Use of Molecular Immune Signatures for Frontline Treatment Selection in Patients with Advanced Stage Follicular Lymphoma

Introduction. Chemoimmunotherapy (CIT) with bendamustine and rituximab (BR) or rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (RCHOP) represent the standard frontline treatment for patients with advanced and high tumor burden follicular lymphoma (FL). The combination of lenalidomide and rituximab (R²) has shown similar efficacy to frontline CIT. While clinical prognostic scores such as FLIPI, FLIPI-2 and PRIMA-PI have been developed in CIT-treated patients, predictive biological tools for frontline treatment selection are currently lacking for FL. Lymphoma molecular subtyping, identified through transcriptomic characterization of the lymphoma microenvironment (LME), and precise reconstruction of its composition, through deconvolution, have been shown to predict outcomes in patients with large B-cell lymphoma (Kotlov et al., Cancer Discov, 2021). It remains unclear, however, whether molecular immune signatures could also be utilized for treatment selection in FL patients.

Methods. Pre-treatment tissue biopsies were collected from patients with advanced and high tumor burden FL treated with frontline BR, RCHOP, or R² and with available follow-up clinical data. Baseline clinical and laboratory characteristics were retrospectively used to calculate FLIPI, FLIPI-,2 and PRIMA-PI scores. Response and survival were assessed according to 2014 Lugano criteria. Bulk RNA sequencing was generated for LME subtyping, cell deconvolution using the Kassandra algorithm (Zaitsev et al., Cancer Cell, 2022), B-cell associated gene signatures (BAGS) analysis, and B-cell receptor (BCR) repertoire analysis. Mann-Whitney test was used for comparing continuous variables between patient groups. The log rank test was used to assess the difference in progression-free survival between patient groups.

Results. The analysis included 35 patients: 12 treated with frontline BR, 12 with frontline RCHOP, and 11 with frontline R². Twenty-three (66%) had high FLIPI scores, 14 (40%) had high FLIPI-2 scores, and 7 (20%) had high PRIMA-PI scores. Patients with high FLIPI score (3‒5) displayed a significant decrease in BCR diversity as compared to those with low-intermediate FLIPI score (0‒2), shown by smaller Shannon and higher Simpson indexes. In addition, patients with higher FLIPI scores (evaluated as a continuous variable) tended to have higher T-regulatory (T-reg) and T-reg traffic signature scores. No significant associations were observed between LME subtypes, BAGS, cell deconvolution, or BCR repertoire and FLIPI-2 or PRIMA-PI scores.

Median follow-up for the whole cohort was 122 months (95% confidence interval [CI], 107-146 months) and median progression-free survival (PFS) was 143 months (95% CI, 98.6-NA months). No significant difference in median PFS was observed when comparing CIT-treated patients (BR or RCHOP) to R²-treated patients (p=0.27). However, when analyzing PFS within the 4 BAGS subgroups [light-zone like (n=7), dark zone-like (n=10), normal-like (n=13), and plasma cell-like(n=5)], patients with normal-like BAGS experienced a significantly longer median PFS when treated with BR (not reached [NR]) compared to RCHOP (143 months) or R² (31 months)(p=0.05), and PFS with CIT compared to R² (NR vs 31 months, p=0.03). In addition, analysis of T-cell signature, including CD3D, CD3G, TRBC1, TRAT1, TRAC, CD3E, CD28, TRBC2, ITK, and TBX21, categorized as high or low based on the cohort median, revealed patients receiving frontline R² with high T-cell signature scores to experience significantly longer median PFS compared to those with low T-cell signature scores (NR vs 21 months, p=0.04). No association between treatment modality and PFS based on TME subtypes was observed.

Discussion. While FLIPI scores are associated with the molecular features of FL, including BCR diversity and T-reg signatures, clinical prognostic scores have a limited impact in biological signatures. Our findings suggest that longer PFS could be achieved by using CIT to treat patients with normal-like BAGS and R² to treat those with high T-cell signature scores. Pending validation with large datasets and clinical trials, these findings suggest that pre-treatment molecular immune signatures may facilitate frontline treatment selection in FL.