Identification of the SRC pyrimidine-binding protein (SPy) as hnRNP K: implications in the regulation of SRC1A transcription
Bibliographic record
Abstract
The human SRC gene encodes pp60(c-src), a non-receptor tyrosine kinase involved in numerous signaling pathways. Activation or overexpression of c-Src has also been linked to a number of important human cancers. Transcription of the SRC gene is complex and regulated by two closely linked but highly dissimilar promoters, each associated with its own distinct non-coding exon. In many tissues SRC expression is regulated by the housekeeping-like SRC1A promoter. In addition to other regulatory elements, three substantial polypurine:polypyrimidine (TC) tracts within this promoter are required for full transcriptional activity. Previously, we described an unusual factor called SRC pyrimidine-binding protein (SPy) that could bind to two of these TC tracts in their double-stranded form, but was also capable of interacting with higher affinity to all three pyrimidine tracts in their single-stranded form. Mutations in the TC tracts, which abolished the ability of SPy to interact with its double-stranded DNA target, significantly reduced SRC1A promoter activity, especially in concert with mutations in critical Sp1 binding sites. Here we expand upon our characterization of this interesting factor and describe the purification of SPy from human SW620 colon cancer cells using a DNA affinity-based approach. Subsequent in-gel tryptic digestion of purified SPy followed by MALDI-TOF mass spectrometric analysis identified SPy as heterogeneous nuclear ribonucleoprotein K (hnRNP K), a known nucleic-acid binding protein implicated in various aspects of gene expression including transcription. These data provide new insights into the double- and single-stranded DNA-binding specificity, as well as functional properties of hnRNP K, and suggest that hnRNP K is a critical component of SRC1A transcriptional processes.
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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) | 0.000 | 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".