Abstract 1051P
Background
Tertiary Lymphoid Structures (TLS) are critical components of the tumor microenvironment and may influence the efficacy of immune checkpoint inhibitors (ICIs). High tumor mutational burden (TMB) and microsatellite instability-high (MSI-High) are now established biomarkers approved to guide treatment with ICIs such as pembrolizumab. This study explores the impact of TLS status on the outcomes of patients with these biomarker-positive profiles undergoing pembrolizumab treatment.
Methods
Retrospectively reviewed DNA (592-gene or whole exome) and RNA-seq (whole transcriptome) data from real-world patient tumor samples with high TMB (>10 mut/Mb) or MSI-High status (N=8792), representing >40 tumor types. PD-L1 expression was assessed by IHC (22c3, 28-8, SP142 tumor cell only, or SP142 immune cell only). TLS signature analysis included specific gene sets indicative of B cell infiltration/TLS presence (Messina et al., 2012; Goc et al., 2014; Cabrita et al., 2020; Meylan et al., 2022), with a specific focus on the highest quartile (Q4) of expression. Survival outcomes and duration of pembrolizumab treatment were compared across patients stratified by high (Q4) versus low (Q1-Q3) TLS gene signature scores.
Results
Patients with high TLS expression (Q4) demonstrated significantly improved survival outcomes and prolonged treatment duration compared to those with lower TLS levels (Q1, Q2, and Q3) across both TMB-high (HR 0.80, 0.85, and 0.92, respectively) and MSI-High groups (HR 0.81, 0.90, and 1.0, respectively), p<0,0001. Multivariate analysis, adjusting for gender, age, tumor type, and PD-L1 expression status confirmed the independent predictive value of high TLS status for better clinical outcomes in this patient cohort.
Conclusions
High TLS gene expression signatures, particularly in the highest quartile, are associated with favorable outcomes in patients with high TMB or MSI-High status treated with pembrolizumab. These findings suggest that TLS status could serve as a potent biomarker to stratify patients more likely to benefit from ICI therapy, advocating for its integration into routine clinical assessments prior to ICI treatment in these specific group of patients.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Caris.
Funding
Caris.
Disclosure
All authors have declared no conflicts of interest.
Resources from the same session
927P - Preliminary results of the BROADEN study: Burden of human papillomavirus-related head and neck cancers
Presenter: Laia Alemany
Session: Poster session 03
928P - Radiomic analysis based on machine learning of multi-MR sequences to assess early treatment response in locally advanced nasopharyngeal carcinoma
Presenter: Lei Qiu
Session: Poster session 03
929P - Advanced laryngeal squamous cell carcinoma prognosis and machine learning insights
Presenter: Tala Alshwayyat
Session: Poster session 03
Resources:
Abstract
930P - Real-world data analysis of oncological outcomes in patients with pathological extranodal extension (ENE) in OSCC: A proposal to refine the pathological nodal staging system
Presenter: Abhinav Thaduri
Session: Poster session 03
931P - Deep learning models for predicting short-term efficacy in locally advanced nasopharyngeal carcinoma
Presenter: Kexin Shi
Session: Poster session 03
932P - Accuracy and prognostic implications of extranodal extension on radiologic imaging in HPV-positive oropharyngeal cancer (HNCIG-ENE): A multinational, real-world study
Presenter: Hisham Mehanna
Session: Poster session 03
933P - Prediction of survival in patients with head and neck merkel cell carcinoma: Statistical and machine-learning approaches
Presenter: Jehad Yasin
Session: Poster session 03
934P - Harnessing artificial intelligence on real-world data to predict recurrence in head and neck squamous cell carcinoma patients: The HNC-TACTIC study
Presenter: Hisham Mehanna
Session: Poster session 03
936P - Chronic pain in cancer survivors: Head and neck versus other cancers
Presenter: Rong Jiang
Session: Poster session 03