Tumor Mutational Burden Assessment Research Articles

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.

Tumor mutational burden assessment and standardized bioinformatics approach using custom NGS panels in clinical routine

BackgroundHigh tumor mutational burden (TMB) was reported to predict the efficacy of immune checkpoint inhibitors (ICIs). Pembrolizumab, an anti-PD-1, received FDA-approval for the treatment of unresectable/metastatic tumors with high TMB as determined by the FoundationOne®CDx test. It remains to be determined how TMB can also be calculated using other tests.ResultsFFPE/frozen tumor samples from various origins were sequenced in the frame of the Institut Curie (IC) Molecular Tumor Board using an in-house next-generation sequencing (NGS) panel. A TMB calculation method was developed at IC (IC algorithm) and compared to the FoundationOne® (FO) algorithm.Using IC algorithm, an optimal 10% variant allele frequency (VAF) cut-off was established for TMB evaluation on FFPE samples, compared to 5% on frozen samples. The median TMB score for MSS/POLE WT tumors was 8.8 mut/Mb versus 45 mut/Mb for MSI/POLE-mutated tumors. When focusing on MSS/POLE WT tumor samples, the highest median TMB scores were observed in lymphoma, lung, endometrial, and cervical cancers. After biological manual curation of these cases, 21% of them could be reclassified as MSI/POLE tumors and considered as “true TMB high.” Higher TMB values were obtained using FO algorithm on FFPE samples compared to IC algorithm (40 mut/Mb [10–3927] versus 8.2 mut/Mb [2.5–897], p < 0.001).ConclusionsWe herein propose a TMB calculation method and a bioinformatics tool that is customizable to different NGS panels and sample types. We were not able to retrieve TMB values from FO algorithm using our own algorithm and NGS panel.

Harmonization of tumor mutation burden testing with comprehensive genomic profiling assays: an IQN Path initiative

BackgroundAlthough conflicting results emerged from different studies, the tumor mutational burden (TMB) appears as one of most reliable biomarkers of sensitivity to immune checkpoint inhibitors. Several laboratories are reporting TMB...

Enhancing the quality of panel-based tumor mutation burden assessment: a comprehensive study of real-world and in-silico outcomes

Targeted panel-based tumor mutation burden (TMB) assays are widely employed to guide immunotherapy for patients with solid tumors. However, the accuracy and consistency of this method can be compromised due to the variability in technical details across different laboratories, particularly in terms of panel size, somatic mutation detection and TMB calculation rules. Currently, systematic evaluations of the impact of these technical factors on existing assays and best practice recommendations remain lacking. We assessed the performance of 50 participating panel-based TMB assays involving 38 unique methods using cell line samples. In silico experiments utilizing TCGA MC3 datasets were performed to further dissect the impact of technical factors. Here we show that the panel sizes beyond 1.04 Mb and 389 genes are necessary for the basic discrete accuracy, as determined by over 40,000 synthetic panels. The somatic mutation detection should maintain a reciprocal gap of recall and precision less than 0.179 for reliable psTMB calculation results. The inclusion of synonymous, nonsense and hotspot mutations could enhance the accuracy of panel-based TMB assay. A 5% variant allele frequency cut-off is suitable for TMB assays using tumor samples with at least 20% tumor purity. In conclusion, this multicenter study elucidates the major technical factors as sources of variability in panel-based TMB assays and proposed comprehensive recommendations for the enhancement of accuracy and consistency. These findings will assist clinical laboratories in optimizing the methodological details through bioinformatic experiments to enhance the reliability of panel-based methods.

Comprehensive somatic mutational analysis in glioblastoma: Implications for precision medicine approaches.

Glioblastoma multiforme (GBM), a malignant neoplasm originating from glial cells, remains challenging to treat despite the current standard treatment approach that involves maximal safe surgical resection, radiotherapy, and adjuvant temozolomide chemotherapy. This underscores the critical need to identify new molecular targets for improved therapeutic interventions. The current study aimed to explore the somatic mutations and potential therapeutic targets in GBM using somatic mutational information from four distinct GBM datasets including CGGA, TCGA, CPTAC and MAYO-PDX. The analysis included the evaluation of whole exome sequencing (WES) of GBM datasets, tumor mutation burden assessment, survival analysis, drug sensitivity prediction, and examination of domain-specific amino acid changes. The results identified the top ten commonly altered genes in the aforementioned GBM datasets and patients with mutations in OBSCN and AHNAK2 alone or in combination had a more favorable overall survival (OS). Also, the study identified potential drug sensitivity patterns in GBM patients with mutations in OBSCN and AHNAK2, and evaluated the impact of amino acid changes in specific protein domains on the survival of GBM patients. These findings provide important insights into the genetic alterations and somatic interactions in GBM, which could have implications for the development of new therapeutic strategies for this aggressive malignancy.

Analysis of tumor mutational burden and mutational landscape comparing whole-exome sequencing and comprehensive genomic profiling in patients with resectable early-stage non-small-cell lung cancer

Background: Identifying actionable driver mutations via tissue-based comprehensive genomic profiling (CGP) is paramount in treatment decisions for metastatic non-squamous, non-small-cell lung cancer (NSCLC). However, the role of CGP remains elusive in resectable NSCLC. Here, we elucidate the feasibility of CGP in early-stage NSCLC Korean patients and compare the tumor mutational burden (TMB) and mutation landscape using three different platforms. Methods: All surgically resected NSCLC samples ( N = 96) were analyzed to assess the concordance in TMB calculation and targetable mutations using whole-exome sequencing (WES) and TruSight Oncology 500 (TSO500). In all, 26 samples were analyzed with Foundation One CDx Assay (F1CDx). Programmed death-ligand 1 (PD-L1) expression was evaluated using Vectra Polaris. Results: Stage distribution post-surgery was 80% I ( N = 77) and 20% II ( N = 19). Ninety-nine percent ( N = 95) were adenocarcinoma. The median TMB with WES and TSO500 was 1.6 and 4.7 mut/Mb, respectively ( p &lt; 0.05). Using all three platforms, the median TMB was 1.9, 5.5, and 4 mut/Mb for WES, TSO500, and F1CDx, respectively ( p = 0.0048). Linear regression analysis of TMB values calculated between WES and TSO500 resulted in a concordance correlation coefficient of 0.83. For the PD-L1 tumor proportion score of &lt;1% (negative, N = 18), 1–49% (low, N = 68), and ⩾50% (high, N = 10), the R2 values were 0.075, 0.79, and 0.95, respectively. The R2 values for TMB concordance were variable between the three platforms. Mutation landscape revealed EGFR mutation (51%, N = 49) as the most common actionable driver mutation, comprising L858R ( N = 22), E19del ( N = 20), and other non-common EGFR mutations ( N = 7). Conclusion: TSO500 and F1CDx showed robust analytical performance for TMB assessment with TSO500 showing stronger concordance of TMB with high PD-L1 expression. As the paradigm for the management of early-resected NSCLC continues to evolve, understanding TMB and the mutation landscape may help advance clinical outcomes for this subset of patients.

Challenges and Future Directions in the Management of Tumor Mutational Burden-High (TMB-H) Advanced Solid Malignancies.

A standardized assessment of Tumor Mutational Burden (TMB) poses challenges across diverse tumor histologies, treatment modalities, and testing platforms, requiring careful consideration to ensure consistency and reproducibility. Despite clinical trials demonstrating favorable responses to immune checkpoint inhibitors (ICIs), not all patients with elevated TMB exhibit benefits, and certain tumors with a normal TMB may respond to ICIs. Therefore, a comprehensive understanding of the intricate interplay between TMB and the tumor microenvironment, as well as genomic features, is crucial to refine its predictive value. Bioinformatics advancements hold potential to improve the precision and cost-effectiveness of TMB assessments, addressing existing challenges. Similarly, integrating TMB with other biomarkers and employing comprehensive, multiomics approaches could further enhance its predictive value. Ongoing collaborative endeavors in research, standardization, and clinical validation are pivotal in harnessing the full potential of TMB as a biomarker in the clinic settings.

Evaluation of tissue- and plasma-derived tumor mutational burden (TMB) and genomic alterations of interest in CheckMate 848, a study of nivolumab combined with ipilimumab and nivolumab alone in patients with advanced or metastatic solid tumors with high TMB

BackgroundAn accumulation of somatic mutations in tumors leads to increased neoantigen levels and antitumor immune response. Tumor mutational burden (TMB) reflects the rate of somatic mutations in the tumor genome,...

Biomarker-directed, pembrolizumab-based combination therapy in non-small cell lung cancer: phase 2 KEYNOTE-495/KeyImPaCT trial interim results.

Although pembrolizumab confers clinical benefit in non-small cell lung cancer (NSCLC), only a subset of patients will respond due to a heterogenous tumor microenvironment. KEYNOTE-495/KeyImPaCT is an ongoing biomarker-directed, adaptively randomized phase 2 study investigating first-line pembrolizumab (200 mg every 3 weeks) + lenvatinib (20 mg daily), anti-CTLA-4 quavonlimab (25 mg every 6 weeks) or anti-LAG-3 favezelimab (200 mg or 800 mg every 3 weeks) in advanced NSCLC. Patients were categorized by T-cell-inflamed gene expression profile (TcellinfGEP) and tumor mutational burden (TMB) status and randomly assigned 1:1:1 to receive pembrolizumab + lenvatinib, pembrolizumab + quavonlimab or pembrolizumab + favezelimab. The primary outcome was investigator-assessed objective response rate (ORR) per Response Evaluation Criteria in Solid Tumors version 1.1 using pre-specified efficacy thresholds for each biomarker-defined subgroup (>5% (TcellinfGEPlowTMBnon-high (group I)), >20% (TcellinfGEPlowTMBhigh (group II) and TcellinfGEPnon-lowTMBnon-high (group III)) and >45% (TcellinfGEPnon-lowTMBhigh (group IV))). Secondary outcomes were progression-free survival, overall survival and safety. At data cutoff, ORR ranges were 0-12.0% in group I, 27.3-33.3% in group II, 13.6-40.9% in group III and 50.0-60.0% in group IV. ORR with pembrolizumab + lenvatinib in group III met the pre-specified efficacy threshold. The safety profile of each treatment arm was consistent with the known safety profile of each combination. These data demonstrate the feasibility of prospective TcellinfGEP and TMB assessment to study the clinical activity of first-line pembrolizumab-based combination therapies in advanced NSCLC. ClinicalTrials.gov registration: NCT03516981 .

Tumor mutational burden (TMB) in real-world patients with pancreatic ductal adenocarcinoma (PDAC): Differences in genomic alterations (GA) and predictive value for immune checkpoint inhibitor (ICI) effectiveness.

4146 Background: Currently, ICI therapy is recommended for patients with metastatic PDAC whose tumors exhibit dMMR, MSI-H, or high TMB (≥10 mutations/Mb). However, due to the low prevalence of high TMB in PDAC (~1%), few studies have evaluated the role of ICI therapy in this subpopulation. This study aimed to compare GA between PDAC patients with high TMB and low TMB ( &lt; 10 mutations/Mb) and to evaluate the effectiveness of ICIs in real-world PDAC patients by TMB status. Methods: This study included PDAC patients who underwent genomic testing using Foundation Medicine tissue comprehensive genomic profiling (CGP) assays. GA were compared between tissue specimens with high and low TMB by chi-squared, adjusted for multiple comparisons. Patient clinical data was obtained by the US-wide de-identified Flatiron Health and Foundation Medicine real-world clinicogenomic pancreatic database (CGDB), originated from ~280 US cancer clinics between 01/2011 and 09/2022. Real-world overall survival (OS) and time to treatment discontinuation (TTD) were compared between patients receiving an ICI (high TMB versus low TMB) and between patients with high TMB (ICI versus other therapies) by Cox models. Results: We included 21,932 patients with PDAC with tissue CGP data available; 98.7% with low TMB and 1.3% with high TMB. Among actionable alterations, patients with high TMB had higher prevalence of mutations in BRCA2 (p &lt; 0.0001), BRAF (p &lt; 0.0001), PALB2 (p &lt; 0.0001), and genes of the mismatch repair pathway ( MSH2, MSH6, MLH1, and PMS2, p &lt; 0.0001), but lower prevalence of KRAS mutations (p &lt; 0.0001). The most common KRAS mutation in both groups of patients was G12D. In CGDB, 51 patients received an ICI (10 with high TMB and 41 with low TMB) and 17 patients with high TMB received other therapies. Among patients receiving an ICI, those with high TMB had more favorable median OS compared to those with low TMB (25.7 versus 5.2 months, hazard ratio (HR) 0.27, 95% confidence interval (CI) 0.09 - 0.76, p = 0.01) and median TTD (20.7 versus 3.0 months, HR 0.33, 95% CI 0.13 - 0.82, p = 0.02). Among patients with high TMB, those receiving an ICI had more favorable OS compared to those receiving other therapies (25.7 versus 6.6 months, HR 0.31, 95% CI 0.10-0.96, p = 0.043), nominally favoring ICI use in this small cohort (n = 10 versus 17). Conclusions: There is no randomized clinical trial evaluating ICI versus other therapies in PDAC. To our knowledge, this is the largest cohort to date comparing ICI effectiveness in PDAC. We observed more favorable OS among PDAC patients with high TMB receiving ICI versus those with low TMB who received an ICI and more favorable to those with high TMB receiving other therapies. This study supports the FDA-approved use of ICIs in patients with PDAC and high TMB and demonstrates the importance of TMB assessment for patients with PDAC.

Assessment of Tumor Mutational Burden and Outcomes in Patients With Diverse Advanced Cancers Treated With Immunotherapy

There are few studies assessing the association of tumor mutational burden (TMB) and clinical outcomes in a large cohort of patients with diverse advanced cancers. To clinically validate a TMB biomarker from a next-generation sequencing targeted gene panel assay. A prespecified cohort study using the deidentified clinicogenomic Tempus database of patients sequenced between 2018 and 2022, which contained retrospective, observational data originating from 300 cancer sites including 199 community sites and 101 academic sites. Patients with advanced solid tumors across 8 cancer types and more than 20 histologies, sequenced with Tempus xT who were treated with immune checkpoint inhibitors (ICIs) in the first-line or second-line setting were included. Data were analyzed from September 2018 to August 2022. Treatment with US Food and Drug Administration (FDA)-approved antiprogrammed cell death-1/programmed cell death-ligand 1 (PD-1/PD-L1) ICI and/or in combination with a cytotoxic T-lymphocyte-associated protein-4 ICI. The primary outcome was the association of tumor mutational burden (TMB) binary category (high [≥10 mut/mb] vs low) with overall survival (OS) in patients treated with ICIs. Secondary outcomes were progression-free survival (PFS), and time to progression (TTP). In the evaluable cohort of 674 patients, the median (IQR) age was 69.4 (28.6-89.8) years, 271 patients (40.2%) were female, and 435 patients (64.5%) were White. The most common advanced cancers were non-small cell lung cancer (330 patients [49.0%]), followed by bladder cancer (148 patients [22.0%]), and head and neck squamous cell carcinoma (96 patients [14.8%]). Median (IQR) follow-up was 7.2 (3.2-14.1) months. High TMB (TMB-H) cancers (206 patients [30.6%]) were significantly associated with longer OS than low TMB (TMB-L) cancers (hazard ratio [HR], 0.72; upper confidence bound [UCB], 0.91; P = .01). In a prospective subset of 403 patients treated with ICIs after TMB testing, TMB-H cancers (135 patients [33.5%]) were significantly associated with longer OS (HR, 0.61; UCB, 0.84; P = .005), PFS (HR, 0.62; UCB, 0.82; P = .003), and TTP (HR, 0.67; UCB, 0.92; P = .02) than TMB-L cancers. An overall survival benefit was seen regardless of the type of ICI used (pembrolizumab, 339 patients; HR, 0.67; UCB, 0.94; P = .03), other ICIs (64 patients; HR, 0.37; UCB, 0.85; P = .03), and after adjusting for PD-L1 and microsatellite stability status (403 patients; HR = 0.67; UCB, 0.92; P = .02). In this cohort study of patients with advanced solid tumors treated with ICIs in diverse clinics, TMB-H cancers were significantly associated with improved clinical outcomes compared with TMB-L cancers.

Abstract 1027: Assessment of tumor mutation burden (TMB) based on whole exome sequencing using extracellular vesicles-derived DNA obtained from bronchoalveolar lavage fluid (BALF) in advanced NSCLC patients treated with pembrolizumab

Abstract Background: Although multiple immune checkpoint inhibitors showed improved outcomes in patients with high tumor mutational burden (TMB) as well as high PD-L1 expression, obtaining adequate tumor tissue for various molecular testing including next-generation sequencing (NGS) is not a simple issue in patients with advanced non-small cell lung cancer (NSCLC). We aimed to assess TMB based on whole exome sequencing (WES) using extracellular vesicles (EV)-derived DNA isolated from bronchoalveolar lavage fluid (BALF) and determine the correlation of TMB between BALF and tissue. Methods: Patients diagnosed with advanced NSCLC and who were treated with pembrolizumab between December 2018 and December 2021 were included in this multicenter translational cohort study. The correlation of TMB between BALF and tissue measured by WES was evaluated by Spearman’s rank correlation coefficient in matched BALF and tissue samples from 62 patients. We analyzed the association of BALF TMB level with progression-free survival (PFS) and response to pembrolizumab. Results: Of 62 patients, 47 (75.8%) had evaluable tissue TMB and 57 (91.9%) had evaluable BALF TMB. There were no significant differences between BALF and tissue with regards to DNA amounts, estimated library size, mean depth, and uniformity. Median tissue TMB and BALF TMB were 6.02 and 2.16 mut/Mb, respectively. There was a weak positive correlation between tissue TMB and BALF TMB (r=0.23, p &amp;lt; 0.001), whereas BALF TMB found higher correlations with tissue TMB in patients with squamous cell carcinoma (r=0.77, p &amp;lt; 0.001). Neither tissue TMB nor BALF TMB showed significant differences PFS or ORR benefit for treatment with pembrolizumab, however the BALF TMB of patients who had been treated with pembrolizumab for more than 6 months was higher than that of those who did not (p=0.039). Conclusions: The findings suggest that NGS using BALF EV DNA is feasible for TMB calculation to overcome the matter of small biopsy issue in advanced NSCLC patients, which may play a supplementary serve as a potential biomarker of clinical benefit in patients with NSCLC treated with pembrolizumab. Citation Format: Heejoung Kim, Jaeyoung Hur, Wan Seop Kim, In Ae Kim, Dong Il Park, In-Jae Oh, Kye Young Lee. Assessment of tumor mutation burden (TMB) based on whole exome sequencing using extracellular vesicles-derived DNA obtained from bronchoalveolar lavage fluid (BALF) in advanced NSCLC patients treated with pembrolizumab [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1027.

Heterogeneous expression of predictive biomarkers PD-L1 and TIGIT in non-mucinous lung adenocarcinoma and corresponding lymph node metastasis: A challenge for clinical biomarker testing

The use of immune checkpoint inhibitors (ICI) targeting the PD-L1:PD1 interaction revolutionized tumor treatment by re-activating the anti-tumoral capacity of the immune system. Assessment of tumor mutational burden, microsatellite instability, or expression of the surface marker PD-L1 have been used to predict individual response to ICI therapy. However, the predicted response does not always correspond to the actual therapy outcome. We hypothesize that tumor heterogeneity might be a major cause of this inconsistency. In this respect we recently demonstrated that PD-L1 shows heterogenous expression in the different growth patterns of non-small cell lung cancer (NSCLC) - lepidic, acinar, papillary, micropapillary and solid. Furthermore, additional inhibitory receptors, like T cell immunoglobulin and ITIM domain (TIGIT), appear to be heterogeneously expressed and affect the outcome of anti-PD-L1 treatment. Given this heterogeneity in the primary tumor, we set out to analyze the situation in corresponding lymph node metastases, since these are often used to obtain biopsy material for tumor diagnosis, staging and molecular analysis. Again, we observed heterogeneous expression of PD-1, PD-L1, TIGIT, Nectin-2 and PVR in relation to different regions and growth pattern distribution that varied between the primary tumor and their metastases. Together, our study underscores the complex situation regarding the heterogeneity of NSCLC samples and suggest that the analysis of a small biopsy from lymph node metastases may not be sufficient to ensure a reliable prediction of ICI therapy success.

Abstract A006: Increased germline mutational burden in individuals of African ancestry: Implications for interpretation of tumor mutation burden

Abstract Introduction: Tumor mutation burden (TMB), defined as the number of somatic gene mutations per megabase in a tumor genome, is used clinically to identify cancer patients that may respond to immune checkpoint inhibitors. Recent studies suggest that patient ancestry can influence TMB, where individuals of African ancestry were found to have elevated TMB values based on tumor-only sequencing analysis. However, the impact of patient ancestry on germline mutational burden and implications for interpretation of tumor-only mutational burden data is largely unexplored. Methods: We examined the influence of patient ancestry on germline and tumor mutation burden using tumor-normal whole exome sequencing (WES) data from a pan-cancer cohort of 1228 individuals from a single institution. Genetic ancestry was estimated from constitutional WES data using single nucleotide polymorphism weights from external reference panels. Variant calling was performed using constitutional, tumor-only, and paired tumor-normal workflows. Total and loss-of-function burden scores were calculated for each participant from each workflow based on the total number of mutations detected in each sample and the total number of predicted loss-of-function mutations, based on snpEff annotations, respectively. Results: Genetic ancestry analysis found that one-third of this pan-cancer cohort was of non-European ancestry. 9.4% of individuals were of Eastern Asian ancestry, 5.3% of African ancestry, 1.0% of South Asian ancestry, 0.2% of Native American ancestry, and 17.1% of admixed ancestry, predominantly European and Native American admixed ancestry (15.6%). Total and loss-of-function germline burden scores varied across ancestral groups, with individuals of African ancestry showing significantly increased germline burden scores compared to other ancestral groups (p&amp;lt;0.0001). Tumor-only analysis also showed increased mutation burden for individuals of African ancestry. However, when private and rare germline variation was taken into account using paired tumor-normal analysis, tumor mutation burden did not differ based on patient ancestry, suggesting the differences seen in tumor-only analysis are due to germline variation rather than differences in true somatic mutation burden. Conclusion: Our study reveals that the paucity of knowledge of ancestry-specific reference genomes leads to unacceptable health disparities in cancer, specifically in patients with African ancestry. We show that germline mutational burden varies by ancestral background, with individuals of African ancestry displaying increased genetic variation compared to other ancestral populations. These results suggest that patient ancestry should be considered when interpreting tumor mutational burden values, particularly from tumor-only analysis. Approaches utilizing paired tumor-normal analysis or ancestry-specific reference genomes can aid in more accurate assessment of TMB, thereby avoiding futile treatments targeted at presumed high mutational burden tumors specifically in African American populations. Citation Format: Janith Don, Sara A. Byron, Guangfa Zhang, Tyler Izatt, Jiaming Zhang, Bethany Davis, Bryce Turner, Jonathan J. Keats, Jeffrey M. Trent, Lorna Rodriguez-Rodriguez, Nicholas J. Schork. Increased germline mutational burden in individuals of African ancestry: Implications for interpretation of tumor mutation burden [abstract]. In: Proceedings of the 15th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2022 Sep 16-19; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr A006.

External quality assessment (EQA) for tumor mutational burden: results of an international IQN path feasibility pilot scheme

Tumor mutational burden (TMB) has recently been approved as an agnostic biomarker for immune checkpoint inhibitors. However, methods for TMB testing have not yet been standardized. The International Quality Network for Pathology (IQNPath) organized a pilot external quality assessment (EQA) scheme for TMB testing. The aim of this program was the validation of the materials and the procedures for the EQA of this complex biomarker. Five formalin-fixed paraffin-embedded (FFPE) cell lines were selected to mimic the various TMB values observed in clinical practice. The FFPE samples were tested with the FoundationOne CDx (F1CDx) assay as the reference test and three commercially available targeted sequencing panels. Following this internal validation, the five cell lines were sent to 29 laboratories selected on the basis of a previous survey. Nineteen of the 23 laboratories that submitted results (82.6%) used targeted sequencing for TMB estimation. Only two laboratories performed whole exome sequencing (WES) and two assessed TMB by clinical exome. A high variability in the reported TMB values was observed. The variability was higher for samples with the highest TMB value according to the F1CDx test. However, good reproducibility of the TMB score was shown by laboratories using the same panel. The majority of laboratories did not indicate a TMB cut-off value for clinical interpretation. In conclusion, this pilot EQA scheme suggests that it is feasible to run such an EQA program for TMB assessment. However, the results of our pilot highlight the numerous challenges for the standardization of this test.

New methodology of TMB assessment from tissue and liquid biopsy in NSCLC.

Immunotherapy has dramatically influenced and changed therapeutical approach in non-small cell lung cancer (NSCLC) in recent five years. Even though we can reach long-term response to this treatment in approximately 20% of patients with NSCLC, we are still not able to identify this cohort of patients based on predictive biomarkers. In our study we have focused on tumor mutation burden (TMB), one of the potential biomarkers which could predict effectiveness of check-point inhibitors, but has several limitations, especially in multiple approaches to TMB quantification and ununiform threshold. We determined the value of TMB in tumor tissue (tTMB) and blood (bTMB) in 20 patients with early stage NSCLC using original custom gene panel LMB_TMB1. We evaluated various possibilities of TMB calculation and concluded that TMB should be counted from both somatic non-synonymous and synonymous mutations. Considering various factors, we established cut-offs of tTMB in/excluding HLA genes as ≥22 mut/Mb and 12 mut/Mb respectively, and cut-offs of bTMB were defined as ≥21 mut/Mb and ≥5 mut/Mb, respectively. We also observed trend in correlation of somatic mutations in HLA genes with overall survival of patients.

A new deep learning technique reveals the exclusive functional contributions of individual cancer mutations

Cancers are caused by genomic alterations that may be inherited, induced by environmental carcinogens, or caused due to random replication errors. Postinduction of carcinogenicity, mutations further propagate and drastically alter the cancer genomes. Although a subset of driver mutations has been identified and characterized to date, most cancer-related somatic mutations are indistinguishable from germline variants or other noncancerous somatic mutations. Thus, such overlap impedes appreciation of many deleterious but previously uncharacterized somatic mutations. The major bottleneck arises due to patient-to-patient variability in mutational profiles, making it difficult to associate specific mutations with a given disease outcome. Here, we describe a newly developed technique Continuous Representation of Codon Switches (CRCS), a deep learning-based method that allows us to generate numerical vector representations of mutations, thereby enabling numerous machine learning-based tasks. We demonstrate three major applications of CRCS; first, we show how CRCS can help detect cancer-related somatic mutations in the absence of matched normal samples, which has applications in cell-free DNA–based assessment of tumor mutation burden. Second, the proposed approach also enables identification and exploration of driver genes; our analyses implicate DMD, RSK4, OFD1, WDR44, and AFF2 as potential cancer drivers. Finally, we used CRCS to score individual mutations in a tumor sample, which was found to be predictive of patient survival in bladder urothelial carcinoma, hepatocellular carcinoma, and lung adenocarcinoma. Taken together, we propose CRCS as a valuable computational tool for analysis of the functional significance of individual cancer mutations.

Abstract 611: Assessment of tumor mutation burden and microsatellite instability by single-cell circulating tumor cell genomic profiling

Abstract The success of immune checkpoint inhibitors rests on biomarkers such as tumor mutation burden (TMB) and microsatellite instability (MSI), both FDA-approved predictors of anti PD-1/L1 therapy benefit. Tissue biopsies often collected once in the metastatic setting through an invasive procedure, or archived primary tumor tissue often collected much prior to treatment consideration, are the specimen types of choice for biomarker identification. The tissue sample originates from a limited region of one disease site, which may limit its usefulness given intra-patient tumor heterogeneity. TMB and MSI measurement by liquid biopsy, including proteins, circulating tumor cells (CTC), and cell-free circulating tumor DNA (ctDNA), is an attractive, minimally-invasive way to obtain a real-time picture of the entire disease. While TMB and MSI assessment from ctDNA have been reported, their measurement can be limited by low ctDNA tumor fraction. Single-cell next generation sequencing of CTC, on the other hand, is a particularly well-suited, but largely unexplored method of measuring TMB and MSI to complement tissue and ctDNA for better overall specificity of detection. In this proof-of-concept study, we show the ability to detect single-cell TMB and MSI. We analyzed 14 CTC and 4 ctDNA samples from 6 metastatic breast cancer patients, as well as 3 single cells and 1 cell pellet sample each from HCT-116 (MSI-High) and WiDr (MSI-Low) cell lines. CTC and cell line cells were enriched with the CellSearch® system and/or isolated with the DEPArray™ system. Whole genome amplified single-cell DNA was sequenced with the Oncomine Comprehensive Assay covering ~500 genes and 1.1Mb of genomic space. TMB and MSI scores obtained in CTC and ctDNA were compared to those measured in matched clinical tissue biopsies. Single-cell TMB scores and MSI status were assessable in all CTC tested. CTC TMB scores were highly concordant with the matched tissue samples (r=1.00), as were ctDNA TMB scores (r=0.98) in patients with assessable TMB scores in both biospecimen types compared. Importantly, TMB was detectable in CTC from one patient whose tissue sample was inadequate for clinical sequencing, and from another patient with inadequate, low tumor fraction ctDNA. Intriguingly, one patient harbored 3 TMB-high and 2 TMB-low CTC, potentially indicating intra-patient TMB heterogeneity. The known MSI-low status from clinical tumor tissue sequencing was correctly detected in CTC and ctDNA from all patients. MSI status and scores from single cells of HCT-116 and WiDr cell lines purified with the DEPArray™ system (mimicking CTC isolation), perfectly matched that of the corresponding cell pellet samples (r=1.00). Taken together, these data suggest the potential validity and continued interrogation of potential utility of CTC TMB and MSI detection to complement tissue and ctDNA in guiding checkpoint inhibitor immunotherapy. Citation Format: Andi K. Cani, Emily M. Dolce, Chia-Jen Liu, Brittany Rupp, Elizabeth P. Darga, Costanza Paoletti, Dafydd G. Thomas, Yi-Mi Wu, Dan R. Robinson, Sunitha Nagrath, Arul M. Chinnaiyan, Scott A. Tomlins, Aaron M. Udager, John M. Carethers, Erin F. Cobain, Daniel F. Hayes. Assessment of tumor mutation burden and microsatellite instability by single-cell circulating tumor cell genomic profiling [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 611.

Abstract 537: Development of blood TMB (bTMB) reference materials for validation of cfDNA-based targeted NGS assays that measure tumor mutational burden (TMB) in patient blood samples

Abstract TMB is a biomarker with potential for predicting positive patient response to immune checkpoint inhibitors. TMB measurements can be determined using genomic DNA extracted from FFPE-preserved tissue biopsy samples. However, assessment of TMB from a liquid biopsy, or blood TMB (bTMB), is an attractive alternative clinical diagnostic tool that would allow clinicians and patients to avoid the invasive challenge of tissue biopsies. Accurately measuring bTMB with targeted gene panels has been problematic, thus we have developed the new Seraseq® bTMB reference materials at various mutational burden levels from genomic DNA extracted from tumor-derived and SNP-matched normal cell lines. Somatic variants were identified in each cell line by whole exome sequencing (WES). TMB assessments were made by an in-house developed TMB bioinformatics pipeline based on recommendations by the Friends of Cancer Research (FoCR) TMB Harmonization Consortium. DNA from tumor and normal cell lines were blended at 0%, 0.5%, and 2% tumor fractions and fragmented to approximate the size of cell free DNA (cfDNA). The resulting bTMB mixes were enriched with the TruSight™ Oncology 500 ctDNA Assay (2x151 bp), in triplicate, and sequenced on a NovaSeq™ 6000. Blood TMB scores were determined using the DRAGEN™ TruSight Oncology 500 ctDNA Analysis Software v1.1. The observed bTMB scores for the tumor-containing materials were slightly lower in the TF 0.5% mix versus the TF 2% mix due to variants moving below the limit of detection of the TSO500 ctDNA assay (Table 1). As is the case with patient samples and clonal hematopoiesis, there are background variants in 0% tumor content material that may elevate apparent bTMB scores, thus adjusted bTMB scores are shown. The Seraseq Blood TMB Score reference materials provide a tumor-normal matched blood TMB control to aid development, validation and QC of cfDNA NGS assays for accurate determination of bTMB Scores. Table 1. Average bTMB scores and adjusted bTMB scores for each mix. Mix Average bTMB Score (mutations/megabase ± 1 SD) Adjusted bTMB Score (mutations/megabase ± 1 SD) Score 7 0% 7.5 ± 1.7 0 Score 7 0.5% 13.1 ± 2.6 5.6 ± 3.1 Score 7 2% 17.9 ± 1.3 10.4 ± 2.1 Score 13 0% 4.6 ± 0.5 0 Score 13 0.5% 18.7 ± 2.1 14.1 ± 2.2 Score 13 2% 24.6 ± 0.8 20.0 ± 0.9 Score 20 0% 7.5 ± 1.4 0 Score 20 0.5% 26.0 ± 2.3 18.5 ± 2.7 Score 20 2% 35.6 ± 1.0 28.1 ± 1.7 Score 26 0% 6.0 ± 0.5 0 Score 26 0.5% 20.7 ± 5.5 14.7 ± 5.5 Score 26 2% 30.4 ± 1.5 24.4 ± 1.9 Citation Format: Dana Ruminski Lowe, Benedicta Forson, Matthew G. Butler, Yves Konigshofer, Catherine Huang, Omoshile Clement, Russell K. Garlick, Bharathi Anekella. Development of blood TMB (bTMB) reference materials for validation of cfDNA-based targeted NGS assays that measure tumor mutational burden (TMB) in patient blood samples [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 537.

Development of a Novel Reference Material for Tumor Mutational Burden Measurement Based on CRISPR/Cas9 Technology.

As a biomarker that affects treatment decisions of immune checkpoint inhibitors, the accuracy, reliability, and comparability of tumor mutational burden (TMB) estimation is of paramount importance. To improve the consistency and reliability of these tests, qualified reference materials providing ground-truth data are crucial. In this study, we developed a set of formalin-fixed and paraffin-embedded (FFPE) samples with different TMB values as the novel reference materials for TMB estimation. By introducing several clinically relevant variants in MutS Homolog 2 (MSH2) gene and DNA polymerase epsilon (POLE) gene into human cell lines using CRISPR/Cas9 technology, we first constructed four typical cell lines which verified with hypermutator or ultramutator phenotype. Followed by cell mixing and paraffin embedding, the novel FFPE samples were prepared. It was confirmed that our novel FFPE samples have sufficient quantity of cells, high reproducibility, and they can provide matched wild type sample as the genetic background. The double-platform whole exome sequencing validation showed that our FFPE samples were also highly flexible as they containing different TMB values spanning a clinically relevant range (2.0–106.1 mut/Mb). Without limitations on production and TMB values, our novel FFPE samples based on CRISPR/Cas9 editing are suitable as candidate reference materials. From a practical point of view, these samples can be used for the validation, verification, internal quality control, and proficiency testing of TMB assessment.