TP53 Gene Expression, Correlated with 17p13 Deletion, Is a Significant and Independent Adverse Prognostic Factor in Multiple Myeloma Treated with High-Dose Therapy and Auto-Transplants.

Blood ◽  
2006 ◽  
Vol 108 (11) ◽  
pp. 3394-3394
Author(s):  
Wei Xiong ◽  
Fenghuang Zhan ◽  
Yongsheng Huang ◽  
Bart Barlogie ◽  
John D. Shaughnessy
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Sequence Analysis ◽  
Copy Number ◽  
Tp53 Gene ◽  
Gene Copy ◽  
High Dose ◽  
Newly Diagnosed ◽  
Prognostic Variable ◽  
Relapsed Disease

Abstract Deletion of chromosome 17p13 is a poor risk feature in MM, presumably resulting from a loss-of-hetrozygosity of the TP53 locus. However, details on the role of TP53 in the pathogenesis of MM and its relevance as a prognostic variable remain uncertain. We determined TP53 mRNA expression, DNA sequence integrity and copy number in newly diagnosed and relapsed disease and correlated these features with disease progression and outcome. Among 351 newly diagnosed cases treated on TT2, a randomized trial of high-dose chemotherapy and autotransplants +/− thalidomide. TP53 gene expression, as determined by Affymetrix microarray of CD138-selected cells, varied from a high of 5,241 to a low of 10 (mean 1,460). TP53 expression lower than 727, present in 10% of tumors, was associated with shorter event-free survival (EFS: P=0.0012) and overall survival (OS: P=0.0006) with a median follow-up of 40 months. Short EFS (P<0.0538) and OS (P<0.0384) was also associated with a low TP53 expression (< 727) in 10% of 214 cases treated on TT3 followed a median of 16 months. On univariate analyses, low TP53 was linked to high CRP (>4.1 mg/L), creatinine (>221 umol/L), and LDH (>191 IU/L), Amp1q21, del13, MRI lesions (>3), and high-risk molecular groups (PR, MS, and MF) (P < .05) in the TT2 cohort. There was no significant difference in cytogenetic abnormalities, B2M (>4 mg/L), albumin (<3.5 g/dl), or marrow plasmacytosis (>33%). On multivariate regression analysis, low TP53 expression was an independent variable predicting shorter survival (EFS: P=0.044; OS: P=0.019), even in the context of high-risk molecular entities and ISS. We next used interphase FISH to correlate TP53 gene copy number with expression in randomly selected cases from the TT2 cohort. 17p13 deletion was observed in 88% (27% with bi-allelic deletion) of 17 cases from the group of 35 (10% of total) with the lowest TP53 expression, while deletion was present in 36% in 22 cases with low-, 12% in 17 cases with mid-level, and 6% in 17 samples with high-expression of TP53 (P<0.001). Surprisingly, there was no correlation between TP53 gene expression levels and expression of 121 known TP53 targets genes in newly diagnosed and relapsed disease, yet a strong correlation was observed in myeloma cell lines. Sequence analysis of TP53 revealed no mutations in 24 newly diagnosed cases, whereas mutations were seen in exon 7, 8 and 9 in 5 of 20 relapsed samples (P=0.014). Analysis of TP53 expression in 90 relapses from the TT2 cohort revealed that 18% had TP53 at or below the high-risk level of 727, representing a near doubling of the percentage seen in newly diagnosed disease (P=0.019). Comparison of TP53 expression in 50 paired baseline-relapse samples from the TT2 cohort revealed a near significant trend for a reduction across 32 relapses from the no thalidomide arm (P=0.08) and a significant increase in expression across 18 relapses on the thalidomide arm (P=0.0035). Sequence analysis of TP53 in seven paired baseline and relapse samples from cases treated with thalidomide revealed no mutations were observed. A more comprehensive sequence and copy number analysis on paired samples from both arms is pending. Together these data demonstrate that low TP53 expression is strongly correlated with 17p13 deletion and is a significant and independent prognostic variable, independent of changes in TP53 target genes.

scholarly journals The mTOR Component, Rictor, Is Regulated By the Microenvironment to Control Dormancy and Proliferative States in Myeloma Cells

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 4412-4412
Author(s):  
Syed J. Mehdi ◽  
Sarah K Johnson ◽  
Tarun K. Garg ◽  
Cody Ashby ◽  
Maurizio Zangari ◽  
...  
Keyword(s):  
Gene Expression ◽  
Growth Factors ◽  
High Risk ◽  
Copy Number ◽  
Annexin V ◽  
Newly Diagnosed ◽  
Double Immunostaining ◽  
Proliferating Cells ◽  
Number Variation ◽  
Pathway Analyses

Introduction: Multiple myeloma (MM) cell dormancy and proliferative states, particularly in standard risk patients, are regulated by the BM niches and factors they secrete. Mesenchymal stem cells (MSCs) and their differentiated progeny are key microenvironmental components in MM. We established a reproducible experimental system in which normal MSCs were co-cultured with BM-dependent MM lines for 5 days, at which point MM cells were removed through a trypsinization and replating process (primed MSCs). MSCs cultured alone were similarly processed (unprimed MSCs). Conditioned media (CM) from primed MSCs, but not unprimed MSCs, consistently promoted the growth of primary MM cells from 12 newly diagnosed patients with low-risk MM and 6 patients with high-risk MM (p<0.0003). We hypothesized that primed MSCs represent a high-risk microenvironment akin to growth of MM within focal lesions. The aim of the study was to identify and study microenvironmental pathways that mediate dormancy and proliferative states in MM cells. Methods: CD138+ MM cells from 27 newly diagnosed patients were used for growth experiments and molecular characterization. BM-dependent MM lines were established through passaging MM cells from patients with advanced MM in the SCID-rab model. Unprimed and primed MSCs were molecularly characterized by global gene expression profiling (GEP) and growth factor content in CM was quantified using protein arrays. Proliferation of MSCs was determined by Ki67 immunostaining and cellular senescence by beta-galactosidase (SA-beta-Gal). MM growth was assessed after culturing primary MM cells with 50% CM from unprimed MSCs, primed MSCs or fresh media for 5 days. Cell survival and proliferation were determined by MTT assay and by detection of annexin V- and Ki67-positive MM cells by flow cytometry. Ultra low depth WGS was performed to assess copy number variation. MM cells were molecularly characterized by GEP, followed by pathway analyses using Ingenuity. Rictor activity was detected in MM cells by Western Blot and double immunostaining for Ki67 and Rictor. Adenoviral-based vectors and siRNA were used for transient RICTOR overexpression and gene expression silencing, respectively. Results: Fewer Ki67+ proliferating cells and increased numbers of SA-beta-Gal senescent cells were detected in primed MSCs compared to unprimed MSCs. Primed MSCs expressed a higher level of secreted factors such as CCL5, FGF1, IL6 and IL1B, and reduced expression of FGF7, CXCL12 (SDF1) and IGFBP2 compared to unprimed MSCs. CM of primed MSCs had a higher level of IL6, FGF1 and a lower level of IGFBP2 than CM of unprimed MSCs. There was no significant difference in the proportion of annexin V+ apoptotic MM cells cultured in CM from unprimed and primed MSCs, whereas the proportion of Ki67+ proliferating cells was 5 fold higher in MM cells treated with primed MSCs CM (p<0.03). The top genes overexpressed in MM cells treated with primed MSCs CM versus unprimed MSCs CM were related to proliferation, whereas underexpressed genes were related to dormancy including BCL2, RICTOR, and CXCR4. Pathway analyses identified oxidative phosphorylation with mitochondrial dysfunction, cell cycle, mitosis and p53 as the most significantly altered pathways in MM cells treated with primed MSCs CM. WGS revealed similar copy number variation in MM cells treated with unprimed and primed CM, suggesting other mechanisms produced the observed gene expression changes. mTOR signaling is controlled by major MM growth factors such as IL6 and IGF1, therefore we investigated the role of the mTOR2 component, Rictor, in MM growth. Blocking IL6 or IGF1 with the use of neutralizing antibodies against their receptors inhibited the stimulatory effect of primed MSCs CM on MM cell growth (p<0.01). Western blot analysis and immunostaining revealed a lower level of Rictor in MM cells treated with primed MSCs CM than unprimed MSCs CM. Furthermore, Ki67+ proliferating MM cells were negative for Rictor as assessed by double immunostaining. Transient overexpression of RICTOR inhibited the growth of 3 MM cell lines by 2-fold (p<0.001), whereas RICTOR siRNA increased the growth of primary MM cells treated with unprimed MSCs CM by 1.8-fold (n=3, p<0.03). Conclusions: Primed MSCs possess a senescence phenotype but produce MM growth factors capable of shifting MM cell status from a dormant to proliferative state through downregulation of Rictor expression in MM cells. Disclosures Walker: Celgene: Research Funding. van Rhee:Takeda: Consultancy; Castleman Disease Collaborative Network: Consultancy; EUSA: Consultancy; Adicet Bio: Consultancy; Kite Pharma: Consultancy; Karyopharm Therapeutics: Consultancy; Sanofi Genzyme: Consultancy.

A Gene Expression-Based Risk Stratification Model Developed in Newly Diagnosed Multiple Myeloma Treated with High Dose Therapy Is Predictive of Outcome in Relapsed Disease Treated with Single Agent Bortezomib.

Blood ◽  
2007 ◽  
Vol 110 (11) ◽  
pp. 656-656 ◽  
Author(s):  
Fenghaung Zhan ◽  
Barb Bryant ◽  
Bart Barlogie ◽  
George Mulligan ◽  
John D. Shaughnessy
Keyword(s):  
High Risk ◽  
Risk Model ◽  
Single Agent ◽  
Risk Groups ◽  
Low Risk ◽  
High Dose ◽  
Newly Diagnosed ◽  
Gene Model ◽  
High Dose Therapy ◽  
Relapsed Disease

Abstract Using data derived from the U133Plus2.0 microarray (U2), we recently constructed a 17-gene model predictive of high-risk multiple myeloma (MM). In the model, 13% of newly diagnosed cases were considered to have high-risk MM with 24 month overall survival estimates of 50% and 90% in the high- and low-risk groups, respectively (p<0.0001). Although validated in a separate cohort of newly diagnosed cases also receiving high dose therapy, it is not known whether this model has broader utility. To address this issue we applied the model to a dataset from a pharmacogenomic effort as part of a multi-center phase III trial testing the efficacy of the proteasome inhibitor bortezomib compared to dexamethasone. For purposes of evaluating the robustness of our model, this dataset is particularly useful in that it differs from the UAMS dataset in several important areas, such as relapsed vs. newly diagnosed disease, single agent bortezomib or dexamethasone vs. multi-agent induction therapy and high-dose melphalan-based tandem transplants, multiple centers vs. single center, delayed processing of bone marrow aspirates vs. immediate processing, negative vs. positive selection of plasma cells, and microarray platform U133A/B (UA) vs. U2 in the Millennium and UAMS datasets, respectively. A total of 144 of the first 351 UAMS cases applied to the U2 had also been applied to UA and were analyzed together with the 188 Millennium samples. Of the 17 genes on U2 we were able to find exact matches for 16 genes on UA. We applied the UA signal intensities of the 16 genes and the exact multivariate stepwise discriminant analysis (MSDA) model used to derive the 17-gene model using U2 data to the 144 UAMS cases. Risk scores for the 144 UAMS cases using the 17-gene U2- and 16-gene UA-derived models were calculated and a strong correlation observed (r=0.89; P<0.001). Using a score of greater than 1.6 as the high-risk cut-point with both models, a confusion matrix revealed a 96.5% agreement between high- and low-risk annotations among the 144 cases. Kaplan-Meier survival analysis of high- and low-risk groups defined by the 17- and 16-gene models revealed similar survival differences between high- and low-risk MM (U2: P=0.0046, HR=2.49; UA: P=0.0026; HR=2.58). These data suggests that the risk model is highly stable across these platforms. We then applied the 16-gene model to 188 cases of relapsed disease treated with bortezomib. Using the same discriminant score cut-off of 1.6 on the Millennium data, the 16-gene model defined 17.6% of cases as high-risk and this subset had significantly shorter overall survival times (P<0.0001; HR=2.93). The estimated 24-month survival was 9% in the high-risk vs. 40% in the low-risk cohort. The model also identified high-risk disease in a dexamethasone treated cohort (P<0.0001; HR=3.01). These data suggest that the 17-gene high-risk model is robust and not confounded by variables distinguishing these two datasets. These data also reveal a common molecular signature of high-risk MM in patients with newly diagnosed and relapsed disease pointing to a potential common molecular mechanism of drug resistance in MM that is revealed in this signature. We are currently developing and validating the 17-gene model using technology that quantifies tumor RNA directly in purified cells.

scholarly journals Location of the t(4;14) Translocation Breakpoint Identifies a Subset of Newly-Diagnosed Multiple Myeloma Patients with Poor Prognosis

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 2681-2681
Author(s):  
Nicholas Stong ◽  
Maria Ortiz ◽  
Fadi Towfic ◽  
William Pierceall ◽  
Erin Flynt ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Copy Number ◽  
Fusion Transcript ◽  
Newly Diagnosed ◽  
Rna Seq ◽  
Publicly Traded ◽  
Genomic Dataset ◽  
Fusion Transcripts ◽  
Breakpoint Location

Abstract Introduction: The recombination of chromosomes 4 and 14 (t(4;14)) is a primary, predominantly clonal event in newly diagnosed multiple myeloma (ndMM) that is present in ~15% of patients. The translocation results in enhancer regions from the immunoglobulin heavy chain locus upregulating the expression of NSD2 and FGFR3 genes implicated in the disease biology of this subset of MM patients (Chesi et al. Blood. 1998, Keats et al, Leuk Lymph. 2006). The presence of t(4;14) translocation is a considered a biomarker of aggressive disease and is part of the Revised International Staging System (R-ISS) for clinical risk stratification. However, historically only ~40% of t(4;14) patients are high-risk based on the GEP70 gene expression signature. (Weinhold et al. Leukemia. 2016) Our previous analysis of a large cohort of ndMM patients described the genomic features of t(4;14) vs ndMM overall population demonstrating that only ~25% of t(4;14) patients died within 24 months of diagnosis and described biomarkers in this high-risk subset. This analysis identified both known and novel aberrations in ndMM, including some that were associated with high-risk t(4;14) (Ortiz et al Blood. 2019; 134 (Suppl_1):366). In this updated analysis, we provide a more robust analysis of the t(4;14) dataset and demonstrate the prognostic value of the NSD2 breakpoint location. Methods: We generated a large genomic dataset from t(4;14) ndMM patients with whole genome sequencing (WGS) and RNA-seq from a TOUL dataset (t(4;14) N=114) patients treated in routine practice), the IFM2009 trial (N=19), and the Myeloma Genome Project (MGP) (N=34) for discovery and validation. Gene expression, copy number aberration, single nucleotide variant and translocations were derived from RNAseq and WGS profiling of biopsies from patients aged less than 75 years who received transplant, and integrated with clinical information (including age, OS). Cytogenetic assessments from WGS were made by MANTA and used to identify translocation DNA breakpoint location. Results: In all datasets, three DNA breakpoint locations were identified, and based on their position with respect to the NSD2 gene named "no-disruption" (upstream of NSD2 gene), "early-disruption" (in the 5' UTR of NSD2 gene) and "late-disruption" (in the coding region of NSD2 gene). Using paired RNA-seq data, we identified IGH-NSD2 RNA fusion transcripts relative to the breakpoints that corresponded with previously described NSD2 isoforms. "No-disruption" and "early-disruption" breakpoints predominantly produced a fusion transcript (MB4-1) that retained the full coding sequence of the gene, while the "late-disruption" produced truncated fusion transcripts (MB4-2/3). We conducted survival analysis in our datasets based on both DNA breakpoint location and RNA fusion transcripts. This analysis demonstrated a significant difference in outcome between the patient samples with "no-disruption" and the "late-disruption" breakpoints that associated with good and poor OS, respectively (OS pval &lt; 3e-4) in the discovery TOUL dataset. Patients with "late-disruption" had a median OS of 28.64 mo vs 59.18 mo for "early disruption" and 82.26 mo for those with "no disruption" (Figure). This association was replicated in an independent dataset (MGP N=33, replication pval&lt;4.3e-5). The mOS difference of patients based on which fusion transcript they express is less than the difference based on breakpoint (mOS MB4-1 = 47.38 mo. vs. MB4-2/3 = 60.89 mo.). These analyses demonstrate that the breakpoint location has a stronger association with outcome than fusion transcript expression. Conclusion: From a large genomic dataset, we were able to discover and validate a clear association between the translocation breakpoints and survival outcome in t(4:14) ndMM patients. While prospective validation is needed before clinical application of our finding, molecular identification of high-risk t(4;14) patients using DNA breakpoint location may enable proper risk classification for this patient group at diagnosis, and would provide improved opportunities for risk-adjusted therapy and identification of a therapeutic target for this high-risk subpopulation. Ongoing work on mutations, copy number, and differential gene expression analyses between translocation breakpoint sub-groups and will be presented. Figure 1 Figure 1. Disclosures Stong: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Ortiz: Bristol Myers Squibb: Current Employment. Towfic: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Pierceall: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company. Flynt: Bristol Myers Squibb: Current Employment. Thakurta: Bristol Myers Squibb: Current Employment, Current equity holder in publicly-traded company, Patents & Royalties.

Integration of DNA Copy Number and Gene Expression Alterations Reveal Novel Insights into the Molecular Pathogenesis and Prognosis of Multiple Myeloma

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 250-250 ◽  
Author(s):  
Yiming Zhou ◽  
Bart Barlogie ◽  
Damir Herman ◽  
Owen Stephens ◽  
Erming Tian ◽  
...  
Keyword(s):  
Gene Expression ◽  
Multiple Myeloma ◽  
High Risk ◽  
Copy Number ◽  
Risk Model ◽  
Proliferation Index ◽  
High Dose ◽  
Copy Number Alterations ◽  
Expression Of Genes ◽  
Highly Correlated

Abstract Multiple myeloma (MM) is characterized by a profound genomic instability and a highly variable clinical course. To comprehensively analyze the effects of copy number alterations on gene activity and prognosis, we applied novel bioinformatics and computational approaches to integrate high-resolution aCGH data (Agilent 244K array) and gene expression profiling data (Affymetrix U133Plus2.0 array) from CD138-selected plasma cells from 92 newly diagnosed MM treated with high-dose therapy and stem cell transplantation. We identified what we have termed the “atom region” (AR). ARs are found throughout the genome and define recurrent breakpoint boundaries of sub-chromosomal loss or gain. Genes coding for miRNAs were significantly enriched in regions of the genome defined by ARs. Although many AR-related breakpoints lie in intergenic regions, and thus capture whole genes, a substantial number were identified within genes, making these genes strong candidate disease genes. We found that gain of 1q and loss of 1p represent the most significant copy number alterations linked to early disease-related death. Importantly, 1q gains and 1p loss were significantly linked to a recently described 70-gene expression model of high-risk disease predominated by increased expression of genes mapping to 1q and reduced expression of genes mapping to 1p (1). Gain of 1q and loss of 1p were also highly correlated with a gene-expression-based proliferation index widely used across many tumor types. We provide evidence that gain of 8q24 was also highly correlated with the 70-gene high-risk score, but not the proliferation index. 8q24 gains and survival were linked to elevated expression of EIF2C2/AGO2, a master regulator of microRNA expression and maturation and an overexpressed gene previously identified in our 70-gene high-risk model (1). Interestingly, although the expression of MYC, which also maps to 8q24, was related to copy number changes, its expression was not related to survival. Given the importance of AGO2 in B-cell development (2), and miRNAs in cancer, detailed functional studies of the potential role of AGO2 in MM are underway.

scholarly journals MUKnine OPTIMUM protocol: a screening study to identify high-risk patients with multiple myeloma suitable for novel treatment approaches combined with a phase II study evaluating optimised combination of biological therapy in newly diagnosed high-risk multiple myeloma and plasma cell leukaemia

BMJ Open ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. e046225
Author(s):  
Sarah Brown ◽  
Debbie Sherratt ◽  
Samantha Hinsley ◽  
Louise Flanagan ◽  
Sadie Roberts ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
High Risk ◽  
Plasma Cell ◽  
Phase Ii ◽  
Whole Body ◽  
Cell Leukaemia ◽  
High Dose ◽  
Newly Diagnosed ◽  
Genetic Changes ◽  
Novel Treatment

IntroductionMultiple myeloma (MM) is a plasma cell tumour with over 5800 new cases each year in the UK. The introduction of biological therapies has improved outcomes for the majority of patients with MM, but in approximately 20% of patients the tumour is characterised by genetic changes which confer a significantly poorer prognosis, generally termed high-risk (HR) MM. It is important to diagnose these genetic changes early and identify more effective first-line treatment options for these patients.Methods and analysisThe Myeloma UK nine OPTIMUM trial (MUKnine) evaluates novel treatment strategies for patients with HRMM. Patients with suspected or newly diagnosed MM, fit for intensive therapy, are offered participation in a tumour genetic screening protocol (MUKnine a), with primary endpoint proportion of patients with molecular screening performed within 8 weeks. Patients identified as molecularly HR are invited into the phase II, single-arm, multicentre trial (MUKnine b) investigating an intensive treatment schedule comprising bortezomib, lenalidomide, daratumumab, low-dose cyclophosphamide and dexamethasone, with single high-dose melphalan and autologous stem cell transplantation (ASCT) followed by combination consolidation and maintenance therapy. MUKnine b primary endpoints are minimal residual disease (MRD) at day 100 post-ASCT and progression-free survival. Secondary endpoints include response, safety and quality of life. The trial uses a Bayesian decision rule to determine if this treatment strategy is sufficiently active for further study. Patients identified as not having HR disease receive standard treatment and are followed up in a cohort study. Exploratory studies include longitudinal whole-body diffusion-weighted MRI for imaging MRD testing.Ethics and disseminationEthics approval London South East Research Ethics Committee (Ref: 17/LO/0022, 17/LO/0023). Results of studies will be submitted for publication in a peer-reviewed journal.Trial registration numberISRCTN16847817, May 2017; Pre-results.

scholarly journals Insulin-like Growth Factor Receptor 1 (IGF1R) Gene Copy Number Is Associated With Survival in Operable Non–Small-Cell Lung Cancer: A Comparison Between IGF1R Fluorescent In Situ Hybridization, Protein Expression, and mRNA Expression

2010 ◽  
Vol 28 (13) ◽  
pp. 2174-2180 ◽  
Author(s):  
Rafal Dziadziuszko ◽  
Daniel T. Merrick ◽  
Samir E. Witta ◽  
Adelita D. Mendoza ◽  
Barbara Szostakiewicz ◽  
...  
Keyword(s):  
Gene Expression ◽  
Growth Factor ◽  
Protein Expression ◽  
Squamous Cell ◽  
Copy Number ◽  
Gene Copy Number ◽  
Growth Factor Receptor ◽  
Gene Copy ◽  
Cell Versus

PurposeThe purpose of this study was to characterize insulin-like growth factor-1 receptor (IGF1R) protein expression, mRNA expression, and gene copy number in surgically resected non–small-cell lung cancers (NSCLC) in relation to epidermal growth factor receptor (EGFR) protein expression, patient characteristics, and prognosis.Patients and MethodsOne hundred eighty-nine patients with NSCLC who underwent curative pulmonary resection were studied (median follow-up, 5.3 years). IGF1R protein expression was evaluated by immunohistochemistry (IHC) with two anti-IGF1R antibodies (n = 179). EGFR protein expression was assessed with PharmDx kit. IGF1R gene expression was evaluated using quantitative reverse transcription polymerase chain reaction (qRT-PCR) from 114 corresponding fresh-frozen samples. IGF1R gene copy number was assessed by fluorescent in situ hybridization using customized probes (n = 181).ResultsIGF1R IHC score was higher in squamous cell carcinomas versus other histologies (P < .001) and associated with stage (P = .03) but not survival (P = .46). IGF1R and EGFR protein expression showed significant correlation (r = 0.30; P < .001). IGF1R gene expression by qRT-PCR was higher in squamous cell versus other histologies (P = .006) and did not associate with other clinical features nor survival (P = .73). Employing criteria previously established for EGFR copy number, patients with IGF1R amplification/high polysomy (n = 48; 27%) had 3-year survival of 58%, patients with low polysomy (n = 87; 48%) had 3-year survival of 47% and patients with trisomy/disomy (n = 46; 25%) had 3-year survival of 35%, respectively (P = .024). Prognostic value of high IGF1R gene copy number was confirmed in multivariate analysis.ConclusionIGF1R protein expression is higher in squamous cell versus other histologies and correlates with EGFR expression. IGF1R protein and gene expression does not associate with survival, whereas high IGF1R gene copy number harbors positive prognostic value.

scholarly journals Whole-genome optical mapping of bone-marrow myeloma cells reveals association of extramedullary multiple myeloma with chromosome 1 abnormalities

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Eva Kriegova ◽  
Regina Fillerova ◽  
Jiri Minarik ◽  
Jakub Savara ◽  
Jirina Manakova ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Bone Marrow ◽  
High Risk ◽  
Copy Number ◽  
Optical Mapping ◽  
Chromosome 1 ◽  
Gene Copy ◽  
Whole Genome ◽  
Myeloma Cells ◽  
Genomic Architecture

AbstractExtramedullary disease (EMM) represents a rare, aggressive and mostly resistant phenotype of multiple myeloma (MM). EMM is frequently associated with high-risk cytogenetics, but their complex genomic architecture is largely unexplored. We used whole-genome optical mapping (Saphyr, Bionano Genomics) to analyse the genomic architecture of CD138+ cells isolated from bone-marrow aspirates from an unselected cohort of newly diagnosed patients with EMM (n = 4) and intramedullary MM (n = 7). Large intrachromosomal rearrangements (> 5 Mbp) within chromosome 1 were detected in all EMM samples. These rearrangements, predominantly deletions with/without inversions, encompassed hundreds of genes and led to changes in the gene copy number on large regions of chromosome 1. Compared with intramedullary MM, EMM was characterised by more deletions (size range of 500 bp–50 kbp) and fewer interchromosomal translocations, and two EMM samples had copy number loss in the 17p13 region. Widespread genomic heterogeneity and novel aberrations in the high-risk IGH/IGK/IGL, 8q24 and 13q14 regions were detected in individual patients but were not specific to EMM/MM. Our pilot study revealed an association of chromosome 1 abnormalities in bone marrow myeloma cells with extramedullary progression. Optical mapping showed the potential for refining the complex genomic architecture in MM and its phenotypes.

scholarly journals Drug Repositioning Based on the Reversal of Gene Expression Signatures Identifies TOP2A as a Therapeutic Target for Rectal Cancer

Cancers ◽  
2021 ◽  
Vol 13 (21) ◽  
pp. 5492
Author(s):  
Robson Francisco Carvalho ◽  
Luisa Matos do Canto ◽  
Sarah Santiloni Cury ◽  
Torben Frøstrup Hansen ◽  
Lars Henrik Jensen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Rectal Cancer ◽  
Cancer Patients ◽  
Copy Number ◽  
Topoisomerase Ii ◽  
Drug Repositioning ◽  
Gene Copy ◽  
Common Disease ◽  
Topoisomerase Ii Inhibitors ◽  
Gene Expression Signatures

Rectal cancer is a common disease with high mortality rates and limited therapeutic options. Here we combined the gene expression signatures of rectal cancer patients with the reverse drug-induced gene-expression profiles to identify drug repositioning candidates for cancer therapy. Among the predicted repurposable drugs, topoisomerase II inhibitors (doxorubicin, teniposide, idarubicin, mitoxantrone, and epirubicin) presented a high potential to reverse rectal cancer gene expression signatures. We showed that these drugs effectively reduced the growth of colorectal cancer cell lines closely representing rectal cancer signatures. We also found a clear correlation between topoisomerase 2A (TOP2A) gene copy number or expression levels with the sensitivity to topoisomerase II inhibitors. Furthermore, CRISPR-Cas9 and shRNA screenings confirmed that loss-of-function of the TOP2A has the highest efficacy in reducing cellular proliferation. Finally, we observed significant TOP2A copy number gains and increased expression in independent cohorts of rectal cancer patients. These findings can be translated into clinical practice to evaluate TOP2A status for targeted and personalized therapies based on topoisomerase II inhibitors in rectal cancer patients.

Evolutionary Trajectories toward Ceftazidime-Avibactam Resistance in Klebsiella pneumoniae Clinical Isolates

2021 ◽  
Author(s):  
Alessandra Carattoli ◽  
Gabriele Arcari ◽  
Giulia Bibbolino ◽  
Federica Sacco ◽  
Dario Tomolillo ◽  
...  
Keyword(s):  
High Risk ◽  
Klebsiella Pneumoniae ◽  
Copy Number ◽  
Residual Activity ◽  
Gene Copy Number ◽  
Resistance Mechanisms ◽  
University Hospital ◽  
Gene Copy ◽  
Carbapenemase Gene ◽  
Evolutionary Trajectories

From January 2019 to April 2020, 32 KPC-producing, ceftazidime-avibactam (CZA) resistant Klebsiella pneumoniae strains were isolated in a university hospital in Rome, Italy. These strains belonged to the ST512, ST101 and ST307 high-risk clones. Nine different CZA-resistant KPC-3 protein variants were identified, five of them never previously reported (KPC-66 to KPC-70). Among them, KPC-31, KPC-39, KPC-49, KPC-66, KP-68, KPC-69 and KPC-70 showed amino acid substitutions, insertions and deletions in the Ω loop of the protein. KPC-29 has the duplication, while the novel KPC-67 has the triplication of the KDD triplet in the 270-loop of the protein. Genomics performed on contemporary resistant and susceptible clones underlined that those novel mutations emerged in bla KPC-3 genes located on conserved plasmids: in ST512, all bla KPC-3 mutant genes were located in pKpQIL plasmids, while the three novel bla KPC-3 mutants identified in ST101 were on FIIk-FIA(HI1)-R plasmids. Selection also promoted multiplication of the carbapenemase gene copy number by transposition, recombination, and fusion of resident plasmids. When expressed in Escherichia coli recipient cells cloned in the high-copy number pTOPO vector, the Ω loop mutated variants showed CZA-resistant phenotype associated with susceptibility to carbapenems, while KPC variants with insertions in the 270-loop showed residual activity on carbapenems. The investigation of CZA-resistance mechanisms offered the unique opportunity to study vertical, horizontal, and oblique evolutionary trajectories of K. pneumoniae high-risk clones.

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