Analytical Performance of a qRT-PCR Assay to Detect Guanylyl Cyclase C in FFPE Lymph Nodes of Patients With Colon Cancer
Bibliographic record
Abstract
Up to 30% of patients with stage II (pN0) colon cancer develop recurrences, suggesting that the presence of lymph node (LN) metastases escaped detection at histopathologic staging. A simple way to overcome this limitation and to improve staging accuracy is to use reverse transcription-polymerase chain reaction (RT-PCR) to examine a larger fraction or an entire specimen. The Guanylyl cyclase C (GCC) gene is uniquely expressed in apical cells of the gastrointestinal tract. Its expression in colon cancer cells and metastases is conserved. Therefore, detection of GCC mRNA in LNs has been shown to be indicative of the presence of colon cancer metastases. As the current processing of LNs involves formalin fixation and paraffin embedding, we developed a method for extracting RNA from formalin-fixed paraffin-embedded LN specimens and detecting GCC mRNA by quantitative RT-PCR. The assay has a dynamic range of 5 logs, an average amplification efficiency of 98.4% (95% confidence interval, 96.6-100.3), a reaction linearity of 0.998 (95% confidence interval, 0.997-0.999), and also intraplate and interplate CVs of <1% and <5%, respectively. The test specificity was 98% with LNs collected from patients affected by conditions other than colon cancer (n=380). Sensitivity was 97% for patients with stage III colon cancer (n=34), whereas 35% of patients with stages I and II disease (n=51) had at least 1 GCC mRNA-positive LN. The high specificity of GCC mRNA suggests that routine utilization of the quantitative RT-PCR test has the potential to improve the detection of colon cancer metastases in LNs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".