Data from Cetuximab Responses in Patients with HNSCC Correlate to Clonal Expansion Feature of Peripheral and Tumor-Infiltrating T Cells with Top T-Cell Receptor Clonotypes

Abstract

<div>AbstractPurpose:<p>Cetuximab is a standard-of-care treatment for head and neck squamous cell carcinoma (HNSCC). Well-defined correlative markers of therapeutic responses are still lacking. Characterizing dynamic changes of T-cell receptor (TCR) repertoire in peripheral blood and tumor tissue may facilitate developing markers for cetuximab response in HNSCCs.</p>Experimental Design:<p>We analyzed high-throughput TCRβ sequencing data generated with ImmunoSEQ platform using peripheral blood mononuclear cells (PBMC) and tumor-infiltrating lymphocytes (TIL) from patients with HNSCC before and after cetuximab treatment (pre-/post-PBMC vs. pre-/post-TIL). Multiple analytic approaches were employed to normalize sequencing data.</p>Results:<p>Normalized TCR richness was significantly lower in post-TIL than pre-TIL, suggesting that cetuximab reduced TCR diversity and promoted TCR expansion in TIL samples, regardless of response status. The magnitude of clonal expansion (defined as expansion rate) in top 20 TCR clonotypes was significantly higher in responder PBMC with or without normalization, and in responder TIL upon normalization, than nonresponder ones. Notably, the expanded top 20 or top 50 TCR clonotypes overlapped between PBMC and TIL samples, which occurred significantly more frequently in responders than nonresponders.</p>Conclusions:<p>Patients with cetuximab-treated HNSCC harbor dynamic changes of TCR repertoires correlative to therapeutic responses. The expansion rate of top TCR clonotypes in peripheral blood may serve as a minimally invasive, readily accessible, and feasible marker for predicting cetuximab responses in HNSCCs and beyond, and the expansion rate of top TCR clonotypes in TILs and their overlapping probability between PBMC and TIL may serve as additional predictive markers. Our study also highlights the importance of data normalization for TCR repertoire analysis.</p></div>