Abstract B10: Modulation of mRNA translation regulation in highly metastatic ssteosarcoma cells increases their sensitivity to redox stress
Bibliographic record
Abstract
Abstract Improvement in outcomes for pediatric patients with metastatic osteosarcoma still remains elusive despite the development of new multiagent combinations. This unmet clinical need underscores the need for novel approaches that examine the metastatic process itself in order to identify new molecular targets whose modulation may have antimetastatic activity. During lung metastasis progression, osteosarcoma cells (OS) have to quickly adapt to the hostile microenvironment of the lung. Elucidating exactly how highly aggressive metastatic OS cells adapt to the lung microenvironment is the subject of the current work. Our research utilizes a pair of clonally related human OS cell lines, MG63.3 and MG63, with highly or poorly metastatic in vivo phenotypes, respectively. These OS cells experience redox stress in the lung microenvironment, as evident by in situ immunoreactivity with 3-nitrotyrosine (3-NT)---a marker of oxidative damage. In cell culture studies where high and poorly metastatic OS cells are exposed to PABA/NO, a chemical inducer of redox stress which also causes 3-NT accumulation, highly metastatic MG63.3 cells show functional differences in their response to redox stress compared to poorly metastatic MG63 cells. MG63.3 cells show lower levels of 3-NT staining, lower levels of caspase 3/7 activity, and have higher growth rates compared to MG63 cells in the presence of PABA/NO. These results suggest that MG63.3 cells show a greater adaptability to redox stress compared to MG63 cells. It is known that regulation of mRNA translation is a mechanism by which cancer cells can quickly adapt to the changing extracellular milieu. Furthermore, it has been shown that MG63.3 cells are able to translate weak mRNAs more efficiently than MG63 cells under stressful conditions. Such weak mRNAs encode for proteins involved in growth and proliferation. When we examine the expression levels of eukaryotic initiation factors such as eIF4E, eIF4G, and eIF4A, all of which are part of the eIF4F cap-initiation complex, we find that certain factors (such as eIF4G1) are differentially upregulated (both at the transcript and protein level) in MG63.3 cells compared to MG63 cells. We hypothesize that inhibition of eIF4G binding to the eIF4F complex will reduce the ability of MG63.3 cell to translate mRNAs important for survival and proliferation during redox stress. To address this hypothesis, we tested whether a small-molecule inhibitor of eIF4G/eIF4E interactions, called 4EGI-1, can sensitize highly metastatic MG63.3 cells to PABA/NO. When exposed to noncytotoxic levels of 4EGI-1 (≤ 20 μM), we find that 4EGI-1 can sensitize MG63.3 cells with lower concentrations of PABA/NO compared to control groups. 4EGI-1 treatment, in the presence of PABA/NO, can cause MG63.3 cells to accumulate higher levels of 3-NT compared to control groups. Furthermore, using an Incucyte machine to assess cell proliferation over 5 days, we find that combination treatment (4EGI-1 and PABA/NO) can greatly inhibit the growth of MG63.3 cells. These results suggest that certain mRNA transcripts that are important in adapting to redox stress are dependent on the eIF4F cap-initiation complex. Efforts are currently under way to further characterize which gene transcripts are important to redox stress adaptation. In addition, by using the pulmonary metastasis assay, we will be assessing whether 4EGI-1 has antimetastatic activity. Collectively, the data presented in the current work suggest that the adaptive mechanisms that metastatic OS cells use to manage redox stress may be an attractive therapeutic target in the development of novel antimetastatic therapeutics. Citation Format: Michael M. Lizardo, Poul Sorensen. Modulation of mRNA translation regulation in highly metastatic ssteosarcoma cells increases their sensitivity to redox stress [abstract]. In: Proceedings of the AACR Conference on Advances in Sarcomas: From Basic Science to Clinical Translation; May 16-19, 2017; Philadelphia, PA. Philadelphia (PA): AACR; Clin Cancer Res 2018;24(2_Suppl):Abstract nr B10.
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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) | 0.003 | 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".