PLoS ONE (Jan 2020)

Density of CD3+ and CD8+ cells in gingivo-buccal oral squamous cell carcinoma is associated with lymph node metastases and survival.

  • Geetashree Mukherjee,
  • Swarnendu Bag,
  • Prasenjit Chakraborty,
  • Debdeep Dey,
  • Samrat Roy,
  • Prateek Jain,
  • Paromita Roy,
  • Richie Soong,
  • Partha Pratim Majumder,
  • Suparna Dutt

DOI
https://doi.org/10.1371/journal.pone.0242058
Journal volume & issue
Vol. 15, no. 11
p. e0242058

Abstract

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The tumor immune microenvironment is emerging as a critical player in predicting cancer prognosis and response to therapies. However, the prognostic value of tumor-infiltrating immune cells in Gingivo-Buccal Oral Squamous Cell Carcinoma (GBOSCC) and their association with tumor size or lymph node metastases status require further elucidation. To study the relationship of tumor-infiltrating immune cells with tumor size (T stage) and lymph node metastases (N stages), we analyzed the density of tumor-infiltrating immune cells in archived, whole tumor resections from 94 patients. We characterized these sections by immune-histochemistry using 12 markers and enumerated tumor-infiltrating immune cells at the invasive margins (IM) and centers of tumors (CT). We observed that a higher density of CD3+ cells in the IM and CT was associated with smaller tumor size (T1-T2 stage). Fewer CD3+ cells was associated with larger tumor size (T3-T4 stage). High infiltration of CD3+and CD8+ cells in IM and CT as well as high CD4+ cell infiltrates in the IM was significantly associated with the absence of lymph node metastases. High infiltrates of CD3+ and CD8+ cells in CT was associated with significantly improved survival. Our results illustrate that the densities and spatial distribution of CD3+ and CD8+ cell infiltrates in primary GBOSCC tumors is predictive of disease progression and survival. Based on our findings, we recommend incorporating immune cell quantification in the TNM classification and routine histopathology reporting of GBOSCC. Immune cell quantification in CT and IM may help predict the efficacy of future therapies.