Baker, A. M. | bioRxiv Science

bioRxiv2019

Macrophage-mediated immunoediting drives ductal carcinoma evolution: Space is the game changer

Under normal conditions, the immune system is capable of rapidly detecting and eliminating potentially dangerous entities, including tumor cells. Due to intense selection pressure imposed by the immune response, tumor cells often evolve strategies to avoid elimination in a process known as immunoediting. It is less known how the evolutionary response to immune predation is altered by context. We explore the evolution of immune escape strategies in ductal cancers, a natural case in which to study evolution in different contexts: inside and outside of ducts. We highlight the role of macrophages as a source of \"public goods,\" releasing diffusible factors (reactive oxygen species and growth factors). Immunohistochemistry reveals differences between macrophage densities of invasive ductal carcinomas and non-invasive ductal carcinomas in situ. For the first time, immunohistochemistry (IHC) imaging data comparing DCIS to IDC were used to initialize mechanistic agent-based models of evolutionary dynamics. By using IHC to map the initial conditions of a growing tumor, we show that spatial competition and structure influence transient dynamics during invasion. These dynamics are context-dependent, a conclusion that may be missed from interpreting imaging or non-spatial modeling alone. Before invasion, the presence of macrophages correlate with shorter ductal breach times. After invasion, tumors may employ a \"pioneer-engineer\" strategy where pioneering immunoresistant cells on the tumors edge stimulate the release of M1-macrophage-derived reactive oxygen species, degrading surrounding stroma. Behind the invasive edge, the engineering immunosuppressive cells promote the release of M2-macrophage-derived growth factors, providing a long-term immune escape strategy. Together, mathematical modeling and image analysis highlight the crucial role tumor-associated macrophages play in immune escape and invasion, both inside and outside of ducts.

cancer biology↗

bioRxiv2017

Defining Depression Cohorts Using the EHR: Multiple Phenotypes Based on ICD-9 Codes and Medication Orders

BackgroundMajor Depressive Disorder (MDD) is one of the most common mental illnesses and a leading cause of disability worldwide. Electronic Health Records (EHR) allow researchers to conduct unprecedented large-scale observational studies investigating MDD, its disease development and its interaction with other health outcomes. While there exist methods to classify patients as clear cases or controls, given specific data requirements, there are presently no simple, generalizable, and validated methods to classify an entire patient population into varying groups of depression likelihood and severity. MethodsWe have tested a simple, pragmatic electronic phenotype algorithm that classifies patients into one of five mutually exclusive, ordinal groups, varying in depression phenotype. Using data from an integrated health system on 278,026 patients from a 10-year study period we have tested the convergent validity of these constructs using measures of external validation, including patterns of psychiatric prescriptions, symptom severity, indicators of suicidality, comorbidity, mortality, health care utilization, and polygenic risk scores for MDD. ResultsWe found consistent patterns of increasing morbidity and/or adverse outcomes across the five groups, providing evidence for convergent validity. LimitationsThe study population is from a single rural integrated health system which is predominantly white, possibly limiting its generalizability. ConclusionOur study provides initial evidence that a simple algorithm, generalizable to most EHR data sets, provides categories with meaningful face and convergent validity that can be used for stratification of an entire patient population.

epidemiology↗