MiRNA expression analysis of breast cancer tissue and matched nomal tissue
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE154255 | GEO | 2023/06/15
REPOSITORIES: GEO
Similar Datasets
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:Breast cancer is a heterogeneous disease for which prognosis and treatment strategies are largely governed by the receptor status (estrogen, progesterone and Her2-neu) of the tumor cells. Gene expression profiling of whole breast tumors further stratifies breast cancer into several molecular subtypes which also co-segregate with the receptor status of the tumor cells. We postulated that cancer associated fibroblasts (CAFs) within the tumor stroma may exhibit subtype specific gene expression profiles and thus contribute to the biology of the disease in a subtype specific manner. Several studies have reported gene expression profile differences between CAFs and normal breast fibroblasts but in none of these studies were the results stratified based on tumor subtypes. To address whether gene expression in breast cancer associated fibroblasts varies between breast cancer subtypes, we compared the gene expression profiles of early passage primary CAFs isolated from twenty human breast cancer samples representing three main subtypes; seven ER+, seven triple negative (TNBC) and six Her2+. We observed significant expression differences between CAFs derived from Her2+ breast cancer and CAFs from TNBC and ER+ cancers, particularly in pathways associated with cytoskeleton and integrin signaling. In the case of Her2+ breast cancer, the signaling pathways found to be selectively up regulated in CAFs may contribute to the more invasive properties and unfavorable prognosis of Her2+ breast cancer. These data demonstrate that in addition to the distinct molecular profiles that characterize the neoplastic cells, CAF gene expression is also differentially regulated in distinct subtypes of breast cancer. We isolated CAFs from twenty primary breast cancer samples representing three main subtypes (ER+ (n=7), TNBC (n=7), Her2+ (n=6)) and performed gene expression profile analyses on RNA isolated from these early passage CAFs. Those samples were done in two batches with 4 samples repeated in both batches. One TNBC sample was found to be an outlier and not used in the analysis.
2013-12-20 | E-GEOD-37614 | biostudies-arrayexpress
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
2013-11-08 | GSE52194 | GEO
Project description:This study developed a triple-negative breast cancer (TNBC) surrogate subtype classification that represents TNBC subtypes based on the Vanderbilt subtype classification The web-based subtyping tool TNBCtype was used to classify the TNBC cohort into Vanderbilt subtypes
2023-03-04 | GSE226289 | GEO
Project description:We performed high throughput transcriptome of breast cancer and normal tissues, identifying lincRNA associated molecular subtype with powerful capacity to distinct breast cancer population and predict prognosis. We also identified subtype-specific lincRNAs that may be a useful complement to intrinsic molecular subtype classification when divergence emerges among pathologists.Paired-end transcriptome sequencing were carried out on a cohort of 33 breast tissues from 11 groups including five breast cancer subtypes including luminal A (LA), luminal B (HER2 negative)(LB, HER2-), luminal B (HER2 positive) (LB, HER2+), HER2 and tripple negative breast cancer (TNB), adjacent noncancerous breast tissue (ANT, three samples for each subtype) and the complete normal breast tissues (three samples)
2017-09-06 | GSE71651 | GEO
Project description:RNA-seq was performed on breast cancer cell lines and primary tumors RNA-seq was performed on 28 breast cancer cell lines, 42 Triple Negative Breast Cancer (TNBC) primary tumors, and 42 Estrogen Receptor Positive (ER+) and HER2 Negative Breast Cancer primary tumors, 30 uninovlved breast tissue samples that were adjacent to ER+ primary tumors, 5 breast tissue samples from reduction mammoplasty procedures performed on patients with no known cancer, and 21 uninvolved breast tissue samples that were adjacent to TNBC primary tumors.
2014-06-11 | E-GEOD-58135 | biostudies-arrayexpress
Project description:Breast cancer is a heterogeneous disease for which prognosis and treatment strategies are largely governed by the receptor status (estrogen, progesterone and Her2-neu) of the tumor cells. Gene expression profiling of whole breast tumors further stratifies breast cancer into several molecular subtypes which also co-segregate with the receptor status of the tumor cells. We postulated that cancer associated fibroblasts (CAFs) within the tumor stroma may exhibit subtype specific gene expression profiles and thus contribute to the biology of the disease in a subtype specific manner. Several studies have reported gene expression profile differences between CAFs and normal breast fibroblasts but in none of these studies were the results stratified based on tumor subtypes. To address whether gene expression in breast cancer associated fibroblasts varies between breast cancer subtypes, we compared the gene expression profiles of early passage primary CAFs isolated from twenty human breast cancer samples representing three main subtypes; seven ER+, seven triple negative (TNBC) and six Her2+. We observed significant expression differences between CAFs derived from Her2+ breast cancer and CAFs from TNBC and ER+ cancers, particularly in pathways associated with cytoskeleton and integrin signaling. In the case of Her2+ breast cancer, the signaling pathways found to be selectively up regulated in CAFs may contribute to the more invasive properties and unfavorable prognosis of Her2+ breast cancer. These data demonstrate that in addition to the distinct molecular profiles that characterize the neoplastic cells, CAF gene expression is also differentially regulated in distinct subtypes of breast cancer.
2013-12-20 | GSE37614 | GEO
Project description:Transcriptome analysis of 130 breast cancer samples (41 TNBC ; 30 Her2 ; 30 Luminal B and 29 Luminal A), 11 normal breast tissue samples and 14 TNBC cell lines.
2015-01-23 | GSE65212 | GEO
Project description:Transcriptome analysis of 130 breast cancer samples (41 TNBC ; 30 Her2 ; 30 Luminal B and 29 Luminal A), 11 normal breast tissue samples and 14 TNBC cell lines.
2015-01-23 | GSE65194 | GEO
Project description:Specific Breast Cncer (BC) subtypes are associated with a bad prognosis due to the absence of successful treatment plans. Moreover, the triple negative breast cancer (TNBC) subtype, with estrogen (ER), progesterone (PR) and human epidermal growth factor-2 (HER2) negative receptors status, were characterized by unsuccessful therapies, makes it a clinical challenge for oncologists. In addition, Proton RadioTherapy (PRT) represents an effective treatment also against conventional radiotherapy (RT) resistant cancers, and a promising therapeutically choice for TNBC. Our study aimed at analyze the in vivo molecular response induced by PRT in a MDA-MB-231 triple negative Breast Cancer xenograft model, focusing on gene expression profile (GEP) analyses. Our results demonstrate the multiple advantages of xenograft tissue microarrays for preclinical signature characterization of PRT to understand the molecular mechanism activated and to discover new molecular targets.
2020-10-02 | GSE149023 | GEO