Abstract 1855: SCT methylation is a potential cancer biomarker for lung cancer
Bibliographic record
Abstract
Abstract Purpose: To validate SCT (secretin) methylation as a potential cancer biomarker for lung cancer. Background: There is an urgent need for specific and sensitive biomarkers for lung cancer. The human secretin (SCT) gene is located on chromosome 11p15.5 and encodes the precursor gene of secretin, an endocrine hormone. From analysis of The Cancer Genome Atlas methylation array data, we (XM and MQZ) observed that the exon 1 promoter region of SCT gene is differentially hypermethylated in lung cancer (unpublished). These observations led us to further validate whether SCT methylation can be a useful cancer biomarker for lung cancer. Methods/Results: (1). We designed a novel nested PCR assay for SCT bisulfite sequencing of the promoter and exon 1 region of SCT. Bisulfite sequencing showed that SCT was fully methylated in nearly all CpG sites examined in 10 lung cancer cell lines, whereas SCT was non-methylated in 11 normal WBC blood cells. Accordingly we designed a semi-quantitative SCT qMSP assay. (2). We applied SCT qMSP on genomic DNA from frozen tissues of 131 lung tumors and 65 non-malignant adjacent lung tissues (53 paired). The level of SCT methylation was significantly higher (>24 fold) in all 111 malignant lung tumors (64 adenocarcinomas, 19 squamous cell carcinomas, 12 large cell neuroendocrine carcinomas, 16 NSCLC-other type), as compared to 65 non-malignant adjacent lung tissues. The high SCT methylation was further confirmed in malignant lung tumor formalin-fixed paraffin-embedded (FFPE) tissues samples (8 pairs tested). SCT methylation distinguishes malignant lung from non-malignant adjacent lung with area under curve (AUC) score of 0.92 (p<0.0001). (3). Interestingly, SCT hypermethylation does not significantly distinguishes low grade lung carcinoids tumors (n=20) from non-malignant adjacent lung with AUC score of 0.54 (p=0.5759). (4). Nearly full SCT methylation was detected in lung cancer cell lines (n=27) as compared to absent or lower levels of SCT methylation in immortalized human respiratory cell lines (n=38). Conclusions: SCT methylation is a highly specific and sensitive tissue biomarker for malignant lung cancer and can be detected in FFPE samples. SCT methylation is infrequent in low grade lung carcinoids tumors. Its clinical uses need to be explored. Citation Format: Yu-An Zhang, Xiaotu Ma, Junya Fujimoto, Ignacio Wistuba, Stephen Lam, Victor Stastny, Boning Gao, Jill Larsen, Xiaoyun Liu, John D. Minna, Michael Q. Zhang, Adi F. Gazdar. SCT methylation is a potential cancer biomarker for lung cancer. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1855. doi:10.1158/1538-7445.AM2014-1855
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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 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.003 | 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".