Genomic and protein expression analysis reveals flap structure-specific endonuclease(FEN1) as a key prognostic, predictive and therapeutic target in breast and ovarian cancer


Session type:

Vivek Mohan1,4, Tarek MA Abdel-Fatah1, Roslin Russell2,3, Nada Albarakati4, David J Maloney5, Dorjbal Dorjsuren5, Oscar M Rueda2,3, Paul Moseley1, Hongmao Sun5, Abhik Mukherjee6, Devika Ravindra Agarwal7, Jennifer L Illuzzi8, Ajit Jadhav5, Anton Simeonov5, Graham Ball7, Stephen Chan1, Carlos Caldas2,3, Ian O Ellis6, David M Wilson III8, Srinivasan Madhusudan1,4
1Nottingham University Hospitals, Nottingham, UK, 2University of Cambridge, Cambridge, UK, 3Cancer Research UK Cambridge Research Institute, Cambridge, UK, 4University of Nottingham, Nottingham, UK, 5National Institutes of Health, Rockville, USA, 6School of Molecular Medical Sciences, University of Nottingham, Nottingham University Hospitals, Nottingham, UK, 7Nottingham Trent University, Nottingham, UK, 8National Institute on Aging, National Institutes of Health, Baltimore, USA


FEN1 has key roles in Okazaki fragment maturation during replication, long patch base excision repair, rescue of stalled replication forks, maintenance of telomere stability and apoptosis. We hypothesised that FEN1 may be dysregulated and have clinicopathological and therapeutic significance in breast and ovarian cancer.


A whole-genome data-mining approach was undertaken to investigate FEN1 in multiple cohorts of breast cancer [training set (128), test set (249), external validation (1952)]. Artificial neural network analysis, ensemble classification and cross validation analysis of 47,293 probes was performed in 249 breast tumours. FEN1 protein expression was evaluated in 568 oestrogen receptor (ER) negative breast cancers, 894 ER positive breast cancers and 156 ovarian cancers. FEN1 knockdown or blockade by a small molecule inhibitor was investigated for enhancement of chemotherapy sensitivity. A chemical library of 391,275 compounds was screened to identify FEN1 inhibitors.


FEN1 mRNA over expression was significantly associated with high grade, high mitotic index, pleomorphism, triple negative & basal-like phenotype, resistance to endocrine & chemotherapy, and poor survival (ps<0.0001). Artificial neural network analysis revealed novel FEN1 interaction genes involved in DNA repair, replication and cell cycle regulation. FEN1 protein over expression is significantly linked to aggressive phenotype, therapy resistance, and poor survival in oestrogen receptor (ER) negative breast cancers, ER positive breast cancers and ovarian epithelial cancers. In cancer cell lines, FEN1 depletion or inhibition by a small molecule results in sensitivity to DNA damaging chemotherapy. High throughput screening has identified novel FEN1 inhibitors for therapeutic evaluation.


We conclude that FEN1 is a key biomarker as well as an attractive drug target in breast and ovarian cancer.