Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA306765 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Comprehensive genomic analysis identify novel subtypes and targets of triple-negative breast cancer (198 TNBC tumors)
| PRJNA306372 | ENA
Project description:Comprehensive genomic analysis identify novel subtypes and targets of triple-negative breast cancer
| PRJNA306766 | ENA
Project description:Analysis of 143 formalin-fixed, paraffin-embedded (FFPE) primary breast tumors using a Custom Breast Cancer Panel and Human Cancer Panel for the DASL platform. Molecular markers between the pathology defined subtypes of breast cancer were assessed to hypothesize potential therapeutic targets specific to the subtypes Molecular Characterization of 143 primary breast carcinomas including 101 triple negative (TN: ER-, PR-, HER2-), 3 HER2-positive (HER2+: ER-, PR-, HER2+), and 39 hormone receptor-positive (HR+: ER+ and/or PR+)
2009-10-23 | E-GEOD-18539 | biostudies-arrayexpress
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:Recent meta-analyses suggest triple-negative breast cancer (TNBC) is a heterogenous disease. In this study we sought to define these TNBC subtypes and identify subtype-specific markers and targets. We identified and confirmed four distinct, stable TNBC subtypes: (1) Luminal-AR (LAR); 2) Mesenchymal (MES); 3) Basal-Like Immune-Suppressed (BLIS), and 4) Basal-Like Immune-Activated (BLIA). RNA profiling analysis was conducted on 198 TNBC tumors (ER-negativity defined as Allred Scale value â¤2) with >50% cellularity (discovery set: n=84; validation set: n=114)
2015-12-18 | E-GEOD-76124 | biostudies-arrayexpress
Project description:CD8 T cells drive the anti-cancer immune response through the recognition of MHC I-associated peptides. In order to identify relevant targets for cancer immunotherapy in breast cancer, we characterized the immunopeptidome of 26 primary breast cancer samples from two different subtypes, hormone-receptor positive (n=14) and triple negative (n=12). We were able to identify tumor-specific and tumor associated antigens in both subtypes of breast cancer, which can be used for the development of anti-cancer vaccines or as targets for engineered T-cells.
2023-11-15 | PXD034818 | Pride
Project description:The dire need for more effective treatments for clinically aggressive breast cancers has motivated intensive investigations into their cellular and molecular etiology. Breast cancers that are “triple-negative” for the clinical markers, ESR1, PGR, and HER2, typically belong to the Basal-like molecular subtype. Defective Rb, p53, and Brca1 pathways are each associated with triple-negative and Basal-like subtypes. Our mouse genetic studies demonstrate that concomitant inactivation of all three pathways in mammary epithelium has an additive effect on tumor latency, and predisposes highly penetrant, metastatic, adenocarcinomas. These tumors are poorly differentiated with histologic features that are common among human Brca1-mutated tumors, including heterogeneous morphology, metaplasia, and necrosis. Transcriptomic analyses demonstrated that the tumors shared attributes of both Basal-like and Claudin-low signatures, two molecular subtypes encompassed by the broader triple-negative category defined by clinical markers. Ex vivo tumorsphere formation, which was suppressed by Notch and Wnt pathway inhibition, and tumor antigen profiles and are consistent with enrichment of stem-like and luminal progenitor cells among these tumors. These studies establish a novel mouse model of malignant breast cancer based on events in the human disease and underscore the non-reciprocal requirements of three canonical tumor suppressor pathways in breast cancer evolution. Morphogenetic pathways may provide additional avenues for targeted therapeutic intervention. Gene expression analysis of mouse mammary tumors with perturbation of Rb family pathways, p53, and/or Brca1 are compared to other mouse model tumors (n=152)
2011-12-17 | E-GEOD-34479 | biostudies-arrayexpress
Project description:Systems-wide profiling of breast cancer has so far built on RNA and DNA analysis by microarray and sequencing techniques. Dramatic developments in proteomic technologies now enable very deep profiling of clinical samples, with high identification and quantification accuracy. We analyzed 40 estrogen receptor positive (luminal), Her2 positive and triple negative breast tumors and reached a quantitative depth of more than 10,000 proteins. Comparison to mRNA classifiers revealed multiple discrepancies between proteins and mRNA markers of breast cancer subtypes. These proteomic profiles identified functional differences between breast cancer subtypes, related to energy metabolism, cell growth, mRNA translation and cell-cell communication. Furthermore, we derived a 19-protein predictive signature, which discriminates between the breast cancer subtypes, through Support Vector Machine (SVM)-based classification and feature selection. The deep proteome profiles also revealed novel features of breast cancer subtypes, which may be the basis for future development of subtype specific therapeutics.
2016-01-05 | PXD002619 | Pride
Project description:Breast cancer is one of the most common cancers in women. Of the different subtypes of breast cancer, the triple negative breast cancer subtype of breast cancer is the most aggressive. A proteomic screen of nucleolar content across breast cancer subtypes found that triple negative breast cancer cell lines have a distinct nucleolar proteome signature in comparison to non-TNBC breast cancer cell lines.
2021-03-05 | PXD021201 | Pride
Project description:Triple-negative breast cancer is a heterogeneous disease characterized by poor clinical outcomes and a shortage of targeted treatment options. To discover molecular features of triple-negative breast cancer, we performed quantitative proteomics analysis of twenty human-derived breast cell lines and four primary breast tumors to a depth of more than 12,000 distinct proteins. We used this data to identify breast cancer subtypes at the protein level and demonstrate the precise quantification of biomarkers, signaling proteins, and biological pathways by mass spectrometry. We integrated proteomics data with exome sequence resources to identify genomic aberrations that affect protein expression. We performed a high-throughput drug screen to identify protein markers of drug sensitivity and understand the mechanisms of drug resistance. The genome and proteome provide complementary information that, when combined, yield a powerful engine for therapeutic discovery. This resource is available to the cancer research community to catalyze further analysis and investigation.
2017-12-12 | PXD008222 | Pride