Tumor Mutational Burden From Tumor-Only Sequencing Compared With Germline Subtraction From Paired Tumor and Normal Specimens

Abstract

IMPORTANCE Tumor mutation burden (TMB) is an emerging factor associated with survival with immunotherapy. When tumor-normal pairs are available, TMB is determined by calculating the difference between somatic and germline sequences. In the case of commonly used tumor-only sequencing, additional steps are needed to estimate the somatic alterations. Computational tools have been developed to determine germline contribution based on sample copy state, purity estimates, and occurrence of the variant in population databases; however, there is potential for sampling bias in population data sets. OBJECTIVE To investigate whether tumor-only filtering approaches overestimate TMB. DESIGN, SETTING, AND PARTICIPANTS This was a retrospective cohort study of 50 tumor samples from 10 different tumor types. A 595-gene panel test was used to assess TMB by adding all missense, indels, and frameshift variants with an allelic fraction of at least 5% and coverage of at least 100× within each tumor. Tumor-only TMB was evaluated against the criterion standard of matched germline-subtracted TMB at 3 levels. Level 1 removed all the tumor-only variants with allelic fraction of at least 1% in the Exome Aggregation Consortium database (with the Cancer Genome Atlas cohort removed). Level 2 removed all variants observed in population databases, simulating a naive approach of removing germline variation. Level 3 used an internal tumor-only pipeline for calculating TMB. These specimens were processed with a commercially available panel, and results were analyzed at the Mayo Clinic. Data were analyzed between December 1, 2018, and May 28, 2019. MAIN OUTCOMES AND MEASURES Tumor mutation burden per megabase (Mb) as determined by 3 levels of filtering and germline subtraction. RESULTS There were significantly higher estimates of TMB with level 1 (median [range] mutations per Mb, 28.8 [17.5-67.1]), level 2 (median [range] mutations per Mb, 20.8 [10.4-30.8]), and level 3 (median [range] mutations per Mb, 3.8 [0.8-12.1]) tumor-only filtering approaches than those determined by germline subtraction (median [range] mutations per Mb, 1.7 [0.4-9.2]). There were no strong associations between TMB estimates and tumor-germline TMB for level 1 filtering

Validation of a NGS panel, with automated analysis, designed for detection of medically actionable tumor biomarkers for Latin America

“…Overestimation of somatic variants is a problem when facing the tumor of a patient from any region or ancestry without a reference genome informative of the genetic variation in that specific population. This issue is critical for therapy determinants such as the tumor mutational load, which should be carefully interpreted in these patients 39 .…”

Inflation of tumor mutation burden by tumor-only sequencing in under-represented groups

“…TMB-H status is now an FDA-approved patient selection biomarker for ICI therapy. Because the collection of patient-matched germline samples is still not a common practice in clinic, TMBs are routinely estimated using tumor-only sequencing which led to significantly inflated TMB estimates 4 . Here we demonstrate that TMB inflations are racially disparate with significantly higher inflated TMBs in the tumors from Black patients due to the under-representation of minority groups in public variant DBs for variant filtering, regardless whether all (Figs.…”

“…peripheral blood) are not routinely collected in clinic for germline analysis, TMB is often calculated from tumor-only sequencing relying on public germline variant databases (DBs) to filter out non-somatic polymorphisms. We previously reported that filtering based on public DBs significantly inflated TMB 4 . In this study, we investigated the impact of minority group representation in these DBs and hypothesized that TMB would be more greatly inflated in under-represented groups.…”

Chimeric antigen receptor (CAR)-T-cell therapy in non-small-cell lung cancer (NSCLC): current status and future perspectives

“…Additionally, tyrosine kinase inhibitors may serve as clinical therapy for metastatic NSCLC patients harboring epidermal growth factor receptor (EGFR)-enhancing mutations [8]. Despite advances in surgical therapy, chemotherapy, and radiotherapy during the past 20 years that resulted in the increased survival time in NSCLC patients, the prognosis of NSCLC has not substantially improved, owing to the tumor mutational burden and the heterogeneity of the disease [4,[9][10][11]. Thus, it is imperative to explore novel strategies to prolong patient survival time.…”