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Leptomeningeal disease (LMD) refers to the infiltration of cancer cells into the leptomeningeal compartment. Leptomeninges are the two membranous layers, called the arachnoid membrane and pia mater. The diffuse nature of LMD poses a challenge to its effective diagnosis and successful management. Furthermore, the predominant phenotype; solid masses or freely floating cells, has altering implications on the effectiveness of drug delivery systems. The standard of care is the intrathecal delivery of chemotherapy drugs but it is associated with increased instances of treatment-related complications, low patient compliance, and suboptimal drug distribution. An alternative involves administering the drugs systemically, after which they must traverse fluid barriers to arrive at their destination within the leptomeningeal space. However, this route is known to cause off-target effects as well as produce subtherapeutic drug concentrations at the target site within the central nervous system. The development of new drug delivery systems such as liposomal cytarabine has improved drug delivery in leptomeningeal metastatic disease, but much still needs to be done to effectively target this challenging condition. In this review, we discuss about the anatomy of leptomeninges relevant for drug penetration, the conventional and advanced drug delivery methods for LMD. We also discuss the future directions being set by different clinical trials.
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Antineoplásicos , Sistemas de Liberación de Medicamentos , Humanos , Sistemas de Liberación de Medicamentos/métodos , Antineoplásicos/administración & dosificación , Antineoplásicos/farmacocinética , Neoplasias Meníngeas/tratamiento farmacológico , Liposomas , Animales , MeningesRESUMEN
Advancing personalized medicine in brain cancer relies on innovative strategies, with mRNA vaccines emerging as a promising avenue. While the initial use of mRNA vaccines was in oncology, their stunning success in COVID-19 resulted in widespread attention, both positive and negative. Regardless of politically biased opinions, which relate more to the antigenic source than form of delivery, we feel it is important to objectively review this modality as relates to brain cancer. This class of vaccines trigger robust immune responses through MHC-I and MHC-II pathways, in both prophylactic and therapeutic settings. The mRNA platform offers advantages of rapid development, high potency, cost-effectiveness, and safety. This review provides an overview of mRNA vaccine delivery technologies, tumor antigen identification, combination therapies, and recent therapeutic outcomes, with a particular focus on brain cancer. Combinatorial approaches are vital to maximizing mRNA cancer vaccine efficacy, with ongoing clinical trials exploring combinations with adjuvants and checkpoint inhibitors and even adoptive cell therapy. Efficient delivery, neoantigen identification, preclinical studies, and clinical trial results are highlighted, underscoring mRNA vaccines' potential in advancing personalized medicine for brain cancer. Synergistic combinatorial therapies play a crucial role, emphasizing the need for continued research and collaboration in this area.
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Neoplasias Encefálicas , Vacunas contra el Cáncer , Neoplasias , Humanos , Medicina de Precisión/métodos , Inmunoterapia/métodos , Neoplasias Encefálicas/terapia , Neoplasias Encefálicas/tratamiento farmacológico , ARN Mensajero/genética , Neoplasias/terapiaRESUMEN
In diabetes, possibly the most significant site of microvascular damage is the kidney. Due to diabetes and/or other co-morbidities, such as hypertension and age-related nephron loss, a significant number of people with diabetes suffer from kidney diseases. Improved diabetic care can reduce the prevalence of diabetic nephropathy (DN); however, innovative treatment approaches are still required. MicroRNA-21 (miR-21) is one of the most studied multipotent microRNAs (miRNAs), and it has been linked to renal fibrosis and exhibits significantly altered expression in DN. Targeting miR-21 offers an advantage in DN. Currently, miR-21 is being pharmacologically silenced through various methods, all of which are in early development. In this review, we summarize the role of miR-21 in the molecular pathogenesis of DN and several therapeutic strategies to use miR-21 as a therapeutic target in DN. The existing experimental interventions offer a way to rectify the lower miRNA levels as well as to reduce the higher levels. Synthetic miRNAs also referred to as miR-mimics, can compensate for abnormally low miRNA levels. Furthermore, strategies like oligonucleotides can be used to alter the miRNA levels. It is reasonable to target miR-21 for improved results because it directly contributes to the pathological processes of kidney diseases, including DN.
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Traumatic brain injury (TBI) is a significant cause of mortality and morbidity worldwide resulting from falls, car accidents, sports, and blast injuries. TBI is characterized by severe, life-threatening consequences due to neuroinflammation in the brain. Contact and collision sports lead to higher disability and death rates among young adults. Unfortunately, no therapy or drug protocol currently addresses the complex pathophysiology of TBI, leading to the long-term chronic neuroinflammatory assaults. However, the immune response plays a crucial role in tissue-level injury repair. This review aims to provide a better understanding of TBI's immunobiology and management protocols from an immunopathological perspective. It further elaborates on the risk factors, disease outcomes, and preclinical studies to design precisely targeted interventions for enhancing TBI outcomes.
Traumatic brain injury (TBI) is a leading cause of death and disability worldwide due to falls, car accidents, sports and blast injuries. TBI causes severe, life-threatening consequences due to inflammation in the brain. Unfortunately, no current therapy or drug protocol can address the complexity of TBI, leading to long-term chronic inflammation. However, the immune response plays a crucial role in repairing injured brain tissue. This review aims to provide a better understanding of TBI's immunobiology and management protocols to design targeted interventions for better outcomes in TBI patients.
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Chordomas are rare slow growing tumors, arising from embryonic remnants of notochord with a close predilection for the axial skeleton. Recurrence is common and no effective standard medical therapy exists. Thymidylate synthase (TS), an intracellular enzyme, is a key rate-limiting enzyme of DNA biosynthesis and repair which is primarily active in proliferating and metabolically active cells. Eighty-four percent of chordoma samples had loss of TS expression which may predict response to anti-folates. Pemetrexed suppresses tumor growth by inhibiting enzymes involved in folate metabolism, resulting in decreased availability of thymidine which is necessary for DNA synthesis. Pemetrexed inhibited growth in a preclinical mouse xenograft model of human chordoma. We report three cases of metastatic chordoma that had been heavily treated previously with a variety of standard therapies with poor response. In two cases, pemetrexed was added and objective responses were observed on imaging with one patient on continuous treatment for > 2 years with continued shrinkage. One case demonstrated tumor growth after treatment with pemetrexed. The two cases which had a favorable response had a loss of TS expression, whereas the one case with progressive disease had TS present. These results demonstrate the activity of pemetrexed in recurrent chordoma and warrant a prospective clinical trial which is ongoing (NCT03955042).
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Cordoma , Humanos , Animales , Ratones , Pemetrexed/farmacología , Pemetrexed/uso terapéutico , Cordoma/tratamiento farmacológico , Estudios Prospectivos , Guanina/farmacología , Guanina/uso terapéutico , Glutamatos/uso terapéutico , Glutamatos/farmacología , Recurrencia Local de Neoplasia/tratamiento farmacológico , ADN , Timidilato Sintasa/genética , Timidilato Sintasa/metabolismoRESUMEN
The cerebrospinal fluid (CSF) is a clear ultrafiltrate of blood that envelopes and protects the central nervous system while regulating neuronal function through the maintenance of interstitial fluid homeostasis in the brain. Due to its anatomic location and physiological functions, the CSF can provide a reliable source of biomarkers for the diagnosis and treatment monitoring of different neurological diseases, including neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and primary and secondary brain malignancies. The incorporation of CSF biomarkers into the drug discovery and development can improve the efficiency of drug development and increase the chances of success. This review aims to consolidate the current use of CSF biomarkers in clinical practice and explore future perspectives for the field.
Cerebrospinal fluid (CSF) is a clear fluid that protects our brain and spinal cord, and can help diagnose and monitor neurological diseases like Alzheimer's and Parkinson's. Biomarkers in CSF are like clues that help doctors and researchers better understand these diseases. By using CSF biomarkers, doctors can diagnose and monitor patients more accurately, while researchers can develop more effective treatments. This review looks at how we use CSF biomarkers in medicine and how they might help us in the future. Better understanding of CSF biomarkers can improve the lives of people living with neurological diseases.
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Neoantigen vaccines are based on epitopes of antigenic parts of mutant proteins expressed in cancer cells. These highly immunogenic antigens may trigger the immune system to combat cancer cells. Improvements in sequencing technology and computational tools have resulted in several clinical trials of neoantigen vaccines on cancer patients. In this review, we have looked into the design of the vaccines which are undergoing several clinical trials. We have discussed the criteria, processes, and challenges associated with the design of neoantigens. We searched different databases to track the ongoing clinical trials and their reported outcomes. We observed, in several trials, the vaccines boost the immune system to combat the cancer cells while maintaining a reasonable margin of safety. Detection of neoantigens has led to the development of several databases. Adjuvants also play a catalytic role in improving the efficacy of the vaccine. Through this review, we can conclude that the efficacy of vaccines can make it a potential treatment across different types of cancers.
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Vacunas contra el Cáncer , Neoplasias , Humanos , Antígenos de Neoplasias , Sistema Inmunológico , EpítoposRESUMEN
The presence of missing values in a time-series dataset is a very common and well-known problem. Various statistical and machine learning methods have been developed to overcome this problem, with the aim of filling in the missing values in the data. However, the performances of these methods vary widely, showing a high dependence on the type of data and correlations within the data. In our study, we performed some of the well-known imputation methods, such as expectation maximization, k-nearest neighbor, iterative imputer, random forest, and simple imputer, to impute missing data obtained from smart, wearable health trackers. In this manuscript, we proposed the use of data binning for imputation. We showed that the use of data binned around the missing time interval provides a better imputation than the use of a whole dataset. Imputation was performed for 15 min and 1 h of continuous missing data. We used a dataset with different bin sizes, such as 15 min, 30 min, 45 min, and 1 h, and we carried out evaluations using root mean square error (RMSE) values. We observed that the expectation maximization algorithm worked best for the use of binned data. This was followed by the simple imputer, iterative imputer, and k-nearest neighbor, whereas the random forest method had no effect on data binning during imputation. Moreover, the smallest bin sizes of 15 min and 1 h were observed to provide the lowest RMSE values for the majority of the time frames during the imputation of 15 min and 1 h of missing data, respectively. Although applicable to digital health data, we think that this method will also find applicability in other domains.
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Algoritmos , Dispositivos Electrónicos Vestibles , Factores de Tiempo , Bosques AleatoriosRESUMEN
Oral squamous cell carcinoma (OSCC) is an invasive and highly malignant cancer with significant morbidity and mortality. Existing treatments including surgery, chemotherapy and radiation have poor overall survival rates and prognosis. The intended therapeutic effects of chemotherapy are limited by drug resistance, systemic toxicity and adverse effects. This review explores advances in OSCC treatment, with a focus on lipid-based platforms (solid lipid nanoparticles, nanostructured lipid carriers, lipid-polymer hybrids, cubosomes), polymeric nanoparticles, self-assembling nucleoside nanoparticles, dendrimers, magnetic nanovectors, graphene oxide nanostructures, stimuli-responsive nanoparticles, gene therapy, folic acid receptor targeting, gastrin-releasing peptide receptor targeting, fibroblast activation protein targeting, urokinase-type plasminogen activator receptor targeting, biotin receptor targeting and transferrin receptor targeting. This review also highlights oncolytic viruses as OSCC therapy candidates.
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Carcinoma de Células Escamosas , Neoplasias de Cabeza y Cuello , Neoplasias de la Boca , Nanopartículas , Humanos , Carcinoma de Células Escamosas/tratamiento farmacológico , Neoplasias de la Boca/tratamiento farmacológico , Carcinoma de Células Escamosas de Cabeza y Cuello/tratamiento farmacológico , Sistemas de Liberación de Medicamentos , Nanopartículas/química , Neoplasias de Cabeza y Cuello/tratamiento farmacológico , Lípidos/uso terapéuticoRESUMEN
Glioblastoma is the most lethal form of brain tumor with a recurrence rate of almost 90% and a survival time of only 15 months post-diagnosis. It is a highly heterogeneous, aggressive, and extensively studied tumor. Multiple studies have proposed therapeutic approaches to mitigate or improve the survival for patients with glioblastoma. In this article, we review the loss of the 5'-methylthioadenosine phosphorylase (MTAP) gene as a potential therapeutic approach for treating glioblastoma. MTAP encodes a metabolic enzyme required for the metabolism of polyamines and purines leading to DNA synthesis. Multiple studies have explored the loss of this gene and have shown its relevance as a therapeutic approach to glioblastoma tumor mitigation; however, other studies show that the loss of MTAP does not have a major impact on the course of the disease. This article reviews the contrasting findings of MTAP loss with regard to mitigating the effects of glioblastoma, and also focuses on multiple aspects of MTAP loss in glioblastoma by providing insights into the known findings and some of the unexplored areas of this field where new approaches can be imagined for novel glioblastoma therapeutics.
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Glioblastoma , Humanos , Glioblastoma/genética , Glioblastoma/terapia , Purina-Nucleósido Fosforilasa/genética , Purina-Nucleósido Fosforilasa/metabolismoRESUMEN
The increasing usage of smart wearable devices has made an impact not only on the lifestyle of the users, but also on biological research and personalized healthcare services. These devices, which carry different types of sensors, have emerged as personalized digital diagnostic tools. Data from such devices have enabled the prediction and detection of various physiological as well as psychological conditions and diseases. In this review, we have focused on the diagnostic applications of wrist-worn wearables to detect multiple diseases such as cardiovascular diseases, neurological disorders, fatty liver diseases, and metabolic disorders, including diabetes, sleep quality, and psychological illnesses. The fruitful usage of wearables requires fast and insightful data analysis, which is feasible through machine learning. In this review, we have also discussed various machine-learning applications and outcomes for wearable data analyses. Finally, we have discussed the current challenges with wearable usage and data, and the future perspectives of wearable devices as diagnostic tools for research and personalized healthcare domains.
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Wearable devices use sensors to evaluate physiological parameters, such as the heart rate, pulse rate, number of steps taken, body fat and diet. The continuous monitoring of physiological parameters offers a potential solution to assess personal healthcare. Identifying outliers or anomalies in heart rates and other features can help identify patterns that can play a significant role in understanding the underlying cause of disease states. Since anomalies are present within the vast amount of data generated by wearable device sensors, identifying anomalies requires accurate automated techniques. Given the clinical significance of anomalies and their impact on diagnosis and treatment, a wide range of detection methods have been proposed to detect anomalies. Much of what is reported herein is based on previously published literature. Clinical studies employing wearable devices are also increasing. In this article, we review the nature of the wearables-associated data and the downstream processing methods for detecting anomalies. In addition, we also review supervised and un-supervised techniques as well as semi-supervised methods that overcome the challenges of missing and un-annotated healthcare data.
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Análisis de Datos , Dispositivos Electrónicos Vestibles , Algoritmos , Frecuencia CardíacaRESUMEN
Coronavirus disease 2019 (COVID-19), a pandemic disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV2), is growing at an exponential rate worldwide. Manifestations of this disease are heterogeneous; however, advanced cases often exhibit various acute respiratory distress syndrome-like symptoms, systemic inflammatory reactions, coagulopathy, and organ involvements. A common theme in advanced COVID-19 is unrestrained immune activation, classically referred to as a "cytokine storm", as well as deficiencies in immune regulatory mechanisms such as T regulatory cells. While mesenchymal stem cells (MSCs) themselves are objects of cytokine regulation, they can secrete cytokines to modulate immune cells by inducing anti-inflammatory regulatory Treg cells, macrophages and neutrophils; and by reducing the activation of T and B cells, dendritic and nature killer cells. Consequently, they have therapeutic potential for treating severe cases of COVID-19. Here we discuss the unique ability of MSCs, to act as a "living anti-inflammatory", which can "rebalance" the cytokine/immune responses to restore equilibrium. We also discuss current MSC trials and present different concepts for optimization of MSC therapy in patients with COVID-19 acute respiratory distress syndrome.
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Functional and genomic heterogeneity of individual cells are central players in a broad spectrum of normal and disease states. Our knowledge about the role of cellular heterogeneity in tissue and organism function remains limited due to analytical challenges one encounters when performing single cell studies in the context of cell-cell interactions. Information based on bulk samples represents ensemble averages over populations of cells, while data generated from isolated single cells do not account for intercellular interactions. We describe a new technology and demonstrate two important advantages over existing technologies: first, it enables multiparameter energy metabolism profiling of small cell populations (<100 cells)-a sample size that is at least an order of magnitude smaller than other, commercially available technologies; second, it can perform simultaneous real-time measurements of oxygen consumption rate (OCR), extracellular acidification rate (ECAR), and mitochondrial membrane potential (MMP)-a capability not offered by any other commercially available technology. Our results revealed substantial diversity in response kinetics of the three analytes in dysplastic human epithelial esophageal cells and suggest the existence of varying cellular energy metabolism profiles and their kinetics among small populations of cells. The technology represents a powerful analytical tool for multiparameter studies of cellular function.