CXCR1 and CXCR2 Antagonism with G31P Attenuates Chemotherapy-Induced Lung Inflammation and Augments the Gefitinib Therapeutic Response in Lung Cancer
Bibliographic record
Abstract
Objectives: Chemotherapy-induced lung inflammation limits the efficacy of anticancer therapies such as gefitinib in non-small cell lung cancer (NSCLC). Glutamic acid-leucine-arginine positive (ELR+) CXC chemokines and their receptors, CXC chemokine receptor 1 and 2 (CXCR1 and CXCR2), mediate both inflammatory responses and tumor progression. This study evaluated the effects of CXCR1/2 antagonism by G31P, a CXC motif chemokine ligand 8 (CXCL8)-mutated peptide, alone or in combination with gefitinib, on lung cancer growth and chemotherapy-induced pulmonary inflammation. Methods: Human NSCLC cell lines (A549 and H460) were treated with gefitinib and/or G31P. Cell proliferation, apoptosis, and signaling pathways, including protein kinase B (AKT) and extracellular signal-regulated kinase (ERK) phosphorylation, were evaluated by cell counting kit-8 (CCK-8) assay, flow cytometry, and Western blotting. An orthotopic lung tumor xenograft model was established in BALB/c nude mice to evaluate tumor growth, metastasis, cytokine expression, and lung histopathology. A bleomycin-induced lung injury model was also used to assess the anti-inflammatory effects of G31P, with or without gefitinib, by quantitative reverse transcription polymerase chain reaction (qRT-PCR) and flow cytometry of inflammatory markers. Results: , G31P with gefitinib significantly suppressed tumor growth, metastasis, and increased apoptosis. G31P decreased CXCL1 and CXCL2, and tumor necrosis factor-alpha (TNF-α) mRNA levels, lung hydroxyproline content, and myeloperoxidase (MPO) activity in the lungs of mice. In the bleomycin-induced lung injury model, G31P similarly reduced inflammatory responses. Conclusion: CXCR1/2 antagonism by G31P attenuates chemotherapy-induced pulmonary inflammation and enhances the anti-tumor efficacy of gefitinib in NSCLC. These findings support the therapeutic potential of G31P as an adjuvant to epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKIs) to improve clinical outcomes by limiting inflammation.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.001 |
| 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".