Improved classification of Endometrial Cancer by integrated genomics

We have three ongoing projects on endometrial cancer.

Molecular classification of endometrial cancer

The current classification system of endometrial cancers is based on staging, grading and histological subtype. This is challenging due to unprecise risk estimation, over-/undertreatment, treatment inconsistency among medical centers and difficulties in comparisons of cohorts. In this project we are using data from exome sequencing and immunohistochemistry to improve classification of stage IB grade 3 endometrioid endometrial adenocarcinoma.

Project participants: Ane Gerda Zahl Eriksson, Pamela Soliman, Han Cun, Laurence Bernard, Kristina Lindemann, Ben Davidson, Karin Teien Lande

Promise-classification of endometrial cancers not possible to classify by traditional pathology

Occasionally, endometrial carcinomas are difficult to classify by conventional histopathology. In this project, we are using data from immunohistochemistry and exome sequencing to classify tumors according to the ProMisE classification system.

Project participants: Ane Gerda Zahl Eriksson, Ben Davidson, Daniel Nebdal, Karin Teien Lande

Circulating tumor DNA as prognostic factor in endometrial cancer

Analysis of cfDNA in liquid biopsies is a promising tool to identify endometrial cancer patients at high risk of relapse, to capture tumor heterogeneity and for monitoring treatment response. In this project, we are establishing a pipeline for the analysis of ctDNA and to assess the feasibility of utilizing ctDNA as prognostic marker in endometrial cancer. This includes targeted sequencing of cfDNA and exome sequencing of tumor DNA.

Project participants: Kristina Lindemann, Franziska Siegenthaler, Camilla Krakstad, Karin Teien Lande, Carlos Casas Arozamena