LRG1 mRNA expression in breast cancer associates with PIK3CA genotype and with aromatase inhibitor therapy outcome
MOLECULAR ONCOLOGY
Authors: Ramirez-Ardila, Diana E.; Ruigrok-Ritstier, Kirsten; Helmijr, Jean C.; Look, Maxime P.; van Laere, Steven; Dirix, Luc; Berns, Els M. J. J.; Jansen, Maurice P. H. M.
Abstract
Background: PIK3CA is the most frequent somatic mutated oncogene in estrogen receptor (ER) positive breast cancer. We previously observed an association between PIK3CA genotype and aromatase inhibitors (AI) treatment outcome. This study now evaluates whether expression of mRNAs and miRs are linked to PIK3CA genotype and are independently related to AI therapy response in order to define potential expressed biomarkers for treatment outcome. Materials and methods: The miR and mRNA expression levels were evaluated for their relationship with the PIK3CA genotype in two breast tumor datasets, i.e. 286 luminal cancers from the TCGA consortium and our set of 84 ER positive primary tumors of metastatic breast cancer patients who received first line AI. BRB Array tools class comparison was performed to define miRs and mRNAs whose expression associate with PIK3CA exon 9 and 20 status. Spearman correlations established miR mRNA pairs and mRNAs with related expression. Next, a third dataset of 25 breast cancer patients receiving neo-adjuvant letrozole was evaluated, to compare expression levels of identified miRs and mRNAs in biopsies before and after treatment. Finally, to identify potential biomarkers miR and mRNA levels were related with overall survival (OS) and progression free survival (PFS) after first-line AI therapy. Results: Expression of 3 miRs (miR-449a, miR-205-5p, miR-301a-3p) and 9 mRNAs (CCNO, FAM81B, LRG1, NEK10, PLCL1, PGR, SERPINA3, SORBS2, VTCN1) was related to the PIK3CA status in both datasets. All except miR-301a-3p had an increased expression in tumors with PIK3CA mutations. Validation in a publicly available dataset showed that LRG1, PGR, and SERPINA3 levels were decreased after neo-adjuvant AI-treatment. Six miR mRNA pairs correlated significantly and stepdown analysis of all 12 factors revealed 3 mRNAs (PLCL1, LRG1, FAM81B) related to PFS. Further analyses showed LRG1 and PLCL1 expression to be unrelated with luminal subtype and to associate with OS and with PFS, the latter independent from traditional predictive factors. Conclusion: We showed in two datasets of ER positive and luminal breast tumors that the expression of 3 miRs and 9 mRNAs associate with the PIK3CA status. Expression of LRG1 is independent of luminal (A or B) subtype, decreased after neo-adjuvant AI-treatment, and is proposed as potential biomarker for AI therapy outcome. (C) 2016 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
Identification of a Novel Susceptibility Locus for Juvenile Idiopathic Arthritis by Genome-Wide Association Analysis
ARTHRITIS AND RHEUMATISM
Authors: Hinks, Anne; Barton, Anne; Shephard, Neil; Eyre, Steve; Bowes, John; Cargil, Michele; Wang, Eric; Ke, Xiayi; Kennedy, Giulia C.; John, Sally; Worthington, Jane; Thomson, Wendy
Abstract
Objective. Juvenile idiopathic arthritis (JIA) is a chronic rheumatic disease of childhood. Two well-established genetic factors known to contribute to JIA susceptibility, HLA and PTPN22, account for less than half of the genetic susceptibility to disease; therefore, additional genetic factors have yet to be identified. The purpose of this study was to perform a systematic search of the genome to identify novel susceptibility loci for JIA. Methods. A genome-wide association study using Affymetrix GeneChip 100K arrays was performed in a discovery cohort (279 cases and 184 controls). Single-nucleotide polymorphisms (SNPs) showing the most significant differences between cases and controls were then genotyped in a validation sample of cases (n = 321) and controls, combined with control data from the 1958 UK birth cohort (n = 2,024). In one region in which association was confirmed, fine-mapping was performed (654 cases and 1,847 controls). Results. Of the 112 SNPs that were significantly associated with JIA in the discovery cohort, 6 SNPs were associated with JIA in the independent validation cohort. The most strongly associated SNP mapped to the HLA region, while the second strongest association was with a SNP within the VTCN1 gene. Fine-mapping of that gene was performed, and 10 SNPs were found to be associated with JIA. Conclusion. This study is the first to successfully apply a SNP-based genome-wide association approach to the investigation of JIA. The replicated association with markers in the VTCN1 gene defined an additional susceptibility locus for JIA and implicates a novel pathway in the pathogenesis of this chronic disease of childhood.