SPARC promoter hypermethylation in colorectal cancers can be reversed by 5-Aza-2′deoxycytidine to increase SPARC expression and improve therapy response
Bibliographic record
Abstract
Poor clinical outcomes in cancer can often be attributed to inadequate response to chemotherapy. Strategies to overcome either primary or acquired chemoresistance may ultimately impact on patients' survival favourably. We previously showed that lower levels of SPARC were associated with therapy-refractory colorectal cancers (CRC), and that upregulating its expression enhances chemo-sensitivity resulting in greater tumour regression in vivo. Here, we examined aberrant hypermethylation of the SPARC promoter as a potential mechanism for repressing SPARC in CRCs and whether restoration of its expression with a demethylating agent 5-Aza-2'deoxycytidine (5-Aza) could enhance chemosensitivity. Initially, the methylation status of the SPARC promoter from primary human CRCs were assessed following isolation of genomic DNA from laser capture microdissected specimens by direct DNA sequencing. MIP101, RKO, HCT 116, and HT-29 CRC cell lines were also used to evaluate the effect of 5-Aza on: SPARC promoter methylation, SPARC expression, the interaction between DNMT1 and the SPARC promoter (ChIP assay), cell viability, apoptosis, and cell proliferation. Our results revealed global hypermethylation of the SPARC promoter in CRCs, and identified specific CpG sites that were consistently methylated in CRCs but not in normal colon. We also demonstrate that SPARC repression in CRC cell lines could be reversed following exposure to 5-Aza, which resulted in increased SPARC expression, leading to a significant reduction in cell viability (by an additional 39% in RKO cells) and greater apoptosis (an additional 18% in RKO cells), when combined with 5-FU in vitro (in comparison to 5-FU alone). Our exciting findings suggest potential diagnostic markers of CRCs based on specific methylated CpG sites. Moreover, the results reveal the therapeutic utility of employing demethylating agents to improve response through augmentation of SPARC expression.
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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 | 0.000 | 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) | 0.001 | 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".