Higher Expression Levels of SSX1 and SSX2 in Patients with Colon Cancer: Regulated In Vitro by the Inhibition of Methylation and Histone Deacetylation
Bibliographic record
Abstract
Background and Objectives: Colon cancer (CC) has a high mortality rate and is often diagnosed at an advanced stage in Saudi Arabia. Thus, the identification and characterization of potential new cancer-specific biomarkers are imperative for improving the diagnosis of CC by detecting it at an early stage. Cancer-testis (CT) genes have been identified as potential biomarkers for the early diagnosis of various cancers. Among the CT genes are those belonging to the SSX family. In order to assess the usefulness of SSX family genes as cancer biomarkers for the detection of early-stage CC, the goal of this research was to validate the expressions of these genes in patients with CC and in matched patients with normal colons (NCs). Materials and Methods: RT-PCR assays were used to analyze the SSX1, SSX2, and SSX3 family gene expression levels in 30 neighboring NC and CC tissue samples from male Saudi patients. Epigenetic alterations were also tested in vitro using qRT-PCR analysis to determine whether reduced DNA methyltransferase or histone deacetylation could stimulate SSX gene expression via 5-aza-2′-deoxycytidine and trichostatin treatments, respectively. Results: The RT-PCR results showed SSX1 and SSX2 gene expression in 10% and 20% of the CC tissue specimens, respectively, but not in any of the NC tissue specimens. However, no SSX3 expression was detected in any of the examined CC or NC tissue samples. In addition, the qRT-PCR results showed significantly higher SSX1 and SSX2 expression levels in the CC tissue samples than in the NC tissue samples. The 5-aza-2′-deoxycytidine and trichostatin treatments significantly induced the mRNA expression levels of the SSX1, SSX2, and SSX3 genes in the CC cells in vitro. Conclusions: These findings suggest that SSX1 and SSX2 are potentially suitable candidate biomarkers for CC. Their expressions can be regulated via hypomethylating and histone deacetylase treatments, subsequently providing a potential therapeutic target for CC.
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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".