women undergoing cosmetic breast surgery (3 patients; data not shown).The mRNA values of the breast cancer samples were normalized such that the median of the 10 normal breast tissue mRNA values was 1. To determine the cutoff point for altered target genes expression in breast cancer tissues, the Ntarget value, calculated as described in Materials and Methods, was determined for the 10 normal breast RNA samples. As these normal values were consistently between 0.39 (CBX7) and 2.45 (ANRIL), values of 0.33 or less were considered to represent underexpression, and values of 3 or more to represent overexpression of these genes in tumor samples. We have previously used the same approach to determine cutoff points for tumor gene altered expression (14, 19). In our series of 456 breast carcinomas, we observed overexpression of ANRIL in 19.7% of IBCs (median = 1.58; minimum = 0.05; maximum = 13.5). Concerning Polycomb subunits, we observed a marked overexpression of EZH2 in 77.0% of IBCs (median = 5.09; minimum = 0.76; maximum = 48.3) and to a lesser extent of BIM1 (median = 1.23; minimum = 0.00; maximum = 14.0) in 10.1% of IBCs and an unexpected underexpression of CBX7 in 39.7% of IBCs (median = 0.38; minimum = 0.00; maximum = 2.59). SUZ12, EED, and JARID2 were overexpressed only in 2.6%, 1.8%, and 5.1% of IBCs, respectively.
ANRIL pathway genes mRNA expression levels in the series of 456 breast tumors
Genes . | Median Ct of normal breast tissue (n = 10) . | Normal breast tissue (n = 10) . | Breast tumors (n = 456) . | Percentage of underexpressed tumors (Ntarget < 0.33) . | Percentage of normal expressed tumors . | Percentage of overexpressed tumors (Ntarget > 3) . |
---|---|---|---|---|---|---|
ANRIL | 34.07 (31.91–35.96)a | 1.0 (0.35–2.45)b | 1.58 (0.05–13.5)b | 0.9c | 79.4c | 19.7c |
Polycomb complex PRC2 genes (n = 4) | ||||||
EZH2 | 32.39 (31.23–34.30) | 1.0 (0.48–2.32) | 5.09 (0.76–48.3) | 0 | 23.0 | 77.0 |
SUZ12 | 28.26 (27.17–29.98) | 1.0 (0.56–1.25) | 1.23 (0.43–59.2) | 0 | 97.4 | 2.6 |
EEDd | 29.77 (28.70–33.16) | 1.0 (0.58–1.84) | 1.21 (0.03–7.74) | 3.1 | 95.1 | 1.8 |
JARID2e | 28.63 (27.3–30.55) | 1.0 (0.83–1.46) | 1.37 (0.34–8.53) | 0 | 94.9 | 5.1 |
Polycomb complex PRC1 genes (n = 2) | ||||||
BMI1 | 28.40 (26.91–30.22) | 1.0 (0.59–1.47) | 1.23 (0.00–14.0) | 4.2 | 85.8 | 10.1 |
CBX7 | 28.99 (27.78–31.25) | 1.0 (0.39–1.62) | 0.38 (0.00–2.59) | 39.7 | 60.3 | 0 |
ANRIL regulated genes (n = 3) | ||||||
ARF | 32.93 (31.69–34.75) | 1.0 (0.21–2.41) | 2.28 (0.00—105) | 3.3 | 56.8 | 39.9 |
P16f | 37.55 (34.64–50) | 0.0 (0.0–6.95) | 0.65 (0.0–63.4) | 0 | 84.2 | 15.8 |
P15 | 30.89 (29.21–33.74) | 1.0 (0.11-2.91) | 1.62 (0.00–40.5) | 7.0 | 71.3 | 21.7 |
Genes . | Median Ct of normal breast tissue (n = 10) . | Normal breast tissue (n = 10) . | Breast tumors (n = 456) . | Percentage of underexpressed tumors (Ntarget < 0.33) . | Percentage of normal expressed tumors . | Percentage of overexpressed tumors (Ntarget > 3) . |
---|---|---|---|---|---|---|
ANRIL | 34.07 (31.91–35.96)a | 1.0 (0.35–2.45)b | 1.58 (0.05–13.5)b | 0.9c | 79.4c | 19.7c |
Polycomb complex PRC2 genes (n = 4) | ||||||
EZH2 | 32.39 (31.23–34.30) | 1.0 (0.48–2.32) | 5.09 (0.76–48.3) | 0 | 23.0 | 77.0 |
SUZ12 | 28.26 (27.17–29.98) | 1.0 (0.56–1.25) | 1.23 (0.43–59.2) | 0 | 97.4 | 2.6 |
EEDd | 29.77 (28.70–33.16) | 1.0 (0.58–1.84) | 1.21 (0.03–7.74) | 3.1 | 95.1 | 1.8 |
JARID2e | 28.63 (27.3–30.55) | 1.0 (0.83–1.46) | 1.37 (0.34–8.53) | 0 | 94.9 | 5.1 |
Polycomb complex PRC1 genes (n = 2) | ||||||
BMI1 | 28.40 (26.91–30.22) | 1.0 (0.59–1.47) | 1.23 (0.00–14.0) | 4.2 | 85.8 | 10.1 |
CBX7 | 28.99 (27.78–31.25) | 1.0 (0.39–1.62) | 0.38 (0.00–2.59) | 39.7 | 60.3 | 0 |
ANRIL regulated genes (n = 3) | ||||||
ARF | 32.93 (31.69–34.75) | 1.0 (0.21–2.41) | 2.28 (0.00—105) | 3.3 | 56.8 | 39.9 |
P16f | 37.55 (34.64–50) | 0.0 (0.0–6.95) | 0.65 (0.0–63.4) | 0 | 84.2 | 15.8 |
P15 | 30.89 (29.21–33.74) | 1.0 (0.11-2.91) | 1.62 (0.00–40.5) | 7.0 | 71.3 | 21.7 |
aMedian (range) of gene Ct values (cycle threshold).
bMedian (range) of gene mRNA levels; the mRNA values of the samples were normalized such that the median of the 10 normal breast tissues mRNA values was 1.
cPercentage of underexpressing, normal, and overexpressing tumors using cutoffs of Ntarget < 0.33 and Ntarget > 3.
dData available in 446 samples.
eData available in 454 samples.
fThe mRNA values of the samples were normalized such that a Ct value of 35 was 1.
We performed an IHC analysis by using anti-EZH2 and anti-CBX7 antibodies in a series of 80 IBCs (standard prognostic factors are shown in Supplementary Table S2). We identified a moderate-to-intense nuclear staining of tumor cells (H-score = 2–3) with EZH2 antibodies in 75.9% of IBCs (n = 63 of 80) and an absence or a slight nuclear and cytoplasmic staining of tumor cells (H-score = 0–1) with CBX7 antibodies in 63.8% of IBCs (n = 51 of 80; Fig. 1).
IHC staining for EZH2 and CBX7. Nuclear overexpression of EZH2 (H-score = 2 and 3) in cancer cells was observed in 75.2% of IBCs and nuclear EZH2 underexpression in 24.8% of IBCs. Nuclear and cytoplasmic under expression of CBX7 (H-score = 0 and 1) was observed in 63.8% of IBCs and nuclear and cytoplasmic CBX7 overexpression in 36.2% of IBCs. Score 0, no cytoplasmic staining for CBX7 or nuclear staining for EZH2 is seen in tumor cells; Score 1, weak cytoplasmic staining for CBX72 and weak nuclear staining for EZH is seen in a subset of tumor cells; Score 2, moderate cytoplasmic staining for CBX7 and moderate nuclear staining for EZH2 is seen in a subset of tumor cells; Score 3: strong and diffuse cytoplasmic staining for CBX7, and strong nuclear staining for EZH2 is seen in most of tumor cells.
IHC staining for EZH2 and CBX7. Nuclear overexpression of EZH2 (H-score = 2 and 3) in cancer cells was observed in 75.2% of IBCs and nuclear EZH2 underexpression in 24.8% of IBCs. Nuclear and cytoplasmic under expression of CBX7 (H-score = 0 and 1) was observed in 63.8% of IBCs and nuclear and cytoplasmic CBX7 overexpression in 36.2% of IBCs. Score 0, no cytoplasmic staining for CBX7 or nuclear staining for EZH2 is seen in tumor cells; Score 1, weak cytoplasmic staining for CBX72 and weak nuclear staining for EZH is seen in a subset of tumor cells; Score 2, moderate cytoplasmic staining for CBX7 and moderate nuclear staining for EZH2 is seen in a subset of tumor cells; Score 3: strong and diffuse cytoplasmic staining for CBX7, and strong nuclear staining for EZH2 is seen in most of tumor cells.
The p15/CDKN2B-p16/CDKN2A-p14/ARF cluster is unexpectedly not silenced in IBCs
We measured mRNA levels of p15/CDKN2B, p16/CDKN2A, and p14/ARF in the series of 456 patients. We showed marked overexpression of p16, p14/ARF, and p15, respectively, in 15.8%, 39.9%, and 21.7% of IBCs (Table 1).
We studied protein expression of p14, p16, and p15 in IBCs by using IHC in our series of 80 breast tumors. We observed nuclear and cytoplasmic overexpression of cancer cells (H-score = 2–3) with anti-p14, p16, and p15 antibodies in, respectively, 41.2% (n = 33 of 80), 51.3% (n = 41 of 80), and 37.5% (n = 30 of 80) of IBCs (Supplementary Fig. S2).
PRC2/PRC1 activity status revealed decrease of H3K27me3 expression levels and increase of H3K27ac expression levels in IBCs
To evaluate PRC2/PRC1 repressive activity status in breast tumors, we performed an IHC analysis in our series of 80 IBCs by using anti-H3K27me3 and anti-H3K27ac antibodies. We could identify an absence or a slight nuclear staining of cancer cells (H-score = 0–1) with H3K27me3 antibody in 76.3% of IBCs (n = 61 of 80) and a moderate-to-intense nuclear staining of tumor cells (H-score = 2–3) with H3K27ac antibody in 73.8% of IBCs (n = 59 of 80; Supplementary Fig. S3). An expected negative correlation was observed between staining of H3K27me3 and H3K27ac (P = 0.0000073).
ANRIL, PRC2/PRC1 subunits and p15/CDKN2B-p16/CDKN2A-p14/ARF cluster expression levels are associated with clinicopathologic parameters, molecular subtypes, and patient outcome
Clinicopathologic parameters.
ANRIL mRNA expression level was exclusively and weakly correlated with ERα (P = 0.038) and PR (P = 0.011) status (Supplementary Table S3).
Concerning the PRC2 complex, EZH2 mRNA expression level was strongly associated with SBR histologic grade (P < 10−7), ERα status (P = 3 × 10−7), and PR status (P = 3 × 10−7), moderately associated with ERBB2 status (P = 0.00020) and tumor size (P = 0.0062; Supplementary Table S4). Expression of SUZ12 was exclusively associated with lymph node status (P < 10−7; Supplementary Table S5), EED with SBR histologic grade (P = 0.0011), and PR status (P = 0.0028; Supplementary Table S6) and JARID2 with ERα status (P = 0.0027) and ERBB2 status (P = 0.0035; Supplementary Table S7).
Concerning the PRC1 complex, CBX7 mRNA expression level was highly significantly correlated with SBR histologic grade (P = 0.000025), ER status (P = 0.000011), and PR status (P = 0.0000013; Supplementary Table S8). BMI1 was weakly associated with ERα status (P = 0.036) but not with any of other clinical predictive factors (Supplementary Table S9).
Finally, ARF/p14 and p16 mRNA expression levels were highly correlated with SBR histological grade (P < 10−7 and P = 0.000019, respectively), ERα status (P = 1.8 × 10−7 and P < 10−7, respectively), and PR status (P = 1.3 × 10−5 and P = 1.8 × 10−6, respectively; Supplementary Table S10), whereas p15 was moderately correlated with ERα status (P = 0.009) and PR status (P = 0.0008), but not with SBR histologic grade, like ARF/p14 and p16 (Supplementary Tables S11 and S12).
It is also noteworthy that none of these 10 gene expressions showed significant link with the adjuvant treatment status including hormone therapy alone (176 patients), chemotherapy alone (91 patients), both hormone therapy and chemotherapy (102 patients), and no adjuvant therapy (87 patients; Supplementary Tables S3–S12).
Breast cancer molecular subtypes.
By using HR (ERα and PR) and ERBB2 status, we subdivided our total population of IBCs (n = 456) into 4 subgroups: HR+/ERBB2+ (n = 54), HR+/ERBB2− (n = 289), HR−/ERBB2+ (n = 45), and HR−/ERBB2− (n = 68). ANRIL, PRC1/2 genes, and p14/p15/p16 mRNA levels of expression in the different breast cancer molecular subtypes are shown in Supplementary Table S13. A strong correlation was observed between molecular subgroups and ANRIL (P = 0.00013), EZH2 (P < 10−7), JARID2 (P = 0.00090), CBX7 (P = 0.000020), and p14/ARF and p16 (P < 10−7) mRNA levels. High frequencies of ANRIL, p14/ARF, and p16 deregulated expressions (under- or overexpressions) were mainly observed in triple-negative subtypes, EZH2 overexpression, and CBX7 underexpression in the two HR− subtypes, and JARID2 overexpression in HR−/ERBB2+ subtypes (Supplementary Table S13).
Patient outcome.
We assessed the impact of variations of ANRIL, EZH2, SUZ12, EED, JARID2, CBX7, BMI1, p14/ARF, p15, and p16 mRNA levels on patient outcome. We used a log-rank test to identify relations between MFS and mRNA levels of these 10 genes (Table 2). EZH2 overexpression and CBX7 underexpression were significantly associated with shorter MFS (P = 0.000045 and P = 0.0051, respectively). We observed also a light significant difference in MFS among patients with p16 overexpression (P = 0.025). MFS was not influenced by expression status of ANRIL and other genes analyzed (i.e. SUZ12, EED, JARID2,BMI1, ARF, and p15).
Relationship between ANRIL pathway gene mRNA levels and MFS in the 456 breast tumors
Gene mRNA expression . | Population (%) . | Number of metastases (%) . | Pa . |
---|---|---|---|
Total population (%) | 456 (100.0) | 169 (37.1) | |
ANRIL | |||
Non-overexpression | 366 (80.3) | 129 (76.3) | 0.062 (NS) |
Overexpression | 90 (19.7) | 40 (23.7) | |
EZH2 | |||
Non-overexpression | 105 (23.0) | 20 (11.8) | 0.000045 |
Overexpression | 351 (77.0) | 149 (88.2) | |
SUZ12 | |||
Non-overexpression | 444 (97.4) | 163 (96.4) | 0.71 (NS) |
Overexpression | 12 (2.6) | 6 (3.6) | |
EEDb | |||
Underexpression | 14 (3.1) | 3 (1.8) | 0.20 (NS) |
Nonunderexpression | 432 (96.9) | 161 (98.2) | |
JARID2c | |||
Non-overexpression | 431 (94.9) | 161 (96.4) | 0.80 (NS) |
Overexpression | 23 (5.1) | 6 (3.6) | |
BMI | |||
Non-overexpression | 410 (89.9) | 148 (87.6) | 0.49 (NS) |
Overexpression | 46 (10.1) | 21 (12.4) | |
CBX7 | |||
Underexpression | 181 (39.7) | 79 (46.7) | 0.0051 |
Non-underexpression | 275 (60.3) | 90 (53.3) | |
ARF | |||
Non-overexpression | 274 (60.1) | 96 (56.8) | 0.086 (NS) |
Overexpression | 182 (39.9) | 73 (43.2) | |
P16 | |||
Normal expression | 384 (84.2) | 137 (81.1) | 0.025 |
Overexpression | 72 (15.8) | 32 (18.9) | |
P15 | |||
Non-overexpression | 357 (78.3) | 128 (75.7) | 0.090 (NS) |
Overexpression | 99 (21.7) | 41 (24.3) |
Gene mRNA expression . | Population (%) . | Number of metastases (%) . | Pa . |
---|---|---|---|
Total population (%) | 456 (100.0) | 169 (37.1) | |
ANRIL | |||
Non-overexpression | 366 (80.3) | 129 (76.3) | 0.062 (NS) |
Overexpression | 90 (19.7) | 40 (23.7) | |
EZH2 | |||
Non-overexpression | 105 (23.0) | 20 (11.8) | 0.000045 |
Overexpression | 351 (77.0) | 149 (88.2) | |
SUZ12 | |||
Non-overexpression | 444 (97.4) | 163 (96.4) | 0.71 (NS) |
Overexpression | 12 (2.6) | 6 (3.6) | |
EEDb | |||
Underexpression | 14 (3.1) | 3 (1.8) | 0.20 (NS) |
Nonunderexpression | 432 (96.9) | 161 (98.2) | |
JARID2c | |||
Non-overexpression | 431 (94.9) | 161 (96.4) | 0.80 (NS) |
Overexpression | 23 (5.1) | 6 (3.6) | |
BMI | |||
Non-overexpression | 410 (89.9) | 148 (87.6) | 0.49 (NS) |
Overexpression | 46 (10.1) | 21 (12.4) | |
CBX7 | |||
Underexpression | 181 (39.7) | 79 (46.7) | 0.0051 |
Non-underexpression | 275 (60.3) | 90 (53.3) | |
ARF | |||
Non-overexpression | 274 (60.1) | 96 (56.8) | 0.086 (NS) |
Overexpression | 182 (39.9) | 73 (43.2) | |
P16 | |||
Normal expression | 384 (84.2) | 137 (81.1) | 0.025 |
Overexpression | 72 (15.8) | 32 (18.9) | |
P15 | |||
Non-overexpression | 357 (78.3) | 128 (75.7) | 0.090 (NS) |
Overexpression | 99 (21.7) | 41 (24.3) |
Abbreviation: NS, not significant.
aLog-rank test.
bInformation available for 446 patients.
cInformation available for 454 patients.
Two molecular markers may provide a more accurate prediction of patient outcome when combined than when considered in isolation. By combining EZH2 and CBX7 status, we identified four separate prognostic groups with significantly different MFS curves (P = 0.00011; Fig. 2). The patients with the poorest prognosis had EZH2 overexpression and CBX7 underexpression [5-year MFS: 61.7% (57.7%–65.7%); 10-year MFS: 51.4% (47.2%–55.6%)], whereas those with the best prognosis had EZH2 and CBX7 normal expression [5-year MFS: 86.4% (82.4%–90.4%); 10-year MFS: 81.2% (76.5%–85.9%)].
Survival curves of 4 patients groups according to EZH2 mRNA overexpression (over-EZH2) and CBX7 mRNA underexpression (under-CBX7) in the series of 456 breast tumors.
Survival curves of 4 patients groups according to EZH2 mRNA overexpression (over-EZH2) and CBX7 mRNA underexpression (under-CBX7) in the series of 456 breast tumors.
Multivariate analysis (Cox proportional hazards model) showed that lymph node status, tumor size, and combined EZH2/CBX7 status were independent variables predictive of MFS (P = 0.00021, P = 0.014, and P = 0.001, respectively; Supplementary Table S14).
There is a complex interplay between ANRIL, PRC1/PRC2 subunits and p15/CDKN2B-p16/CDKN2A-p14/ARF genes cluster
By using the Spearman rank correlation test for continuous variables, we could find a strong positive correlation between mRNA expression levels of the following genes belonging to the ANRIL pathway: (i) ANRIL and both ARF (r = +0.594, P < 10−7), p15 (r = +0.381, P < 10−7), and p16 (r = +0.323, P < 10−7); (ii) EZH2 and both EED (r = +0.295, P < 10−7), JARID2 (r = +0.278, P < 10−7), and BMI1 (r = +0.229, P = 0.0000031); and (iii) SUZ12 and CBX7 (r = +0.317, P < 10−7), reflecting very complex interplay across this gene set (Supplementary Table S15).
Hierarchical clustering of ANRIL pathway genes according to their expression patterns in the series of 456 IBCs represented in dendrogram format, subdivided genes into two subgroups (Supplementary Fig. S4). Group I included ANRIL, p14/ARF, p15, p16, EZH2, EED, JARID2, and BMI1 and contained 4 genes, ANRIL and the p15/CDKN2B-p16/CDKN2A-p14/ARF gene cluster, highly related. Group II included SUZ12 (from the PRC2 complex) and CBX7 (from the PRC1 complex).
Correlations of ANRIL and PRC2/PRC1 genes expression levels with epithelial–mesenchymal transition, proliferation, and breast cancer stem cell markers
Data from the literature have suggested that Polycomb complexes are implicated in proliferation, epithelial–mesenchymal transition (EMT) induction, and stem cell differentiation. In consequence, we tested the possible links between ANRIL pathway gene expression and mRNA levels of various markers of proliferation (i.e., MKI67), of EMT (i.e., VIM and TWIST1), and of breast cancer stem cell (i.e., ALDH1A1, ALDH1A3, and CD133) in our series of 456 IBCs (Table 3). Marked positive associations were observed between CBX7 and two EMT markers (VIM and TWIST1; P < 10−7 and P < 10−7, respectively). A significant positive correlation was also identified between CBX7 and one breast cancer stem cell marker (ALDH1A1; P < 10−7). EZH2 was highly linked to MKI67 (P < 10−7), whereas EED was linked to two breast cancer stem cell markers: ALDH1A3 and CD133 (P < 10−7 and P = 0.000082, respectively).
Correlations between ANRIL pathway and EMT, proliferation and breast cancer stem cell genes mRNA expression levels in the series of 456 breast tumors
. | EMT . | Proliferation . | Stem cell . | |||
---|---|---|---|---|---|---|
. | VIM . | TWIST1 . | MKI67 . | ALDH1A1 . | ALDH1A3c . | CD133d . |
ANRIL | +0.134a | +0.117 | +0.187 | +0.182 | +0.050 | −0.098 |
0.0043 | 0.012 | 0.0001 | 0.00015 | 0.29 (NS) | 0.038 | |
EZH2 | −0.068 | −0.010 | +0.738 | −0.164 | +0.109 | +0.043 |
0.14 (NS) | 0.83 (NS) | <0.0000001 | 0.00057 | 0.020 | 0.37 (NS) | |
SUZ12 | +0.165 | +0.131 | +0.191 | +0.049 | +0.013 | −0.128 |
0.00052 | 0.0053 | 0.000075 | 0.30 (NS) | 0.78 (NS) | 0.0073 | |
EEDb | +0.115 | +0.123 | +0.208 | +0.123 | +0.295 | +0.155 |
0.014 | 0.0092 | 0.000023 | 0.0093 | <0.0000001 | 0.0015 | |
JARID2c | +0.214 | +0.116 | +0.276 | +0.061 | +0.233 | +0.088 |
0.000012 | 0.013 | <0.0000001 | 0.19 (NS) | 0.0000022 | 0.064 (NS) | |
BMI1 | −0.141 | −0.081 | +0.176 | −0.122 | −0.071 | −0.199 |
0.0028 | 0.080 (NS) | 0.00023 | 0.0087 | 0.13 (NS) | 0.0000053 | |
CBX7 | +0.300 | +0.328 | −0.261 | +0.464 | +0.190 | −0.028 |
<0.0000001 | <0.0000001 | 0.00000016 | <0.0000001 | 0.000082 | 0.57 (NS) | |
ARF | −0.032 | +0.059 | +0.351 | −0.029 | +0.126 | +0.043 |
0.50 (NS) | 0.20 (NS) | <0.0000001 | 0.54 (NS) | 0.0071 | 0.37 (NS) | |
P16 | +0.035 | +0.154 | +0.114 | +0.001 | +0.185 | +0.160 |
0.47 (NS) | 0.0011 | 0.015 | 0.97 (NS) | 0.00013 | 0.00093 | |
P15 | +0.155 | +0.279 | +0.025 | +0.178 | +0.282 | +0.034 |
0.0011 | <0.0000001 | 0.60 (NS) | 0.00021 | <0.0000001 | 0.48 (NS) |
. | EMT . | Proliferation . | Stem cell . | |||
---|---|---|---|---|---|---|
. | VIM . | TWIST1 . | MKI67 . | ALDH1A1 . | ALDH1A3c . | CD133d . |
ANRIL | +0.134a | +0.117 | +0.187 | +0.182 | +0.050 | −0.098 |
0.0043 | 0.012 | 0.0001 | 0.00015 | 0.29 (NS) | 0.038 | |
EZH2 | −0.068 | −0.010 | +0.738 | −0.164 | +0.109 | +0.043 |
0.14 (NS) | 0.83 (NS) | <0.0000001 | 0.00057 | 0.020 | 0.37 (NS) | |
SUZ12 | +0.165 | +0.131 | +0.191 | +0.049 | +0.013 | −0.128 |
0.00052 | 0.0053 | 0.000075 | 0.30 (NS) | 0.78 (NS) | 0.0073 | |
EEDb | +0.115 | +0.123 | +0.208 | +0.123 | +0.295 | +0.155 |
0.014 | 0.0092 | 0.000023 | 0.0093 | <0.0000001 | 0.0015 | |
JARID2c | +0.214 | +0.116 | +0.276 | +0.061 | +0.233 | +0.088 |
0.000012 | 0.013 | <0.0000001 | 0.19 (NS) | 0.0000022 | 0.064 (NS) | |
BMI1 | −0.141 | −0.081 | +0.176 | −0.122 | −0.071 | −0.199 |
0.0028 | 0.080 (NS) | 0.00023 | 0.0087 | 0.13 (NS) | 0.0000053 | |
CBX7 | +0.300 | +0.328 | −0.261 | +0.464 | +0.190 | −0.028 |
<0.0000001 | <0.0000001 | 0.00000016 | <0.0000001 | 0.000082 | 0.57 (NS) | |
ARF | −0.032 | +0.059 | +0.351 | −0.029 | +0.126 | +0.043 |
0.50 (NS) | 0.20 (NS) | <0.0000001 | 0.54 (NS) | 0.0071 | 0.37 (NS) | |
P16 | +0.035 | +0.154 | +0.114 | +0.001 | +0.185 | +0.160 |
0.47 (NS) | 0.0011 | 0.015 | 0.97 (NS) | 0.00013 | 0.00093 | |
P15 | +0.155 | +0.279 | +0.025 | +0.178 | +0.282 | +0.034 |
0.0011 | <0.0000001 | 0.60 (NS) | 0.00021 | <0.0000001 | 0.48 (NS) |
Abbreviation: NS, not significant.
aSpearman rank correlation test.
bData available in 446 samples.
cData available in 454 samples.
dData available in 438 samples.
As previous studies suggested a role of ANRIL in EMT (13), we further investigated the correlations between the expression levels of ANRIL and 9 different biomarkers of EMT in a series of 60 breast carcinomas (30 tumors with high expression level for ANRIL and 30 tumors with low expression level for ANRIL). We confirmed the absence of significant associations between ANRIL and various EMT-associated markers including TWIST1, ZEB1, ZEB2, SNAI1/Snail, SNAI2/Slug, VIM/Vimentin, CDH2/N-cadherin, CDH1/E-cadherin, and ZO-1 (Supplementary Table S16).
miRNAs are implicated in posttranscriptional regulation of PRC1/PRC2
Previous studies suggested complex regulations between Polycomb subunit genes and miRNAs in carcinomas (20, 21). To investigate roles of miRNAs in posttranscriptional deregulation of the ANRIL/PRC pathway in IBCs, we selected 17 miRNAs from the literature. Among them, 4 miRNAs (miR-26A1, miR-101, miR-125B2, and miR-214) are known to target directly EZH2 transcript (22–24) and 2 miRNAs (miR-181B1, miR-181A2) to target directly CBX7 transcript (25). The 11 others miRNAs also target putatively EZH2 and CBX7 (26). We analyzed expression of these 17 miRNAs, using real-time quantitative RT-PCR, in IBCs with normal (n = 20) and marked low (n = 20) levels of CBX7 transcripts and with normal (n = 20) and marked high (n = 20) levels of EZH2 transcripts. We showed that (i) miR-181B1, miR-181A2, and miR-203 levels were marked significantly increased (P < 0.01) in CBX7-underexpressed tumors (Table 4) and that (ii) miR-26A1 and miR-125B1 levels were significantly decreased in EZH2-overexpressed tumors (Table 5).
Statistical analysis of microRNAs expressions relative to CBX7 mRNA expression level
MiRNAs . | Breast cancer with underexpression of CBX7 (n = 20) . | Breast cancer with normal expression of CBX7 (n = 20) . | Pa . | ROC-AUCb . |
---|---|---|---|---|
MIRN181B1 | 1.0 (0.22–2.29)a | 0.34 (0.12–1.30)b | 0.000024 | 0.11 |
MIRN181A2 | 1.0 (0.33–4.83) | 0.39 (0.13–1.92) | 0.00011 | 0.142 |
MIRN203 | 1.0 (0.25–4.72) | 0.42 (0.16–1.02) | 0.0058 | 0.245 |
MIRN200C | 1.0 (0.22–3.34) | 0.45 (0.11–1.77) | 0.02 | 0.285 |
MIRN98 | 1.0 (0.17–7.66) | 0.76 (0.14–3.35) | 0.048 | 0.317 |
MIRN200B | 1.0 (0.20–3.33) | 0.73 (0.24–1.94) | 0.11 (NS) | 0.352 |
MIRN21 | 1.0 (0.25–3.62) | 0.97 (0.13–6.49) | 0.30 (NS) | 0.405 |
MIRN192 | 1.0 (0.20–7.00) | 0.75 (0.11–84.4) | 0.37 (NS) | 0.418 |
MIRN219-1 | 1.0 (0.00–4.05) | 0.55 (0.10–7.50) | 0.59 (NS) | 0.45 |
MIRN200A | 1.0 (0.02–3.92) | 0.79 (0.14–6.33) | 0.65 (NS) | 0.458 |
MIRN183 | 1.0 (0.30–4.93) | 0.55 (0.07–3.84) | 0.70 (NS) | 0.465 |
MIRN138-2 | 1.0 (0.09–33.9) | 2.10 (0.06–41.0) | 0.89 (NS) | 0.512 |
MIRN217 | 1.0 (0.22–2.96) | 1.32 (0.19–7.49) | 0.23 (NS) | 0.611 |
MIRN214 | 1.0 (0.29–2.12) | 1.51 (0.26–3.22) | 0.088 (NS) | 0.658 |
MIRN101-1 | 1.0 (0.17–4.02) | 1.95 (0.26–13.4) | 0.041 | 0.689 |
MIRN125B1 | 1.0 (0.43–4.51) | 2.12 (0.27–12.1) | 0.019 | 0.718 |
MIRN26A1 | 1.0 (0.24–4.64) | 3.05 (0.57–21.4) | 0.015 | 0.725 |
MiRNAs . | Breast cancer with underexpression of CBX7 (n = 20) . | Breast cancer with normal expression of CBX7 (n = 20) . | Pa . | ROC-AUCb . |
---|---|---|---|---|
MIRN181B1 | 1.0 (0.22–2.29)a | 0.34 (0.12–1.30)b | 0.000024 | 0.11 |
MIRN181A2 | 1.0 (0.33–4.83) | 0.39 (0.13–1.92) | 0.00011 | 0.142 |
MIRN203 | 1.0 (0.25–4.72) | 0.42 (0.16–1.02) | 0.0058 | 0.245 |
MIRN200C | 1.0 (0.22–3.34) | 0.45 (0.11–1.77) | 0.02 | 0.285 |
MIRN98 | 1.0 (0.17–7.66) | 0.76 (0.14–3.35) | 0.048 | 0.317 |
MIRN200B | 1.0 (0.20–3.33) | 0.73 (0.24–1.94) | 0.11 (NS) | 0.352 |
MIRN21 | 1.0 (0.25–3.62) | 0.97 (0.13–6.49) | 0.30 (NS) | 0.405 |
MIRN192 | 1.0 (0.20–7.00) | 0.75 (0.11–84.4) | 0.37 (NS) | 0.418 |
MIRN219-1 | 1.0 (0.00–4.05) | 0.55 (0.10–7.50) | 0.59 (NS) | 0.45 |
MIRN200A | 1.0 (0.02–3.92) | 0.79 (0.14–6.33) | 0.65 (NS) | 0.458 |
MIRN183 | 1.0 (0.30–4.93) | 0.55 (0.07–3.84) | 0.70 (NS) | 0.465 |
MIRN138-2 | 1.0 (0.09–33.9) | 2.10 (0.06–41.0) | 0.89 (NS) | 0.512 |
MIRN217 | 1.0 (0.22–2.96) | 1.32 (0.19–7.49) | 0.23 (NS) | 0.611 |
MIRN214 | 1.0 (0.29–2.12) | 1.51 (0.26–3.22) | 0.088 (NS) | 0.658 |
MIRN101-1 | 1.0 (0.17–4.02) | 1.95 (0.26–13.4) | 0.041 | 0.689 |
MIRN125B1 | 1.0 (0.43–4.51) | 2.12 (0.27–12.1) | 0.019 | 0.718 |
MIRN26A1 | 1.0 (0.24–4.64) | 3.05 (0.57–21.4) | 0.015 | 0.725 |
Abbreviations: AUC, area under curve; NS, not significant; ROC, receiver operating characteristics.
aKruskal–Wallis H test.
bMedian (range) of microRNA levels.
Statistical analysis of microRNAs expressions relative to EZH2 mRNA expression level
MicroRNAs . | Breast cancer with normal expression of EZH2 (n = 20) . | Breast cancer with overexpression of EZH2 (n = 20) . | Pa . | ROC-AUC . |
---|---|---|---|---|
MIRN26A1 | 1.0 (0.17–6.46)b | 0.29 (0.04–5.76)b | 0.0027 | 0.222 |
MIRN125B1 | 1.0 (0.09–5.74) | 0.37 (0.14–1.60) | 0.0063 | 0.247 |
MIRN214 | 1.0 (0.11–2.35) | 0.44 (0.20–1.42) | 0.016 | 0.277 |
MIRN101-1 | 1.0 (0.06–7.72) | 0.51 (0.13–1.99) | 0.37 (NS) | 0.417 |
MIRN217 | 1.0 (0.14–4.25) | 0.45 (0.18–465) | 0.69 (NS) | 0.464 |
MIRN138-2 | 1.0 (0.12–36.3) | 0.67 (0.07–25.7) | 0.70 (NS) | 0.465 |
MIRN192 | 1.0 (0.09–97.0) | 0.91 (0.26–7.65) | 0.85 (NS) | 0.482 |
MIRN21 | 1.0 (0.08–3.86) | 0.85 (0.21–5.98) | 0.98 (NS) | 0.498 |
MIRN203 | 1.0 (0.48–3.16) | 1.59 (0.29–8.84) | 0.76 (NS) | 0.529 |
MIRN200A | 1.0 (0.14–3.75) | 1.66 (0.25–13.7) | 0.30 (NS) | 0.595 |
MIRN98 | 1.0 (0.43–3.47) | 1.50 (0.26–13.2) | 0.088 (NS) | 0.657 |
MIRN200C | 1.0 (0.45–2.37) | 1.59 (0.28–8.50) | 0.055 (NS) | 0.677 |
MIRN200B | 1.0 (0.17–1.77) | 1.23 (0.40–8.87) | 0.048 | 0.682 |
MIRN183 | 1.0 (0.05–4.35) | 1.06 (0.26–10.8) | 0.04 | 0.69 |
MIRN181A2 | 1.0 (0.20–2.28) | 1.54 (0.46–5.97) | 0.027 | 0.705 |
MIRN219-1 | 1.0 (0.16–3.56) | 1.92 (0.32–14.0) | 0.019 | 0.716 |
MIRN181B1 | 1.0 (0.41–2.37) | 1.94 (0.44–5.30) | 0.011 | 0.738 |
MicroRNAs . | Breast cancer with normal expression of EZH2 (n = 20) . | Breast cancer with overexpression of EZH2 (n = 20) . | Pa . | ROC-AUC . |
---|---|---|---|---|
MIRN26A1 | 1.0 (0.17–6.46)b | 0.29 (0.04–5.76)b | 0.0027 | 0.222 |
MIRN125B1 | 1.0 (0.09–5.74) | 0.37 (0.14–1.60) | 0.0063 | 0.247 |
MIRN214 | 1.0 (0.11–2.35) | 0.44 (0.20–1.42) | 0.016 | 0.277 |
MIRN101-1 | 1.0 (0.06–7.72) | 0.51 (0.13–1.99) | 0.37 (NS) | 0.417 |
MIRN217 | 1.0 (0.14–4.25) | 0.45 (0.18–465) | 0.69 (NS) | 0.464 |
MIRN138-2 | 1.0 (0.12–36.3) | 0.67 (0.07–25.7) | 0.70 (NS) | 0.465 |
MIRN192 | 1.0 (0.09–97.0) | 0.91 (0.26–7.65) | 0.85 (NS) | 0.482 |
MIRN21 | 1.0 (0.08–3.86) | 0.85 (0.21–5.98) | 0.98 (NS) | 0.498 |
MIRN203 | 1.0 (0.48–3.16) | 1.59 (0.29–8.84) | 0.76 (NS) | 0.529 |
MIRN200A | 1.0 (0.14–3.75) | 1.66 (0.25–13.7) | 0.30 (NS) | 0.595 |
MIRN98 | 1.0 (0.43–3.47) | 1.50 (0.26–13.2) | 0.088 (NS) | 0.657 |
MIRN200C | 1.0 (0.45–2.37) | 1.59 (0.28–8.50) | 0.055 (NS) | 0.677 |
MIRN200B | 1.0 (0.17–1.77) | 1.23 (0.40–8.87) | 0.048 | 0.682 |
MIRN183 | 1.0 (0.05–4.35) | 1.06 (0.26–10.8) | 0.04 | 0.69 |
MIRN181A2 | 1.0 (0.20–2.28) | 1.54 (0.46–5.97) | 0.027 | 0.705 |
MIRN219-1 | 1.0 (0.16–3.56) | 1.92 (0.32–14.0) | 0.019 | 0.716 |
MIRN181B1 | 1.0 (0.41–2.37) | 1.94 (0.44–5.30) | 0.011 | 0.738 |
NOTE: miRNA levels were standardized versus U44 control microRNA.
Abbreviations: AUC, area under curve; NS, not significant; ROC, receiver operating characteristics.
aKruskal–Wallis H test.
bMedian (range) of microRNA levels.
Discussion
Among the major discovered lncRNAs deregulated in carcinogenesis, ANRIL has been shown to regulate its neighbor tumor suppressor genes CDKN2B, CDKN2A, and ARF by epigenetic mechanisms and thereby control cell proliferation and senescence (27). ANRIL, acting in cis, specifically binds various Polycomb proteins, in particular EZH2 (PRC2) and CBX7 (PRC1), resulting in histone modification in the CDKN2A/CDKN2B/ARF locus. EZH2 is a histone methyltransferase and a member of PRC2 that not only methylates histone H3 on Lysine 27 but also interacts with and recruits DNA methyltransferases to methylate CpG of certain EZH2 target genes to establish firm repressive chromatin structures, contributing to tumor progression. CBX7 is a Chromobox family protein and a member of the PRC1 and is directly involved in regulation of genes frequently silenced in cancer.
To assess expression of the lncRNA ANRIL and the Polycomb subunits of PRC2/PRC1 as well as CDKN2A/CDKN2B/ARF locus in IBCs, we used qRT-PCR in a large series of 456 IBCs from patients with known clinical and pathologic status and long-term outcome. Evaluation at mRNA level was combined with an IHC study in a series of 80 IBCs. Indeed, these two techniques of expression analysis (qRT-PCR and IHC) give complementary information, the technique of qRT-PCR with an extraction in homogeneous solution quantified transcripts levels both in tumor cells and in stroma cells, while IHC study allows only a semiquantitative analysis of protein levels, but on an individual cell basis (allowing distinction between epithelial tumor cells and stroma cells).
In the present study, we observed ANRIL overexpression in 19.7% of IBCs. ANRIL depletion has been associated with reduced proliferation (28), suggesting a procarcinogenic role supported by overexpression of this lncRNA in various others cancer types (29–31). In our IBC series, ANRIL overexpression was observed more particularly in the aggressive TNC subtype.
We also observed a marked overexpression of EZH2 and to a lesser extent of BMI1, respectively, in 77.0% and 10.1% of IBCs and CBX7 underexpression in 39.7% of the tumors. We confirmed these data at the protein level in the series of 80 IBCs by identifying a moderate and intense nuclear staining with an anti-EZH2 antibody in 82% of IBCs and an absence or a slight nuclear and cytoplasmic staining of cancer cells with a CBX7 antibody in 43% of IBCs. In malignant tumors, ANRIL is a natural antisense transcript which usually recruits the two Polycomb repressor complexes PRC2 and PRC1, resulting in chromatin reorganization with silencing of the INK4A/ARF/INK4B locus. For example, positive links were observed between CBX7 overexpression, ANRIL overexpression, and CDKN2A/CDKNB/ARF underexpression in prostate cancer (10). Conversely, in our series of breast tumors, we showed marked CBX7 underexpression and a nonexpected high positive link between ANRIL overexpression and CDKN2A/CDKNB/ARF overexpression, and more particularly with p14/ARF. Although these results seem to be contradictory, it can be hypothesized that CBX7 can exhibit both oncosuppressive and oncogenic functions, depending on type of cancer, microenvironment, and presence of interacting proteins (32–35).
CBX7 underexpression was strongly correlated with high SBR histologic grade, negative ERα and PR status, and EMT and breast cancer stem cell markers. Apart from few exceptions (as prostate cancer), CBX7 expression is lost in human malignant neoplasias, and a clear correlation between its downregulated expression and a cancer aggressiveness and poor prognosis has been observed (36).
EZH2 overexpression was also strongly associated with high SBR histologic grade and negative ERα and PR status. But, unlike CBX7, EZH2 overexpression was highly linked to the proliferation marker MKI67, suggesting a different role of these two proteins in breast tumorigenesis (37). Numerous studies point on the widespread roles of PRC2 (as well as H3K27 methylation) in developmental and differentiation processes of multicellular organisms, and on their implication in fundamental chromatin mechanisms that underlie stem cell regulatory circuits and cancer progression (38). Thus, it is not surprising that increasing evidences indicate that EZH2 deregulation is frequently observed in a variety of cancers (39–41). EZH2 overexpression is mainly found in solid tumors (as in our present study in breast cancer), whereas activating or inactivating mutations are identified in hematologic malignancies (42).
Using log-rank analysis to identify relations between MFS and mRNA levels of the 10 ANRIL pathway genes, only EZH2 overexpression and CBX7 underexpression were significantly associated with shorter MFS. Multivariate analysis showed that combined EZH2/CBX7 status was an independent prognostic factor.
Results from previous studies suggest complex interactions between Polycomb complexes and miRNAs in cancer progression. As no mutation or allelic loss of CBX7 located in 22q13.1 were identified in large genomic studies (43) and focal amplification of EZH2 located in 7q36 was only observed in 1% of IBCs (43), we suspected epigenetic mechanisms implicating miRNAs could account for CBX7 underexpression and EZH2 overexpression in IBCs. Among the 17 miRNAs selected, (i) miR-181B1, miR-181A2, and miR-203 expressions were significantly increased in IBCs with CBX7 underexpression and (ii) miR-26A1 and miR-125B2 expressions were significantly decreased in IBCs with EZH2 overexpression, in agreement with the literature (44, 45). Our results thus showed that EZH2 is targeted by 3 oncosuppressive miRNAs (miR-26A1, miR-125B, and miR-214) that are decreased in IBCs, suggesting an epigenetic mechanism of EZH2 overexpression in IBCs. Concerning CBX7, our results were also consistent with recent data in the literature, suggesting that the 2 oncomiRs miR-181B1 and miR-181A2 could be induced by the oncogene HMGA1, resulting in CBX7 underexpression (46). Indeed, we observed a positive link between HMGA1 mRNA levels and expression of both miR-181B1 (r = +0.340, P = 0.0038) and miR-181A2 (r = +0.264, P = 0.025) in 71 tumors of our IBC series (data not shown).
Recent data revealed that histone modifier complexes PRC2 and PRC1 have a bivalent role in cancer, bearing both oncogenic and tumor-suppressive properties depending on cell tumor type (47). Complex deficiency in PRC2 and PRC1 components could decrease expression levels of epigenetic repressive mark H3K27 trimethylation, thereby contributing to H3K27 acetylation and resulting in increased transcription and activation of oncogenic pathways. Thus, defining a PRC2/PRC1 activity status in IBCs may be pivotal in combining or reconsidering therapeutic options. We identified a moderate-to-intense nuclear staining of tumor cells with H3K27ac antibodies in 73.8% of IBCs associated to an absence or a slight nuclear staining of cancer cells with H3K27me3 antibody in 76.3% of IBCs. Collectively, these data suggest that loss of Polycomb repressive function in IBCs might be due to epigenetic alteration of PRC1 and PRC2 by several microRNA targeting CBX7 and EZH2, resulting in altered H3K27trimethylation and H3K27 acetylation. Development of therapies targeting epigenetic processes in cancer has gained increasing focus with study of HDAC and DNA methyltransferase inhibitors and more recently of BET bromodomain inhibitors (48). Indeed, recent studies of malignant peripheral nerve sheath tumors (MPNST) have showed that alterations of PRC2 subunits lead to the amplification of Ras-driven transcription and confer sensitivity to BET bromodomain inhibitors (49, 50).
In conclusion, our results revealed a complex pattern of interactions between ANRIL, PRC2/PRC1 and suppressive and oncogenic miRNAs in IBCs. Our findings also point to EZH2 and CBX7 as the most promising of the 10 genes investigated for clinical applications and therapeutic approaches to breast cancer. This study suggest that it is the global pattern of expression, rather than expression of individual family members, that should be taken into account when defining functionality of repressive Polycomb complexes and evaluating antitumor drugs targeting these genes. Thus, establishment of a PRC2/PRC1 activity status in IBCs could be contributive in targeting BET proteins by using bromodomain inhibitors when levels of H3K27me3 are decreased and H3K27ac increased. Moreover, inhibition of oncomiRNAs miR-181B1 and miR-181A2 (as well as restoration of oncosuppressive miR-26A1, miR-125B, and miR-214) may represent another attractive combined strategy for breast cancer–targeted therapy.
Disclosure of Potential Conflicts of Interest
No potential conflicts of interest were disclosed.
Authors' Contributions
Conception and design: D. Meseure, E. Pasmant, I. Bieche
Development of methodology: D. Meseure, S. Vacher, I. Bieche
Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): D. Meseure, S. Vacher, K. Drak Alsibai, A. Nicolas, I. Bieche
Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): D. Meseure, S. Vacher, K. Drak Alsibai, W. Chemlali, R. Lidereau, I. Bieche
Writing, review, and/or revision of the manuscript: D. Meseure, E. Pasmant, C. Callens, I. Bieche
Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): K. Drak Alsibai, M. Caly, C. Callens, I. Bieche
Study supervision: I. Bieche
Grant Support
This work was supported by grant INCa-DGOS-4654.
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