Abstract 1869: Methylation signatures associated with T790M status in progressive NSCLC
Bibliographic record
Abstract
Abstract Background: Emergence of the EGFR T790M mutation accounts for acquired first generation EGFR TKI resistance in over half of patients with EGFR mutant NSCLC. In patients without emergent T790M, resistance mechanisms are less well understood. We explored the impact of DNA methylation status and TKI treatment failure in these patients. Methods: Using a prospective cohort of patients with acquired TKI resistance, tumour tissue samples pre/post TKI exposure were identified. DNA was extracted from FFPE tissue using the Qiagen AllPrep DNA/RNA FFPE Extraction Protocol, and subsequently analyzed using the Illumina Infinium EPIC array. Raw microarray data files were processed using the software package minfi for data normalization (Illumina method) and extraction of methylation levels (M-values). Samples were split into two groups according to the T790M status of each sample (T790M + or T790M-). The set of most informative probes, those whose M-value profiles align most closely with the T790M status of the study samples, was generated by selecting the 1,000 probes with lowest ANOVA's p-value. The stability of the resulting sample clustering was assessed by hierarchical clustering (Euclidean distance), classification with internal cross-validation (SVM leave-one-out), and non-parametric dimensional reduction (t-SNE). Results: 40 samples from 36 EGFR mutant NSCLC patients were successfully profiled. Pre TKI samples were available in 10 patients with an EGFR mutation of which 4 had matched post TKI tissue (3 T790M+, 1 T790M-). The remaining 26 samples in post TKI patients included 17 T790M + and 9 T790M- cases. A DNA methylation-based signature was developed by selecting the array probes that best discriminated T790M+ from T790M- cases. Group membership was stable, as shown by cross-validation by three different methods (hierarchical clustering, SVM leave-one-out and t-SNE). The 1,000 probe cut-off was arbitrarily selected; however, identical sample clusters were obtained using 500 or 2,000 methylation array probes. When analyzing the genomic location of the set of probes that form the signature, we found broad distribution across all chromosomes, thus, ruling out the possibility of selection bias due to focal or chromosome-level aberrations. Several genes contained a higher number of the selected probes, including EGFR, whose expression levels are known to be regulated at the methylation level in certain cancer types. Cluster analysis using the 1,000-probe signature revealed a high degree of concordance between EGFR T790M and DNA methylation status. All post-TKI (n=20) T790M+ samples concentrated within epi-group 2, whereas 8/10 T790M- samples were found within epi-group 1. Of the 4 patients with matched samples, 2 had baseline samples within epi-group 2 and went on to develop EGFR T790M post TKI. Of the 2 with baseline samples within epi-group 1, one went on to develop T790M (post-TKI epigroup 2) and one did not (post-TKI epigroup 1). Conclusions: We observed a concordance between T790M status and epi-group suggesting that the development of resistance to EGFR-TKIs may be associated with distinct DNA methylation signatures. This signature may be present at baseline and predict for subsequent emergence of T790M. Citation Format: Grainne M. O'Kane, Alberto J. León, Muqdas Shabir, Jennifer H. Law, Penelope A. Bradbury, Geoff Liu, Adrian Sacher, Frances A. Shepherd, Dax Torti, Tracy L. Stockley, Ming Tsao, Trevor J. Pugh, Natasha B. Leighl. Methylation signatures associated with T790M status in progressive NSCLC [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 1869.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".