DP011 | CLINICAL IMPACT OF UNTARGETED BASELINE PLASMA METABOLOMICS IN NEWLY DIAGNOSED DIFFUSE LARGE B CELL LYMPHOMA

Introduction. Metabolomics is emerging as a promising tool to identify novel prognostic biomarkers in oncohematology. Its prognostic impact in diffuse large B cell lymphoma (DLBCL) is largely unknown. The aim of this study was to investigate the potential clinical impact and biological correlations of baseline metabolomics in newly diagnosed DLBCL. Methods. The study relies on a real-world cohort of 96 R-CHOP treated DLBCL provided with baseline plasma samples. After metabolite extraction, samples were analyzed with a bidimensional gas chromatography/mass spectrometry. Data were processed using a Statical Compare software. Metabolites were expressed as abundance values. Molecular clusters (A53, BN2, EZB, MCD and ST2) were identified on circulating tumor DNA using the LymphGen tool. A logistic regression approach with Ridge penalization was applied to find potential correlations. The maximally selected rank statistics was used to identify the best cutoff in predicting progression free survival (PFS) for each metabolite abundance value. Results. The median age was 68.7 years. After a median follow-up of 55.6 months, 40-month PFS and overall survival (OS) were 61.4% and 72.8%, respectively. Untargeted metabolomic analysis led to the identification of 281 metabolites, 40 of them associated with DLBCL molecular clusters. Some metabolites were common across all molecular subgroups, but each cluster was also enriched in specific upregulated metabolites (Fig.1A). Based on PFS at 24 months from diagnosis, patients were divided into progressive (N=34) and non-progressive (N=62) cases. 10 metabolites were differentially up- or downregulated in progressive cases. In multivariate analysis, low abundance of L-threonine (HR 5.65, p=0.002) and isopropyl stearate (HR 3.38, p=0.028) and high abundance of 4-hydroxybenzeneacetic acid (HR 4.12, p=0.004) and ribitol (HR 2.91, p=0.004) retained an independent association with shorter PFS, whereas other metabolites lost their prognostic value (Kaplan Meier curves: fig.1B-E). L-threonine and ribitol are mainly involved in cell energy metabolism. 4-hydroxybenzeneacetic acid and ribitol are associated with changes in intestinal microbiome composition. Conclusions. Baseline plasma metabolites harbor a promising prognostic value in DLBCL and exhibit distinct distributions across molecular clusters. If validated, these findings may provide new insights into DLBCL biology and may identify novel potential therapeutic targets.