Establishment of EGFR-inhibitor resistant triple negative breast cancer models from patient derived xenografts
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ABSTRACT:
PROVIDER: PRJNA782552 | ENA |
REPOSITORIES: ENA
Dataset's files
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| SRR16992317_1.fastq.gz | Fastqsanger.gz | |||
| SRR16992317_2.fastq.gz | Fastqsanger.gz | |||
| SRR16992318_1.fastq.gz | Fastqsanger.gz | |||
| SRR16992318_2.fastq.gz | Fastqsanger.gz | |||
| SRR16992319_1.fastq.gz | Fastqsanger.gz |
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Project description:Establishment of EGFR-inhibitor resistant triple negative breast cancer models from patient derived xenografts [scRNA-seq]
| PRJNA782558 | ENA
Project description:Establishment of EGFR-inhibitor resistant triple negative breast cancer models from patient derived xenografts [Bulk RNA-seq]
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Project description:Aim: The goals of this study were to identify transcriptomic changes that arise in basal-like breast cancer cells during the development of resistance to epidermal growth factor receptor inhibitors (EGFRi) and to identify drugs that are cytotoxic once EGFRi resistance occurs. Methods: Human patient-derived xenografts (PDXs) were grown in immunodeficient mice and were treated with a set of EGFRi; the EGFRi erlotinib was selected for more expansive in vivo studies. Single-cell RNA sequencing was performed on mammary tumors from the basal-like PDX WHIM2 that was treated with vehicle or erlotinib for nine weeks. The PDX was then subjected to long-term erlotinib treatment in vivo and through serialserially passaging, an erlotinib-resistant subline of WHIM2 was generated. Bulk RNA-sequencing was performed on parental and erlotinib-resistant tumors. In vitro high-throughput drug screening with >500 clinically used compounds was performed on parental and erlotinib-resistant cells. Previously published bulk gene expression microarray data from MMTV-Wnt1 tumors were contrasted with the WHIM2 PDX data. Results: Erlotinib effectively inhibited WHIM2 tumor growth for ~four weeks. Compared to untreated cells, single-cell RNA sequencing revealed that a greater proportion of erlotinib-treated cells were in the G1 phase of the cell cycle. Comparison of WHIM2 and MMTV-Wnt1 RNA level data revealed a set of 37 overlapping genes that were differentially expressed in the erlotinib-resistant subsets of WHIM2 and MMTV-Wnt1 tumors. Comparison of all three data types revealed five genes that were upregulated across all erlotinib-resistant samples: IL19, KLK7, LCN2, SAA1, and SAA2. Despite transcriptomic differences, parental and erlotinib-resistant WHIM2 displayed similar responses to the majority of drugs assessed for cytotoxicity in vitro. Conclusion: This study identified transcriptomic changes arising in erlotinib-resistant basal-like breast cancer. Interestingly, four of the five genes that were found to be upregulated in the basal-like erlotinib-resistant samples were also upregulated in erlotinib-resistant non-small cell lung cancer samples. These gene signatures could be used to identify basal-like breast cancer patients that would best respond to EGFRi. Future studies should explore the predictive capacity of these gene signatures as well as how these differentially expressed genes contribute to the development of EGFRi resistance.
2022-12-07 | GSE189324 | GEO
Project description:Aim: The goals of this study were to identify transcriptomic changes that arise in basal-like breast cancer cells during the development of resistance to epidermal growth factor receptor inhibitors (EGFRi) and to identify drugs that are cytotoxic once EGFRi resistance occurs. Methods: Human patient-derived xenografts (PDXs) were grown in immunodeficient mice and were treated with a set of EGFRi; the EGFRi erlotinib was selected for more expansive in vivo studies. Single-cell RNA sequencing was performed on mammary tumors from the basal-like PDX WHIM2 that was treated with vehicle or erlotinib for nine weeks. The PDX was then subjected to long-term erlotinib treatment in vivo and through serialserially passaging, an erlotinib-resistant subline of WHIM2 was generated. Bulk RNA-sequencing was performed on parental and erlotinib-resistant tumors. In vitro high-throughput drug screening with >500 clinically used compounds was performed on parental and erlotinib-resistant cells. Previously published bulk gene expression microarray data from MMTV-Wnt1 tumors were contrasted with the WHIM2 PDX data. Results: Erlotinib effectively inhibited WHIM2 tumor growth for ~four weeks. Compared to untreated cells, single-cell RNA sequencing revealed that a greater proportion of erlotinib-treated cells were in the G1 phase of the cell cycle. Comparison of WHIM2 and MMTV-Wnt1 RNA level data revealed a set of 37 overlapping genes that were differentially expressed in the erlotinib-resistant subsets of WHIM2 and MMTV-Wnt1 tumors. Comparison of all three data types revealed five genes that were upregulated across all erlotinib-resistant samples: IL19, KLK7, LCN2, SAA1, and SAA2. Despite transcriptomic differences, parental and erlotinib-resistant WHIM2 displayed similar responses to the majority of drugs assessed for cytotoxicity in vitro. Conclusion: This study identified transcriptomic changes arising in erlotinib-resistant basal-like breast cancer. Interestingly, four of the five genes that were found to be upregulated in the basal-like erlotinib-resistant samples were also upregulated in erlotinib-resistant non-small cell lung cancer samples. These gene signatures could be used to identify basal-like breast cancer patients that would best respond to EGFRi. Future studies should explore the predictive capacity of these gene signatures as well as how these differentially expressed genes contribute to the development of EGFRi resistance.
2022-12-07 | GSE189257 | GEO
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2022-12-07 | GSE189325 | GEO
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.
2018-10-22 | GSE117926 | GEO
Project description:DNA methylation of two triple-negative patient-derived breast cancer xenografts
| PRJNA483984 | ENA
Project description:RNA sequencing data from triple-negative breast cancer patient-derived xenografts (PDX)
| PRJNA434130 | ENA
Project description:Inhibitor of apoptosis (IAP) proteins constitute a conserved family of molecules which regulate both apoptosis and receptor signaling. They are often deregulated in cancer cells and represent potential targets for therapy. In our work, we investigated the effect of IAP inhibition in vivo to identify novel downstream genes expressed in an IAP-dependent manner that could contribute to cancer aggressiveness. To this end, immunocompromised mice engrafted subcutaneously with the triple negative breast cancer MDA-MB231 cell line were treated with SM83, a pan-IAP inhibitor developed by us, and tumor nodules were profiled for gene expression. Our work suggests that IAP-targeted therapy could contribute to EGFR inhibition and the reduction of its downstream mediators. This approach could be particularly effective in cells characterized by high levels of EGFR and Snai2, such as triple negative breast cancer.
2018-12-06 | GSE98691 | GEO
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.
2013-05-30 | E-GEOD-46106 | biostudies-arrayexpress