The Clinical Role of SRSF1 Expression in Cancer: A Review of the Current Literature
Bibliographic record
Abstract
Background: SFRS1 is a member of the splicing factor protein family. Through a specific sequence of alteration, SRSF1 can move from the cytoplasm to the nucleus where it can work autonomously as a splicing activator, or as a silencer when interacting with other regulators. Alternative splicing (AS) is a fundamental biological process that ensures protein diversity. In fact, different proteins, produced by alternative splicing, can gain different and even antagonistic biological functions. Methods: Our review is based on English articles published in the MEDLINE/PubMed medical library between 2000 and 2021. We retrieved articles that were specifically related to SRSF1 and cancers, and we excluded other reviews and meta-analyses. We included in vitro studies, animal studies and clinical studies, evaluated using the Medical Education Research Study Quality Instrument (MERSQI) and the Newcastle–Ottawa Scale-Education (NOSE). Result: SRSF1 is related to various genes and plays a role in cell cycle, ubiquitin-mediated proteolysis, nucleotide excision repair, p53 pathway, apoptosis, DNA replication and RNA degradation. In most cases, SRSF1 carries out its cancer-related function via abnormal alternative splicing (AS). However, according to the most recent literature, SRSF1 may also be involved in mRNA translation and cancer chemoresistance or radio-sensitivity. Conclusion: Our results showed that SRSF1 plays a key clinical role in tumorigenesis and tumor progression in several types of cancer (such as Prostate, Lung, Breast, Colon, Glioblastoma), through various mechanisms of action and different cellular pathways. This review could be a starting point for several studies regarding the biology of and therapies for cancer.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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 | 0.001 | 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 teacher head, 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".