Abstract 3149: Identification of genes associated with the cisplatin resistance in cervical cancer cells expressing E545K mutation
Bibliographic record
Abstract
Abstract The phosphatidylinositol-3 kinase (PI3K)/AKT/ mTOR signaling pathway is activated in several human cancers and activation is frequently mediated by “hotspot” mutations including E542K, E545K and H1047R in the PIK3CA gene. Approximately 30% of cervical cancer patients have the PIK3CA-E545K mutation. Cisplatin with radiotherapy (RT) is the standard treatment of cervical cancer world-wide, used in both the radical and post-operative adjuvant settings. However, details of the molecular mechanisms responsible for cisplatin resistance remain unclear. We previously reported PIK3CA mutation in patients with earlier stage (IB/II) cervical cancer was associated with poor survival (McIntyre et al. Gynecol Oncol. 2013, PMID:23266353), and in our recent study we observed that PIK3CA-E545K mutation renders cervical cancer cells more resistant to cisplatin or cisplatin plus RT and results in a more migratory phenotype than isogenic cell lines with wild type-PIK3CA. Moreover, these phenotypes are reversed by the PI3K inhibitor GDC-0941/Pictilisib (Wani et al. Oncotarget. 2016, PMID:27489350). The aim of the present study is to identify the expression of genes related to cisplatin resistance in cervical cancer cells engineered to express PIK3CA-E545K. Microarray analysis identified 161 genes that were up-regulated and 189 that were down-regulated in the cervical cancer cells stably expressing PIK3CA-E545K, some of which are involved in well-characterized mechanisms that could be relevant to cisplatin resistance. We are currently validating some of those genes by Real-time PCR that will help us to determine the mechanism of PIK3CA-E545K induced cisplatin resistance and enhanced migration in cervical cancer cells expressing PIK3CA-E545K and extending our in vitro findings to animal models. Together, our data will provide a useful basis for screening candidate targets for risk stratification and provide valuable information for potential targeted intervention in patients whose tumors harbor cisplatin-resistant molecular characteristics. Citation Format: Wani Arjumand, Nicholas Jette, Jb McIntyre, Prafull Ghatage, Corinne M. Doll, Susan P. Lees-Miller. Identification of genes associated with the cisplatin resistance in cervical cancer cells expressing E545K mutation [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3149. doi:10.1158/1538-7445.AM2017-3149
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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) | 0.002 | 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".