Abstract P4-05-01: Massively parallel sequencing analysis of microsatellite instability in breast cancer
Authors: Selenica Pier , Pareja Fresia , Ferrando Lorenzo , Brown David N , Riaz Nadeem , Weigelt Britta , Drago Joshua Z , Robson Mark E , Razavi Pedram , Chandarlapaty Sarat , Reis-Filho Jorge S 
Published: March 2020

Abstract
Introduction: Breast cancers (BCs) with microsatellite instability (MSI)/DNA mismatch repair (MMR) deficiency are rare. Their identification is key, given that these tumors might be sensitive to immune checkpoint blockade. Here we sought to define the characteristics of primary and metastatic MSI-high (MSI-H) BCs using massively parallel sequencing.
Materials and methods: To define MSI, MSISensor was applied to MSK-IMPACT targeted sequencing data of 918 primary BCs (pBCs) and 1,000 metastatic BCs (mBCs), and MSISensor and MANTIS to whole-exome sequencing (WES) data of 1,084 pBCs from The Cancer Genome Atlas (TCGA) BC project. BCs were classified as MSI-H if they displayed an MSISensor score ≥3.5 for WES or ≥10 for targeted sequencing data, or a MANTIS score ≥0.4 for WES data. The dominant mutational signature was inferred using SigMA in cases harboring at least 5 single nucleotide variants (SNVs). Mann-Whitney U and Fisher’s exact t-tests were employed for statistical analyses.
Results: MSISensor classified 0.3% (3/903) of pBCs and 0.3% (3/965) of the mBCs subjected to MSK-IMPACT sequencing as MSI-H. The MSI-H pBCs were invasive ductal carcinomas (IDC), preferentially ER-positive/HER2-negative (66.6%). Compared to MSS pBCs, MSI-H pBCs displayed a higher tumor mutational burden (TMB; 11.2 vs 2.6 somatic mutations) and were enriched for dominant MMR mutational signatures 20 or 26 (33% vs 1.1%). MSI-H mBCs were all ER-positive/HER2-negative IDCs, displayed similar TMBs, percentage of small insertions and deletions (indels) and fraction of the genome altered (FGA) as compared to MSS mBCs. Only one of the three MSI-H mBCs had enough SNVs for inference of a dominant mutational signature, which was aging. MSISensor and MANTIS classified 1.5% (11/735) and 1.8% (15/836) of pBCs from TCGA as MSI-H. We observed a moderate agreement between MSISensor and MANTIS (Cohen’s Kappa = 0.552) with 1% (7/735) of pBCs being classified as MSI-H by both algorithms. pBCs from TCGA classified as MSI by either MSISensor or MANTIS were IDCs (90.9% and 85.7%, respectively) and invasive lobular carcinoma (ILC; 9.1% and 14.3%, respectively), and were either ER-positive/HER2-negative (45.5% and 42.9%, respectively) or ER-negative/HER2-negative (45.5% and 42.9%, respectively). These MSI-H pBCs (TCGA) displayed a higher TMB (MSISensor: 12.7 vs 0.8; MANTIS: 3.6 vs 0.8; both P&lt;0.01), percentage of indels (MSISensor: 8.2% vs 4.7%; MANTIS: 8.1% vs 4.8%, both P&lt;0.01) and were enriched for dominant MMR mutational signatures 15, 20 or 26 (MSISensor: 63.6% vs 1.4%, MANTIS: 46.7% vs 1.2%, both P&lt;0.01) than MSS pBCs. pBCs from TCGA classified as MSI by both MSISensor and MANTIS were IDCs (85.7%) and ILCs (14.3%), and were preferentially ER-positive/HER2-negative or ER-negative/HER2-negative (42.9%, each). Compared to MSS pBCs, MSI-H pBCs from TCGA displayed a higher TMB (17.4 MSI-H vs 0.8 MSS; P&lt;0.01), percentage of indels (12.1% MSI-H vs 4.7% MSS; P&lt;0.01) and an enrichment for dominant MMR mutational signatures 15, 20 or 26 (87.5% MSI-H vs 1.4% MSS; P&lt;0.01).
Conclusions: We observed a moderate agreement between different MSI detection algorithms in the classification of pBCs as MSI-H based on WES analysis. pBCs classified as MSI-H were of common histologic types, either ER-positive/HER2-negative or ER-negative/HER2-negative, and displayed features characteristic of MSI, including a high TMB, high percentage of indels and an enrichment for MMR deficiency mutational signatures. mBCs classified as MSI-H by targeted capture sequencing were found to be of ER-positive/HER2-negative phenotype.
Citation Format: Pier Selenica, Fresia Pareja, Lorenzo Ferrando, David N Brown, Nadeem Riaz, Britta Weigelt, Joshua Z Drago, Mark E Robson, Pedram Razavi, Sarat Chandarlapaty, Jorge S Reis-Filho. Massively parallel sequencing analysis of microsatellite instability in breast cancer [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P4-05-01.