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Expression of B7-H3 and TIM-3 in gastric-type endocervical adenocarcinoma: prevalence, association with PD-L1 expression, and prognostic significance.

Yao SunXin ZhouElena LucasLili ChenHuijuan ZhangHao ChenFeng Zhou
Published in: The journal of pathology. Clinical research (2023)
Gastric-type endocervical adenocarcinoma (GEA) is the second most common subtype of endocervical adenocarcinoma and has a poor prognosis. Anti-programmed death-1 and anti-programmed death-ligand 1 (PD-L1) inhibitors have emerged as a major treatment option for GEA; however, data on the expression of other immune checkpoints in GEA are limited. We analyzed the expression of T-cell immunoglobulin and mucin-domain containing-3 (TIM-3) and B7 homolog 3 protein (B7-H3) in 58 GEA and investigated their prognostic significance as well as association with PD-L1 expression and other known prognostic factors. Applying the tumor proportion score (TPS) with a cutoff of 1%, B7-H3 and TIM-3 were present in 48.3% and 17.2% of cases, respectively. Applying the combined positive score (CPS) with a cutoff of 1, TIM-3 expression was present in 70.7% of cases. Moreover, the expression of three checkpoints (B7-H3, TIM-3, and PD-L1) was incompletely overlapping. Patients with B7-H3 positive tumors (by TPS) or TIM-3 positive tumors (by TPS) had significantly worse recurrence-free survival (RFS) and overall survival (OS) (log-rank). Using CPS, patients with TIM-3 positive tumors showed significantly worse RFS (log-rank). Similarly, B7-H3 positivity (by TPS) and TIM-3 positivity (by TPS) were associated with worse RFS and OS in univariate analysis. TIM-3 positivity (by CPS) was associated with worse RFS in univariate analysis and the final Cox multivariate analysis. In conclusion, our results show that (1) B7-H3 and TIM-3 are frequently expressed in GEA and their expression overlaps incompletely with PD-L1; and (2) both B7-H3 and TIM-3 are independent negative prognostic markers in GEA.
Keyphrases
  • poor prognosis
  • long non coding rna
  • free survival
  • squamous cell carcinoma
  • prognostic factors
  • binding protein
  • risk factors
  • small molecule
  • electronic health record
  • deep learning
  • mass spectrometry
  • big data
  • high speed