The Construction of Novel Risk Scores in Diffuse Large B-Cell Lymphoma with Diabetes and the Identification of Glycosylation-Related Prognostic Biomarkers

Background: Glucose metabolism and glycosylation modification have been found to be associated with the development of a variety of tumors, and targeting them has become a new avenue of therapeutic intervention in tumors. Diffuse large B-cell lymphoma (DLBCL) patients accompanied with diabetes has been found to display worse prognosis. However, the role of glucose metabolism and glycosylation modification in DLBCL development has not been elucidated. Here, we aimed to establish novel risk scores in DLBCL patients with diabetes, and identify glycosylation-related prognostic biomarkers, which might significantly improve the risk stratification and individualized treatment in DLBCL patients with diabetes.

Methods: We retrospectively analyzed 176 patients diagnosed with DLBCL with diabetes in Shandong Provincial Hospital from June 2011 to Feb 2022. Univariate analysis and multivariate analysis were applied to evaluate the prognostic role of clinical indicators in DLBCL patients with diabetes. This study was approved by the Medical Ethical Committee of Shandong Provincial Hospital, and all samples were collected with informed consents. RNA sequencing (RNA-seq) data and clinical data of DLBCL patients were collected from GSE23647 (n = 42), GSE32018 (n = 35), GSE181063 (n = 1037). Then, LASSO Cox regression analysis and immune infiltration estimate were applied to illuminate the role of differentially expressed glycosylation-related genes (GRGs) in prognostic prediction and immune response in DLBCL development.

Results:

A total of 176 eligible DLBCL patients with diabetes were included. Through univariate and multivariate analysis, three clinical variables were confirmed as independently prognostic predictors in DLBCL patients with diabetes, including sialic acid (SA) ≥ 754 mg/L (HR: 2.684, P = 0.01), lactic dehydrogenase (LDH) ≥ 250 U/L (HR: 3.730, P = 0.005) and creatinine (CREA) ≥ 135 μmol/L (HR: 12.550, P = 0.04).

Subsequently, a novel prognostic model, SLC-Score (= 2.5 × SA + 3.5 × LDH + 12.5 × CREA), was constructed, and patients were stratified into 2 groups: low-score (< 6 score, n=31) group, and high-score (≥ 6 score, n=79) group. The prognosis of DLBCL patients in the 2 groups presented significant differences (Fig. 1A). ROC curve showed that the discriminative ability of the SLC-Score was better than NCCN-IPI score (AUC=0.818 vs 0.635, Fig. 1A). Time-dependent ROC also revealed the high predictable ability of SLC-Score in DLBCL with diabetes (1-year AUC=0.850, 3-year AUC=0.860, 5-year AUC=0.950, respectively). Decision curve analysis revealed that SLC-Score model had higher net benefit than NCCN-IPI score.

To identify prognostic GRGs in DLBCL and explore the regulatory role of glycosylation modification in DLBCL development, we obtained 438 GRGs using GeneCards and KEGG. Univariate Cox regression analysis was applied to evaluate the predictive ability of these GRGs in the assessment of clinical prognosis of DLBCL patients, and five GRGs (MAN1C1, BAG2, FBP1, ST8SIA1, HSPH1) were found to be differentially expressed and display prognostic role in DLBCL patients (Fig. 1B). Through Lasso Cox analysis, we established a 5-gene signature in DLBCL patients, which displayed reliable predictive ability in the prognosis of DLBCL patients (Fig. 1B). Furthermore, immune infiltration estimate revealed the close association between GRGs and immune response in DLBCL, indicating the underlying mechanism of glycosylation modification in DLBCL development. Furthermore, we performed pan-cancer analysis in 33 kinds of tumors from TCGA database, and illuminated the prognostic role of glycosylation-related gene signature in several tumors, including DLBCL, acute myeloid leukemia, and bladder urothelial carcinoma, etc.

Conclusions: For the first time, we established the novel SLC-Score and illuminated its superiority in prognostic prediction for DLBCL patients with diabetes. GRGs were found to be intimately associated with immune response and clinical prognosis in the development of DLBCL. Our findings might provide novel risk scores and glycosylation-related biomarkers to improve the risk stratification of DLBCL patients with diabetes.