Pharmacogenomic epidemiology is a research area that utilizes epidemiologic methodologies to interrogate pharmacogenomic questions. This research focuses on the use of observational datasets or secondary analyses of clinical trials to evaluate the impact of genetic variation and tumour genomics within pharmacodynamic and pharmacokinetic pathways of therapies on important patient outcomes, such as treatment response, survival or toxicity.
The Liu laboratory, known as AMPPEL (Applied Molecular Profiling Pharmacogenomic Epidemiologic Laboratory) involves a wet component (cell line, primary human xenografts, and primary human tissues, functional assays) and a dry laboratory (clinic-epidemiologic recruitment, data collection, sample acquisition, statistical analysis, epidemiologic and health services outcomes research analyses). The application of molecular epidemiologic methods to pharmacogenetics has provided new opportunities to evaluate rigorously the role of genomic factors in cancer treatment outcomes and toxicity. When large clinical trials involving the drugs of interest are available, secondary analysis of such trials is the preferred method of studying pharmacogenetics. However, there are many instances, such as in rare tumours or when trying to evaluate pharmacogenomics of standard chemotherapy or radiotherapy treatments, where clinical trials are not available to answer important pharmacogenetic questions. Under these circumstances, the role of carefully planned prospective observational studies becomes instrumental to answer both pharmacogenomic and cancer prognosis questions. The quality of results obtainable from these studies is highly dependent on the methods used to recruit patients, to obtain and process samples, to accurately measure genetic markers, to determine accurate phenotypes and outcomes, and to perform appropriate statistical analysis. In addition, pharmacogenomic functional assays and testing are an important component. Therefore, PGE results from these high quality observational studies and clinical trials, the goal of much of AMPPEL's efforts, have strong potential to impact on patient risk stratification and in the choice of appropriate therapies. Dr. Liu is the overall lead PI of the CARMA BROS study (Canadian Rare Molecular Alteration Basket-umbrella Real-world Observational Study; NCT04151342), and site PI of PALEOS (Pan-Canadian Lung cancEr Observational Study; NCT04706754).
AMPPEL Dry Lab
A major impediment to performing PGE research has been the lack of systematic collection of toxicity outcomes outside of the clinical trial setting. Dr. Liu is co-director of the ON-PROST ACRU (Ontario Patient Reported Outcomes of Symptoms and Toxicity Applied Clinical Research Unit) funded by Cancer Care Ontario (CCO). This clinical research unit is envisioned as a virtual laboratory for piloting different methods for systematically collecting patient symptoms and toxicity as part of routine care and for research purposes, developing province-wide consensus on what toxicities and symptoms to collect, to support the computer adaptive technology required for province-wide implementation. The majority of pilots are beginning at PMH (lung, head and neck, gastro-esophageal, testicular cancers), in areas that correspond to ongoing molecular epidemiological studies.
Evaluations of Clinical Utility and Clinical Uptake of pharmacogenomic testing are critical to translation from bench to bedside. In the era of personalized medicine, evaluating whether patients understand what pharmacogenomic testing means and involves, their attitude and preferences is important. Through interview-based research utilizing theoretical scenarios and either trade-off testing or conjoint testing, AMPPEL has been ascertaining PMH patient and physician attitudes, understanding and preferences for pharmacogenetic testing.
Dr. Liu is co-lead on 2BLAST (Biostatistics and bioinformatics for the longitudinal analysis of symptoms and toxicity) data science project at Princess Margaret Cancer Centre and co-lead on MBLAST (Machine Learning and Biostatistics for the longitudinal analysis of symptoms and toxicity). This research integrates use of the electronic health record with patient-reported data for analysis of patterns of care and outcomes, using machine learning and natural language processing methods. Some of these analyses are helping the 9th Edition Lung Cancer Staging Project. He is co-leading these efforts with Dr. Wei Xu (Biostatistics) and Dr. Robert Grant (Machine Learning).
AMPPEL Wet Lab section
AMPPEL is performing PGE evaluations in clinical trials and observational studies, using archival tissue, fresh tissue, blood and other surrogate tissues. The methodologic approaches used include: candidate-based analyses, pharmacokinetic (PK) and pharmacodynamic (PD) pathway analyses, genome-wide association studies (GWAS) and post-GWAS analyses (includes methods development), and in the next few years, Next Generation Sequencing (Whole Exome, Whole Genome Sequencing). In addition, AMPPEL has recruited hundreds of patients into molecular epidemiologic studies, including patients with Lung, Head and Neck, Gastro-esophageal, hepatobiliary, pancreatic, and testicular cancer patients, thymomas and mesotheliomas. The laboratory has helped to integrate and coordinate consenting, recruitment, data collection, data management, quality control and clinico-epidemiologic analyses for multiple cancer site
Dr. Liu has been PI of a five-year CCSRI Impact Grant, lung cancer primary derived xenograft program, and is currently PI of a subsequent CIHR-funded grant on primary derived organoids of lung cancer, OPTIMAL (Organoids to guide Post-resistance Therapy In driver MutAted Lung cancers (OPTIMAL). He is also co-lead of POLOR (Patient-derived Organoids of Lung cancer to understand Osimertinib Resistance), an industry sponsored organoid project. He co-leads these research programs with Dr. Ming Tsao at Princess Margaret Cancer Centre
Dr. Liu is lead of Princess Margaret CALIBRE program (Cancer And Liquid biopsy, Integrated analysis, Breathomics, Radiomics for Early Detection). In Lung-CALIBRE, the specific focus of this research is to identify biomarkers that can refine the selection for lung cancer CT screening, identify biomarkers that identify patients for specific interventions and develop risk stratification that incorporates biomarkers. He is Principal Investigator of breathomics as a predictive test for immune checkpoint inhibitor efficacy, which is funded through Industry support and the Canadian Cancer Society Research Institute (CCSRI). As co-Principal Applicant, he also co-leads the CIHR funded Lung cancer early detection and classification using methylome analysis of plasma cell free DNA.