Abstract
The exact roles of copy number alteration (CNA) in initiation, progression and immunotherapy of breast cancer and the genomic alterations behind progression from ductal carcinoma in situ (DCIS) to invasive carcinoma remain unknown. Quantitative multi-gene fluorescence in situ hybridization (QM-FISH) opens a possibility of large scale genomic analysis of specific deletions and amplifications with high-resolution at one cell level. We detected CNAs of 30 genes using QM-FISH and analyzed their association with clinicopathological parameters and patients’ outcomes in 66 breast cancers with synchronous invasive carcinoma and DCIS. The copy numbers of 30 genes in DCIS and the invasive area in all tumors were compared. The results revealed some recurrent CNAs including amplifications of MDMx, CCNE2, HER2 and deletions in Chek1, p53, Rb1 with a frequency of over 20%. By comparing the CNAs in invasive tumors and co-occurring DCIS, the similarity of chromosomal instability (CIN) in both components was visualized. Some co-occurrence patterns of CNAs of 30 genes were observed. The study also demonstrated higher frequencies of occurrence of CNAs in aneuploidy tumors, high grade tumors and tumors with high proliferation index. Higher CNAs were also found in death patients. Overall, we uncovered some frequently occurring gene aberrations out of 30 genes and synchronous pre-invasive lesions share majority of CNAs with invasive breast cancer. Moreover QM-FISH is a powerful technique to detect CNAs of multi-genes and give more information on co-occurrence of CNAs.
Keywords: Breast cancer, ductal carcinoma in situ, copy number alteration, quantitative multi-gene fluorescence in situ hybridization, chromosomal instability
Introduction
Breast cancer is a complex disease characterized by accumulation of genetic changes in a large number of genes, including point mutations, rearrangements, deletions, and amplifications. In the last 10 years many different multi-gene assays provide possibility in clinical practice to stratify patients for prognostic predictions and selecting treatments [1,2]. However, the complexity of breast cancer is not fully reflected by the genes or biomarkers used currently for clinical purpose.
The genomic copy number alterations (CNAs) can alter the ability of the cancer cell to proliferate, survive, and spread in the host and therefore is now recognized as a characteristic of most breast cancers [3,4]. The comprehensive characterization of CNAs in cancer genomes is critical for understanding breast carcinogenesis and for development of targeted therapies for individual cancer patients [5]. Curtis et al conducted an integrated analysis of copy number in a large numbers of patients and developed a novel molecular stratification of the breast cancer population [6]. It provides a definitive framework for understanding how gene copy number aberrations affect gene expression in breast cancer and reveals novel subgroups that should be the target of future investigation and tumor therapy. However there remains much more unknown about the roles of CNAs in initiation and progression of breast cancer. Quantitative multi-gene fluorescence in situ hybridization (QM-FISH) is a cytological technique that targets for cytological analysis and enables the detection of multiple chromosomal changes in single cells [7]. We developed the protocol involving in optimization of fixation and signal-washing methods for tumor samples in Anders Zetterberg Lab in CCK, Sweden. Up to 32 genes can be quantified synchronously in the same individual tumor cell nuclei, making QM-FISH a high-resolution, accurate and powerful tool for large scale clinical analysis. Herein, QM-FISH is the technique of choice to quantify copy number changes of genes or chromosomal regions in clinical samples. Meanwhile QM-FISH procedure gives the chance to analyze the relationship of CNAs of multi-genes at the single cell level and to avoid intra-tumor genomic heterogeneity to the largest extent.
Based on the ROMA data of breast cancer tumors obtained by Hick et al [8], 30 genes located at “hot-spots” were chosen for further analyses including some well-known genes and a few new genes. We detected gene CNAs in breast cancers by QM-FISH, and analyzed their association with clinicopathologic parameters and outcomes. We addressed the following questions: (1) to identify a panel of specific disease-associated CNA loci using QM-FISH, (2) to determine whether there are some features in the genomes of tumor cells that correlate with invasion by comparing CNAs of 30 genes in synchronous ductal carcinoma in situ (DCIS) and invasive cancer, (3) to better understand which and how CNAs might combine, and (4) to find some valuable markers for predicting prognosis of patients with breast cancer.
Results
CNAs of genes
All tumors had at least 1 chromosomal aberration out of 30 loci with the maximum of 12 and the average was 6.1. Totally 404 gene abnormalities were found with 166 amplifications and 238 deletions. Gene amplifications includes high level amplifications (cluster pattern) and low level amplifications (dot like pattern). As shown in Table 1, gain of MDMx was most frequently observed in this cohort of cases with a frequency of 54.5%. Other common CNAs were amplification of CCNE2, HER2, IGF1R, CKS1a, c-myc and deletion in Chek1, p53, Rb1, CDH1, Chek2, Nek9, all of which were observed in more than 20% of the analyzed cases. CKS1a and CCNE2 as well as MDMx gene showed low level increase of gene copy number.
Table 1.
CNAs of 30 genes in primary breast cancer (n=66)
| Genes | N | Frequency (%) |
|---|---|---|
| Amplifications | ||
| MDMx | 36 | 54.5 |
| PIK3CA | 5 | 7.6 |
| JARID2 | 2 | 3.0 |
| FGFR1 | 10 | 15.2 |
| CKS1a | 19 | 28.8 |
| CCNE2 | 23 | 34.8 |
| c-myc | 18 | 27.3 |
| Cyclin D1 | 12 | 18.2 |
| MDM2 | 2 | 3.03 |
| IGF1R | 16 | 24.2 |
| HER2 | 15 | 22.7 |
| TBX2 | 3 | 4.5 |
| STK6 | 5 | 7.6 |
| Deletions | ||
| PAX7 | 7 | 10.6 |
| FHIT | 13 | 19.7 |
| MAD4 | 3 | 4.5 |
| MAP3K7 | 9 | 13.6 |
| WTAP | 4 | 6.1 |
| LZTS1 | 5 | 7.6 |
| p16 | 14 | 21.2 |
| Chek1 | 27 | 41.0 |
| LATS2 | 10 | 15.2 |
| Rb1 | 25 | 37.9 |
| Nek9 | 17 | 25.8 |
| MAPK3 | 2 | 3.03 |
| CDH1 | 23 | 34.5 |
| p53 | 30 | 45.5 |
| MADH4 | 10 | 15.2 |
| TPTE | 13 | 19.7 |
| Chek2 | 25 | 37.9 |
CNAs in DCIS and invasive carcinoma
We successfully compared copy number of 30 genes in DCIS and the invasive area in all of the tumors. Majority of cases showed identical CNAs though differential CNAs of a few genes were observed in DCIS and invasive carcinoma. 341 events of gene abnormality were reported in DCIS, with average of 5.2 genes showing CNAs for each tumor. We identified differential CNAs of Chek1 (34.8% vs. 41.0% in DCIS and invasive cancer respectively, P=0.591), CCNE2 (28.8% vs. 34.8%, P=0.564), Cyclin D1 (12.1% vs. 18.2%, P=0.467), Chek2 (34.8% vs. 37.9%, P=0.857), CDH1 (30.3% vs. 34.5%, P=0.711), TPTE (16.7% vs. 19.7%, P=0.822), MDMx (48.5% vs. 54.5%, P=0.711), LZST1 (4.6% vs. 7.6%, P=1), MAP3K7 (10.6% vs. 13.6%, P=0.791), PAX7 (9.1% vs. 10.6%, P=1), c-myc (25.8% vs. 27.3%, P=1), Rb1 (36.4% vs. 37.9%, P=1), LATS2 (13.6% vs. 15.2%, P=1).
Concurrent of gene CNAs
Genetic abnormalities of 30 genes for an individual cell were analyzed. Some gene alterations occurred concurrently in the same cells were found (examples are shown in Figure 1). 9 out of 12 Cyclin D1 amplification positive cases showed concurrent Chek1 deletion (Figure 2). There was significant association between Cyclin D1 amplification and Chek1 deletion (P=0.011). C-myc amplification was identified in 16 out of 23 cases with CCNE2 amplification (P<0.001). All 5 tumors with LZST1 deletion had c-myc amplification (P=0.002). Other co-occurring CNAs included CKS1a and IGF1R amplification (in 9 cases, P=0.01), c-myc amplification and HER2 amplification (in 8 cases, P=0.025). Inverse correlation between deletion of CDH1 and p16 was found (P=0.001) as well.
Figure 1.
Case 18 showing MDMX, Cyclin D1, c-myc, MDM2, PIK3A, TBX2 amplification, and Chek1, LZST1, MADH4 deletion using QM-FISH. A. CDH1 (green), MDMX (orange), PAX7 (red) and MAPK3 (purple); B. Cyclin D1 (green), Chek1 (orange), Chek2 (red), FHIT (purple); C. HER2 (green), LZST1 (orange), c-myc (red), p53 (purple); D. FGFR1 (green), MAP3K7 (orange), MDM2 (red), JARID-2 (purple); E. CCNE2 (green), Rb1 (orange), p16 (red), PIK3A (purple); F. LATS2 (green), IGF1R (orange), MADH4 (red), TPTE (purple); G. CKS1a (green), MAD4 (red), WATP (purple); H. TBX2 (green), STK6 (orange), Nek9 (red).
Figure 2.
QM-FISH detection showing gene copy number changes of CCND1 and Chek1 (×630).
Relationship between CNAs of genes and the clinicopathological characteristics
The correlation of CNAs with clinicopathological features was evaluated. Overall, there were more CNAs in aneuploid tumor (A-tumor) than those in diploid tumor (D-tumor) (average 6.6 vs. 5.2, P=0.032). Tumors with high ki67 index had more CNAs than tumors with low ki67 (P=0.033). There were 5.0 CNAs in average in low grade tumors (Elson and Ellis grade 1 and 2) compared with 6.8 in high grade tumors (Elson and Ellis grade 3) (P=0.008) (Table 2; Figure 3). No significant association was seen between copy number changes and ER status, PR status, HER2, tumor size and node status.
Table 2.
Summary of patients and tumor characteristics and CNAs of 30 genes in studied cases with breast cancer
| Characteristics | Patients no. (%) | Means of CNAs | P value |
|---|---|---|---|
| Age at diagnosis (y) | |||
| ≤35 ys | 10 | 5.3 | 0.134 |
| >35 ys | 56 | 6.3 | |
| Tumor size1 | |||
| d≤20 mm | 22 | 5.5 | 0.874 |
| >20 mm | 44 | 6.4 | |
| Grades | |||
| Low | 47 | 5.0 | 0.008 |
| High | 19 | 6.8 | |
| Nodal Status2 | |||
| N0 | 26 | 5.7 | 0.745 |
| N+ | 40 | 6.5 | |
| ER | |||
| Negative | 22 | 6.2 | 0.582 |
| Positive | 44 | 6.1 | |
| PR | |||
| Negative | 21 | 6.4 | 0.378 |
| Positive | 45 | 6.1 | |
| HER2 | |||
| Negative | 51 | 5.9 | 0.855 |
| Positive | 15 | 6.8 | |
| Ki67 | |||
| Low | 27 | 5.3 | 0.033 |
| High | 39 | 6.6 | |
| Tumor Ploidy | |||
| D | 22 | 5.2 | 0.032 |
| A | 44 | 6.6 |
d, diameter;
N0, node metastasis negative; N+, node metastasis positive.
Figure 3.
CNAs of 30 genes were more common in A-tumors, high grade tumors and tumors with high ki67 index (N0, node metastasis negative; N+, node metastasis positive).
Amplification of HER2, c-myc, CCNE2, CKS1a, Cyclin D1 were more frequent in A-tumor than that in D-tumor (P=0.001, P<0.001, P<0.001, P=0.019, P=0.049 respectively) while D-tumors has more deletion of PAX7 (P=0.036). The incidence of Nek9 deletion significantly increased with grade (P=0.027). Axillary lymph node metastasis positive tumors showed more IGF1R amplification (P=0.036) and MAPK3 and LATS2 deletion (P=0.009 and 0.005 respectively). Cyclin D1 amplification was present more often in ER and PR positive tumors (P=0.049 and 0.045) while more HER2 amplification and WTAP deletion were present in ER and PR negative tumors (P<0.001, P<0.001 and P=0.039, P=0.046). There were more CNAs of HER2, CCNE2 and IGF1R in high ki67 group than those in low ki67 group (P=0.017, P=0.034, P=0.009), more details seen in Supplementary Table 1.
Correlation between CNAs of the genes and prognosis of the patients
The survival analysis based on CNAs of 30 genes was investigated. There were less CNAs in survival group than in death group (5.3 vs 7.7, P<0.001). Survival analysis revealed that the gene deletions of p16 (P<0.001), CDH1 (P=0.004), Chek1 (P=0.025), TPTE (P=0.009), Nek9 (P=0.002), p53 (P=0.001) were significantly associated with a poor prognosis (Figure 4).
Figure 4.
Kaplan-Meier analysis of overall survival and CNAs of genes.
Discussion
The investigation of CNAs is of high relevance for improving the diagnosis of breast cancer and prognosis of the patients. During the last decades, modern techniques such as cytogenetic analysis, gene sequencing or array based analyses were developed to detect genomic alterations of tumors [9-13]. However, the problem of resolution and lack of commercial availability limited clinical applications of most genomic array technologies. So microarray studies are mostly used to screen genes aberration. CNAs identified by microarray always include a contiguous set of genes. Up to now FISH is still the rapid, most precise means to assess copy numbers of specific sequences in tumor samples due to its simplicity and reliability in evaluating the key biomarkers [7]. Currently, conventional FISH could detect 1 or 2 genes once a time on one section. Weak signals or losing one of the hybridization signals may occur accompanied with high background and consequently results in a relatively low signal-to-noise ratio when multi-genes are detected. In current study we used three to five different BAC probes with partially overlapping DNA sequences for each gene to enhance resolution. Using QM-FISH copy number values of dozens of genes in individual cells can be measured and high signals/noise ratio with intact nuclear morphology is reached.
Although a flood of CNAs have been reported, they only cover a small proportion of the functional genes and tend to occur at distinct ‘hot-spots’. Therefore, as for a certain tumor, the leading couples of genetic changes could describe its genetic features. Our study was designed to detect CNAs of 30 genes based on previous gene array study. Some are well known genes (such as HER2 and c-myc) involved in breast cancer, however some are rather new (such as LZST1 and Nek9). To my knowledge there have not been such studies before. The data showed all cases had at least one chromosomal aberration out of 30 loci with an average 6 CNAs. It confirmed that CNA is a hallmark of malignant tumors and indicated it plays an important role in driving breast cancer. MDMx, CCNE2, HER2, IGF1R, CKS1a, c-myc, Chek1, p53, Rb1, CDH1, Chek2, Nek9 were frequently affected chromosomal region in breast cancers. We firstly found Nek9 deleted frequently in breast cancer.
DCIS is a non-obligate pre-invasive lesion for invasive breast cancer. Histologic and epidemiologic studies showed similarities between these two lesions. Several studies suggested that molecular genetic alterations in DCIS of mixed DCIS-invasive cancer strongly resemble that seen in invasive ductal carcinoma [14-16]. However, over the last decade few studies have specifically compared the CNAs between these two lesions, and more related genomic alterations remain unknown. To better understand the mechanisms behind progression to invasive breast cancer, we used QM-FISH to detect specific genetic alterations. We found the degree of genomic alteration of DCIS resembled that of invasive carcinoma, indicating that these alterations may be essential for the early phase of DCIS development. This also suggests that, in most cases, CNA occurs before the acquisition of an invasive phenotype and may not contribute to the development of invasion. Combined DCIS-invasive breast cancer and pure DCIS have been reported to be genetically distinct. Kim et al performed whole-exome sequencing and copy number profiling for six cases of pure DCIS and five pairs of synchronous DCIS and invasive ductal carcinoma and found genomic features of DCIS associated with invasive cancer were closer to invasive cancer than pure DCIS [17]. To get more information, step studies with comparing pure DCIS and invasive carcinoma and with expanded sample size are needed. This raises the possibility of using QM-FISH of a panel of such genes to predict disease progression.
It is well known that breast cancers develop through an accumulation of a variety of genetic alterations [18-20]. It is essential to carry out comprehensive CNAs profiling on tumor specimens to assess the role and impact of coincident CNAs. The study on concurrent genetic changes may provide insight into the underlying mechanisms that drive this divergent biological and clinical behaviour of breast cancer and facilitate the discovery of potential biomarkers with therapeutic value. A great advantage of QM-FISH is that it is relatively easy to be conducted in a clinical setting, thereby gives the chance to study the concurrent of various genes at the same single cell level, which can avoid intra-tumor heterogeneity. Significantly, we uncovered high frequency of co-existing genetic alterations. This is the first report for most of the concurrent gains and deletions in breast cancer by QM-FISH. Meanwhile it indicated a more complex gene expression/genomic variation interaction in breast cancer.
Our study demonstrated more frequent gene copy number gains/losses in A-tumors, and high grade tumors. Moreover, more copy number abnormality of a few genes was observed in A-tumor, tumors in larger size, node positive tumors and high grade tumors, confirming more aggressive behaviour of the tumors with more frequent CNAs. Our data also indicated higher CNAs in death patients. As correlated with low survival, the copy numbers of p16, CDH1, Chek1, TPTE, Nek9 and p53 might be used as prognosis markers for breast cancer.
In conclusion, this is the first report of detection of 30 genes using QM-FISH in the same tumor section. Our protocol of high resolution QM-FISH would be useful in detection of CNAs of multi-genes and give the chance to get more information on co-occurrence of CNAs. Frequently affected gene aberrations of 30 genes includes amplification of MDMx, CCNE2, HER2, IGF1R, CKS1a, c-myc and deletion in Chek1, p53, Rb1, CDH1, Chek2, Nek9, with a frequency of over 20%. These genes can more precisely reveal the overall abnormalities present in breast cancer patients relative to a single gene. Detecting CNAs of a panel of above recurrent genes will assist accurate prognosis and facilitate individual therapeutic plans. In addition, synchronous DCIS and invasive breast cancer have similarities at genomic level.
Materials and methods
Patients and tumor characteristics
The study was approved by the Ethics Committee of Shandong University (no. MECSDU-MS2012052). Sixty-six consecutively cases of non-specified invasive breast carcinoma associated with various percentage of DCIS were collected from 66 women undergoing surgery in Qilu Hospital, Shandong University, Jinan, China, from January to June 2005. None of the patients received either neoadjuvant chemotherapy or radiation therapy prior to operation. From each specimen ten contiguous sections were prepared and used for H&E staining and QM-FISH procedure.
The ages of patients at the time of the diagnosis ranged from 23 to 85 years (mean 46.3 years). The tumor size ranged from 1.0 to 7.8 cm in the greatest dimension (mean 2.9 cm). Detailed patient and disease characteristics are documented in Table 1. Patients were followed up from the date of surgery until death or the last observation (median follow-up, 71.4 months, ranging 13-120 months). At the time of the last follow-up, 44 patients (66.7%) were alive, 22 patients (33.3%) were dead from the disease.
Tumor ploidy evaluation
The ploidy of 66 tumors was evaluated by measurement of DNA content using image cytometry on Feulgen stained sections as previously described [21]. DNA histograms were interpreted according to a modified subjective method. The normal control cells were given the value 2c, denoting the normal diploid DNA content, and all tumor-cell DNA values were expressed in relation to that. The histograms were divided into two groups. Cases with a major peak near the 2c region (1.8c-2.2c), and less than 10% cells exceeding 2.5c were denoted D-tumor. DNA profiles with a stem line outside the diploid and tetraploid region and distinctly scattered DNA values exceeding the tetraploid region (3.8c-4.2c) were classified as A-tumor.
Preparation of probes
The UCSC (University of California, Santa Cruz) genome browser database (http://genome.ucsc.edu/) was used to design probes for all genes. The probes were created from bacterial artificial chromosomes (BAC) plasmid DNA (Deutsche Ressourcenzentrum für Genomforschung, RZPD, Berlin) isolated by using a Qiagen® plasmid purification kit. All probes were labeled with Spectrum Green-dUTP, Spectrum Orange-dUTP (Abbott Molecular Inc., Downers Grove, IL), Alexa Fluo 594-5-dUTP (Texas Red, Invitrogen) and Cy5-dUTP (purple, Amersham Life Science) with dUTP by nick translation. Three to five different BAC probes with partially overlapping DNA sequences were chosen for each gene to boost the hybridization signal and enhance resolution. For example, five continuous sequences p53-N1, p53-N2, p53-N, p53-N3, p53-N4 were used as probes for p53 gene. All probes tested on HDF cells in order to obtain probes with as high specificity as possible. 30 genes were divided into eight groups, which were summarized in Table 3. Labeled probes were mixed with human Cot1 DNA, tRNA and salmon sperm DNA to compete for repetitive elements. Sodium acetate and ice cold absolute ethanol were added in and the mixture was precipitated at -80°C overnight. Ethanol was removed by centrifugation and the pellet was washed once with 70% ethanol. The pellet was air dried and redissolved in hybridization buffer.
Table 3.
30 genes labeled by 4 fluorophores
| Group 1 | Group 2 | Group 3 | Group 4 | Group 5 | Group 6 | Group 7 | Group 8 | |
|---|---|---|---|---|---|---|---|---|
| Spectrum Green | CDH1 | Cyclin D1 | C-erbB2 | FGFR1 | CCNE2 | LATS2 | CKS1a | TBX2 |
| Spectrum Orange | MDMX | Chek1 | LZST1 | MAP3K7 | Rb1 | IGF1R | MAD4 | STK6 |
| Texas Red | PAX7 | Chek2 | c-myc | MDM2 | p16 | MADH4 | WATP | Nek9 |
| Cy 5 (purple) | MAPK3 | FHIT | p53 | JARID-2 | PIK3A | TPTE |
FISH procedure
Formalin-fixed paraffin-embedded tissue sections were removed excess wax followed by dehydration in absolute alcohol. Antigenic recovery was performed through incubating the slides for 1 hour at 80°C in 0.1 M citric buffer (pH 6.0). A 10-minute digestion with pepsin (1 mg/ml in 0.01 M HCL) was performed followed by fixation in 1% formaldehyde. The probes were dissolved in the hybridization mixture. Denaturation of probe and target DNA were performed simultaneously at 90°C for 10 min and each slide was incubated in a moist chamber for hybridization at 47°C overnight. After hybridization, slides were washed in 4×SSPE for 10 min at 37°C and 47°C respectively. Nuclei were mounted and counterstained with DAPI (4’, 6-diamino-2-phenylindole; Vector Laboratories) followed by view in the fluorescence microscope. After photographing, the slides were stored in the cold room for review and next hybridization.
Sequential FISH
The cover slips were removed for hybridization with next probe. The signals were removed by incubation of sections with 70% formamide at 70°C for 3 min, immediately immersed in precooling 70% ethanol and washed. Then, slides were dehydrated, denatured, hybridized and mounted as described above. After mounting for every round, the slides were placed in the microscope. Fields were chosen with filter for DAPI, and the position was recorded for image acquisition. One monochrome image with each of the filter sets for detection of DAPI, Spectrum Green, Spectrum Orange, Alexa 594, and Cy3 was acquired using ×630 objective lens before moving the focal plane to the next position. After re-hybridization the slides were reinserted in the microscope, they were repositioned using the automatic repositioning system of the Delta Vision system. So images were obtained from the same area.
Signal evaluation was carried out using an Axioplan 2 confocal fluorescence microscope (Carl Zeiss AB, Sweden) mounted with a charge-coupled device (CCD) camera Axiocam MRm (Carl Zeiss AB) , coupled with a computer with Axio Vision software (Carl Zeiss AB). Two researchers independently carried out all investigations without knowledge of the clinicopathological data of the patients studied. Only signals in the tumor areas based on both a consecutive section stained by H&E and DAPI morphology were counted and evaluated. At least 100 non-overlapping nuclei per sample were analyzed for each tumor. More than 50% of counted nuclei with 0-1 signal defined those samples containing gene deletion. Gene amplification was defined by the presence of an excess in the number of gene loci (except HER2) over the number of corresponding chromosomes in more than 20% counted tumor cells.
Immunostaining evaluation
The immunostained slides of ER, PR, HER2 and ki67 were reviewed and reevaluated. Tumors were counted as positive for ER and PR if >1% of the nuclei of neoplastic cells showed definitive staining [22]. Ki67 index was scored low if <14% of the nuclei of neoplastic cells were positive, and high if ≥14% of the nuclei of neoplastic cells were positive [23]. HER2 was scored according to ASCO/CAP HER2 clinical practice guideline [24].
Statistical analysis
All statistical analyses were performed using SPSS 16.0 (SPSS Inc. Chicago, IL). The Chi-square and Fisher exact test was used to evaluate the statistical significance between clinicopathological variables and CNAs of genes. Correlations were studied using the Spearman test. Mann-Whitney U test was used to identify the number of CNAs associated with clinicopathological parameters. Survival of patients was analyzed using the Kaplan-Meier and Log-rank test. Statistical significance was set at 0.05 and all p value is two-sided.
Acknowledgements
We thank Professor Anders Zetterberg (Cancer Centre, Karolinska Institute, Sweden) for his valuable probes, technical assistance and useful discussions. This study was supported by National Natural Science Foundation of China [81272902 and 30901456 to LL].
Disclosure of conflict of interest
None.
Supporting Information
References
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