Nature Communications (Feb 2024)

Tumor histoculture captures the dynamic interactions between tumor and immune components in response to anti-PD1 in head and neck cancer

  • Nandini Pal Basak,
  • Kowshik Jaganathan,
  • Biswajit Das,
  • Oliyarasi Muthusamy,
  • Rajashekar M,
  • Ritu Malhotra,
  • Amit Samal,
  • Moumita Nath,
  • Ganesh MS,
  • Amritha Prabha Shankar,
  • Prakash BV,
  • Vijay Pillai,
  • Manjula BV,
  • Jayaprakash C,
  • Vasanth K,
  • Gowri Shankar K,
  • Sindhu Govindan,
  • Syamkumar V,
  • Juby,
  • Koushika R,
  • Chandan Bhowal,
  • Upendra Kumar,
  • Govindaraj K,
  • Mohit Malhotra,
  • Satish Sankaran

DOI
https://doi.org/10.1038/s41467-024-45723-z
Journal volume & issue
Vol. 15, no. 1
pp. 1 – 15

Abstract

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Abstract Dynamic interactions within the tumor micro-environment drive patient response to immune checkpoint inhibitors. Existing preclinical models lack true representation of this complexity. Using a Head and Neck cancer patient derived TruTumor histoculture platform, the response spectrum of 70 patients to anti-PD1 treatment is investigated in this study. With a subset of 55 patient samples, multiple assays to characterize T-cell reinvigoration and tumor cytotoxicity are performed. Based on levels of these two response parameters, patients are stratified into five sub-cohorts, with the best responder and non-responder sub-cohorts falling at extreme ends of the spectrum. The responder sub-cohort exhibits high T-cell reinvigoration, high tumor cytotoxicity with T-cells homing into the tumor upon treatment whereas immune suppression and tumor progression pathways are pre-dominant in the non-responders. Some moderate responders benefit from combination of anti-CTLA4 with anti-PD1, which is evident from better cytotoxic T-cell: T-regulatory cell ratio and enhancement of tumor cytotoxicity. Baseline and on-treatment gene expression signatures from this study stratify responders and non-responders in unrelated clinical datasets.