Sp1 coordinately regulates <i>de novo</i> lipogenesis and proliferation in cancer cells
Bibliographic record
Abstract
Cancers express high levels of fatty acid synthase (FAS) from which they derive fatty acids for membrane biosynthesis to sustain cell proliferation. How cancer cells coordinate de novo lipogenesis and proliferation has not been investigated. Transcription factors Sp1, Sp3 and Sp4 are overexpressed in a variety of cancers and regulate gene expression by interacting with GC-rich Sp1 binding sites. Genes encoding FAS and cell cycle proteins such as CDC25A contain Sp1 binding sites in their promoters. We demonstrate by RNA interference that Sp1, Sp3 and Sp4 all play a role in regulating CDC25A expression and proliferation in human breast cancer cells. Only Sp1, however, also regulates FAS. Furthermore, mithramycin, which blocks Sp1 binding sites, decreased proliferation, inhibited CDC25A and FAS expression and reduced binding of Sp1 to the promoters of these genes as assessed by ChIP assays. Conversely, 17beta-estradiol (E(2)) increased proliferation and CDC25A and FAS expression along with increased binding of Sp1 to the promoters of the 2 genes. In addition, we showed that the expression of sterol regulatory element-binding protein-1c (SREBP-1c), the only transcription factor that has been shown to regulate genes of lipogenic enzymes in cancer cells, is also regulated by Sp1. Finally, we demonstrated that Sp1 plays a role in sustaining proliferation and FAS expression in colon as well as prostate cancer cells. Overall, these observations suggest that Sp1 coordinately regulates de novo lipogenesis and proliferation in cancer cells.
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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".