A Novel Processing-Free Method for RNAseq Analysis of Spontaneous Sputum in Chronic Obstructive Pulmonary Disease

Abstract

Background: Assessments of airways inflammation in patients with chronic obstructive pulmonary disease (COPD) require semi-invasive procedures and specialized sample processing know-how. In this study we aimed to set up and validate a novel non-invasive processing-free method for RNA sequencing (RNAseq) of spontaneous sputum samples collected from COPD patients.Methods: Spontaneous sputum samples were collected and stabilized, with or without selection of plugs and with or without the use of a stabilizer specifically formulated for downstream diagnostic testing (PrimeStore® Molecular Transport Medium). After 8 days storage at ambient temperature RNA was isolated according to an optimized RNAzol® method. An average percentage of fragments longer than 200 nucleotides (DV200) >30% and an individual yield >50 ng were required for progression of samples to sequencing. Finally, to assess if the transcriptome generated would reflect a true endotype of COPD inflammation, the outcome of single-sample gene-set enrichment analysis (ssGSEA) was validated using an independent set of processed induced sputum samples. Results: RNA extracted from spontaneous sputum using a stabilizer showed an average DV200 higher than 30%. 70% of the samples had a yield >50 ng and were submitted to downstream analysis. There was a straightforward correlation in terms of gene expression between samples handled with or without separation of plugs. This was also confirmed by principal component analysis and ssGSEA. The top ten enriched pathways resulting from spontaneous sputum ssGSEA were associated to features of COPD, namely, inflammation, immune responses and oxidative stress; up to 70% of these were in common within the top ten enriched pathways resulting from induced sputum ssGSEA.Conclusion: This analysis confirmed that the typical COPD endotype was represented within spontaneous sputum and supported the current method as a non-invasive processing-free procedure to assess the level of sputum cell inflammation in COPD patients by RNAseq analysis.

The PDE4 inhibitor tanimilast shows distinct immunomodulatory properties associated with a type 2 endotype and CD141 upregulation

“…Buffy coats from blood donations of 3 to 4 (as specified in each Figure and legend) anonymous healthy donors were obtained and preserved by the Centro Trasfusionale, Spedali Civili of Brescia according to the Italian law concerning blood component preparation and analysis. Peripheral blood mononuclear cells (PBMC) were obtained by density gradient centrifugation and monocytes were subsequently purified by immunomagnetic separation using anti CD14-conjugated magnetic microbeads (Miltenyi Biotec) according to the manufacture's protocol and as previously published [21]. Briefly, Conclusion: Taken together, these findings demonstrate distinct immunomodulatory properties of tanimilast associated with a type 2 endotype and CD141 upregulation in DCs and provide a mechanistic rationale for the administration of tanimilast on top of inhaled corticosteroids.…”

“…However, excessive T cell activation and polarization paves the way to the development of chronic inflammatory and autoimmune diseases [19,20]. Notably, T cell activation is one of the main biological processes activated in COPD [21], together with Th1/Th17 skewed T-cell responses, CD8 + T cell activation and continuous inflammation with neutrophil and macrophage infiltration [22,23]. Therefore, DCs are a relevant pharmacological targets to selectively modulate the T effector response in COPD [24].…”

Severity of Lung Function Impairment Drives Transcriptional Phenotypes of COPD and Relates to Immune and Metabolic Processes

“…Transcriptomics can provide useful information relating to disease heterogeneity, mechanisms of pathogenesis, treatment responses and classifications of COPD, along with an opportunity for novel biomarker discovery. 9,10 Over the past few years, a number of studies have examined transcriptomics in COPD cohorts using samples obtained from lung tissue, [11][12][13][14][15][16] blood, [16][17][18][19][20][21][22] and spontaneous 23 and induced sputum. 16,[20][21][22][24][25][26][27] However, these studies have not investigated unbiased clustering of whole transcriptomic profiles, how these clusters relate to clinical and inflammatory phenotypes, and what underlying mechanisms and features are driving these transcriptional clusters.…”