Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA99969 | ENA |
REPOSITORIES: ENA
Similar Datasets
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: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. Blood samples were collected in Becton Dickinson (Franklin Lakes, NJ) Vacutainer SST tubes. Serum was harvested by centrifugation at 2200g after allowing blood to clot for 30mins. 32 patient samples and 22 samples from healthy controls were obtained for profiling. Sera samples were stored at -80oC.
2013-09-06 | E-GEOD-41922 | biostudies-arrayexpress
Project description:The aim of this study was to analyse alterations in circulating microRNA expression during breast tumour progression in a murine model, and to apply significantly altered miRNAs to patient samples to identify novel circulating microRNA markers or tumour progression. Athymic nude mice (n=10) received an injection of 2 x 105 MDA-MB-231 cells. Tumour volume was monitored weekly and blood sampling performed at weeks 1 and 6 following tumour induction. A microRNA array was performed comparing circulating 384 microRNAs in animals with early (week 1, n=5) versus late (week 6, n=5) disease.
2013-09-01 | GSE47455 | 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.
2013-09-06 | GSE41922 | GEO
Project description:Goal: To define the digital transcriptome of three breast cancer subtypes (TNBC, Non-TNBC, and HER2-positive) using RNA-sequencing technology. To elucidate differentially expressed known and novel transcripts, alternatively spliced genes and differential isoforms and lastly expressed variants in our dataset. Method: Dr. Suzanne Fuqua (Baylor College of Medicine) provided the human breast cancer tissue RNA samples. All of the human samples were used in accordance with the IRB procedures of Baylor College of Medicine. The breast tumour types, TNBC, Non-TNBC and HER2-positive, were classified on the basis of immunohistochemical and RT-qPCR classification. Results: Comparative transcriptomic analyses elucidated differentially expressed transcripts between the three breast cancer groups, identifying several new modulators of breast cancer. We discovered subtype specific differentially spliced genes and splice isoforms not previously recognized in human transcriptome. Further, we showed that exon skip and intron retention are predominant splice events in breast cancer. In addition, we found that differential expression of primary transcripts and promoter switching are significantly deregulated in breast cancer compared to normal breast. We also report novel expressed variants, allelic prevalence and abundance, and coexpression with other variation, and splicing signatures. Additionally we describe novel SNPs and INDELs in cancer relevant genes with no prior reported association of point mutations with cancer mRNA profiles of 17 breast tumor samples of three different subtypes (TNBC, non-TNBC and HER2-positive) and normal human breast organoids (epithelium) samples (NBS) were sequenced using Illumina HiSeq.
2013-11-08 | E-GEOD-52194 | biostudies-arrayexpress
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
2013-09-06 | GSE42072 | GEO
Project description:MicroRNAs (miRNAs), a class of short non-coding RNAs, often act post-transcriptionally to inhibit gene expression. We used a bead-based flow cytometric profiling method to obtain miRNA expression data for 93 primary human breast tumours, 21 cell lines and five normal breast samples. Of 309 human miRNAs assayed we identify 133 miRNAs expressed in human breast and breast tumours. We used mRNA expression profiling to classify the breast tumours into Luminal A, Luminal B, Basal-like, HER2+/ER- and Normal-like. A number of miRNAs are differentially expressed between these molecular tumour subtypes and individual miRNAs are associated with clinicopathological factors. Furthermore, we find that miRNAs could classify basal versus luminal tumour subtypes in an independent data set. Keywords = miRNA Keywords = microRNA Keywords = normal Keywords = tumour Keywords = cell line Keywords = breast Keywords = cancer Keywords: Bead-based flow cytometric profiling miRNA expression data for 93 primary human breast tumours, 21 cell lines and five normal breast samples
2007-10-09 | E-GEOD-7842 | biostudies-arrayexpress
Project description:MicroRNAs (miRNAs), a class of short non-coding RNAs, often act post-transcriptionally to inhibit gene expression. We used a bead-based flow cytometric profiling method to obtain miRNA expression data for 93 primary human breast tumours, 21 cell lines and five normal breast samples. Of 309 human miRNAs assayed we identify 133 miRNAs expressed in human breast and breast tumours. We used mRNA expression profiling to classify the breast tumours into Luminal A, Luminal B, Basal-like, HER2+/ER- and Normal-like. A number of miRNAs are differentially expressed between these molecular tumour subtypes and individual miRNAs are associated with clinicopathological factors. Furthermore, we find that miRNAs could classify basal versus luminal tumour subtypes in an independent data set. Keywords = miRNA Keywords = microRNA Keywords = normal Keywords = tumour Keywords = cell line Keywords = breast Keywords = cancer Keywords: Bead-based flow cytometric profiling
2007-10-09 | GSE7842 | GEO
Project description:Accurate characterization and understanding of the breast cancer subtypes is of crucial clinical importance to the heterogeneity of this disease. Several layers of information, including immunohistochemical markers, mRNA and microRNA expression profiles, and pathway analysis have been used for such purpose in several studies. However, a comprehensively integrative approach is currently missing. This paper provides microRNA and mRNA expression profiles, characterizing four breast tumor subtypes, as defined by four immunohistochemical markers. The defined sets of features were validated in two independent data sets at multiple levels, including unsupervised clustering and supervised classification. Moreover, the gene expression signatures of the tumor subtypes were screened by in-depth analysis of 12 cancer core pathways. We successfully identified and validated a novel breast cancer subtypes gene expression signature composed of 976 mRNAs and 69 miRNAs. Luminal and non-luminal tumors are shown to significantly differ both at the mRNA and miRNA levels. HER2 positive tumors are more closely related to triple negative tumors by mRNA profiling than by miRNA expression. Closely related miRNAs sharing the same targets may exert opposite roles during tumor progression. Besides the core cancer pathways, other pathways such as those controling biomass synthesis are shown to be important to enable the core basal subtype with additional progressive nature compared with the other triple negative tumors. Some therapeutic strategies are proposed for breast cancer treatment, including the combined blockage of MAPK/ERK and PI3K/Pten signalings for tumors with poor clinical outcome, and targeting Wnt and JAK/STAT and/or Hedgehog, depending on tumor subtypes, together with conventional chemotherapy with the purpose of achieving an eradicative outcome. The pathway analysis also reveals that the clinical strategy and pivotal targets need to be tuned according to different tumor subtypes. This study is the first attempt to elucidate breast cancer subtypes by combining microRNA and mRNA expression, immunohistochemical markers, and cancer core pathways. The results can avail the functional studies of the etiology of breast cancer and translated for clinical use given their intrinsic link in terms of immunohistochemistry and survival. This submission consists of microRNA profiles of 115 breast cancer tumors of several subtypes only.
2013-06-01 | E-GEOD-43040 | biostudies-arrayexpress
Project description:Plasticity delineates cancer subtypes with more or less favourable outcomes. In breast cancer, triple-negative is the subtype that lacks the expression of major differentiation markers (i.e. estrogen receptor [ER]), ant its high cellular plasticity results in higher aggressiveness and poor prognosis compared to other subtypes. Whether plasticity poses a vulnerability to cancer cells remains elusive. Here, we show that cancer cell plasticity can be exploited to differentiate triple-negative breast cancer. Using a high-throughput reporter drug screen with 9,501 compounds, we identify three polo-like kinase 1 (PLK1) inhibitors as major inducers of ER protein expression and downstream activity in triple-negative breast cancer cells via the transcription factor BATF. PLK1 inhibition upregulates a cell differentiation program characterized by increased DNA damage, mitotic arrest and ultimately cell death. Notably, cells surviving PLK1 inhibition have decreased tumorigenic potential, and targeting PLK1 in already established tumours reduces tumour growth both in cell line and patient-derived xenograft models. In addition, genes upregulated upon PLK1 inhibition are correlated with expression in normal breast tissue and confer better overall survival in breast cancer patients. Our results indicate that differentiation therapy based on PLK1 inhibition might be an alternative strategy to treat triple-negative breast cancer.
2022-08-23 | PXD028495 | Pride