Glycolysis and Immune Interplay: Shaping Prognosis and Treatment in DLBCL

Glycolysis-related modification patterns define three immune subtypes in diffuse large B‑cell lymphoma (DLBCL) that stratify prognosis and predict treatment response.

This retrospective genomic profiling study of DLBCL cases assessed associations between glycolysis-related modification patterns and clinical outcomes, including overall survival and chemotherapy response.

These subtypes reveal molecular heterogeneity that helps explain variable treatment resistance and relapse after standard immunochemotherapy.

Historically, genetics and clinical indices have provided imperfect risk stratification in DLBCL. Adding metabolic and immune phenotyping refines that prediction. Methodologically, the team combined glycolysis-focused gene modification profiling with immune-feature mapping to classify tumors into metabolic–immune subtypes, producing actionable prognostic categories.

Across the identified glycolysis-driven immune subtypes, Kaplan–Meier analyses showed the immune‑inflamed subtype had longer median overall survival and higher response rates to anthracycline‑based regimens than the immune‑excluded and immune‑desert subtypes.

Distinct glycolytic states correlate with differing degrees of immune infiltration and suppressive microenvironments. Glycolysis‑associated signatures map to immune‑desert and immune‑excluded phenotypes—characterized by low intratumoral T‑cell penetration or stromal‑mediated exclusion—whereas lower or reprogrammed glycolysis corresponds with immune‑inflamed contexts rich in activated CD4+ and CD8+ cells. These microenvironment differences—via acidification, stromal activation, and recruitment of suppressive myeloid elements—can plausibly drive therapy resistance, while inflamed microenvironments facilitate chemotherapy‑induced tumor cell death. Overall, metabolic state aligns with immune phenotype and directly influences clinical outcomes.

Key Takeaways:

• The glycolysis–immune classification separates DLBCL into immune‑inflamed, immune‑excluded, and immune‑desert subtypes with distinct outcomes and chemotherapy sensitivity.
• Immune‑inflamed tumors associate with better overall survival and greater anthracycline responsiveness; immune‑desert and immune‑excluded tumors show poorer outcomes and relative resistance.
• Metabolic profiling coupled with immune phenotyping offers a practical path toward prognostic refinement and rational trial design, pending prospective validation.