| Background and objective:Breast cancer, the number of cases and deaths of which are both located in the forefront of female cancer, is by far the most frequent cancer of women worldwide. Thus it is a kind of serious disease which is harmful to women’s physical and mental health. Although breast cancer is a kind of malignant tumor which mainly affects postmenopausal women, the age when patients suffer from it is gradually getting younger and younger. Cancer epidemiology studies have revealed that the incidence of young breast cancer differs in different ethnic populations. The overall incidence of breast cancer is low in Asia, however, the morbidity and proportion of young breast cancer patients in Asian countries is higher than in Western countries. Moreover, the peak age of breast cancer patients in Asia is younger than in Western countries.Compared with older breast cancer, young breast cancer has been found to have a unique biological behavior with later tumor TNM stage, more aggressive histological type, higher histological grade, more lymph node or hematogenous metastasis, higher malignancy degree, higher recurrence rate, higher ER and PR negative rate, higher HER2positive rate, higher triple-negative breast cancer proportion, higher p53mutation rate, and higher BRCA1/BRCA2mutation rate. It is concluded that young and older breast cancer may be two different disease processes. Foreign scientists tried to reveal the potential biological mechanism of young breast cancer on the genetic level. Weber-Mangal found that additions or deletions of genomic copy number in young breast cancer patients are mainly located in parts of chromosome region. Anders reported that breast cancer arising in young patients had significantly low ERa, ERβ, and PR mRNA expression, but higher HER2and epidermal growth factor receptor (EGFR) expression. Pirone showed that significant associations between gene expression levels and age were identified for802gene probes. Yet there are seldom researches concentrating on the Asian young patients with breast cancer so far.Gene chip technology has been widely applied because of its characteristics of large-scale and high-throughput in recent years, thus gene expression data in the public network database increases day by day, which makes it possible to perform data mining and analysis using large sample.Young breast cancer patients were defined as<45years, while tumors arising in women≥65years were selected to represent an older comparison group in this study. We make a retrospective study with a large sample of clinical cases and a data mining and analysis using gene expression data downloaded from GEO datasets in order to gain a preliminary understanding of the clinical features and the potential biological mechanism of young breast cancer in Asia. This study has the vital practical significance in in-depth exploration of the molecular mechanism, guiding individualized treatment and improving prognosis of young breast cancer in Asia.Materials and Methods:1. Research object1.1A large-sample clinical data of patients with breast cancerWe collected the records of1,125cases of patients diagnosed with breast cancer in Nanfang Hospital, Southern Medical University between October2009and November2013. They were all female and the age at diagnosis was between20and87years, while the median and average ages were46and47.3years, respectively. The breast cancer patients aged≤45years or≥65years were allocated into different groups named younger group (experimental group) and older group (control group). 1.2152pairs of tissue specimens of breast cancerA consecutive series of breast cancer samples were collected from primary tumor of152patients (n=130,≤45years; n=22,≥65years) who did not accept neoadjuvant chemotherapy but underwent breast-conserving surgery or modified radical mastectomy between January2012and August2013.1.3Gene expression dataThe following two publicly-available datasets were downloaded from the GEO datasets:GSE45255, GSE15852. After age screening, there were totally36cases of young breast cancer patients’ microarray data and21cases of older breast cancer patients’microarray data been enrolled into the data mining and analysis finally.2. Research method2.1Retrospective studyA large-sample retrospective analysis was made between two groups in the clinical indicators such as clinicopathologic feature, immunohistochemical indicators, molecular subtype, tumor TNM stage and so on.2.2Analysis of gene expression dataThe gene expression profiling data was loaded using software packages based on R/Bioconductor and re-summarized using the RMA method and Entrez gene-centric CDF files (instead of original Affymetrix CDF files) after data quality assurance. Then the batch influence of two different datasets was eliminated using the combat algorithm. After the preprocessing of data, screening of differentially expressed genes, cluster analysis, GO (gene ontology) analysis and KEGG Pathway analysis were done step by step.2.3Real-time fluorescent quantitative PCRReal-time PCR was performed using the SYBR method to detect CXCL13, GABRP and ESRl gene mRNA expression of152pairs of tissue specimens and mRNA expression of housekeeping gene GAPDH was employed to normalized the expression of target genes. Relative quantification (Fold Change) between different samples was compared according to the2-△△Ct method. Quantitative RT-PCR (qRT-PCR) was conducted for each sample in triplicate. 2.4Western blottingThe total protein were extracted from6pairs of tissue specimens of young breast cancer patients and6pairs of tissue specimens of older breast cancer patients, which were randomly selected, and Western blotting and semi-quantitative analysis were performed using housekeeping protein GAPDH.2.5Immunohistochemistry48randomly selected paraffin sections of patients with breast cancer were stained with antibodies of CXCL13using SP method. CXCL13protein was localized in the cytoplasm, and five horizons of each slide were observed under high magnification. No positive staining, primrose yellow, yellow and brown were thought to be negative, weak, moderate and high expression of CXCL13, respectively.2.6Analysis of differences of CXCL13gene mRNA expression in different groups of clinical indicatorsThe differences of CXCL13gene mRNA expression in different groups of indicators were analyzed using Kruskal-Wallis H test and Mann-Whitney U test.Statistical analysis of all results in this study was performed using SPSS Statistic20.0, and P valve of <0.05was considered statistically significant.Results:1. Results of the large-sample retrospective analysisThere were535cases of young breast cancer patients, accounting for47.6%of all breast cancer patients, while the number of the older one was74, accounting for6.6%.There were statistically significant differences of composition of histological type between younger group and older group (P=0.001), and the proportion of IDC-NOS (invasive ductal carcinoma, not otherwise specified) in younger group was higher than in the older one (85.4%VS72.9%), while the proportion of special invasive ductal carcinoma in younger group was lower (5.1%VS18.9%). Also there were differences of histological grade, lymph node metastasis rate, ER-positive rate and proportion of molecular subtype between two groups, and the differences were statistically significant (P=0.009, P=0.035, P=0.041, P=0.005). There were no statistically significant differences of diameter of tumor, PR-positive rate, the intensity of HER2expression and tumor TNM stage.2. Analysis results of gene expression dataAnalysis of gene expression data showed that there were553differentially expressed genes in young breast cancer,81genes up-regulated and472genes down-regulated. GO analysis displayed that the differentially expressed genes were associated with59cell functions such as cofactor binding, mammary gland development, Wnt receptor signaling pathway and so on. KEGG pathway analysis revealed that the potential pathway included post translational protein modification, butanoate metabolism, inositol phosphate metabolism, phosphatidylinositol signaling system, Wnt signaling pathway, plcbeta mediated events, opioid signaling, purine metabolism, insulin signaling pathway, vascular smooth muscle contraction and calcium signaling pathway. Among these differentially expressed genes, there was a class of genes related to immune function such as CXCL13, IGHM, IGLL3P, IGJ, IGKC and so on, which were overexpressed significantly in young breast cancer. CXCL13showed the biggest fold change, amounting to2.64times, P=7.2×10-6.3. Detection of mRNA expression of target genesCXCL13gene mRNA expression significantly up-regulated in63.2%of breast cancer tissue (96/152, P=0.045), and the CXCL13gene mRNA expression in young breast cancer was significantly higher than in the older one (P=0.011). GABRP gene mRNA expression significantly down-regulated in67.8%of breast cancer tissue (103/152, P<0.0001), and the GABRP gene mRNA expression in young breast cancer was significantly higher than in the older one (P=0.005). ESR1gene mRNA expression significantly up-regulated in53.3%of breast cancer tissue (81/152, P=0.008), and the ESR1gene mRNA expression in young breast cancer was significantly lower than in the older one (P=0.009).4. Detection of CXCL13protein expression by Western blottingThe result of Western blotting showed that CXCL13protein relative expression in breast cancer tissues was significantly higher than in their corresponding adjacent normal tissues (P=0.015), while that in the young breast cancer was significantly higher than in their older counter (P=0.041).5. Detection of CXCL13protein expression by immunohistochemistryThe result of immunohistochemistry confirmed again that CXCL13protein expression in young breast cancer was significantly higher than in the older one (P=0.015).6. Analysis results of CXCL13gene mRNA expression in different groups of clinical indicatorsCXCL13gene mRNA expression in lymph node-positive or ER-negative group was higher than in lymph node-negative or ER-positive group, respectively (P=0.012, P=0.005).Conclusion:1. Young breast cancer accounts for47.6%of all female breast cancer. Compared with the older breast cancer, there are more invasive histological type, higher histological grade, lymph node-positive rate, lower ER-positive rate and less Luminal A subtype in young breast cancer.2. Analysis results of gene expression data displayed that the differentially expressed genes were associated with59cell functions such as cofactor binding, mammary gland development, Wnt receptor signaling pathway and so on. KEGG pathway analysis revealed that the potential pathway included post translational protein modification, Wnt signaling pathway, calcium signaling pathway and so on.3. CXCL13is up-regulated in young breast cancer, and the overexpression of CXCL13is related to lymph node-positive or ER-negative.Young breast cancer shows us a special biological behavior and there may be different potential biological mechanisms in it. The association between overexpression of CXCL13and poor prognosis in young breast cancer possibly presents a new diagnostic marker or therapeutic target, worthy of further research to investigate the function or mechanism of CXCL13. Background and objective:Breast cancer is one of the most frequent cancer of women worldwide by far. In different regions or races, there are differences between tumor biological factors of breast cancer. Widely use of gene chip technology makes it possible to carry out a comprehensive analysis of gene expression in Asian breast cancer for us. Meanwhile, the abnormal expression of multiple genes is the most important biological factors in oncogenesis and progression of breast cancer. A preliminary analysis of differences in gene expression and signaling pathways of breast cancer in Asia is practically significant for further exploring in the pathogenesis of Asian breast cancer, guidance of individualized treatment of breast cancer patients and improving the prognosis of patients with breast cancer.Materials and Methods:1. Downloading and analysis of gene expression dataThe following five publicly-available datasets were downloaded from the GEO datasets:GSE6367, GSE9309, GSE15852, GSE33447and GSE45255. Finally there were totally318cases of breast cancer microarray data and60cases of their corresponding normal tissue microarray data been enrolled into the data mining and analysis. 2. Collection of tissue specimens of breast cancerA consecutive series of breast cancer samples were collected from primary tumor of32patients who did not accept neoadjuvant chemotherapy but underwent modified radical mastectomy between August2013and September2013.3. Real-time fluorescent quantitative PCRTotal RNA of32pairs of tissue specimens was extracted according to Trizol method, reverse transcription was performed according to the instructions. Real-time PCR was performed using the SYBR method to detect the gene mRNA expression of32pairs of tissue specimens and mRNA expression of housekeeping gene GAPDH was employed to normalized the expression of target genes. Relative quantification (Fold Change) between different samples was compared according to the2-△△Ct method. Quantitative RT-PCR (qRT-PCR) was conducted for each sample in triplicate.Statistical analysis of all results in this study was performed using SPSS Statistic20.0, and P valve of <0.05was considered statistically significant.Results:1. Gene expression differences between Asians breast cancer tissue and normal breast tissueAnalysis of gene expression data showed that there were436differentially expressed genes in Asian breast cancer,259genes up-regulated and177genes down-regulated. KEGG pathway analysis revealed that the potential pathway included fatty acid metabolism, metabolism of lipids and lipoproteins and PPAR signaling pathway.2. Validation of differentially expressed genesThe results of quantitative PCR showed that, KRT19upregulated in breast cancer, while ADIPOQ, CFD, RBP4, LPL, ABCA8and CD36down-regulated in breast cancer tissues.Conclusion:Asian breast cancer primarily related to KRT19, ADIPOQ, CFD, RBP4, LPL, ABCA8and CD36gene. ADIPOQ, CFD, RBP4and LPL gene may play an important role in the metabolic processes, resulting in the occurrence, development and metastasis of breast cancer. CD36gene may be a specific gene that causes breast cancer in Asians; ABCA8gene may be a new Asian breast cancer-related gene. |
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