Project description:Patient derived xenografts (PDX) were created from two triple-negative breast cancers (PDX-110 and PDX-332) taken at the time of surgery from drug-naive patients. Freshly sorted epithelial cells were profiled by single-cell RNA-seq (scRNA-seq) using a 10X Genomics Chromium System.
Project description:Breast cancer research is hampered by difficulties in obtaining and studying primary human breast tissue, and by the lack of in vivo preclinical models that reflect patient tumor biology accurately. To overcome these limitations, we propagated a cohort of human breast tumors grown in the epithelium-free mammary fat pad of SCID/Beige and NOD/SCID/IL2γ-receptor null (NSG) mice, under a series of transplant conditions. Both models yielded stably transplantable xenografts at comparably high rates (~23% and ~19%, respectively). Of the conditions tested, xenograft take rate was highest in the presence of a low-dose estradiol pellet. Overall, 32 stably transplantable xenograft lines were established, representing unique 25 patients. Most tumors yielding xenografts were “triple-negative” (ER-PR-HER2+) (n=19). However, we established lines from three ER-PR-HER2+ tumors, one ER+PR-HER2-, one ER+PR+HER2- and one “triple-positive” (ER+PR+HER2+) tumor. Serially passaged xenografts show biological consistency with the tumor of origin, are phenotypic stability across multiple transplant generations at the histological, transcriptomic, proteomic, and genomic levels, and show comparable treatment responses. Xenografts representing 12 patients, including two ER+ lines, showed metastasis to the mouse lung. These models thus serve as a renewable, quality-controlled tissue resource for preclinical studies investigating treatment response and metastasis. The study was designed to determine how stable patient-derived xenografts are across multiple transplant generations in mice, and to determine how closely xenografts established with pre-treatment samples cluster with xenografts established with post-treatment samples. Overall, pre-treatment and post-treatment samples derived from the same patient cluster together, and multiple transplant generations of xenografts derived from an individual patient cluster together.
Project description:This microarray dataset contains 51 triple-negative breast cancers, 25 normal breast tissues, and 106 luminal breast cancers (reanalyzed data from Series GSE24124, GSE9309, and GSE17040). Keywords: Expression profiling by array
Project description:Breast cancer research is hampered by difficulties in obtaining and studying primary human breast tissue, and by the lack of in vivo preclinical models that reflect patient tumor biology accurately. To overcome these limitations, we propagated a cohort of human breast tumors grown in the epithelium-free mammary fat pad of SCID/Beige and NOD/SCID/IL2γ-receptor null (NSG) mice, under a series of transplant conditions. Both models yielded stably transplantable xenografts at comparably high rates (~23% and ~19%, respectively). Of the conditions tested, xenograft take rate was highest in the presence of a low-dose estradiol pellet. Overall, 32 stably transplantable xenograft lines were established, representing unique 25 patients. Most tumors yielding xenografts were “triple-negative” (ER-PR-HER2+) (n=19). However, we established lines from three ER-PR-HER2+ tumors, one ER+PR-HER2-, one ER+PR+HER2- and one “triple-positive” (ER+PR+HER2+) tumor. Serially passaged xenografts show biological consistency with the tumor of origin, are phenotypic stability across multiple transplant generations at the histological, transcriptomic, proteomic, and genomic levels, and show comparable treatment responses. Xenografts representing 12 patients, including two ER+ lines, showed metastasis to the mouse lung. These models thus serve as a renewable, quality-controlled tissue resource for preclinical studies investigating treatment response and metastasis.
Project description:This SuperSeries is composed of the SubSeries listed below. All the data are described in the article "Fra-1 regulates its target genes via binding to remote enhancers without exerting major control on chromatin architecture in triple negative breast cancers" by Bejjani et al.
Project description:Background: This study focuses on the analysis of miRNAs expression data in a cohort of 181 well characterised breast cancer samples composed primarily of triple-negative (ER/PR/HER2-negative) tumours with associated genome-wide DNA and mRNA data, extensive patient follow-up and pathological information. Results: We identified 7 miRNAs with a prognostic role in the triple-negative tumours and an additional 8 prognostic miRNAs when the analysis was extended to the set of all ER-negative cases. miRNAs linked to an unfavourable prognosis were associated with a broad spectrum of motility mechanisms involved in the invasion of stromal tissues, such as cell-adhesion, growth factor-mediated signalling pathways, interaction with the extracellular matrix and cytoskeleton remodelling. When we compared different intrinsic molecular subtypes we found 46 miRNAs that were specifically expressed in one or more intrinsic subtypes. Integrated genomic analyses indicated these miRNAs to be largely influenced by DNA genomic aberrations and to exert a silencing effect on their targets through transcriptional down-regulation. Among others, our analyses highlighted the role of miR17-92 and miR-106b-25, two polycistronic miRNA clusters with known oncogenic functions. We showed that their basal-like specific up-regulation is influenced by increased DNA copy number and contributes to the transcriptional phenotype and the activation of oncogenic pathways in basal-like tumours.Conclusions: This is the first study analysing miRNA, mRNA and DNA data in integration with pathological and clinical information, in a large and well-annotated cohort of triple-negative breast cancers. It provides a conceptual framework, as well as integrative methods and system-level results to elucidate the role of miRNAs as biomarkers and modulators of oncogenic processes in these types of tumours. 181 breast tumour samples were analyzed, extracted from 173 patients. For the great majority of patients (165) only one sample was extracted, while for 8 patients two samples were extracted (biological replicates).
Project description:Long non-coding RNAs have been implicated in many of the hallmarks of cancer. We previously annotated lncRNA152 (lnc152; a.k.a. DRAIC) and demonstrated its roles in proliferation, cell cycle progression, and regulation of the estrogen signaling pathway in breast cancer cells. Herein, we found that lnc152 is highly upregulated in luminal breast cancers, but is downregulated in triple-negative breast cancers (TNBC). Using a set of complementary experimental approaches, we found that knockdown of lnc152 promotes cell migration and invasion in luminal breast cancer cell lines. In contrast, ectopic expression of lnc152 inhibits growth, migration, invasion, and angiogenesis in TNBC cell lines. In xenograft studies in mice, lnc152 inhibited the growth and metastasis of TNBC cells. Transcriptome analysis of the xenografts indicated that lnc152 downregulates genes regulating cancer-related phenotypes, including angiogenesis. Using RNA-pull down assays coupled with LC-MS/MS analysis, we identified RBM47, a known tumor suppressor protein in breast cancer, as a lnc152-interacting protein. We found that lnc152 suppresses the aggressive phenotypes of TNBC cells by regulating the expression of RBM47. Collectively, our results demonstrate that lnc152 is an angiogenesis-inhibiting tumor suppressor that attenuates the aggressive cancer-related phenotypes found in TNBC.