Post-neoadjuvant cellular dissociation grading based on tumour budding and cell nest size is associated with therapy response and survival in oesophageal squamous cell carcinoma

Br J Cancer. 2019 Dec;121(12):1050-1057. doi: 10.1038/s41416-019-0623-2. Epub 2019 Nov 6.

Abstract

Background: Cellular Dissociation Grade (CDG) composed of tumour budding and cell nest size has been shown to independently predict prognosis in pre-therapeutic biopsies and primary resections of oesophageal squamous cell carcinoma (ESCC). Here, we aimed to evaluate the prognostic impact of CDG in ESCC after neoadjuvant therapy.

Methods: We evaluated cell nest size and tumour budding activity in 122 post-neoadjuvant ESCC resections, correlated the results with tumour regression groups and patient survival and compared the results with data from primary resected cases as well as pre-therapeutic biopsies.

Results: CDG remained stable when results from pre-therapeutic biopsies and post-therapeutic resections from the same patient were compared. CDG was associated with therapy response and a strong predictor of overall, disease-specific (DSS) and disease-free (DFS) survival in univariate analysis and-besides metastasis-remained the only significant survival predictor for DSS and DFS in multivariate analysis. Multivariate DFS hazard ratios reached 3.3 for CDG-G2 and 4.9 for CDG-G3 neoplasms compared with CDG-G1 carcinomas (p = 0.016).

Conclusions: CDG is the only morphology-based grading algorithm published to date, which in concert with regression grading, is able to contribute relevant prognostic information in the post-neoadjuvant setting of ESCC.

MeSH terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Biopsy
  • Cell Size*
  • Disease-Free Survival
  • Esophageal Squamous Cell Carcinoma / drug therapy*
  • Esophageal Squamous Cell Carcinoma / epidemiology
  • Esophageal Squamous Cell Carcinoma / pathology*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Neoadjuvant Therapy / methods
  • Neoplasm Grading
  • Neoplasm Metastasis
  • Prognosis*
  • Proportional Hazards Models