Composite versus individual biomarkers for predicting clinical benefit to PD-1 blockade in NSCLC 83 3 Introduction The success of monoclonal antibodies targeting the inhibitory receptor programmed cell death protein 1 (PD-1) and its ligand programmed death-ligand 1 (PD‑L1) has changed the therapeutic landscape of advanced stage non-small cell lung cancer (NSCLC). A subset of patients treated with these PD-1/PD-L1 blocking agents experience durable responses, translating into a significant survival advantage1–7. However, the majority fails to derive durable clinical benefit, underscoring the need for predictive biomarkers to support treatment decision-making in clinical practice. Specifically, the identification of biomarkers capable of excluding patients unlikely to benefit from PD-1/PD-L1 blockade therapy can prevent unnecessary side effects and contribute to the reduction of health care costs. The assessment of tumor PD-L1 expression through immunohistochemistry (IHC) has been a focal point in numerous clinical trials as a potential predictive biomarker8. Although a positive correlation between PD-L1 expression and treatment outcomes has been observed in advanced stage NSCLC patients1,5–7, a considerable proportion (60% to 70%) of patients with PD-L1 positive tumors do not respond1,2,5. Besides this, PD-L1 assessment by IHC is hampered by intratumor heterogeneity, interassay- and interobserver variability as well as pre-analytical variation9–14. Tumor Mutation Burden (TMB), reflecting the number of somatic mutations as a surrogate for potential tumor antigenicity, has also shown predictive potential. However, its clinical implementation faces challenges, including the lack of a robust and predictive TMB cut-off and technical issues related to variation across platforms15–17. Given these challenges, there is an urgent need for biomarkers that can more accurately predict responses to PD-1/PD-L1 blockade in advanced NSCLC. Since this treatment regimen is thought to reinvigorate tumor-reactive T cells18–20, several T cell markers have been investigated. For example, the density of CD8+ tumor infiltrating lymphocytes (TILs) has been correlated with responses to PD-1 blockade in various cancer types, including melanoma18, colorectal cancer21, and NSCLC22,23. In addition, previous work showed that a distinct T cell population, termed PD-1T TILs, can predict clinical benefit in NSCLC24,25. These PD-1T TILs predominantly localize in tertiary lymphoid structures (TLS)24,25. Notably, B cells, critical components of these TLS, have also been associated with response to PD-1 blocking agents26–28. Other studies have developed predictive RNA expression signatures, such as the “tumor inflammation signature” (TIS), characterizing features of immune activity in the tumor microenvironment (TME)29–31.
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