Aligning tumor mutational burden (TMB) quantification across diagnostic platforms: phase II of the Friends of Cancer Research TMB Harmonization Project.

BACKGROUND: Tumor mutational burden (TMB) measurements aid in identifying patients who are likely to benefit from immunotherapy; however, there is empirical variability across panel assays and factors contributing to this variability have not been comprehensively investigated. Identifying sources of variability can help facilitate comparability across different panel assays, which may aid in broader adoption of panel assays and development of clinical applications. MATERIALS AND METHODS: Twenty-nine tumor samples and 10 human-derived cell lines were processed and distributed to 16 laboratories; each used their own bioinformatics pipelines to calculate TMB and compare to whole exome results. Additionally, theoretical positive percent agreement (PPA) and negative percent agreement (NPA) of TMB were estimated. The impact of filtering pathogenic and germline variants on TMB estimates was assessed. Calibration curves specific to each panel assay were developed to facilitate translation of panel TMB values to whole exome sequencing (WES) TMB values. RESULTS: Panel sizes >667 Kb are necessary to maintain adequate PPA and NPA for calling TMB high versus TMB low across the range of cut-offs used in practice. Failure to filter out pathogenic variants when estimating panel TMB resulted in overestimating TMB relative to WES for all assays. Filtering out potential germline variants at >0% population minor allele frequency resulted in the strongest correlation to WES TMB. Application of a calibration approach derived from The Cancer Genome Atlas data, tailored to each panel assay, reduced the spread of panel TMB values around the WES TMB as reflected in lower root mean squared error (RMSE) for 26/29 (90%) of the clinical samples. CONCLUSIONS: Estimation of TMB varies across different panels, with panel size, gene content, and bioinformatics pipelines contributing to empirical variability. Statistical calibration can achieve more consistent results across panels and allows for comparison of TMB values across various panel assays. To promote reproducibility and comparability across assays, a software tool was developed and made publicly available.

Myc overexpression brings out unexpected antiapoptotic effects of miR-34a.

Downregulation of microRNA-34a by Myc is known to be essential for tumorigenesis and improve tumor-cell survival. Conversely, upregulation of miR-34a by p53 is thought to enhance its acetylation and activity and contribute to the pro-apoptotic effects of this tumor suppressor. We sought to determine whether restoration of miR-34a levels in B-lymphoid cells with Myc overexpression would aid therapeutic apoptosis. Unexpectedly, delivery of miR-34a, which doesn't target p53 directly, severely compromised steady-state p53 levels. This effect was preceded and mediated by direct targeting of Myc, which sustained p53 protein levels via the Arf-Hdm2 pathway. As a result, in the presence of Myc, miR-34a inhibited p53-dependent bortezomib-induced apoptosis as efficiently as anti-p53 small interfering RNA. Conversely, inhibition of miR-34a using antisense RNA sensitized lymphoma cells to therapeutic apoptosis. Thus, in tumors with deregulated Myc expression, miR-34a confers drug resistance and could be considered a therapeutic target.