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Expression profiling of uterine leiomyomata cytogenetic subgroups reveals distinct signatures in matched myometrium: transcriptional profilingof the t(12;14) and evidence in support of predisposing genetic heterogeneity.

ABSTRACT: Uterine leiomyomata (UL), the most common neoplasm in reproductive-age women, are classified into distinct genetic subgroups based on recurrent chromosome abnormalities. To develop a molecular signature of UL with t(12;14)(q14-q15;q23-q24), we took advantage of the multiple UL arising as independent clonal lesions within a single uterus. We compared genome-wide expression levels of t(12;14) UL to non-t(12;14) UL from each of nine women in a paired analysis, with each sample weighted for the percentage of t(12;14) cells to adjust for mosaicism with normal cells. This resulted in a transcriptional profile that confirmed HMGA2, known to be overexpressed in t(12;14) UL, as the most significantly altered gene. Pathway analysis of the differentially expressed genes showed significant association with cell proliferation, particularly G1/S checkpoint regulation. This is consistent with the known larger size of t(12;14) UL relative to karyotypically normal UL or to UL in the deletion 7q22 subgroup. Unsupervised hierarchical clustering demonstrated that patient variability is relatively dominant to the distinction of t(12;14) UL compared with non-t(12;14) UL or of t(12;14) UL compared with del(7q) UL. The paired design we employed is therefore important to produce an accurate t(12;14) UL-specific gene list by removing the confounding effects of genotype and environment. Interestingly, myometrium not only clustered away from the tumors, but generally separated based on associated t(12;14) versus del(7q) status. Nine genes were identified whose expression can distinguish the myometrium origin. This suggests an underlying constitutional genetic predisposition to these somatic changes which could potentially lead to improved personalized management and treatment.

SUBMITTER: Hodge JC

PROVIDER: S-EPMC3335314 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature

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Expression profiling of uterine leiomyomata cytogenetic subgroups reveals distinct signatures in matched myometrium: transcriptional profilingof the t(12;14) and evidence in support of predisposing genetic heterogeneity.

Hodge Jennelle C JC Kim Tae-Min TM Dreyfuss Jonathan M JM Somasundaram Priya P Christacos Nicole C NC Rousselle Marissa M Quade Bradley J BJ Park Peter J PJ Stewart Elizabeth A EA Morton Cynthia C CC

Human molecular genetics 20120217 10

Uterine leiomyomata (UL), the most common neoplasm in reproductive-age women, are classified into distinct genetic subgroups based on recurrent chromosome abnormalities. To develop a molecular signature of UL with t(12;14)(q14-q15;q23-q24), we took advantage of the multiple UL arising as independent clonal lesions within a single uterus. We compared genome-wide expression levels of t(12;14) UL to non-t(12;14) UL from each of nine women in a paired analysis, with each sample weighted for the perc ...[more]

PMID: 22343407

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Project description:PurposeMedulloblastoma comprises four distinct molecular subgroups: WNT, SHH, Group 3, and Group 4. Current medulloblastoma protocols stratify patients based on clinical features: patient age, metastatic stage, extent of resection, and histologic variant. Stark prognostic and genetic differences among the four subgroups suggest that subgroup-specific molecular biomarkers could improve patient prognostication.Patients and methodsMolecular biomarkers were identified from a discovery set of 673 medulloblastomas from 43 cities around the world. Combined risk stratification models were designed based on clinical and cytogenetic biomarkers identified by multivariable Cox proportional hazards analyses. Identified biomarkers were tested using fluorescent in situ hybridization (FISH) on a nonoverlapping medulloblastoma tissue microarray (n = 453), with subsequent validation of the risk stratification models.ResultsSubgroup information improves the predictive accuracy of a multivariable survival model compared with clinical biomarkers alone. Most previously published cytogenetic biomarkers are only prognostic within a single medulloblastoma subgroup. Profiling six FISH biomarkers (GLI2, MYC, chromosome 11 [chr11], chr14, 17p, and 17q) on formalin-fixed paraffin-embedded tissues, we can reliably and reproducibly identify very low-risk and very high-risk patients within SHH, Group 3, and Group 4 medulloblastomas.ConclusionCombining subgroup and cytogenetic biomarkers with established clinical biomarkers substantially improves patient prognostication, even in the context of heterogeneous clinical therapies. The prognostic significance of most molecular biomarkers is restricted to a specific subgroup. We have identified a small panel of cytogenetic biomarkers that reliably identifies very high-risk and very low-risk groups of patients, making it an excellent tool for selecting patients for therapy intensification and therapy de-escalation in future clinical trials.

Dataset Information

Expression profiling of uterine leiomyomata cytogenetic subgroups reveals distinct signatures in matched myometrium: transcriptional profilingof the t(12;14) and evidence in support of predisposing genetic heterogeneity.

Publications

Expression profiling of uterine leiomyomata cytogenetic subgroups reveals distinct signatures in matched myometrium: transcriptional profilingof the t(12;14) and evidence in support of predisposing genetic heterogeneity.

Similar Datasets

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