ABSTRACT
Altered A-to-I RNA editing has been widely observed in many human cancers and some editing sites are associated with drug sensitivity, implicating its therapeutic potential. Increasing evidence has demonstrated that a quantitative trait loci mapping approach is effective to understanding the genetic basis of RNA editing. We systematically performed RNA editing quantitative trait loci (edQTL) analysis in 33 human cancer types for >10 000 cancer samples and identified 320 029 edQTLs. We also identified 1688 ed-QTLs associated with patient overall survival and 4672 ed-QTLs associated with GWAS risk loci. Furthermore, we demonstrated the associations between RNA editing and >1000 anti-cancer drug response with â¼3.5 million significant associations. We developed GPEdit (https://hanlab.uth.edu/GPEdit/) to facilitate a global map of the genetic and pharmacogenomic landscape of RNA editing. GPEdit is a user-friendly and comprehensive database that provides an opportunity for a better understanding of the genetic impact and the effects on drug response of RNA editing in cancers.
Subject(s)
Antineoplastic Agents/classification , Databases, Factual , Neoplasms/drug therapy , RNA Editing/genetics , Antineoplastic Agents/chemistry , Antineoplastic Agents/therapeutic use , Genome-Wide Association Study , Humans , Neoplasms/genetics , Neoplasms/pathology , Pharmacogenetics , Quantitative Trait Loci/genetics , Transcriptome/drug effectsABSTRACT
Importance: Both novel and next-in-class cancer drugs have a role in oncology, but the relative development of each is understudied. Objective: To characterize the mechanisms of action of anticancer drugs approved by the US Food and Drug Administration (FDA) between 2009 and 2020, noting how many approvals were based on a new mechanism of action vs next-in-class approvals. Design, Study, and Participants: This cross-sectional study included all anticancer drugs approved by the FDA from January 2009 to December 2020. The mechanism of action of each drug was extracted from FDA labels. Supportive-care treatments were excluded. Exposures: Name of drug approved, date of approval, indication, tumor type, mechanism of action, broad pharmaceutical class, and biological target. Approvals considering all tumor types and each tumor type separately were classified in 3 nonoverlapping categories: new mechanism of action, next in class, or subsequent approval. Main Outcomes and Measures: The number of all approvals each year; the number of approvals based on a new mechanism of action, either by drug (considering all tumor types) or by indication (considering tumor types separately); and the frequency of these numbers over time. Results: Overall, 332 approvals were included. Between 2009 and 2020, there was an increase in the total number of approvals from 8 to 57. We found that 209 approvals (63%) were for a next-in-class indication in a new tumor type (84 [25%]) or a subsequent indication of the same drug in the same tumor type (195 [59%]). When considering each tumor type separately, 123 approvals (37%) were based on a new mechanism of action. Conclusions and Relevance: In this study, approvals based on a new mechanism of action represented a minority of all approvals. Further consideration of incentives for drug development are needed to prioritize novel or highly innovative and transformative anticancer drugs.
Subject(s)
Antineoplastic Agents/pharmacology , Drug Approval/statistics & numerical data , United States Food and Drug Administration , Antineoplastic Agents/classification , Antineoplastic Agents/standards , Cross-Sectional Studies , Drug Approval/methods , Humans , Retrospective Studies , United StatesABSTRACT
Increasing oncological treatment costs are a major global concern with the risk of entailing two-tiered health care. Among cost determining factors is the price of individual drugs. In recognition of the central role of this factor, we present a comprehensive overview of the development of monthly prices of oncological drugs introduced over the last 15 years in Switzerland. We identified all oncological drugs newly reimbursed by mandatory health insurance in 2005-2019, and searched public repositories for their package prices, indications with approval dates, and treatment regimens for the calculation of (indication-specific) monthly prices. We found 81 products covering 77 different substances (39.5% protein kinase inhibitors, 21.0% monoclonal antibodies). Most indications related to the topography "blood", followed by "lung and thorax" and "digestive tract". From 20052009 to 20152019, the median monthly product price over all distinct indications of all products decreased by 7.56% (CHF 5,699 [interquartile range 4,4837,321] to CHF 5,268 [4,0196,967]), whereas it increased by 73.7% for monoclonal antibodies. In December 2019, six products had monthly prices over CHF 10,000, all approved for hematological or dermatological cancers. Our analysis suggests that individual price developments of oncological drugs are presently not the major driver of rising cancer treatment costs. However, rising launch prices of some new, mostly hematological drugs are of concern and require continued monitoring.
Subject(s)
Antineoplastic Agents/economics , Drug Costs/trends , Neoplasms/drug therapy , Antineoplastic Agents/classification , Antineoplastic Agents/therapeutic use , Humans , Insurance, Health, Reimbursement , Neoplasms/economics , SwitzerlandABSTRACT
Kirsten rat sarcoma viral oncogene homolog (KRAS) is a proto-oncogene of the RAS-MAPK pathway. KRAS mutations are present in a variety of malignancies including lung, colorectal, and pancreatic cancer. Until the recent approval of sotorasib, a KRAS G12C inhibitor, lack of targeted therapy for KRAS has resulted in poor prognosis of patients with tumors harboring KRAS mutations. While the conditional approval of sotorasib was a major breakthrough for those patients harboring KRAS G12C mutations, G12C only accounts for a fraction of those with KRAS mutations and eventual resistance to G12C inhibitors are unavoidable. This comprehensive review on KRAS inhibitors covers accumulating evidence on not only the G12C inhibitors but also other therapeutic attempts to tackle KRAS including combination therapy as well as direct inhibition with vaccines, adoptive T cell therapy, proteolysis-targeted chimeras (PROTACs) and CRISPR/Cas9.
Subject(s)
Antineoplastic Agents , Cancer Vaccines/pharmacology , Gene Editing/methods , Immunotherapy, Adoptive/methods , Neoplasms , Proto-Oncogene Proteins p21(ras) , Antineoplastic Agents/classification , Antineoplastic Agents/pharmacology , CRISPR-Associated Protein 9/metabolism , Genetic Therapy/methods , Humans , Molecular Targeted Therapy/methods , Neoplasms/drug therapy , Neoplasms/genetics , Neoplasms/pathology , Proto-Oncogene Mas , Proto-Oncogene Proteins p21(ras)/antagonists & inhibitors , Proto-Oncogene Proteins p21(ras)/geneticsABSTRACT
ABSTRACT: This study aimed to investigate the effect of molecular targeted agents (MTAs) in chemo on platinum-resistant recurrent ovarian cancer (ROC). We performed this meta-analysis according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses statements. Randomized controlled trials reporting data about platinum-resistant ovarian cancer treated by MTAs were included. The endpoints for the present study included overall survival and progression-free survival. We analyzed 9 randomized controlled trials including 3631 patients with ROC. The pooled analysis indicated that a combination of MTAs with chemo could markedly increase objective response rate in those patients (Pâ=â.012). Nevertheless, the survival rate of those patients was not markedly changed (Pâ=â.19). Besides, the combination of MTAs with chemo dramatically aggravated the occurrence of adverse events (Pâ<â.05). Moreover, it resulted in the termination of treatment (Pâ=â.044) in those patients, but it had no effect on fatal adverse events (Pâ=â.16). Our results indicated that the combination of MTAs with chemo notably improved objective response rate in patients with platinum-resistant ROC, but its benefit did not translate into survival benefits.
Subject(s)
Antineoplastic Agents , Molecular Targeted Therapy/methods , Neoplasm Recurrence, Local/drug therapy , Ovarian Neoplasms , Antineoplastic Agents/classification , Antineoplastic Agents/pharmacology , Drug Resistance, Neoplasm , Female , Humans , Ovarian Neoplasms/drug therapy , Ovarian Neoplasms/mortality , Ovarian Neoplasms/pathology , Survival AnalysisABSTRACT
Breast cancer is the most common and deadliest cancer in women worldwide. Although notable advances have been achieved in the treatment of breast cancer, the overall survival rate of metastatic breast cancer patients is still considerably low due to the development of resistance to breast cancer chemotherapeutic agents and the non-optimal specificity of the current generation of cancer medications. Hence, there is a growing interest in the search for alternative therapeutics with novel anticancer mechanisms. Recently, antimicrobial peptides (AMPs) have gained much attention due to their cost-effectiveness, high specificity of action, and robust efficacy. However, there are no clinical data available about their efficacy. This warrants the increasing need for clinical trials to be conducted to assess the efficacy of this new class of drugs. Here, we will focus on the recent progress in the use of AMPs for breast cancer therapy and will highlight their modes of action. Finally, we will discuss the combination of AMP-based therapeutics with other breast cancer therapy strategies, including nanotherapy and chemotherapy, which may provide a potential avenue for overcoming drug resistance.
Subject(s)
Antimicrobial Peptides/administration & dosage , Antineoplastic Agents/administration & dosage , Breast Neoplasms/drug therapy , Animals , Antimicrobial Peptides/chemistry , Antimicrobial Peptides/classification , Antineoplastic Agents/chemistry , Antineoplastic Agents/classification , Antineoplastic Combined Chemotherapy Protocols/administration & dosage , Drug Delivery Systems , Female , HumansABSTRACT
BACKGROUND: Increasingly, cancer drugs are being approved based on surrogate measurements of efficacy. Clinically meaningful data, such as overall survival (OS) and quality of life, are often only presented in subsequent publications. We examined if the clinical benefit of cancer drugs, as measured by the European Society for Medical Oncology Magnitude of Clinical Benefit Scale (ESMO-MCBS), improves post-European Medicines Agency (EMA) approval as more data emerges. METHODS: Cancer drug indications approved by the EMA from January 2006 to December 2016 were reviewed and trials cited for efficacy were identified. Primary and subsequent publications (up to December 2019) of scorable trials were included. Changes in benefit over time were measured using ESMO-MCBS thresholds for non-curative (≥4 for substantial, =3 for intermediate and ≤2 for low benefit) and curative intent (A or B for major benefit) scoring. RESULTS: Fifty-five non-curative and two curative intent trials were included. At approval, 29.1% of non-curative trials were substantial, 45.5% intermediate and 25.5% low benefit. For curative intent trials, one displayed major benefit and one displayed no major benefit. We identified 82 subsequent publications for reassessment. A change in ESMO-MCBS classification was seen in 34.5% of non-curative trials (11 raised and 8 lowered). At 3-year reassessment, 36.4% of non-curative trials were substantial, 34.5% intermediate and 29.1% low benefit. Both curative trials showed no major benefit at reassessment. CONCLUSION: As over a third of trials changed classification, in either direction, reassessing the ESMO-MCBS score of approved cancer drugs may help to inform patients and ensure ongoing relevance of regulatory and reimbursement decisions.
Subject(s)
Antineoplastic Agents/therapeutic use , Drug Approval , Government Agencies , Neoplasms/drug therapy , Technology Assessment, Biomedical , Antineoplastic Agents/adverse effects , Antineoplastic Agents/classification , Clinical Trials as Topic , Endpoint Determination , Europe , Humans , Life Expectancy , Neoplasms/mortality , Quality of Life , Research Design , Time Factors , Treatment OutcomeABSTRACT
Transient receptor potential vanilloid (TRPV) channels are part of the TRP channel superfamily and named after the first identified member TRPV1, that is sensitive to the vanillylamide capsaicin. Their overall structure is similar to the structure of voltage gated potassium channels (Kv) built up as homotetramers from subunits with six transmembrane helices (S1-S6). Six TRPV channel subtypes (TRPV1-6) are known, that can be subdivided into the thermoTRPV (TRPV1-4) and the Ca2+-selective TRPV channels (TRPV5, TRPV6). Contrary to Kv channels, TRPV channels are not primary voltage gated. All six channels have distinct properties and react to several endogenous ligands as well as different gating stimuli such as heat, pH, mechanical stress, or osmotic changes. Their physiological functions are highly diverse and subtype as well as tissue specific. In many tissues they serve as sensors for different pain stimuli (heat, pressure, pH) and contribute to the homeostasis of electrolytes, the maintenance of barrier functions and the development of macrophages. Due to their fundamental role in manifold physiological and pathophysiological processes, TRPV channels are promising targets for drug development. However, drugs targeting specific TRPV channels, that are suitable for drug therapy, are rare. Moreover, selective and potent compounds for further research at TRPV channels are often lacking. In this review different aspects of the structure, the different gating stimuli, the expression pattern, the physiological and pathophysiological roles as well as the modulating mechanisms of synthetic, natural and endogenous ligands are summarized.
Subject(s)
Analgesics/pharmacology , Antineoplastic Agents/pharmacology , Immunologic Factors/pharmacology , Membrane Transport Modulators/pharmacology , TRPV Cation Channels/metabolism , Analgesics/chemistry , Analgesics/classification , Antineoplastic Agents/chemistry , Antineoplastic Agents/classification , Binding Sites , Brain/cytology , Brain/drug effects , Brain/metabolism , Humans , Immunologic Factors/chemistry , Immunologic Factors/classification , Ion Channel Gating/drug effects , Ligands , Lung/cytology , Lung/drug effects , Lung/metabolism , Membrane Transport Modulators/chemistry , Membrane Transport Modulators/classification , Models, Molecular , Organ Specificity , Protein Binding , Protein Isoforms/agonists , Protein Isoforms/antagonists & inhibitors , Protein Isoforms/classification , Protein Isoforms/metabolism , Protein Structure, Secondary , Spleen/cytology , Spleen/drug effects , Spleen/metabolism , TRPV Cation Channels/agonists , TRPV Cation Channels/antagonists & inhibitors , TRPV Cation Channels/classificationABSTRACT
Organoids allow the recapitulation of intestinal homeostasis and cancerogenesis in vitro; however, RNA sequencing (RNA-seq)-based methods for drug screens are missing. We develop targeted organoid sequencing (TORNADO-seq), a high-throughput, high-content drug discovery platform that uses targeted RNA-seq to monitor the expression of large gene signatures for the detailed evaluation of cellular phenotypes in organoids. TORNADO-seq is a fast, highly reproducible time- and cost-effective ($5 per sample) method that can probe cell mixtures and their differentiation state in the intestinal system. We apply this method to isolate drugs that enrich for differentiated cell phenotypes and show that these drugs are highly efficacious against cancer compared to wild-type organoids. Furthermore, TORNADO-seq facilitates in-depth insight into the mode of action of these drugs. Our technology can easily be adapted to many other systems and will allow for more systematic, large-scale, and quantitative approaches to study the biology of complex cellular systems.
Subject(s)
Antineoplastic Agents/pharmacology , Early Detection of Cancer/methods , Gene Expression Regulation, Neoplastic/drug effects , Organoids/drug effects , Prescription Drugs/pharmacology , Small Molecule Libraries/pharmacology , Antineoplastic Agents/chemistry , Antineoplastic Agents/classification , Cell Differentiation/drug effects , Colorectal Neoplasms/drug therapy , Colorectal Neoplasms/genetics , Colorectal Neoplasms/metabolism , Colorectal Neoplasms/pathology , Drug Discovery/methods , Drug Repositioning , Enterocytes/drug effects , Enterocytes/metabolism , Enterocytes/pathology , Gene Regulatory Networks , Goblet Cells/drug effects , Goblet Cells/metabolism , Goblet Cells/pathology , High-Throughput Screening Assays , Humans , Neoplasm Proteins/antagonists & inhibitors , Neoplasm Proteins/genetics , Neoplasm Proteins/metabolism , Neoplastic Stem Cells/drug effects , Neoplastic Stem Cells/metabolism , Neoplastic Stem Cells/pathology , Organoids/metabolism , Organoids/pathology , Paneth Cells/drug effects , Paneth Cells/metabolism , Paneth Cells/pathology , Prescription Drugs/chemistry , Prescription Drugs/classification , RNA-Seq , Sequence Analysis, RNA , Small Molecule Libraries/chemistry , Small Molecule Libraries/classificationABSTRACT
BACKGROUND: Information regarding response to past treatments may provide clues concerning the classes of drugs most or least likely to work for a particular metastatic or neoadjuvant early stage breast cancer patient. However, currently there is no systematized knowledge base that would support clinical treatment decision-making that takes response history into account. METHODS: To model history-dependent response data we leveraged a published in vitro breast cancer viability dataset (84 cell lines, 90 therapeutic compounds) to calculate the odds ratios (log (OR)) of responding to each drug given knowledge of (intrinsic/prior) response to all other agents. This OR matrix assumes (1) response is based on intrinsic rather than acquired characteristics, and (2) intrinsic sensitivity remains unchanged at the time of the next decision point. Fisher's exact test is used to identify predictive pairs and groups of agents (BH p < 0.05). Recommendation systems are used to make further drug recommendations based on past 'history' of response. RESULTS: Of the 90 compounds, 57 have sensitivity profiles significantly associated with those of at least one other agent, mostly targeted drugs. Nearly all associations are positive, with (intrinsic/prior) sensitivity to one agent predicting sensitivity to others in the same or a related class (OR > 1). In vitro conditional response patterns clustered compounds into five predictive classes: (1) DNA damaging agents, (2) Aurora A kinase and cell cycle checkpoint inhibitors; (3) microtubule poisons; (4) HER2/EGFR inhibitors; and (5) PIK3C catalytic subunit inhibitors. The apriori algorithm implementation made further predictions including a directional association between resistance to HER2 inhibition and sensitivity to proteasome inhibitors. CONCLUSIONS: Investigating drug sensitivity conditioned on observed sensitivity or resistance to prior drugs may be pivotal in informing clinicians deciding on the next line of breast cancer treatments for patients who have progressed on their current treatment. This study supports a strategy of treating patients with different agents in the same class where an associated sensitivity was observed, likely after one or more intervening treatments.
Subject(s)
Antineoplastic Agents/therapeutic use , Breast Neoplasms/drug therapy , Carcinoma, Ductal, Breast/secondary , Drug Resistance, Neoplasm , Salvage Therapy/methods , Algorithms , Antineoplastic Agents/classification , Antineoplastic Agents/pharmacology , Breast Neoplasms/pathology , Breast Neoplasms/therapy , Carcinoma, Ductal, Breast/therapy , Cell Line, Tumor , Clinical Decision-Making , Cluster Analysis , Combined Modality Therapy , Data Mining/methods , Datasets as Topic , Disease Management , Drug Screening Assays, Antitumor , Drug Substitution , Female , Humans , Internet , Neoadjuvant Therapy , Progression-Free Survival , Quality of Life , Software Design , Treatment OutcomeABSTRACT
Cancer drug resistance is a major problem for cancer therapy. While many drugs can be effective in first-line treatments, cancer cells can become resistant due to genetic (mutations and chromosomal aberrations) but also epigenetic changes. Hence, many research studies addressed epigenetic drugs in circumventing resistance to conventional therapeutics in different tumor entities and in increasing the efficiency of immune checkpoint therapies. Furthermore, repositioning of already approved drugs in combination with epigenetic modifiers could potentiate their efficacy and thus could be an attractive strategy for cancer treatment. Summarizing, we recapitulate current data on epigenetic drugs and their targets in modulating sensitivity towards conventional and immune therapies, providing evidence that altering expression profiles by epigenetic modifiers holds great potential to improve the clinical outcome of cancer patients.
Subject(s)
Antineoplastic Agents/pharmacology , Drug Resistance, Neoplasm/genetics , Epigenesis, Genetic/drug effects , Histone Code , Neoplasms , Antineoplastic Agents/classification , Drug Discovery , Drug Repositioning , Drug Therapy, Combination/methods , Drug Therapy, Combination/trends , Gene Expression Regulation, Neoplastic , Histone Code/drug effects , Histone Code/physiology , Humans , Neoplasms/drug therapy , Neoplasms/genetics , Neoplasms/metabolismABSTRACT
Peptide-drug conjugates are organic molecules composed of (i) a small drug molecule, (ii) a peptide and (iii) a linker. The drug molecule is mandatory for the biological action, however, its efficacy can be enhanced by targeted delivery, which often also reduces unwanted side effects. For site-specificity the peptide part is mainly responsible. The linker attaches chemically the drug to the peptide, but it could also be biodegradable which ensures controlled liberation of the small drug. Despite the importance of the field, there is no public comprehensive database on these species. Herein we describe ConjuPepBD, a freely available, fully annotated and manually curated database of peptide drug conjugates. ConjuPepDB contains basic information about the entries, e.g. CAS number. Furthermore, it also implies their biomedical application and the type of chemical conjugation employed. It covers more than 1600 conjugates from â¼230 publications. The web-interface is user-friendly, intuitive, and useable on several devices, e.g. phones, tablets, PCs. The webpage allows the user to search for content using numerous criteria, chemical structure and a help page is also provided. Besides giving quick insight for newcomers, ConjuPepDB is hoped to be also helpful for researchers from various related fields. The database is accessible at: https://conjupepdb.ttk.hu/.
Subject(s)
Databases, Factual , Delayed-Action Preparations/chemistry , Drugs, Investigational/chemistry , Peptides/chemistry , Prescription Drugs/chemistry , Anti-Infective Agents/chemistry , Anti-Infective Agents/classification , Anti-Infective Agents/therapeutic use , Anti-Inflammatory Agents/chemistry , Anti-Inflammatory Agents/classification , Anti-Inflammatory Agents/therapeutic use , Antineoplastic Agents/chemistry , Antineoplastic Agents/classification , Antineoplastic Agents/therapeutic use , Delayed-Action Preparations/classification , Delayed-Action Preparations/therapeutic use , Drugs, Investigational/classification , Drugs, Investigational/therapeutic use , Humans , Internet , Neuroprotective Agents/chemistry , Neuroprotective Agents/classification , Neuroprotective Agents/therapeutic use , Peptides/therapeutic use , Prescription Drugs/classification , Prescription Drugs/therapeutic use , SoftwareABSTRACT
The prevalence of cancer as a threat to human life, responsible for 9.6 million deaths worldwide in 2018, motivates the search for new anticancer agents. While many options are currently available for treatment, these are often expensive and impact the human body unfavourably. Anticancer peptides represent a promising emerging field of anticancer therapeutics, which are characterized by favourable toxicity profile. The development of accurate in silico methods for anticancer peptide prediction is of paramount importance, as the amount of available sequence data is growing each year. This study leverages advances in machine learning research to produce a novel sequence-based deep neural network classifier for anticancer peptide activity. The classifier achieves performance comparable to the best-in-class, with a cross-validated accuracy of 98.3%, Matthews correlation coefficient of 0.91 and an Area Under the Curve of 0.95. This innovative classifier is available as a web server at https://research.timmons.eu/ennaact, facilitating in silico screening and design of new anticancer peptide chemotherapeutics by the research community.
Subject(s)
Antineoplastic Agents/pharmacology , Deep Learning , Neoplasms/drug therapy , Peptides/pharmacology , Amino Acid Sequence , Animals , Antineoplastic Agents/chemistry , Antineoplastic Agents/classification , Humans , Peptides/chemistry , Peptides/classification , Reproducibility of Results , Structure-Activity RelationshipABSTRACT
Almost all currently approved systemic therapies for hepatocellular carcinoma (HCC) failed to achieve satisfactory therapeutic effect. Exploring tailored treatment strategies for different individuals provides an approach with the potential to maximize clinical benefit. Previously, multiple studies have reported that hepatoma cell lines belonging to different molecular subtypes respond differently to the same treatment. However, these studies only focused on a small number of typical chemotherapy or targeted drugs across limited cell lines due to time and cost constraints. To compensate for the deficiency of previous experimental researches as well as link molecular classification with therapeutic response, we conducted a comprehensive in silico screening, comprising nearly 2000 compounds, to identify compounds with subclass-specific efficacy. Here, we first identified two transcriptome-based HCC subclasses (AS1 and AS2) and then made comparison of drug response between two subclasses. As a result, we not only found that some agents previously considered to have low efficacy in HCC treatment might have promising therapeutic effects for certain subclass, but also identified novel therapeutic compounds that were not routinely used as anti-tumor drugs in clinic. Discovery of agents with subclass-specific efficacy has potential in changing the status quo of population-based therapies in HCC and providing new insights into precision oncology.
Subject(s)
Antineoplastic Agents/therapeutic use , Carcinoma, Hepatocellular , Gene Expression Regulation, Neoplastic , Liver Neoplasms , Transcriptome , Antineoplastic Agents/classification , Carcinoma, Hepatocellular/drug therapy , Carcinoma, Hepatocellular/genetics , Carcinoma, Hepatocellular/metabolism , Drug Screening Assays, Antitumor , Humans , Liver Neoplasms/drug therapy , Liver Neoplasms/genetics , Liver Neoplasms/metabolism , Precision MedicineABSTRACT
Though promising, identifying synergistic combinations from a large pool of candidate drugs remains challenging for cancer treatment. Due to unclear mechanism and limited confirmed cases, only a few computational algorithms are able to predict drug synergy. Yet they normally require the drug-cell treatment results as an essential input, thus exclude the possibility to pre-screen those unexplored drugs without cell treatment profiling. Based on the largest dataset of 33,574 combinational scenarios, we proposed a handy webserver, H-RACS, to overcome the above problems. Being loaded with chemical structures and target information, H-RACS can recommend potential synergistic pairs between candidate drugs on 928 cell lines of 24 prevalent cancer types. A high model performance was achieved with AUC of 0.89 on independent combinational scenarios. On the second independent validation of DREAM dataset, H-RACS obtained precision of 67% among its top 5% ranking list. When being tested on new combinations and new cell lines, H-RACS showed strong extendibility with AUC of 0.84 and 0.81 respectively. As the first online server freely accessible at http://www.badd-cao.net/h-racs, H-RACS may promote the pre-screening of synergistic combinations for new chemical drugs on unexplored cancers.
Subject(s)
Antineoplastic Agents/pharmacology , Antineoplastic Combined Chemotherapy Protocols/pharmacology , Databases, Pharmaceutical , Machine Learning , Neoplasms/drug therapy , Antineoplastic Agents/chemistry , Antineoplastic Agents/classification , Cell Line, Tumor , Drug Synergism , Humans , Molecular Structure , Neoplasms/genetics , Neoplasms/metabolism , Neoplasms/pathology , Reproducibility of Results , Structure-Activity RelationshipABSTRACT
Worldwide incidence and mortality due to the coronavirus disease 2019 (COVID-19) pandemic is greatest in the United States, with the initial epicenter in New York. In Nassau County, New York, where we practice, our institution has had more than 2500 cases and has discharged from the hospital more than 1000 patients. As many academic and private institutions have swiftly shifted their clinical and research priorities to address the pandemic, data are emerging regarding both the impact of malignancy on COVID-19 outcomes as well as the challenges faced in assuring that cancer care remains unimpeded. Of concern, recent studies of cancer patients primarily in China and Italy have suggested that advanced malignancy is associated with increased susceptibility to severe COVID-19 infection. At present, more than 500 clinical trials are underway investigating the pathogenesis and treatment of COVID-19, including expanded use of oncology drugs, such as small molecular inhibitors of cytokine pathways. Here, we begin by reviewing the latest understanding of COVID-19 pathophysiology and then focus our attention on the impact of this virus on hematologic and oncologic practice. Finally, we highlight ongoing investigational treatment approaches that are so relevant to the care of oncology patients during this extraordinary pandemic.
Subject(s)
Antineoplastic Agents , Betacoronavirus , Coronavirus Infections , Delivery of Health Care , Infection Control , Medical Oncology , Neoplasms , Pandemics , Pneumonia, Viral , Antineoplastic Agents/classification , Antineoplastic Agents/pharmacology , Betacoronavirus/drug effects , Betacoronavirus/pathogenicity , Betacoronavirus/physiology , COVID-19 , Clinical Trials as Topic/methods , Clinical Trials as Topic/standards , Coronavirus Infections/epidemiology , Coronavirus Infections/prevention & control , Coronavirus Infections/therapy , Coronavirus Infections/virology , Delivery of Health Care/organization & administration , Delivery of Health Care/standards , Delivery of Health Care/trends , Drugs, Investigational/pharmacology , Humans , Infection Control/methods , Infection Control/organization & administration , Medical Oncology/methods , Medical Oncology/standards , Neoplasms/epidemiology , Neoplasms/therapy , New York/epidemiology , Pandemics/prevention & control , Patient Care/methods , Patient Care/standards , Pneumonia, Viral/epidemiology , Pneumonia, Viral/prevention & control , Pneumonia, Viral/therapy , Pneumonia, Viral/virology , Risk Adjustment/methods , Risk Assessment , SARS-CoV-2ABSTRACT
The article summarizes the roles of polysaccharides in the biology of fungi and their relationship in the development of new technologies. The comparative approach between the evolution of fungi and the chemistry of glycobiology elucidated relevant aspects about the role of polysaccharides in fungi. Also, based on the knowledge of fungal glycobiology, it was possible to address the development of new technologies, such as the production of new anti-tumor drugs, vaccines, biomaterials, and applications in the field of robotics. We conclude that polysaccharides activate pathways of apoptosis, secretion of pro-inflammatory substances, and macrophage, inducing anticancer activity. Also, the activation of the immune system, which opens the way for the production of vaccines. The development of biomaterials and parts for robotics is a promising and little-explored field. Finally, the article is multidisciplinary, with a different and integrated approach to the role of nature in the sustainable development of new technologies.
Subject(s)
Antineoplastic Agents/chemistry , Biotechnology/methods , Fungal Polysaccharides/chemistry , Fungi/chemistry , Immunologic Factors/chemistry , Antineoplastic Agents/classification , Antineoplastic Agents/isolation & purification , Antineoplastic Agents/pharmacology , Biocompatible Materials/isolation & purification , Biocompatible Materials/pharmacology , Electronics/methods , Fungal Polysaccharides/classification , Fungal Polysaccharides/isolation & purification , Fungal Polysaccharides/pharmacology , Fungi/metabolism , Glycomics/methods , Humans , Immunologic Factors/classification , Immunologic Factors/isolation & purification , Immunologic Factors/pharmacology , Macrophages/cytology , Macrophages/drug effects , Macrophages/immunology , Rheology , Robotics/methods , Signal Transduction , Vaccines/administration & dosage , Vaccines/chemical synthesisABSTRACT
SUMMARY: Antineoplastic drugs are used to treat cancer, having their therapeutic effect by inhibiting the cell division process. Although cancer cells, due to their rapid growth, are more sensitive to the toxic effects of chemotherapeutic agents, healthy cells and tissues may also be damaged. Many studies show acute and chronic toxicity both in patients treated with chemotherapy and in exposed workers. In fact, exposure to these substances can also be linked to the formation of different types of secondary tumors. The International Agency on Research on Cancer (IARC) included some antineplastic drugs in Group 1 (carcinogenic to humans), in Group 2A (probable carcinogens for In recent years, many studies have evidenced the presence of antineoplastic drug contamination on work surfaces, materials and floors and based on these observations, international and national guidelines have been published to limit occupational exposure, with particular attention to procedures post-preparation of chemotherapy to limit as much as possible the accumulation of contaminated residues. The aim of the following study is to determine the effectiveness of the degradation of four antineoplastic drugs: 5-fluorouracil, azacitidine, cytarabine and irinotecan using a low concentration of sodium hypochlorite solution (0.115%). The analytical platform used to monitor the degradation course of the substances under examination was hydrogen nuclear magnetic spectroscopy (1H NMR). In the same experimental conditions the effectiveness of the degradation of the same antineoplastic drugs with a 99.9% ethanol solution was also evaluated. The study showed that the best degradation efficiency (> 90% ) is obtained with the hypochlorite solution after 15 minutes.
Subject(s)
Antineoplastic Agents/chemistry , Carcinogens/chemistry , Magnetic Resonance Spectroscopy/methods , Sodium Hypochlorite/pharmacology , Antineoplastic Agents/adverse effects , Antineoplastic Agents/classification , Azacitidine/chemistry , Carcinogens/classification , Cytarabine/chemistry , Decontamination/methods , Drug Interactions , Ethanol/pharmacology , Fluorouracil/chemistry , Humans , Hypochlorous Acid/pharmacology , Irinotecan/chemistry , Occupational Exposure/adverse effects , Occupational Exposure/prevention & control , Preliminary Data , Sodium Chloride/pharmacology , Time FactorsABSTRACT
PURPOSE: The current standard-of-care for front-line therapy for acute myeloid leukaemia (AML) results in short-term and long-term toxicity, but still approximately 40% of children relapse. Therefore, there is a major need to accelerate the evaluation of innovative medicines, yet drug development continues to be adult-focused. Furthermore, the large number of competing agents in rare patient populations requires coordinated prioritisation, within the global regulatory framework and cooperative group initiatives. METHODS: The fourth multi-stakeholder Paediatric Strategy Forum focused on AML in children and adolescents. RESULTS: CD123 is a high priority target and the paediatric development should be accelerated as a proof-of-concept. Efforts must be coordinated, however, as there are a limited number of studies that can be delivered. Studies of FLT3 inhibitors in agreed paediatric investigation plans present challenges to be completed because they require enrolment of a larger number of patients than actually exist. A consensus was developed by industry and academia of optimised clinical trials. For AML with rare mutations that are more frequent in adolescents than in children, adult trials should enrol adolescents and when scientifically justified, efficacy data could be extrapolated. Methodologies and definitions of minimal residual disease need to be standardised internationally and validated as a new response criterion. Industry supported, academic sponsored platform trials could identify products to be further developed. The Leukaemia and Lymphoma Society PedAL/EUpAL initiative has the potential to be a major advance in the field. CONCLUSION: These initiatives continue to accelerate drug development for children with AML and ultimately improve clinical outcomes.