Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

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Expression data from CD138+ cells obtained from MM patients at diagnosis

ABSTRACT: Thalidomide-dexamethasone (TD) combination is an effective induction therapy for newly diagnosed multiple myeloma patients, candidates for subsequent autologous stem cell transplantation (ASCT). Since maximization of tumor response before ASCT may favorably affect the clinical outcomes, we designed a study to identify a gene expression profile (GEP) signature predictive of attainment of complete response to TD induction therapy. CD138+ bone marrow samples obtained at diagnosis from 112/311 patients were analyzed. Two subsequent time phases were planned. Firstly, a GEP supervised analysis, performed on a training set of 32 patients, allowed to identify 157 probe sets differentially expressed in complete responder + near complete responder (CR+nCR) versus ?partial responder patients. Than, we generated an 8-gene GEP signature predicting at diagnosis the probability to achieve CR+nCR to TD induction therapy. The performance of this assay was subsequently validated in an 80 patients training set. The 8-gene signature provide a negative predictive value of 93% and a positive predictive value of 44%. The 8 genes were down-regulated in patients who achieved at least a nCR. These results could be an important first step to adopting a diagnostic assay, used to determine, at diagnosis, patients who will respond more favourably to a particular treatment strategy. This series of microarray experiments contains the gene expression profiles of purified plasma cells (PCs) obtained from 32 newly diagnosed multiple myeloma (MM). PCs were purified from bone marrow specimens, using CD138 immunomagnetic microbeads. The purity of the positively selected PCs was assessed by flow cytometry and was > 90% in all cases. 5 micrograms of total RNA was processed and hybridized to the Affymetrix HG U133 Plus 2.0 GeneChip following the manufacturer's instructions.

ORGANISM(S): Homo sapiens

SUBMITTER: Carolina Terragna

PROVIDER: E-GEOD-16791 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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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 A total of 22 patients with confirmed diagnosis of AL based on the presence of amyloid-related systemic syndrome, positive amyloid tissue staining with Congo red, and evidence of PC clonality were studied. Samples were collected after informed consent was given, in accordance with local ethical committee guidelines and the Helsinki Declaration. GEP was performed in 9/22 AL cases with adequate RNA extracted from FACS-purified clonal PCs according to patient-specific aberrant phenotypes, and compared to that of normal PCs from 5 healthy individuals (FACSAriaIIb, BDB; â¥95% purity). RNA was hybridized to the Human Gene 1.0 ST Array (Affymetrix, Santa Clara, CA, USA) and normalization was carried using the expression console (Affymetrix) with the RMA algorithm which includes background correction, normalization and calculation of expression values (log2). Differentially expressed genes between classes were identified using the Significant Analysis of Microarrays (SAM) algorithm (http://www-stat.standford.edu/-tibs/SAM), and significant genes were selected based on the lowest q-value (<10-5).

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Expression data from CD138+ cells obtained from MM patients at diagnosis

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