Project description:We report the application of single-molecule-based sequencing technology for high-throughput profiling of genes in E-, M-BCSCs and bulk tumor cells in two PDX models of triple negative breast cancer .
Project description:RNA-sequencing data from MDA-MB231 breast cancer cells, U87MG glioblastoma cells, and mouse breast cancer PDX models treated with antisense oligonucleotides targeting exon 2 of TRA2B. Additionally, RNA-sequencing data from MDA-MB231 breast cancer cells and U87MG glioblastoma cells treated with siRNAs targeting TRA2B. RNA-sequencing data from MDA-MB231 breast cancer cells nad U87MG glioblastoma cells treated with antisense oligonucleotides targeting exon 2 of TRA2B.
Project description:End-stage breast cancers are clonally heterogeneous and harbor many poorly-understood treatment resistance mechanisms. We therefore established multiple Patient-Derived-Xenograft (PDX) models to study genomic events driving advanced disease. Comparative whole-genome sequencing of paired primary tumors and their PDX models demonstrated that PDX retain the vast majority of the structural variations and copy number aberrations seen within the originating tumor, and with high fidelity. Variant allele fractions (VAF) were preserved, even for rare mutations. Clonal representation is therefore a transplantable phenotype, indicating that genomic heterogeneity can be regulated in a tumor-autonomous mechanism, indifferent to host immune status. Mutations and gene rearrangements were documented in the ESR1 gene in three of five sequenced luminal PDX/progenitor tumor pairs (amplification, point mutation and translocation), and were associated with clinical endocrine response phenotypes, differential PDX estradiol responsiveness and all induced estradiol-independent growth in standard cell lines. PDX models are therefore a significant new tool for fundamental studies on the molecular basis for resistance to endocrine treatment in advanced breast cancer. reference x sample
Project description:Developing animal models representating the cancer biology of advanced prostate cancer patients is challenging but essential for delivering individualized medical therapies. In an effort to develop patient derived xenograft (PDX) models, we took the metastatic site tissue from the rib lesion twice (ie, before and after enzalutamide treatment) over a twelve week period and implanted subcutaneously and under the renal capsule in immuno-deficient mice. To characterize and compare the genome and transcriptome landscapes of patient tumor tissues and the corresponding PDX models, we performed whole exome and transcriptome sequencing for metastatic tumor tissue as well as its derived PDXs. We demonstrated the feasibility of developping PDX models from patient who developed castrate-resistant prostate cancer. Our data suggested PDX models preserve the patient’s genomic and transcriptomic alterations in high fidelity, as illustrated by somatic mutation, copy number variation, gene fusion and gene expression. RNA sequencing of prostate cancer tumor tissue and derived xenograft using Illumina HiSeq 2000.
Project description:Breast cancer is the most commonly diagnosed cancer among women. PDXs (patient-derived xenografts) are similar to cancer cell lines but differ in that they are maintained in a physiological setting as soon as they are isolated from the patient and for subsequent passages. These models are valuable for preclinical trials because PDX models have been shown to closely match their patient counterparts, both in genomic profile and response to treatment. One challenge to treatment development is tumor heterogeneity. In this study, we profiled ER+ and triple negative breast cancer PDX models using single-cell RNA-sequencing. This data may help identify populations of cells which are susceptible to certain treatments in order to improve clinical outcomes for breast cancer patients.
Project description:Breast cancer is the most commonly diagnosed cancer among women. PDXs (patient-derived xenografts) are similar to cancer cell lines but differ in that they are maintained in a physiological setting as soon as they are isolated from the patient and for subsequent passages. These models are valuable for preclinical trials because PDX models have been shown to closely match their patient counterparts, both in genomic profile and response to treatment. One challenge to treatment development is tumor heterogeneity. In this study, we profiled ER+ and triple negative breast cancer PDX models using single-cell RNA-sequencing. This data may help identify populations of cells which are susceptible to certain treatments in order to improve clinical outcomes for breast cancer patients.
2024-09-30 | GSE276609 | GEO
Project description:WES of BRCA1-associated human PDX models (Bulk)
Project description:RNA-Seq and a species-specific mapping strategy were used to profile the human and mouse transcriptomes of tumour samples taken from 79 PDX models representing multiple cancer types (19 x breast, 37 x lung, 8 x colorectal, 7 x ovarian, 3 x endometrial, 2 x pancreatic, 2 x ampullary, 1 x leukaemia).
