Targeting the inhibitory programmed death-ligand 1 (PD-L1)/programmed death-1 (PD-1) axis with the immune checkpoint blocker nivolumab (Opdivo®) or atezolizumab (Tecentriq®), and the cytotoxic T-Lymphocyte Associated Protein 4 (CTLA4 or CD152) with the immune checkpoint blocker ipilimumab (Yervoy™) or tremelimumab, has become the face of immuno-oncology (1-5).
Treatment modalities with established predictive biomarkers that provide information about the effect of a therapeutic intervention and can be a target for therapy, and prognostic biomarkers that provide information about patients’ overall cancer outcome, regardless of therapy, can translate into precision medicine. In the case of predictive biomarkers, patients who will benefit from the treatment can be identified and, subsequently, targeted, leading to a wider-successfully-targeted patient populations, and a higher survival rate. Immunotherapy, in its current shape, lacks well-established predictive biomarkers, and, hence, applying immunotherapy to patients, unfortunately, remains more of a blind-not-precision-medicine. The only currently-adopted predictive biomarker, PD-L1 expression in the tumor microenvironment (6, 7), suffers several limitations (8, 9).
In melanoma, Snyder and colleagues (10) found that tumor mutation burden (TMB) measured by whole-exome sequencing (WES), was a predictor of increased survival in patients taking ipilimumab or tremelimumab. Hugo and coworkers (11) noted that higher TMB was associated with improved survival in patients with metastatic melanoma receiving PD-1 immune checkpoint blockade. Whilst, Van Allen et al. (12) found that higher TMB correlated with higher clinical benefit in patients with metastatic cutaneous melanoma taking ipilimumab.
In colorectal cancer, Le and coworkers (13) noted that mismatch-repair status, a part of TMB, predicted clinical benefit in patients taking pembrolizumab (Keytruda®, PD-1 inhibitor in lymphocytes).
In non-small cell lung cancer (NSCLC), Rizvi and colleagues (14) demonstrated that a higher somatic nonsynonymous mutation burden measured by WES, was associated with improved overall response rates (ORRs), progression-free survival (PFS) and durable clinical benefit in patients taking pembrolizumab. This observation aligned with metastatic NSCLC, where Carbone and coworkers (15), in the CheckMate 026 study, noted that a higher TMB was associated with higher response rates in patients receiving nivolumab in combination with platinum doublet chemotherapy as first-line therapy. Specifically, patients with higher TMB alongside higher PD-L1 expression, achieved best clinical outcomes. Hellman and coworkers (16), in CheckMate 012, noted that that TMB could identify advanced NSCLC patients, who would benefit from the nivolumab/ipilimumab combination as first line therapy. This spurred the conduction of CheckMate 568, where Ramalingam and colleagues (17), found that in NSCLC, a TMB score of ≥ 10 mutations/megabase set responders from non-responders apart, to the nivolumab/ipilimumab combination as first line therapy, regardless of their PD-L1 levels. These studies bonify the clinical benefit of TMB as a predictive biomarker in the setting of advanced NSCLC.
Tumors with higher TMB are perceived to have more immunogenic neoantigens that can be recognized by the immune system in response to immune checkpoint inhibitors (18, 19) (see Fig. 1 below).
Rizvi et al. (20) noted that in advanced NSCLC, a higher TMB measured by next-generation sequencing (NGS) versus WES, correlated with durable clinical benefit and improved ORRs and PFS rates, in patients receiving immune checkpoint inhibitors. Kowanetz and coworkers (21) reported that in advanced NSCLC, a higher TMB measured by NGS, was associated with higher ORRs, PFS, and overall survival (OS), in patients taking atezolizumab, independent of their PD-L1 status.
In various cancers, Goodman and colleagues (22) found that a higher TMB measured by NGS, correlated with higher ORRs, PFS, and OS, in patients taking different immune checkpoint inhibitors. In the previous three studies (20-22), investigators defined high TMB at different thresholds and used different NGS panels. In addition, NGS is less expensive in comparison with WES in providing TMB molecular data. Two studies (20, 23) looked into TMB, assessed by NGS versus WES, in relation to clinical outcomes with immune checkpoint inhibitors, and concluded that TMB is a predictive biomarker of value. Opting for NGS in clinical practice after conducting larger clinical trials that substantiate NGS’s value over WES in assessing TMB, and synchronizing the threshold for high TMB, alongside unifying the NGS panels, are areas of improvement.
In many of the aforementioned studies, a higher TMB correlated with higher clinical benefit, irrespective of PD-L1 levels. This already sets TMB at an advantage over PD-L1 expression, as a better predictive biomarker.
Another method to assess TMB is cell-free DNA in peripheral blood, which was shown to be predictive of the benefit of immune checkpoint inhibition (24). Aside from TMB, there are other promising immunotherapy predictive biomarkers in the making (25) such as: imaging biomarkers, peripheral blood T cells (26), T-cell receptor clonality, tumor-infiltrating lymphocytes (27, 28) and immune gene signatures (29).
As promising as TMB may be (22), limitations include: cost, patient access to testing, long turnaround time, diverse testing platforms, tumor genomic heterogeneity and specimen availability.
The research and development of cost-effective, patient accessible and precise predictive biomarkers, remains a clinical priority to derive most patient-benefit from immunotherapy. TMB is one candidate worth-considering.
Author profile: Balkees Abderrahman, M.D. is the Dallas/Ft. Worth Living Legend Fellow of Cancer Research at the Department of Breast Medical Oncology, the University of Texas MD Anderson Cancer Center (TX, USA) and a PhD trainee under model “Individuals of Very High Quality” at the Faculty of Biological Sciences, the University of Leeds (West Yorkshire, UK). Balkees is a regular contributor to Oncology Central; you can view her full biography here.