EGFR and K-ras gene mutation status in squamous cell anal carcinoma: a role for concurrent radiation and EGFR inhibitors?
Bibliographic record
Abstract
BACKGROUND: There is a growing appreciation for radio-sensitiser use in multi-modal cancer treatment models. Squamous cell anal carcinoma (SCAC) is a rare gastrointestinal tumour traditionally treated with concurrent chemotherapy and radiation. Cetuximab, an epidermal growth factor receptor (EGFR) inhibitor, has demonstrated significant efficacy when combined with radiation in squamous cell carcinoma of the head and neck (SccH&N). We wanted to assess EGFR and Kirsten-ras (K-ras) status in SCAC to see whether it compares with SccH&N. METHODS: Over 90 SCAC paraffin-embedded biopsies were mounted onto a tissue microarray and were assessed for EGFR expression by immunohistochemistry. These samples were also assessed for the most frequently mutated K-ras and EGFR exons by high-resolution melting analysis. RESULTS: The EGFR was present in over 90% of samples tested. The K-ras and EGFR mutations were absent in all samples tested, although a synonymous single-nucleotide polymorphism was found in 3 out of 89 samples tested for EGFR exon 19. CONCLUSION: The low rate of K-ras and EGFR mutations, coupled with the high surface expression of EGFR, suggests similarity in the EGFR signalling pathway between SCAC and SccH&N, and thus a potential role for EGFR inhibitors in SCAC. To our knowledge this is the largest cohort of invasive SCAC samples investigated for EGFR and K-ras mutations reported to date.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".