[2081] Quantitative Assessment of Mutant Allele Burden in Solid Tumors by Semiconductor Based Multi-Gene Next Generation Sequencing

Bryce P Portier, Rajyalakshmi Luthra, Rajesh Singh, Mark Routbort, Brian Handal, Neeli Reddy, Bedia A Barkoh, Zhuang Zuo, L Jeffrey Medeiros, Ken Aldape, Keyur P Patel. MD Anderson, Houston, TX

Background: The ability of next generation sequencing (NGS) to provide a quantitative assessment of mutant allele burden in multiple genes provides a significant advantage over conventional qualitative genotyping platforms such as Sanger sequencing or quantitative platforms with limited multiplexing capabilities. Quantitative assessments of mutatant allele burden are likely to yield significant insights into tumor biology with regards to tumor heterogeneity and clonal evolution. In this study, we assessed the quantitative ability of semiconductor based NGS to that of an alternate quantitative platform and determined correlation with morphologic assessment of tumor percentage.
Design: DNA was isolated from 45 microdissected, formalin fixed paraffin embedded solid tumors with a somatic mutation detected by a quantitative primer-extension MALDI-TOF assay (PE-MALDI). Tumor percentages ranged from 20-95% as verified by pathologist consensus. The PE-MALDI assay interrogated hotspot mutations in 11-genes. NGS was performed utilizing the 46-gene Ion AmpliSeq™ Cancer Panel (Life Technologies, CA, USA). Mutant allele burden was calculated as a ratio of mutant allele to combined mutant and wild type alleles. Mutant allele burden in BRAF, KRAS, MET and NRAS were used for the correlation study. Statistical analysis was performed using GraphPad Prism 6.0.
Results: NGS-based estimation of mutant allele burden ranged from 13.6% to 79.1% for all 45 solid tumor samples (Individual genes: BRAF (13.6-79.1%), KRAS (14.1-66.5%), NRAS (15.1-78.1%), and MET (46.1-57.7%)). NGS detected all mutant alleles identified by PE-MALDI (100% concordance). The correlation between NGS and PE-MALDI for all interrogated mutations was r2= 0.85 (P< 0.0001). The correlation between NGS and PE-MALDI for individual genes was BRAF r2= 0.90, KRAS r2= 0.94, and NRAS r2= 0.92 (P< 0.0001). Correlation for MET (n=6) did not reach statistical significance r2= 0.60 (P= 0.071). Pathologist based morphologic assessment of tumor percentage did not correlate to the percent mutant alleles detected by either NGS (P=0.20) or PE-MALDI (P=0.61).
Conclusions: NGS-based multi-gene sequencing using nanogram amounts of DNA allows quantitative assessment of mutant allele burden, comparable to lower throughput quantitative mutation analysis platforms. The ability to use high-throughput NGS to quantitatively measure somatic mutations in solid tumors will rapidly advance our basic knowledge of tumor biology and ultimately will advance our ability to offer personalized cancer care.
Category: Techniques

Tuesday, March 5, 2013 1:00 PM

Proffered Papers: Section E, Tuesday Afternoon

 

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