Screening of candidate adenovirus expressing shRNAs for functional recovery of dF508-CFTR
Bibliographic record
Abstract
Devising molecular strategies that overcome ΔF508 folding and trafficking defects comprise a central objective of CF therapeutic development. An understanding of disease mechanisms can be improved by new method(s) and/or compounds that redirect ΔF508-CFTR to the plasma membrane. RNA interference (siRNA) mediated knock-down of gene expression has proven to be a powerful tool for investigating protein function(s) and advancing drug discovery. BioFocus (a Galapagos company) has developed adenoviral vectors expressing small hairpin RNAs (shRNAs) for genomewide functional screening that allow robust transduction and durable gene repression. In this project, sixty-eight adenoviral-shRNA constructs (targeting 28 high priority genes) were provided by BioFocus to five collaborating laboratories in the United States and Canada. Putative gene targets were identified by a consortium-based review of the existing CF literature. Each research group established independent protocols to investigate effect(s) of gene knock-down (via Ad-shRNA) on ΔF508-CFTR maturation. Protocols included 1) A study of CF bronchial epithelial cells expressing the halide sensitive variant of eYFP and measurement of ΔF508-CFTR activity at the cell surface. 2) Short circuit current in primary human bronchial epithelial cells (ΔF508/ΔF508), 3) Appearance of rescued ΔF508 CFTR at the plasma membrane in CF bronchial epithelial cells monitored biochemically, 4) Effects on CFTR-dependent release of inflammatory markers (chemokines and cytokines) from IB3 cells (ΔF508/W1282X), and 5) Short circuit current and Western blotting in CFBE cells transduced with lentivirus encoding ΔF508-CFTR. Preliminary results indicate significant activity of BioFocus shRNAs in several of the independent protocols and laboratories, particularly against gene products such as AHSA1 and 2 (activators of HSP 90) and HDAC7A (a member of the histone deacetylase family). A profile of shRNAs found to improve ΔF508 processing, including spectrum of activity data and gene-network annotation of the relevant pathways, will be presented. Identifying the most robust molecular targets for ΔF508 CFTR correction (from among hundreds of candidates in the CFTR “interactome”) has been limited by the complexity of the relevant cellular pathways. The studies described here provide a means by which chaperones and other contributors to CFTR misprocessing can be evaluated, prioritized, and better understood in the future for development of new therapeutic approaches and delineating genetic modifiers that contribute to variation in severity of CF onset and disease progression. The project represents a collaboration among members of the CFTR Folding Consortium. Supported by the CFF and NIH.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 0.001 |
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".