Oncogene amplification as tumor marker in a group of Colombian lung cancer patients
Bibliographic record
Abstract
Introduction: In spite of recent treatment advances, lung cancer continues to be the first world cancer related death cause; its mortality associated occupied the fifth place in Colombia in 2004. Complete surgical resection is the therapeutic option with the greatest cure probability, however it results frequently ineffective given the current incapacity in Colombia to an early detection of the disease. This study reports the characterization of a group of 30 lung cancer patients regarding the gene dose (gene copy number) found at the loci corresponding to genes EGFR (erb B1), PIK3CA and C-myc in tumor samples, and compares the results with the dose found in adjacent lung from the same patients. Methods: The gene dose of EGFR (erbB1), PIK3CA, and C-myc were measured by real time PCR in matched tumor and normal lung tissue samples. Results are expressed as the multiplicity of each gene dose with respect to a single copy reference gene. In this case the gene HHB (human hemoglobin). Antiquity of the cases ranged from 5 to 10 years. Results: An increased gene dose for EGFR and PIK3CA was a feature clearly associated to the tumor phenotype of the sample (found in 96 and 100% of the tumors respectively). Quantitative measure of this feature demonstrated for both genes a high sensitivity and specificity for tumor/normal discrimination as confirmed by the ROC analysis. On the other hand, the Spearman test showed a great correlation between EGFR and PIK3CA doses (r=0.75). C-myc was the gene whose dose was less consistently correlated to the tumor phenotype, however most of the patients with amplified C-myc presented distant spread of tumor cells (metastasis) at diagnosis. Conclusion: Quantitative measurement of EGFR, PIK3CA, and C-myc gene dose by real time PCR provides a method for tumor phenotype recognition in DNA samples from lung tissue. These markers can be considered at the construction of a marker panel for lung cancer detection on alternative, non-invasive clinical samples. However clinical value will depend on the use of additional molecular markers, some of which could be of epigenetic character.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".