PVRIG is Expressed on Stem-Like T Cells in Dendritic Cell-Rich Niches in Tumors and Its Blockade May Induce Immune Infiltration in Non-Inflamed Tumors.

Cancers that are poorly immune infiltrated pose a substantial challenge, with current immunotherapies yielding limited clinical success. Stem-like memory T cells (TSCM) have been identified as a subgroup of T cells that possess strong proliferative capacity and that can expand and differentiate following interactions with dendritic cells (DCs). In this study, we explored the pattern of expression of a recently discovered inhibitory receptor poliovirus receptor-related immunoglobulin domain protein (PVRIG) and its ligand, poliovirus receptor-related ligand 2 (PVRL2), in the human tumor microenvironment. Using spatial and single-cell RNA transcriptomics data across diverse cancer indications, we found that among the T-cell checkpoints, PVRIG is uniquely expressed on TSCM and PVRL2 is expressed on DCs in immune aggregate niches in tumors. PVRIG blockade could therefore enhance TSCM-DC interactions and efficiently drive T-cell infiltration to tumors. Consistent with these data, following PVRIG blockade in patients with poorly infiltrated tumors, we observed immune modulation including increased tumor T-cell infiltration, T-cell receptor (TCR) clonality, and intratumoral T-cell expansion, all of which were associated with clinical benefit. These data suggest PVRIG blockade as a promising strategy to induce potent antitumor T-cell responses, providing a novel approach to overcome resistance to immunotherapy in immune-excluded tumors.

Peptides modulating conformational changes in secreted chaperones: from in silico design to preclinical proof of concept.

Blocking conformational changes in biologically active proteins holds therapeutic promise. Inspired by the susceptibility of viral entry to inhibition by synthetic peptides that block the formation of helix-helix interactions in viral envelope proteins, we developed a computational approach for predicting interacting helices. Using this approach, which combines correlated mutations analysis and Fourier transform, we designed peptides that target gp96 and clusterin, 2 secreted chaperones known to shift between inactive and active conformations. In human blood mononuclear cells, the gp96-derived peptide inhibited the production of TNFalpha, IL-1beta, IL-6, and IL-8 induced by endotoxin by >80%. When injected into mice, the peptide reduced circulating levels of endotoxin-induced TNFalpha, IL-6, and IFNgamma by >50%. The clusterin-derived peptide arrested proliferation of several neoplastic cell lines, and significantly enhanced the cytostatic activity of taxol in vitro and in a xenograft model of lung cancer. Also, the predicted mode of action of the active peptides was experimentally verified. Both peptides bound to their parent proteins, and their biological activity was abolished in the presence of the peptides corresponding to the counterpart helices. These data demonstrate a previously uncharacterized method for rational design of protein antagonists.

Prevention of bleomycin-induced pulmonary fibrosis by a novel antifibrotic peptide with relaxin-like activity.

Pulmonary fibrosis is a progressive and lethal lung disease characterized by accumulation of extracellular matrix and loss of pulmonary function. No cure exists for this pathologic condition, and current treatments often fail to slow its progression or relieve its symptoms. Relaxin was previously shown to induce a matrix-degrading phenotype in human lung fibroblasts in vitro and to inhibit pulmonary fibrosis in vivo. A novel peptide that targets the relaxin RXFP1/LGR7 receptor was recently identified using our computational platform designed to predict novel G protein-coupled receptor peptide agonists. In this study, we examined the antifibrotic properties of this novel peptide, designated CGEN25009, in human cell-based assays and in a murine model of bleomycin-induced pulmonary fibrosis. Similar to relaxin, CGEN25009 was found to have an inhibitory effect on transforming growth factor-ß1-induced collagen deposition in human dermal fibroblasts and to enhance MMP-2 expression. The peptide's biological activity was also similar to relaxin in generating cellular stimulation of cAMP, cGMP, and NO in the THP-1 human cell line. In vivo, 2-week administration of CGEN25009 in a preventive or therapeutic mode (i.e., concurrently with or 7 days after bleomycin treatment, respectively) caused a significant reduction in lung inflammation and injury and ameliorated adverse airway remodeling and peribronchial fibrosis. The results of this study indicate that CGEN25009 displays antifibrotic and anti-inflammatory properties and may offer a new therapeutic option for the treatment of pulmonary fibrosis.

Predicting proteolytic sites in extracellular proteins: only halfway there.

MOTIVATION: Many secretory proteins are synthesized as inactive precursors that must undergo post-translational proteolysis in order to mature and become active. In the current study, we address the challenge of sequence-based discovery of proteolytic sites in secreted proteins using machine learning. RESULTS: The results revealed that only half of the extracellular proteolytic sites are currently annotated, leaving over 3600 unannotated ones. Furthermore, we have found that only 6% of the unannotated sites are similar to known proteolytic sites, whereas the remaining 94% do not share significant similarity with any annotated proteolytic site. The computational challenges in these two cases are very different. While the precision in detecting the former group is close to perfect, only a mere 22% of the latter group were detected with a precision of 80%. The applicability of the classifier is demonstrated through members of the FGF family, in which we verified the conservation of physiologically-relevant proteolytic sites in homologous proteins.

CD6 and syntaxin binding protein 6 variants and response to tumor necrosis factor alpha inhibitors in Danish patients with rheumatoid arthritis.

BACKGROUND: TNFα inhibitor therapy has greatly improved the treatment of patients with rheumatoid arthritis, however at least 30% do not respond. We aimed to investigate insertions and deletions (INDELS) associated with response to TNFα inhibitors in patients with rheumatoid arthritis (RA). METHODOLOGY AND PRINCIPAL FINDINGS: In the DANBIO Registry we identified 237 TNFα inhibitor naïve patients with RA (81% women; median age 56 years; disease duration 6 years) who initiated treatment with infliximab (n=160), adalimumab (n=56) or etanercept (n=21) between 1999 and 2008 according to national treatment guidelines. Clinical response was assessed at week 26 using EULAR response criteria. Based on literature, we selected 213 INDELS potentially related to RA and treatment response using the GeneVa® (Compugen) in silico database of 350,000 genetic variations in the human genome. Genomic segments were amplified by polymerase chain reaction (PCR), and genotyped by Sanger sequencing or fragment analysis. We tested the association between genotypes and EULAR good response versus no response, and EULAR good response versus moderate/no response using Fisher's exact test. At baseline the median DAS28 was 5.1. At week 26, 68 (29%) patients were EULAR good responders, while 81 (34%) and 88 (37%) patients were moderate and non-responders, respectively. A 19 base pair insertion within the CD6 gene was associated with EULAR good response vs. no response (OR=4.43, 95% CI: 1.99-10.09, p=7.211×10(-5)) and with EULAR good response vs. moderate/no response (OR=4.54, 95% CI: 2.29-8.99, p=3.336×10(-6)). A microsatellite within the syntaxin binding protein 6 (STXBP6) was associated with EULAR good response vs. no response (OR=4.01, 95% CI: 1.92-8.49, p=5.067×10(-5)). CONCLUSION: Genetic variations within CD6 and STXBP6 may influence response to TNFα inhibitors in patients with RA.

Activation of relaxin-related receptors by short, linear peptides derived from a collagen-containing precursor.

In a screening effort based on algorithmic predictions for novel G-protein-coupled receptor (GPCR) peptide activators, we were able to identify and examine two novel peptides (P59 and P74) which are short, linear, and derived from a natural, previously unidentified precursor protein containing a collagen-like repeat. Both peptides seemed to show an apparent cAMP-related effect on CHO-K1 cells transiently transfected with either LGR7 or LGR8, usually after treatment with cAMP-generating forskolin, compared to the same cells treated with forskolin plus relaxin. This activation was not found for the relaxin-3 receptor (GPR135). In a set of follow-up experiments, both peptides were found to stimulate cAMP production, mostly upon initial stimulation of cAMP production by 5 micro M forskolin in cells transfected with either LGR7 or LGR8. In a dye-free cell impedance GPCR activation assay, we were able to show that these peptides were also able to activate a cellular response mediated by these receptors. Although untransfected CHO-K1 cells showed some cellular activation by both relaxin and at least one of our newly discovered peptides, both LGR7- and LGR8-transfected cells showed a stronger response, indicating stimulation of a cellular pathway through activation of these receptors. In conclusion, we were able to show that these newly discovered peptides, which have no similarity to any member of the relaxin-insulin-like peptide family, are potential ligands for the relaxin-related family of receptors and as such might serve as novel candidates for relaxin-related therapeutic indications. Both peptides are linear and were found to be active after being chemically synthesized.

Discovery and validation of novel peptide agonists for G-protein-coupled receptors.

G-protein-coupled receptors (GPCRs) represent an important group of targets for pharmaceutical therapeutics. The completion of the human genome revealed a large number of putative GPCRs. However, the identification of their natural ligands, and especially peptides, suffers from low discovery rates, thus impeding development of therapeutics based on these potential drug targets. We describe the discovery of novel GPCR ligands encrypted in the human proteome. Hundreds of potential peptide ligands were predicted by machine learning algorithms. In vitro screening of selected 33 peptides on a set of 152 GPCRs, including a group of designated orphan receptors, was conducted by intracellular calcium measurements and cAMP assays. The screening revealed eight novel peptides as potential agonists that specifically activated six different receptors in a dose-dependent manner. Most of the peptides showed distinct stimulatory patterns targeted at designated and orphan GPCRs. Further analysis demonstrated a significant in vivo effect for one of the peptides in a mouse inflammation model.

Large-scale unrestricted identification of post-translation modifications using tandem mass spectrometry.

TwinPeaks, a close variant of the SEQUEST protein identification algorithm, is capable of unrestricted, large-scale, identification of post-translation modifications (PTMs). TwinPeaks is applied on a sample of 100441 tandem mass spectra from the HUPO Plasma Proteome Project data set, with full non-redundant human as a reference protein database. With a 3.5% error rate, TwinPeaks identifies a collection of 539 spectra that were not identified by the usual PTM-restricted identification algorithm. At this error rate, TwinPeaks increases the rate of spectra identifications by at least 17.6%, making unrestricted PTM identification an integral part of proteomics.

Precalibration of matrix-assisted laser desorption/ionization-time of flight spectra for peptide mass fingerprinting.

Identification of proteins using matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) peptide mass fingerprinting (PMF) is a key technique in proteomics. The method is known to be sensitive as well as amenable to high-throughput operation, but the resulting identifications suffer from a relatively low level of confidence. One way of increasing the confidence is by improving measurement accuracy using one of several calibration methods. This paper presents a new strategy for calibration of MALDI-TOF PMF spectra that makes use of the phenomenon of peptide mass clustering, and enables spectrum calibration prior to the step of database interrogation, before or after peak extraction. Typically, mass errors are reduced by 40-60%. Accuracy improvement at this early stage can help avoid losing protein candidates, reduce the number of external calibration spots, eliminate internal calibrants, and reduce the number of candidates being scored, thereby reducing analysis time. Different variants of the method are discussed and compared to known calibration methods, such as relying on known calibrants or comparison to putative database candidates. In order to allow precise description of the method and to place the results in perspective, theoretical considerations of peptide databases and scoring functions are also discussed.