Evidence Builds for Tumor Mutational Burden as Immunotherapy Biomarker

Amid a pressing need to identify patients most likely to respond to immune checkpoint inhibitors (ICIs), tumor mutational burden (TMB) has emerged as a highly promising and clinically validated biomarker, at least in the setting of lung cancer. Results from studies have demonstrated that subsets of patients with high TMB exist across almost all cancer types and that assessing TMB through whole-exome sequencing (WES) or next-generation sequencing (NGS) can predict response to a range of different types of immunotherapy.

The impetus for focusing on TMB stems in part from the recent FDA approval of ICIs for tumor-agnostic and colorectal cancer (CRC) indications in patients with impaired DNA repair capabilities, as determined by high levels of mismatch repair deficiency (dMMR) or microsatellite instability (MSI). The efficacy of ICIs in patients with defective DNA repair mechanisms further reinforced a long-held idea that immunotherapies may be more effective in patients who have highly mutated genomes, reflected in their TMB.

A Heavy Load

TMB has been a hot topic at oncology conferences this year. Investigators and test developers must overcome a variety of challenges before it is ready for prime time as a biomarker, but it appears poised to bring immunotherapy into the era of personalized medicine.It is a central tenet of cancer biology that tumors arise and evolve as a result of the acquisition of damage to the genome, generating characteristic genomic alterations that lead to the dysregulation of key cellular processes termed cancer hallmarks.^1,2 In addition to identifying individual frequently altered genes that function as drivers of particular cancer types, results from genome sequencing studies have revealed the global spectrum of somatic mutations across a given tumor, known as the TMB or mutational load. TMB is defined as the number of mutations per megabase (Mb) of DNA.

Results from recent large-scale pan-cancer genome sequencing studies have revealed that TMB varies widely among cancer types, ranging from 0.1 mutations per megabase in some pediatric tumors to approximately 100 mutations per megabase in lung cancer and melanoma (Figure).^3-5

There are many possible mechanisms underlying increased mutation rates in certain tumor types. Exposure to certain mutagens, such as ultraviolet radiation and cigarette smoke, can greatly increase the number of mutations. Genomic assaults on certain cellular pathways can create a more unstable genome, including the DNA damage repair and DNA replication pathways, which can lead to the accumulation of mutations as a result of unrepaired DNA damage and replicative errors.

Seeds of Their Own Destruction

Loss of function mutations in the TP53 gene are among the most commonly observed alterations in human cancer and are another source of increased TMB. The protein encoded by this gene, p53, is dubbed the guardian of the genome because it helps to ensure genome stability.⁵It has long been suspected that cancers with a greater number of gene mutations may provoke a stronger antitumor immune response. The thinking behind this hypothesis relates to the production of neoantigens—fragments of proteins expressed on the surface of cancer cells that are encoded by mutated genes. Neoantigens are unique to cancer cells because they are derived from a mutant gene, which may encode a mutant protein that differs from that expressed by normal cells. Therefore, neoantigens have the potential to be recognized as foreign by the cells of the immune system that patrol the body. A greater number of neoantigens might mean increased stimulation of those immune cells and a stronger immune response. In this way, cancer cells may generate the seeds of their own destruction.^6,7

Figure. TMB Prevalence Across Solid Cancer Types: Findings from A Large-Scale Study

My Kingdom for a Biomarker

The efficacy of ICIs in patients with defects in the DNA mismatch repair pathways seemingly provides proof of concept. It culminated in the approvals of pembrolizumab (Keytruda) across solid tumor types that display dMMR or high levels of MSI, as well as nivolumab (Opdivo) as a single agent and in combination with ipilimumab (Yervoy) for the treatment of CRCs that are dMMR or are MSI-high.^8-10MSI and dMMR and are just 2 of the many phenotypes that can cause hypermutant tumors and contribute to high levels of TMB. If tumors with higher TMB provoke a stronger immune response, then it stands to reason that TMB could provide a means for more comprehensive assessment of patients who might respond to ICIs and potentially other immunotherapies. In the past several years, investigators have started to evaluate TMB in this capacity, and it has emerged as a powerful predictor of response to ICIs in a range of tumor types (Table 1).^5,11-27 Investigators are seeking to correlate TMB with clinical and biological outcomes in a number of ongoing clinical trials (Table 2).

In initial studies, WES was used to measure TMB levels in tumor biopsy samples in retrospective or exploratory analyses of clinical trials of ICIs. Results from these studies demonstrated that patients with high TMB experienced improved outcomes following either PD-1 blockade with pembrolizumab or nivolumab monotherapy, a combination of nivolumab and ipilimumab, which inhibits CTLA-4, or CTLA-4 blockade alone with ipilimumab or the investigational drug tremelimumab.^12-16

Results from more recent studies have demonstrated that NGS of a targeted panel of genes, which is faster and less expensive than WES, can be used with comparable efficacy to assess TMB levels.17-20 Results from these studies demonstrated that improved efficacy in patients with higher levels of TMB also applied to atezolizumab (Tecentriq), a PD-L1 inhibitor.²⁸

There are currently 2 FDA-approved comprehensive issuebased NGS panels that can also capture TMB and MSI.^28,29 The first, MSK-IMPACT (integrated mutation profiling of actionable cancer targets), leverages a 468-gene panel that captures all classes of genomic alterations targeted by currently approved drugs or those in clinical investigation. It was developed by Memorial Sloan Kettering (MSK) Cancer Center and is available only for patients treated at MSK or through one of its special initiatives.³⁰

Table 1. Findings From Key TMB Studies^{5, 11-27}

Analytical Validation in a Prospective Trial

The FoundationOne CDx, a commercially available 324-gene panel that Foundation Medicine developed, has been the predominant method used in clinical trials assessing TMB via NGS to date. Although both assays are approved by the FDA, currently only FoundationOne CDx has been prospectively validated in clinical trials for TMB measurement.^16,24,30Results from retrospective studies are able to demonstrate only an association between TMB and response to ICIs. To confirm the predictive power of TMB as a biomarker and provide analytical validation of the NGS assays as a companion diagnostic, prospective clinical trials are needed.

Several have begun, and data from the first were recently published. CheckMate-227 is an ongoing phase III study evaluating the combination of nivolumab and ipilimumab in the frontline setting in patients with advanced non—small cell lung cancer (NSCLC) whose tumors have high TMB (defined as ≥10 mutations per megabase and assessed using FoundationOne CDx).

Patients with PD-L1 expression ≥1% were randomly assigned in a 1:1:1 ratio to receive nivolumab plus ipilimumab, nivolumab plus chemotherapy, or chemotherapy alone. A total of 2877 patients were enrolled at the time of study publication, and 1739 underwent randomization. Among this population, 1004 had valid data for TMB-based efficacy analyses and 444 patients (44.2%) were found to be TMB high.

The combination of nivolumab and ipilimumab significantly improved 1-year progression-free survival (PFS) to 43% compared with 13% for chemotherapy in patients with high TMB (HR, 0.58; P <.001). Median PFS was 7.2 months versus 5.5 months, and the objective response rate (ORR) was 45.3% versus 26.9%. Notably, the benefit of nivolumab plus ipilimumab was shown to be independent of PD-L1 expression and tumor histology.²²

Liquid Biopsy Potential

Based on these findings, the FDA agreed to review a supplemental biologics license application for the combinatorial use of the 2 ICIs in patients with high TMB, according to Bristol-Myers Squibb, which is developing both drugs.Several studies have established the possibility of evaluating TMB in a liquid biopsy, using circulating tumor DNA (ctDNA) isolated from a patient’s blood instead of tumor tissue, which could help to overcome the challenges of obtaining sufficient tumor tissue samples for molecular testing.^15,16,25,26

In a retrospective analysis of Foundation Medicine’s bloodbased TMB assay, 794 plasma samples from the phase III OAK and phase II POPLAR trials of atezolizumab were analyzed to correlate blood TMB levels with atezolizumab clinical activity. There was a correlation between longer PFS and high blood TMB independent of PD-L1 expression levels. Results of analytical validation studies demonstrated that this assay could determine TMB with high precision and accuracy from as little as 1% tumor content in a blood sample.^26,31

This liquid biopsy assay is currently being prospectively evaluated in the ongoing phase II/III B-FAST and phase II B-F1RST clinical trials. B-FAST is an umbrella trial that is evaluating the safety and efficacy of atezolizumab in patients with NSCLC selected on the basis of actionable somatic mutations or high TMB (NCT03178552).

Table 2. Select Studies Exploring TMB as a Biomarker

Expanding the Scope of Immunotherapy

Interim results from the B-F1RST trial, which is evaluating frontline atezolizumab monotherapy in patients with advanced NSCLC, were presented at the 2018 ASCO Annual Meeting. At the time of analysis, 78 patients had been treated, 58 of whom had adequate blood samples for detection of ctDNA. Among the biomarker-evaluable population, 11 patients had high TMB, defined as ≥16 mutations per megabase, and 47 had low TMB. After a median follow-up of 6 months, the median PFS was 9.5 months for patients with high TMB compared with 2.8 months for those with low TMB (HR, 0.49; P = 0.11). The ORR was 36.4% in patients with high TMB and 6.4% in those with low TMB.²⁵Although most TMB studies have focused on the major tumor types in which ICIs have demonstrated significant efficacy— NSCLC, melanoma, and urothelial carcinoma—several recent studies have sought to evaluate the distribution of TMB across a broader spectrum of cancer types (Figure).

A team of investigators at Foundation Medicine recently published an analysis of more than 100,000 cancer genomes, representing 541 distinct cancer types, with the majority of specimens from patients with significantly pretreated, advanced, and metastatic disease. The median TMB was 3.6 mutations per megabase but ranged from 0 to 1241 mutations per megabase, and TMB rose significantly with increased age, although this differed across disease types.

Among samples spanning 167 cancer types, for which more than 50 specimens were tested, the median TMB ranged from 0.8 mutations per megabase to 45.2 mutations per megabase. Pediatric cancers had lower TMB than adult cancers, and cancers known to be related to mutagen exposure, such as lung cancer and melanoma, had higher TMB.

This study helped to identify additional cancer types that demonstrate high TMB, such as skin squamous cell carcinoma and diffuse large B-cell lymphoma, but most important, it demonstrated that a subset of patients with high TMB can be observed in almost every cancer type, even in those with a low TMB overall.

The study identified 20 tumor types affecting 8 tissues in which more than 10% of patients had high TMB and 38 tumor types affecting 19 tissues with greater than 5% of patients with high TMB. It also provided more evidence that WES and targeted NGS assays have comparable efficacy in assessing TMB, as long as more than 0.5 Mb of the coding genome is assayed.⁵

Challenges to Overcome

These findings suggest that clinical implementation of TMB as a predictive biomarker has the potential to greatly expand the scope of ICIs. Enrolling patients in tumor-agnostic trials that select for patients with high TMB across multiple cancer types could help some patients with tumor types that have previously proved unresponsive to immunotherapy as well as patients with rare tumors in which randomized clinical trials are challenging.Despite mounting evidence of the significant promise of TMB as a predictive biomarker, the consensus among immunooncologists is that it is not yet ready for prime time. There are a number of challenges to overcome before TMB assays can be widely adopted in clinical practice.

One limitation of TMB testing is that it is still a surrogate marker of response that tells us only that there is a greater likelihood of response, not that an individual patient probably will respond. There are cases in which tumors with high TMB fail to respond to ICIs.

For TMB testing to be embraced in clinical practice, its definitions— different cutoffs to define high, intermediate, and low TMB have been used in clinical trials—and the analytical validation requirements must be standardized. The use of different TMB assays necessitates consistency across these platforms. There is also the question of how broadly applicable TMB assays will be to other types of immunotherapy, beyond ICIs.

Additionally, some investigators have proposed adaptations to the TMB biomarker that could improve its predictive power. In some cases, the tumor types that have failed to respond to ICIs have a high pretreatment tumor burden, and it is possible that even a robust antitumor immune response may be rendered mute against a high tumor burden.

A team at the Naval Medical University in Shanghai, China, proposed that assessing the ratio of TMB to tumor burden could provide a more effective prediction of the clinical benefit of ICIs, although this has yet to be tested in clinical trials.³²

References

1. Hanahan D, Weinberg RA. The hallmarks of cancer. Cell. 2000;100(1):57-70. doi:https://doi.org/10.1016/S0092-8674(00)81683-9
2. Hanahan D, Weinberg Robert A. Hallmarks of cancer: the next generation. Cell. 2011;144(5):646-674. doi: 10.1016/j.cell.2011.02.013.
3. Lawrence MS, Stojanov P, Polak P, et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature. 2013;499(7457):214-218. doi: 10.1038/nature12213.
4. Vogelstein B, Papadopoulos N, Velculescu VE, Zhou S, Diaz LA, Kinzler KW. Cancer Genome Landscapes. Science. 2013;339(6127):1546-1558. doi: 10.1126/science.1235122.
5. 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. doi: 10.1186/s13073-017-0424-2.
6. Chen L, Flies DB. Molecular mechanisms of T cell co-stimulation and co-inhibition. Nat Rev Immunol. 2013;13(4):227-242. doi: 10.1038/nri3405
7. Gubin MM, Artyomov MN, Mardis ER, Schreiber RD. Tumor neoantigens: building a framework for personalized cancer immunotherapy. J Clin Invest. 2015;125(9):3413-3421. doi: 10.1172/JCI80008.
8. Boyiadzis MM, Kirkwood JM, Marshall JL, Pritchard CC, Azad NS, Gulley JL. Significance and implications of FDA approval of pembrolizumab for biomarker-defined disease. J Immunother Cancer. 2018;6(1):35. doi: 10.1186/s40425-018-0342-x.
9. Smith KM, Desai J. Nivolumab for the treatment of colorectal cancer. Expert Rev Anticancer Ther. 2018;18(7):611-618. doi: 10.1080/14737140.2018.1480942.
10. Overman MJ, Lonardi S, Wong KYM, et al. Durable Clinical Benefit With Nivolumab Plus Ipilimumab in DNA Mismatch Repair-Deficient/Microsatellite Instability-High Metastatic Colorectal Cancer. J Clin Oncol. 2018;36(8):773-779. doi: 10.1200/JCO.2017.76.9901.
11. Nebot-Bral L, Brandao D, Verlingue L, et al. Hypermutated tumours in the era of immunotherapy: The paradigm of personalised medicine. Eur J Cancer. 2017;84:290-303. doi: 10.1016/j.ejca.2017.07.026.
12. Le DT, Uram JN, Wang H, et al. PD-1 Blockade in Tumors with Mismatch-Repair Deficiency. N Engl J Med. 2015;372(26):2509-2520. doi: 10.1056/NEJMoa1500596.
13. Rizvi NA, Hellmann MD, Snyder A, et al. Mutational landscape determines sensitivity to PD-1 blockade in non—small cell lung cancer. Science. 2015;348(6230):124-128. doi: 10.1126/science.aaa1348.
14. Snyder A, Makarov V, Merghoub T, et al. Genetic Basis for Clinical Response to CTLA-4 Blockade in Melanoma. N Engl J Med. 2014;371(23):2189-2199. doi: 10.1056/NEJMoa1406498.
15. 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.e854. doi: 10.1016/j.ccell.2018.03.018
16. 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):843-852.e4. doi: 10.1016/j.ccell.2018.03.018.
17. Campesato LF, Barroso-Sousa R, Jimenez L, et al. Comprehensive cancer-gene panels can be used to estimate mutational load and predict clinical benefit to PD-1 blockade in clinical practice. Oncotarget. 2015;6(33):34221-34227. doi: 10.18632/oncotarget.5950.
18. Johnson DB, Frampton GM, Rioth MJ, et al. Targeted Next Generation Sequencing Identifies Markers of Response to PD-1 Blockade. Cancer Immunol Res. 2016;4(11):959-967. doi: 10.1158/2326-6066.
19. Ramalingam SS, Hellmann MD, Awad MM, et al. Tumor mutational burden (TMB) as a biomarker for clinical benefit from dual immune checkpoint blockade with nivolumab (nivo) + ipilimumab (ipi) in first-line (1L) non-small cell lung cancer (NSCLC): identification of TMB cutoff from CheckMate 568. Presented at: Annual Meeting of the American Association of Cancer Research; April 14-18, 2018; Chicago, IL. Abstract CT078. abstractsonline.com/pp8/#!/4562/presentation/11131.
20. 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. doi: 10.1200/JCO.2017.75.3384.
21. Legrand FA, Gandara DR, Mariathasan S, et al. Association of high tissue TMB and atezolizumab efficacy across multiple tumor types. J Clin Oncol. 2018;36(suppl):abstr 12000. meetinglibrary.asco.org/record/161442/abstract.
22. Hellmann MD, Ciuleanu T-E, Pluzanski A, et al. Nivolumab plus Ipilimumab in Lung Cancer with a High Tumor Mutational Burden. N Engl J Med. 2018;378(22):2093-2104. doi: 10.1056/NEJMoa1801946.
23. Goodman AM, Kato S, Bazhenova L, et al. Tumor Mutational Burden as an Independent Predictor of Response to Immunotherapy in Diverse Cancers. Mol Cancer Ther. 2017;16(11):2598-2608. doi: 10.1158/1535-7163.
24. Rosenberg JE, Hoffman-Censits J, Powles T, et al. Atezolizumab in patients with locally advanced and metastatic urothelial carcinoma who have progressed following treatment with platinum-based chemotherapy: a single-arm, multicentre, phase 2 trial. The Lancet. 2016;387(10031):1909-1920. doi: 10.1016/S0140-6736(16)00561-4.
25. Velchetti V, Kim ES, Mekhail T, et al. Prospective clinical evaluation of blood-based tumor mutational burden (bTMB) as a predictive biomarker for atezolizumab (atezo) in 1L non-small cell lung cancer (NSCLC): Interim B-F1RST results. J Clin Oncol. 2018;36(suppl;abstr12001). meetinglibrary.asco.org/record/161594/abstract.
26. Fabrizio D, Malboeuf C, Lieber D, et al. 102PAnalytic validation of a next generation sequencing assay to identify tumor mutational burden from blood (bTMB) to support investigation of an anti-PD-L1 agent, atezolizumab, in a first line non-small cell lung cancer trial (BFAST). Annals Oncol. 2017;28(suppl_5):mdx363.018-mdx363.018. academic.oup.com/annonc/article/28/suppl_5/mdx363.018/4108401
27. Domingo E, Camps C, Kaisaki PJ, et al. Mutation burden and other molecular markers of prognosis in colorectal cancer treated with curative intent: results from the QUASAR 2 clinical trial and an Australian community-based series. Lancet Gastroenterol Hepatol. 2018;3(9):635-643. doi: 10.1016/S2468-1253(18)30117-1.
28. Frampton GM, Fichtenholtz A, Otto GA, et al. Development and validation of a clinical cancer genomic profiling test based on massively parallel DNA sequencing. Nature Biotechnology. 2013;31:1023. doi: 10.1038/nbt.2696.
29. Zehir A, Benayed R, Shah RH, et al. Mutational landscape of metastatic cancer revealed from prospective clinical sequencing of 10,000 patients. Nat Med. 2017;23(6):703-713. doi: 10.1038/nm.4333.
30. Allegretti M, Fabi A, Buglioni S, et al. Tearing down the walls: FDA approves next generation sequencing (NGS) assays for actionable cancer genomic aberrations. J Exp Clin Cancer Res. 2018;37(1):47. doi: 10.1186/s13046-018-0702-x.
31. Gandara DR, Kowanetz M, Mok TSK, et al. 1295O Blood-based biomarkers for cancer immunotherapy: tumor mutational burden in blood (bTMB) is associated with improved atezolizumab (atezo) efficacy in 2L+ NSCLC (POPLAR and OAK). Annals Oncol. 2017;28(suppl_5):mdx380-mdx380. Abstract 1295O. hacademic.oup.com/annonc/article/28/suppl_5/mdx380/4109443
32. Qin BD, Jiao XD, Zang YS. Tumor mutation burden to tumor burden ratio and prediction of clinical benefit of anti-PD-1/PD-L1 immunotherapy. Med Hypotheses. 2018;116:111-113. doi: 10.1016/j.mehy.2018.05.005.