Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

A compendium of long non-coding RNAs transcriptional fingerprint in multiple myeloma

ABSTRACT: Multiple myeloma (MM) is a malignant proliferation of bone marrow plasma cells (PCs) characterized by highly heterogeneous genetic background and clinical course, and whose pathogenesis remains largely unknown. Long ncRNAs (lncRNAs) are a large class of non-protein-coding RNA, involved in many physiological cellular and genomic processes as well as in carcinogenesis, cancer metastasis and invasion. Although still in its infancy, the knowledge of the role of lncRNAs in MM is progressively expanding. Besides studies on selected candidates, lncRNAs expression at genome-wide transcriptome level is confined to microarray technologies, thus investigating a limited collection of transcripts. Herein, we assessed the lncRNAs expression profiling by RNA-sequencing in a cohort of 30 MM patients, aimed at defining a comprehensive catalogue of lncRNAs specifically associated with the main MM molecular subgroups and genetic alterations. We identified 391 deregulated lncRNAs, 67% of which were also detectable and validated by whole-transcript microarrays. In addition, we identified a list of lncRNAs, with potential relevance in MM, co-expressed and in close proximity to genes that might undergo a cis-regulatory relationship.

ORGANISM(S): Homo sapiens

PROVIDER: GSE109342 | GEO | 2018/06/05

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

A compendium of long non-coding RNAs transcriptional fingerprint in multiple myeloma.

Project description:Multiple myeloma (MM) is a malignant proliferation of bone marrow plasma cells (PCs) characterized by highly heterogeneous genetic background and clinical course, and whose pathogenesis remains largely unknown. Long ncRNAs (lncRNAs) are a large class of non-protein-coding RNA, involved in many physiological cellular and genomic processes as well as in carcinogenesis, cancer metastasis and invasion. Although still in its infancy, the knowledge of the role of lncRNAs in MM is progressively expanding. Besides studies on selected candidates, lncRNAs expression at genome-wide transcriptome level is confined to microarray technologies, thus investigating a limited collection of transcripts. Herein, we assessed the lncRNAs expression profiling by RNA-sequencing in a cohort of 30 MM patients, aimed at defining a comprehensive catalogue of lncRNAs specifically associated with the main MM molecular subgroups and genetic alterations. We identified 391 deregulated lncRNAs, 67% of which were also detectable and validated by whole-transcript microarrays. In addition, we identified a list of lncRNAs, with potential relevance in MM, co-expressed and in close proximity to genes that might undergo a cis-regulatory relationship. Herein, we assessed the lncRNAs expression profiling by RNA-sequencing in a cohort of 30 MM patients, aimed at defining a comprehensive catalogue of lncRNAs specifically associated with the main MM molecular subgroups and genetic alterations. We identified 391 deregulated lncRNAs, 67% of which were also detectable and validated by whole-transcript microarrays. In addition, we identified a list of lncRNAs, with potential relevance in MM, co-expressed and in close proximity to genes that might undergo a cis-regulatory relationship.

2018-06-05 | GSE109116 | GEO

Expression data of newly diagnosed multiple myeloma and extramedullary myeloma

Project description:Despite the development of novel therapeutic agents, multiple myeloma (MM) remains incurable, owing mainly to inevitable relapse in almost all patients. Some relapses occur as extramedullary disease (EMD), which is rare but is the most aggressive event in MM patients. Extramedullary myeloma (EMM) has extraordinary heterogeneous biological and clinical features. Previous studies have shown that expression levels of LncRNAs and mRNAs in different stages of MM are different. This study analyzes the expression levels of LncRNAs and mRNAs in primary plasma cells (PCs) from MM and EMM patients.

2023-03-01 | GSE147841 | GEO

Phenotypic and genomic analysis of multiple myeloma minimal residual disease clonal plasma cells: a new model to understand chemoresistance [HuGene-1_0 Expression]

Project description:Persistence of chemoresistant minimal residual disease (MRD) plasma cells (PCs) relates to inferior survival in multiple myeloma (MM). MRD PCs are therefore a minor clone able to recapitulate the initial tumor burden at relapse and accordingly, its characterization may represent a unique model to understand chemoresistance; unfortunately, the MRD clone has never been biologically investigated. Here, we compared the antigenic profile of MRD vs. diagnostic clonal PCs in 40 elderly MM patients enrolled in the GEM2010MAS65 study, and showed that the MRD clone is enriched by cells over-expressing integrins (CD11a/CD11c/CD29/CD49d/CD49e), chemokine receptors (CXCR4) and adhesion molecules (CD44/CD54). Genetic profiling of MRD vs. diagnostic PCs showed identical copy number alterations (CNAs) in 3/8 cases, 2 patients with linear acquisition of additional CNAs in MRD clonal PCs, and 3 cases with variable acquisition and loss of CNAs over time. The MRD clone showed significant downregulation of genes particularly related to protein processing in endoplasmic reticulum, as well as novel deregulated genes such as ALCAM that is prognostically relevant in MM and identifies chemoresistant PCs in vitro. Together, we show that therapy-induced clonal selection is already present at the MRD stage, in which chemoresistant PCs show a specific phenotypic signature that may result from the persistence of clones with different genetic and gene expression profiles.

2016-01-28 | GSE70398 | GEO

Phenotypic and genomic analysis of multiple myeloma minimal residual disease clonal plasma cells: a new model to understand chemoresistance [CytoScan750K Copy Number, LOH]

2016-01-28 | GSE70397 | GEO

FP-ADMET: a compendium of fingerprint-based ADMET prediction models.

Project description:MotivationThe absorption, distribution, metabolism, excretion, and toxicity (ADMET) of drugs plays a key role in determining which among the potential candidates are to be prioritized. In silico approaches based on machine learning methods are becoming increasing popular, but are nonetheless limited by the availability of data. With a view to making both data and models available to the scientific community, we have developed FPADMET which is a repository of molecular fingerprint-based predictive models for ADMET properties. In this article, we have examined the efficacy of fingerprint-based machine learning models for a large number of ADMET-related properties. The predictive ability of a set of 20 different binary fingerprints (based on substructure keys, atom pairs, local path environments, as well as custom fingerprints such as all-shortest paths) for over 50 ADMET and ADMET-related endpoints have been evaluated as part of the study. We find that for a majority of the properties, fingerprint-based random forest models yield comparable or better performance compared with traditional 2D/3D molecular descriptors.AvailabilityThe models are made available as part of open access software that can be downloaded from https://gitlab.com/vishsoft/fpadmet .

| S-EPMC8479898 | biostudies-literature

Phenotypic, transcriptomic and genomic characterization of clonal plasma cells in light chain amyloidosis [Copy number analysis]

Project description:Immunoglobulin light-chain amyloidosis (AL) is a rare clonal plasma cell (PC) disorder that remains largely incurable. AL and multiple myeloma (MM) share the same cellular origin, but while knowledge about MM PC biology has improved significantly, the same does not apply for AL. Here, we undertook an integrative phenotypic, molecular, and genomic approach to study clonal PCs from 22 newly-diagnosed AL patients. Through principal-component-analysis, we demonstrated highly overlapping phenotypic profiles between AL and MGUS or MM patients. However, in contrast to MM, highly-purified FACSs-sorted clonal PCs in AL (n=9/22) show virtually normal transcriptomes with only 68 deregulated genes as compared to normal PCs, including a few tumor suppressor (CDH1, RCAN) and pro-apoptotic (GLIPR1, FAS) genes. Notwithstanding, clonal PCs in AL (n=11/22) were genomically unstable with a median of 9 copy-number-abnormities (CNAs) per case; many of which similar to those found in MM. Whole-exome sequencing (WES) was performed in three AL patients and revealed a median of 10 non-recurrent mutations per case. Altogether, we showed that although clonal PCs in AL display phenotypic and CNA profiles similar to MM, their transcriptome is remarkably similar to that of normal PCs. First-ever WES revealed the lack of a unifying mutation in AL

2016-07-22 | GSE73041 | GEO

Phenotypic, transcriptomic and genomic characterization of clonal plasma cells in light chain amyloidosis [Gene expression profiling]

2016-07-22 | GSE73040 | GEO

A compendium of long non-coding RNAs transcriptional fingerprint in multiple myeloma.

Project description:Multiple myeloma (MM) is a clonal proliferation of bone marrow plasma cells characterized by highly heterogeneous genetic background and clinical course, whose pathogenesis remains largely unknown. Long ncRNAs (lncRNAs) are a large class of non-protein-coding RNA, involved in many physiological cellular and genomic processes as well as in carcinogenesis and tumor evolution. Although still in its infancy, the role of lncRNAs in MM is progressively expanding. Besides studies on selected candidates, lncRNAs expression at genome-wide transcriptome level is confined to microarray technologies, thus investigating a limited collection of transcripts. In the present study investigating a cohort of 30 MM patients, a deep RNA-sequencing analysis overwhelmed previous array studies and allowed the most accurate definition of lncRNA transcripts structure and expression, ultimately providing a comprehensive catalogue of lncRNAs specifically associated with the main MM molecular subgroups and genetic alterations. Despite the small number of analyzed samples, the high accuracy of RNA-sequencing approach for complex transcriptome processing led to the identification of 391 deregulated lncRNAs, 67% of which were also detectable and validated by whole-transcript microarrays. In addition, we identified a list of lncRNAs, with potential relevance in MM, co-expressed and in close proximity to genes that might undergo a cis-regulatory relationship.

| S-EPMC5920050 | biostudies-literature

Long non-coding RNAs in B cells (ChIP-Seq)

Project description:Using RNA sequencing and de novo transcript assembly, we identified 4516 lncRNAs expressed in 8 different stages of B cell development and activation. Chromatin immuno-precipitation sequencing was used to classify a substantial fraction (38%) of these lncRNAs as enhancer-associated or promoter-associated RNAs (eRNAs or pRNAs). A catalogue of lncRNAs expressed in eight murine B cell populations

2016-07-15 | E-GEOD-72017 | biostudies-arrayexpress

Long non-coding RNAs in B cells (RNA-Seq)

2016-07-15 | E-GEOD-72018 | biostudies-arrayexpress