Immune checkpoint expression, microsatellite instability, and mutational burden: Identifying immune biomarker phenotypes in uterine cancer


N.L. Jones, J. Xiu, T. Herzog, and I. S. Winer


Endometrioid endometrial cancer (EEC) is categorized on a histologic continuum from Grade 1 to 3 (G1 or low grade (LG), G2, G3 or high‐grade (HG)). Increasing grade is associated with aggressive behavior and poor prognosis. Treatment options for advanced/recurrent disease are limited. Emerging data has shown promise of immune checkpoint therapy (IT) in gynecologic malignancies 1. MSI‐H status, tumor mutation burden, and high PD‐L1 expression have been associated with higher response rates 2. Herein we identify distinct immune “biomarker phenotypes” to identify patients who may benefit from immune therapy (IT).


  • 621 endometrioid endometrial tumors were retrospectively analyzed for immune biomarker phenotype by multiplatform profiling: 156 grade 3, 172 grade 2, 113 grade 1, 180 unknown.
  • NextGen sequencing (NGS) was performed on 592 genes (Illumina NextSeq platform).
  • Mutational burden was calculated based on somatic nonsynonymous missense mutations; TMB‐high was defined as ≥17 mutations/megabase.
  • Microsatellite Instability (MSI) was determined by examining altered microsatellite loci using NGS ( ≥46 loci).
  • Antibody used for PD‐L1 was SP142 and positivity was defined as ≥2+, >5% staining on tumor cells.
  • Data were compared using chi‐square tests.


  • We evaluated TMB, MSI and PD‐L1 expression in over 600 EECs.
  • MSI and TMB are highly correlated in low grade,intermediate and high grade tumors while the correlation of PD‐L1 expression with MSI or TMB is not seen.
  • High grade tumors appear to be more immunogenic than low grade tumors, and may preferentially benefit from IT providing a potentially powerful treatment option. Conversely, LG tumors are less likely to benefit from IT

Download Publication