Metabolomics to Assess Response to Immune Checkpoint Inhibitors in Patients with Non-Small-Cell Lung Cancer

Abstract

In the treatment of advanced non-small cell lung cancer (NSCLC), immune checkpoint inhibitors have shown remarkable results. However, not all patients with NSCLC respond to this drug treatment or receive durable benefits. Thus, patient stratification and selection, as well as the identification of predictive biomarkers, represent pivotal aspects to address. In this framework, metabolomics can be used to support the discrimination between responders and non-responders. Here, metabolomics was used to analyze the sera samples from 50 patients with NSCL treated with immune checkpoint inhibitors. All the samples were collected before the beginning of the treatment and were analyzed by NMR spectroscopy and multivariate statistical analyses. Significantly, we show that the metabolomic fingerprint of serum acts as a predictive “collective” biomarker to immune checkpoint inhibitors response, being able to predict individual therapy outcome with > 80% accuracy. Metabolomics represents a potential strategy for the real-time selection and monitoring of patients treated with immunotherapy. The prospective identification of responders and non-responders could improve NSCLC treatment and patient stratification, thus avoiding ineffective therapeutic strategies.

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A Contemporary Review of Immune Checkpoint Inhibitors in Advanced Clear Cell Renal Cell Carcinoma

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“…Factors such as the inherent variability of cancer and the complexity of the TME make it very difficult to detect a viable and reproducible metabolic fingerprint, especially when considering how certain components of the TME, such as Th17 cells and other subsets with IL-17 and IL-23, can help both fight (Muranski et al, 2008) and promote cancer growth (Numasaki et al, 2005;Dawod et al, 2020), but it is also notable that positive results have been achieved recently during attempts to find biomarkers of chemotherapeutic responses (Cardoso et al, 2018;Amin et al, 2019;Ghini et al, 2020). Biomarkers for response to immune checkpoint inhibitor therapy (ICI), such as the ratio of serum kynurenine/tryptophan, have shown promise in detecting negative outcomes for treatment in advanced melanoma and renal cell carcinoma patients treated with nivolumab, an antibody against programed cell death protein 1 (PD1) (Li H. et al, 2019).…”