Blood plasma proteomics for biomarker discovery in Multiple Myeloma
Aim
In this project, we will investigate the blood plasma proteome of healthy individuals from the UK Biobank and MM primary samples from the UCAN Biobank to identify proteins that could serve as biomarkers for early disease detection, aggressiveness, treatment selection, relapse, response and potentially for novel treatment strategies that would facilitate the management of MM.
Background
Multiple Myeloma (MM) is a heterogeneous hematological malignancy characterized by the aberrant proliferation of plasma cells within the bone marrow and the accumulation of monoclonal (M-spike) protein in the blood and serum. It is the second most common hematological malignancy with 660 new myeloma cases diagnosed each year in Sweden out of which 25 are diagnosed yearly at the Dept. of Haematology, Akademiska Sjukhuset, Uppsala, Sweden. To date, diagnosis of MM is quite complex, involves multiple steps and requires that plasma/serum M component >30 g/L (IgA, IgG) and/or Bence Jones proteinuria (lambda or kappa) > 500 mg/24 h and/or at least 10% clonal MB PCs. Furthermore, the patient must fulfil one of the following criteria: hypercalcemia (C), renal failure (R), anaemia (A) and bone lesions (B) (CRAB). In addition, since 2014 myeloma defining events (MDE) are also factored in when establishing treatment procedures. MDE is defined by at least 60% clonal plasma cells in bone marrow sample, a serum free light chain (FLC) (kappa/lambda) ratio >100 and/or two or more skeletal lesions detected using Magnetic Resonance Imaging (MRI).
If CRAB or MDE are absent, the patient is diagnosed with smouldering MM, by which no treatment is initiated but the patient will be scheduled for continued follow-ups. Initial symptoms for seeking medical care include bone pain and extensive fatigue, which is associated with anaemia, renal failure and hypercalcemia. However, by the time the patient seeks medical care the disease might have already progressed. Despite the introduction of novel therapies such as immunomodulating agents, proteasome inhibitors, corticosteroids and alkylators, MM still remains largely incurable. Hence, there is an urgent need to unravel the molecular mechanisms that drive heterogeneous treatment response and resistance in MM patients.
The blood plasma proteome is a source for identification of potentially new treatment avenues. Prior studies have shown that in most cases there is a systemic response observed as a result of the disease which represents the general status of the patient. Thus, the altered blood plasma proteome of MM could constitute a novel target for personalised medicine.
Project plan
Our initial investigation will focus on the analysis of the blood plasma proteome of 50.000 healthy individuals from the UK Biobank to identify a protein signature that could predict multiple myeloma years before symptom initiation and diagnosis. To validate our findings, we will perform large scale blood plasma proteomics analysis with the Olink Explore platform on the 384 diagnosed MM primary samples collected within the UCAN biobank. Furthermore, using the clinical information of the patients (M component levels, CRP, ISS-stage, CRAB symptoms, MDE status, survival, treatment, treatment response, relapse, age, gender and ASCT status) together with rule-based machine learning (RBML) we aim to identify proteins that could serve as biomarkers for early disease detection, aggressiveness, treatment selection, response and relapse and potentially as new therapeutic targets.
If you are a driven and highly motivated medical student with an interest in proteomics and cancer biology, please don’t hesitate to contact us.
Contact details
Patrick Nylund, PhD: patrick.nylund@igp.uu.se
Stefania Iliana Tziola, PhD student: stefania.tziola@igp.uu.se