4 research outputs found
Exosomes in liquid biopsy and oncology: Nanotechnological interplay and the quest to overcome cancer drug resistance
Exosomes, small extracellular vesicles of endocytic origin, have emerged as pivotal mediators in intercellular communication, driving transformative advancements across diverse fields of biology and medicine. This comprehensive review delves into the multifaceted roles of exosomes in health and disease, elucidating their biogenesis, cargo composition, and far-reaching implications. Exosomes, secreted by virtually all cell types, encapsulate a cargo comprising proteins, lipids, and nucleic acids, reflecting their cellular origin. Their molecular cargo modulates cellular processes, facilitating complex signalling cascades and contributing to the pathogenesis of various diseases, including cancer, neurodegenerative disorders, and infectious diseases. In cancer, exosomes serve as messengers of tumorigenesis and metastasis, orchestrating critical events within the tumor micro environment. Furthermore, exosomes participate in drug resistance mechanisms, presenting significant challenges in cancer therapy. The diagnostic potential of exosomes, particularly in the context of liquid biopsy, is underscored by their presence in various biofluids. This offers non-invasive disease monitoring and biomarker discovery, revolutionizing early detection and monitoring strategies. Additionally, exosomes have gained recognition as therapeutic vehicles, holding promise for targeted drug delivery, immunomodulation, and regenerative medicine. This review comprehensively explores the ever-expanding landscape of exosome biology, emphasizing their roles in health and disease. It underscores the transformative potential of exosomes in liquid biopsy-based diagnostics and therapeutics while acknowledging the complexities and challenges that lie ahead in harnessing their full clinical utility.</p
Revolutionizing human papillomavirus (HPV)‐related cancer therapies: unveiling the promise of proteolysis targeting chimeras (PROTACs) and proteolysis targeting antibodies (PROTABs) in cancer nano‐vaccines
Personalized cancer immunotherapies, combined with nanotechnology (nano‐ vaccines), are revolutionizing cancer treatment strategies, explicitly targeting Human papilloma virus (HPV)‐related cancers. Despite the availability of preventive vaccines, HPV‐related cancers remain a global concern. Personalized cancer nano‐vaccines, tailored to an individual's tumor genetic mutations, offer a unique and promising solution. Nanotechnology plays a critical role in these vaccines by efficiently delivering tumor‐specific antigens, enhancing immune responses, and paving the way for precise and targeted therapies. Recent advancements in preclinical models have demonstrated the potential of polymeric nanoparticles and high‐density lipoprotein‐mimicking nano‐discs in augmenting the efficacy of personalized cancer vaccines. However, challenges related to optimizing the nano‐carrier system and ensuring safety in human trials persist. Excitingly, the integration of nanotechnology with Proteolysis‐ Targeting Chimeras (PROTACs) provides an additional avenue to enhance the effectiveness of personalized cancer treatment. PROTACs selectively degrade disease‐causing proteins, amplifying the impact of nanotechnology‐based therapies. Overcoming these challenges and leveraging the synergistic potential of nanotechnology, PROTACs, and Proteolysis‐Targeting Antibodies hold great promise in pursuing novel and effective therapeutic solutions for individuals affected by HPV‐related cancers.</p
Unlocking exosome-based theragnostic signatures: deciphering secrets of ovarian cancer metastasis
Ovarian cancer (OC) is a common gynecological cancer worldwide. Unfortunately, the lack of early detection methods translates into a substantial cohort of women grappling with the pressing health crisis. The discovery of extracellular vesicles (EVs) (their major subpopulation exosomes, microvesicles, and apoptotic bodies) has provided new insights into the understanding of cancer. Exosomes, a subpopulation of EVs, play a crucial role in cellular communication and reflect the cellular status under both healthy and pathological conditions. Tumor-derived exosomes (TEXs) dynamically influence ovarian cancer progression by regulating uncontrolled cell growth, immune suppression, angiogenesis, metastasis, and the development of drug and therapeutic resistance. In the field of OC diagnostics, TEXs offer potential biomarkers in various body fluids. On the other hand, exosomes have also shown promising abilities to cure ovarian cancer. In this review, we address the interlink between exosomes and ovarian cancer and explore their theragnostic signature. Finally, we highlight future directions of exosome-based ovarian cancer research.</p
Data_Sheet_1_Recognizing novel drugs against Keap1 in Alzheimer’s disease using machine learning grounded computational studies.xlsx
Alzheimer’s disease (AD) is the most common neurodegenerative disorder in the world, affecting an estimated 50 million individuals. The nerve cells become impaired and die due to the formation of amyloid-beta (Aβ) plaques and neurofibrillary tangles (NFTs). Dementia is one of the most common symptoms seen in people with AD. Genes, lifestyle, mitochondrial dysfunction, oxidative stress, obesity, infections, and head injuries are some of the factors that can contribute to the development and progression of AD. There are just a few FDA-approved treatments without side effects in the market, and their efficacy is restricted due to their narrow target in the etiology of AD. Therefore, our aim is to identify a safe and potent treatment for Alzheimer’s disease. We chose the ursolic acid (UA) and its similar compounds as a compounds’ library. And the ChEMBL database was adopted to obtain the active and inactive chemicals against Keap1. The best Quantitative structure-activity relationship (QSAR) model was created by evaluating standard machine learning techniques, and the best model has the lowest RMSE and greatest R2 (Random Forest Regressor). We chose pIC50 of 6.5 as threshold, where the top five potent medicines (DB06841, DB04310, DB11784, DB12730, and DB12677) with the highest predicted pIC50 (7.091184, 6.900866, 6.800155, 6.768965, and 6.756439) based on QSAR analysis. Furthermore, the top five medicines utilize as ligand molecules were docked in Keap1’s binding region. The structural stability of the nominated medications was then evaluated using molecular dynamics simulations, RMSD, RMSF, Rg, and hydrogen bonding. All models are stable at 20 ns during simulation, with no major fluctuations observed. Finally, the top five medications are shown as prospective inhibitors of Keap1 and are the most promising to battle AD.</p