Abstract LB-196: EGFR-mutant lung adenocarcinomas mutation profiles reveal ARID1A might be a novel tyrosine kinase resistance pathway
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Lung cancer has the highest mortality across all cancers in the world. Epidermal growth factor receptor (EGFR) is commonly mutated in lung adenocarcinomas from Asian non-smoking females. These tumors usually respond to EGFR tyrosine kinase inhibitors (EGFR-TKI), but the outcomes vary in different patients. Though EGFR T790M, amplification of MET and other mechanisms have been shown to confer EGFR-TKI resistance, the molecular mechanisms in around 30% of patients are still unknown. To uncover novel candidate pathways of EGFR-TKI resistance, we analyzed the whole exome mutation profiles of pre-treatment, EGFR T790M-free lung adenocarcinomas with typical activating mutations (L858R, exon 19 deletions). Amongst 19 non-responding (NR) tumors without significant shrinkage after gefitinib or erlotinib treatment, 67 cancer-related genes showed coding region non-synonymous single nucleotide variations (SNV) or insertion-deletions (indels) but they were not detected in 22 responding tumors. Gene set enrichment analysis (GSEA) showed 14 of the 67 genes were involved in the EGFR and WNT signaling network (false discovery rate q=1.14 e-8 for EGFR and q=4.3 e-9 for WNT), including well-known TKI resistance-related genes PIK3CA, PTEN and NF1. Notably, ARID1A, which encodes a subunit of the chromatin remodeling complex, showed nonsense mutations in 2 NR but not responding tumors, which were validated by Sanger sequencing. More than 40% of ARID1A mutations in lung adenocarcinomas recorded in COSMIC were nonsense mutations or frameshift indels. Loss of function mutations of ARID1A have also been reported in various cancers, together suggesting ARID1A might be a tumor suppressor but its involvement in EGFR mutant lung cancers is unknown. To investigate the potential role of ARID1A, its expression was first studied using Kaplan-Meier plotter. Low expression of ARID1A is associated with significantly better overall survival than high expression level in lung adenocarcinoma patients (p=8.5 e-7). To test whether loss of ARID1A could cause TKI resistance, ARID1A was knocked down by shRNA in HCC827 lung cancer cell line harboring EGFR exon19 deletion. MTT cell viability assay using gefitinib showed increase of IC50. Western blot assay further showed ARID1A knockdown increased phosphorylation of AKT at Ser473. Together, the findings suggest loss of ARID1A could lead to EGFR bypass and promote activation of the downstream PI3K/AKT pathway, leading to EGFR TKI resistance. Overall, our findings suggest EGFR-TKI resistance mutations could be detected before TKI drug selection. Resistant gene mutations present in pre-treatment tumors could help to predict the treatment response. More specifically, our study identified a promising gene list involved in EGFR-TKI resistance, and suggested ARID1A loss could be a novel EGFR-TKI resistance mechanism. Citation Format: Xuyuan Gao, Hang Xu, James CM Ho, Oscar SH Chan, Feng Xu, Junwen Wang, Victor HF Lee, Vicky PC Tin, Zhijie Xiao, Siqi Wang, Judy WP Yam, Maria P Wong. EGFR-mutant lung adenocarcinomas mutation profiles reveal ARID1A might be a novel tyrosine kinase resistance pathway [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-196.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it