Exploring PI3Kδ Molecular Pathways in Stable COPD and Following an Acute Exacerbation, Two Randomized Controlled Trials

Figures & data

Figure 1 mRNA 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).

Table 1 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 2 mRNA 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 3 Inflammatory 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.

Table 2 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 4 Summary 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 5 Lung 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 6 Blood 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).

ECLIPSE investigators; Vestbo J, Anderson W, Coxson HO, et al. Evaluation of COPD longitudinally to identify predictive surrogate end-points (ECLIPSE). Eur Respir J. 2008;31:869–873. doi:10.1183/09031936.00111707

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