Proceedings of the 13th annual conference of INEBRIA

CITATION: Watson, R., et al. 2016. Proceedings of the 13th annual conference of INEBRIA. Addiction Science & Clinical Practice, 11:13, doi:10.1186/s13722-016-0062-9.The original publication is available at https://ascpjournal.biomedcentral.comENGLISH SUMMARY : Meeting abstracts.https://ascpjournal.biomedcentral.com/articles/10.1186/s13722-016-0062-9Publisher's versio

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

Applications of nanoparticles to diagnostics and therapeutics in colorectal cancer

Nanotechnology has considerable promise for the detection, staging and treatment of cancer. Here, we outline one such promising application: the use of nanostructures with surface-bound ligands for the targeted delivery and ablation of colorectal cancer (CRC), the third most common malignancy and the second most common cause of cancer-related mortality in the US. Normal colonic epithelial cells as well as primary CRC and metastatic tumors all express a unique surface-bound guanylyl cyclase C (GCC), which binds the diarrheagenic bacterial heat-stable peptide enterotoxin ST. This makes GCC a potential target for metastatic tumor ablation using ST-bound nanoparticles in combination with thermal ablation with near-infrared or radiofrequency energy absorption. Furthermore, the incorporation of iron or iron oxide into such structures would provide advantages for magnetic resonance imaging (MRI). Although the scenarios outlined in this article are hypothetical, they might stimulate ideas about how other cancers could be attacked using nanotechnology

Identification and Characterization of Proteins Involved in Nuclear Organization Using <em>Drosophila</em> GFP Protein Trap Lines

<div><h3>Background</h3><p>Strains from a collection of <em>Drosophila</em> GFP protein trap lines express GFP in the normal tissues where the endogenous protein is present. This collection can be used to screen for proteins distributed in the nucleus in a non-uniform pattern.</p> <h3>Methodology/Principal Findings</h3><p>We analyzed four lines that show peripheral or punctate nuclear staining. One of these lines affects an uncharacterized gene named <em>CG11138</em>. The CG11138 protein shows a punctate distribution in the nuclear periphery similar to that of <em>Drosophila</em> insulator proteins but does not co-localize with known insulators. Interestingly, mutations in Lamin proteins result in alterations in CG11138 localization, suggesting that this protein may be a novel component of the nuclear lamina. A second line affects the <em>Decondensation factor 31</em> (<em>Df31</em>) gene, which encodes a protein with a unique nuclear distribution that appears to segment the nucleus into four different compartments. The X-chromosome of males is confined to one of these compartments. We also find that <em>Drosophila</em> Nucleoplasmin (dNlp) is present in regions of active transcription. Heat shock leads to loss of dNlp from previously transcribed regions of polytene chromosome without redistribution to the heat shock genes. Analysis of Stonewall (Stwl), a protein previously found to be necessary for the maintenance of germline stem cells, shows that Stwl is present in a punctate pattern in the nucleus that partially overlaps with that of known insulator proteins. Finally we show that Stwl, dNlp, and Df31 form part of a highly interactive network. The properties of other components of this network may help understand the role of these proteins in nuclear biology.</p> <h3>Conclusions/Significance</h3><p>These results establish screening of GFP protein trap alleles as a strategy to identify factors with novel cellular functions. Information gained from the analysis of CG11138 Stwl, dNlp, and Df31 sets the stage for future studies of these proteins.</p> </div

Stwl expression in germline stem and differentiated cells.

<p>Panels (A–D) show the germarium of a single ovariole in the ovary (lower portion of panels) as well as an early stage egg chamber (upper portion of panel). In (A) nuclei are labeled with DAPI, (B) shows α-Stwl staining, (C) outlines the germline stem cells (arrowhead) using α-Vasa and (D) shows the merged image. Stwl colocalizes with CP190 in ovarian somatic cells. Panels (E–N) show Stwl and CP190 colocalization in terminal filament cells (E–H), follicle cells (I–K), and imaginal disc cells (L–N); DAPI is blue (E), α- Stwl is red (F, I and L), α-CP190 is green (G, J and M) and in the merged panels yellow regions show colocalization (H, K and N).</p

Distribution of dNLP in various cell types.

<p>(A–C) dNLP-GFP flourescence in diploid cells from third instar larvae imaginal tissue from a dNLP protein-trap allele; DAPI (A), dNLP-GFP (B) and merged (C). Panels (D–G) depict dNLP localization in both somatic and germline cell nuclei including the oocyte nucleus (arrowhead in F and G); (D) DAPI, (E) α- Lamin Dm0, (F) α-dNLP and (G) merged. Panels H and I show dNLP-GFP fluorescence in an egg from a dNLP protein-trap allele (H) as compared to a wild type egg (I) indicating that dNLP-GFP is being dumped into the developing egg of the protein-trap allele. Panels J-N show Kc cells labeled with DAPI- blue, α-dNLP- red and α-H3S10ph-green in interphase (J), prophase (K), metaphase (L), anaphase (M) and telophase (N); the results suggest that dNLP is not associated with condensed chromosomes during metaphase. Panels (O–V). (O–R) show polytene chromosomes from wild type third instar larvae prior to heat shock while (S–V) show chromosomes from larvae subjected to a 20 min heat shock at 37°C. dNLP is broadly present in interbands and frequently colocalizes with RNA Pol II phosphorylated at Ser5 on the non-heats hocked polytene chromosomes. dNLP seems to become more diffuse and dissociate from the DNA following heat shock. The distribution of dNLP is particularly weak at the heat shock puffs, which are the only sites of transcription following temperature elevation (S–V). (O and S)-DAPI, (P and T)-α-dNLP, (Q and U)-α-PolII^ser5 and (R and V)-merged.</p

CG11138 does not significantly colocalize with insulator proteins on polytene chromosomes or in diploid cells.

<p>Panels (A–D) show labeling of polytene chromosomes with DAPI (A), α-CG11138 (B), α-Mod(mdg4)2.2 (C) as well as the merged image (D). Panels E–H show an enlarged portion of the chromosome displayed in panels A–D in the region defined by the white arrows. Panels I–L show a second region of a different chromosome labeled with antibodies to CG11138 and Mod(mdg4)2.2, further underscoring the limited amount of colocalization between these two proteins. Panels M-O show diploid cells from OR third instar imaginal tissue labeled with DAPI (M), α- CG11138 (N) and α-CP190 (O). Panel P shows the merged image indicating that CP190 and CG11138 do not overlap in diploid cells and specifically the bodies formed by each protein appear mutually exclusive. Panels Q–T show diploid cells from OR third instar imaginal tissue labeled with DAPI (Q), α- CG11138 (R) and α-dTopors (S). Panel T shows the merged image indicating that dTopors and CG11138 do not significantly overlap in diploid cells and specifically the bodies formed by each protein appear mutually exclusive with some exceptions were they seem to overlap.</p

dNlp, Stwl and Df31 form part of a protein interaction network.

<p>A matrix of <i>Drosophila</i> interacting proteins was imported into Cytoscape and a child network was created by selecting the dNlp, Stwl and Df31 nodes plus all adjacent edges. For easier visualization, single nodes were deleted with the exception of those shown, which correspond to proteins of special interest. All other interactions are shown.</p