The value of defining molecular resistance in patients with progressive <i>EGFR</i> and <i>ALK</i>-driven lung cancer in a public system.
Bibliographic record
Abstract
3126 Background: Repeat molecular profiling, except to detect EGFR T790M, is not routinely performed in Canadian patients with lung cancer progressing on EGFR tyrosine kinase inhibitors (TKIs). We performed genomic profiling on post-progression biopsies in patients with stage IV non-small cell lung cancer (NSCLC) and known EGFR/ ALK aberrations treated with TKIs to identify resistance mechanisms, evaluate options for subsequent treatment, and to assess clinical trial eligibility and costs. Methods: From Feb 2018-Aug 2020, post-progression tumour biopsies from consenting patients at a major cancer centre underwent genomic profiling (ThermoFisher OCA v3.0 including hotspots, fusions, and copy number variations in 161 cancer-associated genes). Outcomes of interest were the identification of resistance mutations, actionable targets, clinical trial eligibility (per clinicaltrials.gov), and costs. Results: Thirty-two patients consented to the study. Most, 84% (n = 27), had successful testing completed while 16% (n = 5) had insufficient tissue. Median age of the cohort was 56 yrs, 59% (n = 16) were female, 74% (n = 20) were never-smokers, 81% (n = 22) had ECOG performance status 0-1, and 67% (n = 18) were Asian. The majority, 81% (n = 22) had EGFR mutated NSCLC, and had progressed on EGFR TKIs (15 with previously identified T790M had progressed on osimertinib), and 19% (n = 5) had ALK fusions. Patients had received a median of 2 prior lines of targeted therapy prior to re-biopsy (IQR 1.5,3). One patient had evidence of small cell transformation and associated TP53 and RB1 mutations, 11% (n = 3) had acquired EGFR C797S mutations, and 11% (n = 3) had acquired ALK resistance point mutations (G1202R n = 2, I1171N n = 1). Genomic profiling identified additional actionable targets in 19% of patients (n = 5: MET exon 14 skip mutation n = 1, MET amplification n = 2, BRAF V600E n = 2). Overall, 33% (n = 9) patients had management-changing resistance mechanisms identified (small cell transformation n = 1, actionable targets n = 5, ALK inhibitor resistance = 3). New clinical trial options based on genomic profiling results were identified for 67% (n = 18) of patients. Incremental costs for repeat genomic profiling were approximately $880 CAD per case. Conclusions: Molecular profiling upon development of resistance to targeted therapy in our cohort revealed actionable resistance mechanisms for over a third of patients and clinical trial options for 67%. These incremental benefits for patients highlight the importance of routine molecular profiling in the setting of acquired TKI resistance in lung cancer.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".