Tumor Mutational Burden Measurement Research Articles

Tumor purity as confounder for the determination of tumor mutational burden (TMB).

e14656 Background: TMB determination is a prerequisite to stratify advanced cancer patients for pembrolizumab based on the histology-agnostic FDA approval. The accuracy of TMB measurement is challenged by low tumor purity resulting in a lower number of detected somatic variants for a fixed threshold of variant allele frequency (VAF) and a lower measured TMB level as a consequence. Methods: We derived a mathematical formula describing the influence of tumor purity on the VAF of somatic variants, in which the DNA copy number of the corresponding region of the tumor genome is a parameter. We simulated the effect of tumor purity in a cohort of 4,900 tumors from the TCGA project with tumor purity of at least 80%. TMB was calculated as the number of missense mutations with VAF greater or equal than 5%. Tumors were classified as TMB-high when harboring at least 199 missense mutations. This cutpoint corresponds to 10 mut/Mb as derived in the TMB bridging study. We compared tumors with a simulated tumor purity of 70%, 60%, ..., and 10% with tumors with a tumor purity of 80%, which served as reference. Results: The median of TMB in the pan-cancer cohort was reduced by 2%, 10%, and 32% for tumor purity of 60%, 40%, and 20% compared to the reference of 80%. For the 10% tumors with the worst estimation, TMB was reduced even by 12%, 35%, and 77% or more, respectively. In the pan-cancer cohort, the sensitivity to detect high TMB was 98%, 90%, and 62% for tumor purity of 60%, 40%, and 20%, respectively. For head and neck cancer, lung adenocarcinoma, lung squamous cell carcinoma, and cutaneous melanoma, the sensitivity to detect high TMB was 80%, 89%, 92%, and 91%, respectively, for tumors of tumor purity 40%. Conclusions: High tumor purity is critical for accurate determination of the TMB and to reach a high sensitivity concerning the selection of patients for immunotherapy. As shown by the simulations, the sensitivity to detect high TMB is close to 100% for tumor purity of at least 60%, while a substantial proportion of patients that could receive immunotherapy is missed for tumors with purity of 40% or less. Potential ways out of the TMB underestimation include increasing the sequencing coverage and lowering the VAF threshold for mutation calling or using clonal TMB with an adapted cutpoint instead of total TMB as biomarker for immunotherapy guidance.

TTN Mutation in Endometrial Endometrioid Carcinoma Is Associated with Poor Clinical Outcomes and High Tumor Mutation Burden

Endometrioid endometrial carcinoma (EEC) stands as a prevalent gynecologic malignancy in developed regions. However, predicting relapse cases remains challenging, necessitating the identification of a novel biomarker for EEC relapse. The assessment of tumor mutational burden (TMB) is pivotal for immunotherapy in EEC patients. However, both whole-exome sequencing (WES) and targeted sequencing encountered application-related difficulties. In light of this, standardized and simplified techniques for TMB measurement are imperative. In this study, we employed WES on 25 EEC patients (12 relapsed cases and 13 non-relapsed cases) who accepted hysterectomy surgery (CHCAMS cohort). We additionally obtained a total of 391 tumor samples with clinicopathological features from TCGA website to broaden the study cohort. In the CHCAMS cohort, the TTN mutant group showed shorter progression-free survival (p < 0.001) and overall survival (p < 0.001) than TTN wild-type group. Additionally, we discovered that the number of TTN mutations per sample was significantly linked with TMB-WES in CHCAMS cohort and TCGA cohort (p < 0.05). And the number of TTN mutations per sample in POLE mutant group was greater than in the POLE wild-type group (p < 0.0001). In conclusion, TTN mutation may serve as a biomarker for EEC prognosis. TTN mutation is also associated with WES-TMB, and could be a simplified TMB measurement technique.

Analytical validation and clinical utilization of K-4CARE™: a comprehensive genomic profiling assay with personalized MRD detection.

Background: Biomarker testing has gradually become standard of care in precision oncology to help physicians select optimal treatment for patients. Compared to single-gene or small gene panel testing, comprehensive genomic profiling (CGP) has emerged as a more time- and tissue-efficient method. This study demonstrated in-depth analytical validation of K-4CARE, a CGP assay that integrates circulating tumor DNA (ctDNA) tracking for residual cancer surveillance. Methods: The assay utilized a panel of 473 cancer-relevant genes with a total length of 1.7Mb. Reference standards were used to evaluate limit of detection (LOD), concordance, sensitivity, specificity and precision of the assay to detect single nucleotide variants (SNVs), small insertion/deletions (Indels), gene amplification and fusion, microsatellite instability (MSI) and tumor mutational burden (TMB). The assay was then benchmarked against orthogonal methods using 155 clinical samples from 10 cancer types. In selected cancers, top tumor-derived somatic mutations, as ranked by our proprietary algorithm, were used to detect ctDNA in the plasma. Results: For detection of somatic SNVs and Indels, gene fusion and amplification, the assay had sensitivity of >99%, 94% and >99% respectively, and specificity of >99%. Detection of germline variants also achieved sensitivity and specificity of >99%. For TMB measurement, the correlation coefficient between whole-exome sequencing and our targeted panel was 97%. MSI analysis when benchmarked against polymerase chain reaction method showed sensitivity of 94% and specificity of >99%. The concordance between our assay and the TruSight Oncology 500 assay for detection of somatic variants, TMB and MSI measurement was 100%, 89%, and 98% respectively. When CGP-informed mutations were used to personalize ctDNA tracking, the detection rate of ctDNA in liquid biopsy was 79%, and clinical utility in cancer surveillance was demonstrated in 2 case studies. Conclusion: K-4CARE™ assay provides comprehensive and reliable genomic information that fulfills all guideline-based biomarker testing for both targeted therapy and immunotherapy. Integration of ctDNA tracking helps clinicians to further monitor treatment response and ultimately provide well-rounded care to cancer patients.

Tumor mutational burden (TMB) measurement from an FDA-approved assay and real-world overall survival (rwOS) on single-agent immune checkpoint inhibitors (ICI) in over 8,000 patients across 24 cancer types.

2503 Background: There is controversy around the applicability of TMB across cancer types and reliability between assays from different manufacturers. The KEYNOTE 158 trial supported FDA approval of the Foundation Medicine test (FoundationOne CDx) at TMB ≥ 10 mut/Mb as a solid tumor companion diagnostic (CDx) for single-agent pembrolizumab in 2nd+ line. Using a large real-world dataset with validated rwOS endpoint data, we evaluated the clinical validity of the TMB measurement by the FDA approved test in over 8,000 patients across 24 cancer types who received single agent ICI. Methods: Following a prespecified analysis plan, this study used the nationwide (US-based) de-identified Flatiron Health-Foundation Medicine clinico-genomic database (FH-FMI CGDB), with data originating from approximately 280 US cancer clinics (~800 sites of care). The overall cohort included patients from 24 cancer types of interest with adv/metastatic disease treated with single-agent anti-PD(L)1 therapy in the FH network between 1/1/2011 - 9/30/2022. This study used the TMB algorithm from the FDA-approved test supporting solid tumor CDx and composite mortality variable validated against the national death index. Relative hazards of death by TMB interval were assessed using Cox PH models adjusted for ECOG PS, prior treatment, sex, age, opioid rx pre-therapy, genetic ancestry, and socioeconomic assessment. Multi-solid tumor cohort Cox models were additionally adjusted for MSI status, with baseline hazards stratified by cancer type. Results: 8,440 patients from 24 cancer types met inclusion criteria for the overall cohort. Adjusting for aforementioned factors, the hazards of death {HR, (95% CI)} across the entire cohort, relative to TMB &lt; 5, was 0.95 (0.89 – 1.02) for TMB 5-10, 0.79 (0.73 – 0.85) for TMB 10-20, and 0.52 (0.47 – 0.58) for TMB 20+. Adjusted Cox models comparing TMB ≥ 10 vs. TMB &lt; 10 were pre-specified for cancer types with at least 15 death events in each group: breast 0.51 (0.35 - 0.76), colorectal 0.37 (0.27 - 0.49), cancers of unknown primary 0.52 (0.30 - 0.90), endometrial 0.38 (0.26 - 0.55), gastric 0.46 (0.34 - 0.62), head &amp; neck 0.49 (0.33 - 0.73), melanoma 0.55 (0.43 - 0.71), non-small cell lung 0.76 (0.71 - 0.83), small cell lung 0.69 (0.44 - 1.09), and urothelial 0.63 (0.53 – 0.75). Additional individual tumor types, stratification by MSI status, and time to next treatment associations to be presented at conference. Conclusions: Across a heterogeneous cohort, and within individual cancer types with sufficient power, elevated TMB using the TMB measurement based on the FDA-approved test associated with more favorable rwOS on ICI than for similar patients with lower TMB levels. Completed and ongoing randomized controlled trials are encouraged to report out subgroup analyses comparing ICI vs. comparator arm by TMB level.

Distributional range of tumor mutational burden (TMB) across multiple cancer types emphasizing the importance of different cutoff values in different tumor types for clinical interpretation: A consensus statement from the SEQUOIA consortium.

2615 Background: The measurement of tumor mutational burden (TMB) is critical to select patients who are expected to respond to immune checkpoint inhibitors or immune-oncology (IO). The majority of the clinical guidelines on the interpretation &amp; utility of TMB values are based on studies performed on lung cancer, setting a cutoff of 10. Laboratories that are using comprehensive genomic profiling (CGP) for tumor testing are reporting TMB values &amp;/or interpretations (high/low) beyond lung cancer. Multiple studies have shown that the TMB signature is not universal, but rather tumor &amp;/or even patient-specific. However, the pan-cancer trial for IO (KEYNOTE-158) failed to consider setting different cutoffs per tumor type. Currently, no major guidelines or consensus statements address the issue of reporting TMB as a biomarker beyond lung cancer. In the current study, the membership of the SEQUOIA (Sequencing &amp; Oncology Informatics Academic Team) Consortium investigates the landscape of TMB values across multiple cancer types. Methods: We investigated TMB values in 11,670 patient samples (M = 6225; F= 5445) across 13 different tumor types &amp; histological subtypes, including cancers with lung, colorectal, gastrointestinal, brain, prostate, pancreatic, biliary, endometrioid, ovarian, skin, hematological (CLL myeloma) &amp; lymphoid origin. All samples were processed by a CGP panel of 523 genes. Multiple specimen types were included in the study consisting of tissue, blood, marrow, &amp; lymph node. Results: The range of TMB values varied significantly across different cancer types &amp; histological subtypes. The colorectal, melanoma &amp; endometrial cancers have a wider range of TMB values (2-400 mutations/MB) relative to prostate, breast, myeloma, &amp; serous cancers (0-30 mutations/MB). Along with the range, the mean, &amp; median TMB values are also significantly varied across these tumor types. We also identified that a subset of patients exhibits high TMB (&gt;30 mutations/MB) values across almost all types of cancer. Conclusions: TMB values &amp; their association with response to immune checkpoint inhibitors are not very well studied in all cancer types, although a TMB cut-off of 10 mutations/MB was defined as TMB-high for FDA-approved IO in patients with unresectable or metastatic solid tumors. The range, mean, median, cut-offs &amp; clinical interpretations of TMB-high &amp; low for IO based therapies for different tumor types has not been well established. Our data confirm the wide range, mean, &amp; median across different tumor types, &amp; thus laboratories &amp; oncologists need to be cautious in the clinical interpretation of TMB values for patient management. Future studies should assess responsiveness to IO in specific tumor types based on TMB value to determine tumor-specific TMB cutoff values.

Development and validation of blood tumor mutational burden reference standards.

Tumor mutational burden (TMB), measured by exome or panel sequencing of tumor tissue or blood (bTMB), is a potential predictive biomarker for treatment benefit in patients with various cancer types receiving immunotherapy targeting checkpoint pathways. However, significant variability in TMB measurement has been observed. We developed contrived bTMB reference materials using DNA from tumor cell lines and donor-matched lymphoblastoid cell lines to support calibration and alignment across laboratories and platforms. Contrived bTMB reference materials were developed using genomic DNA from lung tumor cell lines blended into donor-matched lymphoblastoid cell lines at 0.5% and 2% tumor content, fragmented and size-selected to mirror the size profile of circulating cell-free tumor DNA with TMB scores of 7, 9, 20, and 26 mut/Mb. Variant allele frequency (VAF) and bTMB scores were assessed using PredicineATLAS and GuardantOMNI next-generation sequencing assays. DNA fragment sizes in the contrived reference samples were similar to those found within patient plasma-derived cell-free DNA, and mutational patterns aligned with those in the parental tumor lines. For the 7, 20, and 26 mut/Mb contrived reference samples with 2% tumor content, bTMB scores estimated using either assay aligned with expected scores from the parental tumor cell lines and showed good reproducibility. A bioinformatic filtration step was required to account for low-VAF artifact variants. We demonstrate the feasibility and challenges of producing and using bTMB reference standards across a range of bTMB levels, and how such standards could support the calibration and validation of bTMB platforms and help harmonization between panels and laboratories.

Abstract 5757: Germline and somatic mutational landscape of Chinese early-onset colorectal cancers

Abstract Background: The incidence of colorectal cancer (CRC) in young people, described as early-onset colorectal cancer (EOCRC) has been rising up in decades. Apart from definite familial genetic disease, a considerable proportion of EOCRC remained unknown of the mechanism. Characterizing the difference in genomic features of EOCRC and late-onset CRC (LOCRC) would help us to understand it. Methods: A total of 1777 Chinese CRC patients diagnosed in 2019-2020 were included. 489 patients under 50 years were defined as EOCRC. A 733-gene panel next-generation sequencing (NGS) testing and measurement of tumor mutational burden (TMB) levels based on the panel were conducted in all patients’ tumor specimen. Lynch syndrome (LS) was defined as patients harboring at least one non-benign germline mutation in four LS MMR genes (MLH1, MSH2, MSH6, PMS2). Results: 43 of 489(8.8%) cases and 54 of 1288 (4.2%) cases were MSI-H in EOCRC and LOCRC, separately. Excluded 97 LS patients (84.3% in MSI-H EOCRC and 72.0% in MSI-H LOCRC), the proportion of non-LS MSI-H in EOCRC and in LOCRC were 1.8% and 1.7%, separately. Compared to non-LS MSI-H LOCRC, EOCRC has higher germline mutational frequencies in APC, CD74, ATM, BCL2L11, CHEK2, and RECQL4 genes and somatic mutational frequencies in APC, ERCC4, CHD2, ARHGAP5, CASP8, and ATM genes. In non-LS MSS patients, germline mutations in CHEK2, NBN and POLE genes, somatic SNV/indels in RNF43, ATR, AFF3, JAK2, POLG, CHD2 genes and somatic copy number gain in genes on chromosome 8 (ZNF703, FGFR1, MYC, PTK2) occurred more frequently in EOCRC. KEGG enrichment analysis in somatic mutations indicated significant overexpressed MAPK signaling pathway. The TMB level was significantly lower in non-LS MSS EOCRC than in LOCRC. Conclusions: The proportion of non-LS MSI-H in Chinese EOCRC and LOCRC were approximate. Non-LS MSS EOCRC had marked chromosome 8 somatic copy number gain and MAPK signaling pathway, indicating the potential mechanism. The comparative lower TMB level in EOCRC was concordance with previous studies and the correlations between low TMB level and high CNV burden also corroborate the etiopathogenesis. Citation Format: Xiancheng Zeng, Junhao Liu, Yurong Luo, Hailiang Li, Xinyi Liu, Mengli Huang. Germline and somatic mutational landscape of Chinese early-onset colorectal cancers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5757.

Tumor mutational burden measurement using comprehensive genomic profiling assay.

Tumors with a high number of mutations in the genome, or tumor mutational burden, are presumed to be more likely to respond to immune checkpoint inhibitors. However, the optimal method to calculate tumor mutational burden using comprehensive genomic profiling assays is unknown. Todai OncoPanel is a dual panel of a deoxyribonucleic acid panel and a ribonucleic acid panel. Todai OncoPanel deoxyribonucleic acid panel version 6 is an improvement over version 3 with increased number of targeted genes and limited targeting of intronic regions. We calculated tumor mutational burden measured by Todai OncoPanel deoxyribonucleic acid panel versions 3 and 6 using three different calculation methods: all mutations within the targeted region (target tumor mutational burden), all mutations within the coding region (all coding tumor mutational burden) and non-synonymous mutations (non-synonymous coding tumor mutational burden). We then compared them with whole exosome sequencing tumor mutational burden. In addition, 16 lung cancer patients whose samples were analyzed using Todai OncoPanel deoxyribonucleic acid version 3 were treated with anti-PD-1 or PD-L1 antibody monotherapy. When compared with whole exosome sequencing tumor mutational burden as the standard, tumor mutational burden measured by Todai OncoPanel deoxyribonucleic acid version 3 resulted in accuracy of 71% for all three calculation methods. In version 6, accuracy was 96% for target tumor mutational burden and all coding tumor mutational burden and 91% for non-synonymous coding tumor mutational burden. Patients with either partial response or stable disease had higher non-synonymous coding tumor mutational burden (6.7/Mb vs. 1.6/Mb, P=0.02) and higher PD-L1 expression (40% vs. 3%, P=0.01) and a trend toward higher target tumor mutational burden (9.2/Mb vs. 2.4/Mb, P=0.09) compared with patients with progressive disease. Increase in targeted gene number and limiting intronic regions improved tumor mutational burden measurement by Todai OncoPanel when compared with whole exosome sequencing tumor mutational burden. Target tumor mutational burden may be the method of choice to measure tumor mutational burden.

Visualization of the Effect of Assay Size on the Error Profile of Tumor Mutational Burden Measurement.

Tumor mutational burden (TMB) refers to the number of somatic mutations in a tumor per megabase and is a biomarker for response to immune checkpoint inhibitor therapy. Immune checkpoint inhibitors are currently approved for tumors with TMB greater than or equal to 10 mutations/megabase. Many laboratories are currently reporting TMB values based upon targeted resequencing panels with limited genomic coverage. Due to sampling variation, this leads to significant uncertainty in the assay’s TMB result, particularly at relatively low TMB levels near the 10 mutation per megabase therapeutic threshold. In order to allow clinicians and laboratorians to explore this uncertainty, we built a novel web application that allows a user to view the potential error of a TMB result given the sequencing panel size. This application also allows the user to explore the effect of incorporating knowledge of a specific tumor type’s typical TMB distribution on the error profile of the TMB result.

Evaluation of the TruSight Oncology 500 Assay for Routine Clinical Testing of Tumor Mutational Burden and Clinical Utility for Predicting Response to Pembrolizumab

Pembrolizumab is approved for treating patients with unresectable or metastatic solid tumors with high tumor mutational burden (TMB), as assessed by the Food and Drug Administration-approved companion diagnostic FoundationOneCDx, after progression on prior treatment. To expand TMB assessment for enriching response to pembrolizumab, TMB measurement from TruSight Oncology 500 (TSO500) was evaluated in archival pan-tumor samples from 294 patients enrolled in eight pembrolizumab monotherapy studies. TSO500 is a panel-based next-generation sequencing assay with broad availability, quick turnaround time, and a standardized bioinformatics pipeline. TSO500 TMB was evaluated for correlation and concordance with two reference methods: FoundationOneCDx and whole-exome sequencing. The TSO500 cut-off for TMB-high was selected based on the receiver-operating characteristic curve analysis against each reference method's cut-off for TMB-high. Clinical utility of the selected TSO500 cut-off (10 mutations/Mb) was assessed by calculating the sensitivity, specificity, positive and negative predictive values, and objective response rate enrichment. There was high correlation and concordance of TSO500 TMB with both reference methods. TSO500 TMB was associated significantly with the best overall response, and the selected cut-off had comparable clinical utility with respective cut-offs for the reference methods in predicting response to pembrolizumab. As a commercial assay with global kit distribution complete with an off-the-shelf software package, TSO500 may provide additional access to immunotherapy for patients with tumors with TMB ≥10 mutations/Mb.

Abstract P2-08-15: Clinical, pathologic, and molecular associations of tumor mutational burden in metastatic breast cancer

Abstract Background: Tumor mutational burden (TMB) is a biomarker approved to predict response to immune checkpoint blockade (ICB) in solid tumors irrespective of their tissue of origin. However, there are limited data in patients with breast cancer and high TMB to support the use of ICB. The goal of this analysis is to describe clinical, pathological and molecular associations with TMB within a cohort of patients with metastatic breast cancer. Methods: We included patients enrolled onto an ongoing prospective study titled Individualized Molecular Analyses Guide Efforts (IMAGE)-II. Patients eligible for IMAGE-II have metastatic breast cancer of any subtype that had progressed on at least one standard-of-care therapy. Genetic profiling of tumor tissue was performed at the discretion of the treating team using one of several commercially available next generation sequencing platforms. For purposes of this analysis, only patients who underwent tissue-based Foundation Medicine analysis are included as TMB assessments are different across different platforms. Data are summarized by descriptive statistics. Linear and logistic regression analyses are conducted to evaluate the association between TMB and other clinical, pathological and molecular factors. We will present data on associations with specific mutations (i.e. ESR1, ERBB2, DNA repair, Pi3K signaling, TP53) and ctDNA TMB at a later time. Results:Of 117 patients in the IMAGE-II database, median age was 57 (range 23-86), 65% were White, 29% Black, and 6% Other. TMB data were available on 62 patients. Of those with both TMB and subtype information, 35 (70%) had ER+HER2- tumors, and 15 (30%) had ER-HER2- tumors. Median TMB was 4 mutations/megabase and ranged from 0 to 27. We did not observe significant differences in TMB in patients with ER+HER2- and those with ER-HER2- tumors (median TMB of 4 [0-27] and 5 [1-25], respectively), nor between White versus Black patients (median TMB of 4 [0-27] and 5 [0-12], respectively). However, we did observe that age was positively associated with higher TMB (p-value = 0.02). Additionally, we observed that the time between metastatic diagnosis and TMB measurement was positively associated with TMB (p-value &amp;lt; 0.01); this significant association was also observed in ER+HER2- patients (p-value &amp;lt; 0.01) but not in ER-HER2- patients. Median time to obtaining TMB since metastatic diagnosis was 1.1 (range -0.8 - 12.8) years. More lines of chemotherapy prior to TMB assessment was not observed to be associated with higher TMB. Conclusions: We observed that TMB was higher in patients who have had a longer disease course. Further research is required to understand changes in TMB over time, and how TMB is correlated with. other genomic and tumor microenvironment characteristics. A deeper understanding of TMB may help refine it as a predictive biomarker for ICB. Citation Format: Mohamed A Mohamed, Chenghuang Wang, Morgan Buckley, Jennifer Lehman, Jenna Canzoniero, Christopher D Gocke, Raquel Nunes, Ben Ho Park, Karen L Smith, Jessica Tao, Hanna Tukachinsky, Mary Wilkinson, Antonio C Wolff, Vered Stearns, Cesar A Santa-Maria. Clinical, pathologic, and molecular associations of tumor mutational burden in metastatic breast cancer [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr P2-08-15.

Plasma Cell-Free DNA Genotyping: From an Emerging Concept to a Standard-of-Care Tool in Metastatic Non-Small Cell Lung Cancer.

Plasma cell‐free DNA (cfDNA) genotyping is an alternative to tissue genotyping, particularly when tissue specimens are insufficient or unavailable, and provides critical information that can be used to guide treatment decisions in managing patients with non‐small cell lung cancer (NSCLC). In this article, we review the evolution of plasma cfDNA genotyping from an emerging concept, through development of analytical methods, to its clinical applications as a standard‐of‐care tool in NSCLC.The number of driver or resistance mutations recommended for testing in NSCLC continues to increase. Because of the expanding list of therapeutically relevant variants, comprehensive testing to investigate larger regions of multiple genes in a single run is often preferable and saves on time and cost, compared with performing serial single‐gene assays. Recent advances in nucleic acid next‐generation sequencing have led to a rapid expansion in cfDNA genotyping technologies. Analytic assays that have received regulatory approval are now routinely used as diagnostic companions in the setting of metastatic NSCLC. As the demand for plasma‐based technologies increases, more regulatory approvals of cfDNA genotyping assays are expected in the future.Plasma cfDNA genotyping is currently aiding oncologists in the delivery of personalized care by facilitating matching of patients with targeted therapy and monitoring emergence of resistance to therapy in NSCLC. Further advances currently underway to increase assay sensitivity and specificity will potentially expand the use of plasma cfDNA genotyping in early cancer detection, monitoring response to therapy, detection of minimal residual disease, and measurement of tumor mutational burden in NSCLC.Implications for PracticePlasma cell‐free DNA (cfDNA) genotyping offers an alternative to tissue genotyping, particularly when tissue specimens are insufficient or unavailable. Advances in cfDNA genotyping technologies have led to analytic assays that are now routinely used to aid oncologists in the delivery of personalized care by facilitating matching of patients with targeted therapy and monitoring emergence of resistance to therapy. Further advances underway to increase assay sensitivity and specificity will potentially expand the use of plasma cfDNA genotyping in early cancer detection, monitoring response to therapy, detection of minimal residual disease, and evaluation of tumor mutational burden in non‐small cell lung cancer.

Influence of low tumor content on tumor mutational burden estimation by whole-exome sequencing and targeted panel sequencing.

BackgroundTumor mutational burden (TMB) is a promising biomarker for stratifying patient subpopulation who would benefit from immune checkpoint blockade (ICB) therapies. Although great efforts have been made for standardizing TMB measurement, mutation calling and TMB quantification can be challenging in samples with low tumor content including liquid biopsies. The effect of varying tumor content on TMB estimation by different assay methods has never been systematically investigated.MethodWe established a series of reference standard DNA samples derived from 11 pairs of tumor–normal matched human cell lines across different cancer types. Each tumor cell line was mixed with its matched normal at 0% (control), 1%, 2%, 5%, and 10% mass‐to‐mass ratio to mimic the clinical samples with low tumor content. TMB of these reference standards was evaluated by both ∼1000× whole‐exome sequencing (wesTMB) and targeted panel sequencing (psTMB) at four different vendors. Both regression and classification analyses of TMB were performed for theoretical investigation and clinical practice purposes.ResultsLinear regression model was established that demonstrated in silico psTMB determined by regions of interest (ROI) as a great representative of wesTMB based on TCGA dataset. It was also true in our reference standard samples as the predicted psTMB interval based on the observed wesTMB captured the intended 90% of the in silico psTMB values. Although ∼1000× deep WES was applied, reference standard samples with less than 5% of tumor proportions are below the assay limit of detection (LoD) of wesTMB quantification. However, predicted wesTMB based on observed psTMB accurately classify (>0.97 AUC) for TMB high and low patient stratification even in samples with 2% of tumor content, which is more clinically relevant, as TMB determination should be a qualitative assay for TMB high and low patient classification. One targeted panel sequencing vendor using an optimized blood psTMB pipeline can further classify TMB status accurately (>0.82 AUC) in samples with only 1% of tumor content.ConclusionsWe developed a linear model to establish the quantitative correlation between wesTMB and psTMB. A set of DNA reference standards was produced in aid to standardize TMB measurements in samples with low tumor content across different targeted sequencing panels. This study is a significant contribution aiming to harmonize TMB estimation and extend its future application in clinical samples with low tumor content including liquid biopsy.

A Blood-based Assay for Assessment of Tumor Mutational Burden in First-line Metastatic NSCLC Treatment: Results from the MYSTIC Study.

Tumor mutational burden (TMB) has been shown to be predictive of survival benefit in patients with non-small cell lung cancer (NSCLC) treated with immune checkpoint inhibitors. Measuring TMB in the blood (bTMB) using circulating cell-free tumor DNA (ctDNA) offers practical advantages compared with TMB measurement in tissue (tTMB); however, there is a need for validated assays and identification of optimal cutoffs. We describe the analytic validation of a new bTMB algorithm and its clinical utility using data from the phase III MYSTIC trial. The dataset used for the clinical validation was from MYSTIC, which evaluated first-line durvalumab (anti-PD-L1 antibody) ± tremelimumab (anticytotoxic T-lymphocyte-associated antigen-4 antibody) or chemotherapy for metastatic NSCLC. bTMB and tTMB were evaluated using the GuardantOMNI and FoundationOne CDx assays, respectively. A Cox proportional hazards model and minimal P value cross-validation approach were used to identify the optimal bTMB cutoff. In MYSTIC, somatic mutations could be detected in ctDNA extracted from plasma samples in a majority of patients, allowing subsequent calculation of bTMB. The success rate for obtaining valid TMB scores was higher for bTMB (809/1,001; 81%) than for tTMB (460/735; 63%). Minimal P value cross-validation analysis confirmed the selection of bTMB ≥20 mutations per megabase (mut/Mb) as the optimal cutoff for clinical benefit with durvalumab + tremelimumab. Our study demonstrates the feasibility, accuracy, and reproducibility of the GuardantOMNI ctDNA platform for quantifying bTMB from plasma samples. Using the new bTMB algorithm and an optimal bTMB cutoff of ≥20 mut/Mb, high bTMB was predictive of clinical benefit with durvalumab + tremelimumab versus chemotherapy.

Tumor Mutational Burden as a Predictive Biomarker in Solid Tumors.

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.

Abstract 2008: Pan-cancer profiling of the effect of biopsied site on tumor mutational burden measurements in a real-world data cohort

Abstract Background: Tumor mutational burden (TMB) has been associated with efficacy of immune checkpoint therapy and is being investigated as a potential biomarker in several tumor types. The foundational studies evaluating TMB in clinical trials have not examined factors that may affect TMB estimates in real-world practice, such as the site of biopsy relative to the tumor tissue of origin. Methods: We used the Flatiron Health/Foundation Medicine Clinico-Genomic Database (Presley CJ, et al. JAMA 2018; Singal G, et al. JAMA 2019), which contains deidentified patient-level clinical records from Flatiron Health (New York, NY), combined with genomic sequencing test results of tissue TMB from Foundation Medicine (Cambridge, MA). We examined patient records from 7 advanced cancer types: non-small cell lung cancer (NSCLC), breast cancer (BC), gastric/esophageal cancer (G/EC), melanoma (MEL), metastatic castration-resistant prostate cancer (CRPC), head and neck cancer (H&amp;N), and small cell lung cancer (SCLC). We performed a multivariate mixed-model linear regression to test for associations between the site of tissue biopsy and TMB measurement. We used a cutoff of 10 mutations per megabase (mut/Mb) to classify specimens as high TMB. Results: TMB data were available for 11,928 biopsy specimens from 11,567 patients: NSCLC, n = 5556; BC, n = 3381; G/EC, n = 1335; MEL, n = 528; CRPC, n = 506; H&amp;N, n = 342; SCLC, n = 280. In multiple cancer types, we found that TMB estimates were significantly associated with the biopsied site. For example, brain metastasis specimens from patients with NSCLC had higher TMB (median 11.3 mut/Mb) than specimens collected from primary lung tissue (median 7.0 mut/Mb) or from pleura or pleural fluid (median 3.5 mut/Mb). TMB measurements were higher in brain metastases than in samples from the primary tissue across multiple cancer types. In contrast, biopsies from lymph nodes showed different TMB patterns depending on the cancer type. Consistent with those results, the proportion of patients with high TMB differed significantly by biopsied site. Conclusion: We used a real-world database of clinical data linked with genomic tests to evaluate TMB values across tissue biopsy sites for multiple cancer types. Our results highlight the biopsied site as a potential source of variation for TMB results measurements in a cancer type–specific manner. This will be important to consider when performing research in heterogenous data sets. Citation Format: Simon Papillon-Cavanagh, Chuan Gao, G. Celine Han, Alice M. Walsh. Pan-cancer profiling of the effect of biopsied site on tumor mutational burden measurements in a real-world data cohort [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 2008.

Abstract 5671: Alignment of TMB measured on clinical samples: Phase IIB of the Friends of Cancer Research TMB Harmonization Project

Abstract Introduction: Tumor mutational burden (TMB) is the number of somatic mutations per megabase in a tumor's genome and has shown promise as a predictive biomarker of response to immune checkpoint inhibitors across several cancers. TMB is typically measured by whole exome sequencing (WES TMB) or by targeted next-generation sequencing gene panels (panel TMB). As more assays are developed to estimate TMB, harmonization is emerging as an unmet need and is a key goal of the Friends of Cancer Research (Friends) TMB Harmonization Project. Phase I of the Harmonization Project demonstrated correlation between panel TMB and WES TMB using TCGA data and defined theoretical sources of variability across panels. In phase IIA, sustainable TMB reference standard materials generated from human derived cell lines were used to characterize variability in TMB measurements across panels and assessed for utility in TMB alignment. Phase IIB aims to characterize variability in TMB measurements in clinical samples and to establish best practices for estimating and aligning TMB in order to improve consistency across panels. Methods: Fifteen laboratories (16 targeted gene panels) at different stages of development participated in phase IIB. Thirty formalin-fixed paraffin-embedded (FFPE) samples with &amp;gt;30% tumor content were acquired; tumor DNA was isolated by a single reference lab. TMB values were calculated for DNA extracted from lung (N=10), bladder (N=10), and gastric tumors (N=10) using WES and a uniform bioinformatics pipeline agreed upon by all Consortium members. DNA samples were also sent to all laboratories, and each used their own sequencing and bioinformatics pipelines to estimate TMB from the genes represented in their respective panels. For each tumor sample, a median across panel TMB estimates was calculated; individual panel TMB estimates were translated to fold-changes relative to the sample median to quantify variability. Association between WES TMB (reference) and panel TMB will be assessed by regression analysis; dependence of association on cancer type was investigated. Results: A subset of tumor samples (9 bladder, 7 lung, and 5 gastric) was analyzed using 11 panels at the time of abstract submission. Median panel TMB values ranged 0.60 - 40.26 across samples, with median of median values of 5.35. Fold-change from sample-level medians ranged 0x - 6.67x. Assessment of these clinical samples by WES and all 16 gene panels, as well as regression analysis results, are forthcoming. Conclusions: The Friends TMB Harmonization Project has made substantial progress in characterization of TMB measurement variability and association between WES TMB and panel TMB. These are important steps toward alignment of TMB estimates generated by different gene panels which may improve the interpretation of findings within clinical development programs and ultimately enhance the usefulness of this predictive biomarker in clinical decision making. Citation Format: Diana M. MERINO, Laura M. Yee, Lisa M. McShane, P. Mickey Williams, Tomas Vilimas, Rajesh Patidar, J. Carl Barrett, Shu-Jen Chen, Jen-Hao Cheng, Jeffrey M. Conroy, Dinesh Cyanam, Kenneth R. Eyring, David A. Fabrizio, Vincent Funari, Elizabeth P. Garcia, Sean T. Glenn, Christopher D. Gocke, Vikas Gupta, Lisa M. Haley, Matthew D. Hellmann, Laurel Keefer, Lauryn R. Keeler, Brett Kennedy, Alexander J. Lazar, Laura E. MacConaill, Kristen L. Meier, Arnaud Papin, Naiyer A. Rizvi, Ethan Sokol, Phillip Stafford, John F. Thompson, Warren Tom, Victor J. Weigman, Mingchao Xie, Chen Zhao, Mark D. Stewart, Jeff Allen. Alignment of TMB measured on clinical samples: Phase IIB of the Friends of Cancer Research TMB Harmonization Project [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 5671.

Abstract 3093: Quantifying the confounders of panel-based tumor mutational burden (TMB) measurement

Abstract Retrospective data including subgroup analyses in clinical studies have sparked strong interest in developing tumor mutational burden (TMB) as a predictive biomarker for immune checkpoint blockade. While individual factors interfering with panel sequencing based measurement of TMB (psTMB) have been discussed in recent studies, an integrative study quantifying, comparing and combining all potential confounders is still missing. We separated different potential confounders of psTMB measurement including “panel size”, “germline mutation filtering”, “biological variance” and “technical variance” and developed a specific error model for each of these factors. Published experimental psTMB data were fitted to the error models to quantify the contribution of each of the confounders. The total psTMB variance was obtained as sum over the different variance contributions. Using a typical large panel (size 1 to 1.5 Mbp) total errors of 57%, 42%, 34% and 28% were observed for tumors with psTMB of 5, 10, 20 and 40 muts/Mbp. Even for large panels, the stochastic error connected to the panel size represented the largest of all contributions to the total psTMB variance, especially for tumors with TMB up to 20 muts/Mbp. Other sources of psTMB variability could be kept under control, but rigorous quality control, best practice laboratory workflows and optimized bioinformatics pipelines are essential. We developed an integrated framework for the analysis of psTMB variability and provide a set of recommendations for implementation of psTMB as a laboratory developed test. Our approach highlights the stochastic portion of psTMB variability. The stochastic error connected inherently with psTMB could in part explain the suboptimal performance of the biomarker in some of the recent lung cancer studies. Citation Format: Jan Budczies, Daniel Kazdal, Michael Allgäuer, Petros Christopoulos, Eugen Rempel, Nicole Pfarr, Wilko Weichert, Stefan Fröhling, Michael Thomas, Solange Peters, Volker Endris, Peter Schirmacher, Albrecht Stenzinger. Quantifying the confounders of panel-based tumor mutational burden (TMB) measurement [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3093.

Abstract 1982: Development of reference material for blood tumor mutational burden measurement

Abstract Tumor mutational burden (TMB) is a measurement of the somatic mutations acquired by a tumor genome that cause nonsynonymous changes in proteins. TMB is a biomarker that serves as a proxy for the potential to produce neoantigens that will be recognized by T cells. Despite some reports to the contrary, TMB has successfully categorized the likelihood that an individual will respond positively to immune checkpoint inhibitors in some clinical trials. Although most TMB measurements are made from genomic DNA extracted from formalin-fixed and paraffin-embedded tissue sections, some diagnostic tests measure TMB in circulating tumor DNA (ctDNA) extracted from blood samples; an approach referred to as blood TMB (bTMB). Blood TMB is an attractive biomarker since it bypasses many of the obstacles encountered with resected and hard to biopsy tumors. Only a handful of diagnostic laboratories measure bTMB and their analytic validations rely on hard to obtain specimens acquired from ongoing drug trials or tissue repositories. This specimen scarcity impedes in depth analytic assay validation and the generation of harmonized bTMB data. For bTMB measurements to become routine, robust, and accessible to all diagnostic laboratories, we developed contrived patient-like bTMB reference materials. Blood TMB reference materials were formulated by blending and sizing genomic DNA purified from tumor and corresponding normal cell lines by proprietary methodology. Fragment analysis demonstrated that the bTMB reference materials mimic the size distribution typical of purified ctDNA. Sequencing by a targeted gene panel showed the bTMB reference materials had variant allele frequencies (VAFs) characteristic of ctDNA. For example, bTMB reference materials produced with either 2.0 or 0.5% tumor content had mean VAFs of approximately 1.0 and 0.3 %, respectively. Additional sequencing of bTMB reference materials by other gene panels demonstrated comparable results. Evaluation of contrived bTMB reference materials with various cancer gene panels will assist in the standardization of the measurement of bTMB, an emerging biomarker for clinical utility of immune checkpoint inhibitor therapy. Citation Format: Matthew G. Butler, Yves Konigshofer, Omoshile Clement, Andrew Anfora, Dan Brudzewsky, Bharathi Anekella, Russell Garlick. Development of reference material for blood tumor mutational burden measurement [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1982.

Targeted 595-gene genomic profiling demonstrates low tumor mutational burden in olfactory neuroblastoma.

Olfactory neuroblastoma (ONB) is a rare skull-base malignancy associated with delayed local recurrence. Treatment options in recurrent disease are few and unreliable. We undertook analysis of the ONB exome and immune environment in order to identify potential future immunotherapy treatment options. Retrospective chart review and next-generation targeted 595-gene genomic profiling was performed on a cohort of 14 ONB cases utilizing Tempus proprietary DNA and RNA sequencing technology. Tempus analysis provided a measurement of tumor mutational burden (TMB) and composition of the immune cell infiltrate present in tumor samples. Clinically relevant genomic alterations and associated targeted therapies were identified using cancer.gov and clinicaltrials.gov. TMB was tested by univariate analysis against clinical stage, pathologic grade, recurrence risk, and immune cell infiltration. The mean age for the subjects was 50 years (range, 13 to 76 years) with a male:female ratio of 1:1. TMB for ONB samples ranged from 1.3 to 9.6 mutations/megabase (Mb) with mean of 3.8 mutations/Mb. Univariate analysis showed no association between TMB and tumor stage, pathologic grade, risk of recurrence, or immune cell infiltration. Genomic profile revealed that 6 of 13 tumors had genetic alterations with targeted therapies in clinical trials, whereas 1 tumor demonstrated KRAS Q61R mutation with U.S. Food and Drug Administration (FDA)-approved targeted therapies. TMB is a novel biomarker guiding the classification of neoplasms in the emerging era of immunotherapy. The characterization of ONB as a low-TMB pathology contributes to the overall taxonomy of all cancers and suggests limited utility of immunotherapy treatment.