Neoadjuvant Pembrolizumab and High-Dose IFNα-2b in Resectable Regionally Advanced Melanoma.

PURPOSE: Neoadjuvant immunotherapy may improve the clinical outcome of regionally advanced operable melanoma and allows for rapid clinical and pathologic assessment of response. We examined neoadjuvant pembrolizumab and high-dose IFNα-2b (HDI) therapy in patients with resectable advanced melanoma. PATIENTS AND METHODS: Patients with resectable stage III/IV melanoma were treated with concurrent pembrolizumab 200 mg i.v. every 3 weeks and HDI 20 MU/m2/day i.v., 5 days per week for 4 weeks, then 10 MU/m2/day subcutaneously 3 days per week for 2 weeks. Definitive surgery followed, as did adjuvant combination immunotherapy, completing a year of treatment. Primary endpoint was safety of the combination. Secondary endpoints included overall response rate (ORR), pathologic complete response (pCR), recurrence-free survival (RFS), and overall survival (OS). Blood samples for correlative studies were collected throughout. Tumor tissue was assessed by IHC and flow cytometry at baseline and at surgery. RESULTS: A total of 31 patients were enrolled, and 30 were evaluable. At data cutoff (October 2, 2019), median follow-up for OS was 37.87 months (range, 33.2-43.47). Median OS and RFS were not reached. Radiographic ORR was 73.3% [95% confidence interval (CI): 55.5-85.8], with a 43% (95% CI: 27.3-60.1) pCR rate. None of the patients with a pCR have had a recurrence. HDI and pembrolizumab were discontinued in 73% and 43% of patients, respectively. Correlative analyses suggested that intratumoral PD-1/PD-L1 interaction and HLA-DR expression are associated with pCR (P = 0.002 and P = 0.008, respectively). CONCLUSIONS: Neoadjuvant concurrent HDI and pembrolizumab demonstrated promising clinical activity despite high rates of treatment discontinuation. pCR is a prognostic indicator.See related commentary by Menzies et al., p. 4133.

Multimarker scores of Th1 and Th2 immune cellular profiles in peripheral blood predict response and immune related toxicity with CTLA4 blockade and IFNα in melanoma.

Neoadjuvant therapy with ipilimumab in combination with high dose IFNα was evaluated in patients with locally/regionally advanced melanoma in a previously reported clinical trial [NCT01608594]. In this study, peripheral immune cell profiling was performed in order to investigate the underlying mechanisms of tumor immune susceptibility and resistance. Peripheral blood mononuclear cells (PBMCs) from treated patients (N = 28) were collected at baseline and then at 6-weeks, 3-months and 12-months. High complexity (14-color) flow cytometry, designed to detect key immunological biomarkers was used to evaluate the frequencies of immune cell subsets. Statistical significance was determined using R-package employing Kruskal's test. We found that higher levels of Th1 cells at baseline (defined as CD45RA- CCR6- CXCR3+ CCR4-) correlated with the preoperative radiological response (p = 0.007) while higher Th2 cells (defined as CD45RA- CCR6- CXCR3- CCR4+) were associated with progressive disease (p = 0.009). A multimarker score consisting of higher levels of Th1 cells and CD8+ central memory T-cells was associated with pathologic complete response (pCR) (p = 0.041) at surgical resection. On the other hand, high TIM3 expression on T-cells correlated with gross viable tumor (p = 0.047). With regard to immune related toxicity, higher levels of phenotypically naive (defined as CCR7+CD45RA+) and effector memory (defined as CCR7-CD45RO+) CD8+ T-cells (p = 0.014) or lower levels of Th2 cells were associated with lower toxicity (p = 0.024). Furthermore, a multimarker score consisting of higher CD19+ and CD8+ cells was associated with lower toxicity (p = 0.0014). In conclusion, our study yielded mechanistic insights related to the immune impact of CTLA4 blockade and IFNα and potential biomarkers of immune response and toxicity.

Eight Genome Sequences of Cluster BE1 Phages That Infect Streptomyces Species.

Cluster BE1 Streptomyces bacteriophages belong to the Siphoviridae, with genome sizes over 130 kbp, and they contain direct terminal repeats of approximately 11 kbp. Eight newly isolated closely related cluster BE1 phages contain 43 to 48 tRNAs, one transfer-messenger RNA (tmRNA), and 216 to 236 predicted open reading frames (ORFs), but few of their genes are shared with other phages, including those infecting Streptomyces species.

CHSalign: A Web Server That Builds upon Junction-Explorer and RNAJAG for Pairwise Alignment of RNA Secondary Structures with Coaxial Helical Stacking.

RNA junctions are important structural elements of RNA molecules. They are formed when three or more helices come together in three-dimensional space. Recent studies have focused on the annotation and prediction of coaxial helical stacking (CHS) motifs within junctions. Here we exploit such predictions to develop an efficient alignment tool to handle RNA secondary structures with CHS motifs. Specifically, we build upon our Junction-Explorer software for predicting coaxial stacking and RNAJAG for modelling junction topologies as tree graphs to incorporate constrained tree matching and dynamic programming algorithms into a new method, called CHSalign, for aligning the secondary structures of RNA molecules containing CHS motifs. Thus, CHSalign is intended to be an efficient alignment tool for RNAs containing similar junctions. Experimental results based on thousands of alignments demonstrate that CHSalign can align two RNA secondary structures containing CHS motifs more accurately than other RNA secondary structure alignment tools. CHSalign yields a high score when aligning two RNA secondary structures with similar CHS motifs or helical arrangement patterns, and a low score otherwise. This new method has been implemented in a web server, and the program is also made freely available, at http://bioinformatics.njit.edu/CHSalign/.

Conservation of writhe helicity under anti-parallel reconnection.

Reconnection is a fundamental event in many areas of science, from the interaction of vortices in classical and quantum fluids, and magnetic flux tubes in magnetohydrodynamics and plasma physics, to the recombination in polymer physics and DNA biology. By using fundamental results in topological fluid mechanics, the helicity of a flux tube can be calculated in terms of writhe and twist contributions. Here we show that the writhe is conserved under anti-parallel reconnection. Hence, for a pair of interacting flux tubes of equal flux, if the twist of the reconnected tube is the sum of the original twists of the interacting tubes, then helicity is conserved during reconnection. Thus, any deviation from helicity conservation is entirely due to the intrinsic twist inserted or deleted locally at the reconnection site. This result has important implications for helicity and energy considerations in various physical contexts.

Comparative genomics of Cluster O mycobacteriophages.

Mycobacteriophages--viruses of mycobacterial hosts--are genetically diverse but morphologically are all classified in the Caudovirales with double-stranded DNA and tails. We describe here a group of five closely related mycobacteriophages--Corndog, Catdawg, Dylan, Firecracker, and YungJamal--designated as Cluster O with long flexible tails but with unusual prolate capsids. Proteomic analysis of phage Corndog particles, Catdawg particles, and Corndog-infected cells confirms expression of half of the predicted gene products and indicates a non-canonical mechanism for translation of the Corndog tape measure protein. Bioinformatic analysis identifies 8-9 strongly predicted SigA promoters and all five Cluster O genomes contain more than 30 copies of a 17 bp repeat sequence with dyad symmetry located throughout the genomes. Comparison of the Cluster O phages provides insights into phage genome evolution including the processes of gene flux by horizontal genetic exchange.

Graph-based sampling for approximating global helical topologies of RNA.

A current challenge in RNA structure prediction is the description of global helical arrangements compatible with a given secondary structure. Here we address this problem by developing a hierarchical graph sampling/data mining approach to reduce conformational space and accelerate global sampling of candidate topologies. Starting from a 2D structure, we construct an initial graph from size measures deduced from solved RNAs and junction topologies predicted by our data-mining algorithm RNAJAG trained on known RNAs. We sample these graphs in 3D space guided by knowledge-based statistical potentials derived from bending and torsion measures of internal loops as well as radii of gyration for known RNAs. Graph sampling results for 30 representative RNAs are analyzed and compared with reference graphs from both solved structures and predicted structures by available programs. This comparison indicates promise for our graph-based sampling approach for characterizing global helical arrangements in large RNAs: graph rmsds range from 2.52 to 28.24 Å for RNAs of size 25-158 nucleotides, and more than half of our graph predictions improve upon other programs. The efficiency in graph sampling, however, implies an additional step of translating candidate graphs into atomic models. Such models can be built with the same idea of graph partitioning and build-up procedures we used for RNA design.

Novel features for identifying A-minors in three-dimensional RNA molecules.

RNA tertiary interactions or tertiary motifs are conserved structural patterns formed by pairwise interactions between nucleotides. They include base-pairing, base-stacking, and base-phosphate interactions. A-minor motifs are the most common tertiary interactions in the large ribosomal subunit. The A-minor motif is a nucleotide triple in which minor groove edges of an adenine base are inserted into the minor groove of neighboring helices, leading to interaction with a stabilizing base pair. We propose here novel features for identifying and predicting A-minor motifs in a given three-dimensional RNA molecule. By utilizing the features together with machine learning algorithms including random forests and support vector machines, we show experimentally that our approach is capable of predicting A-minor motifs in the given RNA molecule effectively, demonstrating the usefulness of the proposed approach. The techniques developed from this work will be useful for molecular biologists and biochemists to analyze RNA tertiary motifs, specifically A-minor interactions.

Predicting helical topologies in RNA junctions as tree graphs.

RNA molecules are important cellular components involved in many fundamental biological processes. Understanding the mechanisms behind their functions requires knowledge of their tertiary structures. Though computational RNA folding approaches exist, they often require manual manipulation and expert intuition; predicting global long-range tertiary contacts remains challenging. Here we develop a computational approach and associated program module (RNAJAG) to predict helical arrangements/topologies in RNA junctions. Our method has two components: junction topology prediction and graph modeling. First, junction topologies are determined by a data mining approach from a given secondary structure of the target RNAs; second, the predicted topology is used to construct a tree graph consistent with geometric preferences analyzed from solved RNAs. The predicted graphs, which model the helical arrangements of RNA junctions for a large set of 200 junctions using a cross validation procedure, yield fairly good representations compared to the helical configurations in native RNAs, and can be further used to develop all-atom models as we show for two examples. Because junctions are among the most complex structural elements in RNA, this work advances folding structure prediction methods of large RNAs. The RNAJAG module is available to academic users upon request.

A computational approach to finding RNA tertiary motifs in genomic sequences: a case study.

Motif finding in DNA, RNA and proteins plays an important role in life science research. Recent patents concerning motif finding in biomolecular data are recorded in the DNA Patent Database which serves as a resource for policy makers and members of the general public interested in fields like genomics, genetics and biotechnology. In this paper, we present a computational approach to mining for RNA tertiary motifs in genomic sequences. Specifically, we describe a method, named CSminer, and show, as a case study, the application of CSminer to genome-wide search for coaxial helical stackings in RNA 3-way junctions. A coaxial helical stacking occurs in an RNA 3-way junction where two separate helical elements form a pseudocontiguous helix and provide thermodynamic stability to the RNA molecule as a whole. Experimental results demonstrate the effectiveness of our approach.

Predicting coaxial helical stacking in RNA junctions.

RNA junctions are important structural elements that form when three or more helices come together in space in the tertiary structures of RNA molecules. Determining their structural configuration is important for predicting RNA 3D structure. We introduce a computational method to predict, at the secondary structure level, the coaxial helical stacking arrangement in junctions, as well as classify the junction topology. Our approach uses a data mining approach known as random forests, which relies on a set of decision trees trained using length, sequence and other variables specified for any given junction. The resulting protocol predicts coaxial stacking within three- and four-way junctions with an accuracy of 81% and 77%, respectively; the accuracy increases to 83% and 87%, respectively, when knowledge from the junction family type is included. Coaxial stacking predictions for the five to ten-way junctions are less accurate (60%) due to sparse data available for training. Additionally, our application predicts the junction family with an accuracy of 85% for three-way junctions and 74% for four-way junctions. Comparisons with other methods, as well applications to unsolved RNAs, are also presented. The web server Junction-Explorer to predict junction topologies is freely available at: http://bioinformatics.njit.edu/junction.

Computational approaches to RNA structure prediction, analysis, and design.

RNA molecules are important cellular components involved in many fundamental biological processes. Understanding the mechanisms behind their functions requires RNA tertiary structure knowledge. Although modeling approaches for the study of RNA structures and dynamics lag behind efforts in protein folding, much progress has been achieved in the past two years. Here, we review recent advances in RNA folding algorithms, RNA tertiary motif discovery, applications of graph theory approaches to RNA structure and function, and in silico generation of RNA sequence pools for aptamer design. Advances within each area can be combined to impact many problems in RNA structure and function.

Computational approaches to 3D modeling of RNA.

Many exciting discoveries have recently revealed the versatility of RNA and its importance in a variety of functions within the cell. Since the structural features of RNA are of major importance to their biological function, there is much interest in predicting RNA structure, either in free form or in interaction with various ligands, including proteins, metabolites and other molecules. In recent years, an increasing number of researchers have developed novel RNA algorithms for predicting RNA secondary and tertiary structures. In this review, we describe current experimental and computational advances and discuss recent ideas that are transforming the traditional view of RNA folding. To evaluate the performance of the most recent RNA 3D folding algorithms, we provide a comparative study in order to test the performance of available 3D structure prediction algorithms for an RNA data set of 43 structures of various lengths and motifs. We find that the algorithms vary widely in terms of prediction quality across different RNA lengths and topologies; most predictions have very large root mean square deviations from the experimental structure. We conclude by outlining some suggestions for future RNA folding research.

Tertiary motifs revealed in analyses of higher-order RNA junctions.

RNA junctions are secondary-structure elements formed when three or more helices come together. They are present in diverse RNA molecules with various fundamental functions in the cell. To better understand the intricate architecture of three-dimensional (3D) RNAs, we analyze currently solved 3D RNA junctions in terms of base-pair interactions and 3D configurations. First, we study base-pair interaction diagrams for solved RNA junctions with 5 to 10 helices and discuss common features. Second, we compare these higher-order junctions to those containing 3 or 4 helices and identify global motif patterns such as coaxial stacking and parallel and perpendicular helical configurations. These analyses show that higher-order junctions organize their helical components in parallel and helical configurations similar to lower-order junctions. Their sub-junctions also resemble local helical configurations found in three- and four-way junctions and are stabilized by similar long-range interaction preferences such as A-minor interactions. Furthermore, loop regions within junctions are high in adenine but low in cytosine, and in agreement with previous studies, we suggest that coaxial stacking between helices likely forms when the common single-stranded loop is small in size; however, other factors such as stacking interactions involving noncanonical base pairs and proteins can greatly determine or disrupt coaxial stacking. Finally, we introduce the ribo-base interactions: when combined with the along-groove packing motif, these ribo-base interactions form novel motifs involved in perpendicular helix-helix interactions. Overall, these analyses suggest recurrent tertiary motifs that stabilize junction architecture, pack helices, and help form helical configurations that occur as sub-elements of larger junction networks. The frequent occurrence of similar helical motifs suggest nature's finite and perhaps limited repertoire of RNA helical conformation preferences. More generally, studies of RNA junctions and tertiary building blocks can ultimately help in the difficult task of RNA 3D structure prediction.

Analysis of four-way junctions in RNA structures.

RNA secondary structures can be divided into helical regions composed of canonical Watson-Crick and related base pairs, as well as single-stranded regions such as hairpin loops, internal loops, and junctions. These elements function as building blocks in the design of diverse RNA molecules with various fundamental functions in the cell. To better understand the intricate architecture of three-dimensional (3D) RNAs, we analyze existing RNA four-way junctions in terms of base-pair interactions and 3D configurations. Specifically, we identify nine broad junction families according to coaxial stacking patterns and helical configurations. We find that helices within junctions tend to arrange in roughly parallel and perpendicular patterns and stabilize their conformations using common tertiary motifs such as coaxial stacking, loop-helix interaction, and helix packing interaction. Our analysis also reveals a number of highly conserved base-pair interaction patterns and novel tertiary motifs such as A-minor-coaxial stacking combinations and sarcin/ricin motif variants. Such analyses of RNA building blocks can ultimately help in the difficult task of RNA 3D structure prediction.

Annotation of tertiary interactions in RNA structures reveals variations and correlations.

RNA tertiary motifs play an important role in RNA folding and biochemical functions. To help interpret the complex organization of RNA tertiary interactions, we comprehensively analyze a data set of 54 high-resolution RNA crystal structures for motif occurrence and correlations. Specifically, we search seven recognized categories of RNA tertiary motifs (coaxial helix, A-minor, ribose zipper, pseudoknot, kissing hairpin, tRNA D-loop/T-loop, and tetraloop-tetraloop receptor) by various computer programs. For the nonredundant RNA data set, we find 613 RNA tertiary interactions, most of which occur in the 16S and 23S rRNAs. An analysis of these motifs reveals the diversity and variety of A-minor motif interactions and the various possible loop-loop receptor interactions that expand upon the tetraloop-tetraloop receptor. Correlations between motifs, such as pseudoknot or coaxial helix with A-minor, reveal higher-order patterns. These findings may ultimately help define tertiary structure restraints for RNA tertiary structure prediction. A complete annotation of the RNA diagrams for our data set is available at http://www.biomath.nyu.edu/motifs/.