Biomarkers in Cancer Immunotherapy: Personalization and Overcoming Resistance

In the rapidly evolving landscape of cancer treatment, biomarkers spearhead a new frontier in immunotherapy, heralding personalized interventions tailored to individual patient profiles. Current NCCN and ESMO guidelines incorporate biomarker stratification for immunotherapy in select tumors. This approach not only enhances treatment efficacy but also confronts the formidable challenge of therapeutic resistance.

The biomarkers defining a tumor’s molecular profile have transformed diagnostic pathways and therapeutic decisions alike, weaving innovation into routine care—and, critically, help reveal where resistance may emerge. These biomarkers, including PD-L1 expression, tumor mutational burden, and microsatellite instability, guide precision therapy by predicting responses and tailoring interventions.

Interrogating oncogenic pathways and the tumor microenvironment has identified biomarkers that inform targeted and immunotherapeutic strategies. Recent advancements in single-cell transcriptomics provide a profound understanding of tumor-immune interactions, a crucial step in refining tailored therapeutic options. In practice, single-cell maps can reveal exhausted T-cell states or myeloid-driven suppression, pointing to rational combinations that pair checkpoint blockade with agents targeting specific cellular niches.

Recent studies suggest biomarkers can refine therapeutic choices, though benefits vary by tumor type and biomarker thresholds (e.g., MSI‑H predicts response to PD‑1 blockade). Biomarker-focused approaches can help align therapies with tumor biology without guaranteeing uniform outcomes. For example, high PD‑L1 expression can enrich for responders in non–small cell lung cancer, whereas tumor mutational burden has shown variable predictive value across diseases, reinforcing the need for context-specific interpretation.

Clinical practice is moving towards embedding single-cell analysis to reinterpret how treatments align with patient-specific profiles. This evolution in diagnostic technology is increasingly likely, though adoption remains uneven due to resource and workflow constraints, as biomarkers open nuanced narratives in patient management and care. Multidisciplinary tumor boards now frequently discuss whether to repeat biopsies or leverage liquid biopsy to reassess biomarkers at progression, balancing clinical utility against procedure risks and cost.

For patients grappling with aggressive tumors, biomarker-focused approaches can illuminate pathways to effective interventions. In settings such as melanoma and renal cell carcinoma, combination checkpoint blockade has improved outcomes for some patients and may help address resistance in select contexts. Still, toxicity trade-offs and patient comorbidities demand careful selection and shared decision-making, underscoring that escalation is not universally beneficial.

Navigating resistance remains daunting, particularly in immunosuppressive tumor microenvironments or high‑burden, poorly inflamed disease. Early-phase studies of combining checkpoint inhibitors with tumor microenvironment modulators show signals of activity, but efficacy remains under investigation. Beyond pharmacologic strategies, optimizing sequencing—such as introducing radiation to induce immunogenic cell death prior to immunotherapy—continues to be explored to tilt the balance toward response.

Yet despite progress, not all therapeutic responses are favorable, highlighting gaps in current approaches. This underscores unmet needs in trial design, biomarker validation, and equitable access to testing and therapies. Pragmatic trials that integrate real-world populations and standardized biomarker assays could accelerate learning while reducing disparities.

Multipronged regimens are being tested and may expand options for select patients; most evidence is from early-phase studies with variable response rates. As the field matures, aligning trial endpoints with patient-centered outcomes and validating biomarkers prospectively will determine which approaches meaningfully improve survival and quality of life.

Key Takeaways:

• Biomarkers such as PD‑L1, TMB, and MSI inform therapy selection in specific contexts, and PD‑L1 thresholds are tumor‑specific.
• Single‑cell approaches are emerging tools that may refine biomarker discovery and patient stratification.
• Combination strategies show promise in certain cancers, but benefits are disease‑ and biomarker‑dependent.
• Investigational combinations (for example, PD‑1 with Wnt pathway inhibitors) are under study; efficacy is unproven.