Alternative Splicing as a Target for Cancer Treatment
Bibliographic record
Abstract
Alternative splicing is a key mechanism determinant for gene expression in metazoan. During alternative splicing, non-coding sequences are removed to generate different mature messenger RNAs due to a combination of sequence elements and cellular factors that contribute to splicing regulation. A different combination of splicing sites, exonic or intronic sequences, mutually exclusive exons or retained introns could be selected during alternative splicing to generate different mature mRNAs that could in turn produce distinct protein products. Alternative splicing is the main source of protein diversity responsible for 90% of human gene expression, and it has recently become a hallmark for cancer with a full potential as a prognostic and therapeutic tool. Currently, more than 15,000 alternative splicing events have been associated to different aspects of cancer biology, including cell proliferation and invasion, apoptosis resistance and susceptibility to different chemotherapeutic drugs. Here, we present well established and newly discovered splicing events that occur in different cancer-related genes, their modification by several approaches and the current status of key tools developed to target alternative splicing with diagnostic and therapeutic purposes.
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 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 | 0.001 |
| 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".