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Genomics based Precision and Personalized Medicine Research Group

​Genomics based Precision and Personalized Medicine Research Group focuses on the advancement of precision and personalized care through high throughput and state-of-the art diagnostic techniques. The group specializes in sequencing technologies and cell-based assays to improve diagnostics for targeted treatment. 

​Our research aim is to advance therapeutic diagnostics through an understanding of basic biology while incorporating genomic medicine. Our overall goal is to increase the number of patients that can benefit from targeted treatment. 

  • Breast Cancer genes database – Aims to augment the comprehensive nature of our newly published curated breast cancer genes (cbcg.dk) database. This will expedite clinical diagnostics and support the ongoing efforts in managing breast cancer etiology.

  • New Breast Cancer genes– Aims to identify novel breast cancer genes among young breast cancer patients, thereby improving future diagnostics and treatment for these vulnerable cancer patients. The projects utilize both germline and somatic high throughput sequencing data along with a broad range of functional assays. 

  • Classification of Variant of Uncertain Significance (VUS) – Aims to identify the pathogenicity of VUS, thereby broadening the potential of personalized medicine. VUS's represent a major challenge for clinicians and patients world-wide. Specifically, clinical management of cancer patients and genetic counseling of their family members are a major area of concern. Thus, there is an increasing need to establish an accurate VUS characterization platform that can facilitate to re-classify the VUS as either benign or pathogenic. We established a CRISPR based VUS testing platform to support patient diagnostics. 

  • Homologous Recombination Deficiency (HRD) testing & PARPi sensitivity – Aims to optimize and benchmark our own Laboratory Developmental Test (LDT) to estimate HRD. This will enable the access of PARPi for a greater number of HRD patients across different cancer types. 

  • Predictive value of molecular subtypes – Aims to identify the predictive and prognostic value of different breast cancer molecular subtypes, thereby enabling expedited precision medicine.

  • Transcriptomic analysis from single cell sequencing – Aims to refine molecular taxonomies of heterogenous cancers using single cell technologies.​

Funding

  • ​Novo Nordisk Fonden
  • Neye-fonden
  • AstraZeneca
  • Kræftens Bekæmpelse

Researchers

​Senior Researchers

  • Luca Mariani
  • Muthiah Bose
  • Tiziana Lischetti

Postdoctoral researchers

  • Manika Indrajit Singh 
  • Jayashree Vijay Thatte​

PhD students

  • Maj Kamille Kjeldsen (Department of Oncology, Rigshospitalet)
  • Tobias Berg (Department of Oncology, Rigshospitalet)
  • Aleksandar Martinov Kostov (Department of Pathology, Region Zealand) 
  • Joanna Vitfell-Rasmussen (Department of Oncology, Herlev Hospital)

Research technicians

  • Olivia Rose Williams
  • Sofie Eriksen

Research assistant

  • (None)

Master students

  • Emilie Mia Stets​

Key Collaborators

  • Claus Storgaard Sørensen, Biotech Research & Innovation Centre, KU
  • Bent Ejlertsen ( Department of Oncology, DBCG, Rigshospitalet)​



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