Integration of pharmacology, molecular pathology, and population data science to support precision gastrointestinal oncology

Abstract

Precision medicine has a goal of customizing disease prevention and treatment strategies. Under the precision medicine paradigm, each patient has unique pathologic processes resulting from cellular genomic, epigenomic, proteomic, and metabolomic alterations, which are influenced by pharmacological, environmental, microbial, dietary, and lifestyle factors. Hence, to realize the promise of precision medicine, multi-level research methods that can comprehensively analyze many of these variables are needed. In order to address this gap, the integrative field of molecular pathology and population data science (i.e., molecular pathological epidemiology) has been developed to enable such multi-level analyses, especially in gastrointestinal cancer research. Further integration of pharmacology can improve our understanding of drug effects, and inform decision-making of drug use at both the individual and population levels. Such integrative research demonstrated potential benefits of aspirin in colorectal carcinoma with PIK3CA mutations, providing the basis for new clinical trials. Evidence also suggests that HPGD (15-PDGH) expression levels in normal colon and the germline rs6983267 polymorphism that relates to tumor CTNNB1 (β-catenin)/WNT signaling status may predict the efficacy of aspirin for cancer chemoprevention. As immune checkpoint blockade targeting the CD274 (PD-L1)/PDCD1 (PD-1) pathway for microsatellite instability-high (or mismatch repair-deficient) metastatic gastrointestinal or other tumors has become standard of care, potential modifying effects of dietary, lifestyle, microbial, and environmental factors on immunotherapy need to be studied to further optimize treatment strategies. With its broad applicability, our integrative approach can provide insights into the interactive role of medications, exposures, and molecular pathology, and guide the development of precision medicine.

Fig. 1

Structure of epidemiology and its subfields. Since the formation of the field of epidemiology, a number of subfields have emerged to specialize into particular subject matters, including detailed analyses of exposure factors (depicted on the left) and detailed analyses of health outcomes or diseases (depicted on the right). Six such subfields among many are shown. In addition, a method subfield "molecular pathological epidemiology (MPE)" has been developed under the core method field of epidemiology. MPE can be applied to any exposure and disease settings, and can be integrated with any other subfield of epidemiology

Fig. 2

Influences of various exposures on pathogenic process. A wide variety of endogenous and exogenous factors (including drugs), individually or in combination, can modify phenotypes of cancer, leading to interpersonal heterogeneity. The molecular pathological epidemiology (MPE) approach utilizes integrated analyses of these exposures and tumor phenotypes to improve our understanding of tumor development and progression. Of note, for the sake of simplicity, this illustration does not depict complex interactions between the exposure factors

Fig. 3

Trans-multidisciplinary integration of pharmacology, epidemiology, and molecular pathology. The integration of pharmacology and epidemiology has generated pharmacoepidemiology, while the integration of molecular pathology and epidemiology has generated molecular pathological epidemiology (MPE). We propose the integration of pharmacoepidemiology and MPE to generate pharmaco-MPE

Fig. 4

Collaborative relationship between pharmacoepidemiology and molecular pathological epidemiology (MPE). Both are subfields of epidemiology, and cover the entire spectrum of human diseases. Both fields can be synergized to create an integrative field of pharmaco-MPE, which can further enhance research and education for precision medicine

Fig. 5

Study Designs in pharmaco-molecular pathological epidemiology (MPE) research. Arrows indicate time sequence. Here, the disease of interest is sub-classified based on pathogenic signatures into binary subtypes A and B for simplicity. Note that multiple subtypes can be evaluated in pharmaco-MPE research. Analyses can be conducted to assess effects of a drug of interest on the occurrence and/or consequential event (such as death) of a specific disease subtype. In the MPE research framework, a difference in the associations between disease subtypes is assessed. Panels indicate specific designs (with the corresponding column number in Table 1) as follows: 1, observational hospital-based design; 2, observational population-based design; 3, experimental hospital-based trial; and 4, experimental population-based trial

Fig. 6

Roadmap for implementing molecular pathologic biomarkers for precision medicine. Three themes are set to launch integrated pharmaco-molecular pathological epidemiology (MPE) research and achieve three specific aims. Based on data obtained by research for the specific aims, Strategies 1 through 3 will help implement, monitor, and optimize tumor biomarker testing for clinical impact