Clinical Pan-Cancer Assessment of Mismatch Repair Deficiency Using Tumor-Only, Targeted Next-Generation Sequencing

Author:

Albayrak Adem1,Garrido-Castro Ana C.23,Giannakis Marios234,Umeton Renato15,Manam Monica Devi6,Stover Elizabeth H.23,Porter Rebecca L.23,Johnson Bruce E.23,Liaw Kai-Li7,Amonkar Mayur7,Church Alanna J.38,Janeway Katherine A.9,Nowak Jonathan A.36,Sholl Lynette36,Lin Nancy U.23,Johnson Jason M.1

Affiliation:

1. Informatics and Analytics Department, Dana-Farber Cancer Institute, Boston, MA

2. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA

3. Harvard Medical School, Boston, MA

4. Broad Institute of MIT and Harvard, Cambridge, MA

5. Massachusetts Institute of Technology, Cambridge, MA

6. Department of Pathology, Brigham and Women’s Hospital, Boston, MA

7. Merck, Kenilworth, NJ

8. Department of Pathology, Boston Children’s Hospital, Boston, MA

9. Department of Pediatric Oncology, Dana-Farber Cancer Institute, Boston, MA

Abstract

PURPOSE Given regulatory approval of immune checkpoint inhibitors in patients with mismatch repair–deficient (MMR-D) cancers agnostic to tumor type, it has become important to characterize occurrence of MMR-D and develop cost-effective screening approaches. Using a next-generation sequencing (NGS) panel (OncoPanel), we developed an algorithm to identify MMR-D frequency in tumor samples and applied it in a clinical setting with pathologist review. METHODS To predict MMR-D, we adapted methods described previously for use in NGS panels, which assess patterns of single base-pair insertion or deletion events occurring in homopolymer regions. Tumors assayed with OncoPanel between July 2013 and July 2018 were included. For tumors tested after June 2017, sequencing results were presented to pathologists in real time for clinical MMR determination, in the context of tumor mutation burden, other mutational signatures, and clinical data. RESULTS Of 20,301 tumors sequenced, 2.7% (553) were retrospectively classified as MMR-D by the algorithm. Of 4,404 samples with pathologist sign-out of MMR status, the algorithm classified 147 (3.3%) as MMR-D: in 116 cases, MMR-D was confirmed by a pathologist, five cases were overruled by the pathologist, and 26 were assessed as indeterminate. Overall, the highest frequencies of OncoPanel-inferred MMR-D were in endometrial (21%; 152/723), colorectal (9.7%; 169/1,744), and small bowel (9.3%; 9/97) cancers. When algorithm predictions were compared with historical MMR immunohistochemistry or polymerase chain reaction results in a set of 325 tumors sequenced before initiation of pathologist assessment, the overall sensitivity and specificity of the algorithm were 91.1% and 98.2%, respectively. CONCLUSION We show that targeted, tumor-only NGS can be leveraged to determine MMR signatures across tumor types, suggesting that broader biomarker screening approaches may have clinical value.

Publisher

American Society of Clinical Oncology (ASCO)

Subject

Cancer Research,Oncology

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