Abstract NTOC-083: TARGETED APPROACH WITH MOMELOTINIB TREATMENT ATTENUATES PACLITAXEL–INDUCED ENRICHMENT OF CANCER STEM CELLS (CSC)–LIKE AND SUPPRESSES OVARIAN CANCER TUMORIGENESIS AND RECURRENCE
Bibliographic record
Abstract
Abstract INTRODUCTION: In the era of personalised medicine, chemotherapy treatment alone is inadequate to treat advanced-stage ovarian cancer patients, given that a steady 75% of patients relapse within five years and die of this disease. We have shown that chemotherapy-treated ovarian cancer cell lines express significantly elevated JAK2/STAT3 activation and CSC-like compared to untreated cells in vitro and in vivo mouse models. We aim to investigate the in vivo significance of targeting paclitaxel-induced ovarian CSC-like and the associated JAK2/STAT3 activation using the JAK2-specific inhibitor, Momelotinib. METHODS: Female Balbc nu/nu mice were injected ip with HEY cells and treated at day 19 with paclitaxel (15mg/kg bodyweight) weekly by ip injection and/or Momelotinib (25mg/kg bodyweight) daily by oral gavage. Study 1: All treatment groups (n=3/group) were sacrificed at the same time as the untreated control group (n=4). Study 2: All treatments were terminated after the endpoint of untreated group groups and were sacrificed at their respective endpoints (n=4). Study 3: Paclitaxel+Momelotinib-treated group was further divided into two groups (n=9/group) after the endpoint of the untreated group: (i) termination of paclitaxel and Momelotinib treatments, and (ii) termination of paclitaxel treatment alone for 13 weeks. One-way ANOVA was used to compare the tumour burden (tumour wt/mice wt), survival period, and immunohistochemistry analysis of the tumour xenograft for the activated JAK2/STAT3 and CSC-like markers (Oct3/4 and c-Kit) expressions between multiple groups. Statistical significance was defined as a p value < 0.05. RESULTS: In Study 1, paclitaxel+Momelotinib-treated group produced the smallest tumour burden compared to all groups, and had tumours that showed a reduction in the activated JAK2/STAT3 pathway and CSC-like markers expressions when compared to the paclitaxel-treated group. In Study 2, paclitaxel+Momelotinib-treated group survived the longest compared to all groups. In Study 3, paclitaxel+(ongoing)Momelotinib-treated group survived substantially longer and produced a significantly smaller tumour burden compared to the untreated and paclitaxel+(terminated) Momelotinib-treated groups. Expressions of the activated JAK2/STAT3 and CSC-like markers were significantly upregulated in the tumours isolated from paclitaxel+Momelotinib-treated group post-Momelotinib termination compared to pre-Momelotinib termination. CONCLUSION: Targeting the paclitaxel-induced JAK2/STAT3 activation and CSC-like using Momelotinib not only enhanced paclitaxel cytotoxicity but also prolonged the survival of HEY-bearing mice. This strongly supports the idea for future clinical testing using Momelotinib (currently in Phase 3 clinical trials for treating myelofibrosis) in combination with paclitaxel for advanced-stage ovarian cancer patients. These results also support the use of Momelotinib as a maintenance treatment for the ongoing suppression of the activated JAK2/STAT3 pathway in an attempt to prevent a relapse in ovarian cancer patients. Citation Format: Chan. E, Findlay. JK, Luwor. R, Hickey. M, Ahmed. N. TARGETED APPROACH WITH MOMELOTINIB TREATMENT ATTENUATES PACLITAXEL–INDUCED ENRICHMENT OF CANCER STEM CELLS (CSC)–LIKE AND SUPPRESSES OVARIAN CANCER TUMORIGENESIS AND RECURRENCE [abstract]. In: Proceedings of the 11th Biennial Ovarian Cancer Research Symposium; Sep 12-13, 2016; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(11 Suppl):Abstract nr NTOC-083.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".