Immune Cell Densities Predict Response to Immune Checkpoint-Blockade in Head and Neck Cancer.

Autor:	Ruiz-Torres DA; Department of Otolaryngology-Head and Neck Surgery, Harvard Medical School, Boston, MA 02115, USA.; Massachusetts Eye and Ear, Boston, MA 02118, USA.; Massachusetts General Hospital Cancer Center, Boston, MA 02118, USA., Bryan ME; Department of Otolaryngology-Head and Neck Surgery, Harvard Medical School, Boston, MA 02115, USA.; Massachusetts Eye and Ear, Boston, MA 02118, USA., Hirayama S; Department of Otolaryngology-Head and Neck Surgery, Harvard Medical School, Boston, MA 02115, USA.; Massachusetts Eye and Ear, Boston, MA 02118, USA., Merkin RD; Massachusetts Eye and Ear, Boston, MA 02118, USA.; Massachusetts General Hospital Cancer Center, Boston, MA 02118, USA.; Harvard Medical School, 25 Shattuck St, Boston, MA 02115., Luciani E; Massachusetts General Hospital Cancer Center, Boston, MA 02118, USA., Roberts T; Massachusetts General Hospital Cancer Center, Boston, MA 02118, USA.; Harvard Medical School, 25 Shattuck St, Boston, MA 02115., Patel M; Massachusetts General Hospital Cancer Center, Boston, MA 02118, USA.; Harvard Medical School, 25 Shattuck St, Boston, MA 02115., Park JC; Massachusetts General Hospital Cancer Center, Boston, MA 02118, USA.; Harvard Medical School, 25 Shattuck St, Boston, MA 02115., Wirth LJ; Massachusetts General Hospital Cancer Center, Boston, MA 02118, USA.; Harvard Medical School, 25 Shattuck St, Boston, MA 02115., Sadow PM; Massachusetts Eye and Ear, Boston, MA 02118, USA.; Massachusetts General Hospital Cancer Center, Boston, MA 02118, USA.; Harvard Medical School, 25 Shattuck St, Boston, MA 02115.; Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, USA., Sade-Feldman M; Massachusetts General Hospital Cancer Center, Boston, MA 02118, USA.; Harvard Medical School, 25 Shattuck St, Boston, MA 02115.; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA., Stott SL; Massachusetts General Hospital Cancer Center, Boston, MA 02118, USA.; Harvard Medical School, 25 Shattuck St, Boston, MA 02115.; Center for Engineering in Medicine and BioMEMS Resource Center, Surgical Services, Massachusetts General Hospital, Harvard Medical School, 114 16th Street, Charlestown, MA 02129, USA.; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA., Faden DL; Department of Otolaryngology-Head and Neck Surgery, Harvard Medical School, Boston, MA 02115, USA.; Massachusetts Eye and Ear, Boston, MA 02118, USA.; Harvard Medical School, 25 Shattuck St, Boston, MA 02115.; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA.
Jazyk:	angličtina
Zdroj:	MedRxiv : the preprint server for health sciences [medRxiv] 2024 Sep 12. Date of Electronic Publication: 2024 Sep 12.
DOI:	10.1101/2024.09.10.24313432
Abstrakt:	Immune checkpoint blockade (ICB) is the standard of care for recurrent/metastatic head and neck squamous cell carcinoma (HNSCC), yet efficacy remains low. The current approach for predicting the likelihood of response to ICB is a single proportional biomarker (PD-L1) expressed in immune and tumor cells (Combined Positive Score, CPS) without differentiation by cell type, potentially explaining its limited predictive value. Tertiary Lymphoid Structures (TLS) have shown a stronger association with ICB response than PD-L1. However, their exact composition, size, and spatial biology in HNSCC remain understudied. A detailed understanding of TLS is required for future use as a clinically applicable predictive biomarker. Methods: Pre-ICB tumor tissue sections were obtained from 9 responders (complete response, partial response, or stable disease) and 11 non-responders (progressive disease) classified via RECISTv1.1. A custom multi-immunofluorescence (mIF) staining assay was designed, optimized, and applied to characterize tumor cells (pan-cytokeratin), T cells (CD4, CD8), B cells (CD19, CD20), myeloid cells (CD16, CD56, CD163), dendritic cells (LAMP3), fibroblasts (α Smooth Muscle Actin), proliferative status (Ki67) and immunoregulatory molecules (PD1). Spatial metrics were compared among groups. Serial tissue sections were scored for TLS in both H&E and mIF slides. A machine learning model was employed to measure the effect of these metrics on achieving a response to ICB (SD, PR, or CR). Results: A higher density of B lymphocytes (CD20+) was found in responders compared to non-responders to ICB (p=0.022). A positive correlation was observed between mIF and pathologist identification of TLS ( R 2 = 0.66, p-value= <0.0001 ). TLS trended toward being more prevalent in responders to ICB (p=0.0906). The presence of TLS within 100 μm of the tumor was associated with improved overall (p=0.04) and progression-free survival (p=0.03). A multivariate machine learning model identified TLS density as a leading predictor of response to ICB with 80% accuracy. Conclusion: Immune cell densities and TLS spatial location within the tumor microenvironment play a critical role in the immune response to HNSCC and may potentially outperform CPS as a predictor of ICB response. Competing Interests: Declaration of conflict of interest (COI): The authors have no COI related to this work to declare.
Databáze:	MEDLINE
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