Identification and pathway analysis of microRNAs with no previous involvement in breast cancer.
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE35412 | GEO | 2012/03/10
SECONDARY ACCESSION(S): PRJNA152807
REPOSITORIES: GEO
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Project description:microRNA expression signatures can differentiate normal and breast cancer tissues and can define specific clinico-pathological phenotypes in breast tumors. In order to further evaluate the microRNA expression profile in breast cancer, we analyzed the expression of 667 microRNAs in 29 tumors and 21 adjacent normal tissues using TaqMan Low-density arrays. 130 miRNAs showed significant differential expression (adjusted P value=0.05, Fold Change=2) in breast tumors compared to the normal adjacent tissue. Importantly, the role of 43 of these microRNAs has not been previously reported in breast cancer, including several evolutionary conserved microRNA*, showing similar expression rates to that of their corresponding leading strand. The procedure begins with the retro-transcription of 70ng of total RNA with stem-loop primers to obtain a cDNA template. A pre-amplification step was included in order to increase the concentration of the original material and to detect microRNAs that are expressed at low levels. The pre-amplified product was loaded into the TaqManM-BM-. Low Density Arrays and amplification signal detection was carried out using the 7900 FAST real time thermal cycler (ABI). A total of 29 tumor and 21 normal samples (two pools: one containing five samples, other containing 12 samples, plus 4 independent normal samples) were analyzed. 23 tumors and the two normal pools were processed by triplicate, representing 82% of the total samples.
2012-03-10 | E-GEOD-35412 | biostudies-arrayexpress
Project description:Breast Cancer is the cancer with most incidence and mortality in women. microRNAs are emerging as novel prognosis/diagnostic tools. Our aim was to identify a serum microRNA signature useful to predict cancer development. We focused on studying the expression levels of 30 microRNAs in the serum of 96 breast cancer patients versus 92 control individuals. Bioinformatic studies provide a microRNA signature, designated as a predictor, based upon the expression levels of 5 microRNAs. Then, we tested the predictor in a group of 60 randomly chosen women. Lastly, a proteomic study unveiled the over-expression and down-regulation of proteins differently expressed in the serum of breast cancer patients versus that of control individuals. Twenty-six microRNAs differentiate cancer tissue from healthy tissue and 16 microRNAs differentiate the serum of cancer patients from that of the control group. The tissue expression of miR-99a-5p, mir-497-5p, miR-362, and miR-1274, and the serum levels of miR-141 correlated with patient survival. Moreover, the predictor consisting of mir-125b-5p, miR-29c-3p, mir-16-5p, miR-1260, and miR-451a was able to differentiate breast cancer patients from controls. The predictor was validated in 20 new cases of breast cancer patients and tested in 60 volunteer women, assigning 11 out of 60 women to the cancer group. An association of low levels of mir-16-5p with a high content of CD44 protein in serum was found. Circulating microRNAs in serum can represent biomarkers for cancer prediction. Their clinical relevance and use of the predictor here described might be of potential importance for breast cancer prediction.
2020-09-18 | PXD020795 | Pride
Project description:Using the highly sensitive miRCURY LNA™ microRNA array, we screened 3100 microRNAs abundant in the human colon cancer and Adjacent normal gastric mucosa tissues, and the function of differentially expressed microRNAs were analyzed by bioinformatics. The enrichment results indicated that these microRNAs perhaps participated in the occurrence and development process of colon cancer. In this study, three cases of colon cancer were used to acquire the microRNA expression profiling, and qPCR was employed to confirm the results of microRNA chip. The function of the differentially expressed microRNA were analyzed by bioinformatic methods.Finally,compared with the adjacent normal mucosa tissues，the expression of 2 microRNAs were up regulated in colon cancer. qPCR results showed an expression pattern consistent with that of the chip analysis.
2017-07-18 | GSE101502 | GEO
Project description:Deciphering the molecular mechanisms involved in breast tumorigenesis has been the subject of extensive research in the last years; yet unpredictable response and development of resistance to adjuvant therapies remain major questions in the management of breast cancer patients. The power of miR expression signatures has emerged recently from several studies. Normal and breast tumor tissues can be discriminated by a miR signature as reported by Iorio et al (Iorio et al, 2005). Recent findings have also linked deregulated miR expression to breast cancer metastasis (Adorno et al, 2009; Huang et al, 2008; Tavazoie et al, 2008). Moreover, microRNAs are considering as a powerful tool in diagnosis and prognosis of breast cancer. In our study, we measured microRNA expression profiles from 64 primary breast cancer patients, comprising 56 matched tumor and adjacent peritumoral breast tissues, 5 tumor and 3 peritumor unmatched tissues. Our aim was to identify new microRNAs involved in the process of neoplastic transformation. The microarray data analysis identified, in every subgroup of breast cancers analyzed, a specific subset of microRNAs that were differentially expressed in tumor compared to peritumoral tissues. Among these miRs, we identified two (miR-10b* and miR-139-5p) that were down-regulated and three (miR-425, miR-454 and miR-301a) that were up-regulated for all three subtypes. We further show that microRNA-10b* is a master regulator of breast cancer cell proliferation. Two canonical CpG islands (5kb) upstream from the precursor sequence are hypermethylated in breast cancer tissues analyzed. Ectopic delivery of synthetic microRNA-10b* in breast cancer cell lines or into xenograft mouse breast tumors inhibits cell proliferation and impairs tumor growth in vivo, respectively. We identified and validated in vitro and in vivo three novel target mRNAs of miR-10b*, BUB1, PLK1 and CCNA2 genes, which play a remarkable role in cell cycle regulation and whose high expression in breast cancer patients reduced disease free survival, relapse free survival and metastasis free survival when compared to low expressors. This also suggests that restoration of microRNA-10b* expression might bear therapeutic promise. In exploring the potential involvement of miRs in breast tumorigenesis, we profiled the miRs expression of 64 primary breast cancer patients, comprising 56 matched tumor and adjacent peritumoral breast tissues, 5 tumor and 3 peritumor unmatched tissues, using the Agilent microarray platform. For 14 samples technical replicate were also performed.
2012-10-30 | E-GEOD-40525 | biostudies-arrayexpress
Project description:Proteome characterization of 5 breast tumors and adjacent normal tissue using HiRIEF nanoLC-MS/MS.
2019-02-04 | PXD011385 | JPOST Repository
Project description:Deciphering the molecular mechanisms involved in breast tumorigenesis has been the subject of extensive research in the last years; yet unpredictable response and development of resistance to adjuvant therapies remain major questions in the management of breast cancer patients. The power of miR expression signatures has emerged recently from several studies. Normal and breast tumor tissues can be discriminated by a miR signature as reported by Iorio et al (Iorio et al, 2005). Recent findings have also linked deregulated miR expression to breast cancer metastasis (Adorno et al, 2009; Huang et al, 2008; Tavazoie et al, 2008). Moreover, microRNAs are considering as a powerful tool in diagnosis and prognosis of breast cancer. In our study, we measured microRNA expression profiles from 64 primary breast cancer patients, comprising 56 matched tumor and adjacent peritumoral breast tissues, 5 tumor and 3 peritumor unmatched tissues. Our aim was to identify new microRNAs involved in the process of neoplastic transformation. The microarray data analysis identified, in every subgroup of breast cancers analyzed, a specific subset of microRNAs that were differentially expressed in tumor compared to peritumoral tissues. Among these miRs, we identified two (miR-10b* and miR-139-5p) that were down-regulated and three (miR-425, miR-454 and miR-301a) that were up-regulated for all three subtypes. We further show that microRNA-10b* is a master regulator of breast cancer cell proliferation. Two canonical CpG islands (5kb) upstream from the precursor sequence are hypermethylated in breast cancer tissues analyzed. Ectopic delivery of synthetic microRNA-10b* in breast cancer cell lines or into xenograft mouse breast tumors inhibits cell proliferation and impairs tumor growth in vivo, respectively. We identified and validated in vitro and in vivo three novel target mRNAs of miR-10b*, BUB1, PLK1 and CCNA2 genes, which play a remarkable role in cell cycle regulation and whose high expression in breast cancer patients reduced disease free survival, relapse free survival and metastasis free survival when compared to low expressors. This also suggests that restoration of microRNA-10b* expression might bear therapeutic promise.
2012-10-30 | GSE40525 | GEO
Project description:BACKGROUND: The role played by microRNAs in the deregulation of protein expression in breast cancer is only partly understood. To gain insight, the combined effect of microRNA and mRNA expression on protein expression was investigated in three independent data sets. METHODS: Protein expression was modeled as a multilinear function of powers of mRNA and microRNA expression. The model was first applied to mRNA and protein expression for 105 selected cancer-associated genes and to genome-wide microRNA expression from 283 breast tumors. The model considered both the effect of one microRNA at a time and all microRNAs combined. In the latter case the Lasso penalized regression method was applied to detect the simultaneous effect of multiple microRNAs. RESULTS: An interactome map for breast cancer representing all direct and indirect associations between the expression of microRNAs and proteins was derived. A pattern of extensive coordination between microRNA and protein expression in breast cancer emerges, with multiple clusters of microRNAs being associated with multiple clusters of proteins. Results were subsequently validated in two independent breast cancer data sets. A number of the microRNA-protein associations were functionally validated in a breast cancer cell line. CONCLUSIONS: A comprehensive map is derived for the co-expression in breast cancer of microRNAs and 105 proteins with known roles in cancer, after filtering out the in-cis effect of mRNA expression. The analysis suggests that group action by several microRNAs to deregulate the expression of proteins is a common modus operandi in breast cancer.
2015-02-02 | GSE58210 | GEO
Project description:BACKGROUND: The role played by microRNAs in the deregulation of protein expression in breast cancer is only partly understood. To gain insight, the combined effect of microRNA and mRNA expression on protein expression was investigated in three independent data sets. METHODS: Protein expression was modeled as a multilinear function of powers of mRNA and microRNA expression. The model was first applied to mRNA and protein expression for 105 selected cancer-associated genes and to genome-wide microRNA expression from 283 breast tumors. The model considered both the effect of one microRNA at a time and all microRNAs combined. In the latter case the Lasso penalized regression method was applied to detect the simultaneous effect of multiple microRNAs. RESULTS: An interactome map for breast cancer representing all direct and indirect associations between the expression of microRNAs and proteins was derived. A pattern of extensive coordination between microRNA and protein expression in breast cancer emerges, with multiple clusters of microRNAs being associated with multiple clusters of proteins. Results were subsequently validated in two independent breast cancer data sets. A number of the microRNA-protein associations were functionally validated in a breast cancer cell line. CONCLUSIONS: A comprehensive map is derived for the co-expression in breast cancer of microRNAs and 105 proteins with known roles in cancer, after filtering out the in-cis effect of mRNA expression. The analysis suggests that group action by several microRNAs to deregulate the expression of proteins is a common modus operandi in breast cancer.
2015-02-02 | GSE58212 | GEO
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.
2013-09-06 | E-GEOD-42072 | biostudies-arrayexpress
Project description:Canine mammary gland tumors can be used as predictive models for human breast cancer. There are several types of microRNAs common in human breast cancer and canine mammary gland tumors. The functions of microRNAs in canine mammary gland tumors are not well understood. In the present study, we compared the characterization of microRNA expression in two-dimensional and three-dimensional canine mammary gland tumor cell models. The expression of microRNA-210 in the three-dimensional-SNP cells was 10.19 times higher than that in the two-dimensional-SNP cells.
2022-07-07 | GSE203410 | GEO