Related Experiment Video
Updated: May 27, 2025
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
Spatial characterization of tertiary lymphoid structures as predictive biomarkers for immune checkpoint blockade in
Daniel A Ruiz-Torres1,2,3,4, Michael E Bryan1,4, Shun Hirayama1
1Department of Otolaryngology-Head and Neck Surgery, Massachusetts Eye and Ear, Boston, MA, USA.
Abstract:
Immune checkpoint blockade (ICB) is the standard of care for recurrent/metastatic head and neck squamous cell carcinoma (HNSCC), yet efficacy remains low. The combined positive score (CPS) for PD-L1 is the only biomarker approved to predict response to ICB and has limited performance. Tertiary Lymphoid Structures (TLS) have shown promising potential for predicting response to ICB. However, their exact composition, size, and spatial biology in HNSCC remain understudied. To elucidate the impact of TLS spatial biology in response to ICB, we utilized pre-ICB tumor tissue sections 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 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). A machine learning model was employed to measure the effect of spatial metrics on achieving a response to ICB. A higher density of B cells (CD20+) was found in responders compared to non-responders to ICB (p = 0.022). 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. Immune cell densities and TLS spatial location play a critical role in the response to ICB in HNSCC and may potentially outperform CPS as a predictor of response.
Insights
Tertiary Lymphoid Structures (TLS) density and B cell presence in head and neck squamous cell carcinoma (HNSCC) predict response to immune checkpoint blockade (ICB). This spatial biology approach may outperform PD-L1 combined positive score (CPS) for predicting ICB efficacy.
Area of Science:
- Immunology
- Oncology
- Pathology
Background:
- Immune checkpoint blockade (ICB) is a standard treatment for recurrent/metastatic head and neck squamous cell carcinoma (HNSCC), but its efficacy is limited.
- The PD-L1 combined positive score (CPS) is the sole approved biomarker for predicting ICB response, yet it exhibits suboptimal performance.
- Tertiary Lymphoid Structures (TLS) show promise for predicting ICB response, but their spatial biology in HNSCC requires further investigation.
Purpose of the Study:
- To investigate the impact of Tertiary Lymphoid Structures (TLS) spatial biology on response to immune checkpoint blockade (ICB) in head and neck squamous cell carcinoma (HNSCC).
- To identify potential biomarkers that can more accurately predict ICB response in HNSCC patients.
Main Methods:
- Utilized pre-ICB tumor tissue sections from 9 responders and 11 non-responders with HNSCC.
- Applied a custom multi-immunofluorescence (mIF) staining assay to characterize immune cells, tumor cells, fibroblasts, and immunoregulatory molecules.
- Employed a machine learning model to analyze spatial metrics and predict ICB response.
Main Results:
- Responders exhibited a higher density of B cells (CD20+) compared to non-responders (p=0.022).
- The presence of TLS within 100 µm of the tumor correlated with improved overall survival (p=0.04) and progression-free survival (p=0.03).
- A multivariate machine learning model identified TLS density as a leading predictor of ICB response, achieving 80% accuracy.
Conclusions:
- Immune cell densities and TLS spatial location are critical factors influencing ICB response in HNSCC.
- TLS density shows potential to outperform the PD-L1 CPS as a predictive biomarker for ICB in HNSCC.
- Further research into TLS spatial biology could lead to improved patient stratification and treatment strategies for HNSCC.
