| Literature DB >> 34113094 |
Malcolm Begg1, J Nicole Hamblin1, Emily Jarvis2, Glyn Bradley3, Stephen Mark4, David Michalovich5, Mark Lennon6, Hannah E Wajdner5, Augustin Amour5, Robert Wilson1, Ken Saunders5, Rikako Tanaka7, Saki Arai7, Teresa Tang8, Cedric Van Holsbeke9, Jan De Backer9, Wim Vos9, Ingrid L Titlestad10, J Mark FitzGerald11, Kieran Killian12, Jean Bourbeau13, Claude Poirier14, François Maltais15, Anthony Cahn1, Edith M Hessel1.
Abstract
Background: Inhibition of phosphoinositide 3-kinase δ (PI3Kδ) exerts corrective effects on the dysregulated migration characteristics of neutrophils isolated from patients with chronic obstructive pulmonary disease (COPD). Objective: To develop novel, induced sputum endpoints to demonstrate changes in neutrophil phenotype in the lung by administering nemiralisib, a potent and selective inhaled PI3Kδ inhibitor, to patients with stable COPD or patients with acute exacerbation (AE) of COPD.Entities:
Keywords: COPD exacerbations; PI3Kdelta; nemiralisib; sputum; transcriptomics
Year: 2021 PMID: 34113094 PMCID: PMC8184158 DOI: 10.2147/COPD.S309303
Source DB: PubMed Journal: Int J Chron Obstruct Pulmon Dis ISSN: 1176-9106
Figure 1mRNA transcriptomic alterations in induced sputum from stable COPD patients (Study A). Transcriptomic changes in induced sputum taken from stable COPD patients dosed for 14 days with nemiralisib show a partial clustering by treatment (Panel A). Unbiased pathway analysis highlighted nemiralisib-evoked alterations in neutrophil phenotype and bacterial infection response genes (Panels B and C, left), which were not observed in the samples taken 7 days apart prior to randomization (Panels B and C, right).
Summary of Number of Genes Reaching Cut Offs (Fold Change >1.5 and P<0.05) from the Predefined Gene List, and Entire Gene Array in Sputum and Blood
| Comparison | Sputum Gene Changes Predefined List | Sputum Gene Changes Total Set | Blood Gene Changes Total Set |
|---|---|---|---|
| Screening vs D12 nemiralisib | 29 | 1383 | 336 |
| Screening vs D12 placebo | 35 | 1395 | 90 |
| Screening vs D28 nemiralisib | 3 | 350 | 204 |
| Screening vs D28 placebo | 1 | 329 | 302 |
| Screening vs D84 nemiralisib | 15 | 690 | 529 |
| Screening vs D84 placebo | 29 | 1096 | 590 |
| D84 nemiralisib vs D84 placebo | 10 | 297 | 253 |
Abbreviations: D12, Day 12; D84, Day 84.
Figure 2mRNA transcriptomic alterations in induced sputum from AECOPD patients (Study B). Transcriptomic changes in induced sputum taken from acutely exacerbating COPD patients. Of the predefined neutrophil-related genes a small number were altered in both the nemiralisib and placebo-treated groups (Panel A). The entire unbiased gene array output also showed a similar number of genes changing in the nemiralisib and placebo-treated groups when comparing both day 12 or day 84 to the screening time point (Panel A, SCN v D12). There was a significant overlap in the genes changing between screening and day 12 in the nemiralisib and placebo-treated groups at day 12 and day 84, with almost all genes changing in the same direction (Panel B).
Figure 3Inflammatory biomarkers in induced sputum from AECOPD patients (Study B) Sputum and circulating biomarkers measured were also not impacted by treatment with nemiralisib. Circulating levels of CRP decreased (Panel A, left), as did neutrophil count (Panel A, right), presented as mean (95% CI) at baseline, Day 12, Day 28, Day 56, Day 84 and at follow-up. Total sputum cell count and the inflammatory cytokines IL-8, IL-6 and TNFα were also not inhibited following treatment with nemiralisib (Panel B), presented as geometric mean (95% CI) at baseline, Day 12, Day 28 and Day 84.
Alterations in Functional Respiratory Imaging Endpoints Measured Using HRCT
| Endpoint | Parameter | Region | Placebo (Baseline vs D28, Treatment Ratio (95% Cr I)) | Nemiralisib (Baseline vs D28, Treatment Ratio (95% Cr I)) | Nemiralisib vs Placebo (Baseline vs D28, Treatment Ratio (95% Cr I)) | Probability (θ>1) or (θ<1)a |
|---|---|---|---|---|---|---|
| siVaw | Specific Imaging Airway Volume | Distal | 1.01 (0.83, 1.24) | 1.00 (0.83, 1.20) | 0.98 (0.75, 1.30) | 45.2% |
| siRaw | Specific imaging airway resistance | Distal | 0.97 (0.53, 1.77) | 1.13 (0.63, 2.02) | 1.17 (0.51, 2.72) | 35.6% |
| siVaww | Specific airway wall thickness | Distal | 0.96 (0.88, 1.06) | 0.92 (0.84, 1.00) | 0.95 (0.83, 1.09) | 77.1% |
| LAS | Low attenuation score | Total | 1.01 (0.84, 1.21) | 0.98 (0.83, 1.17) | 0.97 (0.75, 1.26) | 58.6% |
| IALD | Internal airflow lobar distribution | Upper | 1.03 (0.98, 1.09) | 0.99 (0.94, 1.04) | 0.96 (0.89, 1.03) | 59.7% |
| Lower | 0.98 (0.93, 1.02) | 0.99 (0.95, 1.04) | 1.02 (0.95, 1.09) | 97.9% | ||
| BVD | Blood vessel density | Total | 0.95 (0.88, 1.03) | 0.94 (0.88, 1.01) | 0.99 (0.89, 1.10) | 44.4% |
Note: aθ represents the true treatment ratio to placebo.
Abbreviations: BVD, blood vessel density; Cr l, credible interval; D28, day 28; HRCT, high resolution computed tomography; IALD, internal airflow lobar distribution; LAS, low attenuation score; siRaw, specific imaging airway resistance; siVaw, specific imaging airway volume; siVaww, specific imaging airway wall thickness.
Figure 4Summary of statistical analysis of FEV1 and FVC in AECOPD patients (Study B). Treatment with nemiralisib showed an improvement in FEV1 and FVC at all time points. Panel A shows adjusted median change from baseline in FEV1 (95% Cr I), and Panel B shows adjusted median change from baseline in FVC (95% Cr I) measured at clinical visits at baseline, Day 12, Day 28, Day 56 and Day 84. Data presented as adjusted median ± 95% Credible Intervals.
Figure 5Lung transcriptomics during exacerbation recovery (Study B). Combined sputum transcriptomic data shows partial clustering by time point (Panels A and B). Unbiased overlay analysis showed a highly significant overlap with data from ECLIPSE .27,30 The degree of overlap and gene directionality for the matching genes are displayed in (Panel C).
Figure 6Blood transcriptomics during exacerbation recovery (Study B). Combined blood transcriptomic data shows partial clustering by time point (Panels A and B). Unbiased overlay analysis showed a highly significant overlap with data from ECLIPSE.27,30 The degree of overlap and gene directionality for the matching genes are displayed in (Panel C).