The Role of Speedy/RINGO in Triple Negative Breast Cancer Metastasis
Bibliographic record
Abstract
Breast cancer is the most prevalent malignancy and the second leading cause of death among Canadian women. Triple negative breast cancer (TNBC) is an aggressive form of breast cancer accounting for 10-20% of breast cancer diagnoses, affecting younger women, and has higher relapse rates than other forms of breast cancer. The tumour microenvironment plays a pivotal role in TNBC progression and metastasis. While much is known about microenvironmental factors in the extracellular matrix, there remains a gap in understanding the role of cell cycle regulators in these processes. Speedy/RINGO is a family of atypical cyclin-like proteins and has emerged as key players in promoting cell cycle progression in breast cancer. Speedy/RINGO can promote progression through cell cycle checkpoints and is elevated in TNBC. This thesis aims to investigate SpdyA and SpdyC family members potential impact on TNBC cell adhesion, migration, and invasion. In vitro studies will use the TNBC cell lines (MDA-MB-231 and MDA-MB-468) to determine the role of SpdyA and SpdyC in mediating metastatic properties of TNBC cells through different cellular substrates and to investigate integrin signaling and MAPK pathway activation. We report for the first time the effects of CRISPR-Cas9 mediated knockout of SpdyA, as well as the influence of overexpression of SpdyA and SpdyC on functional characteristics of TNBC cells. This work aids in the development of better diagnostic markers for metastatic cancer and more personalized therapeutics to treat metastatic breast cancer as well as providing support for targeting Speedy/RINGO as a new therapeutic strategy in TNBC.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".