Nature Search

Patient-derived organoids reflect the genetic profile of endometrial tumors and predict patient prognosis

Berg et al. establish a panel of patient-derived endometrial cancer organoids and xenograft models. They show that their models recapitulate the genetic profile of the donor tumor and can be used for drug testing and development of a prognostic gene signature.

Hege F. Berg
Marta Espevold Hjelmeland
Camilla Krakstad
ResearchOpen Access30 Jul 2021
Communications Medicine

Volume: 1, P: 1-14
Mismatch repair markers in preoperative and operative endometrial cancer samples; expression concordance and prognostic value

Hege F. Berg
Hilde Engerud
Camilla Krakstad
ResearchOpen Access08 Dec 2022
British Journal of Cancer

Volume: 128, P: 647-655
Development of prediction models for lymph node metastasis in endometrioid endometrial carcinoma

Hege F. Berg
Zhenlin Ju
Henrica M. J. Werner
ResearchOpen Access10 Feb 2020
British Journal of Cancer

Volume: 122, P: 1014-1022
A national precision cancer medicine implementation initiative for Norway

Kjetil Taskén
Hege E. G. Russnes
Åslaug Helland
Correspondence05 May 2022
Nature Medicine

Volume: 28, P: 885-887
Radiomic profiles improve prognostication and reveal targets for therapy in cervical cancer

Mari Kyllesø Halle
Erlend Hodneland
Ingfrid S. Haldorsen
ResearchOpen Access17 May 2024
Scientific Reports

Volume: 14, P: 1-13
Loss of vimentin expression in preoperative biopsies independently predicts poor prognosis, lymph node metastasis and recurrence in endometrial cancer

Marta E. Hjelmeland
Hilde E. Lien
Camilla Krakstad
ResearchOpen Access18 Oct 2024
BJC Reports

Volume: 2, P: 1-9
Author Correction: Patient-derived organoids reflect the genetic profile of endometrial tumors and predict patient prognosis

Hege F. Berg
Marta Espevold Hjelmeland
Camilla Krakstad
Amendments and CorrectionsOpen Access10 Aug 2021
Communications Medicine

Volume: 1, P: 1
A radiogenomics application for prognostic profiling of endometrial cancer

Hoivik, Hodneland and colleagues employ convoluted neural networks alongside radiogenomic biomarkers to profile endometrial tumors. They identify an 11-gene high-risk signature validated with retrospective patient data.

Erling A. Hoivik
Erlend Hodneland
Camilla Krakstad
ResearchOpen Access06 Dec 2021
Communications Biology

Volume: 4, P: 1-12
Serum miR371 in testicular germ cell cancer before and after orchiectomy, assessed by digital-droplet PCR in a prospective study

Mette Pernille Myklebust
Anna Thor
Olav Dahl
ResearchOpen Access02 Aug 2021
Scientific Reports

Volume: 11, P: 1-12
HER2 expression patterns in paired primary and metastatic endometrial cancer lesions

Mari Kyllesø Halle
Ingvild Løberg Tangen
Camilla Krakstad
ResearchOpen Access23 Nov 2017
British Journal of Cancer

Volume: 118, P: 378-387

Search

Filter By:

Search

Quick links