A115 MODELING CYSTIC FIBROSIS (CF) INTESTINAL DISEASE USING PATIENT DERIVED TISSUES
Bibliographic record
Abstract
Abstract Background Cystic Fibrosis is caused by mutations in the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) gene, which encodes for a chloride/bicarbonate anion channel expressed on the apical membrane of most epithelial tissues, such as the lungs, liver, pancreas, small and large intestines, and reproductive tissues. CFTR is responsible for the transport of chloride and bicarbonate ions to maintain tissue surface hydration and pH balance of epithelial tissues. Historically, recurrent lung infections have been the most common cause of mortality in CF patients. With advances in clinical care and therapeutics, the current mean survival age of Canadian patients has increased to 52.3 years. However, this increase in survival has also been associated with an elevated risk of developing gastrointestinal cancers in CF adults. Compared to the general public, CF patients are 10 times more likely to develop cancer. This risk is increased to 25-20 times in patients that have undergone organ transplantations. Although the exact molecular mechanism regarding increased cancer risk in CF remains unclear, chronic intestinal inflammation has been known to contribute to elevated cancer development. Aims CF patients display an increased baseline inflammatory status that is exacerbated with microbiome exposure leading to possible increased risk for inflammation-mediated cancer development. Methods To reduce inter-patient heterogeneity, we have differentiated human intestinal organoids using induced pluripotent stem cells from homozygous F508del CF patients and gene edited isogenic non-CF (Wt-CFTR) controls. We conducted gene expression studies using RT-qPCR to determine baseline differences in gene expression prior to environmental exposures and following exposure to LPS and flagellin. Results We determined the expression levels of stem cell, intestinal epithelial cell, innate immunity genes and differentiation markers and found expression of such genes were not significantly different between 3D CF and gene-edited non-CF organoids. We are currently conducting RNA sequencing to survey expression pattern of all genes to definitively determine possible fundamental changes in the CF intestinal epithelium and determining the effect of LPS and flagellin treatment to determine if there is an altered response to inflammatory stimuli. Conclusions iPSC derived HIOs is a novel, patient based, and renewable model that can be used to dissect the primary intestinal pathologies in CF. Transcriptomic data of CF HIOs at steady state will provide insights to possible developmental defects. Complex interactions between the host intestinal epithelia and the commensal microbiome can also be investigated using this model. Funding Agencies CAG
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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".