Unravelling patient predictors of ex vivo stem cell expansion
Research type
Research Study
Full title
Unravelling patient predictors of mesenchymal stem cell expansion in an orthopaedic setting.
IRAS ID
241572
Contact name
Susan Clarke
Contact email
Sponsor organisation
Queen's University Belfast
Duration of Study in the UK
2 years, 4 months, 23 days
Research summary
Summary of Research
The body has the ability to repair many tissues itself and this repair is driven mainly by stem cells- a group of cells with the ability to become different tissues. In adults, these cells are found in small numbers but new treatments have developed which involve taking a sample of stem cells from the patient, expanding the number in the laboratory outside the body and then delivering them back to the injury site in larger numbers than would usually be found- stimulating greater amounts of repair. This is Cell Therapy and has been used experimentally to treat conditions from cardiovascular disease to dementia. For some patients, however, the cells do not increase in number enough outside the body to be useful for these cell therapies.Stem cells are found in a number of locations in the adult but are usually taken from bone marrow. The amount of stem cells can be affected by patient factors such as age and we recently showed that it was also affected by body mass index (BMI) in men. The application of our research focuses on bone repair and on stimulating these stem cells to become bone-forming cells. We also know that the mechanisms controlling bone and those controlling fat are very closely related which may explain why BMI had an effect in our previous research.
The aim of this study is to investigate this link further and to see if we can use patient measures to predict the size of the stem cell population. This would allow cell therapies to be targeted to those patients likely to respond and prevent the need for invasive procedures on those unlikely to benefit.
Summary of Results
The body can repair many tissues itself and this repair is driven mainly by stem cells within the tissues. In adults, these cells are found in small numbers (when compared to children) but new therapies have developed which involve taking a sample of stem cells from the patient (autologous), expanding their numbers in the lab and then delivering them back to the injury site stimulating greater amounts of repair. This is Cell Therapy and has great potential to treat a variety of diseases. Within the UK alone more than 1000 “cell therapy” clinical trials have already been completed and a further 1500+ clinical trials are currently underway to treat a range of ailments including osteoporosis, and other conditions affecting bone. Yet anecdotally, there is evidence that stem cells from some patients are unable to expand enough in the lab and the therapy is less likely to succeed. Ideally, we could create a way of predicting whether a patient was suitable for stem cell therapy (whether their stem cells would expand enough in the lab to give numbers likely to produce an effect) before their cells were extracted but, given the number of factors that could affect cell growth, is it feasible to try to create a model that would predict this? The aim of this project was to test the feasibility of creating a computational model capable of predicting stem cell expansion based on a set of patient parameters.One of the main sources of adult stem cells is bone marrow. We know that age, body mass index and underlying health conditions can affect the ability of the bone marrow-derived stem cells (BMSCs) to replicate, but other unknown factors are probably also important.
The specific study objectives were to:
investigate the link between regulation of fat metabolism and the ability of the BMSCs to become bone cells
to identify other patient factors that may affect the stem cells growth and function
to build a computational model that could predict the ability of the stem cells to replicate
To achieve the study aims, the work plan was to compare the growth and other characteristics of stem cells taken from 40 participants undergoing elective orthopaedic surgery and to combine this with other patient characteristics to develop a computational model. This initial sample of 40 patients would be used to identify:
the sample size needed to build a robust model in a future study
the feasibility of recruiting the sample required for a full scale study
primary and secondary outcome measures for a full scale study
The project depended on bone marrow samples being collected during surgery at the point of enrolment to the study and the participant was then required to attend a follow-up at the clinical trial unit to complete other measurements. Both parts of participant interaction were essential to fully meet the study objectives. Prior to the UK lockdown in March 2020, 20 participants were recruited with bone marrow sample collection- five failed to return for follow-up giving a retention of 75% prior to the pandemic. Once it was deemed safe to return to work, a further seven participants were recruited- four of these seven participants failed to return for follow-up (42% retention). In total, 25 participants were recruited with nine lost to follow up giving a retention of 64%. Reasons for failure to return included scheduling conflicts, inability to travel and not responding to telephone or SMS messages.
Summary of results:
Sample size and Feasibility of recruitment for full trial
One of the purposes of this feasibility study was to calculate the number of participants needed for a full-scale study. Assuming a medium effect, a future study would require 54 participants to achieve 80% power, but due to the considerable number of factors that may have some influence, it would be more realistic to assume a weak effect. To achieve 80% power with a weak effect would require 84 full participant datasets. Assuming a similar rate of recruitment and retention as in the pre-pandemic pilot, 114 initial participants would be required which would take approximately 6 years at our rate of recruitment.
In addition, we obtained bone marrow from patients undergoing a particular type of spinal surgery but we found that very few women underwent this surgery and most of our participants were male. This means that we would not be able to tell if there was a difference between male and female stem cells in a full-scale study. To address both recruitment rate and participant diversity, a full-scale study should consider including patients undergoing other surgeries.
Outcome Measures for full trial
This pilot study provided valuable information to inform the best patient factors to measure for a full-size study.
Bone markers in the blood (calcium, phosphate, ALP, albumin, P1NP, XNT) were not correlated with changes to BMSCs and could be excluded from future studies. Similarly, measures of blood glucose did not contribute to the predictive model and could be removed. This would remove the need for participants to fast before attending for follow-up which may improve retention rates and will also reduce the number of blood samples required.
We found that physical activity was the factor that was most strongly related to BMSCs growth. A pedometer or accelerometer may provide a more accurate representation of their activity but would ideally be conducted at a time when they are at a normal level of physical activity and may not be possible.
By following these recommendations, reducing the list of measurements taken and with a larger sample population, a better model could be developed which might be able to predict if a patient’s stem cells will be suitable as Cell Therapies.
Conclusion
This was a feasibility study to determine if a prediction model could be developed as a clinical tool to identify the ability of BMSCs to grow and hence the suitability of a patient for stem cell therapy treatment. The study objectives were met and a number of recommendations were made. If this study were to proceed, recruitment would be the main challenge and measures should be taken to address this in the study design.
REC name
HSC REC A
REC reference
18/NI/0174
Date of REC Opinion
19 Oct 2018
REC opinion
Further Information Favourable Opinion