Abstract 1772P
Background
For advanced chordoma, no standard systemic therapy exists, and the low incidence of targetable genetic alterations limits the impact of genomics in precision oncology efforts. Reports of aberrant receptor tyrosine kinase (RTK) expression or activity in chordoma suggest that these tumors might respond to RTK inhibition, but kinase inhibitors have shown modest clinical activity in patients, possibly because no molecular biomarker exists to identify responder patients.
Methods
We generated phosphoproteome profiles of > 100 chordoma patients and 14 chordoma cell lines and developed a new tumor pathway activity (TUPAC) scoring methodology to infer aberrant RTK activity using > 8,000 proteins and 20,000 phosphorylation sites per patient. We found that chordoma cell lines were either sensitive to the EGFR inhibitor afatinib (EC50 < 50 nM) or resistant (EC50 > 1000 nM), providing an opportunity to test the predictive power of using phosphoproteomic TUPAC scores to predict RTK inhibitor sensitivity.
Results
In (phospho)proteome profiling, Chordoma represents a molecularly heterogeneous group of tumors. We discovered aberrant activity for 15 different RTKs in 43% of chordoma patients, notably and most frequently EGFR and MET. In the cell line panel, afatinib sensitivity corresponded with high scores for EGFR activity in 7/8 sensitive cell lines and 3/6 resistant cell lines. Interestingly, EGFR signaling-positive but resistant cell lines showed high type I IFN signaling, previously associated with adaptive resistance to EGFR inhibition in lung cancer. Using the combination of a high EGFR TUPAC score and a low type I IFN signature, the afatinib response can be correctly predicted in 13/14 cell lines. Applying the same stratification scheme in the patient cohort, we predict afatinib response in 15% of advanced chordoma patients.
Conclusions
Although RTKs are not mutated in chordoma, here we use phosphoproteomics to report the detection of aberrant RTK activation in > 40% of advanced chordoma patients – suggesting RTKs may nonetheless represent attractive therapeutic targets in this rare cancer. These data support the testing of phosphoproteome-based biomarkers for selecting advanced chordoma patients who benefit from afatinib or other RTK inhibitors.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
Chair of Proteomics and Bioanalytics.
Funding
Chordoma Foundation, EU fund.
Disclosure
C. Heilig: Non-financial interests, Personal, Advisory Board: Boehringer Ingelheim; Financial interests, Personal, Funding, Other, Honoraria: Novartis; Financial interests, Personal, Funding, Other, Honoraria: Roche; Financial interests, Institutional, Research funding: Boehringer Ingelheim. S. Fröhling: Non-financial interests, Personal, Advisory Board: Bayer; Non-financial interests, Personal, Advisory Board: Illumina; Non-financial interests, Personal, Advisory Board: Roche; Financial interests, Personal, Funding, Other, Honoraria, Travel, Accomodations, Expenses: PharmaMar; Financial interests, Personal and Institutional, Funding, Other, Honoraria, Travel, Accomodations, Expenses, Research Funding: Roche; Financial interests, Personal and Institutional, Funding, Other, Honoraria, Travel, Accomodations, Expenses, Research Funding: Lilly; Financial interests, Personal, Funding, Honoraria, Travel, Accomodations, Expenses: Amgen; Financial interests, Institutional, Research Funding: AstraZeneca; Financial interests, Institutional, Research Funding: Pfizer. B. Küster: Financial interests, Personal, Shareholder: OmicScouts; Financial interests, Personal, Shareholder: MSAID; Non-financial interests, Personal, Advisory Board: Covant Therapeutics; Financial interests, Institutional, Research funding: Merck; Financial interests, Institutional, Research funding: Boehringer Ingelheim. All other authors have declared no conflicts of interest.
Resources from the same session
1362P - Evaluation of imaging-based prognostication (IPRO) for advanced non-small cell lung cancer (aNSCLC) using deep learning applied to computed tomography (CT)
Presenter: Omar Khan
Session: Poster session 06
1363P - An AI-derived tool to pre-screen lung cancer candidates for clinical trials
Presenter: Mihaela Aldea
Session: Poster session 06
1364P - Federated analysis of overall survival (OS) by location of metastases (mets) in patients (pts) with metastatic NSCLC (mNSCLC) from the Digital Oncology Network for Europe (DigiONE)
Presenter: Åsa Öjlert
Session: Poster session 06
1365P - Does cancer care differ for older adults with lung cancer living with and without Alzheimer disease and related dementias (ADRD)?
Presenter: Lorinda Coombs
Session: Poster session 06
1366P - Natural Language Processing (NLP) as promising artificial intelligence (AI) tool to improve patients (pts) enrollment in clinical trials (CT): Analysis in real-world conditions on a lung cancer cohort
Presenter: Julien Mazieres
Session: Poster session 06
1367P - Sex disparities in patient and tumour characteristics, and overall survival in advanced non-small cell lung cancer (NSCLC) within the precision oncology era: A Danish nationwide observational study
Presenter: Matilde Frost
Session: Poster session 06
1368P - Correlation between depth of response at 6 months and survival in patients (pts) with metastatic non-small cell lung carcinoma (mNSCLC): SPORE trial
Presenter: Fabien Moinard-Butot
Session: Poster session 06
1369P - Trilaciclib combined with intraventricular injection chemotherapy in the treatment of advanced NSCLC with leptomeningeal metastasis: A prospective, single-arm, phase II clinical trial
Presenter: Shen Cun Fang
Session: Poster session 06
1370P - Survival of de novo metastatic non-small cell lung cancer according to biomarker status in Denmark and Norway: A register-based cohort study
Presenter: Johan Liseth Hansen
Session: Poster session 06