Abstract 4852: Targeting cancer progression genes upregulated in CREB3L1-deficient breast cancer cells
Bibliographic record
Abstract
Abstract Introduction: Our laboratory is interested in determining ways to block breast cancer metastasis. We discovered that CREB3L1 (cAMP responsive element binding protein 3-like protein), a stress-activated transcription factor, acts as a metastasis suppressor in breast cancer. CREB3L1 is expressed ubiquitously in noncancerous human breast cells and restricts expression of genes that promote cell growth, angiogenesis, and migration. Loss of CREB3L1 expression is a frequent event in high-grade metastatic human breast tumors and can result in enhanced metastatic properties. Experimental Procedures: To establish the mechanisms by which CREB3L1 exerts its tumor suppressive effects, a gene expression microarray analysis was performed to determine which genes are upregulated in CREB3L1-deficient breast cancer cells. Six hundred and eighty genes were statistically significantly upregulated at least 2-fold in all 4 of the CREB3L1-deficient cell lines assessed. To focus our analysis, 4 genes were identified as potential targets for this study, given that they have previously been shown to have a role in cancer progression. Knockdowns were generated for each of the 4 genes in a CREB3L1-deficient breast cancer cell line (HCC1806) and matched CREB3L1-expressing cells (HCC1806 + HA-CREB3L1), as well as a nontumorigenic control breast cell line (MCF10A). To knockdown expression of each of the 4 targets, shRNA directed at the gene of interest was transduced via a lentiviral system into the cells. Cell-based assays were performed to characterize the properties of these cell lines, which included the Boyden chamber assay to measure migration, soft agar assay to assess anchorage-independent growth, and the MTT assay to evaluate cell proliferation. Results: Successful knockdown at both the mRNA and protein level for each target gene was validated using quantitative real time PCR and immunoblotting. Results from the MTT assay verified that knockdown of each of the 4 gene targets did not affect cell survival in MCF10A cells, confirming that these test genes are not essential for survival in noncancerous breast cells (p > 0.05). Similarly, knockdown of each of the test genes did not affect cell proliferation in HCC1806 (± CREB3L1) cells, except for a significant decrease in proliferation in HCC1806 CREB3L1-deficient cells with Gene 1 knockdown (p =0.02). Preliminary results indicate that knockdown of Genes 1, 2, and 4 in HCC1806 CREB3L1-deficient cells reduces cancer cell properties, including cell migration and anchorage-independent growth (p < 0.05). Conclusions: Promising candidates will be tested in follow-up mouse xenograft studies. Encouraging results in these pre-clinical models would provide a strong rationale for the development and testing of inhibitors to one or more of these potential targets as a new therapeutic for the 30% of breast cancers that are CREB3L1-deficient. Citation Format: Deborah Anderson, Shari Smith, Farah Goubran, Paul Mellor. Targeting cancer progression genes upregulated in CREB3L1-deficient breast cancer cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4852. doi:10.1158/1538-7445.AM2017-4852
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".