Since Cell Transcriptomic Profiling of Cytochrome P450 Expression in the Lung in COPD
Bibliographic record
Abstract
Abstract Introduction: Cytochrome P450 enzymes (CYPs) metabolize endogenous and exogenous compounds to preserve tissue integrity. The lung is intimately exposed to the environment and CYPs play an indispensable role in detoxifying airborne irritants like cigarette smoke and pollution. In addition, CYPs can both activate and deactivate carcinogens and thus they exert significant effects on lung cancer development, particularly in smokers. CYPs are expressed in the lung in alveolar and airway epithelial cells, endothelial cells, macrophages and smooth muscle cells. The distribution of cytochrome P450 enzymes in the lung underscores their significance and the effects they exert on both protective and potentially harmful metabolic processes in the lung. Given their impact, it is important to understand whether CYP expression changes within the lungs of COPD subjects. Conceivably, changes in CYP expression could alter the metabolism of inhaled irritants potentially influencing the development of lung cancer and other respiratory diseases. Methods: Formalin fixed paraffin embedded (FFPE) lung tissue blocks from age-matched smokers with and without COPD were collected (N=2 per group). 10-micron shavings from these FFPE blocks underwent deparaffination and rehydration of the cells in order to check RNA integrity. Those samples with good RNA integrity were then processed for single cell sequencing. 20-micron shavings from the FFPE blocks with excellent RNA integrity underwent deparaffination and rehydration of the cells. Single cell sequencing was then conducted on these cells isolated from paraffin-embedded, formalin fixed lung tissue from smokers with and without COPD (N=2 per group). CYP expression in the lung was then analyzed. Results: Using shavings from FFPE lung tissue blocks, we were able to obtain high quality scRNA-seq data and identified 20 distinct cell types within our samples (Figure 1). CYP2E1 was widely expressed in the lung and did not concentrate in the airway epithelium (Figure 2). In contrast to CYP2E1, the expression of CYP2F1 focally concentrated in ciliated and Club cells in the lung (Figure 3). Single cell sequencing of cells from the lungs of age-matched healthy and COPD subjects demonstrated reduced expression of CYP2F1 in COPD (Figure 3) and reduced expression of CYP4X1 and CYP2J2 in Cluster 2 in COPD (Table1). Conclusions: This single cell transcriptomic study identified the diverse distribution of CYP enzymes in the lung and found differential expression of CYP enzymes in COPD. Future studies will evaluate the impact of CYP2F1 depletion in COPD by smoke-exposing airway specific CYP2F1 knockout mice to chronic cigarette smoke exposure.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".