ArticleBMC cancer2019
Genome sequencing analysis of blood cells identifies germline haplotypes strongly associated with drug resistance in osteosarcoma patients.
Article in BMC cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.
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Who cites it
14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 18 citations in OpenAlex.
- Genetic variants associated with osteosarcoma risk: a systematic review and meta-analysis.Scientific reports · 2024Pooled it
- Pharmacogenetics of chemotherapy treatment response and -toxicities in patients with osteosarcoma: a systematic review.BMC cancer · 2022Pooled it
- Pharmacogenetics of Neoadjuvant MAP Chemotherapy in Localized Osteosarcoma: A Study Based on Data from the GEIS-33 Protocol.Pharmaceutics · 2024Article
- LncRNA EBLN3P Facilitates Osteosarcoma Metastasis by Enhancing Annexin A3 mRNA Stability and Recruiting HuR.Annals of surgical oncology · 2023Article
- Allicin Inhibits Osteosarcoma Growth by Promoting Oxidative Stress and Autophagy via the Inactivation of the lncRNA MALAT1-miR-376a-Wnt/Oxidative medicine and cellular longevity · 2022Article
- Flavonoid compound breviscapine suppresses human osteosarcoma Saos-2 progression property and induces apoptosis by regulating mitochondria-dependent pathway.Journal of biochemical and molecular toxicology · 2021Article
- Recent Insights into Therapy Resistance in Osteosarcoma.Cancers · 2020Review
- Targeting Molecular Mechanisms Underlying Treatment Efficacy and Resistance in Osteosarcoma: A Review of Current and Future Strategies.International journal of molecular sciences · 2020Review
- Pharmacogenomics and Pharmacogenetics in Osteosarcoma: Translational Studies and Clinical Impact.International journal of molecular sciences · 2020Review
- Article
- Key genes with prognostic values in suppression of osteosarcoma metastasis using comprehensive analysis.BMC cancer · 2020Article
- Management of Refractory Pediatric Sarcoma: Current Challenges and Future Prospects.OncoTargets and therapy · 2020Review
- Comprehensive Analysis of Key Genes and Regulatory Elements in Osteosarcoma Affected by Bone Matrix Mineral With Prognostic Values.Frontiers in genetics · 2020Article
- LncRNA TTN-AS1 regulates osteosarcoma cell apoptosis and drug resistance via the miR-134-5p/MBTD1 axis.Aging · 2019Article
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
Abstract
backgroundOsteosarcoma is the most common malignant bone tumor in children. Survival remains poor among histologically poor responders, and there is a need to identify them at diagnosis to avoid delivering ineffective therapy. Genetic variation contributes to a wide range of response and toxicity related to chemotherapy. The aim of this study is to use sequencing of blood cells to identify germline haplotypes strongly associated with drug resistance in osteosarcoma patients.
methodsWe used sequencing data from two patient datasets, from Inova Hospital and the NCI TARGET. We explored the effect of mutation hotspots, in the form of haplotypes, associated with relapse outcome. We then mapped the single nucleotide polymorphisms (SNPs) in these haplotypes to genes and pathways. We also performed a targeted analysis of mutations in Drug Metabolizing Enzymes and Transporter (DMET) genes associated with tumor necrosis and survival.
resultsWe found intronic and intergenic hotspot regions from 26 genes common to both the TARGET and INOVA datasets significantly associated with relapse outcome. Among significant results were mutations in genes belonging to AKR enzyme family, cell-cell adhesion biological process and the PI3K pathways; as well as variants in SLC22 family associated with both tumor necrosis and overall survival. The SNPs from our results were confirmed using Sanger sequencing. Our results included known as well as novel SNPs and haplotypes in genes associated with drug resistance.
conclusionWe show that combining next generation sequencing data from multiple datasets and defined clinical data can better identify relevant pathway associations and clinically actionable variants, as well as provide insights into drug response mechanisms.
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