Background
Chronic myeloid leukaemia (CML) is a paradigm of precision medicine, being one of the first cancers to be treated with targeted therapy. This has revolutionised CML therapy and patient outcome, with high survival rates and an ever increasing number of patients living with the disease on life-long therapy [1], and most patients anticipated to have near normal life expectancy [2].
Social and Economic implications of CML
Patients with CML are currently on life-time tyrosine kinase inhibitor (TKI) therapy, this can result in considerable psychological issues for patients as they are ‘living with cancer’ along with the economic burden associated with treating and monitoring the disease. Evaluating biomarkers with the potential to successfully predict patients who will sustain treatment free remission (TFR) is therefore an important avenue of investigation.
DESTINY: The UK de-escalation followed by stopping TKI clinical trial
The DESTINY trial (Pilot of De-Escalation followed by Stopping Treatment with Imatinib, Nilotinib or sprYcel; NCT01804985, study start date December 2013-finish date May 2018) was designed to assess the outcomes of de-escalation and discontinuation of TKI therapy in CP-CML patients in stable MMR or MR4 [major molecular response/MMR; BCR-ABL:ABL transcripts <0.1% on the International Scale (IS)] [3]. TKI treatment (imatinib, dasatinib or nilotinib) was initially reduced to 50% of standard dose for 12 months with monthly molecular monitoring. Thereafter, patients with no rise in BCR-ABL1 transcripts stopped TKI therapy. Monitoring continued monthly for a further 12 months and then 2 monthly for 12 months. Treatment at trial entry was imatinib (148), nilotinib (16) or dasatinib (10), for a median of 6.9 years. In summary, after 36 months on study, molecular recurrence free survival (RFS) was 72% (90% CI: 65-79%) in MR4 patients, and 36% (90% CI 27-50%) in the MMR group. Treatment duration predicted recurrence (p = 0.021), but age, gender, performance status or prior treatment did not. No disease progression was seen; two deaths occurred due to unrelated causes. All recurrences regained MMR within 5 months of treatment resumption [4]. The DESTINY trial took a cautious and novel approach in these optimally responding patients and was the first trial to incorporate a de-escalation phase prior to discontinuation of TKI therapy. Furthermore, the inclusion of patients in both MMR and MR4 was unique, and may identify a further cohort of patients in MMR that can safely de-escalate/discontinue TKI therapy. However, we urgently need to identify accurate biomarkers that will predict those patients that will successfully maintain TFR, especially if we wish to consider the future application of dose reduction/TFR to patients in stable MMR. Critically, for this application, with ethical approval, bone marrow samples were collected and stored in the University of Glasgow CML Biobank from 160/174 DESTINY patients at study entry, and again at molecular recurrence (n=38). Access to these samples gives us a unique opportunity to identify bone marrow biomarkers predictive of TFR success.
Aims
This study aims to understand what biological factors contribute to molecular recurrence in CML patients attempting TFR. To achieve this, we will determine if BCR-ABL1 transcript levels in bone marrow a better predictor of successful TFR compared to BCR-ABL1 transcript levels in peripheral blood; assess whether the presence of leukaemia stem cells (LSC) in the bone marrow of patients in deep molecular remission (DMR) is predictive of TFR failure; explore whether there is a correlation between the immune cell repertoire in the bone marrow of patients in DMR and TFR success; and consider if there is a protein signature in the bone marrow predictive of successful TFR.
Training outcomes
The student will obtain skills in multi-parameter flow cytometry, LUMINEX, proteomics via unbiased proteomic screen using SWATH-MS. Pre-prepared protein reference libraries will target data analysis in silico, SWATH-MS allows for relative quantification of ~500-1000 proteins/sample in collaboration with University of Manchester. Skills in bioinformatics using the Spectronaut DIA search engine (University of Edinburgh) and biostatistics training to integrate data sets to identify Biomarkers through the Robertson Centre University of Glasgow.
Application Instructions
This MRC programme is joint between the Universities of Edinburgh and Glasgow. You will be registered at the host institution of the primary supervisor detailed in your project selection.
All applications should be made via the University of Edinburgh, irrespective of project location. For those applying to a University of Glasgow project, your application along with any supporting documents will be shared with University of Glasgow.
http://www.ed.ac.uk/studying/postgraduate/degrees/index.php?r=site/view&id=919
Please note, you must apply to one of the projects and you must contact the primary supervisor prior to making your application. Additional information on the application process is available from the link above
For more information about Precision Medicine visit:
http://www.ed.ac.uk/usher/precision-medicine
Application Enquiries
Susan Mitchell/Maree Hardie
[Email Address Removed]
https://www.ed.ac.uk/usher/precision-medicine/app-process-eligibility-criteria
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