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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.

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/.

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.

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.