The Transcriptome of Immunomodulator-Resistant Multiple Myeloma

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 1772-1772
Author(s):  
Moritz Binder ◽  
S. Vincent Rajkumar ◽  
Martha Q. Lacy ◽  
Jessica L. Haug ◽  
Angela Dispenzieri ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Overall Survival ◽  
Differentially Expressed Genes ◽  
Research Funding ◽  
Differentially Expressed ◽  
Resistant Disease ◽  
Kaplan Meier ◽  
Gene Coding ◽  
Cellular Pathways

Introduction: While the molecular target of immunomodulators such as pomalidomide (POM) and lenalidomide (LEN) has been identified, the mechanisms underlying therapeutic resistance remain incompletely understood. The uniformly emerging resistance to therapy over time in the absence of identifiable cereblon pathway mutations in the majority of patients raises questions about alternative mechanisms including aberrant gene expression. Methods: We performed gene expression profiling using an Affymetrix GeneChip Human Genome U133 Plus 2.0 microarray on CD138+ bone marrow cells from patients with relapsed / refractory (RRMM) and newly diagnosed (NDMM) multiple myeloma prior to initiating treatment. Patients were treated on two phase II clinical trial protocols (MC0789: POM ± dexamethasone in RRMM; MC0884: LEN ± dexamethasone in NDMM) between 2007 and 2012. We categorized patients based on their IMWG response as non-responders (SD) and responders (VGPR+). We selected 15 responders and 15 non-responders from MC0789 (n = 30) and compared overall survival, gene expression patterns, and involved cellular pathways between the two groups. We selected 5 responders and 5 non-responders from MC0884 (n = 10) for targeted validation of differentially expressed candidate genes. After data quality control and normalization of gene expression values, differential gene expression was estimated using limma. Statistical significance was adjusted for multiple testing in the discovery set using a false discovery rate-based approach for genome-wide experiments (q-value). We used Gene Ontology and PANTHER pathway analysis for functional annotation of differentially expressed genes. Overall survival estimates were calculated using the Kaplan-Meier method. Computation and visualization were performed in R. Results: Median age at treatment initiation on MC0789 was 65 years (40 - 82), 65% of the patients were male. Pomalidomide resistance was associated with an increase in mortality (median overall survival 1.6 versus 6.4 years, p = 0.009, Kaplan-Meier plot). There were 1076 differentially regulated genes between responders and non-responders (521 up- and 555 down-regulated, q < 0.050 for all genes, volcano plot). Expression of CRBN was 1.5-fold down-regulated in non-responders (q = 0.005). Supervised hierarchical clustering of the top 500 differentially expressed genes demonstrated distinct patterns in pomalidomide-resistant disease (heatmap). Gene ontology analysis revealed protein synthesis as one of the most enriched biological processes (bar graph). Pathway analysis showed a 6-fold enrichment (FDR = 0.007) of the ubiquitin proteasome pathway in pomalidomide-resistant disease. Differentially expressed genes involved key protein degradation pathways, epigenetic modifiers, and transcription factors. Targeted validation in MC0884 revealed 13 common genes with at least 1.5-fold differential expression (5 up- and 8 down-regulated), 12 of which have previously been implicated in the regulation of apoptosis, tumor glucose metabolism, Rho and Wnt signaling, miRNA-driven resistance to chemotherapy, and ubiquitin-dependent protein degradation (Table and Sankey diagram). The most up-regulated gene in non-responders was MYRIP, a gene coding for a vesicle trafficking protein associated with platinum resistance and suppression of pro-apoptotic BCL-2 family members in solid malignancies. The most down-regulated gene was FRZB, a gene coding for a negative regulator of Wnt signaling, previously implicated in the progression of monoclonal gammopathy of undetermined significance to multiple myeloma. Conclusions: Overall survival of patients with pomalidomide-resistant RRMM remains poor. Pomalidomide resistance was associated with differential gene expression in several potentially targetable cellular pathways beyond the known drug target cereblon. Targeted validation of candidate genes revealed common cellular pathways in immunomodulator-resistant disease. Elucidating the exact molecular mechanisms underlying immunomodulator resistance is of considerable interest for biomarker development and the identification of novel therapeutic targets and warrants further exploration. Figure Disclosures Lacy: Celgene: Research Funding. Dispenzieri:Celgene: Research Funding; Alnylam: Research Funding; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Akcea: Consultancy; Takeda: Research Funding. Kumar:Takeda: Research Funding; Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding.

scholarly journals Gene Expression Profiling of Structural and Functional High-Risk Multiple Myeloma

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 3061-3061
Author(s):  
Moritz Binder ◽  
S. Vincent Rajkumar ◽  
Martha Q. Lacy ◽  
Jessica L. Haug ◽  
Angela Dispenzieri ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
High Risk ◽  
Research Funding ◽  
Expression Profiles ◽  
Prognostic Significance ◽  
Gene Expression Profiles ◽  
Differentially Expressed ◽  
Cell Labeling ◽  
Kaplan Meier

Introduction: High-risk multiple myeloma can be defined by the presence of specific cytogenetic abnormalities (structural) or by characteristic changes in bone marrow and peripheral blood biomarkers (functional). While both entities are characterized by therapeutic resistance, frequent disease relapses, and adverse survival outcomes, the underlying molecular mechanisms remain incompletely understood. Methods: We performed gene expression profiling (GEP) using an Affymetrix GeneChip Human Genome U133 Plus 2.0 microarray on CD138+ bone marrow cells from 137 patients diagnosed with multiple myeloma between 2004 and 2012. All patients underwent Fluorescence In-situ Hybridization (FISH) evaluation, plasma cell labeling, International Staging System (ISS) risk stratification, and GEP prior to initiating treatment with novel agents. The presence of del(17p), t(4;14), t(14;16), and t(14;20) on FISH, a plasma cell labeling index (PCLI) > 2%, and ISS stage III were considered high-risk abnormalities: FISH-HR (n = 15, structural high-risk, at least one high-risk FISH lesion), PCLI-HR (n = 20; functional high-risk, PCLI > 2%), and ISS-HR (n = 12; functional high-risk, ISS stage III). For each HR group we sampled standard risk (SR) controls in a 4:1 ratio. After data quality control and normalization, differential gene expression was estimated using limma. Statistical significance was adjusted for multiple comparisons using a false discovery rate-based approach for genome-wide experiments (q-value). We employed PANTHER pathway analysis for the differentially expressed genes in each HR group. We implemented a simple gene expression score (GES) by calculating the sum of quartiles of the normalized gene expression values for genes differentially expressed in more than one HR group (GES = ΣUP(quartile - 1) + ΣDN(4 - quartile)) and externally validated its prognostic significance (UAMS TT2 / TT3, GSE24080). Survival outcomes were analyzed using the methods described by Kaplan, Meier, and Cox. Computation and visualization were performed in R. Results: Median age at diagnosis was 63 years (32 - 87), 53% of the patients were male. High-risk disease was associated with inferior overall survival, regardless of the used definition (left Kaplan-Meier plots): FISH-HR (HR 4.3, 95% CI 1.9 - 9.8, p < 0.001), PCLI-HR (HR 2.7, 95% CI 1.4 - 5.3, p = 0.004), and ISS-HR (HR 2.8, 95% CI 1.2 - 6.5, p = 0.015). There were 59 (FISH-HR), 424 (ISS-HR), and 507 (PCLI-HR) differentially expressed genes (q < 0.050 for all genes, volcano plots). PCLI-HR and FISH-HR demonstrated a predominance of transcriptional up-regulation while ISS-HR had a balanced gene expression profile with a similar number of genes being up- and down-regulated. The involved cellular pathways were different across the HR groups except for anti-apoptotic signaling (bar graphs). All HR groups had distinct gene expression profiles with no complete overlap between all HR groups. There were 71 genes with overlap between two HR groups (69 up-regulated, 2 down-regulated, Venn diagrams). The median GES was 97 (18 - 206, higher numbers indicating higher expression of up-regulated and lower numbers of down-regulated high-risk genes) in 559 patients treated on UAMS TT2 / TT3 (GSE24080). Tertiles of the GES were associated with event-free survival (HR 1.4, 95% CI 1.2 - 1.6, p < 0.001) and remained independently prognostic after adjusting for age, sex, and ISS stage (HR 1.3, 95% CI 1.1 - 1.5, p < 0.001). Conclusions: High-risk multiple myeloma remains associated with inferior overall survival, regardless of the used definition (structural or functional). The subtypes of high-risk disease have distinct gene expression profiles and involve different cellular pathways, providing important clues to the underlying biology. A 71 gene signature derived from the different high-risk subtypes was of prognostic significance in a clinical trial population after adjusting for known prognostic factors. Figure Disclosures Lacy: Celgene: Research Funding. Dispenzieri:Akcea: Consultancy; Intellia: Consultancy; Janssen: Consultancy; Pfizer: Research Funding; Takeda: Research Funding; Celgene: Research Funding; Alnylam: Research Funding. Stewart:Takeda: Consultancy; Seattle Genetics: Consultancy; Roche: Consultancy; Ono: Consultancy; Celgene: Consultancy, Research Funding; Ionis: Consultancy; Janssen: Consultancy, Research Funding; Oncopeptides: Consultancy; Amgen: Consultancy, Research Funding; Bristol Myers-Squibb: Consultancy. Bergsagel:Celgene: Consultancy; Ionis Pharmaceuticals: Consultancy; Janssen Pharmaceuticals: Consultancy. Kumar:Celgene: Consultancy, Research Funding; Janssen: Consultancy, Research Funding; Takeda: Research Funding.

scholarly journals Construction of a competitive endogenous RNA network and analysis of potential regulatory axis targets in glioblastoma

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Kai Yu ◽  
Huan Yang ◽  
Qiao-li Lv ◽  
Li-chong Wang ◽  
Zi-long Tan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Differentially Expressed Genes ◽  
Pearson Correlation ◽  
Differentially Expressed ◽  
Migration And Invasion ◽  
Glioblastoma Cells ◽  
Network Chain ◽  
Cerna Network ◽  
Potential Marker

Abstract Background Glioblastoma is the most common primary malignant brain tumor. Because of the limited understanding of its pathogenesis, the prognosis of glioblastoma remains poor. This study was conducted to explore potential competing endogenous RNA (ceRNA) network chains and biomarkers in glioblastoma by performing integrated bioinformatics analysis. Methods Transcriptome expression data from The Cancer Genome Atlas database and Gene Expression Omnibus were analyzed to identify differentially expressed genes between glioblastoma and normal tissues. Biological pathways potentially associated with the differentially expressed genes were explored by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, and a protein-protein interaction network was established using the STRING database and Cytoscape. Survival analysis using Gene Expression Profiling Interactive Analysis was based on the Kaplan–Meier curve method. A ceRNA network chain was established using the intersection method to align data from four databases (miRTarBase, miRcode, TargetScan, and lncBace2.0), and expression differences and correlations were verified by quantitative reverse-transcription polymerase chain reaction analysis and by determining the Pearson correlation coefficient. Additionally, an MTS assay and the wound-healing and transwell assays were performed to evaluate the effects of complement C1s (C1S) on the viability and migration and invasion abilities of glioblastoma cells, respectively. Results We detected 2842 differentially expressed (DE) mRNAs, 2577 DE long non-coding RNAs (lncRNAs), and 309 DE microRNAs (miRNAs) that were dysregulated in glioblastoma. The final ceRNA network consisted of six specific lncRNAs, four miRNAs, and four mRNAs. Among them, four DE mRNAs and one DE lncRNA were correlated with overall survival (p < 0.05). C1S was significantly correlated with overall survival (p= 0.015). In functional assays, knockdown of C1S inhibited the proliferation and invasion of glioblastoma cell lines. Conclusions We established four ceRNA networks that may influence the occurrence and development of glioblastoma. Among them, the MIR155HG/has-miR-129-5p/C1S axis is a potential marker and therapeutic target for glioblastoma. Knockdown of C1S inhibited the proliferation, migration, and invasion of glioblastoma cells. These findings clarify the role of the ceRNA regulatory network in glioblastoma and provide a foundation for further research.

scholarly journals HIF-Mediated and Non-HIF-Mediated Differential Gene Expressions in Sickle Cell Reticulocyte and Their Impact on Clinical Manifestations

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 950-950
Author(s):  
Xu Zhang ◽  
Jihyun Song ◽  
Binal N. Shah ◽  
Jin Han ◽  
Taif Hassan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Differentially Expressed Genes ◽  
Research Funding ◽  
Clinical Manifestations ◽  
Hemoglobin Concentration ◽  
Differentially Expressed ◽  
Erythroid Progenitors ◽  
Advisory Committees ◽  
Deconvolution Analysis ◽  
Stress Erythropoiesis

Abstract Reticulocytosis in sickle cell disease (SCD) is driven by tissue hypoxia from hemolytic anemia and vascular occlusion. Gene expression changes caused by hypoxia and other factors during reticulocytosis may impact SCD outcomes. We detected 1226 differentially expressed genes in SCD reticulocyte transcriptome compared to normal Black controls. To assess the role of hypoxia-mediating HIFs from other regulation of changes of the SCD reticulocyte transcriptome, we compared differential expression in SCD to that in Chuvash erythrocytosis (CE), a disorder characterized by constitutive upregulation of HIFs in normoxia. Of the SCD differentially expressed genes, 28% were shared between CE and SCD and thus classified as HIF-mediated. The HIF-mediated changes were generally in genes promoting erythroid maturation. We found that genes encoding the response to endoplasmic reticulum stress generally lacked HIF mediation. We then investigated the clinical correlation of erythroid gene expression for the 1226 differentially expressed genes detected in SCD reticulocytes, using clinical measures and gene expression data previously profiled in peripheral blood mononuclear cells (PBMCs) of 157 SCD patients at the University of Illinois at Chicago (UIC). Normal PBMCs contain only a small number of erythroid progenitors, but in SCD or CE PBMCs the erythroid transcriptome is enriched due to elevated circulating erythroid progenitors from heightened erythropoiesis (PMID: 32399971). We applied deconvolution analysis to assess the clinical correlation of erythroid gene expression, using a 16-gene expression signature of erythroid progenitors previously identified in SCD PBMCs. Deconvolution analysis uses the proportion of cell/tissue or specific marker genes (here the erythroid specific 16-gene signature) to dissect gene expression variation in biological samples with cell/tissue type heterogeneity. We correlated, in the 157 UIC patients, erythroid gene expression with i) degree of anemia as indicated by hemoglobin concentration, ii) vaso-occlusive severe pain episodes per year, and iii) degree of hemolysis measured by a hemolysis index. The analysis identified 231 genes associated with at least one of the complications. Increased expression of 40 erythroid specific genes, including 15 HIF-mediated genes, was associated with all three complications. These 40 genes are all upregulated in SCD reticulocytes and correlated with low hemoglobin concentration, frequent severe pain episodes, and high hemolysis index, suggesting that these manifestations may share a relationship to stress erythropoiesis-driven transcriptional activity. Expression quantitative trait loci (eQTL) contain genetic polymorphisms that associate with gene expression level, which can be viewed as a natural experiment to investigate the causal relations between gene expression change and phenotypic outcomes. To assess the causal effect of erythroid gene expression, we tested association between erythroid eQTL and the clinical manifestations in 906 SCD patients from the Walk-PHaSST and PUSH cohorts. We first mapped erythroid eQTL in the 157 UIC patients, who were previously genotyped by array, applying deconvolution algorithm on the same PBMC data for the 1226 differential genes in SCD reticulocytes, and detected 54 distinct eQTL for 30 genes at 5% false discovery rate. After adjusting for multiple comparisons, we found that the C allele of rs16911905, located in the β-globin cluster and associated with increased erythroid expression of HBD (encodes δ-globin of hemoglobin A 2), significantly correlated with lower hemoglobin concentration (β=-0.064, 95% CI -0.092 - -0.036, P=6.7×10 -6). The C allele was also associated with higher hemolytic rate (P=0.031), less frequent pain episodes (P=0.045), and increased erythroid expression of HBB here encoding sickle β-globin (P=5.1x10 -5). The association of the C allele with lower hemoglobin concentration was then validated in 242 patients from the UIC cohort (β=-0.071, 95% CI -0.13 - -0.011, P=0.023), as was the trend of association with higher hemolytic rate (P=0.0031) and less pain episodes (P=0.034). Our findings reveal HIF- and non-HIF-mediated genes in SCD stress erythropoiesis, and identify novel clinical associations for a HBD eQTL. Our study highlights the correlation of altered erythroid gene expression with SCD hemolytic and vaso-occlusive manifestations. Disclosures Saraf: Global Blood Therapeutics: Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Membership on an entity's Board of Directors or advisory committees, Research Funding; Pfizer: Research Funding. Gordeuk: Modus Therapeutics: Consultancy; Novartis: Research Funding; Incyte: Research Funding; Emmaus: Consultancy, Research Funding; Global Blood Therapeutics: Consultancy, Research Funding; CSL Behring: Consultancy.

Heterogeneity of MYC Abnormalities in Multiple Myeloma

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 2-3
Author(s):  
Neeraj Sharma ◽  
James B Smadbeck ◽  
Nadine Abdallah ◽  
Kathryn E. Pearce ◽  
Yan Asmann ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
Overall Survival ◽  
Clinical Trials ◽  
Genome Sequencing ◽  
Mayo Clinic ◽  
Research Funding ◽  
Advisory Board ◽  
Expression Levels ◽  
Myc Gene

Background: Multiple myeloma (MM) is an incurable plasma cell malignancy and genetic abnormalities contribute to disease heterogeneity and outcome. Primary abnormalities, namely recurrent immunoglobulin (Ig) heavy chain translocations and hyperdiploidy, occur early in disease course. Secondary events, such as MYC abnormalities occur upon progression. Earlier studies showed MYC abnormalities detected by FISH or by capture sequencing were independently associated with poor outcome (Walker, et al., BCJ, 2014), while recent studies using WGS did not support this finding (excluding MYC/IGL) (Mikulasova, et al. Haematologica, 2020; Misund, et al. Leukemia, 2020). We hypothesize these discrepancies are due to differences in methods and sensitivities of detection of MYC abnormalities by FISH vs. WGS. Given that MYC abnormalities often display remarkable genomic heterogeneity with numerous gene partners, reduced detection of MYC abnormalities by FISH is not unexpected. This hypothesis is supported by lower frequencies of MYC abnormalities found by FISH (15%) vs. NGS (30-35%) consistent with ~50% false-negative rate of the MYC FISH probe (Smadbeck, et al. BCJ, 2019). To better understand the role of MYC in myeloma disease outcome, we compared the MYC abnormality subtype identified by FISH or NGS vs. MYC gene expression levels and overall survival. Methods: We performed a retrospective study of newly diagnosed MM patients seen at Mayo Clinic or enrolled in the MMRF CoMMpass trial. For Mayo cases, MYC FISH results (breakapart probe, Abbott) were obtained from the Mayo Clinic Genomics database (N=1342) and mate pair sequencing (MPseq) was performed on 140 cases. For CoMMpass cases, we obtained tumor long-insert whole genome sequencing (WGS), RNA sequencing (RNAseq) for gene expression and clinical outcome data. Overall survival (OS) was defined as time from diagnosis to death from any cause or to last follow up. Survival curves were estimated using Kaplan Meier and compared using the Log-Rank test. Statistical analyses performed using SPSS and JMP with significance determined when P &lt;0.05. Results: We first evaluated the impact of MYC abnormalities on OS when detected by FISH or NGS. In Mayo cases, OS was significantly shorter in patients with MYC abnormalities compared to patients without MYC abnormalities using FISH (5.3 vs. 8.0 years, P&lt;0.001, N=1342). In contrast, there was no significant difference in OS between patients with or without MYC or abnormalities using MPseq or WGS in both the Mayo and CoMMpass cohorts (Mayo: 6.4 vs. and 6.9 years P=0.78, N=140; CoMMpass: 4.9 vs. and 5.1 years P=0.74, N=546). Since FISH-detected MYC abnormalities were associated with poor outcome, we evaluated differences in the types of MYC abnormalities identified FISH and genome sequencing; 270 of 658 CoMMpass cases had a MYC abnormality and 12 abnormality subgroups were identified. In the Mayo cases, FISH preferentially detected translocations and complex abnormalities and missed insertions with flanking duplicating sequences or terminal tandem duplications (TTD) that occur telomeric to MYC. Since the level of MYC expression should be a consequence of the various genomic abnormalities altering the MYC gene region, we compared MYC expression levels in relation to MYC abnormality subgroups. Highest expression was seen with MYC amplification, followed by Ig abnormalities, non-Ig abnormalities, complex deletion/duplications, proximal deletions, non-Ig insertions, terminal deletions, TTD, trisomy 8, no MYC structural variation, monosomy 8 and cases with MAX mutations had the lowest expression. Abnormalities identified by FISH had higher MYC expression (83.5 TPM) compared to cases predicted to be missed by FISH (63.2 TPM). We tested if high MYC expression, irrespective of MYC structural abnormality, was associated with differences in OS. Boxplot analysis was used to categorize MYC expression in 631 CoMMpass patients as top quartile/high MYC expression (Q4≥ 75 TPM, n=159) and bottom quartile/low MYC expression (Q1≤ 16.5 TPM, n= 158) (see Figure). OS was significantly shorter in patients with high MYC expression compared to patients with low MYC expression (4.6 vs. 5.3 years, P &lt;0.038). Conclusion: We show that FISH detects only a subset of the MYC abnormalities detected by genome sequencing, and that FISH-detected MYC abnormalities are associated with higher MYC gene expression and decreased survival. Figure 1 Disclosures Kumar: Kite Pharma: Consultancy, Research Funding; Janssen Oncology: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; AbbVie: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Oncopeptides: Consultancy, Other: Independent Review Committee; IRC member; Dr. Reddy's Laboratories: Honoraria; Cellectar: Other; Takeda: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Novartis: Research Funding; Tenebio: Other, Research Funding; Carsgen: Other, Research Funding; Amgen: Consultancy, Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments, Research Funding; Merck: Consultancy, Research Funding; Genecentrix: Consultancy; BMS: Consultancy, Research Funding; Karyopharm: Consultancy; Celgene/BMS: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Genentech/Roche: Other: Research funding for clinical trials to the institution, Consulting/Advisory Board participation with no personal payments; Sanofi: Research Funding; MedImmune: Research Funding; Adaptive Biotechnologies: Consultancy.

scholarly journals Outcome of Multiple Myeloma Patients Treated with Carrd-PACE Chemomobilization: A Single-Center Experience

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 3377-3377 ◽  
Author(s):  
Andrew J. Cowan ◽  
Mehdi Karami ◽  
Edward N. Libby ◽  
Pamela S. Becker ◽  
David G. Coffey ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Overall Survival ◽  
Median Time ◽  
Research Funding ◽  
Cardiac Toxicity ◽  
Left Ventricular ◽  
Left Ventricular Ejection ◽  
Autologous Transplant ◽  
Kaplan Meier ◽  
Pet Ct

Abstract Background: Bortezomib was originally incorporated into DT-PACE (thalidomide, dexamethasone, cisplatin, doxorubicin, cyclophosphamide, and etoposide) as an intensive induction regimen (VTD-PACE) prior to high-dose melphalan and autologous transplant for multiple myeloma (MM). This regimen is effective in the induction setting, and also for patients with relapsed disease (Barlogie British Journal of Haematology 2007, Singh ASCO 2013). At our center, we examined the outcomes of MM patients undergoing chemomobilization with a regimen that substituted carfilzomib and lenalidomide for bortezomib and thalidomide (CarRD-PACE). Methods: Twenty MM patients with measureable disease received CarRD-PACE for chemomobilization. We excluded in this report patients with plasma cell leukemia, renal insufficiency, heart failure, or those patients who were refractory to carfilzomib. Results: The median age was 61.5 years (range, 35- 69). Nine of these patients were women (45%). The median left ventricular ejection fraction pre-treatment was 62% (range, 50 - 77%). Of patients with initial staging information, 8 were ISS stage I (47%), 5 patients ISS II (29%), and 4 were ISS III (24%). High risk cytogenetics, defined as presence of deletion 17p, t(4;14), t(14;16), were present in 5 patients at time of chemomobilization (25%). Fourteen patients (82%) had bulky disease (defined as having > 3 lesions, or having a single lesion > 3 cm on PET-CT or MRI) prior to treatment, assessed by MRI (n=12) or PET-CT (n= 2). The median time from diagnosis to mobilization was 9.5 months (range, 4- 44). Patients had previously received a median of 2 regimens of therapy (range, 1- 5). Fifteen patients received 1 cycle of CarRD-PACE, and 5 patients received 2 cycles. Eighteen patients response evaluable; in these patients, the overall CR/PR response rate after completion of treatment was 25% (4 PR, 1 CR), with fifteen patients (75%) having SD. A total of 18 patients (90%) collected stem cells after mobilization, requiring a median of 1 day of collection (range, 1-2), and collected a median of 18.3 x 10^6 CD34+ cells/kg (range, 4.8 - 69.88). Grade 3-4 toxicities occurred in 6 patients (30%), most common was neutropenic fever (n=4) (20%). No patients experienced a cardiac toxicity. Hospital readmission following treatment occurred in 4 patients (20%) for a median of 6.5 days (range, 3 - 15). Eighteen patients (90%) underwent a single autologous transplant, and 2 (10%) received tandem autologous-allogeneic transplant. Following autologous transplant, the median time to neutrophil engraftment was 18 days (range, 14 - 29 days), and the median time to platelet engraftment was 13 days (range, 7 - 19 days). The PFS at 6 months was 63% (95% CI, 0.382 - 1), and the OS at 6 months was 91% (95% CI, 0.754 - 1) (Figure). Discussion: CarRD-PACE is a well-tolerated and effective therapy in heavily treated multiple myeloma patients with substantial disease burden at the time of autologous transplant, and can successfully mobilize autologous PBSC. Despite the theoretical concern regarding the combination of 2 agents with cardiac toxicity (carfilzomib and doxorubicin), we did not observe any cardiac toxicities of any grade during treatment. This approach may be particularly useful in individuals with bortezomib associated neuropathy and or those with bortezomib refractory disease. Figure Kaplan-meier plots for progression free and overall survival. Figure. Kaplan-meier plots for progression free and overall survival. Disclosures Becker: GlycoMimetics: Research Funding. Shadman:Pharmacyclics: Honoraria, Research Funding; Acerta: Research Funding; Gilead: Honoraria, Research Funding; Emergent: Research Funding. Gopal:Seattle Genetics: Research Funding.

Five-Year Follow-up of Randomized, Phase II Trial of Idiotype-Pulsed Dendritic Cell Vaccine with Adjuvant Cytokines In Plateau Phase and Post-Transplant Multiple Myeloma

Blood ◽  
2010 ◽  
Vol 116 (21) ◽  
pp. 1958-1958
Author(s):  
Yi Lin ◽  
Morie Gertz ◽  
Sumithra Mandrekar ◽  
Kristina Laumann ◽  
Angela Dispenzieri ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Overall Survival ◽  
Phase Ii ◽  
Research Funding ◽  
Phase Ii Trial ◽  
Dendritic Cell Vaccine ◽  
Cell Vaccine ◽  
Plateau Phase ◽  
Time To Progression ◽  
Kaplan Meier

Abstract Abstract 1958 Vaccines may offer additional benefit as consolidation therapy after plateau phase or autologous stem cell transplant (ASCT) for multiple myeloma (MM). We have reported previously the results of another phase II trial showing that using APC8020 (Mylovenge™) after ASCT improved the overall survival (OS 5.3 yrs, 95% CI 4.0 yrs – NA) compared to ASCT alone (3.4 yrs, 95% CI 2.7 – 4.6 yrs; p = 0.02; Lacy, AJH (84): 799). We now report the results from a randomized, phase II trial using the same vaccine plus adjuvant cytokines in MM patients in plateau phase after either chemotherapy or ASCT. Twenty patients were enrolled between 2001 and 2003 and were randomized to receive APC8020 and adjuvant cytokine of either interferon-g (IFNg, arm A, n = 10) or interleukin-2 (IL2, arm B, n = 10). Each cycle of treatment included five days of daily subcutaneous injections of either IFNg (106 IU, arm A) or IL2 (200 mg, arm B) followed by APC8020 injection. Each patient received a cycle of treatment every 2 weeks for 4 cycles. One patient in each arm was in plateau phase post-chemotherapy. Time from diagnosis to treatment was 11.9 mos for the patient in arm A and 16.2 mos for arm B. Time to progression (TTP) was 3.7 and 68 months respectively the patient in arm A and B. Both patients were alive at five years. For the 9 post-ASCT patients in each arm, no statistically significant differences were seen in the baseline characteristics between the 2 arms. The median time from diagnosis to treatment was 15.4 months. No grade 4 or 5 adverse events (AEs) were reported. Two patients in each arm had grade 3 AE, including lymphopenia, thrombocytopenia, hemorrhage, infection, and fatigue. One patient in arm B had grade 3 autoimmune disorder that was deemed possibly related to study treatment. The most common AEs were grade 1 fatigue (n = 7) and anemia (n = 5) in arm A and grade 1 anemia (n = 7) and injection site reaction (n = 5) in arm B. The median TTP was 9.3 months (95% CI: 3.9 – 19.3 months) for arm A and 6.6 months for arm B (95% CI: 6.3 – 29.6 months) with no statistically significant difference between the two arms (p = 0.89). The median OS had not been reached for either arm; the 5-year OS rate was 67% and 56% for arms A and B respectively (p = 1.0). Interestingly, similar to our previous study where TTP was not different while OS was improved with vaccine, when we compared the clinical outcome for all patients in this vaccine trial to that of 78 matched control patients who only received ASCT during the same time frame, we did not see significant improvement in TTP (Figure 1). However, the 5-year overall survival for all patients in this trial is significantly improved at 71% (95%CI: 51–96%) compared to ASCT control patients (41%, 95% CI: 31 – 54%; p = 0.03; Figure 1). This trial suggests improved OS with vaccine plus cytokine. It is possible that modulation of patients’ immunity may help them live longer with multiple myeloma. Further investigation is needed to compare the approach in this trial with dendritic cell vaccine alone to better understand optimal strategy for vaccine therapy in MM. Figure 1. Kaplan-Meier curves for time to progression and overall survival Figure 1. Kaplan-Meier curves for time to progression and overall survival Disclosures: Dispenzieri: Celgene: Honoraria, Research Funding; Binding Site: Honoraria. Kumar:Celgene: Consultancy, Research Funding; Millennium: Research Funding; Merck: Consultancy, Research Funding; Novartis: Research Funding; Genzyme: Consultancy, Research Funding; Cephalon: Research Funding. Lacy:Celgene: Research Funding.

scholarly journals Gene Expression and Epigenetic Analysis in Relapsed/Refractory Diffuse Large B Cell Lymphoma Provides Insights into Evolution of Treatment Resistance to R-CHOP

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 26-26
Author(s):  
Manishkumar S. Patel ◽  
Ellen K. Kendall ◽  
Sarah Ondrejka ◽  
Agrima Mian ◽  
Yazeed Sawalha ◽  
...  
Keyword(s):  
Gene Expression ◽  
B Cell ◽  
Differentially Expressed Genes ◽  
Research Funding ◽  
B Cell Lymphoma ◽  
Cell Receptor ◽  
B Cell Receptor ◽  
Gene Set Enrichment Analysis ◽  
Differentially Expressed ◽  
P Value

Background Diffuse large B cell lymphoma (DLBCL) is curable in ~60-70% of patients using standard chemoimmunotherapy, but the prognosis is poor for relapsed/refractory (R/R) DLBCL. Therefore, understanding the underlying molecular mechanisms will facilitate early prediction and effective management of resistance to therapy. Recent studies of paired diagnostic-relapse biopsies from patients have relied on a single "omics" approach, examining either gene expression or epigenetic evolution. Here we present a combined analysis of gene expression and DNA methylation profiles of paired diagnostic-relapse DLBCL biopsies to identify changes responsible for relapse after R-CHOP. Methods Biopsies from 23 DLBCL patients were obtained at the time of diagnosis and relapse following frontline R-CHOP chemoimmunotherapy. The cohort had 18 (78.3%) male patients with median age of 62 (range, 35-86) years and median IPI of 2.5 (range, 1-5). The median time from diagnosis to relapse was 7 (range, 0-57) months. DNA and RNA were extracted simultaneously from formalin-fixed paraffin embedded (FFPE) biopsy samples. DNA methylation levels were measured through Illumina 850k Methylation Array for 22 pairs of diagnostic-relapse biopsies. RNA from diagnostic-relapse paired biopsies from 6 patients was sequenced using Illumina HiSeq4000. Differentially methylated probes were identified using the DMRcate package, and differentially expressed genes were identified using the DESeq2 package. Gene set enrichment analysis was performed using canonical pathway gene sets from MSigDB. Pearson's correlation with a Bonferroni correction to the p-value was used to calculate the correlation between regularized log transformed gene expression counts and methylation beta values. Results In a pairwise comparison of gene expression between diagnostic and R/R biopsy pairs, we found 14 differentially expressed genes (FDR&lt;0.1 & Log2FC&gt;|1|) consistent across all pairs. Compared to gene expression at diagnosis, five genes (CYP1B1, LGR4, ATXN1, CTSC, ZMAT3) were downregulated, and eight genes (ERBB3, CD19, CARD11, MT-RNR2, IGHG3, CCDC88C, ATP2A3, CENPE, and PCNT) were up-regulated in the R/R samples. Many of these genes have been previously implicated in oncogenesis, such as ERBB3, a member of the epidermal growth receptor family. Importantly, some of these genes have known roles in DLBCL biology, such as CD19, a member of the B-cell receptor complex, and CARD11, a gene in which several oncogenic mutations have been identified in DLBCL as a mediator of NF-KB activation. Gene set enrichment analysis revealed overexpression of immune signatures such as cytokine-cytokine receptor interaction, chemokine receptor-chemokine binding, and the IL-12-STAT4 pathway at diagnosis. At relapse, cell cycle, B-cell receptor, and NOTCH signaling pathways were overexpressed. Interestingly, in a pairwise comparison of methylation between diagnostic and R/R biopsy pairs, there were no differentially methylated probes (FDR&lt;0.05), suggesting no coordinated epigenetic evolution between diagnostic and R/R pairs. For biopsy pairs that had both gene expression and methylation data (5 pairs), we correlated gene expression and methylation values. We found that none of the differentially expressed genes between the diagnostic and R/R biopsies were significantly correlated with methylation status (adjusted p-value&lt;0.05). Conclusions By analyzing paired diagnostic and relapse DLBCL biopsies, we found that at the time of relapse, there are significant transcriptomic changes but no significant epigenetic changes when compared to diagnostic biopsies. Activation of B-cell receptor and NOTCH signaling, as well as the loss of immune signaling at relapse, cannot be attributed to coordinated epigenetic changes in methylation. As the epigenetic profile of the biopsies did not consistently evolve, these data emphasize the need for better understanding of the baseline methylation profiles at the time of diagnosis, as well as acquired somatic mutations that may contribute to the emergence of therapeutic resistance. Future studies are needed to focus on how activation of signaling pathways triggered by genomic alterations can be targeted in relapsed/refractory DLBCL. Disclosures Hsi: Seattle Genetics: Consultancy, Honoraria; Miltenyi: Consultancy, Honoraria; Abbvie: Research Funding; Eli Lilly: Research Funding; CytomX: Consultancy, Honoraria. Hill:Takeda: Research Funding; Genentech: Consultancy, Honoraria, Research Funding; Karyopharm: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria, Research Funding; Pharmacyclics: Consultancy, Honoraria, Research Funding; Beigene: Consultancy, Honoraria, Research Funding; AstraZenica: Consultancy, Honoraria, Research Funding; Kite, a Gilead Company: Consultancy, Honoraria, Research Funding; Novartis: Consultancy, Honoraria; BMS: Consultancy, Honoraria, Research Funding.

scholarly journals Prognostic Implications of Multiple Cytogenetic High-Risk Abnormalities in Patients with Newly Diagnosed Multiple Myeloma

Blood ◽  
2016 ◽  
Vol 128 (22) ◽  
pp. 5615-5615
Author(s):  
Moritz Binder ◽  
S. Vincent Rajkumar ◽  
Rhett P. Ketterling ◽  
Angela Dispenzieri ◽  
Martha Q. Lacy ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Overall Survival ◽  
High Risk ◽  
Board Of Directors ◽  
Research Funding ◽  
Cumulative Effect ◽  
Newly Diagnosed ◽  
Advisory Committees ◽  
Kaplan Meier ◽  
Prognostic Implications

Abstract Background: Cytogenetic evaluation using fluorescence in situ hybridization (FISH) at the time of diagnosis is essential for initial risk stratification in multiple myeloma. The presence of specific cytogenetic abnormalities is known to confer a poor prognosis, less is known about the cumulative effect of multiple cytogenetic high-risk abnormalities. We aimed to evaluate the prognostic implications of the presence of multiple cytogenetic high-risk abnormalities at the time of diagnosis. Methods: We studied 226 patients who were diagnosed with multiple myeloma between July 2004 and July 2014 at Mayo Clinic Rochester, underwent FISH evaluation within six months of diagnosis, and presented with cytogenetic high-risk abnormalities. High-risk cytogenetics were defined as t(4;14), t(14;16), t(14;20), del(17p), or gain(1q). Bone marrow aspirates were evaluated for deletions, monosomies, trisomies, and tetrasomies using chromosome- or centromere-specific FISH probes. IGH rearrangements were evaluated using an IGH break-apart probe and evaluating up to five potential partners (FGFR3, CCND1, CCND3, MAF, and MAFB). Kaplan-Meier overall survival estimates were calculated and the log-rank test was used to compare overall survival in patients with single and multiple cytogenetic high-risk abnormalities. A multivariable-adjusted Cox regression model was used to assess the effect of multiple cytogenetic high-risk abnormalities on overall survival adjusting for age, sex, and Revised International Staging System (R-ISS) stage. P-values below 0.05 were considered statistically significant. Results: The median age at diagnosis was 65 years (32 - 90), 129 (57%) of the patients were male. The median overall survival was 3.5 years (3.1 - 4.9) for the entire cohort (n = 226), 4.0 years (3.3 - 5.1) for those with one cytogenetic high-risk abnormality (n = 182, 80%), and 2.6 years (1.7 - 3.1) for those with two cytogenetic high-risk abnormalities (n = 44, 20%). There were no patients with more than two cytogenetic high-risk abnormalities. Ninety-eight patients (45%) had a high-risk translocation, 77 (35%) had del(17p), 39 (18%) had a high-risk translocation plus del(17p), and 5 (2%) had gain(1q) plus either a high-risk translocation or del(17p). Figure 1 shows the Kaplan-Meier overall survival estimates stratified by the number of cytogenetic high-risk abnormalities (n = 226). The presence of two cytogenetic high-risk abnormalities (compared to one) was of prognostic significance after adjusting for age, sex, and R-ISS stage (HR 2.01, 95% CI 1.27 - 3.19, p = 0.003, n = 205). Conclusions: Approximately one in five patients with newly diagnosed high-risk multiple myeloma presented with two high-risk abnormalities at the time of diagnosis. These patients experienced inferior overall survival suggesting a cumulative effect of multiple cytogenetic high-risk abnormalities. The relatively low number of observed gain(1q) was likely related to the fact that not all patients were evaluated for that abnormality. Therefore the presented hazard ratio represents a conservative effect estimate and may underestimate the true effect. Figure 1 Figure 1. Disclosures Dispenzieri: GSK: Membership on an entity's Board of Directors or advisory committees; Jannsen: Research Funding; Alnylam: Research Funding; Celgene: Research Funding; Takeda: Membership on an entity's Board of Directors or advisory committees, Research Funding; Prothena: Membership on an entity's Board of Directors or advisory committees; pfizer: Research Funding. Kapoor:Takeda: Research Funding; Celgene: Research Funding; Amgen: Research Funding. Kumar:Janssen: Consultancy, Research Funding; BMS: Consultancy; AbbVie: Research Funding; Millennium: Consultancy, Research Funding; Onyx: Consultancy, Research Funding; Celgene: Consultancy, Research Funding; Sanofi: Consultancy, Research Funding; Skyline: Honoraria, Membership on an entity's Board of Directors or advisory committees; Array BioPharma: Consultancy, Research Funding; Noxxon Pharma: Consultancy, Research Funding; Kesios: Consultancy; Glycomimetics: Consultancy.

Genomic Analysis of High Hyperdiploid Acute Lymphoblastic Leukemia and Hyperdiploid Multiple Myeloma Suggests Differential Gene Dosage Effect on Expression and Provide Clues to Preferential Selection of Recurrently Trisomic Chromosomes.

Blood ◽  
2005 ◽  
Vol 106 (11) ◽  
pp. 3006-3006
Author(s):  
Wee-Joo Chng ◽  
Scott Van Wier ◽  
Gregory Ahmann ◽  
Tammy Price-Troska ◽  
Kim Henderson ◽  
...  
Keyword(s):  
Gene Expression ◽  
Signal Transduction ◽  
Multiple Myeloma ◽  
Protein Synthesis ◽  
Differentially Expressed Genes ◽  
Gene Dosage ◽  
Lymphoblastic Leukemia ◽  
Differentially Expressed ◽  
Expression Data ◽  
Gene Dosage Effect

Abstract Hyperdiploid (&gt;48 chromosomes) multiple myeloma (H-MM) and high hyperdiploid (&gt;50 chromosomes) acute lymphoblastic leukemia (H-ALL) are characterized by aneuploidy and multiple recurrent trisomies (chromosome 3,5,7,9,11,15,19 for H-MM and chromosomes X,4,6,10,14,17,18,21 for H-ALL). Little is known about the oncogenic events, consequences of the trisomies and reasons for the different recurrent trisomies. In an attempt to answer these questions, we undertook a combined gene expression and network/pathway analysis approach. Gene expression data was generated using the Affymetrix U133A chip (Affymetrix, Santa Clara, Ca) for 53 H-MM and 37 non-hyperdiploid MM (NH-MM) cases using CD138-enriched plasma-cell RNA. Gene expression data using the same chip for ALL was obtained from previous published data (Ross ME et al Blood2004; 104: 3679–3687). Analysis was performed using Genespring 7 (Agilent Technologies, Palo Alto, CA). By comparing the median expression of all genes on each chromosome between H-MM/H-ALL and their non-hyperdiploid counterparts (NH-MM and NH-ALL) for the 23 chromosomes (excluding Y), one can clearly identify the commonly trisomic chromosomes in H-ALL and H-MM. However, the relationship of gene expression was highly variable for H-MM and NH-MM as compared to H-ALL and NH-ALL which tended to have expression ratios close to 1 for the non-trisomic chromosomes. Sixty-nine percent of the differentially expressed genes generated by ANOVA analysis (p&lt;0.001) in H-ALL were on the commonly trisomic chromosomes and were upregulated whereas the corresponding figure in H-MM is 40%. These similarities and differences probably reflect both an overall gene dosage effect and the different complexities of the karyotypes of H-MM and H-ALL compared to NH-MM and NH-ALL respectively (MM karyotypes are more complex, hence difference between H and NH-MM is greater and less confined to the trisomic chromosomes). We next performed network analysis using a curated web-based software (MetaCore, GeneGo Inc, St Joseph, MI) using the 2 sets of differentially expressed genes. Majority of genes differentially expressed in H-MM are involved in mRNA translation/protein synthesis whereas the genes differentially expressed in H-ALL were mainly involved in signal transduction. Therefore the transcriptional program that characterize the difference between H and NH-MM/ALL seem to recapitulate normal cellular function: protein synthesis in the mature secretory plasma cells and signal transduction in response to cytokines in a differentiating early-B cell. However, due to the concurrent deregulation of many genes on these trisomic chromosomes, these and other cellular programs are deregulated resulting in malignant transformation. We also intersected the 2 lists of differentially expressed genes to find genes that are up- or downregulated in both H-MM and H-ALL relative to the NH tumors. Thirteen genes including interferon response genes (TNFSF10, MX1, ZNF185) and transcription factors like RUNX1 were upregulated, whereas 13 genes including a cancer testis antigen gene (MAGED4) were downregulated in both H-MM and H-ALL. These genes may point to common oncogenic mechanisms.

scholarly journals Construction of a competitive endogenous RNA network and analysis of potential regulatory axis targets in glioblastoma

2021 ◽  
Author(s):  
Kai Yu ◽  
Huan Yang ◽  
Qiao-li Lv ◽  
Li-chong Wang ◽  
Zi-long Tan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Overall Survival ◽  
Differentially Expressed Genes ◽  
Pearson Correlation ◽  
Differentially Expressed ◽  
Migration And Invasion ◽  
Glioblastoma Cells ◽  
Network Chain ◽  
Cerna Network ◽  
Potential Marker

Abstract Background: Glioblastoma is the most common primary malignant brain tumor. Because of the limited understanding of its pathogenesis, the prognosis of glioblastoma remains poor. This study was conducted to explore potential competing endogenous RNA (ceRNA) network chains and biomarkers in glioblastoma by performing integrated bioinformatics analysis.Methods: Transcriptome expression data from The Cancer Genome Atlas database and Gene Expression Omnibus were analyzed to identify differentially expressed genes between glioblastoma and normal tissues. Biological pathways potentially associated with the differentially expressed genes were explored by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analysis, and a protein-protein interaction network was established using the STRING database and Cytoscape. Survival analysis using Gene Expression Profiling Interactive Analysis was based on the Kaplan–Meier curve method. A ceRNA network chain was established using the intersection method to align data from four databases (miRTarBase, miRcode, TargetScan, and lncBace2.0), and expression differences and correlations were verified by quantitative reverse-transcription polymerase chain reaction analysis and by determining the Pearson correlation coefficient. Additionally, an MTS assay and the wound-healing and transwell assays were performed to evaluate the effects of complement C1s (C1S) on the viability and migration and invasion abilities of glioblastoma cells, respectively.Results: We detected 2842 differentially expressed (DE) mRNAs, 2577 DE long non-coding RNAs (lncRNAs), and 309 DE microRNAs (miRNAs) that were dysregulated in glioblastoma. The final ceRNA network consisted of six specific lncRNAs, four miRNAs, and four mRNAs. Among them, four DE mRNAs and one DE lncRNA were correlated with overall survival (p < 0.05). C1S was significantly correlated with overall survival (p = 0.015). In functional assays, knockdown of C1S inhibited the proliferation and invasion of glioblastoma cell lines.Conclusions: We established four ceRNA networks that may influence the occurrence and development of glioblastoma. Among them, the MIR155HG/has-miR-129-5p/C1S axis is a potential marker and therapeutic target for glioblastoma. Knockdown of C1S inhibited the proliferation, migration, and invasion of glioblastoma cells. These findings clarify the role of the ceRNA regulatory network in glioblastoma and provide a foundation for further research.

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