Repurposing antimalarials for COVID-19: Doing more harm than good?
In the absence of an effective therapy for COVID-19 there has been growing interest in repurposing drugs, such as the antimalarials chloroquine (CQ) and its derivative hydroxychloroquine (HCQ).
Interest in chloroquine/hydroxychloroquine was sparked by a publication in March, from a French professor , reporting significant reductions in viral loads in COVID-19 patients from a non-randomized, uncontrolled, open study of 20 patients. Currently, nearly 150 clinical trials of CQ, HCQ, or both are registered worldwide, but to date there is no clear indication that either drug improves outcomes from COVID-19.
The rationale for promoting CQ/HCQ as a potential therapy against COVID-19 was based on results from in vitro studies. Three studies, two from the same group in Wuhan and one from researchers in Beijing, reported that both drugs were highly effective in reducing SARS-CoV-2 replication (the virus which causes COVID-19) in a cell line. Using a checklist of strict criteria, we judged the quality of the data from each of these studies and concluded that the data did not support their conclusion.
The investigators used VeroE6 cells (an African green monkey kidney cell line) to determine the effectiveness of HCQ and CQ as anti-virals without replicating in a different model – a human cell line, for example. Both groups quantified viral copy number using qRT-PCR but reported only normalised values. I guess we must take it on trust that both compounds reduced viral load? Unfortunately, this lack of transparency was further compounded by poor reporting of technical repeats and it was not at all clear if any of the experiments were actually repeated?
One of the biggest challenges facing biomedical research is poor reproducibility, yet these studies were fast-tracked without peer review and replicability. Ignoring good practices of transparency and rigour can never be justified, particularly in times of crisis. If we cannot trust the preclinical evidence, then how can be justify going forward into patients?
QED Biomedical is helping to tackle the reproducibility crisis. Our methodology, based on the gold standard of systematic review, can identify the most reliable evidence - towards clinical trial success.
Expt. 2 : Immunofluorescent expression of viral protein (NP) in VeroE6 following treatment with CQ or HCQ
Expt. 3A: Mechanism of action of CQ and or HCQ on viral infection of VeroE6 cells. Quantified viral copies by qRT-PCR and normalised to vehicle control
Expt. 3B: Mechanism of action of CQ and or HCQ on viral infection of Vero E6 cells. Quantified expression of NP (a viral protein) by immunofluorescence
NR = Not reported. NA = Not applicable. EB = Error bars. CI = Confidence Intervals Sources Wang Yao Liu
Hierachical cancer stem cell model challenged in glioblastoma24 July 2019 - posted by Dr Anne Collins
The idea that cancer stem cells (CSCs) exist as a defined cellular entity, driving tumour growth and resistances is challenged by a team at the Luxembourg Institute of Health working in glioblastoma; a form of brain cancer.
The researchers found that cellular heterogeneity-which is a hallmark of glioblastoma and makes it particularly difficult to treat- was due to the inherent plasticity of tumour cells rather than multipotent CSCs. They describe their findings in the journal Nature Communications and caution against therapies targeting CSC cell surface markers because all cancer cells have the capacity to reconstitute tumour heterogeneity.
These findings bring into question the validity of numerous studies describing brain CSCs and the rationale of some biotech companies pursuing a strategy of targeting CSCs using immunotherapy. The peer review system is meant to examine papers on potential shortcoming, yet poor study design is often left unchallenged. For example, numerous studies reporting the existence of CSCs failed to test the potency of marker negative cells, applied different growth conditions on marker positive and negative subpopulations thereby introducing bias.
There are a number of initiatives to tackle the reproducibility crisis in biomedicine, such as replicating key landmark studies before embarking on clinical trials. This is both costly and time consuming. Another approach is to use systematic review and evidence-based decision making to verify evidence before embarking on an investment or new direction. QED Biomedical specialises in systematic reviews and tailored evaluations in biomedicine analysing data for validity as well as reproducibility. We can help you make an informed decision.
Patient derived xenograft models: an emerging platform for translational cancer research? 6th May 2019 - posted by Dr Anne Collins
One of the largest studies to date on new drug approvals reported that around 3% of cancer drugs make it to the market. The probability of success improves significantly, to just over 10%, if biomarkers are used to select patients, but this is still a dismal return for what is a considerable investment by pharma and biotech companies. This points to a failure of existing cancer models to reliably predict anticancer activity in the clinic.
Patient-derived xenografts, otherwise known as PDX models, have been cited extensively in the scientific literature as better predictors of response, compared to the more traditional cancer cell line models because they retain the cellular heterogeneity, architecture and molecular characteristic of the original cancer. With the demand for more personalized medicine, the market for PDX models has grown significantly, with pharmaceutical and biotech companies the biggest users. So how reliable are PDX models? Unfortunately, much of what is claimed does not stand up to scrutiny.
PDX models are based on the direct implantation of fresh cancer specimens from individual patients into immunodeficient mice. Once established, in individual mice, each tumour is subsequently expanded into further mice by a process known as serial transplantation. The challenge is that each copy (or xenograft) should reflect the original human cancer and should not deviate with continuous serial transplantation. To assess how well PDX models mimic the disease in man we carried out a systematic review, recently published in PeerJ . We limited the review to the four most common cancers: breast, prostate, colon and lung and used a checklist of strict criteria to determine model validity. What we found was that around half of all breast and prostate studies, that derived xenografts, did not mirror the donor cancer as claimed by the authors. Lung and colon fared somewhat better with 28% of lung and 16% of colon studies judged high risk. For example, lack of concordant gene mutations, discordant clustering from gene expression studies or failure to express tissue-specific markers in line with the donor cancer, were some of the findings reported in this review.
Overall, we categorized most studies as unclear because one or more validation conditions were not reported, or researchers failed to provide data for a proportion of their models. The most common reasons were, failure to demonstrate tissue of origin, response to standard of care agents and to exclude development of lymphoma (a common phenomenon in the PDX field).
Whether or not PDX models are more clinically predictive is yet to be determined, at least for the four most common cancers. Our ability to judge which discoveries/innovations will be beneficial is crucial. Until we adopt a more formal, unbiased assessment of biomedical research findings, with strict guidelines to ensure transparency, we are unlikely to improve the low rate of clinical trial success.