Abstract 1719: Integrative genomic analysis of ovarian cancer cell lines points to EMT involvement in the development of cisplatin resistance
Bibliographic record
Abstract
Abstract Ovarian cancer is the 5th leading cause of cancer related death in women, and has the highest associated mortality rate of any of the gynecological cancers. Approximately 75-80% of women diagnosed will succumb to the disease. The high mortality rate associated with ovarian cancer is due to poor screening and detection methods, resulting in late stage diagnosis, and also to resistance of the tumours to chemotherapeutic drugs. Primary drug resistance occurs in about 20% of patients during their treatment phase while approximately 70-80% of women that initially respond to chemotherapy will develop drug resistance over the course of treatment or at the time of relapse. Being able to accurately predict which patients will not successfully respond to drugs is the first step in developing personalized medicine and preventing useless chemotherapy treatments. In order to discover biomarkers of cisplatin resistance, a multi-platform integrative approach was taken utilizing data from aCGH as well as miRNA and mRNA microarrays. Data were collected from a drug sensitive and drug resistant ovarian cancer cell line pair (A2780 and A2780cis). Working with the paired cell lines provided a homogeneous population with which to build an integration algorithm. Data analysis using GeneSpring and Nexus software showed an enrichment of genes involved in TGFβ and EGF signaling. These signaling pathways lead us to investigate the involvement of the epithelial to mesenchymal transition (EMT) in drug resistance. Interestingly, many of the key genes involved in the regulation of the EMT process were found to be upregulated in our mRNA expression data. Observations from cell culture work support EMT involvement. We have noted a slower growth rate and a change to a fibroblastic appearance in the resistant cells relative to their drug sensitive parents. Immunohistochemistry has also been utilized to show an increase in mesenchymal markers in the resistant cell line. In order to determine if these findings were representative of drug resistance in human ovarian cancer, expression data from cisplatin sensitive and resistant ovarian cancer tumours were mined specifically for these and other EMT genes. A large number of the same EMT genes were consistently shown to be upregulated in the drug resistant tumour tissues relative to the sensitive tumours. Together, these data suggest the potential involvement of the epithelial to mesenchymal transition in the development of cisplatin resistance in ovarian cancer. Further validation of these results in vitro is currently in progress. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 1719. doi:10.1158/1538-7445.AM2011-1719
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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) | 0.003 | 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".