Unknown,Transcriptomics,Genomics,Proteomics

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Identification of significant gene regulations for breast cancer from human tissues

ABSTRACT: To discover individual genes with potential diagnostic and therapeutic utilities, we use gene expression profiling from real patient tissues to identify significantly regulated genes out of a broad coverage of human transcriptome. We use Agilent gene expression microarray technologies to measure gene expressions of 32 cancerous and normal tissues from breast cancer patients. Total RNAs were extracted and analyzed using Agilent microarray technologies. The whole genome expression profiling has been proformed and several significantly differently expressed genes (such as HS3ST4, MMP1, MMP11) were quatified by qPCR to verify their up/down-regulations, leading to discovery of important genes related to breast cancer metastasis. We examined 32 human breast tissues of three different breast cancer subtypes (including Luminal A, Luminal B, Triple Negative) and normal controls to perform microarray gene expression profiling.

ORGANISM(S): Homo sapiens

SUBMITTER: Xin Qi

PROVIDER: E-GEOD-57297 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Purpose: There is a quest for novel non-invasive diagnostic markers for the detection of breast cancer. The goal of this study is to identify circulating microRNA signatures using a cohort of Asian Chinese breast cancer patients, and to compare microRNA profiles between tumour and serum samples. Experimental design: MicroRNAs from paired breast cancer tumours, normal tissue and serum samples derived from 32 patients were comprehensively profiled using microarrays (1300 microRNAs against tumour and normal tissues) or LNA RT-PCR panels (742 microRNAs against serum samples). Serum samples from healthy individuals (n=22) were also employed as normal controls. Significant serum microRNAs, identified by logistic regression, were validated in an independent set of serum samples from patients (n=82) and healthy controls (n=53). Results: The 20 most significant microRNAs differentially expressed in breast cancer tumours included miR-21, miR-10b, and miR-145, previously shown to be dysregulated in breast cancer. Interestingly, 16 of the 20 most significant microRNAs differentially expressed in serum samples were novel. MiR-1, miR-92a, miR-133a and miR-133b were identified as the most important diagnostic markers, and were successfully validated; receiver operating characteristic curves derived from combinations of these microRNAs exhibited areas under the curves of 0.944-0.946. Only seven microRNAs were overexpressed in both tumours and serum, suggesting that microRNAs may be released into the serum selectively. Conclusion: The clinical employment of microRNA signatures as a non-invasive diagnostic strategy is promising, but should be further validated for different subtypes of breast cancers. "_A" and "_B" are two tissue sections of the same sample; "_1" and "_2" represents 2 runs of the same sample; na = not available All tissue samples were histologically confirmed by a pathologist using hematoxylin and eosin staining of cryosectioned specimens. One tumour sample was rejected due to failure to detect any tumour cells. Except for two samples (with 30% and 40% tumour cells), all tumour tissues employed had a minimum of 60% tumour cells, as estimated microscopically. Overall, the breast cancer tumour samples had an average of 71% tumour cells. The criteria for adjacent normal tissue were absence of tumour cells and presence of epithelial cells. Hence, after histological confirmation, 31 breast cancer tumours and 23 matched normal tissues were employed for microRNA extraction and profiling using microarray.

Project description:Acquired resistance to trastuzumab, a rationally designed HER-2 targeting antibody, remains a major hurdle in management of HER-2 positive breast cancer (HER-2+ BC) patients. Potential resistance mechanisms are numerous, derived primarily from studies where HER-2 positive cell lines are chronically exposed to trastuzumab. Recent evidence suggests a role for epithelial-mesenchymal transition (EMT) in trastuzumab resistance, but a definitive link between the two has been difficult to establish because relevant model systems are lacking. When sub-populations of trastuzumab sensitive SKBR-3 cells were isolated using cloning rings, an (EMT) occurred spontaneously in several (3/8) clones. SKBR-3 EMT-clones featured increased spindle morphology, expressed N-glycosylated M-NM-21-integrin, and decreased HER-2, all characteristics shared by JIMT-1, a cell lines with intrinsic resistance to trastuzumab. SKBR-3 EMT-clones were characterized by gene expression profiling and mammosphere formation. The N-glycosylated isoform of M-NM-2-itnegrin was targeted with M-NM-2-integrin inhibiting antibody, AIIB2. Transcriptional profiling revealed that SKBR-3 EMT-clones underwent a shift from a luminal molecular subtype to a more aggressive mesenchymal/ basal phenotype. Isolating clones from SKBR-3 cells with enforced expression of a M-NM-2-integrin isoform lacking extensive N-glycosylation failed to increase the likelihood for spontaneous EMT in SKBR-3. However, specific inhibition of the heavily N-glycosylated variant of M-NM-21-integrin expressed by SKBR-3 EMT-clones restored epithelial morphology and impaired mammosphere formation. Furthermore, when SKBR-3 EMT-clones were treated with relevant doses of trastuzumab and lapatinib, they showed M-bM-^@M-^\spontaneousM-bM-^@M-^] resistance. In this study we describe a model of spontaneous EMT following clonal selection in HER-2+ cell line, SKBR-3. Using this model we establish the first direct link between EMT and resistance to HER-2 targeted therapies. We also identify the N-glycosylated isoform of M-NM-2-integrin as a potential biomarker and target in HER-2+ BC refractory to HER-2 targeted therapies. RNA was isolated from 10 breast cancer cell lines in triplicate. Pairwise gene expression differences were compared between each of the SKBR-3 cell lines (SKBR-3/ b1, SK-EV-C4, and SK-B1-C1). Features selected had at least a 2X difference in at least one comparison, with a one-way ANOVA corrected p-value of >0.05. In addition, expression profiles from SKBR-3/ EV and SK-B1-C1 cell were compared and a differential gene list was generated to include genes that differed by at least 1.5X, with a t-test p-value of >0.02 (unpaired, Bonferroni corrected). A total of 1940 entities met these criteria and the expression of these genes was investigated in all breast cancer cell lines.

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Identification of significant gene regulations for breast cancer from human tissues

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