The Game-Changing PGA Technology Harnesses Patient’s Gene Signature to Predict Drug Efficacy: A Reality Check

Background: In 1937, President Franklin Roosevelt initiated a nationwide campaign against cancer by signing the National Cancer Act. Eighty-eight years later, while significant strides have been made, cancer treatment still faces challenges. With 50 to 80 percent of patients not responding to treatment and over 600,000 cancer-related deaths annually in the United States, the need for improvement is evident. Imagine if clinicians could accurately predict the success of any cancer treatment, guaranteeing that each patient receives the most effective care possible. Although biomarker tests offer unprecedented capabilities, they ultimately qualify the minority of patients for precision medicine, while excluding the majority. Drug efficacy/response prediction is thus an important prospect for precision oncology, we need a disruptive technology to extend precision treatments and bring benefit to each and every cancer patient. Methods: The revolutionary technology PGA (Patient-derived Gene expression-informed Anticancer drug efficacy) has been documented previously, which integrates a patient’s own gene signature to identify the top-ranking drugs that individual patients most likely will respond to, especially for those unresponsive to targeted therapy or immunotherapy. In this study, we further conducted a benchmarking reality check for evaluating the clinical application of PGA in real-world settings. The framework incorporates three publicly accessible drug utilization datasets for NSCLC – TCGA, NCCN and MEDLINE. To enable a comprehensive assessment of PGA clinical utility, we define evaluation metrics by capturing drug usage trends in the best clinical practice. Results: Aligned with TCGA treatment landscapes and real-world NSCLC treatment trends in the US, the PGA LUNG test could significantly help oncologists by providing them with reliable predictions to choose the most suitable drugs for their patients. PGA LUNG also highlights the potential for off-label cancer drugs to overcome the challenges of ongoing therapy exhaustion and drug resistance. Conclusions: PGA LUNG’s ability to predict drug efficacies/responses for those cancer patient non-responders at a high accuracy provides a critical clinical advantage.