Frontiers in Oncology (Aug 2023)

Predictive signature of response to neoadjuvant chemotherapy in muscle-invasive bladder cancer integrating mRNA expression, taxonomic subtypes, and clinicopathological features

  • Albert Font,
  • Albert Font,
  • Montserrat Domenech,
  • Jose Luis Ramirez,
  • Miriam Marqués,
  • Raquel Benítez,
  • Vicenç Ruiz de Porras,
  • Vicenç Ruiz de Porras,
  • José L. Gago,
  • Cristina Carrato,
  • Francesc Sant,
  • Hector Lopez,
  • Daniel Castellano,
  • Nuria Malats,
  • M. Luz Calle,
  • Francisco X. Real,
  • Francisco X. Real,
  • Francisco X. Real

DOI
https://doi.org/10.3389/fonc.2023.1155244
Journal volume & issue
Vol. 13

Abstract

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Background and objectiveNeoadjuvant chemotherapy (NAC) followed by cystectomy is the standard of care in muscle-invasive bladder cancer (MIBC). Pathological response has been associated with longer survival, but no currently available clinicopathological variables can identify patients likely to respond, highlighting the need for predictive biomarkers. We sought to identify a predictive signature of response to NAC integrating clinical score, taxonomic subtype, and gene expression.Material and methodsFrom 1994 to 2014, pre-treatment tumor samples were collected from MIBC patients (stage T2-4N0/+M0) at two Spanish hospitals. A clinical score was determined based on stage, hydronephrosis and histology. Taxonomic subtypes (BASQ, luminal, and mixed) were identified by immunohistochemistry. A custom set of 41 genes involved in DNA damage repair and immune response was analyzed in 84 patients with the NanoString nCounter platform. Genes related to pathological response were identified by LASSO penalized logistic regression. NAC consisted of cisplatin/methotrexate/vinblastine until 2000, after which most patients received cisplatin/gemcitabine. The capacity of the integrated signature to predict pathological response was assessed with AUC. Overall survival (OS) and disease-specific survival (DSS) were analyzed with the Kaplan-Meier method.ResultsLASSO selected eight genes to be included in the signature (RAD51, IFNγ, CHEK1, CXCL9, c-MET, KRT14, HERC2, FOXA1). The highest predictive accuracy was observed with the inclusion in the model of only three genes (RAD51, IFNɣ, CHEK1). The integrated clinical-taxonomic-gene expression signature including these three genes had a higher predictive ability (AUC=0.71) than only clinical score plus taxonomic subtype (AUC=0.58) or clinical score alone (AUC=0.56). This integrated signature was also significantly associated with OS (p=0.02) and DSS (p=0.02).ConclusionsWe have identified a predictive signature for response to NAC in MIBC patients that integrates the expression of three genes with clinicopathological characteristics and taxonomic subtypes. Prospective studies to validate these results are ongoing.

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