Characterization of MET Exon 14 Skipping Alterations (in NSCLC) and Identification of Potential Therapeutic Targets Using Whole Transcriptome Sequencing

So Yeon Kim; Jun Yin; Stephen Bohlman; Phillip Walker; Sanja Dacic; Chul Kim; Hina Khan; Stephen V Liu; Patrick C Ma; Misako Nagasaka; Karen L Reckamp; Jim Abraham; Dipesh Uprety; Feng Wang; Joanne Xiu; Jian Zhang; Haiying Cheng; Balazs Halmos

doi:10.1016/j.jtocrr.2022.100381

Characterization of MET Exon 14 Skipping Alterations (in NSCLC) and Identification of Potential Therapeutic Targets Using Whole Transcriptome Sequencing

JTO Clin Res Rep. 2022 Jul 22;3(9):100381. doi: 10.1016/j.jtocrr.2022.100381. eCollection 2022 Sep.

Authors

So Yeon Kim^{1

2}, Jun Yin³, Stephen Bohlman¹, Phillip Walker³, Sanja Dacic², Chul Kim⁴, Hina Khan⁵, Stephen V Liu⁴, Patrick C Ma⁶, Misako Nagasaka⁷, Karen L Reckamp⁸, Jim Abraham³, Dipesh Uprety⁹, Feng Wang¹, Joanne Xiu³, Jian Zhang³, Haiying Cheng¹, Balazs Halmos¹

Affiliations

¹ Department of Medical Oncology, Montefiore Medical Center, Albert Einstein Cancer Center, Bronx, New York.
² Yale School of Medicine, New Haven, Connecticut.
³ Caris Life Sciences, Phoenix, Arizona.
⁴ Georgetown Lombardi Comprehensive Cancer Center, Washington, District of Columbia.
⁵ Warren Alpert Medical School of Brown University, Providence, Rhode Island.
⁶ Penn State Cancer Institute, Hershey, Pennsylvania.
⁷ UCI School of Medicine, Orange, California.
⁸ Cedars-Sinai Medical Center, Los Angeles, California.
⁹ Karmanos Cancer Center, Detroit, Michigan.

Abstract

Introduction: Genomic alterations in the juxtamembrane exon 14 splice sites in NSCLC lead to increased MET stability and oncogenesis. We present the largest cohort study of MET Exon 14 (METex14) using whole transcriptome sequencing.

Methods: A total of 21,582 NSCLC tumor samples underwent complete genomic profiling with next-generation sequencing of DNA (592 Gene Panel, NextSeq, whole exome sequencing, NovaSeq) and RNA (NovaSeq, whole transcriptome sequencing). Clinicopathologic information including programmed death-ligand 1 and tumor mutational burden were collected and RNA expression for mutation subtypes and MET amplification were quantified. Immunogenic signatures and potential pathways of invasion were characterized using single-sample gene set enrichment analysis and mRNA gene signatures.

Results: A total of 533tumors (2.47%) with METex14 were identified. The most common alterations were point mutations (49.5%) at donor splice sites. Most alterations translated to increased MET expression, with MET co-amplification resulting in synergistic increase in expression (q < 0.05). Common coalterations were amplifications of MDM2 (19.0% versus 1.8% wild-type [WT]), HMGA2 (13.2% versus 0.98% WT), and CDK4 (10.0% versus 1.5% WT) (q < 0.05). High programmed death-ligand 1 > 50% (52.5% versus 27.3% WT, q < 0.0001) and lower proportion of high tumor mutational burden (>10 mutations per megabase, 8.3% versus 36.7% WT, p < 0.0001) were associated with METex14, which were also enriched in both immunogenic signatures and immunosuppressive checkpoints. Pathways associated with METex14 included angiogenesis and apical junction pathways (q < 0.05).

Conclusions: METex14 splicing alterations and MET co-amplification translated to higher and synergistic MET expression at the transcriptomic level. High frequencies of MDM2 and CDK4 co-amplifications and association with multiple immunosuppressive checkpoints and angiogenic pathways provide insight into potential actionable targets for combination strategies in METex14 NSCLC.

Keywords: Immune signatures; MDM2; METex14; Non–small cell lung cancer; RNA expression; Whole transcriptome sequencing.

Grants and funding

UL1 TR001863/TR/NCATS NIH HHS/United States