# Tumor Mutational Burden as a Prognostic Biomarker in Follicular Lymphoma

## TL;DR

This study shows that the number of genetic mutations in follicular lymphoma tumors can predict patient outcomes, helping identify those at higher risk of early relapse.

## Contribution

The study introduces tumor mutational burden as a novel prognostic biomarker for follicular lymphoma patients.

## Key findings

- Patients with higher tumor mutational burden experienced longer survival and fewer early relapses.
- Tumor mutational burden was associated with specific genetic alterations like t(14;18) translocation and BCL2 mutations.
- Tumor mutational burden remained stable between diagnosis and relapse, despite changes in the molecular landscape.

## Abstract

Follicular lymphoma is a slow-growing type of blood cancer. Around 20% of patients do not respond or relapse early after standard first-line treatment and have a worse outcome. Currently, there are no clinical tools that accurately identify these high-risk patients at diagnosis. In this study, we explored whether the number of genetic alterations present in the tumor, known as tumor mutational burden, could help predict patient prognosis. We analyzed tumor samples obtained from patients with follicular lymphoma using next-generation sequencing and explored the relationship between genetic findings and clinical outcomes. Patients with more tumor mutations were less likely to experience early relapses and lived longer, while those with fewer mutations were more prone to relapse early. These results suggest that measuring tumor mutational burden may help improve risk stratification in follicular lymphoma.

Introduction: Follicular lymphoma (FL) is the most common indolent non-Hodgkin lymphoma. Approximately 20% of patients experience early relapse within 24 months (POD24) of immunochemotherapy (ICT), a subgroup associated with poor prognosis and not well-identified by current prognostic indices. Given that tumor mutational burden (TMB) has been associated with outcome in various cancers, we investigated its potential as a prognostic biomarker in FL. Methods: TMB was estimated by next-generation sequencing using a 409-gene panel in a cohort of 119 patients diagnosed with FL grades 1–3A and treated with frontline immunotherapy or ICT. Results: Although TMB was not associated with clinical variables in non-transformed FL patients, higher TMB values were observed in patients harboring the t(14;18) translocation, mutations in BCL2, TNFRSF14, or genes involved in cellular migration (GNA13, GNAI2). Notably, patients with high TMB (>2.55 mutations per megabase) showed longer progression-free survival, lymphoma-specific survival, and overall survival, and had fewer mutations affecting the mTORC1 pathway. A higher proportion of POD24 patients was observed in the low TMB subgroup. In 25 paired diagnosis-relapse samples, TMB remained globally stable, although variations in the molecular landscape were observed. In addition, we analyzed TMB in a separate cohort of patients presenting transformed FL at diagnosis (n = 16). Higher TMB was also associated with the t(14;18) chromosomal translocation, but not with clinical features or survival. Conclusions: These findings support the potential of TMB as a prognostic biomarker in FL, providing molecular understanding beyond established clinical indices and aiding in the identification of patients at higher risk of early progression following ICT.