Research at IGP
Research at the department aims to increase biological understanding of development and disease, and improve diagnostics and treatment. The overarching goal is translational medicine, i.e. to link basic research with clinical applications, in disease areas such as cancer, autoimmunity, degenerative and genetic diseases.
The Department’s research groups are divided into nine research programmes which you can find via the menu on the left-hand side.
Read more about our research.
The research is also presented in the department's information brochure.
New research findings
- Changes in cellular degradation hubs can lead to cancer
- Careless cancer cells may be susceptible to future drugs
- Smart algorithm finds possible future treatment for childhood cancer
- Drug against epilepsy inhibits tumour development in the brain
- New combination of drugs effective against aggressive brain tumour
New publications from IGP
Sclafani, Francesco; Wilson, Sanna Hulkki; Cunningham, David; De Castro, David Gonzalez; Kalaitzaki, Eleftheria; Begum, Ruwaida; Wotherspoon, Andrew; Capdevila, Jaume; Glimelius, Bengt; Rosello, Susana; Thomas, Janet; Tait, Daina; Brown, Gina; Oates, Jacqui; Chau, Ian
Analysis of KRAS, NRAS, BRAF, PIK3CA and TP53 mutations in a large prospective series of locally advanced rectal cancer patients
Ghaderi Berntsson, Shala; Kristoffersson, Anna; Daniilidou, Makrina; Dahl, Niklas; Ekström, Curt
Aniridia with PAX6 mutations and narcolepsy
Strom, Peter; Kartasalo, Kimmo; Olsson, Henrik; Solorzano, Leslie; Delahunt, Brett; Berney, Daniel M.; Bostwick, David G.; Evans, Andrew J.; Grignon, David J.; Humphrey, Peter A.; Iczkowski, Kenneth A.; Kench, James G.; Kristiansen, Glen; van der Kwast, Theodorus H.; Leite, Katia R. M.; McKenney, Jesse K.; Oxley, Jon; Pan, Chin-Chen; Samaratunga, Hemamali; Srigley, John R.; Takahashi, Hiroyuki; Tsuzuki, Toyonori; Varma, Murali; Zhou, Ming; Lindberg, Johan; Lindskog, Cecilia; Ruusuvuori, Pekka; Wählby, Carolina; Gronberg, Henrik; Rantalainen, Mattias; Egevad, Lars; Eklund, Martin
Artificial intelligence for diagnosis and grading of prostate cancer in biopsies: a population-based, diagnostic study