A Local Versus Centralized Processing Comparison of Plasma Cell Isolation, Viability, and RNA Integrity.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 3413-3413
Author(s):  
Gregory J. Ahmann ◽  
Kimberly J. Henderson ◽  
Tammy L. Price-Troska ◽  
Michael M. Timm ◽  
Rempel Rachel ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Cell Viability ◽  
Plasma Cell ◽  
Mayo Clinic ◽  
Expression Profiles ◽  
Tissue Bank ◽  
Cell Yield ◽  
Color Flow ◽  
Cell Counts

Abstract Introduction: The Multiple Myeloma Research Consortium (MMRC) has established a tissue bank for the deposition of bone marrow (BM) samples from patients with multiple myeloma (MM) to be mailed and processed under good laboratory practices (GLP). To date over 300 samples have been collected. The ability for multiple sites to utilize the same GLP protocols for isolation and storage of BM for batch testing can be cost prohibitive and can introduce derived variability. Currently, limited information is available on shipped BM aspirates in regards to cell viability, cell yield, cell purity, and subsequent RNA yield and quality. Materials and methods: To test these determinants we performed a pilot study on behalf of the MMRC where samples were drawn at Mayo Clinic Rochester (MCR) pooled and split into 2 equal aliquots. One-half of each sample was processed following the provided GLP compliant standard operating procedures (SOP’s), immediately after sample procurement, at MCR. The CD138+ cells were stored in TRIZOLTM and the RNA was isolated and analyzed in a single batch. The other half of the aspirate was sent overnight to Mayo Clinic Scottsdale (MCS) where they were processed using an identical protocol. At both locations samples were tested for the following quality determinants; cell yield, RNA yield and integrity, and viability using a 3 color flow cytometric method (CD45, CD38 and 7ADD). Cell counts were performed on the CD138+ fraction to determine plasma cell recovery and a slide based immunofluorescent assay used to determine purity. RNA recovery and integrity were assessed using the Agilent BioanalyzerTM. Lastly, gene expression profiles was compared to determine the “signature” emanating from the shipment of samples. Results: In aggregate, all quality determinants showed similar values when the two sets of samples were compared. Cell viability was similar in both sets of samples as was our ability to collect a highly enriched plasma cell population. The cell yield was very similar (r2=0.52) but slightly lower in the shipped samples (median 71% of locally processed, range 40–140%), probably due to some shipment-associated apoptosis with subsequent loss of cell surface CD138 antigen. The purity of the shipped samples was very similar to that of locally processed (median 94%). Subjective qualitative analysis of the RNA was similar between both groups (shipped yield being 80% of local) with no evidence of degradation in the shipped samples. Details regarding the shipment signatures using gene expression profiling will be presented at the meeting. Conclusion: Here we show that the shipment of samples is feasible with no appreciable loss in cell yield or quality of derived products. % APOPTOTIC+ DEAD PC YIELD PURITY (%) RNA Recovered MCR MCS MCR MCS MCR MCS MCR MCS 8.9 ND 15.2 6.8 93 90 11.4 12.8 6.2 ND 2 2.8 95 99 8 17.2 17.4 8 1.4 1.4 75 88 2.2 0 2.1 18.7 2.8 1.6 96 68 7.2 2 18.1 9.5 1.2 .8 100 94 3.4 .4 5 5.0 8.5 7.2 98 91 12.6 17.8 3.7 5.1 .4 .4 88 87 ND ND 19.5 10.3 1.6 1.2 88 79 .4 3.6 29.1 ND 9.2 1.2 100 56 30.2 1.4 5.6 ND 9.2 7.6 92 88 5.2 16.8 20.3 62.8 2.4 .8 84 61 4.6 0.2 4.6 3.7 10.4 2.4 100 94 29.4 8.4 26.5 13.5 5.8 2.8 ND 97 16.8 5.8 4.5 6.2 2.2 2 100 99 10 4.4 17.5 ND 19.2 12 ND ND 16.4 14

A Trangenic Mouse Model of Plasma Cell Malignancy Shows Cytogenetic and Gene Expression Profiles Similar to Human Multiple Myeloma.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 619-619
Author(s):  
Kristin Boylan ◽  
Mary A. Kvitrud ◽  
Brian G. Van Ness
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Plasma Cell ◽  
Plasma Cells ◽  
Chromosomal Abnormalities ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Rt Pcr ◽  
Mouse Tumors ◽  
Human Multiple Myeloma

Abstract Multiple myeloma is an incurable plasma cell malignancy for which existing animal models are limited. Human plasma cell tumors are genetically diverse, with no single chromosomal abnormality defining the disease, however, dysregulation of the genes c-myc and bcl-xl are both commonly observed. We have previously shown that targeted expression of c-myc and bcl-xl transgenes in mouse plasma cells produces malignancy which displays features of human myeloma such as localization of tumor cells to the bone marrow and lytic bone lesions. Tumors are also present at extramedullary sites (Cheung et al., J. Clin. Invest.113: 1763, 2004). Tumors rapidly develop (median 16 weeks) in 100% of mice, and can be adoptively transferred to syngeneic controls using as few as 1 million tumor cells to produce tumors in as few as 10 days. Adoptive transfer of similar cell numbers from younger double transgenic mice, without evidence of malignancy, results in increased tumor latency (>8 weeks) or the absence of tumor formation, suggesting that an accumulation of genetic changes is required for tumor development. In order to understand the specific genetic alterations required for tumor progression and for localization of tumors to the bone marrow vs extramedullary sites, we have undertaken a detailed analysis of plasma cell tumors in myc/bcl-xl mice and have begun to compare them with human multiple myeloma. Analysis of cell surface markers shows the majority of tumors have a plasmablast phenotype, expressing CD138+, B220+, CD38+, and CD19+. This result is confirmed by RT-PCR for B cell and plasma cell specific markers Pax5, Xbp1 and Blimp1, which can be detected in tumor samples. In addition, transcripts for Mip1α, EZH2, and Dusp6, genes shown to be upregulated in human myeloma, can also be detected in the mouse myc/bcl-xl tumors. Spectral karyotype analysis of metaphase chromosomes from primary tumor cell cultures demonstrates that a variety of chromosomal abnormalities are present in mouse tumors, including trisomies and translocations, similar to what is observed in human myeloma. The most frequently aberrant chromosomes are 12 and 16, followed by chromosomes 1 and 4. Interestingly, two common sites for translocations were identified; 12F which corresponds to the mouse immunoglobulin heavy chain locus, and 4D, which corresponds to a genomic region containing genes for plasma cell tumor susceptibility (Bliskovsky et al., PNAS100:14982, 2003). Further characterization of these translocations are being done to identify the precise breakpoints involved, and analysis of gene expression by RT-PCR and microarray analysis will be correlated to specific chromosomal abnormalities. Additionally, global gene expression profiles from myc/bcl-xl tumor cell cultures have been compared to existing profiles of human myeloma (Zhan et al., Blood99: 1745, 2002). Our preliminary comparison of gene expression profiles from myc/bcl-xl tumors to human myeloma tumors with high myc expression show the mouse tumors are more similar to human tumors than to normal plasma cells. These data suggest the myc/bcl-xl mouse tumors are similar to a subset of human myelomas, and will provide insight into the specific genes and pathways underlying human disease.

Gene Expression Profiling of Plasma Cell Dyscrasias: The Role of IGH Translocations in the Heterogeneity of Multiple Myeloma.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 4845-4845
Author(s):  
Antonino Neri ◽  
Michela Mattioli ◽  
Luca Agnelli ◽  
Sonia Fabris ◽  
Luca Baldini ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Plasma Cell ◽  
Plasma Cells ◽  
Germ Line ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Plasma Cell Dyscrasia ◽  
Transcriptional Level ◽  
Plasma Cell Dyscrasias

Abstract Multiple Myeloma (MM) is the most common form of plasma cell dyscrasia, characterized by a marked heterogeneity of genetic lesions and clinical course. It may develop from a premalignant condition (monoclonal gammopathy ofundetermined significance, MGUS) or progress from intra-medullary to extra-medullaryforms (plasma cell leukemia, PCL). To provide insights into the molecular characterization of plasma cell dyscrasias and to investigate the contribution of specific genetic lesions to the biological and clinical heterogeneity of MM, we analyzed the gene expression profiles of plasma cells isolated from 7 MGUS, 39 MM and 6 PCL patients by means of DNA microarrays. MMs resulted highly heterogeneous at transcriptional level, whereas the differential expression of genes mainly involved in DNA metabolism and proliferation distinguished MGUS from PCLs and the majority of MM cases. The clustering of MM patients was mainly driven by the presence of the most recurrent translocations involving the immunoglobulin heavy-chain locus. Distinct signatures have been found to be associated with different lesions: the overexpression of CCND2 and genes involved in cell adhesion pathways was observed in cases with deregulated MAF and MAFB, whereas genes upregulated in cases with the t(4;14) showed apoptosis related functions. In addition, we identified a set of cancer germ-line antigens specifically expressed in a sub-group of MM patients characterized by an aggressive clinical evolution, a finding that could have implications for patient classification and immunotherapy.

Characterization of Oncogene Dysregulation in Multiple Myeloma by Combined FISH and DNA Microarray Analyses.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 4844-4844
Author(s):  
Antonino Neri ◽  
Sonia Fabris ◽  
Luca Agnelli ◽  
Michela Mattioli ◽  
Luca Baldini ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Dna Microarray ◽  
Plasma Cell ◽  
Target Genes ◽  
Expression Profiles ◽  
Molecular Cytogenetic ◽  
Igh Locus ◽  
Microarray Analyses

Abstract Chromosomal translocations involving the immunoglobulin heavy chain (IGH@) locus and variuos partner loci are frequently associated with multiple myeloma (MM). We investigated the expression profiles of FGFR3/MMSET, CCND1, CCND3, MAF and MAFB genes, respectively involved in t(4;14)(p16.3;q32), t(11;14)(q13;q32), t(6;14)(p21;q32), t(14;16)(q32;q23) and t(14;20)(q32;q12), in purified plasma cell populations from 39 MMs and six plasma cell leukemias (PCL) using DNA microarray analysis, and compared the results with the presence of translocations as assessed by dual-color FISH or RT-PCR. The t(4;14) was found in six MMs, t(11;14) in 9 MMs and 1 PCL, t(6;14) in one MM, t(14;16) in 2 MMs and 1 PCL, and t(14;20) in one PCL. The translocations were associated with the spiked expression of target genes in all cases. Furthermore, gene expression profiling allowed the identification of putative translocations dysregulating CCND1 (1 MM and 1 PCL) and MAFB (1 MM and 1 PCL) without any apparent involvement of immunoglobulin loci. Notably, all of the translocations were mutually exclusive. Markedly increased levels of MMSET expression were found in one MM showing associated FGFR3 and MMSET signals on an unidentified chromosome. Our data suggest the importance of using combined molecular cytogenetic and gene expression approaches to detect genetic aberrations in MM.

scholarly journals Generation of polyclonal plasmablasts from peripheral blood B cells: a normal counterpart of malignant plasmablasts

Blood ◽  
2002 ◽  
Vol 100 (4) ◽  
pp. 1113-1122 ◽  
Author(s):  
Karin Tarte ◽  
John De Vos ◽  
Thomas Thykjaer ◽  
Fenghuang Zhan ◽  
Geneviève Fiol ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Cell Differentiation ◽  
B Cells ◽  
Plasma Cell ◽  
Peripheral Blood ◽  
Plasma Cells ◽  
Expression Profiles ◽  
Homogeneous Population ◽  
Normal Plasma

A new way to identify tumor-specific genes is to compare gene expression profiles between malignant cells and their autologous normal counterparts. In patients with multiple myeloma, a major plasma cell disorder, normal plasma cells are not easily attainable in vivo. We report here that in vitro differentiation of peripheral blood B lymphocytes, purified from healthy donors and from patients with multiple myeloma, makes it possible to obtain a homogeneous population of normal plasmablastic cells. These cells were identified by their morphology, phenotype, production of polyclonal immunoglobulins, and expression of major transcription factors involved in B-cell differentiation. Oligonucleotide microarray analysis shows that these polyclonal plasmablastic cells have a gene expression pattern close to that of normal bone marrow–derived plasma cells. Detailed analysis of genes statistically differentially expressed between normal and tumor plasma cells allows the identification of myeloma-specific genes, including oncogenes and genes coding for tumor antigens. These data should help to disclose the molecular mechanisms of myeloma pathogenesis and to define new therapeutic targets in this still fatal malignancy. In addition, the comparison of gene expression between plasmablastic cells and B cells provides a new and powerful tool to identify genes specifically involved in normal plasma cell differentiation.

scholarly journals Significant Plasma Cell Loss (up to 90%) Despite Preserved Overall Cell Viability - Time Dependent Changes Observed in Multiparametric Flow Cytometry Analysis of Bone Marrow Samples in Multiple Myeloma

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 4006-4006
Author(s):  
Tukten Rolfe ◽  
Quirine O'Loughlin ◽  
Heather Campbell ◽  
Jordan Barr ◽  
Fiona Shawyer ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Bone Marrow ◽  
Flow Cytometry ◽  
Cell Viability ◽  
Plasma Cell ◽  
Plasma Cells ◽  
Cell Yield ◽  
Relative Reduction ◽  
Sample Processing ◽  
Multiparametric Flow Cytometry

Abstract Multiparametric flow cytometry (MPFC) is a mainstream laboratory method used in the diagnosis of multiple myeloma. Minimal residual disease (MRD) assessment by EuroFlow next-generation flow cytometry allows assessment down to an assay sensitivity of 1x10 -5. Delayed sample processing remains a common challenge due to logistical limitations. Specialized tests performed in central pathology laboratories are frequently located a considerable distance from healthcare providers. Our study aims to evaluate the impact of delayed sample processing on plasma cell yield and bone marrow sample stability. There is little published data available. Plasma cell yield and bone marrow sample stability were investigated in patients with multiple myeloma who underwent bone marrow biopsy. Participants were included based on ³10% plasma cell burden by morphological quantification on the bone marrow aspirate smear. Bone marrow aspirates were collected in EDTA (with three samples also collected in lithium heparin) and stored at four degrees Celsius. Samples were analyzed by MPFC within four hours of collection, at 24 and at 48 hours after collection. CD138 and CD38 co-expression were used to identify plasma cells, and absence of 7-AAD to determine cell viability. Mean fluorescence intensity (MFI) of CD138 and CD38 was recorded. Statistical analyses were performed using two-tailed Wilcoxon signed-rank tests and repeated measures ANOVA with significance assigned at p<0.05. Bone marrow aspirate samples of nine participants were evaluated. Significant reduction in plasma cell yield was observed over time (p<0.001) while sample integrity remained unchanged (p>0.05). The most marked reduction in plasma cell detection was seen between initial processing and 24 hours (median absolute reduction 9%, range 0 to 23% and median relative reduction 37%, range -8 to 90%, p<0.01). Further significant reduction of plasma cells occurred after an additional 24 hours (p=0.025). At 48 hours, the median absolute reduction in plasma cell yield from initial testing was 12% (range 1 to 24%) and median relative reduction was 40% (range 18 to 90%). Sample integrity remained constant. The median viability at collection, 24 hours and 48 hours was 91%, 93% and 95% respectively. The most significant specimen deterioration observed was 13% viability reduction to 75% overall by 48 hours. Three of the participants had additional samples collected in lithium heparin anticoagulant media that were analyzed in parallel with their EDTA samples. Plasma cell yield remained similar across the two different anticoagulants with overall cell viability remaining high in lithium heparin (³90%). A trend of time-dependent reduction of CD138 MFI was observed with lithium heparin but not with EDTA. This study demonstrates the significance of time to processing as a pre-analytical variable in MPFC in multiple myeloma. The greatest loss of plasma cells occurs within the first 24 hours after collection but continues to fall significantly out to 48 hours. Reductions of up to 90% were observed in our small cohort and represent a potential 1 log reduction in yield. This decrease in plasma cell yield raises questions of reliability and validity of flow cytometry, whereby the sensitivity depth may be compromised if the sample cannot be processed on the same day of collection. It is a technical limitation of flow cytometry in comparison to polymerase chain reaction methods where sensitivity is unaffected by delays in processing. The overall viability of cells within the samples remained stable over time, despite the decline in plasma cells. A reduction in CD138 MFI is observed in lithium heparin storage medium that may impact on standardized gating techniques. Further validation studies are warranted to explore these phenomena. MRD monitoring in multiple myeloma is rapidly becoming an accepted standard of care in the evaluation of treatment response and represents an independent prognostic maker of progression free survival that can be used to guide further therapy. Our findings indicate the potential of false negative MRD results with delays in sample processing. This questions the current consensus guidelines that recommend samples can be processed up to 2 days after collection. These guidelines may need to be revised in the near future. Figure 1 Figure 1. Disclosures No relevant conflicts of interest to declare.

scholarly journals Predicting Host Immune Cell Dynamics and Key Disease-Associated Genes Using Tissue Transcriptional Profiles

Processes ◽  
2019 ◽  
Vol 7 (5) ◽  
pp. 301
Author(s):  
Muying Wang ◽  
Satoshi Fukuyama ◽  
Yoshihiro Kawaoka ◽  
Jason E. Shoemaker
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Immune Cell ◽  
Mean Squared Error ◽  
Expression Profiles ◽  
Statistical Tests ◽  
Critical Factor ◽  
Expression Data ◽  
Cell Dynamics ◽  
Cell Counts

Motivation: Immune cell dynamics is a critical factor of disease-associated pathology (immunopathology) that also impacts the levels of mRNAs in diseased tissue. Deconvolution algorithms attempt to infer cell quantities in a tissue/organ sample based on gene expression profiles and are often evaluated using artificial, non-complex samples. Their accuracy on estimating cell counts given temporal tissue gene expression data remains not well characterized and has never been characterized when using diseased lung. Further, how to remove the effects of cell migration on transcript counts to improve discovery of disease factors is an open question. Results: Four cell count inference (i.e., deconvolution) tools are evaluated using microarray data from influenza-infected lung sampled at several time points post-infection. The analysis finds that inferred cell quantities are accurate only for select cell types and there is a tendency for algorithms to have a good relative fit (R 2 ) but a poor absolute fit (normalized mean squared error; NMSE), which suggests systemic biases exist. Nonetheless, using cell fraction estimates to adjust gene expression data, we show that genes associated with influenza virus replication and increased infection pathology are more likely to be identified as significant than when applying traditional statistical tests.

scholarly journals Classify Hyperdiploidy Status of Multiple Myeloma Patients Using Gene Expression Profiles

PLoS ONE ◽  
2013 ◽  
Vol 8 (3) ◽  
pp. e58809 ◽  
Author(s):  
Yingxiang Li ◽  
Xujun Wang ◽  
Haiyang Zheng ◽  
Chengyang Wang ◽  
Stéphane Minvielle ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Expression Profiles ◽  
Gene Expression Profiles

scholarly journals Multiple Myeloma Cells Alter Adipogenesis, Increase Senescence-Related and Inflammatory Gene Transcript Expression, and Alter Metabolism in Preadipocytes

2021 ◽  
Vol 10 ◽  
Author(s):  
Heather Fairfield ◽  
Samantha Costa ◽  
Carolyne Falank ◽  
Mariah Farrell ◽  
Connor S. Murphy ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Bone Marrow ◽  
Lipid Accumulation ◽  
Expression Profiles ◽  
Adipogenic Differentiation ◽  
Gene Expression Profiles ◽  
Mouse Bone Marrow ◽  
Gene Transcript ◽  
Bone Marrow Mscs

Within the bone marrow microenvironment, mesenchymal stromal cells (MSCs) are an essential precursor to bone marrow adipocytes and osteoblasts. The balance between this progenitor pool and mature cells (adipocytes and osteoblasts) is often skewed by disease and aging. In multiple myeloma (MM), a cancer of the plasma cell that predominantly grows within the bone marrow, as well as other cancers, MSCs, preadipocytes, and adipocytes have been shown to directly support tumor cell survival and proliferation. Increasing evidence supports the idea that MM-associated MSCs are distinct from healthy MSCs, and their gene expression profiles may be predictive of myeloma patient outcomes. Here we directly investigate how MM cells affect the differentiation capacity and gene expression profiles of preadipocytes and bone marrow MSCs. Our studies reveal that MM.1S cells cause a marked decrease in lipid accumulation in differentiating 3T3-L1 cells. Also, MM.1S cells or MM.1S-conditioned media altered gene expression profiles of both 3T3-L1 and mouse bone marrow MSCs. 3T3-L1 cells exposed to MM.1S cells before adipogenic differentiation displayed gene expression changes leading to significantly altered pathways involved in steroid biosynthesis, the cell cycle, and metabolism (oxidative phosphorylation and glycolysis) after adipogenesis. MM.1S cells induced a marked increase in 3T3-L1 expression of MM-supportive genes including Il-6 and Cxcl12 (SDF1), which was confirmed in mouse MSCs by qRT-PCR, suggesting a forward-feedback mechanism. In vitro experiments revealed that indirect MM exposure prior to differentiation drives a senescent-like phenotype in differentiating MSCs, and this trend was confirmed in MM-associated MSCs compared to MSCs from normal donors. In direct co-culture, human mesenchymal stem cells (hMSCs) exposed to MM.1S, RPMI-8226, and OPM-2 prior to and during differentiation, exhibited different levels of lipid accumulation as well as secreted cytokines. Combined, our results suggest that MM cells can inhibit adipogenic differentiation while stimulating expression of the senescence associated secretory phenotype (SASP) and other pro-myeloma molecules. This study provides insight into a novel way in which MM cells manipulate their microenvironment by altering the expression of supportive cytokines and skewing the cellular diversity of the marrow.

Molecular Classification of Multiple Myeloma: A Distinct Transcriptional Profile Characterizes Patients Expressing CCND1 and Negative for 14q32 Translocations

2005 ◽  
Vol 23 (29) ◽  
pp. 7296-7306 ◽  
Author(s):  
Luca Agnelli ◽  
Silvio Bicciato ◽  
Michela Mattioli ◽  
Sonia Fabris ◽  
Daniela Intini ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Expression Profiles ◽  
Quantitative Polymerase Chain Reaction ◽  
Gene Expression Pattern ◽  
Marker Genes ◽  
Published Data ◽  
Cyclin D ◽  
Chromosome 13Q ◽  
13Q Deletion

Purpose The deregulation of CCND1, CCND2 and CCND3 genes represents a common event in multiple myeloma (MM). A recently proposed classification grouped MM patients into five classes on the basis of their cyclin D expression profiles and the presence of the main translocations involving the immunoglobulin heavy chain locus (IGH) at 14q32. In this study, we provide a molecular characterization of the identified translocations/cyclins (TC) groups. Materials and Methods The gene expression profiles of purified plasma cells from 50 MM cases were used to stratify the samples into the five TC classes and identify their transcriptional fingerprints. The cyclin D expression data were validated by means of real-time quantitative polymerase chain reaction analysis; fluorescence in situ hybridization was used to investigate the cyclin D loci arrangements, and to detect the main IGH translocations and the chromosome 13q deletion. Results Class-prediction analysis identified 112 probe sets as characterizing the TC1, TC2, TC4 and TC5 groups, whereas the TC3 samples showed heterogeneous phenotypes and no marker genes. The TC2 group, which showed extra copies of the CCND1 locus and no IGH translocations or the chromosome 13q deletion, was characterized by the overexpression of genes involved in protein biosynthesis at the translational level. A meta-analysis of published data sets validated the identified gene expression signatures. Conclusion Our data contribute to the understanding of the molecular and biologic features of distinct MM subtypes. The identification of a distinctive gene expression pattern in TC2 patients may improve risk stratification and indicate novel therapeutic targets.

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