Abstract 5598: Correlating molecular and histopathologic tumor purity: An analysis of 816 patients

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA Background: Clinical cancer samples frequently have significant contamination by stromal cells that increase the difficulty of mutation calling. Histopathologic light microscopy (LM) estimation of purity is commonly used to qualify samples for molecular testing. With large datasets generated by current technologies, more accurate estimations of purity may be facilitated by use of SNP chip (SNP) or sequencing (seq) data. We present a computational framework that considers a variety of technical factors, including percent (%) tumor, seq quality, and mutation type that impact the detection and evaluation of somatic mutations reported to patients. Methods: LCCC1108 (“The development of a tumor molecular analyses program and its uses to support treatment decisions”) is a registry study for cancer patients that performs targeted sequencing with a panel of >200 clinically actionable genes for clinical use. A subset of patients have additional analyses performed including DNA SNP and RNA seq. Any clinically actionable variant is orthogonally confirmed in a CLIA-certified lab. Results: As of 12/1/2013, 816 patients have enrolled. 350 cases have both molecular and LM estimates of tumor purity. Agreement between molecular estimates of % tumor and LM review was low (Pearson's correlation coefficient 0.16 for the most favorable comparison). No clear etiology could explain the low agreement, although examination of extreme cases in which LM approached 100% tumor and molecular estimates approached zero generally included tumors with low rates of molecular alterations (e.g. adenoid cystic carcinoma, chronic myelogenous leukemia). Additionally, independent assessment of % tumor by molecular analysis such as SNP vs. seq also had low agreement (0.13), although a clear pattern could be seen in the disagreement for certain cases. Methods that rely heavily on copy number(CN) alterations often under-predicted estimates of % tumor relative to methods that relied on the mutant allele fraction (MAF) in cases where there were few CN alterations but where point mutations predominated. Excluding these outliers, the agreement was high and molecular estimates of % tumor more reproducible. Most molecular tumor estimates performed more poorly or failed as the % stromal infiltration rose above 50%. Seq estimates of % tumor tended to be noisier for coverage <200x. % tumor as a function of the MAF of actionable mutations was useful in cases where a canonical mutation (e.g. p53) could be used to estimate % tumor as well as homozygous vs heterozygous mutations of actionable genes. Conclusion: In clinical practice, accurate estimates of % tumor spanning the clinical spectrum are critical for somatic mutation calling. Pure analytic approaches to estimates of % tumor may fail in tumors with low rates of somatic mutation and CN alteration. Ultimately, a combination of methods will be required to describe samples for optimal variant detection. Citation Format: Heejoon Jo, Nirali M. Patel, Karen E. Weck, David A. Eberhard, D. Neil Hayes, Joel S. Parker, Michele Hayward, Ashley Salazar, Juneko E. Grilley-Olson. Correlating molecular and histopathologic tumor purity: An analysis of 816 patients. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5598. doi:10.1158/1538-7445.AM2014-5598