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Markel, G.

Publications and source records attributed to Markel, G..

3 recordsLinked to original sources

Novel immunotherapy for multiple solid cancers using an Anti-HVEM blocking monoclonal antibody

INTRODUCTIONImmune checkpoint inhibitors (ICIs) have revolutionized cancer treatment, yet their efficacy remains limited. Therefore, there is a clear need for new anti-tumor agents. HVEM (Herpes Virus Entry Mediator) plays a regulatory role in immunity, making it a promising cancer therapeutic target. EXPERIMENTAL DESIGNWe have developed Anti-4CB1, a fully human HVEM-BTLA and HVEM-CD160 blocking mAb and tested its anti-tumor activity in various in-vitro, ex-vivo and in-vivo models, alone or in combination with Anti-PD1. Finally, we analyzed HVEM expression in serum samples and melanoma tumor tissues and its correlation with HVEM and PD1 blockade treatment response. RESULTSIn-vitro assays demonstrated enhanced melanoma cell killing by autologous TILs in the presence of Anti-4CB1. In addition, Anti-4CB1 significantly increased cytotoxicity by up to 233% in a variety of ex-vivo cancer tissue samples of different indications. Notably, Anti-4CB1 demonstrated effectiveness in samples where Anti-PD1 was ineffective. In addition, significant anti-tumor activity at 10 mg/kg in combination with Anti-PD1 (TGI 95% p=0.0001) or at 25 mg/kg as monotherapy (TGI 50% p=0.0096) was demonstrated in a colon carcinoma transgenic mice model. Moreover, significant anti-tumor activity was observed in a mouse ImmunoGraft model (TGI 53% p=0.0102 as monotherapy). Finally, we demonstrated that HVEM expression correlated with response to Anti-HVEM and Anti-PD1 treatments. DISCUSSIONWe describe the development of Anti-4CB1, a fully human anti-HVEM mAb, blocking HVEM-BTLA and HVEM-CD160 human interactions and enhancing lymphocytes cytotoxicity against various cancer cells ex-vivo. In-vivo, Anti-4CB1 showed promising anti-tumor effects, particularly in combination with Anti-PD1, suggesting its therapeutic potential. Finally, HVEM expression may serve as a predictive marker for Anti-HVEM and Anti-PD1 treatments response, offering potential diagnostic utility in patient selection for these immunotherapies. These results support Anti-4CB1 potential as an anti-cancer therapeutic agent. Translational RelevanceThe discovery of immune checkpoint inhibitors (ICIs), marks a significant breakthrough in cancer therapy. However, despite the remarkable success of current ICIs targeting CTLA4 and PD1/PD-L1 pathways, a significant proportion of patients fail to respond or develop resistance. Therefore, the search for novel ICIs is crucial for advancing cancer immunotherapy. Anti-HVEM emerged as a promising candidate, as we demonstrate in ex-vivo and in-vivo models, its ability to block the HVEM-BTLA interaction, resulting in enhanced antitumor immune responses in solid tumors, alone or in combination with existing ICIs, to improve treatment outcomes. Moreover, the correlation between HVEM expression and treatment responses highlight its potential as an attractive target for biomarker-driven therapies. Investigating HVEM as an ICI offers a promising path to expand therapeutic options, personalize treatment approaches, address the evolving challenges in cancer immunotherapy and improve patient outcomes.

cancer biology↗

Peptriever: A Bi-Encoder approach for large-scale protein-peptide binding search

MotivationIn peptide therapeutics, the successful interaction between a designed peptide and a specific receptor is crucial, while minimizing interactions with other receptors is equally essential. Current computational methods excel at estimating the probability of the former but estimating the latter requires excessive computational resources, making it challenging. ResultsIn this study, we propose transformers-based protein embeddings that can quickly identify and rank millions of interacting proteins. Furthermore, the proposed approach outperforms existing sequence- and structure-based methods, with a mean AUC-ROC and AUC-PR of 0.73. AvailabilityTraining data, scripts, and fine-tuned parameters are available at https://github.com/RoniGurvich/Peptriever. A live demonstration of the application can be found at https://peptriever.app/. Contacttomermrsn@gmail.com and zia.rehman@helsinki.fi

bioinformatics↗

Structural basis of SARS-CoV-2 spike protein induced by ACE2

MotivationThe recent emergence of the novel SARS-coronavirus 2 (SARS-CoV-2) and its international spread pose a global health emergency. The viral spike (S) glycoprotein binds the receptor (angiotensin-converting enzyme 2) ACE2 and promotes SARS-CoV-2 entry into host cells. The trimeric S protein binds the receptor using the distal receptor-binding domain (RBD) causing conformational changes in S protein that allow priming by host cell proteases. Unravelling the dynamic structural features used by SARS-CoV-2 for entry might provide insights into viral transmission and reveal novel therapeutic targets. Using structures determined by X-ray crystallography and cryo-EM, we performed structural analysis and atomic comparisons of the different conformational states adopted by the SARS-CoV-2-RBD. ResultsHere, we determined the key structural components induced by the receptor and characterized their intramolecular interactions. We show that {kappa}-helix (also known as polyproline II) is a predominant structure in the binding interface and in facilitating the conversion to the active form of the S protein. We demonstrate a series of conversions between switch-like {kappa}-helix and {beta}-strand, and conformational variations in a set of short -helices which affect the proximal hinge region. This conformational changes lead to an alternating pattern in conserved disulfide bond configurations positioned at the hinge, indicating a possible disulfide exchange, an important allosteric switch implicated in viral entry of various viruses, including HIV and murine coronavirus. The structural information presented herein enables us to inspect and understand the important dynamic features of SARS-CoV-2-RBD and propose a novel potential therapeutic strategy to block viral entry. Overall, this study provides guidance for the design and optimization of structure-based intervention strategies that target SARS-CoV-2.

bioinformatics↗