Posted: April 1, 2019
Why TMB Should Be Assessed in Patients with Advanced NSCLC
By Fabrice Barlesi, MD, PhD
Immune checkpoint inhibitors, especially PD-1 and PD-L1 inhibitors, have deeply changed the second-line treatment of patients with advanced NSCLC, with three newly registered drugs in only a few years. Immune checkpoint inhibitors are also changing the first-line treatment of patients with advanced and locally advanced NSCLC and will likely change the treatment of patients with extensive small cell lung cancer (SCLC) and mesothelioma. These changes are mainly supported by the long-term efficacy of immune checkpoint inhibitors, with a proportion of patients experiencing long-lasting responses and durable survival. Therefore, identifying those likely to respond while looking for alternative strategies for those who are not likely to respond or whose responses are likely to be limited is crucial.
PD-L1: A Good Strategy
Increased PD-L1 expression is globally associated with an increased benefit of PD-L1 immune checkpoint inhibitors as monotherapy. However, a significant benefit over the standard docetaxel therapy has also been demonstrated in patients with low or no PD-L1 expression.1 Conversely, a significant proportion of patients with high tumor PD-L1 expression (≥ 50%) experience progressive disease within 3 months on first-line pembrolizumab monotherapy.2 Moreover, PD-L1 expression has demonstrated no impact in predicting the benefit of immune checkpoint inhibitor combinations with chemotherapy over chemotherapy alone. In summary, PD-L1 is an imperfect marker, and prediction of immune checkpoint inhibitor efficacy by PD-L1 expression remains a perfectible strategy.
TMB: A Better Strategy
Tumor mutational burden (TMB) offers a solid biologic rationale as a better strategy. TMB is defined as the number of mutations per DNA megabases (Mb). It was first suggested that the creation of neoantigens induced by mutation acquisition would increase tumor immunogenicity and, consequently, response to immune checkpoint inhibitors. Technically, although TMB was historically assessed by tissue whole-genome sequencing or whole-exome sequencing, targeted next-generation sequencing and whole-exome sequencing demonstrated a good correlation to estimate TMB.3 Subsequently, a blood-based assay, a more convenient way to assess TMB in routine practice, has been developed with success. Finally, and more importantly, TMB has been demonstrated to be fully independent of tumor PD-L1 expression, even in the subgroup with high levels of PD-L1 expression.
TMB has demonstrated a strong predictive value for efficacy (response rate and/or progression-free survival [PFS]) of immune checkpoint inhibitors in secondand third-line monotherapy. Rizvi et al. first reported a hazard ratio (HR) below 0.20 for PFS between patients with low and high TMB who were treated with pembrolizumab (median PFS 3.4 months versus NR; HR 0.15, 95% CI [0.04, 0.59] in the validation set).4 Kowanetz et al. showed comparable results in the FIR/ BIRCH and POPLAR studies for atezolizumab alone or versus docetaxel (HR for PFS 0.49, 95% CI [0.25, 0.93] and 0.49, 95% CI [0.19, 1.3] in the ≥ 9.9/MB and ≥ 15.8/MB subgroups, respectively).5 Gandara et al. confirmed those results in blood TMB in samples from the POPLAR and OAK studies (HR for PFS of 0.73, 0.65, and 0.61, for TMB ≥ 10/MB, ≥ 16/ MB, and ≥ 20/MB, respectively).6 TMB has also demonstrated a predictive value for efficacy (response rate and/ or PFS) of immune checkpoint inhibitors in first-line monotherapy. In CheckMate 026, Carbone et al. retrospectively showed an HR for PFS clearly favoring nivolumab over platinum-based chemotherapy in the TMB-high (243 or more mutations) subgroup (median PFS 9.7 months vs. 5.8 months; HR 0.62, 95% CI [0.38, 1.0]).7 Finally, TMB has demonstrated a predictive value for efficacy (response rate and/or PFS) of immune checkpoint inhibitors in the first line for combination nivolumab and ipilimumab. In the predefined high TMB (≥ 10 mut/Mb) subgroup of the CheckMate 227 study, Hellmann et al. showed a better PFS for patients treated with combination immune checkpoint inhibitors compared to platinum-based chemotherapy (median PFS 7.2 versus 5.5 months; HR 0.58, 97.5% CI [0.41, 0.81]; p < 0.001).8 Moreover, when considering those patients with less than 1% PD-L1 expression in the same study, Borghaei et al. nicely showed how TMB allows the selection of patients who derive a large benefit from the combination of nivolumab and ipilimumab over platinum-based chemotherapy (1-year PFS of 45% versus 18% for TMB high vs. low, respectively). In addition, this benefit translated into longlasting responses (with 93% of responses still maintained a year or more).9 These results have also been confirmed in extensive SCLC. Although preliminary, these results together highlight how TMB strongly complements PD-L1 expression assessment and will, therefore, help us treat patients with advanced NSCLC with immune checkpoint inhibitors alone or in combination. Several prospective studies are ongoing to provide clinicians with a simple, fast, reproducible, and affordable blood-based assay to assess TMB in daily practice. ✦
About the Author: Dr. Barlesi is professor of medicine at the University of Aix Marseille and head of the Multidisciplinary Oncology and Therapeutic Innovations department at Assistance Publique Hôpitaux de Marseille, France. He is associate editor for the IASLC Lung Cancer News.
1. Rittmeyer A, Barlesi F, Waterkamp D, et al. Atezolizumab versus docetaxel in patients with previously treated non-small-cell lung cancer (OAK): a phase 3, open-label, multicentre randomised controlled trial. Lancet. 2017;389(10066):255-265.
2. Reck M, Rodríguez-Abreu D, Robinson AG, et al. Pembrolizumab versus Chemotherapy for PD-L1- Positive Non-Small-Cell Lung Cancer. N Engl J Med. 2016;375(19):1823-1833.
3. Rizvi H, Sanchez-Vega F, La K, et al. Molecular Determinants of Response to Anti-Programmed Cell Death (PD)-1 and Anti-Programmed Death-Ligand 1 (PD-L1) Blockade in Patients With Non-Small-Cell Lung Cancer Profiled With Targeted Next-Generation Sequencing. J Clin Oncol. 2018; 36(7):633-641.
4. Rizvi NA, Hellmann MD, Snyder A, et al. Cancer immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 2015;348(6230):124-128.
5. Kowanetz M, Zou W, Shames D, et al. Tumor Mutation Burden (TMB) is Associated with Improved Efficacy of Atezolizumab in 1L and 2L+ NSCLC Patients. J Thorac Oncol. 2017;12(1) S321–S322.
6. Gandara D, Kowanetz M, Mok T, et al. Blood-Based Biomarkers for Cancer Immunotherapy: Tumor Mutational Burden in Blood (bTMB) is Associated With Improved Atezolizumab (atezo) Efficacy. Ann Oncol. 2017:v460-v496.
7. Carbone D, Reck M, Paz-Ares L, et al. First-Line Nivolumab in Stage IV or Recurrent Non–Small-Cell Lung Cancer. N Engl J Med. 2017;376:2415- 2426.
8. Hellmann MD, Ciuleanu TE, Pluzanski A, et al. Nivolumab plus Ipilimumab in Lung Cancer with a High Tumor Mutational Burden. N Engl J Med. 2018;378:2093-2104.
9. Borghaei H, Hellmann MD, Paz-Ares LG, et al. Nivolumab + Ipilimumab, Nivolumab + Chemotherapy, and Chemotherapy in Chemo-Naive Patients With Advanced Non-Small Cell Lung Cancer and <1% Tumor PD-L1 Expression: Results From CheckMate 227. J Clin Oncol. 2018;36 (suppl; abstr 9001).
10. Hellmann MD, Callahan MK, Awad MM, et al. Tumor Mutational Burden and Efficacy of Nivolumab Monotherapy and in Combination with Ipilimumab in Small-Cell Lung Cancer. Cancer Cell. 2018;33(5):853-861.
Tumor Mutation Burden in NSCLC: Not Ready for Prime Time
By Daniel Tan, BSc, MBBS, MRCP, PhD
Despite the expanding scope for the use of immune checkpoint inhibitors in NSCLC, not all patients derive clinical benefit, highlighting the need for high-precision individualized biomarkers that can improve patient selection and future combination strategies. At present, the implementation of PD-L1 expression testing and determination of cutoffs have been based on superior efficacy and quality of life, relative to standard-of-care treatment. After initial studies established the role of monotherapy PD-1/PD-L1 inhibition in the second-line setting and beyond, immuno-oncology combinations (with chemotherapy or CTLA-4 antibodies) have more recently been explored in the first-line setting. Given the variability in PD-L1 testing methodologies, as well as spatial and temporal heterogeneity,1 additional biomarkers to further refine patient stratification, such as tumor mutational burden (TMB), have been actively explored.
The initial premise for TMB was that the number of somatic mutations would correspond to the likelihood of harboring tumor-associated neoantigens, which, in turn, would represent a surrogate indicator of immunogenicity. This hypothesis was first examined in a cohort of 34 patients with NSCLC, where a threshold of 178 nonsynonymous mutations, as determined by whole-exome sequencing, identified patients who were more likely to achieve durable clinical benefit with pembrolizumab.2 This observation was further extended to other clinical datasets involving atezolizumab and nivolumab, independently highlighting the value of TMB across different PD-1/PD-L1 antibodies.3
One of the most striking results was the potential role of TMB in prediction of response to combination PD-1 and CTLA-4 antibodies for those patients with PD-L1 expression levels less than 1%.4 Th is combination was examined in a large prospective phase III study that randomly assigned 1,739 patients with NSCLC to three arms based on PD-L1 status: ipilimumab/nivolumab versus nivolumab monotherapy versus chemotherapy in those with PD-L1 expression of 1% or higher or ipilimumab/ nivolumab versus nivolumab/ chemotherapy versus chemotherapy alone in those with no PD-L1 expression. However, after restricting the patient cohorts to those who had (1) TMB evaluated successfully and (2) patients with 10 or more mutations per megabase, only 139 patients assigned to ipilimumab/ nivolumab and 160 assigned to chemotherapy were included in the efficacy analysis. Most notably in patients with PD-L1 expression levels of 1% or greater, the hazard ratio (HR) for disease progression or death was 0.62 (95% CI [0.44, 0.88]), whereas the HR was 0.48 (95% CI [0.27, 0.85]) for patients with PD-L1 expression levels less than 1%. The comparable patient cohort with TMB ≥ 10 and PD-L1 ≥ 1% showed a HR of 0.75 (95% CI [0.53, 1.07]).4 These data suggest a role for combination ipilimumab/ nivolumab in the absence of PD-L1 expression; because only selected cohorts were included in this analysis, reports on the other subgroups are eagerly awaited.
The lack of relationship between PD-L1 status and TMB has been observed in several different studies, highlighting the potential complementary role for both biomarkers. This discordance suggests that PD-L1 and TMB may reflect different processes in the development of lung cancer. In the context of exhausted T cells from chronic antigen stimulation, PD-L1 overexpression provides a measure of the extent to which immune escape might be implicated. On the other hand, TMB, derived from counting the number of coding mutations, provides a window to crudely infer the life history of a tumor. However, numerous factors can influence the final mutational load, such as DNA repair capacity and mutation rate. Because current neoantigenpredictive algorithms are imperfect, it is likely that the relationship between TMB and antigenicity is not entirely linear. Furthermore, emerging studies suggest that additional factors can affect immunogenicity, including the clonality of neoantigens and the tumor microenvironment.5 Thus, like PD-L1 expression, there can also be reasons for varying clinical relevance of a TMB result, including clonal architecture (distinct between smokers and non-smokers)6 and region-specific increases in mutation load, as well as technical factors such as low tumor purity. The latter is reflected, in part, by the observation that only 58% of patients in CheckMate-227 had TMB successfully evaluated using the FoundationOne panel, a commercial platform using high-depth targeted nextgeneration sequencing.4
Although it has been suggested that exome sequencing estimations of TMB and targeted panels are largely concordant, these studies have been restricted to broad robust panels such as FoundationOne and MSK-IMPACT, encompassing 315 and 468 genes, respectively.7 Indeed, the practical issues of cost, turnaround time, and tissue attrition currently preclude such broad gene panels as a standard assay in the first-line setting for majority of patients with lung cancer. Computerized analysis further suggests that it may be feasible to estimate TMB based on smaller panels (e.g., 0.5 megabases), which result in wider confidence intervals from the true estimate.8 One recent study further highlights the potential of curating a specific gene set (e.g., 24 genes) that correlates with TMB.9 Nevertheless, the significant variability in tumor purities, sequencing parameters, and reference genomes, as well as the hitherto lack of concordance and cross-validation of next-generation sequencing panels, makes it challenging to implement TMB as a routine, reproducible clinical test.
Until more validation data are available from clinical trial cohorts with predefined cutoffs and the logistical challenges are addressed, TMB remains, at best, a promising exploratory biomarker. ✦
About the Author: Dr. Tan is a senior consultant in the Division of Medical Oncology, National Cancer Centre Singapore and senior clinician-scientist at Genome Institute of Singapore. He also directs the Experimental Cancer Therapeutics Unit and is current Chair of the IASLC Education Committee.
1. Hirsch FR, McElhinny A, Stanforth D, et al. PD-L1 Immunohistochemistry Assays for Lung Cancer: Results from Phase 1 of the Blueprint PD-L1 IHC Assay Comparison Project. J Thorac Oncol. 2017;12(2):208-222.
2. Rizvi NA, Hellmann MD, Snyder A, et al. Cancer Immunology. Mutational landscape determines sensitivity to PD-1 blockade in non-small cell lung cancer. Science. 2015;348(6230):124-128.
3. Kowanetz M, Zou W, Shames D, et al. OA20.01 Tumor Mutation Burden (TMB) is Associated with Improved Efficacy of Atezolizumab in 1L and 2L+ NSCLC Patients. J Thorac Oncol. 2017;12:S321-S322.
4. Hellmann MD, Rizvi NA, Goldman JW, et al. Nivolumab plus ipilimumab as first-line treatment for advanced non-small-cell lung cancer (CheckMate 012): results of an open-label, phase 1, multicohort study. Lancet Oncol. 2017;18(1):31- 41.
5. Schumacher TN, Hacohen N. Neoantigens encoded in the cancer genome. Curr Opin Immunol. 2016;41:98-103.
6. Nahar R, Zhai W, Zhang T, et al. Elucidating the genomic architecture of Asian EGFR-mutant lung adenocarcinoma through multi-region exome sequencing. Nat Commun. 2018;9(1):216.
7. Hellmann MD, Nathanson T, Rizvi H, et al. Genomic Features of Response to Combination Immunotherapy in Patients with Advanced Non-Small-Cell Lung Cancer. Cancer Cell. 2018;33(5):843-844.
8. Chalmers ZR, Connelly CF, Fabrizio D, et al. Analysis of 100,000 human cancer genomes reveals the landscape of tumor mutational burden. Genome Med. 2017;9(1):34.
9. Lyu G-Y, Yeh Y-H, Yeh Y-C, Wang Y-C. Mutation load estimation model as a predictor of the response to cancer immunotherapy. NPJ Genom Med. 2018;3:12.