Abstract P5-07-06: Kaiso regulates miRNA-31 and miRNA-200 expression in triple negative breast cancer (TNBC) cells
Bibliographic record
Abstract
Abstract Breast cancer (BC) is the most frequent female cancer and a leading cause of female deaths worldwide. BC-related mortality rates are high among African American (AA) women despite the low incidence rates of breast cancer observed in this population compared with Caucasian Americans (CA). The triple negative breast cancer (TNBC) subtype lacks expression of three biomarkers used to clinically classify BC, and thus TNBCs cannot be treated with traditional receptor therapies. Moreover, as TNBC is biologically aggressive and women diagnosed with TNBC have poor outcomes. Interestingly, TNBC is most prevalent in young women of African Ancestry (WAA) compared to women of other ethnicities, but the cause of this racial disparity remains unknown. Recent studies in our lab revealed that the transcription factor Kaiso is highly expressed in TNBC tissues of WAA patients compared with those from Caucasian patients, suggesting a role for Kaiso in TNBC racial disparity. Intriguingly, our lab and others have also reported a correlation between high Kaiso expression, poor overall survival of AA BC patients compared with Caucasian patients, and increased TNBC aggressiveness/metastasis that is in part mediated via the TGFβ signaling pathway. Notably, Kaiso has also been implicated in tumor cell migration via its regulation of the tumor-suppressing microRNA-31 (miR-31) in prostate cancer cells. Remarkably, the pleiotropic miR-31 functions to suppress metastasis and its expression has been shown to be inversely correlated with aggressive breast tumor metastasis. Although Kaiso has been implicated in epithelial-to-mesenchymal transition (EMT) and TNBC metastasis, Kaiso's exact roles in the regulation of miRNAs in the context of TNBC remains to be elucidated. Using chromatin immunoprecipitation (CHIP) analysis, we found that Kaiso binds to the miR-31 and miR-200 promoters, and we detected increased expression of these microRNAs in Kaiso-depleted TNBC cells using qRT-PCR analysis. Furthermore, using immunoblot analysis, we found that Kaiso depletion resulted in reduced expression of the actin remodelling protein WAVE3, which is a downstream target of both miR-31 and miR-200. Consistent with these molecular changes, transfection of TNBC cells with miR-31 and miR-200 mimics resulted in reduced migration of these cells compared to control TNBC cells as assessed via migration assays. These data suggest that Kaiso regulates miR-31 and miR-200 in TNBC cells, and promotes TNBC cell migration via downregulation of these miRNAs. Ongoing studies seek to assess and correlate miR-31 and miR-200 expression with Kaiso expression in TNBC tissues of WAA. Together, our findings raise the exciting possibility that Kaiso may be developed as a potential target for the treatment of TNBC patients. Citation Format: Rayner LGA, Bassey-Archibong BI, Jaber S, Daniel JM. Kaiso regulates miRNA-31 and miRNA-200 expression in triple negative breast cancer (TNBC) cells [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P5-07-06.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".