title: E2F4 Program Is Predictive of Progression and Intravesical Immunotherapy Efficacy in Bladder Cancer.
abstract: Bladder cancer is a common malignant disease, with non-muscle-invasive bladder cancer (NMIBC) representing the majority of tumors. This cancer subtype is typically treated by transurethral resection. In spite of treatment, up to 70% of patients show local recurrences. Intravesical BCG (Bacillus Calmette-Guerin) immunotherapy has been widely used to treat NMIBC, but it fails to suppress recurrence of bladder tumors in up to 40% of patients. Therefore, the development of prognostic markers is needed to predict the progression of bladder cancer and the efficacy of intravesical BCG treatment. This study demonstrates the effectiveness of an E2F4 signature for prognostic prediction of bladder cancer. E2F4 scores for each sample in a bladder cancer expression dataset were calculated by summarizing the relative expression levels of E2F4 target genes identified by ChIP-seq, and then the scores were used to stratify patients into good- and poor-outcome groups. The molecular signature was investigated in a single bladder cancer dataset and then its effectiveness was confirmed in two meta-bladder datasets consisting of specimens from multiple independent studies. These results were consistent in different datasets and demonstrate that the E2F4 score is predictive of clinical outcomes in bladder cancer, with patients whose tumors exhibit an E2F4 score >0 having significantly shorter survival times than those with an E2F4 score <0, in both non-muscle-invasive, and muscle-invasive bladder cancer. Furthermore, although intravesical BCG immunotherapy can significantly improve the clinical outcome of NMIBC patients with positive E2F4 scores (E2F4>0 group), it does not show significant treatment effect for those with negative scores (E2F4<0 group).
  
  
  CONCLUSIONS
  The E2F4 signature can be applied to predict the progression/recurrence and the responsiveness of patients to intravesical BCG immunotherapy in bladder cancer.
authors.affiliation: Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire. Institute for Quantitative Biomedical Sciences, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire. Norris Cotton Cancer Center, Geisel School of Medicine at Dartmouth, Lebanon, New Hampshire. Chao.Cheng@dartmouth.edu.
authors.forename: Chao
authors.initials: C
authors.lastname: Cheng
authors.affiliation: Department of Genetics, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire.
authors.forename: Frederick S
authors.initials: FS
authors.lastname: Varn
authors.affiliation: Department of Pharmacology and Toxicology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire.
authors.forename: Carmen J
authors.initials: CJ
authors.lastname: Marsit
mesh_terms: D045744:Cell Line, Tumor; D018450:Disease Progression; D018572:Disease-Free Survival; D050704:E2F4 Transcription Factor / Q000235:genetics* / Q000378:metabolism*; D005260:Female; D006801:Humans; D007167:Immunotherapy; D008297:Male; D009163:Mycobacterium bovis / Q000276:immunology* / Q000378:metabolism; D016896:Treatment Outcome; D001749:Urinary Bladder Neoplasms / Q000235:genetics / Q000276:immunology / Q000473:pathology / Q000628:therapy*
chemical_list: D050704:E2F4 Transcription Factor; C493762:E2F4 protein, human