bioRxivGenomicsPreprint
Lung Adenocarcinoma Just Desserts: An Expanding Pie of Activating Oncogenes or a Layer Cake of Integrated Alterations
Minjung KimiD, Wisut LamlertthoniD, Heejoon Jo, Yan CuiiD, Hyo Young ChoiiD, Katherine A. HoadleyiD, Matthew P. SmeltzeriD, Michele C. HaywardiD, Matthew D. WilkersoniD, Liza MakowskiiD, David Neil HayesiD
Abstract
The molecular landscape of lung adenocarcinoma (LUAD) is often summarized as a "pie chart" of driver oncogenes, suggesting identification and targeting of oncogenic drivers is the best clinical approach. However, this model oversimplifies LUAD biology. Patients with identical RAS or RAF mutations exhibit heterogeneous signaling influenced by co-mutations, transcriptional programs, and lineage context. We propose a hierarchical framework integrating oncogenes within cellular context by examining canonical EGFR mutations. We defined an EGFR mutation signature (mSig) by identifying differentially expressed genes in EGFR-mutant LUADs. Semi-supervised clustering and machine learning models were used to test performance and reproducibility across independent datasets. We analyzed molecular subtypes, lineage markers, co-occurring mutations, and candidate drug targets in EGFR-mSig positive (+) versus negative (-) tumors. The EGFR mSig showed robust classification performance across datasets (AUROC = 0.83-0.95; mean NPV = 96.3%). Validated unsupervised gene expression subtypes and lung lineage markers were closely aligned with EGFR mSig status. mSig(+) tumors were identified, even in tumors without EGFR mutations. A subset of canonical RAS mutations mirrored the EGFR mutation pattern. EGFR-mutant/mSig(-) tumors were enriched for non-Bronchioid subtypes and had co-mutations in TP53 or RAS. Coordinated mutations were identified including RAS, KEAP1, STK11, TP53, and CDKN2A, supportive of prior reports. In sum, novel EGFR mSig that captures the transcriptional footprint of EGFR activation, revealed a subset of EGFR wildtype LUADs with "mutant-like" features. Lineage-informed classification highlights subtype-dependent oncogene activity and supports new therapeutic strategies. A context-specific association between RAS mutation and expression of the dual-specificity phosphatase gene DUSP4 may have therapeutic potential.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: clustering
- approach: machine learning (classical)
- Citations
- 0
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