Tissue-specific and SRSF1-dependent splicing of fibronectin, a matrix protein that controls host cell invasion
Bibliographic record
Abstract
Cell invasion targets specific tissues in physiological placental implantation and pathological metastasis, which raises questions about how this process is controlled. We compare dermis and endometrium capacities to support trophoblast invasion, using matching sets of human primary fibroblasts in a coculture assay with human placental explants. Substituting endometrium, the natural trophoblast target, with dermis dramatically reduces trophoblast interstitial invasion. Our data reveal that endometrium expresses a higher rate of the fibronectin (FN) extra type III domain A+ (EDA+) splicing isoform, which displays stronger matrix incorporation capacity. We demonstrate that the high FN content of the endometrium matrix, and not specifically the EDA domain, supports trophoblast invasion by showing that forced incorporation of plasma FN (EDA-) promotes efficient trophoblast invasion. We further show that the serine/arginine-rich protein serine/arginine-rich splicing factor 1 (SRSF1) is more highly expressed in endometrium and, using RNA interference, that it is involved in the higher EDA exon inclusion rate in endometrium. Our data therefore show a mechanism by which tissues can be distinguished, for their capacity to support invasion, by their different rates of EDA inclusion, linked to their SRSF1 protein levels. In the broader context of cancer pathology, the results suggest that SRSF1 might play a central role not only in the tumor cells, but also in the surrounding stroma.
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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".