Abstract LB-230: A prospective clinical trial to evaluate DNA sequencing as a diagnostic tool to guide cancer therapy: results from the initial 50 patients
Bibliographic record
Abstract
Abstract Background:We are conducting a multicenter clinical trial to evaluate the feasibility of including next-generation sequencing in routine clinical care. Study goals are to determine patient acceptance of research biopsies for genomic sequencing, optimal methods and procedures for sample collection, DNA extraction for successful analysis, review and reporting of mutations back to clinicians and patients with three weeks. Methods: Patients (pts) with metastatic cancer potentially eligible for clinical trials are recruited from 4 cancer centers. A tumor biopsy, blood sample and archived tumor specimens are collected from consenting patients. DNA from samples are analyzed using Pacific Biosciences RS targeted gene sequencing and Sequenom Oncocarta™ V1.0 genotyping. Detected mutations are validated in a CAP/CLIA certified laboratory. An expert panel of clinicians and scientists review results to determine whether results are actionable and reportable to clinicians. Results: As of 01/2012, 50 pts have been recruited. Pt demographics include median age = 57; primary tumor colorectal 9 pts (18%), breast 8 (16%), ovary 8 (16%), lung 5 (10%), others 20 (40%); median number prior treatments = 3; median time with metastatic disease = 17 months. Over 90% of approached pts consented to the study. Molecular profiling by Pacific Biosciences RS and Sequenom was successful in 43 pts (86%) with 100% concordance between genomic platforms. Somatic mutations were identified in over 30% of pts; 75% of these (including mutations in KRAS, PIK3CA, EGFR, RET, KIT) were deemed actionable. Seven pts (14%) had treatment impacted by matching a targeted therapy to the genetic profile; 4 patients had benefit (1 PR in ovarian cancer, 1 SD in breast cancer, 2 clinical benefits in thyroid and unknown primary squamous cell cancers). Four pts had novel mutations in AKT1, PDGFRA, EGFR and KRAS not present on the Oncocarta panel demonstrating the added benefit of sequencing the entire exon. Genomic results from of archived tumor specimens and fresh tumor biopsies matched in 26 of 30 patients (90%) with paired samples. 62% of pts had delivery of a clinical report within </= 21 days. Bioinformatics tools developed to assist with sample handling, analyses and reporting mechanisms are being optimized for routine inclusion into the clinical environment. Mutation specific reporting templates have been developed to provide results and curetted information from publically available sources. Conclusion: The study is on track to meet the pre-defined study benchmarks for patient recruitment, sample quality, and turnaround time. Our results indicate that high throughput sequencing with clinical laboratory verification of results is feasible and may be used as a clinical tool to guide cancer therapy and add value to the information generated by traditional genotyping methods. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr LB-230. doi:1538-7445.AM2012-LB-230
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".