scholarly journals Urothelial cancer organoids: a tool for bladder cancer research

Der Pathologe ◽  
2021 ◽  
Author(s):  
R. P. Meijer
Keyword(s):  
Drug Resistance ◽  
Bladder Cancer ◽  
Precision Medicine ◽  
Resistance Mechanisms ◽  
Model Systems ◽  
Preclinical Model ◽  
Cancer Pathogenesis ◽  
Single Fragment ◽  
Parental Tumor ◽  
Therapeutic Decision Making

Abstract Background Bladder cancer ranks among the top ten most common tumor types worldwide and represents a growing healthcare problem, accounting for a large part of total healthcare costs. Chemotherapy is effective in a subset of patients, while causing severe side effects. Tumor pathogenesis and drug resistance mechanisms are largely unknown. Precision medicine is failing in bladder cancer, as bladder tumors are genetically and molecularly very heterogeneous. Currently, therapeutic decision-making depends on assessing a single fragment of surgically acquired tumor tissue. Objective New preclinical model systems for bladder cancer are indispensable for developing therapeutic strategies tailored to individual patient and tumor characteristics. Organoids are small 3D tissue cultures that simulate small-size organs “in a dish” and tumoroids are a special type of cancer organoid (i.e., malignant tissue). Materials and methods Since 2016, we have collaborated with the renowned Hubrecht Institute to provide proof of concept of tissue-based bladder tumoroids mimicking parental tumors. We have developed a living biobank containing bladder organoids and tumoroids grown from over 50 patient samples, which reflect crucial aspects of bladder cancer pathogenesis. Results Histological and immunofluorescence analysis indicated that the heterogeneity and subclassification of tumoroids mimicked those of corresponding parental tumor samples. Thus, urothelial tumoroids mimic crucial aspects of bladder cancer pathogenesis. Conclusion Research with urothelial tumoroids will open up new avenues for bladder cancer pathogenesis and drug-resistance research as well as for precision medicine approaches.

Learning from metabolic networks: current trends and future directions for precision medicine.

2020 ◽  
Vol 28 ◽  
Author(s):  
Ilaria Granata ◽  
Mario Manzo ◽  
Ari Kusumastuti ◽  
Mario R Guarracino
Keyword(s):  
Systems Biology ◽  
Precision Medicine ◽  
Metabolic Networks ◽  
Information Modeling ◽  
Model Systems ◽  
Specific Information ◽  
Important Indicator ◽  
Predictive Values ◽  
Metabolic Systems ◽  
Metabolic Models

Purpose: Systems biology and network modeling represent, nowadays, the hallmark approaches for the development of predictive and targeted-treatment based precision medicine. The study of health and disease as properties of the human body system allows the understanding of the genotype-phenotype relationship through the definition of molecular interactions and dependencies. In this scenario, metabolism plays a central role as its interactions are well characterized and it is considered an important indicator of the genotype-phenotype associations. In metabolic systems biology, the genome-scale metabolic models are the primary scaffolds to integrate multi-omics data as well as cell-, tissue-, condition-specific information. Modeling the metabolism has both investigative and predictive values. Several methods have been proposed to model systems, which involve steady-state or kinetic approaches, and to extract knowledge through machine and deep learning. Method: This review collects, analyzes, and compares the suitable data and computational approaches for the exploration of metabolic networks as tools for the development of precision medicine. To this extent, we organized it into three main sections: "Data and Databases", "Methods and Tools", and "Metabolic Networks for medicine". In the first one, we have collected the most used data and relative databases to build and annotate metabolic models. In the second section, we have reported the state-of-the-art methods and relative tools to reconstruct, simulate, and interpret metabolic systems. Finally, we have reported the most recent and innovative studies which exploited metabolic networks for the study of several pathological conditions, not only those directly related to the metabolism. Conclusion: We think that this review can be a guide to researchers of different disciplines, from computer science to biology and medicine, in exploring the power, challenges and future promises of the metabolism as predictor and target of the so-called P4 medicine (predictive, preventive, personalized and participatory).

Clinical applications of circulating tumor DNA in monitoring breast cancer drug resistance

2020 ◽  
Vol 16 (34) ◽  
pp. 2863-2878
Author(s):  
Yang Liu ◽  
Qian Du ◽  
Dan Sun ◽  
Ruiying Han ◽  
Mengmeng Teng ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Drug Resistance ◽  
Digital Pcr ◽  
Circulating Tumor Dna ◽  
Resistance Mechanisms ◽  
Clinical Applications ◽  
Current Status ◽  
Cancer Drug ◽  
Genomic Alteration ◽  
Tumor Dna

Breast cancer is one of the leading causes of cancer-related deaths in women worldwide. Unfortunately, treatments often fail because of the development of drug resistance, the underlying mechanisms of which remain unclear. Circulating tumor DNA (ctDNA) is free DNA released into the blood by necrosis, apoptosis or direct secretion by tumor cells. In contrast to repeated, highly invasive tumor biopsies, ctDNA reflects all molecular alterations of tumors dynamically and captures both spatial and temporal tumor heterogeneity. Highly sensitive technologies, including personalized digital PCR and deep sequencing, make it possible to monitor response to therapies, predict drug resistance and tailor treatment regimens by identifying the genomic alteration profile of ctDNA, thereby achieving precision medicine. This review focuses on the current status of ctDNA biology, the technologies used to detect ctDNA and the potential clinical applications of identifying drug resistance mechanisms by detecting tumor-specific genomic alterations in breast cancer.

Dissecting the landscape of CAF-mediated drug resistance mechanisms in ALK-rearranged NSCLC

2020 ◽  
Vol 138 ◽  
pp. S48
Author(s):  
Q. Hu ◽  
L.L. Remsing Rix ◽  
X. Li ◽  
E.A. Welsh ◽  
B. Fang ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Resistance Mechanisms

scholarly journals Cyclodextrin-Based Hybrid Polymeric Complex to Overcome Dual Drug Resistance Mechanisms for Cancer Therapy

Polymers ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1254
Author(s):  
Lingjie Ke ◽  
Zhiguo Li ◽  
Xiaoshan Fan ◽  
Xian Jun Loh ◽  
Hongwei Cheng ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Gene Delivery ◽  
Cell Membrane ◽  
Inclusion Complex ◽  
Polymeric Micelles ◽  
Drug Loading ◽  
Resistance Mechanisms ◽  
Polymeric Complex ◽  
Cavity Structure ◽  
Dual Drug

Drug resistance always reduces the efficacy of chemotherapy, and the classical mechanisms of drug resistance include drug pump efflux and anti-apoptosis mediators-mediated non-pump resistance. In addition, the amphiphilic polymeric micelles with good biocompatibility and high stability have been proven to deliver the drug molecules inside the cavity into the cell membrane regardless of the efflux of the cell membrane pump. We designed a cyclodextrin (CD)-based polymeric complex to deliver chemotherapeutic doxorubicin (DOX) and Nur77ΔDBD gene for combating pumps and non-pump resistance simultaneously. The natural cavity structure of the polymeric complex, which was comprised with β-cyclodextrin-graft-(poly(ε-caprolactone)-adamantly (β-CD-PCL-AD) and β-cyclodextrin-graft-(poly(ε-caprolactone)-poly(2-(dimethylamino) ethyl methacrylate) (β-CD-PCL-PDMAEMA), can achieve the efficient drug loading and delivery to overcome pump drug resistance. The excellent Nur77ΔDBD gene delivery can reverse Bcl-2 from the tumor protector to killer for inhibiting non-pump resistance. The presence of terminal adamantyl (AD) could insert into the cavity of β-CD-PCL-PDMAEMA via host-guest interaction, and the releasing rate of polymeric inclusion complex was higher than that of the individual β-CD-PCL-PDMAEMA. The polymeric inclusion complex can efficiently deliver the Nur77ΔDBD gene than polyethylenimine (PEI-25k), which is a golden standard for nonviral vector gene delivery. The higher transfection efficacy, rapid DOX cellular uptake, and significant synergetic tumor cell viability inhibition were achieved in a pump and non-pump drug resistance cell model. The combined strategy with dual drug resistance mechanisms holds great potential to combat drug-resistant cancer.

scholarly journals Mechanisms of Drug Resistance in the Pathogenesis of Epilepsy: Role of Neuroinflammation. A Literature Review

2021 ◽  
Vol 11 (5) ◽  
pp. 663
Author(s):  
Elena D. Bazhanova ◽  
Alexander A. Kozlov ◽  
Anastasia V. Litovchenko
Keyword(s):  
Drug Resistance ◽  
Premature Death ◽  
Resistance Mechanisms ◽  
Biomedical Literature ◽  
Drug Resistant ◽  
Psychological Consequences ◽  
Text Documents ◽  
Neural Connections ◽  
Inflammatory Processes ◽  
Drug Resistant Epilepsy

Epilepsy is a chronic neurological disorder characterized by recurring spontaneous seizures. Drug resistance appears in 30% of patients and it can lead to premature death, brain damage or a reduced quality of life. The purpose of the study was to analyze the drug resistance mechanisms, especially neuroinflammation, in the epileptogenesis. The information bases of biomedical literature Scopus, PubMed, Google Scholar and SciVerse were used. To obtain full-text documents, electronic resources of PubMed Central and Research Gate were used. The article examines the recent research of the mechanisms of drug resistance in epilepsy and discusses the hypotheses of drug resistance development (genetic, epigenetic, target hypothesis, etc.). Drug-resistant epilepsy is associated with neuroinflammatory, autoimmune and neurodegenerative processes. Neuroinflammation causes immune, pathophysiological, biochemical and psychological consequences. Focal or systemic unregulated inflammatory processes lead to the formation of aberrant neural connections and hyperexcitable neural networks. Inflammatory mediators affect the endothelium of cerebral vessels, destroy contacts between endothelial cells and induce abnormal angiogenesis (the formation of “leaky” vessels), thereby affecting the blood–brain barrier permeability. Thus, the analysis of pro-inflammatory and other components of epileptogenesis can contribute to the further development of the therapeutic treatment of drug-resistant epilepsy.

scholarly journals Functional Genomics Approaches to Elucidate Vulnerabilities of Intrinsic and Acquired Chemotherapy Resistance

Cells ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 260
Author(s):  
Ronay Cetin ◽  
Eva Quandt ◽  
Manuel Kaulich
Keyword(s):  
Drug Resistance ◽  
Acquired Resistance ◽  
Chemotherapy Resistance ◽  
Resistance Mechanisms ◽  
Therapy Failure ◽  
Tightly Coupled ◽  
Unbiased Gene ◽  
Multiple Drugs ◽  
Genome Scale ◽  
Gene Perturbations

Drug resistance is a commonly unavoidable consequence of cancer treatment that results in therapy failure and disease relapse. Intrinsic (pre-existing) or acquired resistance mechanisms can be drug-specific or be applicable to multiple drugs, resulting in multidrug resistance. The presence of drug resistance is, however, tightly coupled to changes in cellular homeostasis, which can lead to resistance-coupled vulnerabilities. Unbiased gene perturbations through RNAi and CRISPR technologies are invaluable tools to establish genotype-to-phenotype relationships at the genome scale. Moreover, their application to cancer cell lines can uncover new vulnerabilities that are associated with resistance mechanisms. Here, we discuss targeted and unbiased RNAi and CRISPR efforts in the discovery of drug resistance mechanisms by focusing on first-in-line chemotherapy and their enforced vulnerabilities, and we present a view forward on which measures should be taken to accelerate their clinical translation.

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