Comprehensive Proteomics Analysis and Minimal Residual Disease (MRD) Detection in Mantle Cell Lymphoma (MCL) for Treatment Decision-Making and Early Relapse Detection

Project Aims:

1. Conduct large-scale proteomics analysis to comprehensively characterize the protein expression landscape in Mantle Cell Lymphoma (MCL) samples.
2. Identify key protein biomarkers associated with MCL progression, treatment response, and resistance.
3. Develop and implement sensitive and specific assays for the detection of Minimal Residual Disease (MRD) in MCL patients during and after treatment.
4. Establish MRD thresholds for accurate prediction of relapse and disease progression.

Background:

Mantle Cell Lymphoma (MCL) is a challenging hematologic malignancy characterized by the aberrant proliferation of B lymphocytes. Despite advancements in treatment modalities, achieving a complete response in MCL remains a complex task and many patients relapse due to drug resistance. Large-scale proteomics studies, offers a comprehensive view of the molecular landscape of MCL. Additionally, detecting Minimal Residual Disease (MRD) is crucial for assessing treatment response and predicting relapse. The integration of proteomics and MRD detection aims to provide a holistic understanding of the disease, facilitating clinical decision making on treatment options and early detection of relapse. This project builds upon previous genomic studies in MCL, extending the analysis to the proteomic level to capture dynamic changes in protein expression associated with disease progression and treatment response.

Project plan:

Embark on a ground-breaking journey at the intersection of cutting-edge proteomics and clinical precision medicine. As a key participant in this project, you'll delve into the dynamic world of MCL, where we are not just deciphering protein expressions but shaping the future of personalized treatment decisions. With a strong emphasis on translating scientific insights into clinical applications and with a robust connection to clinical characteristics, this endeavour holds the promise of changing how we approach, understand, and treat this disease.

We will analyse proteomic data to identify candidate biomarkers associated with MCL progression and treatment response. Utilize sensitive and specific assays for MRD detection. Furthermore, we will integrate proteomic and MRD data to identify correlations between protein expression patterns and MRD status. Correlate findings with clinical outcomes and treatment responses to define predictive biomarkers. Develop a treatment decision-making algorithm based on proteomic profiles, MRD status, and clinical parameters. We will also evaluate and implement a monitoring system for real-time MRD assessments and proteomic changes during and after treatment. Establish criteria for early relapse detection and that can determine treatment adjustments. Validate the developed protocols and algorithms through in prospective clinical trials.

What are we looking for?

We currently accept applications from up to 2 students that are interested in joining our projects. If you have an interest in clinical applications, computational proteomics analysis, tumour biology and precision medicine we encourage you to contact us.

Contact Details

Patrick Nylund, PhD
Unit of precision medicine / IGP
Email: Patrick.nylund@igp.uu.se

Professor Ingrid Glimelius
Unit of precision medicine / IGP
Email: Ingrid.glimelius@igp.uu.se