Dataset Information

Tumor Mutational Burden as a Predictive Biomarker in Solid Tumors.

ABSTRACT: Tumor mutational burden (TMB), defined as the number of somatic mutations per megabase of interrogated genomic sequence, varies across malignancies. Panel sequencing-based estimates of TMB have largely replaced whole-exome sequencing-derived TMB in the clinic. Retrospective evidence suggests that TMB can predict the efficacy of immune checkpoint inhibitors, and data from KEYNOTE-158 led to the recent FDA approval of pembrolizumab for the TMB-high tumor subgroup. Unmet needs include prospective validation of TMB cutoffs in relationship to tumor type and patient outcomes. Furthermore, standardization and harmonization of TMB measurement across test platforms are important to the successful implementation of TMB in clinical practice. SIGNIFICANCE: Evaluation of TMB as a predictive biomarker creates the need to harmonize panel-based TMB estimation and standardize its reporting. TMB can improve the predictive accuracy for immunotherapy outcomes, and has the potential to expand the candidate pool of patients for treatment with immune checkpoint inhibitors.

SUBMITTER: Sha D

PROVIDER: S-EPMC7710563 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Tumor Mutational Burden as a Predictive Biomarker in Solid Tumors.

Sha Dan D Jin Zhaohui Z Budczies Jan J Kluck Klaus K Stenzinger Albrecht A Sinicrope Frank A FA

Cancer discovery 20201102 12

Tumor mutational burden (TMB), defined as the number of somatic mutations per megabase of interrogated genomic sequence, varies across malignancies. Panel sequencing-based estimates of TMB have largely replaced whole-exome sequencing-derived TMB in the clinic. Retrospective evidence suggests that TMB can predict the efficacy of immune checkpoint inhibitors, and data from KEYNOTE-158 led to the recent FDA approval of pembrolizumab for the TMB-high tumor subgroup. Unmet needs include prospective v ...[more]

PMID: 33139244

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Project description:BackgroundTumor mutational burden (TMB) has both prognostic value in resected non-small cell lung cancer (NSCLC) patients and predictive value for immunotherapy response. However, TMB evaluation by whole-exome sequencing (WES) is expensive and time-consuming, hampering its application in clinical practice. In our study, we aimed to construct a mutational burden estimation model, with a small set of genes, that could precisely estimate WES-TMB and, at the same time, has prognostic and predictive value for NSCLC patients.MethodsTMB estimation model was trained based on genomic data from 1056 NSCLC samples from The Cancer Genome Atlas (TCGA). Validation was performed using three independent cohorts, including Rizvi cohort and our own Asian cohorts, including 89 early-stage and n late-stage Asian NSCLC patients, respectively. TCGA data were obtained on September 3, 2018. The two Asian cohort studies were performed from September 1, 2018, to March 5, 2019. Pearson's correlation coefficient was used to assess the performance of estimated TMB with WES-TMB. The Kaplan-Meier survival analysis was applied to evaluate the association of estimated TMB with disease-free survival (DFS), overall survival (OS), and response to anti-programmed death-1 (PD-1) and anti-programmed death-ligand 1 (PD-L1) therapy.ResultsThe estimation model, consisted of only 23 genes, correlated well with WES-TMB both in the training set of TCGA cohort and validation set of Rizvi cohort and our own Asian cohort. Estimated TMB by the 23-gene panel was significantly associated with DFS and OS in patients with early-stage NSCLC and could serve as a predictive biomarker for anti-PD-1 and anti-PD-L1 treatment response.ConclusionsThe 23-gene panel, instead of WES or the currently used panel-based methods, could be used to assess the WES-TMB with a high relevance. This customized targeted sequencing panel could be easily applied into clinical practice to predict the immunotherapy response and prognosis of NSCLC.

Project description:An association between mutational burden and response to immune checkpoint therapy has been documented in several cancer types. The potential for such a mutational burden threshold to predict response to immune checkpoint therapy was evaluated in several clinical datasets, where mutational burden was measured either by whole-exome sequencing (WXS) or using commercially available sequencing panels.WXS and RNA-seq data of 33 solid cancer types from TCGA were analyzed to determine whether a robust immune checkpoint activating mutation (iCAM) burden threshold associated with evidence of immune checkpoint activation exists in these cancers that may serve as a biomarker for response to immune checkpoint blockade therapy.We find that a robust iCAM threshold, associated with signatures of immune checkpoint activation, exists in 8 of 33 solid cancers: melanoma, lung adenocarcinoma, colon adenocarcinoma, endometrial cancer, stomach adenocarcinoma, cervical cancer, ER+HER2- breast cancer, and bladder-urothelial cancer. Tumors with mutational burden higher than the threshold (iCAM+) also had clear histologic evidence of lymphocytic infiltration. In published datasets of melanoma, lung adenocarcinoma and colon cancer, patients with iCAM+ tumors had significantly better response to immune checkpoint therapy compared to those with iCAM- tumors. ROC analysis using TCGA predictions as gold standard showed that iCAM+ tumors are accurately identifiable using clinical sequencing assays, such as FoundationOne or StrandAdvantage. Using the FoundationOne derived threshold, analysis of 113 melanoma tumors, showed that iCAM+ patients have significantly better response to immune checkpoint therapy. iCAM+ and iCAM- tumors have distinct mutation patterns and different immune microenvironments.In 8 solid cancers, a mutational burden threshold exists that may predict response to immune checkpoint blockade. This threshold is identifiable using available clinical sequencing assays.

Project description:ImportanceTumor mutational burden (TMB) is a potential biomarker associated with response to immune checkpoint inhibitor therapies. The prognostic value associated with TMB in the absence of immunotherapy is uncertain.ObjectiveTo assess the prevalence of high TMB (TMB-H) and its association with overall survival (OS) among patients not treated with immunotherapy with the same 10 tumor types from the KEYNOTE-158 study.Design, setting, and participantsThis retrospective cohort study evaluated the prognostic value of TMB-H, assessed by Foundation Medicine (FMI) and defined as at least 10 mutations/megabase (mut/Mb) in the absence of immunotherapy. Data were sourced from the deidentified Flatiron Health-FMI clinicogenomic database collected up to July 31, 2018. Eligible patients were aged 18 years or older with any of the following solid cancer types: anal, biliary, endometrial, cervical, vulvar, small cell lung, thyroid, salivary gland, mesothelioma, or neuroendocrine tumor. Patients with microsatellite instability-high tumors were excluded from primary analysis. For OS analysis, patients were excluded if immunotherapy started on the FMI report date or earlier or if patients died before January 1, 2012, and patients were censored if immunotherapy was started later than the FMI report date. Data were analyzed from November 2018 to February 2019.Main outcomes and measuresOverall survival was analyzed using the Kaplan-Meier method and Cox proportional hazards model, adjusting for age, sex, cancer types, practice type, and albumin level.ResultsOf 2589 eligible patients, 1671 (64.5%) were women, and the mean (SD) age was 63.7 (11.7) years. Median (interquartile range) TMB was 2.6 (1.7-6.1) mut/Mb, and 332 patients (12.8%) had TMB-H (≥10 mut/Mb). Prevalence of TMB-H was highest among patients with small cell lung cancer (40.0%; 95% CI, 34.7%-45.6%) and neuroendocrine tumor (29.3%; 95% CI, 22.8%-36.6%) and lowest was among patients with mesothelioma (1.2%; 95% CI, 0.3%-4.4%) and thyroid cancer (2.7%; 95% CI, 1.2%-5.7%). Adjusted hazard ratio for OS of patients not treated with immunotherapy with TMB-H vs those without TMB-H was 0.94 (95% CI, 0.77-1.13). Comparable results were observed when including patients with high microsatellite instability tumors and calculating OS from first observed antineoplastic treatment date.Conclusions and relevanceThese findings suggest that prevalence of TMB-H varies widely depending on tumor type and TMB-H does not appear to be a factor associated with OS among patients across these cancer types treated in the absence of immunotherapy.

Project description:BackgroundSeveral studies have evaluated the relationship between tumor mutational burden (TMB) and outcomes of immune checkpoint inhibitors. In the phase II KEYNOTE-158 study of pembrolizumab monotherapy for previously treated recurrent or metastatic cancer, high TMB as assessed by the FoundationOne CDx was associated with an improved objective response rate (ORR).MethodsWe retrospectively assessed the relationship between TMB and efficacy in participants with previously treated advanced solid tumors enrolled in 12 trials that evaluated pembrolizumab monotherapy, including 3 randomized trials that compared pembrolizumab with chemotherapy. TMB was assessed in formalin-fixed, paraffin-embedded pretreatment tumor samples by whole-exome sequencing. High TMB was defined as ≥175 mutations/exome. Microsatellite instability (MSI) phenotype was based on whole-exome sequencing results. Programmed death ligand 1 (PD-L1) expression was assessed by immunohistochemistry. The primary end point was ORR assessed per RECIST V.1.1 by independent central review. Other end points included progression-free survival (PFS) assessed per RECIST V.1.1 by independent central review and overall survival (OS).ResultsOf the 2234 participants in the analysis, 1772 received pembrolizumab monotherapy and 462 received chemotherapy. Among the pembrolizumab-treated participants, ORR was 31.4% (95% CI 27.1 to 36.0) in the 433 participants with TMB ≥175 mutations/exome and 9.5% (95% CI 8.0 to 11.2) in the 1339 participants with TMB <175 mutations/exome. The association of TMB with ORR was observed regardless of PD-L1 expression and not driven by specific tumor types or participants with very high TMB or high MSI. In the 3 randomized controlled trials, TMB was associated with ORR (p≤0.016), PFS (p≤0.005), and OS (p≤0.029) of pembrolizumab but not of chemotherapy (p≥0.340, p≥0.643, and p≥0.174, respectively), and pembrolizumab improved efficacy versus chemotherapy in participants with TMB ≥175 mutations/exome.ConclusionsTMB ≥175 mutations/exome is associated with clinically meaningful improvement in the efficacy of pembrolizumab monotherapy and improved outcomes for pembrolizumab versus chemotherapy across a wide range of previously treated advanced solid tumor types. These data suggest TMB has broad clinical utility irrespective of tumor type, PD-L1 expression, or MSI status and support its use as a predictive biomarker for pembrolizumab monotherapy in participants with previously treated advanced solid tumors.

Project description:Treatment with immune checkpoint inhibitors (ICPIs) extends survival in a proportion of patients across multiple cancers. Tumor mutational burden (TMB)-the number of somatic mutations per DNA megabase (Mb)-has emerged as a proxy for neoantigen burden that is an independent biomarker associated with ICPI outcomes. Based on findings from recent studies, TMB can be reliably estimated using validated algorithms from next-generation sequencing assays that interrogate a sufficiently large subset of the exome as an alternative to whole-exome sequencing. Biological processes contributing to elevated TMB can result from exposure to cigarette smoke and ultraviolet radiation, from deleterious mutations in mismatch repair leading to microsatellite instability, or from mutations in the DNA repair machinery. A variety of clinical studies have shown that patients with higher TMB experience longer survival and greater response rates following treatment with ICPIs compared with those who have lower TMB levels; this includes a prospective randomized clinical trial that found a TMB threshold of ≥10 mutations per Mb to be predictive of longer progression-free survival in patients with non-small cell lung cancer. Multiple trials are underway to validate the predictive values of TMB across cancer types and in patients treated with other immunotherapies. Here we review the rationale, algorithm development methodology, and existing clinical data supporting the use of TMB as a predictive biomarker for treatment with ICPIs. We discuss emerging roles for TMB and its potential future value for stratifying patients according to their likelihood of ICPI treatment response. IMPLICATIONS FOR PRACTICE: Tumor mutational burden (TMB) is a newly established independent predictor of immune checkpoint inhibitor (ICPI) treatment outcome across multiple tumor types. Certain next-generation sequencing-based techniques allow TMB to be reliably estimated from a subset of the exome without the use of whole-exome sequencing, thus facilitating the adoption of TMB assessment in community oncology settings. Analyses of multiple clinical trials across several cancer types have demonstrated that TMB stratifies patients who are receiving ICPIs by response rate and survival. TMB, alongside other genomic biomarkers, may provide complementary information in selecting patients for ICPI-based therapies.

Dataset Information

Tumor Mutational Burden as a Predictive Biomarker in Solid Tumors.

Publications

Tumor Mutational Burden as a Predictive Biomarker in Solid Tumors.

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