Toward best practice in cancer mutation detection with whole-genome and whole-exome sequencing.

Clinical applications of precision oncology require accurate tests that can distinguish true cancer-specific mutations from errors introduced at each step of next-generation sequencing (NGS). To date, no bulk sequencing study has addressed the effects of cross-site reproducibility, nor the biological, technical and computational factors that influence variant identification. Here we report a systematic interrogation of somatic mutations in paired tumor-normal cell lines to identify factors affecting detection reproducibility and accuracy at six different centers. Using whole-genome sequencing (WGS) and whole-exome sequencing (WES), we evaluated the reproducibility of different sample types with varying input amount and tumor purity, and multiple library construction protocols, followed by processing with nine bioinformatics pipelines. We found that read coverage and callers affected both WGS and WES reproducibility, but WES performance was influenced by insert fragment size, genomic copy content and the global imbalance score (GIV; G > T/C > A). Finally, taking into account library preparation protocol, tumor content, read coverage and bioinformatics processes concomitantly, we recommend actionable practices to improve the reproducibility and accuracy of NGS experiments for cancer mutation detection.

Establishing community reference samples, data and call sets for benchmarking cancer mutation detection using whole-genome sequencing.

The lack of samples for generating standardized DNA datasets for setting up a sequencing pipeline or benchmarking the performance of different algorithms limits the implementation and uptake of cancer genomics. Here, we describe reference call sets obtained from paired tumor-normal genomic DNA (gDNA) samples derived from a breast cancer cell line-which is highly heterogeneous, with an aneuploid genome, and enriched in somatic alterations-and a matched lymphoblastoid cell line. We partially validated both somatic mutations and germline variants in these call sets via whole-exome sequencing (WES) with different sequencing platforms and targeted sequencing with >2,000-fold coverage, spanning 82% of genomic regions with high confidence. Although the gDNA reference samples are not representative of primary cancer cells from a clinical sample, when setting up a sequencing pipeline, they not only minimize potential biases from technologies, assays and informatics but also provide a unique resource for benchmarking 'tumor-only' or 'matched tumor-normal' analyses.

PD-L1 Immunohistochemistry Assays for Lung Cancer: Results from Phase 1 of the Blueprint PD-L1 IHC Assay Comparison Project.

INTRODUCTION: The Blueprint Programmed Death Ligand 1 (PD-L1) Immunohistochemistry (IHC) Assay Comparison Project is an industrial-academic collaborative partnership to provide information on the analytical and clinical comparability of four PD-L1 IHC assays used in clinical trials. METHODS: A total of 39 NSCLC tumors were stained with four PD-L1 IHC assays (22C3, 28-8, SP142, and SP263), as used in the clinical trials. Three experts in interpreting their respective assays independently evaluated the percentages of tumor and immune cells staining positive at any intensity. Clinical diagnostic performance was assessed through comparisons of patient classification above and below a selected expression cutoff and by agreement using various combinations of assays and cutoffs. RESULTS: Analytical comparison demonstrated that the percentage of PD-L1-stained tumor cells was comparable when the 22C3, 28-8, and SP263 assays were used, whereas the SP142 assay exhibited fewer stained tumor cells overall. The variability of immune cell staining across the four assays appears to be higher than for tumor cell staining. Of the 38 cases, 19 (50.0%) were classified above and five (13%) were classified below the selected cutoffs of all assays. For 14 of the 38 cases (37%), a different PD-L1 classification would be made depending on which assay/scoring system was used. CONCLUSIONS: The Blueprint PD-L1 IHC Assay Comparison Project revealed that three of the four assays were closely aligned on tumor cell staining whereas the fourth showed consistently fewer tumor cells stained. All of the assays demonstrated immune cell staining, but with greater variability than with tumor cell staining. By comparing assays and cutoffs, the study indicated that despite similar analytical performance of PD-L1 expression for three assays, interchanging assays and cutoffs would lead to "misclassification" of PD-L1 status for some patients. More data are required to inform on the use of alternative staining assays upon which to read different specific therapy-related PD-L1 cutoffs.