A New Molecular Classification of Multiple Myeloma Using Gene Expression Profiling and Fluorescence In Situ Hybridisation as Predictor for Event Free Survival.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 73-73 ◽  
Author(s):  
Dirk Hose ◽  
Jean-Francois Rossi ◽  
Carina Ittrich ◽  
John deVos ◽  
Axel Benner ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Molecular Classification ◽  
Differentially Expressed ◽  
Event Free Survival ◽  
Free Survival ◽  
Cytogenetic Aberrations

Abstract AIM was to establish a new molecular classification of Multiple Myeloma (MM) based on changes in global gene expression attributable to cytogenetic aberrations detected by interphase FISH (iFISH) in order to (i) predict event free survival (EFS) and (ii) investigate differentially expressed genes as basis for a group specific and risk adapted therapy. PATIENTS AND METHODS. Bone marrow aspirates of 105 newly diagnosed MM-patients (65 trial (TG) / 40 independent validation group (VG)) and 7 normal donors (ND) were CD138-purified by magnetic activated cell sorting. RNA was in-vitro transcribed and hybridised to Affymetrix HG U133 A+B GeneChip (TG) and HG U133 2.0 plus arrays (VG). CCND1 and CCND2 expression was verified by real time RT-PCR. iFISH was performed on purified MM-cells using probes for chromosomes 11q23, 11q13, 13q14, 17p13 and the IgH-translocations t(4;14) and t(11;14). Expression data were normalised (Bioconductor package gcrma) and nearest shrunken centroids (NSC) applied to calculate and cross validate a predictor on 40 patients of the TG with a comprehensive iFISH panel available combined with CCND overexpression. Differentially expressed genes were identified using empirical Bayes statistics for pairwise comparison. RESULTS. Overexpression of a D-type cyclin (D1 or D2) was found in 61/65 patients with MM compared to ND. CCND3 overexpression only appeared concomitantly with CCND2 overexpression. Four groups could be distinguished: (1.1) CCND1 (11q13) overexpression and trisomy 11q13, (1.2) CCND1 overexpression and translocations involving 11q13 i.e. t(11;14), (2.1) CCND2 overexpression without 11q13+, t(11;14), t(4;14), (2.2) CCND2 overexpression with t(4;14) and FGFR3 upregulation. A predictor of 6 to 566 genes correctly classifies all 40 patients of the TG (estimated cross validated error rate 0%). An independent VG of 40 patients was used. Genes with highest scores in NSC are: (1.1) CCND1, ribosomal proteins (e.g. RPL 28, 29), GPX1, CCRL2, (1.2) CCND1, TGIF, and NCAM (non-overexpression), (2.1) CCND2, (2.2) FGFR3, WHSC1, CCND2, IRTA2, SELL, and MAGED4. Distribution of clinical parameters (i.e. β2M, Durie Salmon stages, ISS) was not significantly different between the groups. The distribution of del(13)(q14q14) was (1.1) 31.5%, (1.2) 37.5%, (2.1) 37.5% and (2.2) 100%. (p<0.01). I.e. HGF, DKK1, VCAM, CD163 are differentially expressed between all 4 groups and ND (adjusted p<0.001). The groups defined by the predictor show a significantly different EFS after autologous stem cell transplantation according to the GMMG-HD3 protocol (median: (1.1) 18 / (1.2) not reached (no event) / (2.1) 22 / (2.2) 6 months; log-rank-test: p=0.004). CONCLUSION. CCND1 or CCND2 overexpression is nearly ubiquitous in MM and attributable to defined cytogenetic aberrations. Gene expression and iFISH allow a molecular classification of MM which can be predicted by gene expression profiling alone. Groups in the classification show a distinctive pattern in gene expression as well as a different EFS interpretable as risk stratification and indicator of therapeutic targets.

Cancer/Testis Genes in Multiple Myeloma: Expression Patterns and Vaccination Strategies Determined by Microarray Analysis.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 3401-3401
Author(s):  
Maud Condomines ◽  
Dirk Hose ◽  
Thierry Reme ◽  
Michael Hundemer ◽  
John De Vos ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Tumor Escape ◽  
Event Free Survival ◽  
Chromosome X ◽  
Free Survival ◽  
Ct Antigens ◽  
Cancer Testis

Abstract Cancer-testis (CT) antigens are expressed in testis and malignant tumors, but rarely in non-gametogenic tissues. Due to this pattern, they represent attractive targets for cancer vaccination approaches. The aims of the present study were (1) to assess for the first time the expression of CT genes on a pangenomic basis in multiple myeloma (MM), (2) to provide selection strategies of CT antigens for clinical vaccination trials and (3) to assess the impact of CT gene expression on event-free survival. We report here the expression pattern of CT genes in purified MM cells (MMC) of 64 patients with newly-diagnosed MM, 12 patients with monoclonal gammopathy of unknown significance (MGUS), in normal plasma cell and B cell samples and in 20 MMC lines, using gene expression profiling (GEP). Out of 46 CT genes interrogated by the Affymetrix HG U133 Set arrays, 35 were expressed in MMC of at least one patient, according to the Affymetrix “present” call (frequency range: 2% – 66%). Of these, 24 CT genes were expressed in more than 5% of the MMC samples and 25 are located on chromosome X. MMC of 98% of the patients expressed at least one CT gene, 86% at least two, and 70% at least three CT genes. By using a set of 10 CT genes including KM-HN-1, MAGE-C1, MAGE-A3/6/12, MAGE-A5, MORC, DDX43, SPACA3, SSX-4, GAGE-1–8 and MAGE-C2, a combination of at least three CT genes - desirable to circumvent tumor escape mechanisms and immune tolerance - could be obtained in MMC of 67% of the patients. Thus, gene expression profiling can be used to select CT antigens as vaccination targets in individual patients. In a series of MMC from 111 patients treated with the same high-dose chemotherapy and autologous peripheral blood stem cell transplantation protocol and having a median two-year follow-up, we found that the expression of six CT genes, i.e. CTAG-1B, CTAG-2, MAGE-A1, MAGE-A2, MAGE-A3 and MAGE-A6 was associated with a shorter event-free survival (EFS). Furthermore, considering only the 25 CT genes encoded by chromosome X, a CT-Xhigh cluster comprising MMC of one third of the patients (35 of 111) could be defined using a binary hierarchical clustering based on Affymetrix call. Patients in the CT-Xhigh cluster had a shorter EFS (median 13 months) compared to patients in the CT-Xlow cluster (median 18 months, P = .003). The CT-Xhigh clsuter included more patients with a stage III disease (P = .004). These results confirm data from previous studies indicating that patients expressing some CT genes located on chromosome X have a poor outcome.

Gene expression profiling for molecular classification of multiple myeloma in newly diagnosed patients

Blood ◽  
2010 ◽  
Vol 116 (14) ◽  
pp. 2543-2553 ◽  
Author(s):  
Annemiek Broyl ◽  
Dirk Hose ◽  
Henk Lokhorst ◽  
Yvonne de Knegt ◽  
Justine Peeters ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Plasma Cells ◽  
Medical Science ◽  
Protein Tyrosine Phosphatases ◽  
Molecular Classification ◽  
Newly Diagnosed ◽  
Expression Of Genes

Abstract To identify molecularly defined subgroups in multiple myeloma, gene expression profiling was performed on purified CD138+ plasma cells of 320 newly diagnosed myeloma patients included in the Dutch-Belgian/German HOVON-65/GMMG-HD4 trial. Hierarchical clustering identified 10 subgroups; 6 corresponded to clusters described in the University of Arkansas for Medical Science (UAMS) classification, CD-1 (n = 13, 4.1%), CD-2 (n = 34, 1.6%), MF (n = 32, 1.0%), MS (n = 33, 1.3%), proliferation-associated genes (n = 15, 4.7%), and hyperdiploid (n = 77, 24.1%). Moreover, the UAMS low percentage of bone disease cluster was identified as a subcluster of the MF cluster (n = 15, 4.7%). One subgroup (n = 39, 12.2%) showed a myeloid signature. Three novel subgroups were defined, including a subgroup of 37 patients (11.6%) characterized by high expression of genes involved in the nuclear factor kappa light-chain-enhancer of activated B cells pathway, which include TNFAIP3 and CD40. Another subgroup of 22 patients (6.9%) was characterized by distinct overexpression of cancer testis antigens without overexpression of proliferation genes. The third novel cluster of 9 patients (2.8%) showed up-regulation of protein tyrosine phosphatases PRL-3 and PTPRZ1 as well as SOCS3. To conclude, in addition to 7 clusters described in the UAMS classification, we identified 3 novel subsets of multiple myeloma that may represent unique diagnostic entities.

Molecular Classification of Light Chain (Al) Amyloidosis by Gene Expression Profiling

2004 ◽  
pp. 58-60
Author(s):  
R Abraham ◽  
R Fonseca ◽  
M Manske ◽  
T Price-Troska ◽  
M Gertz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Light Chain ◽  
Expression Profiling ◽  
Molecular Classification ◽  
Al Amyloidosis

scholarly journals Molecular Classification of Parathyroid Neoplasia by Gene Expression Profiling

2004 ◽  
Vol 165 (2) ◽  
pp. 565-576 ◽  
Author(s):  
Carl Morrison ◽  
William Farrar ◽  
Jeff Kneile ◽  
Nita Williams ◽  
Yiwen Liu-Stratton ◽  
...  
Keyword(s):  
Gene Expression ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Molecular Classification ◽  
Parathyroid Neoplasia

Gene Expression Profiling of Isolated Mesenchymal and Osteoblastic Cells Exhibits a Different Pattern of Expression in Multiple Myeloma Patients as Compared to Healthy Subjects: Potential Relationship with the Presence of Bone Lesions.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 3513-3513
Author(s):  
Nicola Giuliani ◽  
Katia Todoerti ◽  
Gina Lisignoli ◽  
Sara Tagliaferri ◽  
Luca Agnelli ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Cell Proliferation ◽  
Osteogenic Differentiation ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Differentially Expressed ◽  
Bone Lesions ◽  
Bone Status ◽  
Probe Set

Abstract Gene expression alterations occurring in the bone microenvironment cells and their potential relationships with the occurrence of bone lesions in multiple myeloma (MM) patients have never been investigated. In this study, we have isolated both mesenchymal (MSC) and osteoblastic (OB) cells, without in vitro differentiation, from bone biopsies obtained by iliac crest of 24 MM patients, 7 MGUS subjects and 8 healthy donors (N) who underwent orthopedics surgery. Bone status was evaluated in all MM patients by total X rays scan and MRI for the spine. Firstly, we evaluated cell proliferation in relationship with growth substrate (bone and glass) and cell phenotype by flow cytometry and immunohistochemistry. We found that both MSC and OB cells have higher cell doubling rate in MM patients as compared to N. Higher expression of alkaline phosphatase and Runx2 was observed in OB as compared to MSC cells in both N and MM patients without osteolytic lesions, but not in osteolytic ones. We performed a gene expression profiling analysis of isolated MSC and OB cells using GeneChip® Affymetrix HG-U133A oligonucleotide arrays. An unsupervised analysis of the most variable genes across the dataset generated a hierarchical clustering with the two major branches containing respectively MSC and OB samples. A multiclass analysis of N, MGUS and MM patients identified 33 differentially expressed probe-set (specific for 27 genes) in MSC cells, and 19 differentially expressed probe-set (13 genes) in OB, and the identified transcripts mainly characterized N versus MM and MGUS samples. A supervised analysis between N and MM samples identified 65 probes (56 genes: 17 up-regulated and 39 down-regulated) differentially expressed in MSC and 35 probes (29 genes, 12 up-regulated and 17 down-regulated) in OB. Notably, genes encoding the Homeobox class proteins, such as HOXB2-6-7, were up-regulated in both MSC and OB of MM patients as compared to N. As regards the bone status, a total of 60 probe-sets (3 up-regulated and 57 down-regulated genes) were found differentially expressed in MSC from osteolytic vs. non-osteolytic MM patients, whereas MGUS-MSC exhibited an intermediate transcriptional profile between osteolytic and non-osteolytic MM patients. A distinct pattern of gene expression profiling was also observed in MSC versus OB when osteolytic and non-osteolytic MM patients were compared (26 vs. 94 differentially expressed probe-sets, respectively), including transcription factors related to MSC osteogenic differentiation belonging to Runx2 pathway (HEY1) or Wnt and BMP signaling On the other hand, few genes were found differentially expressed in OB cells in relationship with the presence of bone lesions. In conclusion, we identified a distinctive transcriptional fingerprint in isolated MSC and OB cells of MM patients as compared to N subjects, which mainly correlated with cell proliferation. Moreover, a different gene expression profile was observed in MSC cells of MM patients according to the presence/absence of bone lesions, highlighting the critical role of the block of the osteogenic differentiation.

Ninety Percent Sustained Complete Response (CR) Rate Projected 4 Years after Onset of CR in Gene Expression Profiling (GEP)-Defined Low-Risk Multiple Myeloma (MM) Treated with Total Therapy 3 (TT3): Basis for GEP-Risk-Adapted TT4 and TT5

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 162-162 ◽  
Author(s):  
Bart Barlogie ◽  
Elias J. Anaissie ◽  
John D. Shaughnessy ◽  
Frits van Rhee ◽  
Mauricio Pineda-Roman ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Complete Response ◽  
Low Risk ◽  
Event Free Survival ◽  
Free Survival ◽  
Response Onset ◽  
Dose Dense

Abstract We have previously reported on the remarkable activity of the TT3 program that incorporated both bortezomib (V) and thalidomide (T) into the up-front management of 303 patients. TT3 consisted of 2 cycles each of induction prior to and of dose-reduced consolidation therapy with VTD-PACE (cisplatin, doxorubicin, cyclophosphamide, etoposide) after melphalan 200mg/m2 (M200)-based tandem transplants, followed by maintenance therapy for 3 years with VTD and, in later stages, VRD (substituting T for lenalidomide, R). Characteristics included a median age of 59yr (range, 33–75yr), B2M &gt;=4mg/L in 37%, albumin &lt;3.5g/dL in 26%, ISS stages II and III in 33% and 21%, cytogenetic abnormalities (CA) in 33% and gene expression profiling (GEP)-defined high-risk MM in 15% of the 275 patients with such data. With a median follow-up of 39 months, 4-yr overall survival (OS) and event-free survival (EFS) estimates were 78% and 71%, respectively, including 84% and 77% among the 85% with GEP-defined low-risk MM contrasting with 43% and 33% in the remainder with high-risk MM (both p&lt;0.0001). Near-CR and CR, attained in 86% and 63%, were sustained at 4 years from response onset in 78% and 87%, which pertained to 83% and 90% with low-risk MM but to only 44% and 57% with high-risk MM (all p &lt;0.0001). These results were corroborated in a TT3 extension trial (TT3E) that enrolled 175 additional patients, comprising higher proportions of CA (42%) and GEP-defined high-risk MM (21%). Two-year estimates of OS and EFS are 85% and 85%, with 94% and 92% in low-risk patients versus 61% and 62% in high-risk MM (p=0.0001, p=0.0003); the 2-yr estimate of remaining in CR is 93% including 100% in low-risk and 77% in high-risk MM (p=0.01). Multivariate analysis of features linked to OS in TT3 included GEP-defined high-risk, CA, B2M and LDH elevation, collectively accounting for 41% of outcome variability by R2 statistics; the corresponding R2 values for EFS and n-CR duration were 38% and 39%. Compared to the predecessor trial, TT2, that evaluated the role of T in a randomized trial design in 668 patients, TT3 data were superior for OS (p=0.08), EFS (&lt;0.0001), n-CR duration (p&lt;0.0001) and CR duration (p=0.0002). In the low-risk subgroup, EFS (p=0.0001), n-CR duration (p&lt;0.0001) and CR duration (Figure 1a; p=0.0002) all were superior in TT3 versus TT2; whereas, in the high-risk MM group, outcomes remained poor also with TT3 despite superior EFS (Figure 1b; p=0.03). Based on these data, we have now started a GEP-risk-based algorithm of assigning separate therapies to good-risk (TT4) and poor-risk MM (TT5). As the TT3 results for low-risk are difficult to improve upon, TT4 randomizes patients between standard TT3 and TT3-LITE that employs only 1 cycle each of induction and consolidation (with anticipated further improvement in compliance) and 4-day-fractionated M50×4 to enable the addition of VTD and thus exploit synergistic drug interactions to occur. In order to sustain tolerable effective therapies for at least 3 years and prevent recurrence from previous drug-free or insufficiently effective phases in TT3, TT5 for high-risk MM employs less dose-intense and more dose-dense highly synergistic combination therapy, utilizing M10-VTD-PACE for induction, M80 (in 4 daily fractions of M20) plus VRD-PACE tandem transplants, separated by 2 cycles of M20 (in 4 daily fractions of M5) plus VTD-PACE, and followed by 2 years of monthly alternating R-VD and M-VD. Figure 1a: Superior CR duration with TT3 v TT2 in GEP-low-risk MM: Figure 1a:. Superior CR duration with TT3 v TT2 in GEP-low-risk MM: Figure 1b: Superior event-free survival with TT3 v TT2 in GEP-high-risk MM: Figure 1b:. Superior event-free survival with TT3 v TT2 in GEP-high-risk MM:

scholarly journals Molecular Classification of MYC-Driven B-Cell Lymphomas by Targeted Gene Expression Profiling of Fixed Biopsy Specimens

2015 ◽  
Vol 17 (1) ◽  
pp. 19-30 ◽  
Author(s):  
Christopher D. Carey ◽  
Daniel Gusenleitner ◽  
Bjoern Chapuy ◽  
Alexandra E. Kovach ◽  
Michael J. Kluk ◽  
...  
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Gene Expression Profiling ◽  
Expression Profiling ◽  
Molecular Classification ◽  
B Cell Lymphomas ◽  
Biopsy Specimens ◽  
Targeted Gene Expression
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