ABSTRACT
PURPOSE: Overall survival in patients with osteosarcoma is only 60%. Poor response to chemotherapy is the dominant risk factor for poor survival. Pharmacogenetic research can offer possibilities to optimize treatment and improve outcome. We applied a pathway-based approach to evaluate the cumulative effect of genes involved in the metabolism of cisplatin and doxorubicin in relationship to clinical outcome. EXPERIMENTAL DESIGN: We included 126 patients with osteosarcoma. To comprehensively assess common genetic variation in the 54 genes selected, linkage disequilibrium (LD; r(2) = 0.8)-based tag-single nucleotide polymorphisms (SNP) strategy was used. A final set of 384 SNPs was typed using Illumina Beadarray platform. SNPs significantly associated with 5-year progression-free survival (PFS) were replicated in another 64 patients with osteosarcoma. RESULTS: We identified five variants in FasL, MSH2, ABCC5, CASP3, and CYP3A4 that were associated with 5-year PFS. Risk stratification based on the combined effects of the risk alleles showed a significant improvement of 5-year PFS. Patients that carried no or only one risk allele had a 5-year PFS of 100% compared with a 5-year PFS of 84.4% for carriers of two or three risk alleles, 66.7% PFS if a patient carried four to five alleles, and a 5-year PFS of 41.8% for patients with >5 risk alleles (P < 0.001). CONCLUSIONS: We identified several genes that showed association with PFS in patients with osteosarcoma. These pharmacogenetic risk factors might be useful to predict treatment outcome and to stratify patients immediately after diagnosis and offer the possibility to improve treatment and outcome.
Subject(s)
Caspase 3/genetics , Cytochrome P-450 CYP3A/genetics , Fas Ligand Protein/genetics , Multidrug Resistance-Associated Proteins/genetics , MutS Homolog 2 Protein/genetics , Osteosarcoma/genetics , Pharmacogenetics , Adult , Aged , Cisplatin/administration & dosage , Disease-Free Survival , Doxorubicin/administration & dosage , Female , Genetic Association Studies , Humans , Male , Middle Aged , Osteosarcoma/drug therapy , Osteosarcoma/pathology , Polymorphism, Single Nucleotide/genetics , Precision Medicine , Prognosis , Treatment OutcomeABSTRACT
BACKGROUND: Treatment strategies blocking tumour necrosis factor (anti-TNF) have proven very successful in patients with rheumatoid arthritis (RA). However, a significant subset of patients does not respond for unknown reasons. Currently, there are no means of identifying these patients before treatment. This study was aimed at identifying genetic factors predicting anti-TNF treatment outcome in patients with RA using a genome-wide association approach. METHODS: We conducted a multistage, genome-wide association study with a primary analysis of 2 557 253 single-nucleotide polymorphisms (SNPs) in 882 patients with RA receiving anti-TNF therapy included through the Dutch Rheumatoid Arthritis Monitoring (DREAM) registry and the database of Apotheekzorg. Linear regression analysis of changes in the Disease Activity Score in 28 joints after 14 weeks of treatment was performed using an additive model. Markers with p<10(-3) were selected for replication in 1821 patients from three independent cohorts. Pathway analysis including all SNPs with p<10(-3) was performed using Ingenuity. RESULTS: 772 markers showed evidence of association with treatment outcome in the initial stage. Eight genetic loci showed improved p value in the overall meta-analysis compared with the first stage, three of which (rs1568885, rs1813443 and rs4411591) showed directional consistency over all four cohorts studied. We were unable to replicate markers previously reported to be associated with anti-TNF outcome. Network analysis indicated strong involvement of biological processes underlying inflammatory response and cell morphology. CONCLUSIONS: Using a multistage strategy, we have identified eight genetic loci associated with response to anti-TNF treatment. Further studies are required to validate these findings in additional patient collections.
