Characterization of Leading Dysregulated Plasma-Proteome Associated Genes in Patients with Gastro-Esophageal Cancers.
Bibliographic record
Abstract
Abstract Background: Gastro-esophageal cancers are one of the major causes of cancer-related death in the world. There is a need for novel biomarkers in the management of gastro-esophageal cancers to identify new therapeutic targets and to yield predictive response to the available therapies. Our study aims to identify leading genes that are dysregulated (upregulated or downregulated) in patients with gastro-esophageal cancers.Methods: We examined gene expression data for those genes whose protein products can be detected in the plasma in 600 independent tumor samples and 46 matching normal tissue samples using the Cancer Genome Atlas (TCGA) to identify leading genes that are dysregulated in patients with gastro-esophageal cancers. Non-parametric Mann-Whitney-U test was used to evaluate differential expression of genes using a cut-off of P< 0.05.Results: The comparison between tumors sample and healthy tissue showed BIRC5 (p=2.61 E-08), APOC2 (p=3.23E-08), CENPF (p=4.38E-08), STMN1 (p=5.74E-08), and HNRPC (p=8.21E-08) were the leading genes significantly overexpressed in esophageal cancer whereas CST1 (p=3.97 E-21), INHBA (p=9.22E-20), ACAN (p=1.08E-19), HSP90AB1 (p=2.62E-19), and HSPD1 (p=3.91E-19) were the leading genes that were overexpressed in stomach cancer. Conversely, C16orf89 (9.78E-08), AR (1.01E-07), CKB (1.17E-07), ADH1B (1.79E-07), and NCAM1 (2.15E-07) were the leading gene that were significantly downregulated in esophageal cancer whereas GPX3 (1.65E-19), CLEC3B (5.70E-19), CFD (5.68E-18), GSN (4.5IE-17), and CCL14 (1.12E-16) were significantly downregulated in stomach cancer. Furthermore, Stage-based examination showed stage-specific differential expression of various genes as well as stage-wise increasing or decreasing up-regulation or down-regulation of selected genes, respectively. Conclusions: The present study identified leading upregulated and downregulated genes in gastro-esophageal cancers that can be detected in the plasma proteome. These genes have potential to become diagnostic and therapeutic biomarkers for early detection of cancer, recurrence following surgery and for development of targeted-treatment.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".