Reduced CREB3L1 expression in triple negative and luminal a breast cancer cells contributes to enhanced cell migration, anchorage-independent growth and metastasis
Bibliographic record
Abstract
Women with metastatic breast cancer have a disheartening 5-year survival rate of only 28%. CREB3L1 (cAMP-responsive element binding protein 3 like 1) is a metastasis suppressor that functions as a transcription factor, and in an estrogen-dependent model of rat breast cancer, it repressed the expression of genes that promote breast cancer progression and metastasis. In this report, we set out to determine the expression level of CREB3L1 across different human breast cancer subtypes and determine whether CREB3L1 functions as a metastasis suppressor, particularly in triple negative breast cancers (TNBCs). CREB3L1 expression was generally increased in luminal A, luminal B and HER2 breast cancers, but significantly reduced in a high proportion (75%) of TNBCs. Two luminal A (HCC1428, T47D) and two basal TNBC (HCC1806, HCC70) CREB3L1-deficient breast cancer cell lines were characterized as compared to their corresponding HA-CREB3L1-expressing counterparts. HA-CREB3L1 expression significantly reduced both cell migration and anchorage-independent growth in soft agar but had no impact on cell proliferation rates as compared to the CREB3L1-deficient parental cell lines. Restoration of CREB3L1 expression in HCC1806 cells was also sufficient to reduce mammary fat pad tumor formation and lung metastases in mouse xenograft models of breast cancer as compared to the parental HCC1806 cells. These results strongly support a metastasis suppressor role for CREB3L1 in human luminal A and TNBCs. Further, the ability to identify the subset of luminal A (7%) and TNBCs (75%) that are CREB3L1-deficient provides opportunities to stratify patients that would benefit from additional treatments to treat their more metastatic disease.
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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 | 0.000 |
| 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".