Establishing guidelines to harmonize tumor mutational burden (TMB): in silico assessment of variation in TMB quantification across diagnostic platforms: phase I of the Friends of Cancer Research TMB Harmonization Project.

BACKGROUND: Tumor mutational burden (TMB), defined as the number of somatic mutations per megabase of interrogated genomic sequence, demonstrates predictive biomarker potential for the identification of patients with cancer most likely to respond to immune checkpoint inhibitors. TMB is optimally calculated by whole exome sequencing (WES), but next-generation sequencing targeted panels provide TMB estimates in a time-effective and cost-effective manner. However, differences in panel size and gene coverage, in addition to the underlying bioinformatics pipelines, are known drivers of variability in TMB estimates across laboratories. By directly comparing panel-based TMB estimates from participating laboratories, this study aims to characterize the theoretical variability of panel-based TMB estimates, and provides guidelines on TMB reporting, analytic validation requirements and reference standard alignment in order to maintain consistency of TMB estimation across platforms. METHODS: Eleven laboratories used WES data from The Cancer Genome Atlas Multi-Center Mutation calling in Multiple Cancers (MC3) samples and calculated TMB from the subset of the exome restricted to the genes covered by their targeted panel using their own bioinformatics pipeline (panel TMB). A reference TMB value was calculated from the entire exome using a uniform bioinformatics pipeline all members agreed on (WES TMB). Linear regression analyses were performed to investigate the relationship between WES and panel TMB for all 32 cancer types combined and separately. Variability in panel TMB values at various WES TMB values was also quantified using 95% prediction limits. RESULTS: Study results demonstrated that variability within and between panel TMB values increases as the WES TMB values increase. For each panel, prediction limits based on linear regression analyses that modeled panel TMB as a function of WES TMB were calculated and found to approximately capture the intended 95% of observed panel TMB values. Certain cancer types, such as uterine, bladder and colon cancers exhibited greater variability in panel TMB values, compared with lung and head and neck cancers. CONCLUSIONS: Increasing uptake of TMB as a predictive biomarker in the clinic creates an urgent need to bring stakeholders together to agree on the harmonization of key aspects of panel-based TMB estimation, such as the standardization of TMB reporting, standardization of analytical validation studies and the alignment of panel-based TMB values with a reference standard. These harmonization efforts should improve consistency and reliability of panel TMB estimates and aid in clinical decision-making.

Mutations in the Kinase Domain of the HER2/ERBB2 Gene Identified in a Wide Variety of Human Cancers.

The HER2 (official name ERBB2) gene encodes a membrane receptor in the epidermal growth factor receptor family amplified and overexpressed in adenocarcinoma. Activating mutations also occur in several cancers. We report mutation analyses of the HER2 kinase domain in 7497 histologically diverse cancers. Forty-five genes, including the kinase domain of HER2 with HER2 IHC and dual in situ hybridization, were analyzed in tumors from 7497 patients with cancer, including 850 breast, 770 colorectal, 910 non-small cell lung, 823 uterine or cervical, 1372 ovarian, and 297 pancreatic cancers, as well as 323 melanomas and 2152 other solid tumors. Sixty-nine HER2 kinase domain mutations were identified in tumors from 68 patients (approximately 1% of all cases, ranging from absent in sarcomas to 4% in urothelial cancers), which included previously published activating mutations and 13 novel mutations. Fourteen cases with coexisting HER2 mutation and amplification and/or overexpression were identified. Fifty-two of 68 patients had additional mutations in other analyzed genes, whereas 16 patients (23%) had HER2 mutations identified as the sole driver mutation. HER2 mutations coexisted with HER2 gene amplification and overexpression and with mutations in other functionally important genes. HER2 mutations were identified as the only driver mutation in a significant proportion of solid cancers. Evaluation of anti-HER2 therapies in nonamplified, HER2-mutated cancers is warranted.