Abstract A186: Novel target to control lung tumor growth: Disruption of cell membrane remodeling by modulating myoferlin expression.
Bibliographic record
Abstract
Abstract Introduction: Lung cancer is the leading cause of cancer death in human. One feature of tumor cells is their ability to rapidly proliferate. These fast dividing tumor cells undergo continuous membrane damage and remodeling cycles. Hence, disruption of membrane remodeling and repair could block tumor growth. Myoferlin has been shown to mediate membrane processes such as receptor trafficking and membrane repair via endocytosis and exocytosis. Loss of myoferlin expression in non-cancer cell lines leads to defects in processes essential for cell proliferation, such as trafficking of membrane receptors (1, 2) and repairing ruptured cell membrane (3). Involvement of myoferlin in multifaceted membrane events shared by cancer pathogenesis suggests that modulating myoferlin expression can block tumorigenic activities. Herein, we investigated whether interfering with normal myoferlin expression, membrane repair and remodeling provides therapeutically relevant antitumor effects. Purpose and Hypothesis: Myoferlin regulates lung tumor growth by mediating cell proliferation and membrane remodeling process. Methods and Results: To investigate the potential expression of myoferlin in tumor, we performed Western blot analysis on a range of mouse and human cancer cell lines and immunohistochemistry on mouse and human lung carcinoma tissues. We found that myoferlin was expressed in various human and mouse cancer cell lines as well as solid tumors. With the use of immunofluorescent assay, we visualized the localization of myoferlin expression around the peri-nuclear region, cytoplasm and Golgi apparatus in cultured mouse Lewis lung carcinoma (LLC) cells. To assess the role of myoferlin in tumor pathogenesis, loss of function studies were performed using a myoferlin silencing RNA (siRNA)-based approach. Briefly, mouse Lewis lung carcinoma (LLC) cells were transfected with myoferlin siRNA and the effects of myoferlin knockdown on tumor cell proliferation and membrane repair were evaluated. A mouse xenograft tumor model was also used to determine the effects of myoferlin knockdown on solid tumor growth. Knockdown of myoferlin caused a 90% decrease in proliferation of mouse LLC cells and disabled membrane resealing after membrane damage. In addition, myoferlin siRNA decreased solid lung tumor growth by 55%, which was attributed to substantial reduction of tumor cell proliferation. Conclusion: Our results identify the anti-proliferative effect associated with attenuated myoferlin expression in lung tumor growth both in vitro and in vivo. This opens up a new therapeutic approach for lung cancer. Citation Information: Mol Cancer Ther 2013;12(11 Suppl):A186. Citation Format: Suk Kei Cleo Leung, Carol Yu, Michelle I. Lin, Cristina Tognon, Pascal Bernatchez. Novel target to control lung tumor growth: Disruption of cell membrane remodeling by modulating myoferlin expression. [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2013 Oct 19-23; Boston, MA. Philadelphia (PA): AACR; Mol Cancer Ther 2013;12(11 Suppl):Abstract nr A186.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".