Similar Programmed Death Ligand 1 (PD-L1) expression profile in patients with mild COPD and lung cancer
Bibliographic record
Abstract
Abstract Rationale: Programmed Death Ligand 1 (PD-L1) is crucial in regulating the immunological tolerance in non-small cell lung cancer (NSCLC). Alveolar macrophage (AM)-derived PD-L1 binds to its receptor, PD-1, on surveilling lymphocytes, leading to lymphocyte exhaustion. Increased PD-L1 expression is associated with cigarette smoke (CS)-exposure. However, the PD-L1 role in CS-associated lung diseases associated with NSCLC, such as chronic obstructive pulmonary disease (COPD), is still unclear. Methods: In two different cohorts of ever smokers with COPD or NSCLC, and ever and never smoker controls, we evaluated PD-L1 expression: 1) via cutting-edge digital spatial proteomic profiling (Geomx) of formalin-fixed paraffin-embedded (FFPE) lung tissue sections (n=19) ; and 2) via triple immunofluorescence staining of bronchoalveolar lavage (BAL) AMs (n = 83). PD-L1 mRNA expression was also quantified in BAL AMs exposed to CS extract. Results: PD-L1 expression was increased in the bronchiolar wall, parenchyma, and vascular wall from global initiative for chronic lung disease (GOLD) 1-2 COPD patients compared to patients with GOLD 3-4 COPD and controls. Within all the COPD patients, PD-L1 protein expression was strongly directly correlated with the FEV1 % predicted, indicating higher PD-L1 expression in the milder vs. more severe COPD stages. In bronchioles, PD-L1 levels were strongly directly correlated with the number of functionally active AMs. In BAL, we confirmed that AMs from patients with both GOLD 1-2 COPD and NSCLC had the highest and similar, PD-L1 expression levels vs. all the other groups, independently from active cigarette smoking. Intriguingly, AMs from patients with more severe COPD (GOLD 3-4) had reduced AM PD-L1 expression compared to GOLD 1-2 COPD patients. Acute CS extract stimulation increased PD-L1 mRNA expression only in never-and not in ever-smoker AMs. Conclusions: Lungs from patients with mild COPD and NSCLC are characterized by a similar strong PD-L1 expression signature in bronchioles and functionally active AMs compared to patients with severe COPD and controls. Active smoking does not affect PD-L1 levels. These observations represent a new resource in understanding the innate immune mechanisms underlying the link between COPD and lung cancer onset and progression and pave the way to future studies focused on the mechanisms by which CS promotes tumorigenesis and COPD.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.003 |
| Research integrity | 0.000 | 0.004 |
| 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 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".