PharmacoDB 2.0 : Improving scalability and transparency of in vitro pharmacogenomics analysis

Cancer pharmacogenomics studies provide valuable insights into disease progression and associations between genomic features and drug response. PharmacoDB integrates multiple cancer pharmacogenomics datasets profiling approved and investigational drugs across cell lines from diverse tissue types. The web-application enables users to efficiently navigate across datasets, view and compare drug dose-response data for a specific drug-cell line pair. In the new version of PharmacoDB (version 2.0, https://pharmacodb.ca/), we present: (i) new datasets such as NCI-60, the Profiling Relative Inhibition Simultaneously in Mixtures (PRISM) dataset, as well as updated data from the Genomics of Drug Sensitivity in Cancer (GDSC) and the Genentech Cell Line Screening Initiative (gCSI); (ii) implementation of FAIR data pipelines using ORCESTRA and PharmacoDI; (iii) enhancements to drug response analysis such as tissue distribution of dose-response metrics and biomarker analysis; (iv) improved connectivity to drug and cell line databases in the community. The web interface has been rewritten using a modern technology stack to ensure scalability and standardization to accommodate growing pharmacogenomics datasets. PharmacoDB 2.0 is a valuable tool for mining pharmacogenomics datasets, comparing and assessing drug response phenotypes of cancer models.

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Abstract B201: Drug response profiling, redox ratio, and biomarker analysis in an in vitro 3D tri-culture model of breast cancer

10.1158/1535-7163.targ-15-b201 ◽

2015 ◽

Author(s):

Tessa DesRochers ◽

Stephen Shuford ◽

Christina Mattingly ◽

Terri Bruce ◽

Matt Gevaert ◽

...

Keyword(s):

Breast Cancer ◽

Drug Response ◽

Redox Ratio ◽

Culture Model ◽

Biomarker Analysis

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Connecting gene expression subtypes of colorectal cancer (CRC) with cell lines and drug resistance.

Journal of Clinical Oncology ◽

10.1200/jco.2013.31.15_suppl.e14544 ◽

2013 ◽

Vol 31 (15_suppl) ◽

pp. e14544-e14544

Author(s):

Eva Budinska ◽

Jenny Wilding ◽

Vlad Calin Popovici ◽

Edoardo Missiaglia ◽

Arnaud Roth ◽

...

Keyword(s):

Gene Expression ◽

Cell Line ◽

Clinical Significance ◽

Cell Lines ◽

Drug Response ◽

Drug Sensitivity ◽

Expression Profiles ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis

e14544 Background: We identified CRC gene expression subtypes (ASCO 2012, #3511), which associate with established parameters of outcome as well as relevant biological motifs. We now substantiate their biological and potentially clinical significance by linking them with cell line data and drug sensitivity, primarily attempting to identify models for the poor prognosis subtypes Mesenchymal and CIMP-H like (characterized by EMT/stroma and immune-associated gene modules, respectively). Methods: We analyzed gene expression profiles of 35 publicly available cell lines with sensitivity data for 82 drug compounds, and our 94 cell lines with data on sensitivity for 7 compounds and colony morphology. As in vitro, stromal and immune-associated genes loose their relevance, we trained a new classifier based on genes expressed in both systems, which identifies the subtypes in both tissue and cell cultures. Cell line subtypes were validated by comparing their enrichment for molecular markers with that of our CRC subtypes. Drug sensitivity was assessed by linking original subtypes with 92 drug response signatures (MsigDB) via gene set enrichment analysis, and by screening drug sensitivity of cell line panels against our subtypes (Kruskal-Wallis test). Results: Of the cell lines 70% could be assigned to a subtype with a probability as high as 0.95. The cell line subtypes were significantly associated with their KRAS, BRAF and MSI status and corresponded to our CRC subtypes. Interestingly, the cell lines which in matrigel created a network of undifferentiated cells were assigned to the Mesenchymal subtype. Drug response studies revealed potential sensitivity of subtypes to multiple compounds, in addition to what could be predicted based on their mutational profile (e.g. sensitivity of the CIMP-H subtype to Dasatinib, p<0.01). Conclusions: Our data support the biological and potentially clinical significance of the CRC subtypes in their association with cell line models, including results of drug sensitivity analysis. Our subtypes might not only have prognostic value but might also be predictive for response to drugs. Subtyping cell lines further substantiates their significance as relevant model for functional studies.

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Facilitating Drug Discovery in Breast Cancer by Virtually Screening Patients Using In Vitro Drug Response Modeling

Cancers ◽

10.3390/cancers13040885 ◽

2021 ◽

Vol 13 (4) ◽

pp. 885

Author(s):

Robert F. Gruener ◽

Alexander Ling ◽

Ya-Fang Chang ◽

Gladys Morrison ◽

Paul Geeleher ◽

...

Keyword(s):

Breast Cancer ◽

Drug Discovery ◽

Cell Line ◽

Drug Response ◽

Drug Efficacy ◽

Standard Of Care ◽

Breast Cancer Patients ◽

Response Modeling

(1) Background: Drug imputation methods often aim to translate in vitro drug response to in vivo drug efficacy predictions. While commonly used in retrospective analyses, our aim is to investigate the use of drug prediction methods for the generation of novel drug discovery hypotheses. Triple-negative breast cancer (TNBC) is a severe clinical challenge in need of new therapies. (2) Methods: We used an established machine learning approach to build models of drug response based on cell line transcriptome data, which we then applied to patient tumor data to obtain predicted sensitivity scores for hundreds of drugs in over 1000 breast cancer patients. We then examined the relationships between predicted drug response and patient clinical features. (3) Results: Our analysis recapitulated several suspected vulnerabilities in TNBC and identified a number of compounds-of-interest. AZD-1775, a Wee1 inhibitor, was predicted to have preferential activity in TNBC (p < 2.2 × 10−16) and its efficacy was highly associated with TP53 mutations (p = 1.2 × 10−46). We validated these findings using independent cell line screening data and pathway analysis. Additionally, co-administration of AZD-1775 with standard-of-care paclitaxel was able to inhibit tumor growth (p < 0.05) and increase survival (p < 0.01) in a xenograft mouse model of TNBC. (4) Conclusions: Overall, this study provides a framework to turn any cancer transcriptomic dataset into a dataset for drug discovery. Using this framework, one can quickly generate meaningful drug discovery hypotheses for a cancer population of interest.

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A regularized functional regression model enabling transcriptome-wide dosage-dependent association study of cancer drug response

10.1101/2020.06.18.158907 ◽

2020 ◽

Author(s):

Evanthia Koukouli ◽

Dennis Wang ◽

Frank Dondelinger ◽

Juhyun Park

Keyword(s):

Gene Expression ◽

Regression Model ◽

Cell Line ◽

Cell Lines ◽

Dose Response ◽

Drug Response ◽

Drug Sensitivity ◽

Cancer Drug ◽

Functional Regression ◽

Response Curves

AbstractCancer treatments can be highly toxic and frequently only a subset of the patient population will benefit from a given treatment. Tumour genetic makeup plays an important role in cancer drug sensitivity. We suspect that gene expression markers could be used as a decision aid for treatment selection or dosage tuning. Using in vitro cancer cell line dose-response and gene expression data from the Genomics of Drug Sensitivity in Cancer (GDSC) project, we build a dose-varying regression model. Unlike existing approaches, this allows us to estimate dosage-dependent associations with gene expression. We include the transcriptomic profiles as dose-invariant covariates into the regression model and assume that their effect varies smoothly over the dosage levels. A two-stage variable selection algorithm (variable screening followed by penalised regression) is used to identify genetic factors that are associated with drug response over the varying dosages. We evaluate the effectiveness of our method using simulation studies focusing on the choice of tuning parameters and cross-validation for predictive accuracy assessment. We further apply the model to data from five BRAF targeted compounds applied to different cancer cell lines under different dosage levels. We highlight the dosage-dependent dynamics of the associations between the selected genes and drug response, and we perform pathway enrichment analysis to show that the selected genes play an important role in pathways related to tumourgenesis and DNA damage response.Author SummaryTumour cell lines allow scientists to test anticancer drugs in a laboratory environment. Cells are exposed to the drug in increasing concentrations, and the drug response, or amount of surviving cells, is measured. Generally, drug response is summarized via a single number such as the concentration at which 50% of the cells have died (IC50). To avoid relying on such summary measures, we adopted a functional regression approach that takes the dose-response curves as inputs, and uses them to find biomarkers of drug response. One major advantage of our approach is that it describes how the effect of a biomarker on the drug response changes with the drug dosage. This is useful for determining optimal treatment dosages and predicting drug response curves for unseen drug-cell line combinations. Our method scales to large numbers of biomarkers by using regularisation and, in contrast with existing literature, selects the most informative genes by accounting for drug response at untested dosages. We demonstrate its value using data from the Genomics of Drug Sensitivity in Cancer project to identify genes whose expression is associated with drug response. We show that the selected genes recapitulate prior biological knowledge, and belong to known cancer pathways.

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Optimization of Catheter Based rtPA Thrombolysis in a Novel In Vitro Clot Model for Intracerebral Hemorrhage

BioMed Research International ◽

10.1155/2017/5472936 ◽

2017 ◽

Vol 2017 ◽

pp. 1-8 ◽

Cited By ~ 4

Author(s):

Naureen Keric ◽

Julia Masomi-Bornwasser ◽

Hendrik Müller-Werkmeister ◽

Sven Rainer Kantelhardt ◽

Jochem König ◽

...

Keyword(s):

Intracerebral Hemorrhage ◽

Dose Response ◽

Blood Clot ◽

Alternative Therapy ◽

Optimal Dose ◽

Clot Lysis ◽

Response Analysis ◽

In Vitro Investigation ◽

Optimal Drug

Hematoma lysis with recombinant tissue plasminogen activator (rtPA) has emerged as an alternative therapy for spontaneous intracerebral hemorrhage (ICH). Optimal dose and schedule are still unclear. The aim of this study was to create a reliable in vitro blood clot model for investigation of optimal drug dose and timing. An in vitro clot model was established, using 25 mL and 50 mL of human blood. Catheters were placed into the clots and three groups, using intraclot application of rtPA, placebo, and catheter alone, were analyzed. Dose-response relationship, repetition, and duration of rtPA treatment and its effectiveness in aged clots were investigated. A significant relative end weight difference was found in rtPA treated clots compared to catheter alone (p=0.002) and placebo treated clots (p<0.001). Dose-response analysis revealed 95% effective dose around 1 mg rtPA in 25 and 50 mL clots. Approximately 80% of relative clot lysis could be achieved after 15 min incubation. Lysis of aged clots was less effective. A new clot model for in vitro investigation was established. Our data suggest that current protocols for rtPA based ICH therapy may be optimized by using less rtPA at shorter incubation times.

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Predicting chemosensitivity using drug perturbed gene dynamics

BMC Bioinformatics ◽

10.1186/s12859-020-03947-y ◽

2021 ◽

Vol 22 (1) ◽

Author(s):

Joshua D. Mannheimer ◽

Ashok Prasad ◽

Daniel L. Gustafson

Keyword(s):

Gene Expression ◽

Cell Line ◽

Computational Methods ◽

Predictive Models ◽

Drug Response ◽

Drug Sensitivity ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Gene Signatures

Abstract Background One of the current directions of precision medicine is the use of computational methods to aid in the diagnosis, prognosis, and treatment of disease based on data driven approaches. For instance, in oncology, there has been a particular focus on development of algorithms and biomarkers that can be used for pre-clinical and clinical applications. In particular large-scale omics-based models to predict drug sensitivity in in vitro cancer cell line panels have been used to explore the utility and aid in the development of these models as clinical tools. Additionally, a number of web-based interfaces have been constructed for researchers to explore the potential of drug perturbed gene expression as biomarkers including the NCI Transcriptional Pharmacodynamic Workbench. In this paper we explore the influence of drug perturbed gene dynamics of the NCI Transcriptional Pharmacodynamics Workbench in computational models to predict in vitro drug sensitivity for 15 drugs on the NCI60 cell line panel. Results This work presents three main findings. First, our models show that gene expression profiles that capture changes in gene expression after 24 h of exposure to a high concentration of drug generates the most accurate predictive models compared to the expression profiles under different dosing conditions. Second, signatures of 100 genes are developed for different gene expression profiles; furthermore, when the gene signatures are applied across gene expression profiles model performance is substantially decreased when gene signatures developed using changes in gene expression are applied to non-drugged gene expression. Lastly, we show that the gene interaction networks developed on these signatures show different network topologies and can be used to inform selection of cancer relevant genes. Conclusion Our models suggest that perturbed gene signatures are predictive of drug response, but cannot be applied to predict drug response using unperturbed gene expression. Furthermore, additional drug perturbed gene expression measurements in in vitro cell lines could generate more predictive models; but, more importantly be used in conjunction with computational methods to discover important drug disease relationships.

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In vitro assessment of the inflammatory breast cancer cell line SUM 149: Discovery of two single nucleotide polymorphisms in the RNase L gene.

Journal of Clinical Oncology ◽

10.1200/jco.2011.29.27_suppl.196 ◽

2011 ◽

Vol 29 (27_suppl) ◽

pp. 196-196

Author(s):

B. T. Nokes ◽

H. Cunliffe ◽

A. R. Brown ◽

G. R. Sheth ◽

A. Stopeck ◽

...

Keyword(s):

Breast Cancer ◽

Cell Line ◽

Cell Lines ◽

Inflammatory Breast Cancer ◽

Dose Response ◽

The United States ◽

Specific Response ◽

Rnase L ◽

Single Nucleotide

196 Background: Inflammatory breast cancer (IBC) is a rare, aggressive form of breast cancer, accounting for 5% of breast cancers diagnosed annually in the United States. Understanding the distinct biology of IBC could help provide novel treatment targets. We sought to evaluate whether or not the IBC cell lines SUM 149 and SUM 190 demonstrated evidence of viral infection. Methods: We performed single nucleotide polymorphism (SNP) genotyping for 2 variants of the ribonuclease (RNase) L gene that have been correlated with the risk of prostate cancer due to a possible viral etiology. We also performed proliferation assays; developed dose response curves to assess the treatment effect of interferon-alpha (IFN-a); and assayed for evidence of the putative human mammary tumor virus (HMTV, which has been implicated but not definitively associated with IBC,) in the DNA and RNA of SUM 149 cells. Results: According to our allelic discrimination SNP assay, 2/2 IBC cell lines were homozygous for the 462 and 541 variants, whereas 0/10 non-IBC cell lines were homozygous positive for the 462 variant (p = 0.015) and 2/10 non-IBC cell lines contained homozygous alleles for the 541 variant (p = 0.52). We also found a dose and time-dependent decrease in the proliferation of SUM 149 IBC cells treated with IFN-a. In contrast, non-IBC cell lines did not show a dose-response decrease in cell proliferation. Our reverse transcriptase polymerase chain reaction (RT-PCR) and Southern blot analysis for the env/LTR and late LTR sequences of the putative HMTV revealed no evidence of the putative viral genome. Conclusions: We discovered 2 SNPs, in the 462 and 541 variants of the RNase L gene, that were homozygously mutated in IBC cell lines but the 462 variant was absent in non-IBC lines. Our discovery of these mutated SNPs present in IBC cell lines suggests a possible genetic risk factor for IBC. In our study, the IBC cell line SUM 149 demonstrated a direct and specific response to treatment with IFN-a, an antiviral agent. We noted no evidence of HMTV infection in that cell line. Further studies of the prevalence and significance of the RNase L 462 and 541 variants in human IBC tissue specimens are warranted to validate our in vitro findings.

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PharmacoDB: an integrative database for miningin vitrodrug screening studies

10.1101/195149 ◽

2017 ◽

Author(s):

Petr Smirnov ◽

Victor Kofia ◽

Alexander Maru ◽

Mark Freeman ◽

Chantal Ho ◽

...

Keyword(s):

Cell Line ◽

Cell Lines ◽

Large Scale ◽

Drug Response ◽

Chemical Compounds ◽

Integrative Analysis ◽

Multiple Drug ◽

List Type ◽

Pharmacogenomic Studies

ABSTRACTRecent pharmacogenomic studies profiled large panels of cancer cell lines against hundreds of approved drugs and experimental chemical compounds. The overarching goal of these screens is to measure sensitivity of cell lines to chemical perturbation, correlate these measures to genomic features, and thereby develop novel predictors of drug response. However, leveraging this valuable data is challenging due to the lack of standards for annotating cell lines and chemical compounds, and quantifying drug response. Moreover, it has been recently shown that the complexity and complementarity of the experimental protocols used in the field result in high levels of technical and biological variation in thein vitropharmacological profiles. There is therefore a need for new tools to facilitate rigorous comparison and integrative analysis of large-scale drug screening datasets. To address this issue, we have developed PharmacoDB (pharmacodb.pmgenomics.ca), a database integrating the largest pharmacogenomic studies published to date. Here, we describe how the curation of cell line and chemical compound identifiers maximizes the overlap between datasets and how users can leverage such data to compare and extract robust drug phenotypes. PharmacoDB provides a unique resource to mine a compendium of curated pharmacogenomic datasets that are otherwise disparate and difficult to integrate.Key pointsCuration of cell line and drug identifiers in the largest pharmacogenomic studies published to dateUniform processing of drug sensitivity data to reduce heterogeneity across studiesMultiple drug response summary metrics enabling visual comparison and integrative analysis

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Oral 25-Hydroxycholecalciferol Acts as an Agonist in the Duodenum of Mice and as Modeled in Cultured Human HT-29 and Caco2 Cells

Journal of Nutrition ◽

10.1093/jn/nxz261 ◽

2019 ◽

Vol 150 (3) ◽

pp. 427-433 ◽

Cited By ~ 1

Author(s):

Carmen J Reynolds ◽

Nicholas J Koszewski ◽

Ronald L Horst ◽

Donald C Beitz ◽

Jesse P Goff

Keyword(s):

Vitamin D ◽

Cytochrome P450 ◽

Dose Response ◽

Intestinal Lumen ◽

Maximal Response ◽

Response Analysis ◽

Cytochrome P450 Family ◽

Ht 29 ◽

25 Hydroxycholecalciferol

ABSTRACT Background 25-Hydroxycholecalciferol [25(OH)D] is the predominant circulating metabolite of vitamin D and serves as the precursor for 1α,25-dihydroxycholecalciferol [1,25(OH)2D], the hormonally active form. The presence of 1α-hydroxylase (1α-OHase) in the intestine suggests that 1,25(OH)2D can be produced from 25(OH)D, but the effects of oral 25(OH)D on the intestine have not been determined. Objectives We investigated the acute intestinal response to orally consumed 25(OH)D in mice by assessing mRNA induction of cytochrome p450 family 24 subfamily A member 1 (Cyp24), a vitamin D–dependent gene. The mechanism of action then was determined through in vitro analyses with Caco2 and HT-29 cells. Methods Adult male C57BL6 mice were given a single oral dose of 40, 80, 200, or 400 ng 25(OH)D (n = 4 per dose) or vehicle (n = 3), and then killed 4 h later to evaluate the duodenal expression of Cyp24 mRNA by qPCR and RNA in situ hybridization. The 25(OH)D-mediated response was also evaluated with Caco2 and HT-29 cells by inhibition assay and dose-response analysis. A cytochrome p450 family 27 subfamily B member 1 (CYP27B1) knockdown of HT-29 was created to compare the dose-response parameters with wild-type HT-29 cells. Results Oral 25(OH)D induced expression of Cyp24 mRNA in the duodenum of mice with 80 ng 25(OH)D by 3.3 ± 0.8 ΔΔCt compared with controls (P < 0.05). In vitro, both Caco2 and HT-29 cells responded to 25(OH)D treatment with 200-fold and 175-fold greater effective concentration at 50% maximal response than 1,25(OH)2D, yet inhibition of 1α-OHase and knockdown of CYP27B1 had no effect on the responses. Conclusions In mice, orally consumed 25(OH)D elicits a vitamin D–mediated response in the duodenum. In vitro assessments suggest that the response from 25(OH)D does not require activation by 1α-OHase and that 25(OH)D within the intestinal lumen acts as a vitamin D receptor agonist.

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Synergistic in Vitro Activity of MOR202, a Human CD38 Antibody, in Combination with Pomalidomide

Blood ◽

10.1182/blood.v124.21.5712.5712 ◽

2014 ◽

Vol 124 (21) ◽

pp. 5712-5712 ◽

Cited By ~ 4

Author(s):

Jan Endell ◽

Rainer Boxhammer ◽

Stefan Steidl

Keyword(s):

Cell Line ◽

Cell Lines ◽

Dose Response ◽

Target Cells ◽

High Potency ◽

Response Curves ◽

Effector Cells ◽

Direct Cytotoxicity ◽

Pre Treatment

Abstract Background: MOR202 is a fully human anti-CD38 antibody currently being tested in a Phase I/IIa clinical trial in multiple myeloma (MM). It mediates antibody-dependent cellular cytotoxicity (ADCC) and antibody-dependent cellular phagocytosis (ADCP) in MM cells with high potency (EC50 ~200 pM) representing a possible promising new therapy for MM patients. In this in vitro study, we evaluated the synergistic potential of MOR202 and pomalidomide (POM), a newly approved IMiD® immunomodulatory agent in MM therapy. Methods: Using flow cytometry analysis, POM was evaluated in relation to its effects on several parameters anticipated to be relevant for anti-tumor activity when combined with MOR202. This included the induction of direct cytotoxicity and CD38 upregulation in several MM cell lines, as well as the activation of human immune effector cells derived from peripheral blood mononuclear cells of healthy donors. On a functional level the interaction of MOR202 and POM was assessed using FACS-based ADCC assays. Different incubation schemes prior to the ADCC assays were evaluated in order to distinguish the influence of POM on ADCC activity when pre-incubated for 72 hours either on target or effector cells or on both in parallel. The observed combination effects were analyzed for synergistic potential. Experiments were carried out in triplicate and mean values (±SEM) were calculated. Results: POM as a single agent showed cytotoxic effects on MM cell lines with high potency (EC50 ~150 nM) and additionally induced an up to 2.7-fold upregulation of CD38 (EC50 ~20 nM) on CD38-expressing MM cell lines. Both effects were maximal at the last tested time point of 72 hours and strongest on cell lines with comparably lower CD38 expression levels. In combination with the observed activation of effector cells these POM-mediated mechanisms lead to a synergistically enhanced cytotoxic activity of MOR202. This synergistic benefit ranged between 1.2-fold and 3.1-fold above theoretical additivity depending on the cell line used and was most pronounced in the case of strong CD38 upregulation. Figure 1 Exemplary ADCC dose-response curves for the comparably lower CD38 expressing cell line AMO-1 after POM pre-treatment of effector cells, target cells or both. Figure 1. Exemplary ADCC dose-response curves for the comparably lower CD38 expressing cell line AMO-1 after POM pre-treatment of effector cells, target cells or both. Conclusions: The cytotoxic activity of MOR202 on MM cells was enhanced and synergized when combined with the immunomodulator agent POM via multiple mechanisms, namely direct cytotoxicity, CD38 upregulation and activation of effector cells. These results provide a mechanistic rationale for combining MOR202 and POM and warrant further evaluation in the clinical setting. Disclosures Endell: MorphoSys AG: Employment, Patents & Royalties. Boxhammer:Morphosys AG: Employment, Patents & Royalties. Steidl:MorphoSys AG: Employment, Patents & Royalties.

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