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Article Abstract

Cisplatin-based chemotherapy is the recommended therapy for muscle-invasive bladder cancer (MIBC). However, the efficacy of MIBC for chemotherapy is only about 40%. Therefore, predictors of therapy response are urgently needed. Neutrophils form neutrophil extracellular traps (NETs), a network structure, and growing evidence indicated that it could be a prognostic and predictive marker in cancer. In MIBC, the predictive role of NETs in chemotherapy resistance is unclear. We used the Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression analyses to develop a NETs-associated signature score (NETs-score) for therapeutic response prediction in the discovery cohort (GSE169455). Then the NETs score-based risk stratification was verified in two validation cohorts (Taber et al.'s cohort, our institutional cohort). In the training cohort, high NETs-score was associated with poor chemotherapy response (AUC = 0.781) and reduced recurrence-free survival (RFS) (hazard ratio [HR] = 2.07, 95% confidence interval [CI]: [1.26-3.40], p = 0.003) in MIBC patients. The NETs-score was also demonstrated to be a predictive factor for the efficacy of neoadjuvant chemotherapy in the validation cohort (AUC = 0.731). The accuracy of the NETs-score was superior to other chemotherapy response predictors such as Ba/Sq expression subtype (AUC = 0.711), BRCA2 mutation (AUC = 0.692) and ERCC2 mutation (AUC = 0.548). Furthermore, in our center cohort, the expression level of H3Cit showed a significant difference between the response and no-response group (p = 0.01). Through immunohistochemical validation, NETs was an independent predictor of MIBC neoadjuvant chemotherapy efficacy as determined by the multivariate logistic regression analysis (OR = 5.94, 95% CI: 1.20-45.50, p = 0.045). Patients with high levels of NETs predicted poor response to neoadjuvant chemotherapy. This study was the first to reveal the correlation between the level of NETs in MIBC and the efficacy of chemotherapy, which may provide a theoretical basis regarding NETs inhibitors.

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http://dx.doi.org/10.1002/mc.23844DOI Listing

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