Abstract 166P
Background
Molecular testing of somatic drivers in tumours expands personalised therapy with improved outcomes. Yet, actionable mutations are found in only 20% of non-small cell lung cancer (NSCLC). Our study aimed to improve molecular diagnostics by connecting somatic mutational signatures with proteogenomic profiles.
Methods
Targeted next-generation sequencing (NGS) test (APEX), whole genome sequencing (WGS), RNA sequencing (RNAseq) and targeted proteomics (Olink) were conducted on Southeast Asian NSCLC tumour/matched adjacent normal pairs. Integrative analyses were conducted to correlate somatic mutational signatures (single-base substitution (SBS), small insertions and deletions (ID) and copy number variation (CN)) with transcriptomic and proteomic profiles. Immune landscape was spatially resolved with multiplex immunohistochemistry (mIHC) staining.
Results
NGS-based molecular testing confirmed actionable mutations (EGFR, ALK, RET, MET) in only half of the cohort, with EGFR mutants found in 7 cases. Integrative multi-omics unravelled distinctive transcriptomic and proteomic features in Asian NSCLC that stratified tumours into function subtypes, reflecting key cancer hallmarks. Tumours exhibiting tobacco-associated mutagenesis (SBS4 signature) display heightened oxidative and hypoxic stress signals, accompanied by a subtype-specific immunosuppressive microenvironment, stressing potential benefits from a combined anti-angiogenic therapy with chemotherapy in SBS4-positive lung squamous cell carcinoma (LUSC). Oncogene-driven lung adenocarcinoma (LUAD) tumours with underlying APOBEC3A mutagenesis (SBS2/13 signature) also displayed perturbed NOTCH signalling akin to persistent, drug-resistant tumours, indicative of a shorter response duration to single agent target therapies among the SBS2/13-positive cases.
Conclusions
Our findings underscore the diagnostic potential of multi-omics in NSCLC, urging the implementation of somatic mutational signatures to advance molecular testing and treatment of NSCLC.
Clinical trial identification
Editorial acknowledgement
Legal entity responsible for the study
The authors.
Funding
Ministry of Education, Singapore.
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