A genomic biomarker signature can predict skin sensitizers using a cell-based in vitro alternative to animal tests

<p>Abstract</p> <p>Background</p> <p>Allergic contact dermatitis is an inflammatory skin disease that affects a significant proportion of the population. This disease is caused by an adverse immune response towards chemical haptens, and leads to a substantial economic burden for society. Current test of sensitizing chemicals rely on animal experimentation. New legislations on the registration and use of chemicals within pharmaceutical and cosmetic industries have stimulated significant research efforts to develop alternative, human cell-based assays for the prediction of sensitization. The aim is to replace animal experiments with in vitro tests displaying a higher predictive power.</p> <p>Results</p> <p>We have developed a novel cell-based assay for the prediction of sensitizing chemicals. By analyzing the transcriptome of the human cell line MUTZ-3 after 24 h stimulation, using 20 different sensitizing chemicals, 20 non-sensitizing chemicals and vehicle controls, we have identified a biomarker signature of 200 genes with potent discriminatory ability. Using a Support Vector Machine for supervised classification, the prediction performance of the assay revealed an area under the ROC curve of 0.98. In addition, categorizing the chemicals according to the LLNA assay, this gene signature could also predict sensitizing potency. The identified markers are involved in biological pathways with immunological relevant functions, which can shed light on the process of human sensitization.</p> <p>Conclusions</p> <p>A gene signature predicting sensitization, using a human cell line in vitro, has been identified. This simple and robust cell-based assay has the potential to completely replace or drastically reduce the utilization of test systems based on experimental animals. Being based on human biology, the assay is proposed to be more accurate for predicting sensitization in humans, than the traditional animal-based tests.</p

31st Annual Meeting and Associated Programs of the Society for Immunotherapy of Cancer (SITC 2016) : part two

Background The immunological escape of tumors represents one of the main ob- stacles to the treatment of malignancies. The blockade of PD-1 or CTLA-4 receptors represented a milestone in the history of immunotherapy. However, immune checkpoint inhibitors seem to be effective in specific cohorts of patients. It has been proposed that their efficacy relies on the presence of an immunological response. Thus, we hypothesized that disruption of the PD-L1/PD-1 axis would synergize with our oncolytic vaccine platform PeptiCRAd. Methods We used murine B16OVA in vivo tumor models and flow cytometry analysis to investigate the immunological background. Results First, we found that high-burden B16OVA tumors were refractory to combination immunotherapy. However, with a more aggressive schedule, tumors with a lower burden were more susceptible to the combination of PeptiCRAd and PD-L1 blockade. The therapy signifi- cantly increased the median survival of mice (Fig. 7). Interestingly, the reduced growth of contralaterally injected B16F10 cells sug- gested the presence of a long lasting immunological memory also against non-targeted antigens. Concerning the functional state of tumor infiltrating lymphocytes (TILs), we found that all the immune therapies would enhance the percentage of activated (PD-1pos TIM- 3neg) T lymphocytes and reduce the amount of exhausted (PD-1pos TIM-3pos) cells compared to placebo. As expected, we found that PeptiCRAd monotherapy could increase the number of antigen spe- cific CD8+ T cells compared to other treatments. However, only the combination with PD-L1 blockade could significantly increase the ra- tio between activated and exhausted pentamer positive cells (p= 0.0058), suggesting that by disrupting the PD-1/PD-L1 axis we could decrease the amount of dysfunctional antigen specific T cells. We ob- served that the anatomical location deeply influenced the state of CD4+ and CD8+ T lymphocytes. In fact, TIM-3 expression was in- creased by 2 fold on TILs compared to splenic and lymphoid T cells. In the CD8+ compartment, the expression of PD-1 on the surface seemed to be restricted to the tumor micro-environment, while CD4 + T cells had a high expression of PD-1 also in lymphoid organs. Interestingly, we found that the levels of PD-1 were significantly higher on CD8+ T cells than on CD4+ T cells into the tumor micro- environment (p < 0.0001). Conclusions In conclusion, we demonstrated that the efficacy of immune check- point inhibitors might be strongly enhanced by their combination with cancer vaccines. PeptiCRAd was able to increase the number of antigen-specific T cells and PD-L1 blockade prevented their exhaus- tion, resulting in long-lasting immunological memory and increased median survival

Genome-wide comparison of phage M13-infected vs. uninfected Escherichia coli

To identify Escherichia coli genes potentially regulated by filamentous phage infection, we used oligonucleotide microarrays. Genome-wide comparison of phage M13-infected and uninfected E. coli, 2 and 20 min after infection, was performed. The analysis revealed altered transcription levels of 12 E. coli genes in response to phage infection, and the observed regulation of phage genes correlated with the known in vivo pattern of M13 mRNA species. Ten of the 12 host genes affected could be grouped into 3 different categories based on cellular function, suggesting a coordinated response. The significantly upregulated genes encode proteins involved in reactions of the energy-generating phosphotransferase system and transcription processing, which could be related to phage transcription. No genes belonging to any known E. coli stress response pathways were scored as upregulated. Furthermore, phage infection led to significant downregulation of transcripts of the bacterial genes gadA, gadB, hdeA, gadE, slp, and crl. These downregulated genes are normally part of the host stress response mechanisms that protect the bacterium during conditions of acid stress and stationary phase transition. The phage-infected cells demonstrated impaired function of the oxidative and the glutamate-dependent acid resistance systems. Thus, global transcriptional analysis and functional analysis revealed previously unknown host responses to filamentous phage infection

The GARD assay for assessment of chemical skin sensitizers.

Allergic contact dermatitis is a skin disease caused by an immunologic reaction to low molecular weight compounds, so called haptens. These substances are commonly present in products used by humans in daily life, such as in cosmetics and fragrances, as well as within chemical industry and in pharmaceuticals. The frequent usage of these compounds in different applications has led to increasing incidences of allergic contact dermatitis, which has become a substantial economic burden for society. As a consequence, chemicals are routinely tested for their ability to induce skin sensitization, using animal models such as the murine Local Lymph Node Assay. However, recent legislations regulate the use of animal models within chemical testing. Thus, there is an urgent need for in vitro alternatives to replace these assays for safety assessment of chemicals. Recently, we identified a signature of predictive genes, which are differentially regulated in the human myeloid cell-line MUTZ-3 when stimulated with sensitizing compounds compared to non-sensitizing compounds. Based on these findings, we have formulated a test strategy for assessment of sensitizing compounds, called Genomic Allergen Rapid Detection, GARD. In this paper, we present a detailed method description of how the assay should be performed

Evaluation of high throughput gene expression platforms using a genomic biomarker signature for prediction of skin sensitization.

Allergic contact dermatitis (ACD) develops upon exposure to certain chemical compounds termed skin sensitizers. To reduce the occurrence of skin sensitizers, chemicals are regularly screened for their capacity to induce sensitization. The recently developed Genomic Allergen Rapid Detection (GARD) assay is an in vitro alternative to animal testing for identification of skin sensitizers, classifying chemicals by evaluating transcriptional levels of a genomic biomarker signature. During assay development and biomarker identification, genome-wide expression analysis was applied using microarrays covering approximately 30,000 transcripts. However, the microarray platform suffers from drawbacks in terms of low sample throughput, high cost per sample and time consuming protocols and is a limiting factor for adaption of GARD into a routine assay for screening of potential sensitizers. With the purpose to simplify assay procedures, improve technical parameters and increase sample throughput, we assessed the performance of three high throughput gene expression platforms - nCounter®, BioMark HD™ and OpenArray® - and correlated their performance metrics against our previously generated microarray data. We measured the levels of 30 transcripts from the GARD biomarker signature across 48 samples. Detection sensitivity, reproducibility, correlations and overall structure of gene expression measurements were compared across platforms

Skin sensitizers differentially regulate signaling pathways in MUTZ-3 cells in relation to their individual potency.

Due to the recent European legislations posing a ban of animal tests for safety assessment within the cosmetic industry, development of in vitro alternatives for assessment of skin sensitization is highly prioritized. To date, proposed in vitro assays are mainly based on single biomarkers, which so far have not been able to classify and stratify chemicals into subgroups, related to risk or potency

Prediction of chemical respiratory sensitizers using GARD, a novel in vitro assay based on a genomic biomarker signature.

Repeated exposure to certain low molecular weight (LMW) chemical compounds may result in development of allergic reactions in the skin or in the respiratory tract. In most cases, a certain LMW compound selectively sensitize the skin, giving rise to allergic contact dermatitis (ACD), or the respiratory tract, giving rise to occupational asthma (OA). To limit occurrence of allergic diseases, efforts are currently being made to develop predictive assays that accurately identify chemicals capable of inducing such reactions. However, while a few promising methods for prediction of skin sensitization have been described, to date no validated method, in vitro or in vivo, exists that is able to accurately classify chemicals as respiratory sensitizers.Recently, we presented the in vitro based Genomic Allergen Rapid Detection (GARD) assay as a novel testing strategy for classification of skin sensitizing chemicals based on measurement of a genomic biomarker signature. We have expanded the applicability domain of the GARD assay to classify also respiratory sensitizers by identifying a separate biomarker signature containing 389 differentially regulated genes for respiratory sensitizers in comparison to non-respiratory sensitizers. By using an independent data set in combination with supervised machine learning, we validated the assay, showing that the identified genomic biomarker is able to accurately classify respiratory sensitizers.We have identified a genomic biomarker signature for classification of respiratory sensitizers. Combining this newly identified biomarker signature with our previously identified biomarker signature for classification of skin sensitizers, we have developed a novel in vitro testing strategy with a potent ability to predict both skin and respiratory sensitization in the same sample

Multimodel Pathway Enrichment Methods for Functional Evaluation of Expression Regulation.

Functional analysis of quantitative expression data is becoming common practice within the proteomics and transcriptomics fields; however, a gold standard for this type of analysis has yet not emerged. To grasp the systemic changes in biological systems, efficient and robust methods are needed for data analysis following expression regulation experiments. We discuss several conceptual and practical challenges potentially hindering the emergence of such methods and present a novel method, called FEvER, that utilizes two enrichment models in parallel. We also present analysis of three disparate differential expression data sets using our method and compare our results to other established methods. With many useful features such as pathway hierarchy overview, we believe the FEvER method and its software implementation will provide a useful tool for peers in the field of proteomics. Furthermore, we show that the method is also applicable to other types of expression data

A carbohydrate binding module as a diversity-carrying scaffold

The growing field of biotechnology is in constant need of binding proteins with novel properties. Not just binding specificities and affinities but also structural stability and productivity are important characteristics for the purpose of large-scale applications. In order to find such molecules, libraries are created by diversifying naturally occurring binding proteins, which in those cases serve as scaffolds. In this study, we investigated the use of a thermostable carbohydrate binding module, CBM4-2, from a xylanase found in Rhodothermus marinus, as a diversity-carrying scaffold. A combinatorial library was created by introducing restricted variation at 12 positions in the carbohydrate binding site of the CBM4-2. Despite the small size of the library (1.6x10(6) clones), variants specific towards different carbohydrate polymers (birchwood xylan, Avicel and ivory nut mannan) as well as a glycoprotein (human IgG4) were successfully selected for, using the phage display method. Investigated clones showed a high productivity (on average 69 mg of purified protein/l shake flask culture) when produced in Escherichia coli and they were all stable molecules displaying a high melting transition temperature (75.7 +/- 5.3degreesC). All our results demonstrate that the CBM4-2 molecule is a suitable scaffold for creating variants useful in different biotechnological applications