Cellworks Biosimulation Study Reveals Biomarkers That Predict Response to Hypomethylating Agents and Patient Survival in MDS
Personalized Therapy Biosimulation Uncovers a Spectrum of Genomic Aberrations that Predict Response to HMA in Myelodysplastic Syndrome Patients
SOUTH SAN FRANCISCO, Calif.--(BUSINESS WIRE)-- Cellworks Group Inc., a leader in Precision Drug Development and Personalized Therapy Biosimulation, today announced results from a study that examined how Differentiation Scoring (DS) derived from key myeloid biomarkers in individual Myelodysplastic Syndrome (MDS) patients using the Cellworks Platform and Computational Biology Model (CBM) can predict response to Hypomethylating Agents (HMA). In the study, DS predicted HMA response in MDS patients and showed a strong correlation to the treatment efficacy score (ES). Non-responders had lower DS and survival than patients with high DS. Conclusions from the study suggest that DS-low MDS patients should be considered for novel combination therapy at the time of diagnosis.
Results from the study were featured in a poster presentation as Abstract 2171 at the 64th American Society of Hematology (ASH) Annual Meeting and Exposition on December 10, 2022 and have been published online at Blood®.
“Given that 50% of MDS patients who are treated with HMA as a single agent will have unsatisfactory outcomes, we need to be able to predict therapy response for individual patients prior to treatment,” said Dr. Guido Marcucci, MD, Chair and Professor, Department of Hematologic Malignancies Translational Science, Director, Gehr; Family Center for Leukemia Research, Professor, Department of Hematology & Hematopoietic Cell Transplantation, City of Hope; and Co-Principal Investigator of the study. “This study demonstrates the power of using Cellworks personalized therapy biosimulation to gain insight into individual patient mutanome, drug resistance pathways and novel biomarkers that determine their drug response and resistance to better inform treatment decisions for MDS patients.”
“MDS patients typically have multiple molecular aberrations which impact how they respond to treatment,” said Dr. Scott Howard, MD, MSc, Professor at University of Tennessee Health Science Center and Co-Principal Investigator of the study. “This study showcases the complexity of MDS-related aberrations and provides a metric for identifying beforehand which patients will benefit from HMA as a single agent. By identifying which patients will not respond to HMA, clinicians can consider other options such as a combination therapy or a clinical trial.”
“Biosimulation of MDS using differentiation scoring was able to identify patients with minimal benefits from HMA for whom an alternative strategy at the outset of treatment could offer a very meaningful chance to enhance outcomes,” said Dr. Michael Castro, MD, Neuro-oncologist, Medical Oncologist at Beverly Hills Cancer Center; Chief Medical Officer at Cellworks, Group Inc. and Co-Principal Investigator of the study.
Cellworks Personalized Therapy Biosimulation
The Cellworks Platform biosimulates how a patient's personalized genomic disease model will respond to therapies prior to treatment and can also identify novel drug combinations for treatment-refractory patients. The platform is powered by the groundbreaking Cellworks CBM, a highly curated mechanistic network of 6,000+ human genes, 30,000 molecular species and 600,000+ molecular interactions. As part of the biosimulation process, personalized disease models are created for each patient using their cytogenetic and molecular data as input to the Cellworks CBM. The Cellworks Platform analyzes the impact of specific therapies on the patient’s personalized disease model and predicts the efficacy of specific chemotherapies.
Study: ASH Abstract 2171
The purpose of the study was to examine how Differentiation Scoring derived from the Cellworks Platform, Computational Biology Model, and each Myelodysplastic Syndrome patient’s genomic aberrations could serve as a biomarker to predict response to Hypomethylating Agents.
Differentiation arrest resulting from aberrant methylation represents a key pathogenic and phenotypic feature of MDS. Hypomethylating agents (HMA) can reverse epigenetic dysregulation, but single agents fail to control the disease in approximately 50% of patients, many of whom progress to AML and carry a dismal prognosis.
The study included 169 MDS patients treated with azacytidine (n = 86) or decitabine (n = 83) whose genomic aberrations and clinical outcomes were available from public databases. Biosimulation of the disease state was computationally derived from pathways that were up- or down-regulated by individual genomic aberrations. DS was defined as the ratio of the quantified impact of key differentiation biomarkers in myeloid malignancies (CEBPA, GATA1, SPI1 and ITGAM) divided by the impact of HOXA9 transcription, a known repressor of differentiation, and normalized on a log2 scale.
The Cellworks Platform and CBM were used to determine the change in DS attributable to HMA to define an efficacy score (ES) as a parameter of drug response. A Pearson correlation coefficient was obtained using the two variables. DS in clinical responders (R) and non-responders (NR) was evaluated with the Student t-test. DS was defined with DS > 1.5 as DS-high and < 1.5 as DS-low. Survival data were available for 101 patients and correlated with DS-high (n=49) and DS-low (n=52) groups using a KM-curve.
Regarding HMA response, 62 patients were responders, while 107 were non-responders. Prior to therapy, 86 patients had DS-high and 83 had DS-low scores. Post-treatment, DS were correlated with HMA ES (R = 0.58, p < 2.2e-16), and showed a favorable HMA response for DS-high patients. Biosimulation showed the incremental benefit on DS of HMA was greater for people with DS-high than DS-low scores (44% vs 16%, p = 7.51 e-17). Median DS was higher in responders than in non-responders (p=0.00232). Patients with DS-high scores had superior survival compared to those with DS-low scores (log rank p = 0.0016).
Different genomic aberrations contributed to the DS scores. DS-high patients had more TP53 mutations, 17p del, 8q amp, and 5q del. On the other hand, DS-low patients more often had mutations in ASXL1, SRSF2, RUNX1, DNMT3A, EZH2, NF1, NRAS, CBL, or 7q deletion.
This study shows that Cellworks personalized therapy biosimulation, which was based on each patient’s genomic aberrations, reveals a high spectrum of DS among patients with MDS. DS strongly predicted HMA response and in general, non-responders had lower DS and survival than high-DS patients. While patients with DS-low scores might have fared even worse without HMA therapy, this study suggests that DS-low patients should be considered for novel combination therapy at the time of diagnosis given their unsatisfactory outcomes with HMA therapy as a single agent.
About Cellworks Group
Cellworks Group, Inc. is a leader in Precision Drug Development and Personalized Therapy Biosimulation. The Cellworks Platform predicts therapy response for individual patients and patient cohorts using a breakthrough Computational Biology Model (CBM) and biosimulation technology. Backed by Artiman Ventures, Bering Capital, Sequoia Capital, UnitedHealth Group and Agilent Ventures, Cellworks has the world’s strongest trans-disciplinary team of molecular biologists, cellular pathway modelers and software technologists working toward a common goal – attacking serious diseases to improve the lives of patients. The company is based in South San Francisco, California with a research and development facility in Bangalore, India. For more information, visit www.cellworks.life.
All trademarks and registered trademarks in this document are the properties of their respective owners.
Reichert Communications, LLC
Source: Cellworks Group, Inc.