Drug-Adapted Cancer Cell Lines as Preclinical Models of Acquired Resistance

Acquired resistance formation limits the efficacy of anti-cancer therapies. Acquired and intrinsic resistance differ conceptually. Acquired resistance is the consequence of directed evolution, whereas intrinsic resistance depends on the (stochastic) presence of pre-existing resistance mechanisms. Preclinical model systems are needed to study acquired drug resistance because they enable: (1) in depth functional studies; (2) the investigation of non-standard treatments for a certain disease condition (which is necessary to identify small groups of responders); and (3) the comparison of multiple therapies in the same system. Hence, they complement data derived from clinical trials and clinical specimens, including liquid biopsies. Many groups have successfully used drug-adapted cancer cell lines to identify and elucidate clinically relevant resistance mechanisms to targeted and cytotoxic anti-cancer drugs. Hence, we argue that drug-adapted cancer cell lines represent a preclinical model system in their own right that is complementary to other preclinical model systems and clinical data

Is the Bombali virus pathogenic in humans?

Motivation: The potential of the Bombali virus, a novel Ebolavirus, to cause disease in humans remains unknown. We have previously identified potential determinants of Ebolavirus pathogenicity in humans by analysing the amino acid positions that are differentially conserved (specificity 15 determining positions; SDPs) between human pathogenic Ebolaviruses and the non-pathogenic Reston virus. Here, we include the many Ebolavirus genome sequences that have since become available into our analysis and investigate the amino acid sequence of the Bombali virus proteins at the SDPs that discriminate between human pathogenic and non-human pathogenic Ebolaviruses. 20 Results: The use of 1408 Ebolavirus genomes (196 in the original analysis) resulted in a set of 166 SDPs (reduced from 180), 146 (88%) of which were retained from the original analysis. This indicates the robustness of our approach and refines the set of SDPs that distinguish human pathogenic Ebolaviruses from Reston virus. At SDPs, Bombali virus shared the majority of amino acids with the human pathogenic Ebolaviruses (63.25%). However, for two SDPs in VP24 (M136L, R139S) 25 that have been proposed to be critical for the lack of Reston virus human pathogenicity because they alter the VP24-karyopherin interaction, the Bombali virus amino acids match those of Reston virus. Thus, Bombali virus may not be pathogenic in humans. Supporting this, no Bombali virusassociated disease outbreaks have been reported, although Bombali virus was isolated from fruit bats cohabitating in close contact with humans, and anti-Ebolavirus antibodies that may indicate 30 contact with Bombali virus have been detected in humans

Risks Posed by Reston, the Forgotten Ebolavirus

Out of the five members of the Ebolavirus family, four cause lifethreatening disease, whereas the fifth, Reston virus (RESTV), is nonpathogenic in humans. The reasons for this discrepancy remain unclear. In this review, we analyze the currently available information to provide a state-of-the-art summary of the factors that determine the human pathogenicity of Ebolaviruses. RESTV causes sporadic infections in cynomolgus monkeys and is found in domestic pigs throughout the Philippines and China. Phylogenetic analyses revealed that RESTV is most closely related to the Sudan virus, which causes a high mortality rate in humans. Amino acid sequence differences between RESTV and the other Ebolaviruses are found in all nine Ebolavirus proteins, though no one residue appears sufficient to confer pathogenicity. Changes in the glycoprotein contribute to differences in Ebolavirus pathogenicity but are not sufficient to confer pathogenicity on their own. Similarly, differences in VP24 and VP35 affect viral immune evasion and are associated with changes in human pathogenicity. A recent in silico analysis systematically determined the functional consequences of sequence variations between RESTV and human-pathogenic Ebolaviruses. Multiple positions in VP24 were differently conserved between RESTV and the other Ebolaviruses and may alter human pathogenicity. In conclusion, the factors that determine the pathogenicity of Ebolaviruses in humans remain insufficiently understood. An improved understanding of these pathogenicity-determining factors is of crucial importance for disease prevention and for the early detection of emergent and potentially human-pathogenic RESTVs

Understanding of researcher behaviour is required to improve data reliability

Background: A lack of data reproducibility (“reproducibility crisis”) has been extensively debated across many academic disciplines. Main body: Although a reproducibility crisis is widely perceived, conclusive data on the scale of the problem and the underlying reasons are largely lacking. The debate is primarily focused on methodological issues. However, examples such as the use of misidentified cell lines illustrate that the availability of reliable methods does not guarantee good practice. Moreover, research is often characterised by a lack of established methods. Despite the crucial importance of researcher conduct, research and conclusive data on the determinants of researcher behaviour are widely missing. Conclusion: Meta-research is urgently needed that establishes an understanding of the factors that determine researcher behaviour. This knowledge can then be used to implement and iteratively improve measures, which incentivise researchers to apply the highest standards resulting in high quality data

Ebola outbreak highlights the need for wet and dry laboratory collaboration

The recent Ebola outbreak in Western Africa taught us that Ebolaviruses can cause much larger outbreaks and represent a much greater health threat than many of us believed (or wanted to believe). As of 30th March, the outbreak had resulted in 28,646 confirmed cases and 11,323 deaths. Although the WHO stated that the Ebola epidemic in West Africa no longer represents a Public Health Emergency of International Concern, since Guinea, Liberia, and Sierra are now capable of controlling and maintaining further small outbreaks, flare-ups still occur, most recently, on 4th April when two new cases were reported in Liberia (www.who.int)

Incorporation of doxorubicin in different polymer nanoparticles and their anticancer activity

Background: Nanoparticles are under investigation as carrier systems for anticancer drugs. The expression of efflux transporters such as the ATP-binding cassette (ABC) transporter ABCB1 is an important resistance mechanism in therapy-refractory cancer cells. Drug encapsulation into nanoparticles has been shown to bypass efflux-mediated drug resistance, but there are also conflicting results. To investigate whether easy-to-prepare nanoparticles made of well-tolerated polymers may circumvent transporter-mediated drug efflux, we prepared poly(lactic-co-glycolic acid) (PLGA), polylactic acid (PLA), and PEGylated PLGA (PLGA-PEG) nanoparticles loaded with the ABCB1 substrate doxorubicin by solvent displacement and emulsion diffusion approaches and assessed their anticancer efficiency in neuroblastoma cells, including ABCB1-expressing cell lines, in comparison to doxorubicin solution. Results: The resulting nanoparticles covered a size range between 73 and 246 nm. PLGA-PEG nanoparticle preparation by solvent displacement led to the smallest nanoparticles. In PLGA nanoparticles, the drug load could be optimised using solvent displacement at pH 7 reaching 53 µg doxorubicin/mg nanoparticle. These PLGA nanoparticles displayed sustained doxorubicin release kinetics compared to the more burst-like kinetics of the other preparations. In neuroblastoma cells, doxorubicin-loaded PLGA-PEG nanoparticles (presumably due to their small size) and PLGA nanoparticles prepared by solvent displacement at pH 7 (presumably due to their high drug load and superior drug release kinetics) exerted the strongest anticancer effects. However, nanoparticle-encapsulated doxorubicin did not display increased efficacy in ABCB1-expressing cells relative to doxorubicin solution. Conclusion: Doxorubicin-loaded nanoparticles made by different methods from different materials displayed substantial discrepancies in their anticancer activity at the cellular level. Optimised preparation methods resulted in PLGA nanoparticles characterised by increased drug load, controlled drug release, and high anticancer efficacy. The design of drug-loaded nanoparticles with optimised anticancer activity at the cellular level is an important step in the development of improved nanoparticle preparations for anticancer therapy. Further research is required to understand under which circumstances nanoparticles can be used to overcome efflux-mediated resistance in cancer cells

COVID-19-Related Coagulopathy—Is Transferrin a Missing Link?

SARS-CoV-2 is the causative agent of COVID-19. Severe COVID-19 disease has been associated with disseminated intravascular coagulation and thrombosis, but the mechanisms underlying COVID-19-related coagulopathy remain unknown. The risk of severe COVID-19 disease is higher in males than in females and increases with age. To identify gene products that may contribute to COVID-19-related coagulopathy, we analyzed the expression of genes associated with the Gene Ontology (GO) term “blood coagulation” in the Genotype-Tissue Expression (GTEx) database and identified four procoagulants, whose expression is higher in males and increases with age (ADAMTS13, F11, HGFAC, KLKB1), and two anticoagulants, whose expression is higher in females and decreases with age (C1QTNF1, SERPINA5). However, the expression of none of these genes was regulated in a proteomics dataset of SARS-CoV-2-infected cells and none of the proteins have been identified as a binding partner of SARS-CoV-2 proteins. Hence, they may rather generally predispose individuals to thrombosis without directly contributing to COVID-19-related coagulopathy. In contrast, the expression of the procoagulant transferrin (not associated to the GO term “blood coagulation”) was higher in males, increased with age, and was upregulated upon SARS-CoV-2 infection. Hence, transferrin warrants further examination in ongoing clinic-pathological investigation

Large inherent variability in data derived from highly standardised cell culture experiments.

Cancer drug development is hindered by high clinical attrition rates, which are blamed on weak predictive power by preclinical models and limited replicability of preclinical findings. However, the technically feasible level of replicability remains unknown. To fill this gap, we conducted an analysis of data from the NCI60 cancer cell line screen (2.8 million compound/cell line experiments), which is to our knowledge the largest depository of experiments that have been repeatedly performed over decades. The findings revealed profound intra-laboratory data variability, although all experiments were executed following highly standardised protocols that avoid all known confounders of data quality. All compound/ cell line combinations with > 100 independent biological replicates displayed maximum GI50 (50% growth inhibition) fold changes (highest/ lowest GI50) > 5% and 70.5% displayed maximum fold changes > 1000. The highest maximum fold change was 3.16 × 10 (lowest GI50: 7.93 ×10 µM, highest GI50: 25.0 µM). FDA-approved drugs and experimental agents displayed similar variation. Variability remained high after outlier removal, when only considering experiments that tested drugs at the same concentration range, and when only considering NCI60-provided quality-controlled data. In conclusion, high variability is an intrinsic feature of anti-cancer drug testing, even among standardised experiments in a world-leading research environment. Awareness of this inherent variability will support realistic data interpretation and inspire research to improve data robustness. Further research will have to show whether the inclusion of a wider variety of model systems, such as animal and/ or patient-derived models, may improve data robustness. [Abstract copyright: Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.