Tumor mutation burden assessment as a predictive biomarker for immunotherapy in lung cancer patients: getting ready for primetime or not?
The emergence of immunotherapy as a first- or second-line of treatment has revolutionized the therapeutic management of lung cancer patients. However, not all lung cancer patients receive the same benefit from this treatment, leading to limitations in the number of patients who can receive anti-PD-1/PD-L1 checkpoint inhibitors because some secondary toxicity has been associated with immunotherapy, and because some patients would benefit more from chemotherapy. In this context, the selection of patients is currently based on PD-L1 immunohistochemistry (IHC), specifically on the percentage of PD-L1 positive tumor cells. To date, this is the only validated biomarker that is used as a companion diagnostic test for immunotherapy in non-small cell carcinoma lung (NSCLC) patients. However, this biomarker is not sufficiently robust and demonstrates many challenges. For example, some patients with more than 50% PD-L1 positive tumor cells are non-responders to anti-PD-1/PD-L1 treatment, while conversely, other patients with no PD-L1 positive tumor cells are good responders. The tumor mutation burden (TMB) or tumor mutation load (TML) emerged recently as a new predictive biomarker for immunotherapy response in NSCLC. However, this biomarker needs to be validated for routine clinical use and shares similar constraints with the PD-L1 IHC biomarker. PD-L1 IHC and TMB are currently the two best predictive biomarkers that could soon be used to systematically inform treatment decisions in advanced or metastatic NSCLC patients. The aim of this review is to consider the possible integration of TMB testing in daily practice through a pros- and cons-debate, and to establish sample quality-dependent algorithms and the main current constraints for laboratories considering TMB assessments.