Abstract 4664: Massively parallel sequencing-based analysis of synchronous gastric cancer and lung cancer
Bibliographic record
Abstract
Abstract Synchronous gastric cancer(GC) and lung cancer(LC) have been suggested to represent independent primary tumors rather than metastatic disease. We subjected sporadic synchronous GC/LC from five patients to whole-exome massively parallel sequencing, which revealed a median of and 1174 and 830 nonsynonymous somatic mutations in the synchronous GC and LC repectively. DNA mutations range between 292 to 2421 in lung samples and 287 to 1995 in stomach sample. Common mutations varies between 41 and 145. The substitution of C>A, C>T and T>C accounts for the most common mutations in both lung and stomach cancers. Tumor mutation burden (TMB ) varies from 2.7 to 11.0 Mut/Mb in Lung cancer and from 1.8 to 30.4 Mut/Mb in gastric cancer. We further did pathway analysis based on the list of mutant genes. Top 20 pathways enriched in each patient were analyzed. We found MAPK signaling pathway was most commonly enriched pathways in lung cancer patients, whereas PI3K-Akt signaling and Hedgehog signaling pathway were most commonly enriched pathways in stomach cancer patients. This result suggests the potential benefit of targeted therapeutic treatments involved in these pathways. Citation Format: Nandie Wu, Rutian Li, Yang Shao, Lifeng Wang, Baorui Liu, Jia Wei. Massively parallel sequencing-based analysis of synchronous gastric cancer and lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4664.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".