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Patient Stratification though Proteomics

Patient stratification through affinity-based proteomics of liquid and tissue biopsies.

Patient stratification in relation to therapy in and outside clinical trials is a major challenge. Treatments are costly and associated with major side-effects. Increasing the precision in this selection of drugs is a fundamental question to solve within clinical oncology. The challenge lies in the heterogeneity of the individual tumor. Tissue-biopsies are often taken at a single site and at a single time-point and do not reflect the heterogeneity found both within the specific tumor mass, between metastatic sites and variations over time.

Project description: We aim at combining several state-of the art principles and technologies to achieve what previously has been impossible – i.e using a liquid biopsy of systemic released immune-regulatory and tumor secreted proteins, to establish a predictive biomarker signature that allow treatment selection. The four work-packages are briefly described below (1-3).

  1. Selection of antigens and development of novel bioinformatics concepts. Bioinformatic mining of previously generated data from the IMMRay platform (immunovia.com) will be used to guide antigen selection in combination with biological insight. The proposed project is further dependent on development of novel bioinformatics concept to combine data from multiple biomarkers.
  2. Capture of novel targets through antibody engineering. Antibody-engineering will be used to develop affinity reagents that can detect circulating proteins relevant for response to immune-regulatory drugs. Specifically, we will use large, in-house antibody fragment libraries and established technology to select specific binders using phage display technology focusing on development of high-affinity antibodies capable of detecting relevant molecules present in liquid biopsies.
  3. Technical development of affinity-based proteomics. Parallel antibody-based enrichment of low abundant proteins followed by exact quantification by mass spectrometry (MS) analysis will allow sensitive and exact detection. This approach is elegant in that the antibody enrichment provides unparalleled sensitivity, while the MS readout ensures an absolute specificity and allows for absolute quantification. Most importantly, this setup also allows for differential analysis of different proteoforms or post-translational modifications, as the antibody would capture all protein variants and the MS provides a specific readout of all. 

The project will be co-supervised by a number of experts to allow an initial and continuous integrated approach, all the way from selection of antigens based on biological knowledge and previous data from the IMMRay platform, selection of antibodies, evaluation and testing on clinical material and development of novel bioinformatics concepts All expertise is available locally in Lund, and is committed to the project.

Lavanya Lokhande. Photo.

Lavanya Lokhande

CanFaster PhD student

lavanya.lokhande@immun.lu.se

Sara Ek. Portrait.

Sara Ek

Professor

sara.ek@immun.lth.se
+46-46-222 4634

Department of Immunotechnology
Lund University
Medicon Village, Building 406
Scheelevägen 2
223 81 Lund

Page Manager: jana.hagman@immun.lth.se | 2023-10-03