Preclinical Drug Response Metric Based on Cellular Response Phenotype Provides Better Pharmacogenomic Variables with Phenotype Relevance

High-throughput screening of drug response in cultured cell lines is essential for studying therapeutic mechanisms and identifying molecular variants associated with sensitivity to drugs. Assessment of drug response is typically performed by constructing a dose-response curve of viability and summarizing it to a representative, such as IC50. However, this is limited by its dependency on the assay duration and lack of reflections regarding actual cellular response phenotypes. To address these limitations, we consider how each response-phenotype contributes to the overall growth behavior and propose an alternative method of drug response screening that takes into account the cellular response phenotype. In conventional drug response screening methods, the ranking of sensitivity depends on either the metric used to construct the dose-response curve or the representative factor used to summarize the curve. This ambiguity in conventional assessment methods is due to the fact that assessment methods are not consistent with the underlying principles of population dynamics. Instead, the suggested phenotype metrics provide all phenotypic rates of change that shape overall growth behavior at a given dose and better response classification, including the phenotypic mechanism of overall growth inhibition. This alternative high-throughput drug-response screening would improve preclinical pharmacogenomic analysis and the understanding of a therapeutic mechanism of action.

A novel gene-by-environment quantitative trait locus on mouse chromosome 15 underlies susceptibility to acute ozone-induced lung injury

Respiratory toxicity caused by the common urban air pollutant ozone (O3) varies considerably within the human population and across inbred mouse strains, suggestive of gene-environment interactions (GxE). Though previous studies genetic mapping studies using classical inbred strains have identified several and quantitative trait locus (QTL) and candidate genes underlying responses to O3 exposure, precise mechanisms of susceptibility remain incompletely described. We sought to expand our understanding of the genetic architecture of O3 responsiveness using the Collaborative Cross (CC) recombinant inbred mouse panel, which contains more genetic diversity than previous inbred strain panels. We evaluated hallmark O3-induced respiratory phenotypes in 56 CC strains after exposure to filtered air or 2 ppm O3, and performed focused genetic analysis of variation in lung injury as measured by the total bronchoalveolar lavage protein concentration. Because animals were exposed in sex- and batch-matched pairs, we defined a protein response phenotype as the difference in lavage protein between the O3- and FA-exposed animal within a pair. The protein response phenotype was heritable, and QTL mapping revealed two novel loci on Chromosomes 10 (peak: 26.2 Mb; 80% CI: 24.6-43.6 Mb) and 15 (peak: 47.1 Mb; 80% CI: 40.2-54.9 Mb), the latter surpassing the 95% significance threshold. At the Chr. 15 locus, C57BL/6J and CAST/EiJ founder haplotypes were associated with higher protein responses compared to all other CC founder strain haplotypes. Using additional statistical analysis and high-density SNP data, we delimited the Chr. 15 QTL to a ~2 Mb region containing 21 genes (10 protein coding). Using a weight of evidence approach that incorporated candidate variant analysis, functional annotations, and publicly available lung gene expression data, we nominated three candidate genes (Oxr1, Rspo2, and Angpt1). In summary, we have shown that O3-induced lung injury is modulated by genetic variation and demonstrated the value of the CC for uncovering and dissecting gene-environment interactions.

Effects of Arabidopsis wall associated kinase mutations on ESMERALDA1 and elicitor induced ROS

Angiosperm cell adhesion is dependent on interactions between pectin polysaccharides which make up a significant portion of the plant cell wall. Cell adhesion in Arabidopsis may also be regulated through a pectin-related signaling cascade mediated by a putative O-fucosyltransferase ESMERALDA1 (ESMD1), and the Epidermal Growth Factor (EGF) domains of the pectin binding Wall associated Kinases (WAKs) are a primary candidate substrate for ESMD1 activity. Genetic interactions between WAKs and ESMD1 were examined using a dominant hyperactive allele of WAK2, WAK2cTAP, and a mutant of the putative O-fucosyltransferase ESMD1. WAK2cTAP expression results in a dwarf phenotype and activation of the stress response and reactive oxygen species (ROS) production, while esmd1 is a suppressor of a pectin deficiency induced loss of adhesion. Here we find that esmd1 suppresses the WAK2cTAP dwarf and stress response phenotype, including ROS accumulation and gene expression. Additional analysis suggests that mutations of the potential WAK EGF O-fucosylation site also abate the WAK2cTAP phenotype, yet only evidence for an N-linked but not O-linked sugar addition can be found. Moreover, a WAK locus deletion allele has no effect on the ability of esmd1 to suppress an adhesion deficiency, indicating WAKs and their modification are not a required component of the potential ESMD1 signaling mechanism involved in the control of cell adhesion. The WAK locus deletion does however affect the induction of ROS but not the transcriptional response induced by the elicitors Flagellin, Chitin and oligogalacturonides (OGs).

Dissecting phenotypic transitions in metastatic disease via photoconversion-based isolation

Cancer patients often harbor occult metastases, a potential source of relapse that is targetable only through systemic therapy. Studies of this occult fraction have been limited by a lack of tools with which to isolate discrete cells on spatial grounds. We developed PIC-IT, a photoconversion-based isolation technique allowing efficient recovery of cell clusters of any size – including single-metastatic cells – which are largely inaccessible otherwise. In a murine pancreatic cancer model, transcriptional profiling of spontaneously arising microcolonies revealed phenotypic heterogeneity, functionally reduced propensity to proliferate and enrichment for an inflammatory-response phenotype associated with NF-κB/AP-1 signaling. Pharmacological inhibition of NF-κB depleted microcolonies but had no effect on macrometastases, suggesting microcolonies are particularly dependent on this pathway. PIC-IT thus enables systematic investigation of metastatic heterogeneity. Moreover, the technique can be applied to other biological systems in which isolation and characterization of spatially distinct cell populations is not currently feasible.

Leveraging a Pharmacogenomics Knowledgebase to Formulate a Drug Response Phenotype Terminology for Genomic Medicine (Preprint)

BACKGROUND Despite the increasing evidence of utility of genomic medicine in clinical practice, systematically integrating genomic medicine information and knowledge into clinical systems with a high-level of consistency, scalability, and computability remains challenging. A comprehensive terminology is required for relevant concepts and the associated knowledge model for representing relationships. OBJECTIVE Our study aims to propose a drug response phenotype terminology to represent relationships between genetic variants and drugs in existing knowledge models. METHODS In this study, we leveraged PharmGKB, a comprehensive pharmacogenomics (PGx) knowledgebase, to formulate a terminology for drug response phenotypes that can represent relationships between genetic mutations and treatments. We evaluated coverage of the terminology through manual review of a randomly selected subset of 200 sentences extracted from genetic reports that contained concepts for “Genes and Gene Products” and “Treatments”. RESULTS Results showed that our proposed drug response phenotype terminology could cover 96% of the drug response phenotypes in genetic reports. Among 18,653 sentences that contained both “Genes and Gene Products” and “Treatments”, 3,011 sentences were able to be mapped to a drug response phenotype in our proposed terminology, among which the most discussed drug response phenotypes were response (994), sensitivity (829), and survival (332). In addition, we were able to re-analyze genetic report context incorporating the proposed terminology and enrich our previously proposed PGx knowledge model to reveal relationships between genetic mutations and treatments. CONCLUSIONS In conclusion, we proposed a drug response phenotype terminology that enhanced structured knowledge representation of genomic medicine.

ASSESSMENT OF THE IMMUNE RESPONSE PHENOTYPE IN PATIENTS WITH SURGICAL SEPSIS DEPENDING ON THE COURSE AND OUTCOMES OF THE DISEASE

Sepsis remains one of the biggest problems of modern medicine throughout the world. Timely determination of the phenotype of the patient’s immune response will be critical to making early therapeutic decisions. Analysis of the content of Treg and TNF-α, IL-6, IL10, TGF-β in patients with sepsis, depending on the severity of organ dysfunction in the dynamics of the disease was carried out. There was a direct correlation of moderate strength between the blood levels of IL-10 and Treg (R = 0.54, p<0.05). High levels of Treg, IL-10 content reflect the immunosuppressive phenotype of the immune response in the late stages and is a prognostic criterion for an unfavorable outcome in sepsis.

Alternative drug-response metric based on cellular response phenotypes

ABSTRACTCurrent drug-response metrics based on viability or apparent growth rates are limited by their dependency on the assay duration and lack of reflections regarding actual cellular drug-response phenotypes. To resolve these limitations, we evaluated the contribution of each cellular response phenotype to a drug on the overall growth behavior. This provides a time-independent phenotype metric which can reveal the mechanisms underlying growth inhibition of specific cells by a given drug.

Dissecting phenotypic transitions in metastatic disease via photoconversion-based isolation

Cancer patients presenting with surgically resectable disease often harbor occult metastases, a potential source of relapse that is targetable only through systemic therapy. Studies of this occult fraction have been limited by a lack of tools with which to isolate discrete cells based on spatial grounds. We developed PIC-IT, photoconversion-based isolation technique allowing efficient recovery of cell clusters of any size including solitary disseminated tumor cells (DTCs), which are largely inaccessible otherwise. In a murine pancreatic cancer model, transcriptional profiling of spontaneously arising DTCs revealed phenotypic heterogeneity, functionally reduced propensity to proliferate and enrichment for inflammatory-response phenotype associated with NF-κB /AP-1 signaling. Pharmacological inhibition of NF-κB depleted DTCs but had no effect on macrometastases, suggesting DTCs are particularly dependent on this pathway. PIC-IT enables systematic investigation of the earliest stages of metastatic colonization. Moreover, this new technique can be applied to other biological systems in which isolation and characterization of spatially distinct cell populations is not currently feasible.

Lipidomic Assessment of Triacylglycerol and Cholesterol Ester Species After n-3 Polyunsaturated Fatty Acid Suppementation in Humans: Comparison of Response Phenotypes

Objectives Assess the differences in triacylglycerol (TAG) and cholesterol ester (CE) species in the plasma of individuals displaying heterogeneous lipid responses following long chain n-3 (LCn-3) polyunsaturated fatty acid supplementation. Methods We performed a targeted, mass spectrometry (MS), infusion-based lipidomic analysis on plasma samples obtained from a clinical study in which participants were supplemented with 3 g/day of LCn-3 in the form of fish oil capsules over a 6-week period. Triacylglycerol (TAG) species and cholesteryl esters (CE) were quantified for 130 participants pre- and post-supplementation. Results Based on the change of total TAG concentrations following supplementation, participants were segregated into three response phenotypes: (1) positive responders (R+; TAG decrease &lt; 10%), (2) non-responders (NR; TAG changes +/− 10%), and (3) negative responders (R−; TAG increase &gt; 10%) representing 87/130 (67%), 24/130 (18%), and 19/130 (15%) of the study samples, respectively. There were no phenotypic differences for age, sex, body-mass index, glycemia, or ApoB concentrations. Sparse partial least squares discriminant analysis separated the three phenotypes with component 1 attributed to changes in TAG 50–53: X with 0–3 desaturations with R + having reductions in these TAG. Separation along component 2 identified lower mass TAG 46–48: X with 1–3 desaturations likely containing 14:0. This latter effect impacted mostly NR and R- phenotypes. Analysis of individual TAG species per response phenotype revealed TAG species that did not align with the overall TAG response phenotype. Using the TAG response phenotype for grouping, we performed SPLDA analysis for CE responses. We observed that distinction of the TAG response phenotypes qualitatively applies to CE in which separation along component 1 (65% of variance) was due to differences in CE 18:0, 18:1, and 14:0. CE 20:5 was elevated equally (&gt;300%) between all phenotypes indicating LCn-3 intake. However, CE 22:6 was elevated R− (86%) to a greater extent vs. Res+ (55%) and NR (49%) phenotypes. Conclusions Our data identify lipidomic signatures (TAG and CE) associated with LCn-3 response phenotypes in humans and provide insight into the variability of lipid metabolism in humans. Funding Sources USDA-NIFA, USDA-ARS and CIHR MOP-229,488.