RNA sequencing data from triple-negative breast cancer patient-derived xenografts (PDX)
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE110626 | GEO | 2018/03/09
REPOSITORIES: GEO
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Project description:SurePrint G3 Human Gene Expression Microarray v2 was used to obtain gene expression profiles of two different TNBC PDX models sensitive to docetaxel and in the docetaxel resistant TNBC PDX models derived from both initially sensitive.
2019-07-30 | GSE110153 | GEO
Project description:RNA sequencing data from triple-negative breast cancer patient-derived xenografts (PDX)
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Project description:Osteosarcoma (OS) and Ewing’s sarcoma (EW) are the two most common pediatric solid tumors, after brain tumors. Multimodal treatments have significantly improved prognosis in localized disease but outcome is still poor in metastatic patients, for whom therapeutic options are often inadequate. Preclinical drug testing to identify promising treatment options that match the molecular make-up of these tumors is hampered by the lack of appropriate and molecularly well-characterized patient-derived models. To address this need, a panel of patient-derived xenografts (PDX) was established by subcutaneous implantation of fresh, surgically resected OS and EW tumors in NSG mice. Tumors were re-transplanted to next mice generations and fragments were collected for histopathological and molecular characterization. A model was considered established after observing stable histological and molecular features for at least three passages. To evaluate the similarity of the model with primary tumor, we performed a global gene expression profiling and tissue microarrays (TMA), to assess tumor specific biomarkers on tissues from OS/EW tumors and their PDXs (1st and 3rd passage). Moreover, we verified the feasibility of these models for preclinical drug testing. We implanted 61 OS and 29 EW samples: 14/38 (37%) primary OS and 9/23 (39%) OS lung metastases successfully engrafted; while among EW, 5/26 (19%) primary samples and 1/3 (33%) metastases were established. Comparison between patient samples and PDXs, highlighted that histology and genetic characteristics of PDXs were stable and maintained over passages. In particular, correlative analysis between OS and EW samples and their PDXs was extremely high (Pearson’s r range r=0.94-0.96), while patient-derived primary cultures displayed reduced correlation with human samples (r=0.90-0.93), indicating that in vitro adaptation superimpose molecular alterations that create genetic diversion from original tumors. No significant differentially expressed gene profile was observed from the comparison between EW samples and PDXs (fold change > 2, adjusted p <0.05 at paired t-test). In OS, the comparison between OS patient-derived tumors and PDX indicated differences in 397 genes, mostly belonging to immune system functional category. This is in line with the idea that human immune cells are gradually replaced by murine counterparts upon engraftment in the mouse. As proof-of concept, two EW PDX and one OS PDX have been treated with conventional and innovated drugs to test their value in terms of drug-sensitivity prediction. Overall, our study indicated that PDX models maintained the histological and genetic markers of the tumor samples and represent reliable models to test sensitivity to novel drug associations.
2019-08-27 | E-MTAB-7568 | biostudies-arrayexpress
Project description:To characterize Homologous recombination deficiency (BRCAness) in triple-negative breast cancer PDX models genomic signature was utilized. After normalization using Genotyping Console we obtained absolute copy number profiles using the GAP software (Popova et al, Genome Biol, 2009). The number of Large-scale State Transitions (LSTs) was used to annotate PDX as BRCAness or not (Popova et al, Cancer Res 2012).
2020-01-01 | E-MTAB-8654 | biostudies-arrayexpress
Project description:To characterize Homologous recombination deficiency (BRCAness) in triple-negative breast cancer PDX models genomic signature was utilized. After normalization using ChAS we obtained absolute copy number profiles using the GAP software (Popova et al, Genome Biol, 2009). The number of Large-scale State Transitions (LSTs) was used to annotate PDX as BRCAness or not (Popova et al, Cancer Res 2012).
2020-01-01 | E-MTAB-8653 | biostudies-arrayexpress
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
Project description:A significant proportion of patients with oestrogen receptor (ER) positive breast cancers (BC) develop resistance to endocrine treatments (ET) and relapse with metastatic disease. Bone is the most common metastatic site in ER+ patients, however bone metastases are technically challenging to biopsy and analyse. Difficulties concern both tumour tissue acquisition and techniques for analysis and RNA extractions. Patient-derived xenografts (PDX) of BC bone metastases have not been reported yet. For the first time we established PDX models from bone metastatic biopsies of patients progressing on ET and treated by vertebroplasty. PDX models were analysed at genomic level to identify new therapeutic targets associated with endocrine resistance in the metastatic setting. Identification of chromosomic alterations in bone metastasis derived PDX.
2020-06-29 | GSE149038 | GEO
Project description:A significant proportion of patients with oestrogen receptor (ER) positive breast cancers (BC) develop resistance to endocrine treatments (ET) and relapse with metastatic disease. Bone is the most common metastatic site in ER+ patients, however bone metastases are technically challenging to biopsy and analyse. Difficulties concern both tumour tissue acquisition and techniques for analysis and RNA extractions. Patient-derived xenografts (PDX) of BC bone metastases have not been reported yet. For the first time we established PDX models from bone metastatic biopsies of patients progressing on ET and treated by vertebroplasty. PDX models were analysed at transcriptomic level and compared to patient’s early primary tumours to identify new therapeutic targets associated with endocrine resistance in the metastatic setting. Identification of activated signalling pathways in bone metastasis by comparative transcriptomic analyses of the bone metastasis derived PDX compared to the patients' primary breast tumor.
2020-06-29 | GSE146661 | GEO
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.
2019-02-26 | GSE123926 | GEO