Panel Size Affects Accuracy of Tumor Mutational Burden Calculation
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Panel size is a critical determinant of test performance and cutoff values for determining the tumor mutational burden (TMB) to guide treatment decisions with immunotherapies, according to a study published Sept. 21 in the International Journal of Cancer. Specifically, panels between 1.5 to 3 Mbp are ideal to effectively estimate TMB.
“To provide a wide availability of testing, lab developed tests to determine TMB need to implemented. However, current data that can provide guidance in this context are scarce and preliminary,” write the authors led by Ivo Buchhalter, from the University Hospital Heidelberg in Germany.
TMB is increasingly used as a marker for predicting which patients will have a positive response to immunotherapies. Evidence shows a higher mutational burden correlates to improved survival benefits in patients receiving checkpoint inhibitor therapies, as more mutations heighten the chance of immune system activation.
While research studies used whole-exome sequencing (WES) for measuring TMB, WES is not feasible for routine clinical use given cost, computational complexity, and turnaround time. Panels are commercially available, but there has been little evidence suggesting the ideal sizes or methods of calculating TMB.
This study assessed the performance parameters of two panels from Illumina (San Diego), the TruSight Tumor 170 (TST 170) and TruSight Oncology 500 (TSO 500), a forthcoming panel. The Germna-based reserachers conducted silico analysis (using combinatorial calculations and extensive simulations) using The Cancer Genome Atlas data for 8,371 tumors, across 25 different cancer types, including lung, melanoma, pancreatic, breast, head, and neck, gynecological, and colorectal cancers.
Somatic variants were extracted and annotated using Annovar and Gencode. Only mutations falling into regions included in the Agilent SureSelect V4 enrichment kit were considered. The vendor provided regions covered by the commercial panels. Sequencing panels of sizes 0.5, 1, 1.5, 2, 3, 5 and 10 Mbp were simulated.
The researchers found that the precision of TMB estimation considerably depends on the size of the targeted sequencing panel. Smaller panels result in imprecise measurement of TMB, especially for tumors with low TMB values. Thus, small panels, the authors say are “clinically suboptimal” for patient stratification and response prediction.
“Our analyses showed that ‘size does matter’ with an optimal panel size being reached between 1.5 and 3 Mbp considering the benefit-cost ratio,” write the authors led by Ivo Buchhalter, from the University Hospital Heidelberg in Germany.
The authors add that inclusion of all point mutations (instead of only missense mutations) is both possible and recommended to enhance precision in calculating the TMB.
Since TMB needs to be extrapolated from the number of mutations detected in the sequenced region, for panels smaller than 1 Mbp, the thresholds for the separation of hypermutated from non-hypermutated tumors fall below 10 mutations and will be inaccurate for classification of tumors with TMB close to the threshold, the authors say. In contrast, larger gene panels were associated with higher cutoff values and resultantly, increased robustness and reliability.
“To the best of my knowledge, this is the first publication to use large-scale computational analysis to evaluate how size of the gene panel, and the type of mutations included in the calculations, impacts measurement of TMB,” said Phil Febbo, M.D., chief medical officer at Illumina, in a statement. “Of course, algorithms for mutation calling and filters to remove artifacts and germline variants are also components of accurate TMB, but this paper will contribute significantly to ongoing efforts working to standardize TMB as a biomarker.”
Takeaway: Panel size is a critical determinant of test performance and cutoff values for determining the TMB.
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