Harmonization of tumor mutational burden quantification and association with response to immune checkpoint blockade in non-small-cell lung cancer Journal Article
| Authors: | Vokes, N. I.; Liu, D.; Ricciuti, B.; Jimenez-Aguilar, E.; Rizvi, H.; Dietlein, F.; He, M. X.; Margolis, C. A.; Elmarakeby, H. A.; Girshman, J.; Adeni, A.; Sanchez-Vega, F.; Schultz, N.; Dahlberg, S.; Zehir, A.; Janne, P. A.; Nishino, M.; Umeton, R.; Sholl, L. M.; Van Allen, E. M.; Hellmann, M. D.; Awad, M. M. |
| Article Title: | Harmonization of tumor mutational burden quantification and association with response to immune checkpoint blockade in non-small-cell lung cancer |
| Abstract: | PURPOSE Heterogeneity in tumor mutational burden (TMB) quantification across sequencing platforms limits the application and further study of this potential biomarker of response to immune checkpoint inhibitors (ICIs). We hypothesized that harmonization of TMB across platforms would enable integration of distinct clinical data sets to better characterize the association between TMB and ICI response. METHODS Cohorts of patients with non-small-cell lung cancer sequenced by 1 of 3 targeted panels or by wholeexome sequencing (WES) were compared (N = 7,297). TMB was calculated uniformly and compared across cohorts. TMB distributions were harmonized by applying a normal transformation followed by standardization to z scores. In subcohorts of patients treated with ICIs (Dana-Farber Cancer Institute n = 272; Memorial Sloan Kettering Cancer Center n = 227), the association between TMB and outcome was assessed. Durable clinical benefit (DCB) was defined as responsive/stable disease lasting ≥ 6 months. RESULTS TMB values were higher in the panel cohorts than in the WES cohort. Average mutation rates per gene were highly concordant across cohorts (Pearson's correlation coefficients, 0.842-0.866). Subsetting the WES cohort by gene panels only partially reproduced the observed differences in TMB. Standardization of TMB into z scores harmonized TMB distributions and enabled integration of the ICI-treated subcohorts. Simulations indicated that cohorts . 900 are necessary for this approach. TMB did not associate with response in neversmokers or patients who harbor targetable driver alterations, although these analyses were underpowered. An increase of TMB thresholds increased DCB rate, but DCB rates within deciles varied. Receiver operating characteristic curves yielded an area under the curve of 0.614, with no natural inflection point. CONCLUSION The z score conversion harmonizes TMB values and enables integration of data sets derived from different sequencing panels. Clinical and biologic features may provide context to the clinical application of TMB and warrant additional study. © 2019 by American Society of Clinical Oncology. |
| Keywords: | adult; cancer survival; controlled study; treatment response; aged; unclassified drug; gene mutation; major clinical study; comparative study; cancer immunotherapy; progression free survival; cohort analysis; simulation; standardization; quantitative analysis; immunomodulating agent; mutation rate; non small cell lung cancer; immune checkpoint inhibitor; never smoker; human; male; female; priority journal; article; whole exome sequencing; mutational load |
| Journal Title: | JCO Precision Oncology |
| Volume: | 3 |
| ISSN: | 2473-4284 |
| Publisher: | American Society of Clinical Oncology |
| Date Published: | 2019-11-12 |
| Language: | English |
| DOI: | 10.1200/po.19.00171 |
| PROVIDER: | scopus |
| PMCID: | PMC6907021 |
| PUBMED: | 31832578 |
| DOI/URL: | |
| Notes: | Article -- Source: Scopus |
Altmetric
Citation Impact
BMJ Impact Analytics
Related MSK Work