Abstract 122P
Background
Interdisciplinary Molecular Tumor Boards (MTB) are increasingly implemented to account for the growing complexity in molecular oncology, yet data on MTB practice patterns and patient benefit are heterogeneous. Our aim was to determine local practice patterns and treatment response data of MTB-directed therapies.
Methods
In this retrospective cohort study, consecutive patients referred to the MTB of the Medical University of Graz from 2021-2023 were included. Patients were referred with either existing molecular profiles, or additional genomic sequencing from tissue/liquid biopsies and/or immunohistochemistry was performed. Treatment recommendations were based on ESMO Scale for Clinical Actionability of Molecular Targets (ESCAT) levels. Preliminary treatment response outcomes were disease control rate (DCR), overall response rate (ORR) and duration of response (DOR).
Results
Overall, 249 patients referred to the MTB Graz were included, including external referrals from regional and national centres (18%). The median time from referral to MTB recommendation was 26 days. The most frequent cancer types were breast- (n=69), pancreatic- (n=42), colorectal- (n=24), and non-small cell lung cancer (n=24). Molecular profiling was performed in 88.8% of referred patients (n=221). An actionable alteration was identified in 115 patients (46.2%), comprising ESCAT level I recommendations in 33%, level II in 21% and level III in 45%. MTB-recommended treatment was so far initiated in 57 patients (23%). Common reasons for not implementing treatment was clinical deterioration (n=25) and ongoing previous therapies (n=22). The DCR in treated patients was 45% and ORR was 19%. In the subgroup of patients with ESCAT level I-II recommendations, DCR was 58% and ORR was 29%. Sustained treatment responses (i.e., >12 months DOR) were observed in 12% of treated patients.
Conclusions
A substantial rate of targetable alterations was detected in patients referred to the MTB. Promising treatment response patterns were observed in a subset of patients treated with MTB-recommended therapies. Additional detailed genomic analyses of included patients and treatment response evaluations can be presented at the meeting.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Has not received any funding.
Disclosure
All 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