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 < 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<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.

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.

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.

Selection of RARA-Positive Newly Diagnosed Unfit AML Patients with Elevated RARA Gene Expression Enriches for Features Associated with Primary Resistance to Venetoclax and Clinical Response to SY-1425, a Potent and Selective RARα Agonist, Plus Azacitidine

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 15-16
Author(s):  
Christopher Fiore ◽  
Michael J. Kelly ◽  
Angela Volkert ◽  
Li Zhou ◽  
Kate Madigan ◽  
...  
Keyword(s):  
Gene Expression ◽  
Clinical Trial ◽  
Clinical Response ◽  
Ex Vivo ◽  
Unmet Need ◽  
Clinical Samples ◽  
Newly Diagnosed ◽  
Rna Seq ◽  
Publicly Traded ◽  
Clinical Responses

Introduction: Super-enhancer (SE) mapping in non-APL AML patient (pt) blasts identified RARα as a novel therapeutic target in approximately 30% of pts, who have elevated RARA gene expression. It was observed that the enhancer profile of this novel pt segment, where RARA expression was elevated, overlapped with the profile of mature monocytes (McKeown, 2017). Recently, several reports describe AML with monocytic features associated with resistance to venetoclax (Ven), a BCL-2 inhibitor that has emerged as a standard of care for treatment of pts with newly diagnosed (ND) unfit AML in combination with hypomethylating agents (HMAs) (Zhang, 2018; Kuusanmäki, 2019; Pei, 2020). Approximately one-third of pts do not respond to Ven plus HMAs including azacitidine (Aza) (DiNardo, 2019 and 2020), highlighting a continuing significant unmet need in ND unfit AML. SY-1425, a potent and selective RARα agonist, is in development for non-APL AML in combination with Aza and has demonstrated clinical activity with high rates of complete remission (CR) and deep CRs in RARA-positive (RARA+) ND unfit AML (DeBotton, 2019). Based on the overlap of monocytic features with RARA gene expression, we evaluated clinical samples of pts treated with SY-1425 plus Aza to correlate features of Ven resistance with the RARA biomarker and with clinical response to SY-1425 plus Aza. Methods: RARA gene expression in non-APL AML was evaluated in the TCGA and Beat AML RNA-seq datasets. AUC of cell viability curves were used to evaluate ex vivo sensitivity to compounds, including Ven, in the Beat AML dataset. A monocytic expression signature (MES) was developed using the expression of monocytic and primitive RNA markers in the TCGA dataset to analyze the monocytic phenotype. The MES used a logistic regression model with lasso regularization to distinguish FAB M4/5 (monocytic) from FAB M0/1/2 (primitive) using 10-fold cross-validation with 85% sensitivity and 80% specificity. The MES was then applied to the RNA-seq datasets from Beat AML and AML blasts from ND unfit AML pts in the ongoing SY-1425 plus Aza trial (NCT02807558), in which RARA+ pts were determined by an RT-qPCR based biomarker clinical trial assay (CTA). The MES, RARA expression, and Ven resistance-associated features were compared using Spearman's rho correlation; the association of the MES with the RARA biomarker and with IWG clinical responses in SY-1425 plus Aza treated pts was evaluated. Results: Analysis of RNA-seq in TCGA non-APL AML pts demonstrated higher RARA expression in monocytic AML (FAB M4/M5) than primitive AML (FAB M0/M1/M2) (p&lt;10-7, t-test). TCGA and Beat AML datasets also demonstrated that RARA expression was associated with the MES (rho=0.6 and 0.58), with approximately 70% of RARA-high pts across both databases having a high MES. We further elucidated the relationships of RARA expression, AML monocytic phenotypes, and Ven resistance. Of 121 inhibitors tested ex vivo in primary Beat AML pt samples, Ven was the inhibitor most associated with treatment resistance in RARA+ vs. RARA- samples. Additionally, MES (rho=0.58), RARA (rho=0.48) and BCL-2 expression (rho=-0.49) had similar magnitude of association with ex vivo Ven resistance, with RARA+ samples showing much lower ex vivo sensitivity to Ven than RARA- samples (p=3×10-8). In 12 AML pt samples (Pei, 2020) treated with Ven ± Aza ex vivo, RARA expression was higher in the monocytic leukemia stem cells resistant to Ven ± Aza (p=0.005). To evaluate whether the RARA+ ND unfit AML pts in the ongoing SY-1425 plus Aza clinical trial were enriched for the monocytic phenotype of Ven resistance, RNA-seq was performed on enrolled pt AML blasts. Among 51 treated pts, 86% (19/22) of RARA+ and 83% (24/29) of RARA- pts yielded RNA-seq results. RARA+ pts were more monocytic than RARA- pts, as demonstrated by higher MES (p=0.002), with higher MCL-1 (p=0.001), and lower BCL-2, CD34, and CD117 expression (p=0.03, 8×10-6, 2×10-4, respectively). In pts with the best IWG response of CR/CRi, RARA+ pts (n=10) had higher MES than RARA- pts (n=8) (p=0.008). Conclusion: In ND unfit AML, RARA+ pts, including those with clinical responses to SY-1425 plus Aza, are enriched for monocytic features associated with resistance to Ven. SY-1425 plus Aza shows potential as a novel targeted regimen for the treatment of RARA+ ND unfit AML and warrants further development in this genomically defined subset of AML pts who may be resistant to upfront SOC therapy with Ven. Disclosures Fiore: Syros Pharmaceuticals, Inc.: Current Employment, Current equity holder in publicly-traded company. Kelly:Syros Pharmaceuticals: Current Employment, Current equity holder in publicly-traded company. Volkert:Syros Pharmaceuticals: Current Employment, Current equity holder in publicly-traded company. Zhou:Incyte: Current equity holder in publicly-traded company, Ended employment in the past 24 months; Syros Pharmaceuticals: Current Employment, Current equity holder in publicly-traded company. Madigan:Syros Pharmaceuticals, Inc.: Current Employment, Current equity holder in publicly-traded company. Eaton:Syros Pharmaceuticals, Inc.: Current Employment, Current equity holder in publicly-traded company. Hodgson:Syros Pharmaceuticals, Inc.: Current Employment, Current equity holder in publicly-traded company. Roth:Syros Pharmaceuticals: Current Employment, Current equity holder in publicly-traded company. Kang-Fortner:Syros Pharmaceuticals, Inc.: Current Employment, Current equity holder in publicly-traded company.

Only Concomitant Presence of Cytogenetic Abnormalities in Randomly Sampled Bone Marrow and in MRI-Defined Focal Lesions Imparts Poor Prognosis and Is Associated with Gene Expression Profiling (GEP)-Based High-Risk Myeloma.

Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 1691-1691 ◽  
Author(s):  
Bijay Nair ◽  
Yiming Zhou ◽  
Bart Barlogie ◽  
Jeffrey Sawyer ◽  
Jackie Szymonifka ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bone Marrow ◽  
High Risk ◽  
Expression Profiling ◽  
Poor Prognosis ◽  
Survival Outcomes ◽  
Focal Lesion ◽  
Newly Diagnosed ◽  
Cytogenetic Abnormalities ◽  
Total Therapy

Abstract Cytogenetic abnormalities (CA) can be detected in one-third of newly diagnosed patients with multiple myeloma (MM), reaching virtually universal presence at the terminal disease stage. According to both histopathological and radiological findings, bone marrow growth patterns are either diffusely infiltrative or characterized by focal lesion (FL) growth, around which typically osteolytic bone destruction develops. The detection of CA at diagnosis confers a poor prognosis, and the sustained suppression of CA is critical for long-term survival. Applying MRI examinations in virtually all newly diagnosed patients prior to protocol-based therapy, FL have been detected in ~80% of patients and impart, along with the detection of CA on random bone marrow examination from the posterior iliac crest, shorter event-free and overall survival. Such MRI-FL harbor viable MM cells often with CA, persist in clinical CR for a median of 1–2 years, eventually resolve in 60% and constitute sites of relapse often without M-protein secretion, collectively suggesting an important role of FL in both disease manifestation and progression. We reviewed our data base of 1202 patients enrolled in Total Therapy (TT) protocols for entries of CT-guided fine needle aspirations (FNA) from MRI-defined FL submitted to cytogenetic analysis at baseline and on any occasion prior to first transplant. We identified 320 patients with cytogenetic information on both randomly sampled (RS) and FNA from FL. Congruency between FL and RS examinations was documented in 71% including 53% without detectable CA and 18% with CA in both sites; 14% had RS-CA without FL-CA and 16% had FL-CA without RS-CA. The overall RS-based CA frequency of 31% was identical to the 31% when all 1202 RS prior to transplant were considered. The relative distribution of standard prognostic factors was similar among the 4 RS-FL constellations in terms of B2M (&gt;5.5mg/L), albumin (&lt;3.5g/dL) and creatinine (&gt;=2mg/dL) levels. The frequency of gene expression profiling (GEP)-defined risk (determined on RS) was 15% among196 patients with concurrent RS and FL sampling and thus virtually identical to the 14% incidence among all 620 subjects with RS information only. However, 53% of the subgroup exhibiting both RS-CA and FL-CA had high-risk disease compared to only 6% in the remainder (p &lt; 0.001). Analysis of overall survival according to the 4 RS-FL CA constellations revealed an adverse impact only of the concomitant presence of RS-CA and FL-CA (Figure), whereas the presence of either RS-CA or FL-CA individually was prognosis-neutral, an observation confirmed by multivariate analysis (HR of 3.27, p&lt;0.001). The much higher frequency of GEP-defined high-risk in patients with concomitant RS-CA and FL-CA requires further study, including the examination by GEP of MM-cells procured from both RS and FL. Figure: Survival outcomes of all patients enrolled in combined Total Therapy protocols according to the presence of cytogenetic abnormalities (CA) in paired random (RS) or focal lesion (FL) sites. Comparisons a v d, p&lt;0.0001; b v d, p&lt;0.0001;c v d, p=0.0063 Figure:. Survival outcomes of all patients enrolled in combined Total Therapy protocols according to the presence of cytogenetic abnormalities (CA) in paired random (RS) or focal lesion (FL) sites. . / Comparisons a v d, p&lt;0.0001; b v d, p&lt;0.0001;c v d, p=0.0063

A High-Risk Survival Classifier for Multiple Myeloma

Blood ◽  
2011 ◽  
Vol 118 (21) ◽  
pp. 1800-1800
Author(s):  
Rowan Kuiper ◽  
Annemiek Broyl ◽  
Yvonne de Knegt ◽  
Martin H. van Vliet ◽  
Erik H. van Beers ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Board Of Directors ◽  
Gene Signature ◽  
Hazard Ratio ◽  
High Risk Population ◽  
Newly Diagnosed ◽  
Advisory Committees ◽  
Cytogenetic Aberrations ◽  
Standard Risk

Abstract Abstract 1800 Introduction: Survival of patients with newly diagnosed multiple myeloma (MM) is highly variable and currently used clinical prognostic markers such as the international staging system (ISS) and cytogenetic markers are insufficiently adequate for defining individual patient prognosis. We established a prognostic signature based on gene expression profiling. Methods: The signature was generated using a training set of 290 newly diagnosed MM patients included in the multicenter, prospective open-label randomized phase 3 HOVON65/GMMG-HD4 trial. Gene expression profiles, obtained from purified plasma cells, were generated using the Affymetrix GeneChip® Human Genome U133 Plus 2.0 platform (GSE19784; Broyl et al.,Blood 2010; 14:2543–2553). The model predictive for survival was built by supervised principal component analysis (Bair et al., J. Amer. Statistical Assoc. 2006;101:119–37) and further optimized by simulated annealing. The generated survival signature was compared to six previously reported MM gene expression signatures (i.e. UAMS-70, UAMS-17 (Shaughnessy et al., Blood. 2007;109:2276–84), gene expression-based proliferation index (GPI, Hose et al., Haematol. 2010; 96: 87–95), MRC-IX-6 gene (Dickens et al., Clin. Cancer Res. 2010;16:1856–1864), Millennium (Mulligan et al., Blood 2007; 109:3177–3188) and IFM (Decaux et al., J. Clin. Oncol. 2008; 26:4798–4805). Results: A signature of 92 probe sets (EMC-92-gene signature) was highly discriminative for high-risk MM patients, defined as overall survival (OS) < 2 yr (21.7%) vs. standard-risk MM. This performance was confirmed in independent validation datasets of newly diagnosed MM patients (UAMS-TT2, n=351, GSE2658; MRC-IX, n=247, GSE15695) and relapse MM patients (APEX, n=264, GSE9782). In the UAMS-TT2 dataset, a high-risk population of 19.1% was identified which had a hazard-ratio of 3.52 (P = 2.5 × 10−8). In the MRC-IX study, 20.2% of patients were identified as high risk with a hazard-ratio of 2·38 (P = 3·6 × 10−6; Figure 1a) The high-risk signature was able to identify patients with significantly shorter survival in both the transplant-eligible and non-transplant-eligible patients included in the MRC-IX study. In non-transplant-eligible patients, 23.8% high risk patients were identified with a hazard-ratio of 2.38 (P = 4.3 × 10−4), whereas 17.5% of transplant-eligible patients were high-risk with a hazard-ratio of 2.54 (P = 1.5 × 10−3). The difference between survival in high-risk and standard risk was not restricted to newly diagnosed patients, as 15.9% of patients included in the APEX relapse study were designated high-risk with a hazard-ratio of 3·14 (P = 5·3 × 10−9; Figure 1b). In all sets the signature gave consistent and significant results and had good performance in comparison to other published high-risk gene signatures (Figure 2). In a pair-wise comparison to other high-risk gene signatures the EMC-92-gene showed to be among the top performing signatures and independent of all other signatures. In multivariate analyses, the EMC-92-gene signature proved an independent and superior predictor against clinical and cytogenetic variables such as the ISS and unfavourable cytogenetic aberrations including del(17p). Using the independent MRC-IX set, poor prognostic cytogenetic aberrations 1q gain, del(17p), t(4;14), t(14;16), t(14;20) and del(13q), were enriched in high-risk patients, whereas the frequency of standard risk cytogenetic aberrations such as t(11;14) was lower in the high-risk populations. Although enriched in the high-risk population, still more than half of patients in the standard risk group showed one or more poor prognostic cytogenetic markers Conclusions: We developed a high-risk signature highly discriminative for patients with high-risk versus standard-risk MM, irrespective of treatment regime, age and relapse setting. Use of this signature in the clinical setting may lead to a more informed treatment choice and potentially better outcome for the patient. Disclosures: van Vliet: Skyline Diagnostics: Employment. van Beers:Skyline Diagnostics: Employment, Patents & Royalties. Mulligan:Millennium Pharmaceuticals, Inc.: Employment. Morgan:Millennium Pharmaceuticals, Inc: Honoraria. Gregory:Celgene: Honoraria. Goldschmidt:Johnson& Johnson: Membership on an entity's Board of Directors or advisory committees. Lokhorst:Genmab: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees. Sonneveld:Janssen: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Skyline Diagnostics: Membership on an entity's Board of Directors or advisory committees.

Impact of therapy on gene expression in high-risk prostate cancer (PCA) treated with neoadjuvant docetaxel and androgen deprivation therapy.

2016 ◽  
Vol 34 (2_suppl) ◽  
pp. 8-8
Author(s):  
Himisha Beltran ◽  
Alexander Wyatt ◽  
Edmund Chedgy ◽  
Ladan Fazli ◽  
Andrea Sboner ◽  
...  
Keyword(s):  
Gene Expression ◽  
High Risk ◽  
Hormone Receptors ◽  
Dna Analysis ◽  
Rna Extraction ◽  
Post Treatment ◽  
Rna Seq ◽  
Sequencing Data ◽  
Quantitative Expression ◽  
High Risk Prostate Cancer

8 Background: Molecular analyses of neoadjuvant post-treatment radical prostatectomy (RP) specimens has been challenging as often times only microscopic foci remain present at time of RP precluding RNA-seq. DNA analysis alone in the absence of expression may be suboptimal in elucidating complex mechanisms of resistance and/or prognostic risk stratification. We therefore set out to develop an assay that could quantify mRNA expression in treated and untreated PCA using formalin fixed paraffin embedded (FFPE) tissues. Methods: We evaluated 40 untreated and post-treatment FFPE specimens as well as patient-matched pre-treated needle biopsies and baseline clinical data from patients enrolled on CALGB 90203: a randomized phase 3 trial comparing noeadjuvant docetaxel and ADT followed by RP vs RP alone for men with high risk localized PCA. High-density tumor areas were selected for RNA extraction (min 50ng RNA). We used NanoString nCounter to quantify gene expression of a custom panel of 75 genes including AR and androgen regulated, neural/neuroendocrine (NE), EMT, cell cycle, hormone receptors, TMPRSS-ERG, ARv7 splice variant, and housekeeper genes. mRNA data was integrated with matched whole exome sequencing data. Frozen specimens and RNA-Seq (n = 7) were used for QC and comparative analysis. Results: Quantitative expression using Nanostring showed high correlation with RNA-seq of patient-matched frozen tissue (Spearman coefficient 0.9). There was significant upregulation of AR and the ARv7 expression following treatment, as well as a subset of NE and EMT genes; three high chromogranin A outlier cases were identified in the treatment arm. There was an overall higher AR score in treated cases (based on expression of 30 AR signaling genes) compared to untreated, along the spectrum of CRPC. Conclusions: These data support the feasibility of quantifying gene expression in neoadjuvant-treated PCA cases with limited FFPE tissue requirement. Extensive characterization of AR status and NE/EMT genes identifies molecular outliers that can arise post-treatment and provides new insight into the heterogeneity of treatment response and potential early markers of resistance. Clinical trial information: NCT00430183.

Prognostic relevance of CD4+ T-cells in the microenvironment of newly diagnosed follicular lymphoma (FL) patients is independent of the tumor gene expression profile.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 8052-8052
Author(s):  
Patrizia Mondello ◽  
Angelo Fama ◽  
Melissa C. Larson ◽  
Andew L. Feldman ◽  
Zhi-Zhang J Yang ◽  
...  
Keyword(s):  
Gene Expression ◽  
T Cell ◽  
High Risk ◽  
Follicular Lymphoma ◽  
Prognostic Score ◽  
Cd4 T Cell ◽  
Newly Diagnosed ◽  
Early Failure ◽  
Tumor Gene Expression ◽  
Tumor Gene

8052 Background: A significant proportion of patients with FL experience an early relapse and a subsequent poor outcome. While several prognostic indices have been developed, none were designed to predict early failure. Recently, we established that lack of intrafollicular CD4+ T-cell expression predicted risk of early failure, and integrating this microenvironment biomarker with the Follicular Lymphoma International Prognostic Index, termed BioFLIPI, further improved identification of FL patients at risk of early failure ( Blood 2019;134(suppl1):121). However, the microenvironment may be influenced by the genetic composition of tumor. We investigated whether the CD4 biomarker and BioFLIPI were impacted by genetic features of the tumor as assessed by a 23-gene expression prognostic score ( Lancet Oncol 2018;19:549-61). Methods: Of the 186 cases with FL grade 1-3A treated with immunochemotherapy (IC) in our prior study, 152 had digital expression quantification of 23 selected genes (23-GEP score), which used RNA from formalin-fixed, paraffin-embedded samples. Event-free survival (EFS) was defined as time from diagnosis to progression, relapse, retreatment, or death. Early failure was defined as failing to achieve EFS at 24 months. Risk of early failure was estimated using odds ratios (ORs) and 95% confidence intervals from logistic regression models. We also used Cox regression to assess associations with continuous EFS and overall survival (OS). Results: 28% of patients failed to achieve EFS24. Lack of CD4+ intrafollicular expression (38% of patients, OR = 2.33, p = 0.024) and high risk 23-GEP score (26% of patients, OR = 3.52, p = 0.001) each predicted early failure, and in a multivariable model that included FLIPI, both CD4+ (OR = 2.26, p = 0.046) and 23-GEP score (OR = 2.26, p = 0.0.057) remained predictors. Similarly, BioFLIPI modeled as a continuous score (1-4, OR per one point increase = 2.31, p < 0.001) predicted early failure, and the association remained (OR = 2.14, p < 0.001) when the high risk 23-GEP score (OR = 2.79, p = 0.013) was included in the model. When stratified on 23-GEP score, BioFLIPI was a stronger predictor of early failure in low risk (74%, OR = 2.51, p = 0.002) relative to high risk (26%, OR = 1.55, p = 0.27) patients. Similar patterns were observed for EFS and OS. Conclusions: CD4+ T-cell infiltrate and tumor gene expression appear to be independently predictive of early failure in newly diagnosed FL patients treated with IC. Future studies should integrate and validate these measures.

scholarly journals High Throughput Genomic Analysis Identifies Low-Risk Smoldering Multiple Myeloma

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 2-2
Author(s):  
Anil Aktas-Samur ◽  
Mariateresa Fulciniti ◽  
Sanika Derebail ◽  
Raphael Szalat ◽  
Giovanni Parmigiani ◽  
...  
Keyword(s):  
Multiple Myeloma ◽  
Dna Repair ◽  
High Risk ◽  
Low Risk ◽  
Newly Diagnosed ◽  
Publicly Traded ◽  
Private Company ◽  
Smoldering Multiple Myeloma ◽  
Mutational Processes

Multiple Myeloma is preceded by precursor states of monoclonal gammopathy of undermined significance (MGUS) and smoldering multiple myeloma (SMM). Studies have shown that progression to symptomatic MM five years after diagnosis is 1% for MGUS and 10% for SMM. However, based on the genomic background, this rate is highly variable, especially for SMM patients. Recent studies have evaluated the high-risk genomic features for SMM, but the genomic background of SMM patients who do not progress to MM after long-term follow-up (&gt;= 5 years) has not been described. Here, we evaluated genomic changes enriched in non-progressor (NP) (no progression after 5 years of follow-up) precursor conditions (N=31) with those progressed within a short time (N=71) as well as newly diagnosed Myeloma (N=192). We also studied additional unique samples from 18 patients at their precursor stage as well as when progressed to Myeloma. We report a similar large-scale CN alteration in non-progressor SMM compared to progressor SMMs or MM at diagnosis. However, whole-genome sequencing data showed that the overall mutational load for non-progressor SMM samples was lower than Progressor MGUS/SMM (median SNV 5460 vs. 7018). This difference significantly increased for mutations affecting the coding regions. NP samples at diagnosis had 26% and 53% less coding mutations (missense, nonsense, and frameshift mutations) compared to progressor MGUS/SMM (p=0.008) and newly diagnosed MM (p &lt; 0.001) respectively. We observed very low NRAS (3%, OR=8.86) and BRAF (3%, OR=2.17), mutation frequency in non-progressor SMM samples compared to newly diagnosed MM. We did not observe driver mutations in FAM46C, TTN, CYLD, TP53, KMT2C, IRF4, HIST1H1E that are otherwise frequently mutated in high-risk SMM or symptomatic MM. None of the non-progressor SMM samples had MYC alteration. We observed t(11;14), t(4;14), and t(14;16) translocations at similar frequency compared to newly diagnosed MM samples. We also observed a significant difference in non-recurrent focal deletions. Based on our recent data in newly-diagnosed MM, we quantified genomic scar score, and observed that non-progressor SMM have lower GSS (median=3,IQR=[1-9]) compared to progressor MGUS/SMM (median=11,IQR=[5-15] / median=9,IQR=[9-15], respectively) as well as MM samples at diagnosis (median=9, IQR= [5-16],p=0.002). We further validated this observation in an independent cohort with 69 SMM samples in whom progressor SMM patients had high GSS (median =4, IQR=[2-7.75]), compared to delayed progressor (&gt; four years) or non-progressor SMM (median =1.5, IQR= [0-3.5]; p=0.029). Moreover, non-progressor SMM had significantly low utilization of APOBEC and DNA repair mutational processes. Next, we compared non- progressor SMM with progressor SMM using RNAseq data. We identified 1653 differentially expressed genes (DEG) (762 up-regulated and 891 down-regulated). Genes that were upregulated in non-progressor SMM samples were enriched in IL6/JAK/STAT3 and IL2/STAT5 signaling and the regulation of cytokine secretion. Whereas genes up-regulated in progressor SMM were enriched in MYC targets, DNA repair, and mTOR pathways. Moreover, genes that control the translational initiation, translational elongation, mitochondrial translation, and ATP control were among the top highly expressed genes in progressor SMM. We used our MGUS/SMM to MM paired samples and showed that the E2F target, MYC target, and G2/M checkpoint pathways are more active at MM. We measured the distance between progressor and non-progressor SMM as well as MM and found that non-progressor SMM is less similar to MM compared to progressor SMM. In conclusion, the global CNA and translocations are similar between progressor and non-progressor SMM and symptomatic MM and confirm their role in the development of precursor condition but not adequate for progression to MM, which requires additional hits. On the other hand, lower GSS score reflecting genomic stability along with lower SNVs, low DNA damage and APOBEC mutational processes, down-regulated MYC target genes, and low DNA repair activation define low-risk SMM. These results now provide the basis to develop a genomic definition of SMM. Disclosures Fulciniti: NIH: Research Funding. Parmigiani:Phaeno Biotehnologies: Current equity holder in publicly-traded company; CRA Health: Current equity holder in publicly-traded company; Foundation Medicine Institute: Consultancy; Delphi Diagnostics: Consultancy; BayesMendel Laboratory: Other: Co-lead. Munshi:Janssen: Consultancy; Adaptive: Consultancy; Legend: Consultancy; Amgen: Consultancy; AbbVie: Consultancy; Karyopharm: Consultancy; Takeda: Consultancy; C4: Current equity holder in private company; BMS: Consultancy; OncoPep: Consultancy, Current equity holder in private company, Membership on an entity's Board of Directors or advisory committees, Patents & Royalties.

scholarly journals Establishment of a novel CNV-related prognostic signature predicting prognosis in patients with breast cancer

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Wei Hu ◽  
Mingyue Li ◽  
Qi Zhang ◽  
Chuan Liu ◽  
Xinmei Wang ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Gene Expression ◽  
High Risk ◽  
Risk Score ◽  
Copy Number ◽  
Risk Group ◽  
Gene Signature ◽  
Low Risk ◽  
Breast Cancer Dataset ◽  
Cox Analysis

Abstract Background Copy number variation (CNVs) is a key factor in breast cancer development. This study determined prognostic molecular characteristics to predict breast cancer through performing a comprehensive analysis of copy number and gene expression data. Methods Breast cancer expression profiles, CNV and complete information from The Cancer Genome Atlas (TCGA) dataset were collected. Gene Expression Omnibus (GEO) chip data sets (GSE20685 and GSE31448) containing breast cancer samples were used as external validation sets. Univariate survival COX analysis, multivariate survival COX analysis, least absolute shrinkage and selection operator (LASSO), Chi square, Kaplan-Meier (KM) survival curve and receiver operating characteristic (ROC) analysis were applied to build a gene signature model and assess its performance. Results A total of 649 CNV related-differentially expressed gene obtained from TCGA-breast cancer dataset were related to several cancer pathways and functions. A prognostic gene sets with 9 genes were developed to stratify patients into high-risk and low-risk groups, and its prognostic performance was verified in two independent patient cohorts (n = 327, 246). The result uncovered that 9-gene signature could independently predict breast cancer prognosis. Lower mutation of PIK3CA and higher mutation of TP53 and CDH1 were found in samples with high-risk score compared with samples with low-risk score. Patients in the high-risk group showed higher immune score, malignant clinical features than those in the low-risk group. The 9-gene signature developed in this study achieved a higher AUC. Conclusion The current research established a 5-CNV gene signature to evaluate prognosis of breast cancer patients, which may innovate clinical application of prognostic assessment.

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