Abstract A094: MSIClass - Identification and classification of microsatellite unstable tumors using cell-free DNA from ultra low pass sequencing
Authors: Maruvka Yosef E. , Frazer Ruslana , Grimsby Jonna , Seventer Emily E Van , Cibulskis Carrie , Adalsteinsson Viktor , Corcoran Ryan , Getz Gad 
Published: March 2020

Abstract
The acquisition of mismatch repair deficiency is common in many tumor types. A unique subtype of mismatch repair deficient tumors, called tumors with microsatellite instability (MSI), has been recently approved for treatment with PD-1\PD-L1 blockade immunotherapy. Therefore, developing a quick, inexpensive, and easy-to-implement technique for classifying tumors as MSI is of utmost importance. Here, we describe such a method using next-generation sequencing data, and show that it can detect MSI from cell-free DNA (cfDNA), even when there is low fraction of tumor DNA in the cfDNA. We first analyzed the unique mutational features of MSI vs. microsatellite stable (MSS) tumors. Using our SignatureAnalyzer tool, we analyzed the signatures of the different insertions and deletions within microsatellite loci (MS-indels), and found that MSI tumors harbor elevated MS-indels of certain types, which we further validated using whole genome sequencing data from The Cancer Genome Atlas. We next used this information to develop a method (MSIClass) that analyzes the WGS data of a given sample by capturing the features unique to MSI tumors. This method assigns each sample a score based on aggregating information from all MS loci simultaneously; since MSIClass is a sample-based tool, it can call the MSI status of tumor samples that have no patient-matched normal sample. We further demonstrate that MSIClass requires minimal genomic information; indeed, sequencing coverage as low as 0.05x (current sequencing cost of ~$2/sample) is sufficient for accurate classification by MSIClass. Using in silico and in vitro DNA mixing we show that MSIClass can accurately identify MSI cases in very low purity cases, at 0.1% tumor DNA (using 0.5x sequencing coverage). We show that MSIClass, applied on cfDNA, could accurately classify 29 colon cases -- 22 MSS and 7 MSI cases, 3 of which are early stage disease and with low tumor content. We then applied MSIClass to ~2000 cfDNA samples from various tumor types and found MSI cases in tumors that are not associated with MSI such as breast. These results demonstrate that MSIClass is an inexpensive MSI test that can be applied in various cases: bulk sequencing where a matched normal is not available, cases of very low purity tumors, and even using cfDNA from blood in cases a biopsy is not available or possible. Finally, this methodology can be the basis for monitoring minimal residual disease, and potential be used for early detection of MSI tumors.
Citation Format: Yosef E. Maruvka, Ruslana Frazer, Jonna Grimsby, Emily E Van Seventer, Carrie Cibulskis, Viktor Adalsteinsson, Ryan Corcoran, Gad Getz. MSIClass - Identification and classification of microsatellite unstable tumors using cell-free DNA from ultra low pass sequencing [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference on Molecular Targets and Cancer Therapeutics; 2019 Oct 26-30; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2019;18(12 Suppl):Abstract nr A094. doi:10.1158/1535-7163.TARG-19-A094