A common promoter hypomethylation signature in invasive breast, liver and prostate cancer cell lines reveals novel targets involved in cancer invasiveness
Bibliographic record
Abstract
// David Cheishvili 1, * , Barbara Stefanska 1, 6, * , Cao Yi 1 , Chen Chen Li 1 , Patricia Yu 1 , Ani Arakelian 2 , Imrana Tanvir 3 , Haseeb Ahmed Khan 3 , Shafaat Rabbani 2 , Moshe Szyf 1, 4, 5, * 1 Department of Pharmacology and Therapeutics, McGill University, Montreal, Quebec, Canada 2 Departments of Medicine, Oncology, and Pharmacology, McGill University, Montreal, Quebec, Canada 3 Department of Pathology, Fatima Memorial Hospital System Lahore, Pakistan 4 Department of Pharmacology and Therapeutics, Sackler Program for Epigenetics & Developmental Psychobiology, McGill University Medical School, Montreal, Quebec, Canada 5 Department of Pharmacology and Therapeutics, Canadian Institute for Advanced Research, Montreal, Quebec, Canada 6 Department of Nutrition Science, Purdue University, West Lafayette, USA * These authors have contributed equally to this work Correspondence to: Moshe Szyf, e-mail: moshe.szyf@mcgill.ca Keywords: DNA methylation, epigenetics, inasiveness, drug targets, hypomethylation Received: July 29, 2015 Accepted: September 10, 2015 Published: September 22, 2015 ABSTRACT Cancer invasion and metastasis is the most morbid aspect of cancer and is governed by different cellular mechanisms than those driving the deregulated growth of tumors. We addressed here the question of whether a common DNA methylation signature of invasion exists in cancer cells from different origins that differentiates invasive from non-invasive cells. We identified a common DNA methylation signature consisting of hyper- and hypomethylation and determined the overlap of differences in DNA methylation with differences in mRNA expression using expression array analyses. A pathway analysis reveals that the hypomethylation signature includes some of the major pathways that were previously implicated in cancer migration and invasion such as TGF beta and ERBB2 triggered pathways. The relevance of these hypomethylation events in human tumors was validated by identification of the signature in several publicly available databases of human tumor transcriptomes. We shortlisted novel invasion promoting candidates and tested the role of four genes in cellular invasiveness from the list C11orf68, G0S2, SHISA2 and TMEM156 in invasiveness using siRNA depletion. Importantly these genes are upregulated in human cancer specimens as determined by immunostaining of human normal and cancer breast, liver and prostate tissue arrays. Since these genes are activated in cancer they constitute a group of targets for specific pharmacological inhibitors of cancer invasiveness. SUMMARY : Our study provides evidence that common DNA hypomethylation signature exists between cancer cells derived from different tissues, pointing to a common mechanism of cancer invasiveness in cancer cells from different origins that could serve as drug targets.
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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".