Posters Reinforce Value of MMprofiler™ Gene-based Prognostic Signature for:
- Identifying High-Risk Elderly Patients
- TOPSPIN Algorithm for Predicting Treatment-Specific Survival
ROTTERDAM, Netherlands and LAGUNA HILLS, Calif., June 20, 2017 /PRNewswire/ --SkylineDx today announced the presentation of new data that validate the use of MMprofiler with SKY92, the company's prognostic tool to risk stratify patients with multiple myeloma (MM). In a poster presentation at the 22nd Congress of the European Hematology Association (EHA) in Madrid, Spain, SkylineDx researchers will demonstrate the prognostic value of MMprofiler for identifying high-risk elderly patients.
In a separate e-poster presentation at EHA, researchers will present data demonstrating the value of the TOPSPIN (Treatment Outcome Prediction using Similarity between PatIeNts) algorithm in predicting survival in patients with MM who received bortezomib.
"Having already established proof of principle for MMprofiler and the TOPSPIN algorithm, we are gratified to have the utility of these prognostic tools further validated by the data presented at EHA," said Dharminder S. Chahal, Chief Executive Officer of SkylineDx. "We are confident that these datasets will enhance clinicians' understanding of the molecular factors that impact risk stratification and survival in patients with multiple myeloma, and that this knowledge will help improve the management of patients living with this devastating disease."
The following two posters will be presented:
- Abstract # P677: Rowan Kuiper, SkylineDx
- Gene Expression Classifier EMC92/SKY92 and Revised ISS Robustly Identify High-Risk Multiple Myeloma in Elderly Patients of the HOVON-87/NMSG-18 Study
- Poster Presentation: Saturday, June 24, 2017 from 17:30 - 19:00
- Abstract # E1279: Joske Ubels, SkylineDx and PhD candidate at University Medical Center Utrecht, and Erasmus Medical Center in Rotterdam
- TOPSPIN: A Novel Algorithm to Predict Treatment Specific Survival in Cancer
- E-poster presentation
MMprofiler with SKY92 Data
These data validate the SKY92 gene expression classifier as a robust marker for identifying high-risk elderly patients with MM who were enrolled in the HOVON-87/NMSG-18 phase III clinical trial. They compared the SKY92 classifier to the revised International Staging System (R-ISS) for multiple myeloma, a prognostic marker that incorporates the conventional International Staging System with fluorescent in situ hybridization (FISH) to detect chromosomal abnormalities and serum lactate dehydrogenase (LDH). The researchers used MMprofiler to obtain risk scores via the SKY92 signature, which measures the activity of 92 MM-related genes.
A total of 178 patients (median age: 73 years) were analyzed for a median follow up of 34 months. Patients were treated with either melphalan, prednisone and thalidomide (MPT) plus thalidomide maintenance therapy, or melphalan, prednisone, lenalidomide (MPR) plus lenalidomide maintenance. The SKY92 classifier identified 25 patients (14%) as high-risk; the median overall survival (OS) was 21 months for the high-risk patients, compared to 53 months for patients classified as standard-risk (hazard ratio [HR] = 3.0; 95% confidence interval [CI] = 1.7 to 5.3; p < 0.001).
The proportion of patients with stage R-ISS-III MM (indicative of high risk) was 8%, a figure comparable to the 10% in the initial International Myeloma Working Group1 report, which developed the R-ISS. The SKY92 classifier performed better than the R-ISS as a high-risk marker for OS; the two-year OS rate was 48% in the SKY92 high-risk patients, versus 58% for the R-ISS-III patients. In a multivariate analysis, SKY92, R-ISS, and deletion of chromosome 13q were independently associated with OS and progression-free survival (PFS).
"SKY92, revised ISS, and FISH markers such as deletion of 13q retained independent prognostic value," stated lead investigator Rowan Kuiper, Bioinformatician at SkylineDx. "Our data built upon previous findings suggesting that MMprofiler, when used in combination with molecular genetic risk profiling, can enable risk stratification in multiple myeloma by elucidating patterns of survival and disease progression in high-risk patients, and may facilitate evaluation of risk-stratified treatment approaches in this patient population."
TOPSPIN is a new computational algorithm identifying gene sets that predict if a patient is likely to survive longer when receiving a treatment of interest versus alternative treatments. The utility of the TOPSPIN method was demonstrated in a multiple myeloma dataset in which 910 patients either received (n = 407) or did not receive (n = 503) bortezomib therapy. SkylineDx researchers defined gene sets using the Gene Ontology (GO) annotation, which provides functionally related groups of genes; they then tested random gene sets with the same structure as the GO sets.
The researchers report that TOPSPIN successfully identified subsets of patients with longer PFS when treated with bortezomib. They note that 28.4% of patients were classified as "will benefit" (Class 1), resulting in an HR of 0.13 (p =7.1* 10-11) between the two treatment arms. Additionally, in an independent test set an HR of 0.47 (p = 0.03) was observed.
"TOPSPIN combines biological knowledge with high-performance computing, and can be applied to any dataset with two treatment arms and a continuous outcome measure," explained Joske Ubels, Bioinformatician at SkylineDx and PhD candidate at University Medical Center Utrecht, and Erasmus Medical Center in Rotterdam, the Netherlands. "In this study, we used TOPSPIN to identify gene sets that enabled us to predict which patients would benefit from bortezomib. That is an important consideration in a disease such as multiple myeloma, for which there are now many treatments available with a wide range of response rates, making it critical to select the right treatment at the time of diagnosis. With the ability to identify gene sets that inform treatment-specific survival, TOPSPIN enables categorization of patients into two subgroups based on their expected benefit from treatment, thereby facilitating therapeutic decision-making."
About Multiple Myeloma
Multiple myeloma (MM) is a cancer that arises from plasma cells, a type of white blood cell made in the bone marrow. In patients with MM, the plasma cells become abnormal, multiply uncontrollably, and release only one type of antibody – known as M-protein – which has no useful function. According to the World Cancer Research Fund International, an estimated 114,000 people around the world are diagnosed with MM annually, and the disease represents 0.8% of all cancers globally.
About MMprofiler with SKY92
MMprofiler assesses risk by measuring the activity of 92 MM-related genes that comprise SKY92, the company's novel, prognostic gene classifier. The lead product of SkylineDx, MMprofiler is proven to be superior to the biomarkers currently used to risk-stratify newly diagnosed and relapsed multiple myeloma patients into a "high" or "standard" risk category.2 Included in a growing number of international treatment guidelines, MMprofiler is CE-IVD registered in Europe and will be coming soon as a laboratory-developed test (LDT) in the United States. For more information, please visit www.mmprofiler.com.
SkylineDx is a commercial-stage biotech company based in Rotterdam, the Netherlands. Originally a spin-off of the Erasmus Medical Center in Rotterdam, the company specializes in the development and marketing of innovative gene signature-based prognostic tests to assist healthcare professionals in making personalized treatment decisions for individual patients. These tests are designed to accurately determine the type or status of the disease or to predict a patient's response to a specific treatment. Based on the test results, healthcare professionals can tailor the treatment to the individual patient. MMprofiler with SKY92 is the company's lead product. To learn more, please visit www.skylinedx.com.
1 Palumbo A, Avet-Loiseau H, Oliva S, et al. Revised International Staging System for multiple myeloma: a report from International Myeloma Working Group. J Clin Oncol. 2015;33(28):2863-9.
2 Van Beers EH, van Vliet M, de Best L, et al. SKY92 GEP, iFISH, and ISS comparisons for risk stratification in multiple myeloma. Poster p661 presented at 20th European Hematology Association Congress, Vienna, Austria, June 13, 2015.