Effects of linear amphiphilicity on membrane interactions of C-terminal thrombin peptides

Effects of linear amphiphilicity on membrane interactions of antimicrobial peptides were investigated by ellipsometry, dual polarization interferometry, fluorescence spectroscopy, light scattering, and circular dichroism. In doing so, the thrombin-derived GKY25 (GKYGFYTHVFRLKKWIQKVIDQFGE) was compared to WFF25 (WFFFYYLIIGGGVVTHQQRKKKKDE) of identical composition, but with amino acids sorted according to hydrophobicity, the latter peptide thus displaying pronounced linear amphiphilicity. In addition, GKY25d (GKYG(f) YTH(v) FRL(k) KWI(q) KVI(d) QFGE; with an identical sequence but with selected D-amino acid substitutions) was included as a control peptide, for which conformationally induced (helix-related) amphiphilicity was suppressed. Through its pronounced linear amphiphilicity, WFF25, but not the less amphiphilic GKY25 and GKY25d, forms aggregates in solution. Through its terminal W/F stretch, WFF25 also displays pronounced selectivity, with higher membrane binding and liposome rupture than GKY25 and GKY25d for anionic membranes, but suppressed peptide insertion and lytic effects for zwitterionic ones. In addition, WFF25 binds extensively to anionic polyelectrolyte components in bacterial membranes, i.e., lipopolysaccharide and lipoteichoic acid, resulting in reduced antimicrobial effects through peptide scavenging, not seen for the less amphiphilic GKY25 and GKY25d peptides. Taken together, the results thus demonstrate a series of striking effects for highly amphiphilic peptides, which need to be recognized in the development of such compounds as potential peptide therapeutics

An antimicrobial helix A-derived peptide of heparin cofactor II blocks endotoxin responses in vivo.

Host defense peptides are key components of the innate immune system, providing multi-facetted responses to invading pathogens. Here, we describe that the peptide GKS26 (GKSRIQRLNILNAKFAFNLYRVLKDQ), corresponding to the A domain of heparin cofactor II (HCII), ameliorates experimental septic shock. The peptide displays antimicrobial effects through direct membrane disruption, also at physiological salt concentration and in the presence of plasma and serum. Biophysical investigations of model lipid membranes showed the antimicrobial action of GKS26 to be mirrored by peptide incorporation into, and disordering of, bacterial lipid membranes. GKS26 furthermore binds extensively to bacterial lipopolysaccharide (LPS), as well as its endotoxic lipid A moiety, and displays potent anti-inflammatory effects, both in vitro and in vivo. Thus, for mice challenged with ip injection of LPS, GKS26 suppresses pro-inflammatory cytokines, reduces vascular leakage and infiltration in lung tissue, and normalizes coagulation. Together, these findings suggest that GKS26 may be of interest for further investigations as therapeutic against severe infections and septic shock

Structure-Activity Studies and Therapeutic Potential of Host Defense Peptides of Human Thrombin

Peptides of the C-terminal region of human thrombin are released upon proteolysis and identified in human wounds. In this study, we wanted to investigate minimal determinants, as well as structural features, governing the antimicrobial and immunomodulating activity of this peptide region. Sequential amino acid deletions of the peptide GKYGFYTHVFRLKKWIQKVIDQFGE (GKY25), as well as substitutions at strategic and structurally relevant positions, were followed by analyses of antimicrobial activity against the Gram-negative bacteria Escherichia coli and Pseudomonas aeruginosa, the Gram-positive bacterium Staphylococcus aureus, and the fungus Candida albicans. Furthermore, peptide effects on lipopolysaccharide (LPS)-, lipoteichoic acid-, or zymosan-induced macrophage activation were studied. The thrombin-derived peptides displayed length-and sequence-dependent antimicrobial as well as immunomodulating effects. A peptide length of at least 20 amino acids was required for effective anti-inflammatory effects in macrophage models, as well as optimal antimicrobial activity as judged by MIC assays. However, shorter (> 12 amino acids) variants also displayed significant antimicrobial effects. A central K14 residue was important for optimal antimicrobial activity. Finally, one peptide variant, GKYGFYTHVFRLKKWIQKVI (GKY20) exhibiting improved selectivity, i.e., low toxicity and a preserved antimicrobial as well as anti-inflammatory effect, showed efficiency in mouse models of LPS shock and P. aeruginosa sepsis. The work defines structure-activity relationships of C-terminal host defense peptides of thrombin and delineates a strategy for selecting peptide epitopes of therapeutic interest

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Integrated Genomic Analysis of the Ubiquitin Pathway across Cancer Types

Protein ubiquitination is a dynamic and reversibleprocess of adding single ubiquitin molecules orvarious ubiquitin chains to target proteins. Here,using multidimensional omic data of 9,125 tumorsamples across 33 cancer types from The CancerGenome Atlas, we perform comprehensive molecu-lar characterization of 929 ubiquitin-related genesand 95 deubiquitinase genes. Among them, we sys-tematically identify top somatic driver candidates,including mutatedFBXW7with cancer-type-specificpatterns and amplifiedMDM2showing a mutuallyexclusive pattern withBRAFmutations. Ubiquitinpathway genes tend to be upregulated in cancermediated by diverse mechanisms. By integratingpan-cancer multiomic data, we identify a group oftumor samples that exhibit worse prognosis. Thesesamples are consistently associated with the upre-gulation of cell-cycle and DNA repair pathways, char-acterized by mutatedTP53,MYC/TERTamplifica-tion, andAPC/PTENdeletion. Our analysishighlights the importance of the ubiquitin pathwayin cancer development and lays a foundation fordeveloping relevant therapeutic strategies

Machine Learning Identifies Stemness Features Associated with Oncogenic Dedifferentiation.

Cancer progression involves the gradual loss of a differentiated phenotype and acquisition of progenitor and stem-cell-like features. Here, we provide novel stemness indices for assessing the degree of oncogenic dedifferentiation. We used an innovative one-class logistic regression (OCLR) machine-learning algorithm to extract transcriptomic and epigenetic feature sets derived from non-transformed pluripotent stem cells and their differentiated progeny. Using OCLR, we were able to identify previously undiscovered biological mechanisms associated with the dedifferentiated oncogenic state. Analyses of the tumor microenvironment revealed unanticipated correlation of cancer stemness with immune checkpoint expression and infiltrating immune cells. We found that the dedifferentiated oncogenic phenotype was generally most prominent in metastatic tumors. Application of our stemness indices to single-cell data revealed patterns of intra-tumor molecular heterogeneity. Finally, the indices allowed for the identification of novel targets and possible targeted therapies aimed at tumor differentiation