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Lung adenocarcinoma subtypes definable by lung development-related miRNA expression profiles in association with clinicopathologic features [pre-miRNA analysis - Whole Human Genome 4 x 44K Microarray]

ABSTRACT: Accumulation of genetic and epigenetic changes alters regulation of a web of interconnected genes including miRNAs, which confer hallmark capabilities and characteristic cancer features. In this study, the miRNA and mRNA expression profiles of 126 non-small cell lung cancer specimens were analyzed, with special attention given to the diversity of lung adenocarcinomas. Of those, 76 adenocarcinomas were classified into two major subtypes, developing lung-like and adult lung-like, based on their distinctive miRNA expression profiles resembling those of either developing or adult lungs, respectively. A systems biology-based approach using a Bayesian network and nonparametric regression was employed to estimate the gene regulatory circuitry functioning in patient tumors in order to identify subnetworks enriched for genes with differential expression between the two major subtypes. miR-30d and miR-195, identified as hub genes in such subnetworks, had lower levels of expression in the developing lung-like subtype, while introduction of miR-30d or miR-195 into the lung cancer cell lines evoked shifts of mRNA expression profiles towards the adult lung-like subtype. Conversely, the influence of miR-30d and miR-195 was significantly different between the developing lung- and adult lung-like subtypes in our analysis of the patient dataset. In addition, RRM2, a child gene of the miR-30d-centered subnetwork, was found to be a direct target of miR-30d. Together, our findings reveal the existence of two miRNA expression profile-defined lung adenocarcinoma subtypes with distinctive clinicopathologic features and also suggest the usefulness of a systems biology-based approach to gain insight into the altered regulatory circuitry involved in cancer development.

ORGANISM(S): Homo sapiens

PROVIDER: GSE51854 | GEO | 2014/06/19

SECONDARY ACCESSION(S): PRJNA225613

REPOSITORIES: GEO

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Project description:Accumulation of genetic and epigenetic changes alters regulation of a web of interconnected genes including miRNAs, which confer hallmark capabilities and characteristic cancer features. In this study, the miRNA and mRNA expression profiles of 126 non-small cell lung cancer specimens were analyzed, with special attention given to the diversity of lung adenocarcinomas. Of those, 76 adenocarcinomas were classified into two major subtypes, developing lung-like and adult lung-like, based on their distinctive miRNA expression profiles resembling those of either developing or adult lungs, respectively. A systems biology-based approach using a Bayesian network and nonparametric regression was employed to estimate the gene regulatory circuitry functioning in patient tumors in order to identify subnetworks enriched for genes with differential expression between the two major subtypes. miR-30d and miR-195, identified as hub genes in such subnetworks, had lower levels of expression in the developing lung-like subtype, while introduction of miR-30d or miR-195 into the lung cancer cell lines evoked shifts of mRNA expression profiles towards the adult lung-like subtype. Conversely, the influence of miR-30d and miR-195 was significantly different between the developing lung- and adult lung-like subtypes in our analysis of the patient dataset. In addition, RRM2, a child gene of the miR-30d-centered subnetwork, was found to be a direct target of miR-30d. Together, our findings reveal the existence of two miRNA expression profile-defined lung adenocarcinoma subtypes with distinctive clinicopathologic features and also suggest the usefulness of a systems biology-based approach to gain insight into the altered regulatory circuitry involved in cancer development. Microarray analysis was conducted to examine miRNA expression profiles using a Human miRNA Microarray, pre-commercial version 6.0 (Agilent) with 470 miRNA probes, according to the manufacturer’s instructions

Project description:Accumulation of genetic and epigenetic changes alters regulation of a web of interconnected genes including miRNAs, which confer hallmark capabilities and characteristic cancer features. In this study, the miRNA and mRNA expression profiles of 126 non-small cell lung cancer specimens were analyzed, with special attention given to the diversity of lung adenocarcinomas. Of those, 76 adenocarcinomas were classified into two major subtypes, developing lung-like and adult lung-like, based on their distinctive miRNA expression profiles resembling those of either developing or adult lungs, respectively. A systems biology-based approach using a Bayesian network and nonparametric regression was employed to estimate the gene regulatory circuitry functioning in patient tumors in order to identify subnetworks enriched for genes with differential expression between the two major subtypes. miR-30d and miR-195, identified as hub genes in such subnetworks, had lower levels of expression in the developing lung-like subtype, while introduction of miR-30d or miR-195 into the lung cancer cell lines evoked shifts of mRNA expression profiles towards the adult lung-like subtype. Conversely, the influence of miR-30d and miR-195 was significantly different between the developing lung- and adult lung-like subtypes in our analysis of the patient dataset. In addition, RRM2, a child gene of the miR-30d-centered subnetwork, was found to be a direct target of miR-30d. Together, our findings reveal the existence of two miRNA expression profile-defined lung adenocarcinoma subtypes with distinctive clinicopathologic features and also suggest the usefulness of a systems biology-based approach to gain insight into the altered regulatory circuitry involved in cancer development. Microarray analysis using a Whole Human Genome 4 x 44K Microarray G4112F (Agilent) was conducted to examine changes in expression of 400 genes in SiGN network by transfection of Pre-miR-30d, Pre-miR-195 or Pre-miR-NC#2 (Ambion) in SK-LC-7 cells, which were then harvested at 72 hours after transfection.

Project description:The regulation of gene expression in cells, including by microRNAs (miRNAs), is a dynamic process. Current methods for identifying microRNA targets by combining sequence, miRNA and mRNA expression data do not adequately utilize the temporal information and thus miss important miRNAs and their targets. We developed a new method, mirDREM, that uses probabilistic modeling to reconstruct dynamic regulatory networks which explain how temporal gene expression is jointly regulated by microRNAs and transcription factors (TFs). We used mirDREM to study the regulation of postnatal lung development in mice. The reconstructed network for this process identified several known miRNAs and TFs and provided novel predictions about additional miRNAs and the specific developmental phases they regulate. Microarray data of Mouse Lung Epithelial cells MLE-12 after transfection with inhibitors for miR-30a, miR-30d, miR-23b and miR-125 and with precursors for miR-337, miR-466a, miR466d and miR-476c. The results provide a general insight into the gene expression profile which was modulated by the inhibition or overexpression of these microRNAs. We experimentally validated several predictions and show that miR-30d, miR-30a, and miR-467c are new regulators of proliferation in lung cells. Our analysis establishes new links between identified miRNAs and lung diseases, supporting recent evidence that such diseases may represent reversal of lung differentiation. We first analyzed the endogenous expression of miR-30a, miR-30d, miR-23b, miR-125, miR-337, miR-466a, miR466d and miR-476c in MLE-12 cells. Then, we transfected the MLE-12 cells with inhibitors ( miR-30a, miR-30d, miR-23b and miR-125) for the highly expressed and precursos for those that were almost undetectable (miR-337, miR-466a, miR466d and miR-476c). RNA level of the 8 microRNAs was verify by qRT-PCR in order to validate the transfection efficiency. Finally, 0.5ug of total RNA was used to performe the gene expression microarrays for each condition

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Lung adenocarcinoma subtypes definable by lung development-related miRNA expression profiles in association with clinicopathologic features [pre-miRNA analysis - Whole Human Genome 4 x 44K Microarray]

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