LRG1 mRNA expression in breast cancer associates with PIK3CA genotype and with aromatase inhibitor therapy outcome
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...
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Wiley
2016-10-01
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Series: | Molecular Oncology |
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Online Access: | https://doi.org/10.1016/j.molonc.2016.07.004 |
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author | Diana E. Ramirez-Ardila Kirsten Ruigrok-Ritstier Jean C. Helmijr Maxime P. Look Steven van Laere Luc Dirix Els M.J.J. Berns Maurice P.H.M. Jansen |
author_facet | Diana E. Ramirez-Ardila Kirsten Ruigrok-Ritstier Jean C. Helmijr Maxime P. Look Steven van Laere Luc Dirix Els M.J.J. Berns Maurice P.H.M. Jansen |
author_sort | Diana E. Ramirez-Ardila |
collection | DOAJ |
description | 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. |
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spelling | doaj.art-8ebe2c3f82f54bf49412c8044bd74e362024-03-05T07:31:04ZengWileyMolecular Oncology1574-78911878-02612016-10-011081363137310.1016/j.molonc.2016.07.004LRG1 mRNA expression in breast cancer associates with PIK3CA genotype and with aromatase inhibitor therapy outcomeDiana E. Ramirez-Ardila0Kirsten Ruigrok-Ritstier1Jean C. Helmijr2Maxime P. Look3Steven van Laere4Luc Dirix5Els M.J.J. Berns6Maurice P.H.M. Jansen7Department of Medical Oncology, Erasmus MC – Cancer Institute, Rotterdam, The NetherlandsDepartment of Medical Oncology, Erasmus MC – Cancer Institute, Rotterdam, The NetherlandsDepartment of Medical Oncology, Erasmus MC – Cancer Institute, Rotterdam, The NetherlandsDepartment of Medical Oncology, Erasmus MC – Cancer Institute, Rotterdam, The NetherlandsDepartment Oncology, Catholic University Leuven, Leuven, BelgiumTranslational Cancer Research Unit, Laboratory of Pathology, Antwerp University, Antwerp, BelgiumDepartment of Medical Oncology, Erasmus MC – Cancer Institute, Rotterdam, The NetherlandsDepartment of Medical Oncology, Erasmus MC – Cancer Institute, Rotterdam, The NetherlandsBackground 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.https://doi.org/10.1016/j.molonc.2016.07.004PIK3CA mutationsBreast cancerFirst line aromatase inhibitors therapyLRG1 |
spellingShingle | Diana E. Ramirez-Ardila Kirsten Ruigrok-Ritstier Jean C. Helmijr Maxime P. Look Steven van Laere Luc Dirix Els M.J.J. Berns Maurice P.H.M. Jansen LRG1 mRNA expression in breast cancer associates with PIK3CA genotype and with aromatase inhibitor therapy outcome Molecular Oncology PIK3CA mutations Breast cancer First line aromatase inhibitors therapy LRG1 |
title | LRG1 mRNA expression in breast cancer associates with PIK3CA genotype and with aromatase inhibitor therapy outcome |
title_full | LRG1 mRNA expression in breast cancer associates with PIK3CA genotype and with aromatase inhibitor therapy outcome |
title_fullStr | LRG1 mRNA expression in breast cancer associates with PIK3CA genotype and with aromatase inhibitor therapy outcome |
title_full_unstemmed | LRG1 mRNA expression in breast cancer associates with PIK3CA genotype and with aromatase inhibitor therapy outcome |
title_short | LRG1 mRNA expression in breast cancer associates with PIK3CA genotype and with aromatase inhibitor therapy outcome |
title_sort | lrg1 mrna expression in breast cancer associates with pik3ca genotype and with aromatase inhibitor therapy outcome |
topic | PIK3CA mutations Breast cancer First line aromatase inhibitors therapy LRG1 |
url | https://doi.org/10.1016/j.molonc.2016.07.004 |
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