Abstract 152: Galectin-7 increases the invasive behavior of ovarian cancer cells and promotes tumor escape
Bibliographic record
Abstract
Abstract Ovarian cancer is the fifth leading cause of cancer-related deaths in the Western world, the second most common gynecological cancer and the leading cause of death from gynecological malignancies. Epithelial ovarian cancer (EOC) accounts for the majority of ovarian cancers. Here, we have investigated the role of galectin-7 in EOC. Galectin-7 is an epithelial cell marker which has been shown to play an important role in the progression of many types of cancer, including breast cancer and colon cancer. Galectins play an important role in several physiological processes, including cell migration, programmed cell death and regulation of the immune response. They are also involved in a number of pathological conditions, including cancer. In fact, galectins have been shown to create an immunosuppressive tumor microenvironment by killing helper and effector T cells. They can also bind to the surface of tumor cells to form cell surface lattice that stabilizes the expression of key growth factor receptors, thereby increasing cell growth, motility, and production of matrix metalloproteinases. Using tissue microarrays, we found that gal-7 expression increases in malignant tumors compared to normal tissues and benign tumors. Detection of galectin-7 was also more frequent in tissue samples with metastasis as compared to non-metastatic primary tumor samples. Western blot analysis showed that OVCAR-3 EOC cells secrete gal-7, while no expression was detected in COV-434, A2780 and SK-OV-3 cell lines. Treatment of EOC cells with recombinant gal-7 increased their invasive behavior through matrigel and their ability to express MMP-9, an extracellular protease which confers an invasive phenotype to cancer cells. Treatment of freshly isolated human PBMCs with gal-7 also showed gal-7 increased apoptosis of monocytes, T CD4+ and T CD8+ cells. Overall, these data provide impetus for further studies to determine the potential of gal-7 as a therapeutic target for the treatment of EOC. Citation Format: Marilyne Labrie, Maria Claudia Vladoiu, Andrée-Anne Grosset, Louis Gaboury, Yves St-Pierre. Galectin-7 increases the invasive behavior of ovarian cancer cells and promotes tumor escape. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 152. doi:10.1158/1538-7445.AM2014-152
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 |
| 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 teacher head, 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".