Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

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

REEPs Are Membrane Shaping Adapter Proteins That Modulate Specific G Protein-Coupled Receptor Trafficking by Affecting ER Cargo Capacity

<div><p>Receptor expression enhancing proteins (REEPs) were identified by their ability to enhance cell surface expression of a subset of G protein-coupled receptors (GPCRs), specifically GPCRs that have proven difficult to express in heterologous cell systems. Further analysis revealed that they belong to the Yip (Ypt-interacting protein) family and that some REEP subtypes affect ER structure. Yip family comparisons have established other potential roles for REEPs, including regulation of ER-Golgi transport and processing/neuronal localization of cargo proteins. However, these other potential REEP functions and the mechanism by which they selectively enhance GPCR cell surface expression have not been clarified. By utilizing several REEP family members (REEP1, REEP2, and REEP6) and model GPCRs (α2A and α2C adrenergic receptors), we examined REEP regulation of GPCR plasma membrane expression, intracellular processing, and trafficking. Using a combination of immunolocalization and biochemical methods, we demonstrated that this REEP subset is localized primarily to ER, but not plasma membranes. Single cell analysis demonstrated that these REEPs do not specifically enhance surface expression of all GPCRs, but affect ER cargo capacity of specific GPCRs and thus their surface expression. REEP co-expression with α2 adrenergic receptors (ARs) revealed that this REEP subset interacts with and alter glycosidic processing of α2C, but not α2A ARs, demonstrating selective interaction with cargo proteins. Specifically, these REEPs enhanced expression of and interacted with minimally/non-glycosylated forms of α2C ARs. Most importantly, expression of a mutant REEP1 allele (hereditary spastic paraplegia SPG31) lacking the carboxyl terminus led to loss of this interaction. Thus specific REEP isoforms have additional intracellular functions besides altering ER structure, such as enhancing ER cargo capacity, regulating ER-Golgi processing, and interacting with select cargo proteins. Therefore, some REEPs can be further described as ER membrane shaping adapter proteins.</p> </div

SGMF analysis of REEP membrane localization.

<p>To differentiate plasma and ER membrane localization of REEPs, sucrose gradient membrane fractionation (SGMF) analysis was performed with HEK293A cells transfected with HA-α2C ARs, and Flag-REEP1, -REEP2, or -REEP6. Forty-eight hrs post-transfection, total cell membranes were isolated and separated by layering upon a discontinuous sucrose gradient. Eleven fractions were collected and analyzed by SDS-PAGE and immunoblotting techniques. <b>Top</b>. Plasma and ER membrane fractions were detected by probing with antibodies against Na/K ATPase (<b>A</b>) or calnexin (<b>B</b>) respectively. Fractions containing lighter plasma membranes (#1-4) and heavier ER membranes (#6-11) are demarcated with bars above the fraction number. Molecular weight markers (<b>M</b>) and input loading control lanes (<b>I</b>) were also included. Note progression of α2C ARs (<b>C</b>) from ER to plasma membrane fractions, demonstrating increasing mature glycosylation in plasma membrane and decreasing immature glycosylation in ER membrane fractions (see <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0076366#pone-0076366-g010" target="_blank">Figure 10</a>). <b>Bottom</b>. Similar SGMF analysis of REEP1 (<b>D</b>), REEP2 (<b>E</b>), and REEP6 (<b>F</b>) demonstrating that all three REEPs tested were only found in heavier ER, but not plasma, membrane fractions. Mr standards (kDa) are indicated. Representative of three separate transfections.</p

Confocal REEP isoform co-localization.

<p>HEK293A cells were transfected with HA-REEP1 (carboxyl terminus HA-epitope tag) and either Flag-REEP1, Flag-REEP2, or Flag–REEP6 (carboxyl terminus Flag-epitope tag) cDNA. Forty-eight hrs post-transfections, cells were fixed with 4% PFA, permeabilized, and examined by confocal microscopy. Flag-REEPs (Left) were identified by FITC-M2 (anti-Flag) antisera and HA-REEP1 (Middle) was labeled with Alexa 594 anti-HA antisera. Merged images are shown (Right). Co-expression of HA-REEP1 and Flag-REEP1 showed tremendous overlap, as expected. Flag-REEP2 and HA-REEP1 showed multiple punctate regions of co-expression. However, Flag-REEP2 also exhibited further extensions devoid of HA-REEP1 expression. Lastly, Flag-REEP6 and HA-REEP1 demonstrated a large degree of co-localization. Representative of three separate transfections. Scale bars: 25 µm.</p

REEP co-expression enhances the presence of a lower molecular weight form of α2C ARs.

<p>HEK293A cells were transfected with either HA-α2A or -α2C ARs and control vector, Flag-REEP1, -REEP2, or –REEP6. Forty-eight hrs post-transfection, crude membranes were isolated and subjected to immunoblot analysis. Molecular weight markers (kDa) are shown to the left. <b>Top</b>: Co-expression of either REEP1, REEP2, or REEP6 with α2C AR correlated with an increased detection of a lower molecular weight form of α2C AR (arrow), not seen following co-expression with α2A ARs. <b>Bottom</b>: Immunoblot analysis of REEPs demonstrated similar levels of REEP1, REEP2, and REEP6 expression when co-expressed with either α2A or α2C ARs. Representative of three experiments.</p

In vivo biotinylation analysis of REEP plasma membrane expression.

<p>To determine if REEPs were expressed at the plasma membrane, HEK293A cells were transfected with Flag-REEP1, Flag-REEP2, or Flag–REEP6 cDNA with or without co-transfected HA-α2A AR or HA-α2C AR cDNAs. Forty-eight hrs post-transfections, cells were treated with the biotinylating reagent EZ-Link Sulfo-NHS-SS-Biotin (Pierce), total cell lysates were isolated, and biotinylated proteins were precipitated by incubation with avidin-agarose. Avidin precipitated proteins and total cell lysates (Input) were then analyzed by SDS-PAGE and immunoblotting techniques. Transferred proteins were probed with monoclonal anti-HA or anti-M2 Ab. Molecular weight markers (kDa) are shown to the left. <b>A</b>. <b>Top</b>: Mature glycosylated α2A and α2C ARs (thick arrow) were predominantly precipitated by avidin, consistent with selective biotinylation of plasma membrane proteins. Aggregated α2 ARs can be seen at the very op of the blot (*). <b>Bottom</b>: No REEPs were precipitated by avidin, demonstrating that they were not present at the plasma membrane, when either expressed with α2 ARs or alone. <b>B</b>. <b>Top</b>: Analysis of total cell lysates for α2A and α2C ARs demonstrated the presence of both mature (thick arrow) and immature forms (thin arrow). <b>Bottom</b>: Immunoblotting of total cell lysates for REEPs is shown, demonstrating strong REEP expression. Representative of three experiments.</p