This single-arm, phase I dose-escalation trial (NCT02983045) evaluated bempega ldesleukin (NKTR-214/BEMPEG), a CD122-preferential IL2 pathway agonist, plus nivolumab in 38 patients with selected immunotherapy-naïve advanced solid tumors (melanoma, renal cell carcinoma, and non-small cell lung cancer). Three dose-limiting toxicities were reported in 2 of 17 patients during dose escalation [hypotension ( n = 1), hyperglycemia ( n = 1), metabolic acidosis ( n = 1)]. The most common treatment-related adverse events (TRAE) were fl u-like symptoms (86.8%), rash (78.9%), fatigue (73.7%), and pruritus (52.6%). Eight patients (21.1%) experienced grade 3/4 TRAEs; there were no treatment-related deaths. Total objective response rate across tumor types and dose cohorts was 59.5% (22/37), with 7 complete responses (18.9%). Cellular and gene expression analysis of longitudinal tumor biopsies revealed increased infi ltration, activation, and cytotoxicity of CD8 + T cells, without regulatory T-cell enhancement. At the recommended phase II dose, BEMPEG 0.006 mg/kg plus nivolumab 360 mg every 3 weeks, the combination was well tolerated and demonstrated encouraging clinical activity irrespective of baseline PD-L1 status. SIGNIFICANCE: These data show that BEMPEG can be successfully combined with a checkpoint inhibitor as dual immunotherapy for a range of advanced solid tumors. Effi cacy was observed regardless of baseline PD-L1 status and baseline levels of tumor-infi ltrating lymphocytes, suggesting therapeutic potential for patients with poor prognostic risk factors for response to PD-1/PD-L1 blockade.

Elucidating the content of a DNA sequence is critical to deeper understand and decode the genetic information for any biological system. As next generation sequencing (NGS) techniques have become cheaper and more advanced in throughput over time, great innovations and breakthrough conclusions have been generated in various biological areas. Few of these areas, which get shaped by the new technological advances, involve evolution of species, microbial mapping, population genetics, genome-wide association studies (GWAs), comparative genomics, variant analysis, gene expression, gene regulation, epigenetics and personalized medicine. While NGS techniques stand as key players in modern biological research, the analysis and the interpretation of the vast amount of data that gets produced is a not an easy or a trivial task and still remains a great challenge in the field of bioinformatics. Therefore, efficient tools to cope with information overload, tackle the high complexity and provide meaningful visualizations to make the knowledge extraction easier are essential. In this article, we briefly refer to the sequencing methodologies and the available equipment to serve these analyses and we describe the data formats of the files which get produced by them. We conclude with a thorough review of tools developed to efficiently store, analyze and visualize such data with emphasis in structural variation analysis and comparative genomics. We finally comment on their functionality, strengths and weaknesses and we discuss how future applications could further develop in this field.

BackgroundProtein-Protein interactions (PPI) play a key role in determining the outcome of most cellular processes. The correct identification and characterization of protein interactions and the networks, which they comprise, is critical for understanding the molecular mechanisms within the cell. Large-scale techniques such as pull down assays and tandem affinity purification are used in order to detect protein interactions in an organism. Today, relatively new high-throughput methods like yeast two hybrid, mass spectrometry, microarrays, and phage display are also used to reveal protein interaction networks.ResultsIn this paper we evaluated four different clustering algorithms using six different interaction datasets. We parameterized the MCL, Spectral, RNSC and Affinity Propagation algorithms and applied them to six PPI datasets produced experimentally by Yeast 2 Hybrid (Y2H) and Tandem Affinity Purification (TAP) methods. The predicted clusters, so called protein complexes, were then compared and benchmarked with already known complexes stored in published databases.ConclusionsWhile results may differ upon parameterization, the MCL and RNSC algorithms seem to be more promising and more accurate at predicting PPI complexes. Moreover, they predict more complexes than other reviewed algorithms in absolute numbers. On the other hand the spectral clustering algorithm achieves the highest valid prediction rate in our experiments. However, it is nearly always outperformed by both RNSC and MCL in terms of the geometrical accuracy while it generates the fewest valid clusters than any other reviewed algorithm. This article demonstrates various metrics to evaluate the accuracy of such predictions as they are presented in the text below. Supplementary material can be found at: http://www.bioacademy.gr/bioinformatics/projects/ppireview.htm

2623 Background: PIVOT-02 is an ongoing phase 1/2 study of bempegaldesleukin (NKTR-214), a CD122-preferential IL-2 pathway agonist, plus nivolumab in patients with advanced solid tumors. Bempegaldesleukin (NKTR-214) increases proliferative tumor infiltrating lymphocytes (TIL) and cell surface PD-1 on immune cells and PD-L1 on tumor cells, demonstrating potential synergy with anti-PD-1 therapy. Pre-treatment tumor biopsies from metastatic 1L melanoma (MEL) and urothelial carcinoma (UC) patients were analyzed to correlate baseline immune phenotype to response. Methods: Pre-treatment TIL (CD8+ T cells/mm2 and %CD3+ by IHC; 29 MEL; 22 UC) were measured and divided into high and low groups based on median values. PD-L1 (% PD-L1 on tumor cells by IHC [28-8 PharmDx]; 33 MEL; 23 UC) was scored negative (<1%) or positive (≥1%). Interferon gamma gene score (IFNG; 11 MEL) was scored as high or low based on median p value of <0.1 for 15 genes (EdgeSeq). High and low groups were correlated with responses per RECIST 1.1. Results: Baseline demographics and prognostic factors were balanced in the biomarker subgroups. Response rates for response evaluable MEL and UC were 53% (SITC 2018) and 48% (ASCO-GU 2019), respectively. In MEL, median values of CD3-TIL and CD8-TIL were 19% and 203 cells/mm2, respectively. Response rate correlations were 67% and 20% with IFNG high and low, 79% and 29% with CD3-TIL high and low, 79% and 33% with CD8-TIL high and low, and 68% and 43% with PD-L1 positive and negative. Most importantly, responses were observed in patients with the least favorable tumor microenvironment, characterized as both PD-L1 negative and TIL low, with responses of 17% (1/6 CD8-TIL), and 25% (2/8 CD3-TIL), respectively. Similar correlative trends were observed in UC, with 50% (4/8 CD8-TIL) and 38% (3/8 CD3-TIL) responses in patients with least favorable microenvironment. Conclusions: The biomarker program included in PIVOT-02 identified baseline immune signatures correlated with response for MEL and UC. The response rates observed in both the favorable and unfavorable tumor microenvironments indicate the potential of this combination and support its broad development. Clinical trial information: NCT02983045.

2545 Background: NKTR-214 is a CD122-biased agonist designed to provide sustained signaling through the heterodimeric IL-2 receptor pathway (IL-2Rβɣ) to preferentially activate and expand effector CD8+ T and NK cells over T regulatory cells in the tumor microenvironment. Immune changes in the tumor microenvironment after NKTR-214 treatment was assessed in patients with locally advanced or metastatic solid tumors. Methods: NKTR-214 was administered IV in an outpatient setting q2w or q3w. Serial blood and tumor tissue samples were collected to measure immune activation using immunophenotyping including flow cytometry, immunohistochemistry (IHC), T cell clonality and gene expression analyses. Results: 26 patients (pts) have been treated with NKTR-214 at q3w, 4@0.003, 9@0.006, 6@0.009 and 1@0.012 mg/kg. Six pts received 0.006 mg/kg q2w. 58% of pts had prior immunotherapy. The most common Gr1-2 TRAEs were fatigue (73%) and pruritus (65%), and decreased appetite (46%). One pt experienced Gr3 syncope and hypotension at the highest dose tested and continued treatment at a lower dose. No drug-related AEs led to study discontinuation. No immune-related AEs or capillary leak syndrome were observed. 6 pts (23%) experienced tumor shrinkage from 10-30%. Three immunotherapy naïve pts receiving sequential anti-PD1 therapy, after ending treatment with NKTR-214, experienced significant tumor regression at first scan. In all pts evaluated, blood samples showed increases in newly proliferating (Ki67+) T and NK cells 8 days post dose. Flow cytometry and/or IHC revealed an up to 10-fold increase from baseline in tumor CD8+T and NK cells in the tumor microenvironment, with minimal changes to Tregs. PD-1 expression increased 2-fold in TILs. Gene expression analysis of tumor tissue showed increases in several immune checkpoint genes, cytotoxic markers (IFNg, PRF1, and GZMB), as well as a dynamic change in T cell clonality. Conclusions: Based on a favorable safety profile and strong correlative biomarker data, a phase 1/2 trial combining NKTR-214 and nivolumab is currently enrolling. Clinical trial information: NCT02869295.