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:All-trans retinoic acid (atRA) regulates gene expression and is used to treat acute promyelocytic leukemia. Attempts to use atRA for breast cancer treatment without a stratification strategy have resulted in limited overall effectiveness. To identify biomarkers for the treatment of triple-negative breast cancer (TNBC) with atRA, we characterized the effects of atRA on the tumor growth of 13 TNBC cell lines. This resulted in a range of tumor growth effects that was not predictable based on the levels of retinoid signaling molecules and transcriptional responses that were mostly independent of retinoic acid response elements. Given the importance of DNA methylation in regulating gene expression, we hypothesized that differential DNA methylation could predict the response of TNBCs to atRA. We identified over 1400 CpG sites that were differentially methylated between atRA resistant and sensitive cell lines. These CpG sites predicted the response of four TNBC patient-derived xenografts to atRA treatment and we utilized these xenografts to refine the profile to 6 CpGs. We identify as many as 17% of TNBC patients who could benefit from atRA treatment. These data illustrate that differential DNA methylation of specific sites may predict the response of patient tumors to atRA treatment.