Abstract 165P
Background
Novel compounds targeting the c-Met protein (also known as MET) are being evaluated in patients (pts) with non-small cell lung cancer (NSCLC). These include anti–c-Met antibody-drug conjugates under investigation in specific NSCLC subpopulations based on c-Met protein overexpression (OE) levels. However, optimal timing of c-Met protein OE assessment remains uncertain (i.e., before treatment initiation or based on previous samples). We investigated stability of c-Met protein OE over time in pts with non-squamous NSCLC.
Methods
Pts with a sample taken at the initial diagnosis (ID) and post-treatment (PT) were included in this translational study. The primary objective was to assess the consistency of c-Met protein OE (≥25% of tumor cells with 3+ staining) at ID and PT. Secondary objectives included assessing stability of high c-Met protein OE (≥50% 3+ tumor cells) and establishing interobserver consistency of c-Met protein OE determination. c-Met protein OE was assessed by immunohistochemistry using the Ventana MET SP44 assay. Agreement of c-Met OE status across timepoints was conducted using Cohen's kappa coefficient (κ).
Results
In total, 195 pts were included in this analysis. Median age was 66 years (range 23–88), 60.0% were male, 95.9% had adenocarcinoma, and 36.2% had EGFR mutation at ID. At ID, 34 (17.4%) pts had c-Met OE and 29 (14.9%) pts had high c-Met OE. Agreement of c-Met OE across ID and PT in paired samples was fair (κ = 0.3388), with an overall percentage agreement of 79.0%. The stability results were similar in c-Met OE–high pts (κ =0.3520), considering that most c-Met OE–positive pts were OE high at ID or at PT. Inter-observer agreement was excellent (100% for both c-Met OE and high c-Met OE).
Conclusions
c-Met OE status remained unchanged between ID and PT in the majority of pts; therefore, the diagnostic sample may effectively establish c-Met protein expression status. In total, 21% of pts experienced modified c-Met status throughout tumor progression, possibly influenced by treatments administered or EGFR mutational status. Hence, c-Met investigations at relapse may potentially improve pt management. Ongoing analyses will provide further information on the contributing factors to the concordance rate.
Clinical trial identification
Editorial acknowledgement
Medical writing support was provided by Joanne Franklin, PhD, CMPP, from Aptitude Health, The Hague, the Netherlands, and funded by AbbVie.
Legal entity responsible for the study
AbbVie Inc.
Funding
AbbVie Inc.
Disclosure
A.B. Cortot: Financial Interests, Institutional, Funding, Grants or Contracts: Exeliom; Financial Interests, Personal, Financially compensated role, Consulting fees: Novartis; Financial Interests, Personal, Financially compensated role, Consulting Fees: AbbVie, Roche, Exeliom, Pfizer, Janssen, Amgen, Takeda, AstraZeneca, MSD; Financial Interests, Personal, Financially compensated role, Payment or honoraria for lectures, presentations, speakers bureaus, manuscript writing or educational events: Pfizer, Amgen, Takeda, Novartis, Roche, AstraZeneca, MSD, Janssen, BMS; Financial Interests, Personal, Other, Support for attending meetings and/or travel: Roche, MSD, Novartis, Pfizer, AstraZeneca, Amgen, BMS; Financial Interests, Personal, Financially compensated role, Participation on a Data Safety Monitoring Board or Advisory Board: InhaTarget, Merck. E. Wasielewski: Financial Interests, Personal, Other, Expert boards: Takeda. D. Feng, A. Lind, P.J. Ansell, R. Thiébaut, C. Hader: Financial Interests, Personal, Full or part-time Employment: AbbVie Inc.; Financial Interests, Personal, Stocks/Shares: AbbVie Inc.. All other authors have declared no conflicts of interest.
Resources from the same session
173P - Unveiling a novel EpCAM-CD24+ circulating cells with unidentified origin associated with breast cancer distant metastasis
Presenter: Evgeniya Grigoryeva
Session: Poster session 08
174P - Prognostic value of the immune and metabolic profile in the response to neoadjuvant treatment with ICIs in triple-negative breast cancer patients (TNBC)
Presenter: Lucía Serrano García
Session: Poster session 08
175P - Utility of artificial intelligence (AI) in Ki67 scoring of a breast cancer (BC) patient population
Presenter: Xavier Pichon
Session: Poster session 08
176P - ERBB2 amplifications across sex, race, and cancer types
Presenter: Marc Machaalani
Session: Poster session 08
177P - HER2 testing in multiple solid tumors: Concordance between 3 scoring algorithms
Presenter: Wentao Yang
Session: Poster session 08
178P - PD-L1 expression in ER-low versus triple-negative (TN) advanced breast cancer (aBC), and according to phenotypic evolution from primary to recurrent disease
Presenter: Federica Miglietta
Session: Poster session 08
179P - Multimodal deep learning integrating MRI and molecular profiles for predicting outcomes in triple-negative breast cancer
Presenter: Seong Hwan Park
Session: Poster session 08
181P - Molecular characterization and immune microenvironment analysis of MSI-H patients with or without MMR gene mutations
Presenter: Mengxi Ge
Session: Poster session 08
182P - Multi-modal artificial intelligence outperforms image-based approaches for mutation prediction from H&E tissue images in colorectal cancer
Presenter: Marc Päpper
Session: Poster session 08