Cleveland Clinic Foundation, Cleveland, OH
Vamsidhar Velcheti , Michael Castro , Drew Watson , Shweta Kapoor , Anuj Tyagi , Mohammed Sauban , Aftab Alam , Kunal Ghosh Roy , Swaminathan Rajagopalan , Shruthi Kulkarni , Nirjhar Mundkur , Jim Christie , Rakhi Purushothaman Suseela , Adity Ghosh , Kabya Basu , Diwyanshu Sahu , Yashaswini Ullal , Prashant Nair , Manmeet Singh Ahluwalia
Background: The Cellworks Singula Therapeutic Response Index (TRI) has been developed to assist clinicians and NSCLC patients in choosing between competing therapeutic options. In contrast to approaches that consider single aberrations, which often yield limited benefit, Cellworks utilizes an individual patient’s next generation sequencing results and a mechanistic multi-omics biology model, the Cellworks Omics Biology Model (CBM), to biosimulate downstream molecular effects of cell signaling, drugs, and radiation on patient-specific in silico diseased cells. For any individual patient and alternative therapy, Cellworks integrates this biologically modeled multi-omics information into a continuous Singula TRI Score, scaled from 0 (low therapeutic benefit) to 100 (high therapeutic benefit). We demonstrate that Singula is strongly associated with overall survival, progression-free survival and relative therapeutic benefit beyond standard clinical factors, including patient age, gender, and physician prescribed treatments (PPT). Methods: In this study, Singula’s ability to predict response was evaluated in a retrospective cohort of 446 NSCLC patients with OS, PFS, and CR data from The Cancer Genome Atlas (TCGA) project, treated with PPT. As a primary analysis of the CBM and TRI Score, Cox Proportional Hazards (PH) regression and likelihood ratio (LR) tests were used to assess the hypothesis that Singula is predictive of OS, PFS, and CR above and beyond standard clinical factors. A p-value < 0.05 for the corresponding likelihood ratio statistic was required to be considered significant. Results: Multivariate analyses were performed to assess the performance of the Singula Therapy Response Index above and beyond physician’s choice of treatment. The same Singula TRI algorithm and clinical cutoffs were used for all clinical outcome measures. For OS the median survival times for the high and low benefit groups were 60.16 and 28.57 months respectively, based on the median Singula value. Also, the hazard ratio per 25 Singula units for OS was 0.5103 (95% CI: 0.3337 - 0.7804) and the odds ratio for CR was 1.6161. These and further analyses, shown in Table, suggest that Singula TRI provides predictive value of OS, PFS, and CR above and beyond standard clinical factors. Conclusions: The Singula TRI Score provides a continuous measure for alternative NSCLC therapeutic options. In this retrospective cohort, Singula was strongly predictive of OS, PFS, and CR and provided predictive value of OS beyond PPT, patient age and gender. These results will be further validated in prospective clinical studies.
OS | OS | PFS | PFS | CR | CR | |
---|---|---|---|---|---|---|
LR Test | χ21 | p-value | χ21 | p-value | χ21 | p-value |
Singula TRI | 10.0120 | 0.0016 | 3.8579 | 0.0495 | 6.9185 | 0.0085 |
LR Analysis for TRI; OS and CR multivariate analysis; PFS univariate analysis.
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Abstract Disclosures
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