Biomarkers for predicting immunotherapy response and resistance in glioblastoma - Scorecard - MDSpire

Biomarkers for predicting immunotherapy response and resistance in glioblastoma

  • By

  • Samuel Kim

  • Matthew Abikenari

  • Brandon Bergsneider

  • Lily H. Kim

  • Michael Lim

  • May 5, 2026

  • 0 min

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Clinical Scorecard: Biomarkers for Assessing Response and Resistance to Immunotherapy in Glioblastoma

At a Glance

CategoryDetail
Condition
Key MechanismsTumor-associated immunosuppression, intra- and inter-tumoral heterogeneity, corruption of the blood-brain barrier, and specific biomarkers like PD-1/PD-L1 enrichment.
Target Population
Care Setting

Key Highlights

  • Biomarkers for immunotherapy response in glioblastoma are critical for patient selection.
  • Current standard of care remains unchanged for over two decades.
  • Emerging biomarkers include interferon signaling and immune cell population studies.
  • Machine learning and liquid biopsy are enhancing biomarker discovery.
  • Standardization of biomarkers is essential for clinical trial implementation.

Guideline-Based Recommendations

Diagnosis

    Management

    • Incorporate biomarker-driven endpoints in clinical trial designs, such as PD-1/PD-L1 enrichment and tumor mutational burden.

    Monitoring & Follow-up

      Risks

        Patient & Prescribing Data

        Biomarkers can inform treatment combinations and predict responses, such as through tumor mutational burden.

        Clinical Best Practices

        • Standardize biomarker evaluation in clinical workflows.
        • Focus on context-dependent biomarker signals for immunotherapy.
        • Ensure systematic validation of biomarkers for clinical utility.

        References

        Original Source(s)

        Biomarkers for predicting immunotherapy response and resistance in glioblastoma

        • by Samuel Kim, Matthew Abikenari, Brandon Bergsneider, Lily H. Kim, Michael Lim

        • May 5, 2026

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