Characterization of a novel <i>FADS2</i> transcript variant: implications for D6D activity regulation in cells
Bibliographic record
Abstract
Delta-6-desaturase (D6D) activity is deficient in MCF-7 and other cancer cell lines, but it is not explained by FADS2 gene mutations. This deficient activity was not ameliorated by induction of the FADS2 gene; therefore, we hypothesized that some of the induced FADS2 transcript variants (tv) may play a negative regulatory role. FADS2_tv1 is the reference FADS2 tv, coding for full-length D6D isoform 1 (D6D-iso1), and alternative transcriptional start sites result in FADS2_tv2 and FADS2_tv3 variants encoding D6D-iso2 and D6D-iso3 isoforms, respectively, which lack the catalytically critical N-terminal domain. In MCF-7 cells, FADS2_tv2 and FADS2_tv3 were expressed at significantly higher levels than FADS2_tv1. Overexpression of FADS2_tv2 in HEK293 cells confirmed that D6D-iso2 is non-functional, and co-transfection demonstrated a dominant-negative role for D6D-iso2 in D6D-iso1 activity regulation. FADS2_tv2 was expressed at higher levels than FADS2_tv1 in HeLa, MDA-MB-435, MCF-10 A, and HT-29 cells, but at lower levels in A549, MDA-MB-231, and LNCaP cells. Overexpression studies indicated roles for FADS2 variants in proliferation and apoptosis regulation, which were also cell-line specific. Increased FADS2_tv2 expression provides a new mechanism to help explain deficient D6D activity in MCF-7 and other cancer cell lines, but it is not a hallmark of malignant cells.
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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) | 0.001 | 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".