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Integrated data analysis reveals uterine leiomyoma subtypes with distinct driver pathways and biomarkers.

ABSTRACT: Uterine leiomyomas are common benign smooth muscle tumors that impose a major burden on women's health. Recent sequencing studies have revealed recurrent and mutually exclusive mutations in leiomyomas, suggesting the involvement of molecularly distinct pathways. In this study, we explored transcriptional differences among leiomyomas harboring different genetic drivers, including high mobility group AT-hook 2 (HMGA2) rearrangements, mediator complex subunit 12 (MED12) mutations, biallelic inactivation of fumarate hydratase (FH), and collagen, type IV, alpha 5 and collagen, type IV, alpha 6 (COL4A5-COL4A6) deletions. We also explored the transcriptional consequences of 7q22, 22q, and 1p deletions, aiming to identify possible target genes. We investigated 94 leiomyomas and 60 corresponding myometrial tissues using exon arrays, whole genome sequencing, and SNP arrays. This integrative approach revealed subtype-specific expression changes in key driver pathways, including Wnt/?-catenin, Prolactin, and insulin-like growth factor (IGF)1 signaling. Leiomyomas with HMGA2 aberrations displayed highly significant up-regulation of the proto-oncogene pleomorphic adenoma gene 1 (PLAG1), suggesting that HMGA2 promotes tumorigenesis through PLAG1 activation. This was supported by the identification of genetic PLAG1 alterations resulting in expression signatures as seen in leiomyomas with HMGA2 aberrations. RAD51 paralog B (RAD51B), the preferential translocation partner of HMGA2, was up-regulated in MED12 mutant lesions, suggesting a role for this gene in the genesis of leiomyomas. FH-deficient leiomyomas were uniquely characterized by activation of nuclear factor erythroid 2-related factor 2 (NRF2) target genes, supporting the hypothesis that accumulation of fumarate leads to activation of the oncogenic transcription factor NRF2. This study emphasizes the need for molecular stratification in leiomyoma research and possibly in clinical practice as well. Further research is needed to determine whether the candidate biomarkers presented herein can provide guidance for managing the millions of patients affected by these lesions.

SUBMITTER: Mehine M

PROVIDER: S-EPMC4747776 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Integrated data analysis reveals uterine leiomyoma subtypes with distinct driver pathways and biomarkers.

Mehine Miika M Kaasinen Eevi E Heinonen Hanna-Riikka HR Mäkinen Netta N Kämpjärvi Kati K Sarvilinna Nanna N Aavikko Mervi M Vähärautio Anna A Pasanen Annukka A Bützow Ralf R Heikinheimo Oskari O Sjöberg Jari J Pitkänen Esa E Vahteristo Pia P Aaltonen Lauri A LA

Proceedings of the National Academy of Sciences of the United States of America 20160119 5

Uterine leiomyomas are common benign smooth muscle tumors that impose a major burden on women's health. Recent sequencing studies have revealed recurrent and mutually exclusive mutations in leiomyomas, suggesting the involvement of molecularly distinct pathways. In this study, we explored transcriptional differences among leiomyomas harboring different genetic drivers, including high mobility group AT-hook 2 (HMGA2) rearrangements, mediator complex subunit 12 (MED12) mutations, biallelic inactiv ...[more]

PMID: 26787895

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Project description:BACKGROUND:Uterine leiomyomas, the most common tumors of the female reproductive system, are characterized by excessive deposition of disordered stiff extracellular matrix and fundamental alteration in the mechanical signaling pathways. Specifically, these alterations affect the normal dynamic state of responsiveness to mechanical cues in the extracellular environment. These mechanical cues are converted through integrins, cell membrane receptors, to biochemical signals including cytoskeletal signaling pathways to maintain mechanical homeostasis. Leiomyoma cells overexpress β1 integrin and other downstream mechanical signaling proteins. We previously reported that simvastatin, an antihyperlipidemic drug, has antileiomyoma effects through cellular, animal model, and epidemiologic studies. OBJECTIVE:This study aimed to examine the hypothesis that simvastatin might influence altered mechanotransduction in leiomyoma cells. STUDY DESIGN:This is a laboratory-based experimental study. Primary leiomyoma cells were isolated from 5 patients who underwent hysterectomy at the Department of Gynecology and Obstetrics of the Johns Hopkins University Hospital. Primary and immortalized human uterine leiomyoma cells were treated with simvastatin at increasing concentrations (0.001, 0.01, 0.1, and 1 μM, or control) for 48 hours. Protein and mRNA levels of β1 integrin and extracellular matrix components involved in mechanical signaling were quantified by quantitative real-time polymerase chain reaction, western blotting, and immunofluorescence. In addition, we examined the effect of simvastatin on the activity of Ras homolog family member A using pull-down assay and gel contraction. RESULTS:We found that simvastatin significantly reduced the protein expression of β1 integrin by 44% and type I collagen by 60% compared with untreated leiomyoma cells. Simvastatin-treated cells reduced phosphorylation of focal adhesion kinase down to 26%-60% of control, whereas it increased total focal adhesion kinase protein expression. Using a Ras homolog family member A pull-down activation assay, we observed reduced levels of active Ras homolog family member A in simvastatin-treated cells by 45%-85% compared with control. Consistent with impaired Ras homolog family member A activation, simvastatin treatment reduced tumor gel contraction where gel area was 122%-153% larger than control. Furthermore, simvastatin treatment led to reduced levels of mechanical signaling proteins involved in β1 integrin downstream signaling, such as A-kinase anchor protein 13, Rho-associated protein kinase 1, myosin light-chain kinase, and cyclin D1. CONCLUSION:The results of this study suggest a possible therapeutic role of simvastatin in restoring the altered state of mechanotransduction signaling in leiomyoma. Collectively, these findings are aligned with previous epidemiologic studies and other reports and support the need for clinical trials.

Project description:Purpose: To identify novel breast cancer subtypes by extracting quantitative imaging phenotypes of the tumor and surrounding parenchyma and to elucidate the underlying biologic underpinnings and evaluate the prognostic capacity for predicting recurrence-free survival (RFS).Experimental Design: We retrospectively analyzed dynamic contrast-enhanced MRI data of patients from a single-center discovery cohort (n = 60) and an independent multicenter validation cohort (n = 96). Quantitative image features were extracted to characterize tumor morphology, intratumor heterogeneity of contrast agent wash-in/wash-out patterns, and tumor-surrounding parenchyma enhancement. On the basis of these image features, we used unsupervised consensus clustering to identify robust imaging subtypes and evaluated their clinical and biologic relevance. We built a gene expression-based classifier of imaging subtypes and tested their prognostic significance in five additional cohorts with publically available gene expression data but without imaging data (n = 1,160).Results: Three distinct imaging subtypes, that is, homogeneous intratumoral enhancing, minimal parenchymal enhancing, and prominent parenchymal enhancing, were identified and validated. In the discovery cohort, imaging subtypes stratified patients with significantly different 5-year RFS rates of 79.6%, 65.2%, 52.5% (log-rank P = 0.025) and remained as an independent predictor after adjusting for clinicopathologic factors (HR, 2.79; P = 0.016). The prognostic value of imaging subtypes was further validated in five independent gene expression cohorts, with average 5-year RFS rates of 88.1%, 74.0%, 59.5% (log-rank P from <0.0001 to 0.008). Each imaging subtype was associated with specific dysregulated molecular pathways that can be therapeutically targeted.Conclusions: Imaging subtypes provide complimentary value to established histopathologic or molecular subtypes and may help stratify patients with breast cancer. Clin Cancer Res; 23(13); 3334-42. ©2017 AACR.

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Integrated data analysis reveals uterine leiomyoma subtypes with distinct driver pathways and biomarkers.

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Integrated data analysis reveals uterine leiomyoma subtypes with distinct driver pathways and biomarkers.

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