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Paraspinous muscle gene expression profiling following simulated staged endovascular repair of thoracoabdominal aortic aneurysm: exploring potential therapeutic pathways

Paraspinous muscle gene expression profiling following simulated staged endovascular repair of... Abstract Open in new tabDownload slide Open in new tabDownload slide OBJECTIVES Thoracic endovascular techniques for aneurysm repair offer less invasive alternatives to open strategies. Both approaches, however, are associated with the risk for neurological complications. Despite adjuncts to maintain spinal cord perfusion, ischaemia and paraplegia continue to occur during thoracoabdominal aortic aneurysm (TAAA) repair. Staging of such extensive procedures has been proven to decrease the risk for spinal cord injury. Archived biopsy specimens may offer insight into the molecular signature of the reorganization and expansion of the spinal collateral network during staged endovascular interventions in the setting of TAAA. METHODS Biological replicates of total RNA were isolated from existing paraspinous muscle samples from 22 Yorkshire pigs randomized to 1 of 3 simulated TAAA repair strategies as part of a previous study employing coil embolization of spinal segmental arteries within the thoracic and lumbar spine. Gene expression profiling was performed using the Affymetrix GeneChip Porcine array. RESULTS Microarray analysis identified 649 differentially expressed porcine genes (≥1.3-fold change, P ≤ 0.05) when comparing paralysed and non-paralysed subjects. Of these, 355 were available for further analysis. When mapped to the human genome, 169 Homo sapiens orthologues were identified. Integrated interpretation of gene expression profiles indicated the significant regulation of transcriptional regulators (such as nuclear factor кB), cytokine (including CXCL12) elements contributing to hypoxia signalling in the cardiovascular system (vascular endothelial growth factor and UBE2) and cytoskeletal elements (like dystrophin (DMD) and matrix metallopeptidase (MMP)). CONCLUSIONS This study demonstrates the ability of microarray-based platforms to detect the differential expression of genes in paraspinous muscle during staged TAAA repair. Pathway enrichment analysis detected subcellular actors accompanying the neuroprotective effects of staged endovascular coiling. These observations provide new insight into the potential prognostic and therapeutic value of gene expression profiling in monitoring and modulating the arteriolar remodelling in the collateral network. Endovascular, Embolization, Thoracoabdominal, Aneurysm, Transcriptomics, Paraplegia INTRODUCTION Mortality associated with thoracoabdominal aortic aneurysm (TAAA) is high in the absence of timely surgical intervention. Surgical and endovascular approaches are not without potential complications and adverse neurological outcomes associated with repairs—ranging from paraparesis to paralysis—can be life-limiting [1–3]. Contemporary strategies to reduce the physiological insult to the spinal cord—including hypothermia [4], cerebrospinal fluid drainage [5], electrophysiological monitoring [6] and adjunctive pharmacological therapies [7]—have dramatically reduced the incidence of paraplegia. Despite these advancements in perioperative care, spinal cord injury (SCI) continues to occur in up to 20% of patients undergoing thoracic endovascular aortic repair of descending thoracic and TAAAs, as well as thoracic aortic dissections [8, 9]. Clinical and translational studies have offered great insight into the anatomic and physiological responses accompanying TAAA repair [10, 11]. Notably, the contribution of the segmental arteries (SA) and extra-SA to the perfusion of the spinal cord and paraspinous muscle (PM) has been highlighted through this work. Our casting model and computed tomography scan imaging studies have demonstrated the nature of the communication between the SA and the aorta; anastomosing with the subclavian arteries cranially and median sacral arteries (equivalent to the hypogastric arteries in humans) caudally, the SA also importantly communicate with the anterior spinal artery [12, 13]. In vivo models have demonstrated that, within 5 days of extensive sacrifice of SAs, there is a quantifiable change from a random to a parallel orientation of arterial vessels within the PM [13]. Along with this adaptation, evidence of an 80–100% increase in the number and density of connections between the anterior spinal artery and the vasculature of the PM adjacent to the spinal cord within 120 h of SA interruption has also been reported [12]. Given evidence that the arteries of the collateral network (CN) connect both the circulation of the spinal cord and paravertebral tissues [14], and extensive sacrifice of SA within the arcades of the SA can inversely influence perfusion pressures leading to negative functional outcomes, the present study is directed at using PM as a surrogate to elucidate the confluence between molecular, cellular and functional responses to interruptions in spinal cord perfusion. Our laboratory has shown that staging TAAA repairs mitigates the unavoidable periods of spinal cord ischaemia; the anatomical changes have been confirmed by both histological examination of spinal cord segments and electron microscopic visualization of arterioles within the paraspinal network [15–19]. Despite the benefits of selective SA endovascular coil embolization, routine application of this approach can be challenging due to anatomical variation, severity of aortic atheroma burden and urgency of intervention. Due to these limitations, exploration of molecular and cellular responses to ischaemia-mediated, stress-induced mechanisms in the CN is a preliminary step towards understanding the gene-level responses to occlusion of SA. To this end, this transcriptomic analysis is the first study using archived PM muscle samples—obtained as part of a previous investigation—to illuminate the gene expression profiles accompanying the conditioning of the spinal CN induced by local responses to hypoxia (angiogenesis) and changes in intravascular fluid dynamics (arteriogenesis). Synthesizing information from our experimental model and clinical observations, the goal of this investigation is to provide new insight into the CN responses to changes in perfusion when either all SAs are occluded in a single procedure or during multiple interventions undertaken as part of a staged approach. Combined with functional and outcomes data, the addition of molecular tools to monitor CN rearrangement and expansion could be a valuable addition to existing treatment modalities, uncovering potential therapeutic targets and advancing progress towards the provision of individually tailored interventions. MATERIALS AND METHODS Animals and treatments Paraspinous muscle (PM) samples for this study were obtained secondary to a previous surgical study [17]. Archived formalin-fixed, paraffin-embedded (FFPE) tissue from 22 female Yorkshire livestock pigs (Sus scrofa, 25.2 ± 1.7 kg)—each receiving humane care in compliance with the guidelines of ‘Principles of Laboratory Animal Care’ formulated by the National Society for Medical Research and the ‘Guide for the Care and Use of Laboratory Animals’ published by the National Institute of Health (NIH Publication No. 88–23, revised 1996)—representing 3 models of coil embolization of the spinal segmental arteries within the lower thoracic and upper lumbar spinal column were used for the present study. In the original study, animals were randomized to 1 of 3 experimental protocols 7–10 days before simulated TAAA repair; group 1 animals received sham operations including no coiling (n = 6), group 2 received coil occlusion of 1.5 ± 0.5 spinal segmental arteries between T13 and L1 (n = 8) and group 3 subjects had 4.5 ± 0.5 spinal segmental arteries embolized between T11 and L3 (n = 8). Additional details regarding the methods for model creation and tissue preparation are further described elsewhere [17]. RNA preparation and microarray hybridization Sections were cut from FFPE PM biopsy specimens from the ninth thoracic spinal cord level (T9). After incubation in deparaffinization solution (QIAGEN, Hamburg, Germany), total RNA was extracted using the RNeasy Mini kit protocol (QIAGEN). The quality and quantity of purified RNA were estimated using a NanoDrop spectrophotometer (ThermoFisher Scientific, Carlsbad, CA, USA) and an Agilent Bioanalyzer 2100 (Agilent, Santa Clara, CA, USA); aliquots of RNA were stored at −80°C. Gene expression profiling was performed using the Affymetrix GeneChip Porcine Gene 1.0 ST array (Affymetrix, Santa Clara, CA, USA). This array interrogates 19 212 S. scrofa genes with 394 580 distinct probes. Microarray sample processing, target hybridization, washing, staining and scanning were performed using the SensationPlus FFPE amplification and WT labelling kit (Affymetrix) according to the manufacturer’s instructions. Briefly, 100 ng of total RNA was subjected to 1 round of cDNA synthesis followed by sense RNA amplification. A second round of cDNA synthesis, fragmentation and biotin labelling was then performed. The biotin-labelled cDNA was hybridized to the array for 16 h at 47°C using the GeneChip Hybridization Oven 640 (ThermoFisher Scientific). Washing and staining with streptavidin-phycoerythrin was performed using the GeneChip Hybridization, Wash and Stain Kit and the GeneChip Fluidics Station 450 (ThermoFisher Scientific). Images were acquired using the GeneChip Scanner 3000 7G (ThermoFisher Scientific) and the GeneChip Command Console Software (Affymetrix). Normalized and background-corrected, raw probe intensity values were uploaded to Partek Genomics Suite version 6.6 (Partek Inc., St. Louis, MO, USA) for downstream differential expression analysis. Transcript analysis Raw gene expression data files, containing signal values and gene detection calls (present, marginally present or absent), were imported into Transcriptome Analysis Console (TAC®, Version 4.0.0.25; ThermoFisher Scientific). Probe set configurations were established using the PorGene-1_0-st array, normalizing each probe set to the median signal values detected in samples from subjects receiving no endovascular coiling in the first stage of the experimental surgical protocol. One-way analysis of variance was used to evaluate the differential effect of coiling and paralysis on gene expression and Benjamini–Hochberg multiple test correction, in addition to classical P-values, was computed. Graphical representation of fold changes between paralysed and recovering subjects were plotted against P-values from t-tests of differences between the 2 outcome groups to create Fig. 1. Figure 1: Open in new tabDownload slide Volcano plot of differentially expressed genes between paralysed and recovering comparison groups interrogating 23 937 porcine probe sets. The vertical component (y-axis) corresponds to the mean gene expression values (−log10) and the horizontal access (x-axis) displays the log2 fold change values. Red spheres represent significantly up-regulated genes, blue dots are transcripts, for which the expression levels were significantly reduced (P < 0.05). Figure 1: Open in new tabDownload slide Volcano plot of differentially expressed genes between paralysed and recovering comparison groups interrogating 23 937 porcine probe sets. The vertical component (y-axis) corresponds to the mean gene expression values (−log10) and the horizontal access (x-axis) displays the log2 fold change values. Red spheres represent significantly up-regulated genes, blue dots are transcripts, for which the expression levels were significantly reduced (P < 0.05). Human orthologues of porcine genes differentially expressed across the 3 experimental groups were additionally analysed using Ingenuity Pathway Analysis (IPA®, Version 44691306; QIAGEN) software to identify key biological functions and significantly enriched pathways. A right-tailed Fisher’s exact test was used to calculate a P-values to determine the probability that the associations were not by random chance alone. Customized pathways were generated to build a structured analysis framework from which to explore the relationships between the genes of interest and known functional pathways within the Ingenuity Knowledge Base. Quantitative real-time polymerase chain reaction validation of microarray data RNA from samples from each coiling group were reverse transcribed using the iScript® cDNA synthesis kit (BioRad, Munich, Germany). A confirmatory panel of 6 genes were run in triplicate on a Mastercycler® ep gradient realplex (Eppendorf, Hamburg, Germany) using the following RT2 qPCR primers for SYBR green detection (RefSeq numbers follow the gene symbols in parentheses): collagen type I4 alpha 1 (COL14A1; XM_005662880), collagen type I alpha 2 (COL1A2; NM_001243655), collagen type 3 alpha 1 (COL3A1; NM_001243297), chemokine ligand 2 (CXC motif) (CXCL2; XM_005652553), vascular endothelial growth factor A (VEGFA; NM_214084) and transforming growth factor β1 (TGFβ1; NM_214015). Quantitative gene expression data were normalized to GAPDH (glyceraldehyde-3-phopshate dehydrogenase; NM_001206359) expression levels (QIAGEN). Relative gene expression data were calculated as a percentage related to GAPDH expression and fold changes compared to group 1 (control) samples utilizing the efficiency-corrected ΔΔ-Ct method [20]. Results were consistent across methods (Table 1). Table 1: Comparison of gene expression results between microarray discovery study and qRT-PCR validation study Gene symbol . Gene name . Microarray . qRT-PCR . Fold change . P-value . Fold change . P-value . COL14A1 Collagen type I4 alpha 1 1.37 0.01 1.37 <0.01 COL1A2 Collagen type I alpha 2 1.53 0.01 1.49 0.05 COL3A1 Collagen type 3 alpha 1 1.70 <0.01 1.28 0.02 CXCL2 Chemokine ligand 2 (CXC motif) 1.46 <0.01 1.35 0.02 TGFβ1 Transforming growth factor β1 1.51 <0.01 1.85 <0.01 VEGFA Vascular endothelial growth factor A 1.45 0.04 1.12 <0.01 Gene symbol . Gene name . Microarray . qRT-PCR . Fold change . P-value . Fold change . P-value . COL14A1 Collagen type I4 alpha 1 1.37 0.01 1.37 <0.01 COL1A2 Collagen type I alpha 2 1.53 0.01 1.49 0.05 COL3A1 Collagen type 3 alpha 1 1.70 <0.01 1.28 0.02 CXCL2 Chemokine ligand 2 (CXC motif) 1.46 <0.01 1.35 0.02 TGFβ1 Transforming growth factor β1 1.51 <0.01 1.85 <0.01 VEGFA Vascular endothelial growth factor A 1.45 0.04 1.12 <0.01 qRT-PCR: real-time quantitative polymerase chain reaction. Open in new tab Table 1: Comparison of gene expression results between microarray discovery study and qRT-PCR validation study Gene symbol . Gene name . Microarray . qRT-PCR . Fold change . P-value . Fold change . P-value . COL14A1 Collagen type I4 alpha 1 1.37 0.01 1.37 <0.01 COL1A2 Collagen type I alpha 2 1.53 0.01 1.49 0.05 COL3A1 Collagen type 3 alpha 1 1.70 <0.01 1.28 0.02 CXCL2 Chemokine ligand 2 (CXC motif) 1.46 <0.01 1.35 0.02 TGFβ1 Transforming growth factor β1 1.51 <0.01 1.85 <0.01 VEGFA Vascular endothelial growth factor A 1.45 0.04 1.12 <0.01 Gene symbol . Gene name . Microarray . qRT-PCR . Fold change . P-value . Fold change . P-value . COL14A1 Collagen type I4 alpha 1 1.37 0.01 1.37 <0.01 COL1A2 Collagen type I alpha 2 1.53 0.01 1.49 0.05 COL3A1 Collagen type 3 alpha 1 1.70 <0.01 1.28 0.02 CXCL2 Chemokine ligand 2 (CXC motif) 1.46 <0.01 1.35 0.02 TGFβ1 Transforming growth factor β1 1.51 <0.01 1.85 <0.01 VEGFA Vascular endothelial growth factor A 1.45 0.04 1.12 <0.01 qRT-PCR: real-time quantitative polymerase chain reaction. Open in new tab RESULTS Functional outcomes and microarray assessment According to the original investigation, which served as the source for the tissue analysed for this study, 50% (n = 3) of control animals (group 1) and 25% (n = 2) of group 2 animals sustained significant intraoperative SCI (modified Tarlov scores < 6). One-hundred percent of group 3 animals (n = 8) showed no evidence of persisting functional deficits (average Tarlov score 7.5 ± 0.2); the process by which hindlimb function was scored is further described elsewhere [17]. Porcine genome microarray using total RNA from these subjects identified 649 genes differentially expressed at a threshold level of ≥1.3-fold change (P ≤ 0.05) when comparing the expression profiles of paralysed and recovering subjects. Of these, only 355 genes were annotated and therefore available for further analysis. Analysis of probe set data Among the annotated porcine genes, 55 were down-regulated and 300 up-regulated. Graphical representation of the magnitude of fold changes and level of statistical significance (Fig. 1) allowed for the visual assessment of gene distribution across the dimensions of biological and statistical relevance. These findings confirm highly significant differences in the gene expression profiles of animals experiencing paralysis and those recovering function. Additionally, this analysis identified a preliminary suite of candidate genes for further investigation. Hierarchical clustering of significant porcine genes, graphically represented by a heat map (Fig. 2), displays the gene expression profiles of animals with and without SCI across the 3 treatment groups; each row on the graph represents a single gene and every column, an individual animal. The graph only includes genes with greater than or equal to 1.3-fold change (absolute value of expression, P ≤ 0.05) determined by one-way analysis of variance. The relative colour and intensity of each box on the grid illustrate changes in gene expression compared to group 1 (control) expression patterns; red represents up-regulated genes, blue represents down-regulated genes and white represents those genes with expression equivalent to control subjects (group 1). Figure 2: Open in new tabDownload slide Heat map of 355 annotated porcine genes significantly differently expressed, tested by one-way analysis of variance (≥1.3-fold change, P ≤ 0.05), in the comparison of expression profiles in the paraspinal muscle of paralysed and recovering subjects. Up-regulated transcripts are shown as red, and down-regulated genes are coloured blue. Coiling group, functional outcome and unique subject ID are located below each expression lane. Figure 2: Open in new tabDownload slide Heat map of 355 annotated porcine genes significantly differently expressed, tested by one-way analysis of variance (≥1.3-fold change, P ≤ 0.05), in the comparison of expression profiles in the paraspinal muscle of paralysed and recovering subjects. Up-regulated transcripts are shown as red, and down-regulated genes are coloured blue. Coiling group, functional outcome and unique subject ID are located below each expression lane. This analysis offers evidence of a coil-dependent stratification of differentially expressed genes with subjects fully recovering hind limb function favouring the up-regulation of genes involved in cell signalling and molecular transport (such as nuclear factor кB and calpain), angiogenesis and inflammatory responses [including chemokine (C-X-C motif) ligand 12 (CXCL12), VEGFA and CD34] and cellular growth and proliferation (for example, serum response factor). Enrichment analysis of deregulated genes Gene ontology enrichment pathway analysis permitted inference of the biological process participating in the expansion of the spinal collateral circulation in animals with segmental artery occlusion recovering function after experimental manipulation. Using the 169 orthologous human genes identified using the g:Orth tool (https://biit.cs.ut.ee/gprofiler/gorth.cgi) (Table 2), the top 47 human canonical pathways characterizing clinical and biological system groupings across significantly differentially expressed genes across outcomes (Fig. 3) were aligned using the IPA platform. Genes participating in calcium signalling and oxidative phosphorylation were among the most significantly aligned; log P-value >6 indicated confidence in the functional grouping to which significant genes were mapped. Figure 3: Open in new tabDownload slide Canonical pathways associated with recovery in human orthologues mapped to significant porcine differentially expressed genes (P < 0.05). (Log P-value indicates confidence in the strength of the functional grouping). AMPK: AMP-activated protein kinase; BMP: bone morphogenetic protein; ILK: integrin-linked kinase; NFAT: nuclear factor of activated T-Cells; nNOS: neuronal nitric oxide synthase; PXR: pregnane X receptor; RAR: retinoic acid receptor; RXR: retinoid X receptor; TCA: tricarboxylic acid cycle. Figure 3: Open in new tabDownload slide Canonical pathways associated with recovery in human orthologues mapped to significant porcine differentially expressed genes (P < 0.05). (Log P-value indicates confidence in the strength of the functional grouping). AMPK: AMP-activated protein kinase; BMP: bone morphogenetic protein; ILK: integrin-linked kinase; NFAT: nuclear factor of activated T-Cells; nNOS: neuronal nitric oxide synthase; PXR: pregnane X receptor; RAR: retinoic acid receptor; RXR: retinoid X receptor; TCA: tricarboxylic acid cycle. Table 2: Human orthologues to differentially expressed porcine genes (list truncated to first 50 genes) Gene ID . Expression fold change . Expression P-value . Entrez gene name . Cellular location . Function . TAF7 −3.11 <0.001 TATA-box-binding protein-associated factor 7 Nucleus Transcription regulator DTL −1.48 <0.001 Denticleless E3 ubiquitin protein ligase homolog Nucleus Other ITK −1.48 <0.001 IL2 inducible T cell kinase Cytoplasm Kinase FBXL8 −1.44 <0.001 F-box and leucine rich repeat protein 8 Cytoplasm Enzyme OR13C4 −1.42 <0.001 Olfactory receptor family 13 subfamily C member 4 Other Other SNN −1.42 <0.001 Stannin Plasma Membrane Other ZNF510 −1.40 0.020 Zinc finger protein 510 Nucleus Other ATG12 −1.37 0.013 Autophagy related 12 Cytoplasm Other KCNN1 −1.37 0.019 Potassium calcium-activated channel subfamily N member 1 Plasma membrane Ion channel LIPN −1.37 0.018 Lipase family member N Extracellular space Enzyme SKOR2 −1.37 <0.001 SKI family transcriptional corepressor 2 Nucleus Transcription regulator BARD1 −1.36 <0.001 BRCA1-associated RING domain 1 Nucleus Transcription regulator ANKRD22 −1.35 <0.001 Ankyrin repeat domain 22 Nucleus Transcription regulator KPNA5 −1.35 <0.001 Karyopherin subunit alpha 5 Cytoplasm Other KRT14 −1.35 0.016 Keratin 14 Cytoplasm Other NPPA −1.35 0.019 Natriuretic peptide A Extracellular space Other ARMC12 −1.34 <0.001 Armadillo repeat containing 12 Nucleus Other HIST1H2AJ −1.34 <0.001 Histone cluster 1 H2A family member j Nucleus Other KISS1R −1.34 <0.001 KISS1 receptor Plasma membrane G protein-coupled receptor GPR6 −1.33 <0.001 G protein-coupled receptor 6 Plasma membrane G protein-coupled receptor CENPS −1.32 0.015 Centromere protein S Nucleus Other OPTC −1.32 0.018 Opticin Extracellular space Other OR9K2 −1.32 0.012 Olfactory receptor family 9 subfamily K member 2 Plasma membrane G protein-coupled receptor SYNDIG1 −1.32 0.019 Synapse differentiation inducing 1 Plasma membrane Other CACNA1I −1.31 0.032 Calcium voltage-gated channel subunit alpha1 I Plasma membrane Ion channel OR4X2 −1.31 0.029 Olfactory receptor family 4 subfamily X member 2 (gene/pseudogene) Plasma membrane Other FBXL12 −1.30 0.019 F-box and leucine rich repeat protein 12 Cytoplasm Enzyme GCNT4 −1.30 <0.001 Glucosaminyl (N-acetyl) transferase 4, core 2 Cytoplasm Enzyme LIPE −1.30 <0.001 Lipase E, hormone sensitive type Cytoplasm Enzyme LRP2 −1.30 <0.001 LDL receptor related protein 2 Plasma membrane Transporter SEC14L5 −1.30 0.011 SEC14 like lipid binding 5 Other Other SLC28A2 −1.30 0.012 Solute carrier family 28 member 2 Plasma membrane Transporter CNOT11 1.30 <0.001 CCR4-NOT transcription complex subunit 11 Cytoplasm Other KLF1 1.30 <0.001 Kruppel like factor 1 Nucleus Transcription regulator KLF10 1.30 <0.001 Kruppel like factor 10 Nucleus Transcription regulator MEF2D 1.30 <0.001 Myocyte enhancer factor 2D Nucleus Transcription regulator NDUFS8 1.30 0.033 NADH: ubiquinone oxidoreductase core subunit S8 Cytoplasm Enzyme NDUFV1 1.30 0.033 NADH: ubiquinone oxidoreductase core subunit V1 Cytoplasm Enzyme NFX1 1.30 0.014 Nuclear transcription factor, X-box binding 1 Nucleus Transcription regulator TMEM109 1.30 0.015 Transmembrane protein 109 Cytoplasm Other AKAP5 1.31 <0.001 A-kinase anchoring protein 5 Plasma membrane Other CAPZA2 1.31 0.011 Capping actin protein of muscle Z-line alpha subunit 2 Cytoplasm Other COX6C 1.31 <0.001 Cytochrome c oxidase subunit 6C Cytoplasm Enzyme DCAF8 1.31 <0.001 DDB1- and CUL4-associated factor 8 Nucleus Other EGLN3 1.31 0.017 egl-9 Family hypoxia inducible factor 3 Cytoplasm Enzyme HOGA1 1.31 <0.001 4-Hydroxy-2-oxoglutarate aldolase 1 Cytoplasm Enzyme IDH3B 1.31 0.037 Isocitrate dehydrogenase 3 [NAD(+)] beta Cytoplasm Enzyme PAIP2 1.31 0.038 Poly(A)-binding protein interacting protein 2 Cytoplasm Translation regulator SMAD7 1.31 0.013 SMAD family member 7 Nucleus Transcription regulator TESK1 1.31 <0.001 Testis-specific kinase 1 Nucleus Kinase Gene ID . Expression fold change . Expression P-value . Entrez gene name . Cellular location . Function . TAF7 −3.11 <0.001 TATA-box-binding protein-associated factor 7 Nucleus Transcription regulator DTL −1.48 <0.001 Denticleless E3 ubiquitin protein ligase homolog Nucleus Other ITK −1.48 <0.001 IL2 inducible T cell kinase Cytoplasm Kinase FBXL8 −1.44 <0.001 F-box and leucine rich repeat protein 8 Cytoplasm Enzyme OR13C4 −1.42 <0.001 Olfactory receptor family 13 subfamily C member 4 Other Other SNN −1.42 <0.001 Stannin Plasma Membrane Other ZNF510 −1.40 0.020 Zinc finger protein 510 Nucleus Other ATG12 −1.37 0.013 Autophagy related 12 Cytoplasm Other KCNN1 −1.37 0.019 Potassium calcium-activated channel subfamily N member 1 Plasma membrane Ion channel LIPN −1.37 0.018 Lipase family member N Extracellular space Enzyme SKOR2 −1.37 <0.001 SKI family transcriptional corepressor 2 Nucleus Transcription regulator BARD1 −1.36 <0.001 BRCA1-associated RING domain 1 Nucleus Transcription regulator ANKRD22 −1.35 <0.001 Ankyrin repeat domain 22 Nucleus Transcription regulator KPNA5 −1.35 <0.001 Karyopherin subunit alpha 5 Cytoplasm Other KRT14 −1.35 0.016 Keratin 14 Cytoplasm Other NPPA −1.35 0.019 Natriuretic peptide A Extracellular space Other ARMC12 −1.34 <0.001 Armadillo repeat containing 12 Nucleus Other HIST1H2AJ −1.34 <0.001 Histone cluster 1 H2A family member j Nucleus Other KISS1R −1.34 <0.001 KISS1 receptor Plasma membrane G protein-coupled receptor GPR6 −1.33 <0.001 G protein-coupled receptor 6 Plasma membrane G protein-coupled receptor CENPS −1.32 0.015 Centromere protein S Nucleus Other OPTC −1.32 0.018 Opticin Extracellular space Other OR9K2 −1.32 0.012 Olfactory receptor family 9 subfamily K member 2 Plasma membrane G protein-coupled receptor SYNDIG1 −1.32 0.019 Synapse differentiation inducing 1 Plasma membrane Other CACNA1I −1.31 0.032 Calcium voltage-gated channel subunit alpha1 I Plasma membrane Ion channel OR4X2 −1.31 0.029 Olfactory receptor family 4 subfamily X member 2 (gene/pseudogene) Plasma membrane Other FBXL12 −1.30 0.019 F-box and leucine rich repeat protein 12 Cytoplasm Enzyme GCNT4 −1.30 <0.001 Glucosaminyl (N-acetyl) transferase 4, core 2 Cytoplasm Enzyme LIPE −1.30 <0.001 Lipase E, hormone sensitive type Cytoplasm Enzyme LRP2 −1.30 <0.001 LDL receptor related protein 2 Plasma membrane Transporter SEC14L5 −1.30 0.011 SEC14 like lipid binding 5 Other Other SLC28A2 −1.30 0.012 Solute carrier family 28 member 2 Plasma membrane Transporter CNOT11 1.30 <0.001 CCR4-NOT transcription complex subunit 11 Cytoplasm Other KLF1 1.30 <0.001 Kruppel like factor 1 Nucleus Transcription regulator KLF10 1.30 <0.001 Kruppel like factor 10 Nucleus Transcription regulator MEF2D 1.30 <0.001 Myocyte enhancer factor 2D Nucleus Transcription regulator NDUFS8 1.30 0.033 NADH: ubiquinone oxidoreductase core subunit S8 Cytoplasm Enzyme NDUFV1 1.30 0.033 NADH: ubiquinone oxidoreductase core subunit V1 Cytoplasm Enzyme NFX1 1.30 0.014 Nuclear transcription factor, X-box binding 1 Nucleus Transcription regulator TMEM109 1.30 0.015 Transmembrane protein 109 Cytoplasm Other AKAP5 1.31 <0.001 A-kinase anchoring protein 5 Plasma membrane Other CAPZA2 1.31 0.011 Capping actin protein of muscle Z-line alpha subunit 2 Cytoplasm Other COX6C 1.31 <0.001 Cytochrome c oxidase subunit 6C Cytoplasm Enzyme DCAF8 1.31 <0.001 DDB1- and CUL4-associated factor 8 Nucleus Other EGLN3 1.31 0.017 egl-9 Family hypoxia inducible factor 3 Cytoplasm Enzyme HOGA1 1.31 <0.001 4-Hydroxy-2-oxoglutarate aldolase 1 Cytoplasm Enzyme IDH3B 1.31 0.037 Isocitrate dehydrogenase 3 [NAD(+)] beta Cytoplasm Enzyme PAIP2 1.31 0.038 Poly(A)-binding protein interacting protein 2 Cytoplasm Translation regulator SMAD7 1.31 0.013 SMAD family member 7 Nucleus Transcription regulator TESK1 1.31 <0.001 Testis-specific kinase 1 Nucleus Kinase Open in new tab Table 2: Human orthologues to differentially expressed porcine genes (list truncated to first 50 genes) Gene ID . Expression fold change . Expression P-value . Entrez gene name . Cellular location . Function . TAF7 −3.11 <0.001 TATA-box-binding protein-associated factor 7 Nucleus Transcription regulator DTL −1.48 <0.001 Denticleless E3 ubiquitin protein ligase homolog Nucleus Other ITK −1.48 <0.001 IL2 inducible T cell kinase Cytoplasm Kinase FBXL8 −1.44 <0.001 F-box and leucine rich repeat protein 8 Cytoplasm Enzyme OR13C4 −1.42 <0.001 Olfactory receptor family 13 subfamily C member 4 Other Other SNN −1.42 <0.001 Stannin Plasma Membrane Other ZNF510 −1.40 0.020 Zinc finger protein 510 Nucleus Other ATG12 −1.37 0.013 Autophagy related 12 Cytoplasm Other KCNN1 −1.37 0.019 Potassium calcium-activated channel subfamily N member 1 Plasma membrane Ion channel LIPN −1.37 0.018 Lipase family member N Extracellular space Enzyme SKOR2 −1.37 <0.001 SKI family transcriptional corepressor 2 Nucleus Transcription regulator BARD1 −1.36 <0.001 BRCA1-associated RING domain 1 Nucleus Transcription regulator ANKRD22 −1.35 <0.001 Ankyrin repeat domain 22 Nucleus Transcription regulator KPNA5 −1.35 <0.001 Karyopherin subunit alpha 5 Cytoplasm Other KRT14 −1.35 0.016 Keratin 14 Cytoplasm Other NPPA −1.35 0.019 Natriuretic peptide A Extracellular space Other ARMC12 −1.34 <0.001 Armadillo repeat containing 12 Nucleus Other HIST1H2AJ −1.34 <0.001 Histone cluster 1 H2A family member j Nucleus Other KISS1R −1.34 <0.001 KISS1 receptor Plasma membrane G protein-coupled receptor GPR6 −1.33 <0.001 G protein-coupled receptor 6 Plasma membrane G protein-coupled receptor CENPS −1.32 0.015 Centromere protein S Nucleus Other OPTC −1.32 0.018 Opticin Extracellular space Other OR9K2 −1.32 0.012 Olfactory receptor family 9 subfamily K member 2 Plasma membrane G protein-coupled receptor SYNDIG1 −1.32 0.019 Synapse differentiation inducing 1 Plasma membrane Other CACNA1I −1.31 0.032 Calcium voltage-gated channel subunit alpha1 I Plasma membrane Ion channel OR4X2 −1.31 0.029 Olfactory receptor family 4 subfamily X member 2 (gene/pseudogene) Plasma membrane Other FBXL12 −1.30 0.019 F-box and leucine rich repeat protein 12 Cytoplasm Enzyme GCNT4 −1.30 <0.001 Glucosaminyl (N-acetyl) transferase 4, core 2 Cytoplasm Enzyme LIPE −1.30 <0.001 Lipase E, hormone sensitive type Cytoplasm Enzyme LRP2 −1.30 <0.001 LDL receptor related protein 2 Plasma membrane Transporter SEC14L5 −1.30 0.011 SEC14 like lipid binding 5 Other Other SLC28A2 −1.30 0.012 Solute carrier family 28 member 2 Plasma membrane Transporter CNOT11 1.30 <0.001 CCR4-NOT transcription complex subunit 11 Cytoplasm Other KLF1 1.30 <0.001 Kruppel like factor 1 Nucleus Transcription regulator KLF10 1.30 <0.001 Kruppel like factor 10 Nucleus Transcription regulator MEF2D 1.30 <0.001 Myocyte enhancer factor 2D Nucleus Transcription regulator NDUFS8 1.30 0.033 NADH: ubiquinone oxidoreductase core subunit S8 Cytoplasm Enzyme NDUFV1 1.30 0.033 NADH: ubiquinone oxidoreductase core subunit V1 Cytoplasm Enzyme NFX1 1.30 0.014 Nuclear transcription factor, X-box binding 1 Nucleus Transcription regulator TMEM109 1.30 0.015 Transmembrane protein 109 Cytoplasm Other AKAP5 1.31 <0.001 A-kinase anchoring protein 5 Plasma membrane Other CAPZA2 1.31 0.011 Capping actin protein of muscle Z-line alpha subunit 2 Cytoplasm Other COX6C 1.31 <0.001 Cytochrome c oxidase subunit 6C Cytoplasm Enzyme DCAF8 1.31 <0.001 DDB1- and CUL4-associated factor 8 Nucleus Other EGLN3 1.31 0.017 egl-9 Family hypoxia inducible factor 3 Cytoplasm Enzyme HOGA1 1.31 <0.001 4-Hydroxy-2-oxoglutarate aldolase 1 Cytoplasm Enzyme IDH3B 1.31 0.037 Isocitrate dehydrogenase 3 [NAD(+)] beta Cytoplasm Enzyme PAIP2 1.31 0.038 Poly(A)-binding protein interacting protein 2 Cytoplasm Translation regulator SMAD7 1.31 0.013 SMAD family member 7 Nucleus Transcription regulator TESK1 1.31 <0.001 Testis-specific kinase 1 Nucleus Kinase Gene ID . Expression fold change . Expression P-value . Entrez gene name . Cellular location . Function . TAF7 −3.11 <0.001 TATA-box-binding protein-associated factor 7 Nucleus Transcription regulator DTL −1.48 <0.001 Denticleless E3 ubiquitin protein ligase homolog Nucleus Other ITK −1.48 <0.001 IL2 inducible T cell kinase Cytoplasm Kinase FBXL8 −1.44 <0.001 F-box and leucine rich repeat protein 8 Cytoplasm Enzyme OR13C4 −1.42 <0.001 Olfactory receptor family 13 subfamily C member 4 Other Other SNN −1.42 <0.001 Stannin Plasma Membrane Other ZNF510 −1.40 0.020 Zinc finger protein 510 Nucleus Other ATG12 −1.37 0.013 Autophagy related 12 Cytoplasm Other KCNN1 −1.37 0.019 Potassium calcium-activated channel subfamily N member 1 Plasma membrane Ion channel LIPN −1.37 0.018 Lipase family member N Extracellular space Enzyme SKOR2 −1.37 <0.001 SKI family transcriptional corepressor 2 Nucleus Transcription regulator BARD1 −1.36 <0.001 BRCA1-associated RING domain 1 Nucleus Transcription regulator ANKRD22 −1.35 <0.001 Ankyrin repeat domain 22 Nucleus Transcription regulator KPNA5 −1.35 <0.001 Karyopherin subunit alpha 5 Cytoplasm Other KRT14 −1.35 0.016 Keratin 14 Cytoplasm Other NPPA −1.35 0.019 Natriuretic peptide A Extracellular space Other ARMC12 −1.34 <0.001 Armadillo repeat containing 12 Nucleus Other HIST1H2AJ −1.34 <0.001 Histone cluster 1 H2A family member j Nucleus Other KISS1R −1.34 <0.001 KISS1 receptor Plasma membrane G protein-coupled receptor GPR6 −1.33 <0.001 G protein-coupled receptor 6 Plasma membrane G protein-coupled receptor CENPS −1.32 0.015 Centromere protein S Nucleus Other OPTC −1.32 0.018 Opticin Extracellular space Other OR9K2 −1.32 0.012 Olfactory receptor family 9 subfamily K member 2 Plasma membrane G protein-coupled receptor SYNDIG1 −1.32 0.019 Synapse differentiation inducing 1 Plasma membrane Other CACNA1I −1.31 0.032 Calcium voltage-gated channel subunit alpha1 I Plasma membrane Ion channel OR4X2 −1.31 0.029 Olfactory receptor family 4 subfamily X member 2 (gene/pseudogene) Plasma membrane Other FBXL12 −1.30 0.019 F-box and leucine rich repeat protein 12 Cytoplasm Enzyme GCNT4 −1.30 <0.001 Glucosaminyl (N-acetyl) transferase 4, core 2 Cytoplasm Enzyme LIPE −1.30 <0.001 Lipase E, hormone sensitive type Cytoplasm Enzyme LRP2 −1.30 <0.001 LDL receptor related protein 2 Plasma membrane Transporter SEC14L5 −1.30 0.011 SEC14 like lipid binding 5 Other Other SLC28A2 −1.30 0.012 Solute carrier family 28 member 2 Plasma membrane Transporter CNOT11 1.30 <0.001 CCR4-NOT transcription complex subunit 11 Cytoplasm Other KLF1 1.30 <0.001 Kruppel like factor 1 Nucleus Transcription regulator KLF10 1.30 <0.001 Kruppel like factor 10 Nucleus Transcription regulator MEF2D 1.30 <0.001 Myocyte enhancer factor 2D Nucleus Transcription regulator NDUFS8 1.30 0.033 NADH: ubiquinone oxidoreductase core subunit S8 Cytoplasm Enzyme NDUFV1 1.30 0.033 NADH: ubiquinone oxidoreductase core subunit V1 Cytoplasm Enzyme NFX1 1.30 0.014 Nuclear transcription factor, X-box binding 1 Nucleus Transcription regulator TMEM109 1.30 0.015 Transmembrane protein 109 Cytoplasm Other AKAP5 1.31 <0.001 A-kinase anchoring protein 5 Plasma membrane Other CAPZA2 1.31 0.011 Capping actin protein of muscle Z-line alpha subunit 2 Cytoplasm Other COX6C 1.31 <0.001 Cytochrome c oxidase subunit 6C Cytoplasm Enzyme DCAF8 1.31 <0.001 DDB1- and CUL4-associated factor 8 Nucleus Other EGLN3 1.31 0.017 egl-9 Family hypoxia inducible factor 3 Cytoplasm Enzyme HOGA1 1.31 <0.001 4-Hydroxy-2-oxoglutarate aldolase 1 Cytoplasm Enzyme IDH3B 1.31 0.037 Isocitrate dehydrogenase 3 [NAD(+)] beta Cytoplasm Enzyme PAIP2 1.31 0.038 Poly(A)-binding protein interacting protein 2 Cytoplasm Translation regulator SMAD7 1.31 0.013 SMAD family member 7 Nucleus Transcription regulator TESK1 1.31 <0.001 Testis-specific kinase 1 Nucleus Kinase Open in new tab Signalling pathways involving differentially expressed genes To further illustrate the relationships and patterns of expression of key differentially expressed genes in animals without functional deficits, network diagrams show the key role of integrated pathways and cellular regulators of responses to ischaemia and hypoxic injury. Relationships between CXCL, VEGF and other mediators of cell signalling cascades involved in arteriogenesis and angiogenesis (Fig. 4) are highlighted to reinforce associations previously described in the literature [21–23], as well as emphasize potential areas for novel exploration. Figure 4: Open in new tabDownload slide Network diagram of subcellular localization of focus molecules participating in CXCL12 signalling cascade (blue lines) including genes participating in cell signalling and molecular transport. Red colouration indicates up-regulation in gene expression. MMP: matrix metallopeptidase; MYD88: myeloid differentiation primary response 88; OPTC: opticin; TNMD: tenomodulin; VEGFA: vascular endothelial growth factor A. Figure 4: Open in new tabDownload slide Network diagram of subcellular localization of focus molecules participating in CXCL12 signalling cascade (blue lines) including genes participating in cell signalling and molecular transport. Red colouration indicates up-regulation in gene expression. MMP: matrix metallopeptidase; MYD88: myeloid differentiation primary response 88; OPTC: opticin; TNMD: tenomodulin; VEGFA: vascular endothelial growth factor A. DISCUSSION In spite of previous studies indicating functional and neuroprotective benefits in staging TAAA repair [16–18, 24], there remains a need to further describe the molecular underpinnings of the regional angiogenesis and vessel rearrangement induced by extensive SA occlusion. Translational and basic science investigations have begun to uncover the molecular signature of aortic pathologies [25, 26] and gene expression patterns in SCI [27, 28], but there have been no studies to date specifically characterizing the transcriptomic profile of acute phase responses to the surgically induced changes in spinal cord perfusion. The present study offers a preliminary demonstration of the feasibility of applying microarray-based profiling techniques to identify the cellular and molecular responses accompanying functional changes in the PM harvested utilizing our experimental model. The work at hand emphasizes the nature of changes in gene expression and demonstrates a high degree of variability and dimensionality in the patterns of expression and enriched cellular pathways. These findings additionally highlight the activation of multiple expression cascades, likely occurring during the preconditioning of the spinal collateral circulation during the ligation of SA up to 10 days before stent placement. This study shows that, with an increasing number of coils, there is an associated increase in the expression of many genes participating in transcriptional regulation, cytokine responses, hypoxia signalling and cytoskeletal arrangement and development. The decreased incidence in paralysis associated with these increases in gene expression (see group 3 expression patterns) suggests a disruption in the activation of responsive pathways stimulated by the massive occlusion of vessels in single-staged procedures. Specifically, this study demonstrates the essential nature of mediators related to cell signalling and molecular transport, inflammatory responses, cardiovascular system development and cellular growth and proliferation significantly down-regulated in paralysed subjects compared to those recovering function; these findings demonstrate the important cellular and molecular pathways up-regulated with preconditioning associated with staged endovascular coiling before TAAA repair. Overall, the data support the use of expression profiling—and subsequent application of relevant hierarchical and canonical pathways of expression—to guide the identification of novel effect-directed methodologies for monitoring and manipulating the changes in the CN vasculature. As there are no biomarkers available to assess changes in the CN as a result of embolization or staged endovascular procedures, applying such transcriptomic tools could enhance clinical practice by revealing mechanisms contributing to SCI in the setting of TAAA repair. With the timing of SA coiling and staging of procedures remaining arbitrary in current surgical practice, confirming the role of mediators of physiological processes essential in the regulation of vascular homeostasis and expansion of the CN through the processes of angiogenesis and arteriogenesis will provide insight into more individualized and precise waiting periods between staged procedures beyond the 5- to 7-day wait that previous studies have indicated might be beneficial. In light of recent successes with minimally invasive controlled release systems to deliver encapsulated proteins, such as CXCL12 to promote arteriogenesis in the setting of ischaemic injury [22], the potential therapeutic application of the findings of this study remains to be further explored. The ability to deliver upstream regulators of arteriogenesis and angiogenesis in the setting of staged interventions could potentially mediate the changes in blood flow accompanying endovascular interventions and significantly impact clinical patient outcomes. Limitations Notable limitations to the present study include small sample size and the use of FFPE tissue for assay. Given evidence that formalin fixation of tissues leads to chemical modifications of biomolecules—notably, the fragmentation of templates for downstream polymerase chain reaction amplification, reduction in efficiency of cDNA synthesis from RNA and the generation of sequence artefacts [29, 30]—subsequent studies will employ extractions from reagent stabilized and fresh frozen specimens to increase the efficiency of downstream applications and improve the detection of differential signals across intervention. Such modifications should support the development of a more robust body of transcriptomic knowledge and, considering the ever-increasing annotation of previously unknown genes, it is anticipated that subsequent studies integrating such genomic tools will be more capable of identifying the molecular underpinnings of mechanisms at play. Presented at the 32nd Annual Meeting of the European Association for Cardio-Thoracic Surgery, Milan, Italy, 18–20 October 2018. ACKNOWLEDGEMENTS Donations of stents from W.L. Gore & Associates, Inc. (Flagstaff, AZ, USA) and embolization coils from Cook Medical (Bloomington, ID, USA) were used to create the animal models from which the tissues used for this study were derived. Funding This work was supported by extramural funding from the New Jersey Commission on Spinal Cord Research [#CSCR15IRG012]. Conflict of interest: none declared. REFERENCES 1 Ullery BW , Cheung AT , Fairman RM , Jackson BM , Woo EY , Bavaria J et al. 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Google Scholar Crossref Search ADS PubMed WorldCat © The Author(s) 2019. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png European Journal of Cardio-Thoracic Surgery Oxford University Press

Paraspinous muscle gene expression profiling following simulated staged endovascular repair of thoracoabdominal aortic aneurysm: exploring potential therapeutic pathways

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Publisher
Oxford University Press
Copyright
© The Author(s) 2019. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved.
ISSN
1010-7940
eISSN
1873-734X
DOI
10.1093/ejcts/ezz113
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See Article on Publisher Site

Abstract

Abstract Open in new tabDownload slide Open in new tabDownload slide OBJECTIVES Thoracic endovascular techniques for aneurysm repair offer less invasive alternatives to open strategies. Both approaches, however, are associated with the risk for neurological complications. Despite adjuncts to maintain spinal cord perfusion, ischaemia and paraplegia continue to occur during thoracoabdominal aortic aneurysm (TAAA) repair. Staging of such extensive procedures has been proven to decrease the risk for spinal cord injury. Archived biopsy specimens may offer insight into the molecular signature of the reorganization and expansion of the spinal collateral network during staged endovascular interventions in the setting of TAAA. METHODS Biological replicates of total RNA were isolated from existing paraspinous muscle samples from 22 Yorkshire pigs randomized to 1 of 3 simulated TAAA repair strategies as part of a previous study employing coil embolization of spinal segmental arteries within the thoracic and lumbar spine. Gene expression profiling was performed using the Affymetrix GeneChip Porcine array. RESULTS Microarray analysis identified 649 differentially expressed porcine genes (≥1.3-fold change, P ≤ 0.05) when comparing paralysed and non-paralysed subjects. Of these, 355 were available for further analysis. When mapped to the human genome, 169 Homo sapiens orthologues were identified. Integrated interpretation of gene expression profiles indicated the significant regulation of transcriptional regulators (such as nuclear factor кB), cytokine (including CXCL12) elements contributing to hypoxia signalling in the cardiovascular system (vascular endothelial growth factor and UBE2) and cytoskeletal elements (like dystrophin (DMD) and matrix metallopeptidase (MMP)). CONCLUSIONS This study demonstrates the ability of microarray-based platforms to detect the differential expression of genes in paraspinous muscle during staged TAAA repair. Pathway enrichment analysis detected subcellular actors accompanying the neuroprotective effects of staged endovascular coiling. These observations provide new insight into the potential prognostic and therapeutic value of gene expression profiling in monitoring and modulating the arteriolar remodelling in the collateral network. Endovascular, Embolization, Thoracoabdominal, Aneurysm, Transcriptomics, Paraplegia INTRODUCTION Mortality associated with thoracoabdominal aortic aneurysm (TAAA) is high in the absence of timely surgical intervention. Surgical and endovascular approaches are not without potential complications and adverse neurological outcomes associated with repairs—ranging from paraparesis to paralysis—can be life-limiting [1–3]. Contemporary strategies to reduce the physiological insult to the spinal cord—including hypothermia [4], cerebrospinal fluid drainage [5], electrophysiological monitoring [6] and adjunctive pharmacological therapies [7]—have dramatically reduced the incidence of paraplegia. Despite these advancements in perioperative care, spinal cord injury (SCI) continues to occur in up to 20% of patients undergoing thoracic endovascular aortic repair of descending thoracic and TAAAs, as well as thoracic aortic dissections [8, 9]. Clinical and translational studies have offered great insight into the anatomic and physiological responses accompanying TAAA repair [10, 11]. Notably, the contribution of the segmental arteries (SA) and extra-SA to the perfusion of the spinal cord and paraspinous muscle (PM) has been highlighted through this work. Our casting model and computed tomography scan imaging studies have demonstrated the nature of the communication between the SA and the aorta; anastomosing with the subclavian arteries cranially and median sacral arteries (equivalent to the hypogastric arteries in humans) caudally, the SA also importantly communicate with the anterior spinal artery [12, 13]. In vivo models have demonstrated that, within 5 days of extensive sacrifice of SAs, there is a quantifiable change from a random to a parallel orientation of arterial vessels within the PM [13]. Along with this adaptation, evidence of an 80–100% increase in the number and density of connections between the anterior spinal artery and the vasculature of the PM adjacent to the spinal cord within 120 h of SA interruption has also been reported [12]. Given evidence that the arteries of the collateral network (CN) connect both the circulation of the spinal cord and paravertebral tissues [14], and extensive sacrifice of SA within the arcades of the SA can inversely influence perfusion pressures leading to negative functional outcomes, the present study is directed at using PM as a surrogate to elucidate the confluence between molecular, cellular and functional responses to interruptions in spinal cord perfusion. Our laboratory has shown that staging TAAA repairs mitigates the unavoidable periods of spinal cord ischaemia; the anatomical changes have been confirmed by both histological examination of spinal cord segments and electron microscopic visualization of arterioles within the paraspinal network [15–19]. Despite the benefits of selective SA endovascular coil embolization, routine application of this approach can be challenging due to anatomical variation, severity of aortic atheroma burden and urgency of intervention. Due to these limitations, exploration of molecular and cellular responses to ischaemia-mediated, stress-induced mechanisms in the CN is a preliminary step towards understanding the gene-level responses to occlusion of SA. To this end, this transcriptomic analysis is the first study using archived PM muscle samples—obtained as part of a previous investigation—to illuminate the gene expression profiles accompanying the conditioning of the spinal CN induced by local responses to hypoxia (angiogenesis) and changes in intravascular fluid dynamics (arteriogenesis). Synthesizing information from our experimental model and clinical observations, the goal of this investigation is to provide new insight into the CN responses to changes in perfusion when either all SAs are occluded in a single procedure or during multiple interventions undertaken as part of a staged approach. Combined with functional and outcomes data, the addition of molecular tools to monitor CN rearrangement and expansion could be a valuable addition to existing treatment modalities, uncovering potential therapeutic targets and advancing progress towards the provision of individually tailored interventions. MATERIALS AND METHODS Animals and treatments Paraspinous muscle (PM) samples for this study were obtained secondary to a previous surgical study [17]. Archived formalin-fixed, paraffin-embedded (FFPE) tissue from 22 female Yorkshire livestock pigs (Sus scrofa, 25.2 ± 1.7 kg)—each receiving humane care in compliance with the guidelines of ‘Principles of Laboratory Animal Care’ formulated by the National Society for Medical Research and the ‘Guide for the Care and Use of Laboratory Animals’ published by the National Institute of Health (NIH Publication No. 88–23, revised 1996)—representing 3 models of coil embolization of the spinal segmental arteries within the lower thoracic and upper lumbar spinal column were used for the present study. In the original study, animals were randomized to 1 of 3 experimental protocols 7–10 days before simulated TAAA repair; group 1 animals received sham operations including no coiling (n = 6), group 2 received coil occlusion of 1.5 ± 0.5 spinal segmental arteries between T13 and L1 (n = 8) and group 3 subjects had 4.5 ± 0.5 spinal segmental arteries embolized between T11 and L3 (n = 8). Additional details regarding the methods for model creation and tissue preparation are further described elsewhere [17]. RNA preparation and microarray hybridization Sections were cut from FFPE PM biopsy specimens from the ninth thoracic spinal cord level (T9). After incubation in deparaffinization solution (QIAGEN, Hamburg, Germany), total RNA was extracted using the RNeasy Mini kit protocol (QIAGEN). The quality and quantity of purified RNA were estimated using a NanoDrop spectrophotometer (ThermoFisher Scientific, Carlsbad, CA, USA) and an Agilent Bioanalyzer 2100 (Agilent, Santa Clara, CA, USA); aliquots of RNA were stored at −80°C. Gene expression profiling was performed using the Affymetrix GeneChip Porcine Gene 1.0 ST array (Affymetrix, Santa Clara, CA, USA). This array interrogates 19 212 S. scrofa genes with 394 580 distinct probes. Microarray sample processing, target hybridization, washing, staining and scanning were performed using the SensationPlus FFPE amplification and WT labelling kit (Affymetrix) according to the manufacturer’s instructions. Briefly, 100 ng of total RNA was subjected to 1 round of cDNA synthesis followed by sense RNA amplification. A second round of cDNA synthesis, fragmentation and biotin labelling was then performed. The biotin-labelled cDNA was hybridized to the array for 16 h at 47°C using the GeneChip Hybridization Oven 640 (ThermoFisher Scientific). Washing and staining with streptavidin-phycoerythrin was performed using the GeneChip Hybridization, Wash and Stain Kit and the GeneChip Fluidics Station 450 (ThermoFisher Scientific). Images were acquired using the GeneChip Scanner 3000 7G (ThermoFisher Scientific) and the GeneChip Command Console Software (Affymetrix). Normalized and background-corrected, raw probe intensity values were uploaded to Partek Genomics Suite version 6.6 (Partek Inc., St. Louis, MO, USA) for downstream differential expression analysis. Transcript analysis Raw gene expression data files, containing signal values and gene detection calls (present, marginally present or absent), were imported into Transcriptome Analysis Console (TAC®, Version 4.0.0.25; ThermoFisher Scientific). Probe set configurations were established using the PorGene-1_0-st array, normalizing each probe set to the median signal values detected in samples from subjects receiving no endovascular coiling in the first stage of the experimental surgical protocol. One-way analysis of variance was used to evaluate the differential effect of coiling and paralysis on gene expression and Benjamini–Hochberg multiple test correction, in addition to classical P-values, was computed. Graphical representation of fold changes between paralysed and recovering subjects were plotted against P-values from t-tests of differences between the 2 outcome groups to create Fig. 1. Figure 1: Open in new tabDownload slide Volcano plot of differentially expressed genes between paralysed and recovering comparison groups interrogating 23 937 porcine probe sets. The vertical component (y-axis) corresponds to the mean gene expression values (−log10) and the horizontal access (x-axis) displays the log2 fold change values. Red spheres represent significantly up-regulated genes, blue dots are transcripts, for which the expression levels were significantly reduced (P < 0.05). Figure 1: Open in new tabDownload slide Volcano plot of differentially expressed genes between paralysed and recovering comparison groups interrogating 23 937 porcine probe sets. The vertical component (y-axis) corresponds to the mean gene expression values (−log10) and the horizontal access (x-axis) displays the log2 fold change values. Red spheres represent significantly up-regulated genes, blue dots are transcripts, for which the expression levels were significantly reduced (P < 0.05). Human orthologues of porcine genes differentially expressed across the 3 experimental groups were additionally analysed using Ingenuity Pathway Analysis (IPA®, Version 44691306; QIAGEN) software to identify key biological functions and significantly enriched pathways. A right-tailed Fisher’s exact test was used to calculate a P-values to determine the probability that the associations were not by random chance alone. Customized pathways were generated to build a structured analysis framework from which to explore the relationships between the genes of interest and known functional pathways within the Ingenuity Knowledge Base. Quantitative real-time polymerase chain reaction validation of microarray data RNA from samples from each coiling group were reverse transcribed using the iScript® cDNA synthesis kit (BioRad, Munich, Germany). A confirmatory panel of 6 genes were run in triplicate on a Mastercycler® ep gradient realplex (Eppendorf, Hamburg, Germany) using the following RT2 qPCR primers for SYBR green detection (RefSeq numbers follow the gene symbols in parentheses): collagen type I4 alpha 1 (COL14A1; XM_005662880), collagen type I alpha 2 (COL1A2; NM_001243655), collagen type 3 alpha 1 (COL3A1; NM_001243297), chemokine ligand 2 (CXC motif) (CXCL2; XM_005652553), vascular endothelial growth factor A (VEGFA; NM_214084) and transforming growth factor β1 (TGFβ1; NM_214015). Quantitative gene expression data were normalized to GAPDH (glyceraldehyde-3-phopshate dehydrogenase; NM_001206359) expression levels (QIAGEN). Relative gene expression data were calculated as a percentage related to GAPDH expression and fold changes compared to group 1 (control) samples utilizing the efficiency-corrected ΔΔ-Ct method [20]. Results were consistent across methods (Table 1). Table 1: Comparison of gene expression results between microarray discovery study and qRT-PCR validation study Gene symbol . Gene name . Microarray . qRT-PCR . Fold change . P-value . Fold change . P-value . COL14A1 Collagen type I4 alpha 1 1.37 0.01 1.37 <0.01 COL1A2 Collagen type I alpha 2 1.53 0.01 1.49 0.05 COL3A1 Collagen type 3 alpha 1 1.70 <0.01 1.28 0.02 CXCL2 Chemokine ligand 2 (CXC motif) 1.46 <0.01 1.35 0.02 TGFβ1 Transforming growth factor β1 1.51 <0.01 1.85 <0.01 VEGFA Vascular endothelial growth factor A 1.45 0.04 1.12 <0.01 Gene symbol . Gene name . Microarray . qRT-PCR . Fold change . P-value . Fold change . P-value . COL14A1 Collagen type I4 alpha 1 1.37 0.01 1.37 <0.01 COL1A2 Collagen type I alpha 2 1.53 0.01 1.49 0.05 COL3A1 Collagen type 3 alpha 1 1.70 <0.01 1.28 0.02 CXCL2 Chemokine ligand 2 (CXC motif) 1.46 <0.01 1.35 0.02 TGFβ1 Transforming growth factor β1 1.51 <0.01 1.85 <0.01 VEGFA Vascular endothelial growth factor A 1.45 0.04 1.12 <0.01 qRT-PCR: real-time quantitative polymerase chain reaction. Open in new tab Table 1: Comparison of gene expression results between microarray discovery study and qRT-PCR validation study Gene symbol . Gene name . Microarray . qRT-PCR . Fold change . P-value . Fold change . P-value . COL14A1 Collagen type I4 alpha 1 1.37 0.01 1.37 <0.01 COL1A2 Collagen type I alpha 2 1.53 0.01 1.49 0.05 COL3A1 Collagen type 3 alpha 1 1.70 <0.01 1.28 0.02 CXCL2 Chemokine ligand 2 (CXC motif) 1.46 <0.01 1.35 0.02 TGFβ1 Transforming growth factor β1 1.51 <0.01 1.85 <0.01 VEGFA Vascular endothelial growth factor A 1.45 0.04 1.12 <0.01 Gene symbol . Gene name . Microarray . qRT-PCR . Fold change . P-value . Fold change . P-value . COL14A1 Collagen type I4 alpha 1 1.37 0.01 1.37 <0.01 COL1A2 Collagen type I alpha 2 1.53 0.01 1.49 0.05 COL3A1 Collagen type 3 alpha 1 1.70 <0.01 1.28 0.02 CXCL2 Chemokine ligand 2 (CXC motif) 1.46 <0.01 1.35 0.02 TGFβ1 Transforming growth factor β1 1.51 <0.01 1.85 <0.01 VEGFA Vascular endothelial growth factor A 1.45 0.04 1.12 <0.01 qRT-PCR: real-time quantitative polymerase chain reaction. Open in new tab RESULTS Functional outcomes and microarray assessment According to the original investigation, which served as the source for the tissue analysed for this study, 50% (n = 3) of control animals (group 1) and 25% (n = 2) of group 2 animals sustained significant intraoperative SCI (modified Tarlov scores < 6). One-hundred percent of group 3 animals (n = 8) showed no evidence of persisting functional deficits (average Tarlov score 7.5 ± 0.2); the process by which hindlimb function was scored is further described elsewhere [17]. Porcine genome microarray using total RNA from these subjects identified 649 genes differentially expressed at a threshold level of ≥1.3-fold change (P ≤ 0.05) when comparing the expression profiles of paralysed and recovering subjects. Of these, only 355 genes were annotated and therefore available for further analysis. Analysis of probe set data Among the annotated porcine genes, 55 were down-regulated and 300 up-regulated. Graphical representation of the magnitude of fold changes and level of statistical significance (Fig. 1) allowed for the visual assessment of gene distribution across the dimensions of biological and statistical relevance. These findings confirm highly significant differences in the gene expression profiles of animals experiencing paralysis and those recovering function. Additionally, this analysis identified a preliminary suite of candidate genes for further investigation. Hierarchical clustering of significant porcine genes, graphically represented by a heat map (Fig. 2), displays the gene expression profiles of animals with and without SCI across the 3 treatment groups; each row on the graph represents a single gene and every column, an individual animal. The graph only includes genes with greater than or equal to 1.3-fold change (absolute value of expression, P ≤ 0.05) determined by one-way analysis of variance. The relative colour and intensity of each box on the grid illustrate changes in gene expression compared to group 1 (control) expression patterns; red represents up-regulated genes, blue represents down-regulated genes and white represents those genes with expression equivalent to control subjects (group 1). Figure 2: Open in new tabDownload slide Heat map of 355 annotated porcine genes significantly differently expressed, tested by one-way analysis of variance (≥1.3-fold change, P ≤ 0.05), in the comparison of expression profiles in the paraspinal muscle of paralysed and recovering subjects. Up-regulated transcripts are shown as red, and down-regulated genes are coloured blue. Coiling group, functional outcome and unique subject ID are located below each expression lane. Figure 2: Open in new tabDownload slide Heat map of 355 annotated porcine genes significantly differently expressed, tested by one-way analysis of variance (≥1.3-fold change, P ≤ 0.05), in the comparison of expression profiles in the paraspinal muscle of paralysed and recovering subjects. Up-regulated transcripts are shown as red, and down-regulated genes are coloured blue. Coiling group, functional outcome and unique subject ID are located below each expression lane. This analysis offers evidence of a coil-dependent stratification of differentially expressed genes with subjects fully recovering hind limb function favouring the up-regulation of genes involved in cell signalling and molecular transport (such as nuclear factor кB and calpain), angiogenesis and inflammatory responses [including chemokine (C-X-C motif) ligand 12 (CXCL12), VEGFA and CD34] and cellular growth and proliferation (for example, serum response factor). Enrichment analysis of deregulated genes Gene ontology enrichment pathway analysis permitted inference of the biological process participating in the expansion of the spinal collateral circulation in animals with segmental artery occlusion recovering function after experimental manipulation. Using the 169 orthologous human genes identified using the g:Orth tool (https://biit.cs.ut.ee/gprofiler/gorth.cgi) (Table 2), the top 47 human canonical pathways characterizing clinical and biological system groupings across significantly differentially expressed genes across outcomes (Fig. 3) were aligned using the IPA platform. Genes participating in calcium signalling and oxidative phosphorylation were among the most significantly aligned; log P-value >6 indicated confidence in the functional grouping to which significant genes were mapped. Figure 3: Open in new tabDownload slide Canonical pathways associated with recovery in human orthologues mapped to significant porcine differentially expressed genes (P < 0.05). (Log P-value indicates confidence in the strength of the functional grouping). AMPK: AMP-activated protein kinase; BMP: bone morphogenetic protein; ILK: integrin-linked kinase; NFAT: nuclear factor of activated T-Cells; nNOS: neuronal nitric oxide synthase; PXR: pregnane X receptor; RAR: retinoic acid receptor; RXR: retinoid X receptor; TCA: tricarboxylic acid cycle. Figure 3: Open in new tabDownload slide Canonical pathways associated with recovery in human orthologues mapped to significant porcine differentially expressed genes (P < 0.05). (Log P-value indicates confidence in the strength of the functional grouping). AMPK: AMP-activated protein kinase; BMP: bone morphogenetic protein; ILK: integrin-linked kinase; NFAT: nuclear factor of activated T-Cells; nNOS: neuronal nitric oxide synthase; PXR: pregnane X receptor; RAR: retinoic acid receptor; RXR: retinoid X receptor; TCA: tricarboxylic acid cycle. Table 2: Human orthologues to differentially expressed porcine genes (list truncated to first 50 genes) Gene ID . Expression fold change . Expression P-value . Entrez gene name . Cellular location . Function . TAF7 −3.11 <0.001 TATA-box-binding protein-associated factor 7 Nucleus Transcription regulator DTL −1.48 <0.001 Denticleless E3 ubiquitin protein ligase homolog Nucleus Other ITK −1.48 <0.001 IL2 inducible T cell kinase Cytoplasm Kinase FBXL8 −1.44 <0.001 F-box and leucine rich repeat protein 8 Cytoplasm Enzyme OR13C4 −1.42 <0.001 Olfactory receptor family 13 subfamily C member 4 Other Other SNN −1.42 <0.001 Stannin Plasma Membrane Other ZNF510 −1.40 0.020 Zinc finger protein 510 Nucleus Other ATG12 −1.37 0.013 Autophagy related 12 Cytoplasm Other KCNN1 −1.37 0.019 Potassium calcium-activated channel subfamily N member 1 Plasma membrane Ion channel LIPN −1.37 0.018 Lipase family member N Extracellular space Enzyme SKOR2 −1.37 <0.001 SKI family transcriptional corepressor 2 Nucleus Transcription regulator BARD1 −1.36 <0.001 BRCA1-associated RING domain 1 Nucleus Transcription regulator ANKRD22 −1.35 <0.001 Ankyrin repeat domain 22 Nucleus Transcription regulator KPNA5 −1.35 <0.001 Karyopherin subunit alpha 5 Cytoplasm Other KRT14 −1.35 0.016 Keratin 14 Cytoplasm Other NPPA −1.35 0.019 Natriuretic peptide A Extracellular space Other ARMC12 −1.34 <0.001 Armadillo repeat containing 12 Nucleus Other HIST1H2AJ −1.34 <0.001 Histone cluster 1 H2A family member j Nucleus Other KISS1R −1.34 <0.001 KISS1 receptor Plasma membrane G protein-coupled receptor GPR6 −1.33 <0.001 G protein-coupled receptor 6 Plasma membrane G protein-coupled receptor CENPS −1.32 0.015 Centromere protein S Nucleus Other OPTC −1.32 0.018 Opticin Extracellular space Other OR9K2 −1.32 0.012 Olfactory receptor family 9 subfamily K member 2 Plasma membrane G protein-coupled receptor SYNDIG1 −1.32 0.019 Synapse differentiation inducing 1 Plasma membrane Other CACNA1I −1.31 0.032 Calcium voltage-gated channel subunit alpha1 I Plasma membrane Ion channel OR4X2 −1.31 0.029 Olfactory receptor family 4 subfamily X member 2 (gene/pseudogene) Plasma membrane Other FBXL12 −1.30 0.019 F-box and leucine rich repeat protein 12 Cytoplasm Enzyme GCNT4 −1.30 <0.001 Glucosaminyl (N-acetyl) transferase 4, core 2 Cytoplasm Enzyme LIPE −1.30 <0.001 Lipase E, hormone sensitive type Cytoplasm Enzyme LRP2 −1.30 <0.001 LDL receptor related protein 2 Plasma membrane Transporter SEC14L5 −1.30 0.011 SEC14 like lipid binding 5 Other Other SLC28A2 −1.30 0.012 Solute carrier family 28 member 2 Plasma membrane Transporter CNOT11 1.30 <0.001 CCR4-NOT transcription complex subunit 11 Cytoplasm Other KLF1 1.30 <0.001 Kruppel like factor 1 Nucleus Transcription regulator KLF10 1.30 <0.001 Kruppel like factor 10 Nucleus Transcription regulator MEF2D 1.30 <0.001 Myocyte enhancer factor 2D Nucleus Transcription regulator NDUFS8 1.30 0.033 NADH: ubiquinone oxidoreductase core subunit S8 Cytoplasm Enzyme NDUFV1 1.30 0.033 NADH: ubiquinone oxidoreductase core subunit V1 Cytoplasm Enzyme NFX1 1.30 0.014 Nuclear transcription factor, X-box binding 1 Nucleus Transcription regulator TMEM109 1.30 0.015 Transmembrane protein 109 Cytoplasm Other AKAP5 1.31 <0.001 A-kinase anchoring protein 5 Plasma membrane Other CAPZA2 1.31 0.011 Capping actin protein of muscle Z-line alpha subunit 2 Cytoplasm Other COX6C 1.31 <0.001 Cytochrome c oxidase subunit 6C Cytoplasm Enzyme DCAF8 1.31 <0.001 DDB1- and CUL4-associated factor 8 Nucleus Other EGLN3 1.31 0.017 egl-9 Family hypoxia inducible factor 3 Cytoplasm Enzyme HOGA1 1.31 <0.001 4-Hydroxy-2-oxoglutarate aldolase 1 Cytoplasm Enzyme IDH3B 1.31 0.037 Isocitrate dehydrogenase 3 [NAD(+)] beta Cytoplasm Enzyme PAIP2 1.31 0.038 Poly(A)-binding protein interacting protein 2 Cytoplasm Translation regulator SMAD7 1.31 0.013 SMAD family member 7 Nucleus Transcription regulator TESK1 1.31 <0.001 Testis-specific kinase 1 Nucleus Kinase Gene ID . Expression fold change . Expression P-value . Entrez gene name . Cellular location . Function . TAF7 −3.11 <0.001 TATA-box-binding protein-associated factor 7 Nucleus Transcription regulator DTL −1.48 <0.001 Denticleless E3 ubiquitin protein ligase homolog Nucleus Other ITK −1.48 <0.001 IL2 inducible T cell kinase Cytoplasm Kinase FBXL8 −1.44 <0.001 F-box and leucine rich repeat protein 8 Cytoplasm Enzyme OR13C4 −1.42 <0.001 Olfactory receptor family 13 subfamily C member 4 Other Other SNN −1.42 <0.001 Stannin Plasma Membrane Other ZNF510 −1.40 0.020 Zinc finger protein 510 Nucleus Other ATG12 −1.37 0.013 Autophagy related 12 Cytoplasm Other KCNN1 −1.37 0.019 Potassium calcium-activated channel subfamily N member 1 Plasma membrane Ion channel LIPN −1.37 0.018 Lipase family member N Extracellular space Enzyme SKOR2 −1.37 <0.001 SKI family transcriptional corepressor 2 Nucleus Transcription regulator BARD1 −1.36 <0.001 BRCA1-associated RING domain 1 Nucleus Transcription regulator ANKRD22 −1.35 <0.001 Ankyrin repeat domain 22 Nucleus Transcription regulator KPNA5 −1.35 <0.001 Karyopherin subunit alpha 5 Cytoplasm Other KRT14 −1.35 0.016 Keratin 14 Cytoplasm Other NPPA −1.35 0.019 Natriuretic peptide A Extracellular space Other ARMC12 −1.34 <0.001 Armadillo repeat containing 12 Nucleus Other HIST1H2AJ −1.34 <0.001 Histone cluster 1 H2A family member j Nucleus Other KISS1R −1.34 <0.001 KISS1 receptor Plasma membrane G protein-coupled receptor GPR6 −1.33 <0.001 G protein-coupled receptor 6 Plasma membrane G protein-coupled receptor CENPS −1.32 0.015 Centromere protein S Nucleus Other OPTC −1.32 0.018 Opticin Extracellular space Other OR9K2 −1.32 0.012 Olfactory receptor family 9 subfamily K member 2 Plasma membrane G protein-coupled receptor SYNDIG1 −1.32 0.019 Synapse differentiation inducing 1 Plasma membrane Other CACNA1I −1.31 0.032 Calcium voltage-gated channel subunit alpha1 I Plasma membrane Ion channel OR4X2 −1.31 0.029 Olfactory receptor family 4 subfamily X member 2 (gene/pseudogene) Plasma membrane Other FBXL12 −1.30 0.019 F-box and leucine rich repeat protein 12 Cytoplasm Enzyme GCNT4 −1.30 <0.001 Glucosaminyl (N-acetyl) transferase 4, core 2 Cytoplasm Enzyme LIPE −1.30 <0.001 Lipase E, hormone sensitive type Cytoplasm Enzyme LRP2 −1.30 <0.001 LDL receptor related protein 2 Plasma membrane Transporter SEC14L5 −1.30 0.011 SEC14 like lipid binding 5 Other Other SLC28A2 −1.30 0.012 Solute carrier family 28 member 2 Plasma membrane Transporter CNOT11 1.30 <0.001 CCR4-NOT transcription complex subunit 11 Cytoplasm Other KLF1 1.30 <0.001 Kruppel like factor 1 Nucleus Transcription regulator KLF10 1.30 <0.001 Kruppel like factor 10 Nucleus Transcription regulator MEF2D 1.30 <0.001 Myocyte enhancer factor 2D Nucleus Transcription regulator NDUFS8 1.30 0.033 NADH: ubiquinone oxidoreductase core subunit S8 Cytoplasm Enzyme NDUFV1 1.30 0.033 NADH: ubiquinone oxidoreductase core subunit V1 Cytoplasm Enzyme NFX1 1.30 0.014 Nuclear transcription factor, X-box binding 1 Nucleus Transcription regulator TMEM109 1.30 0.015 Transmembrane protein 109 Cytoplasm Other AKAP5 1.31 <0.001 A-kinase anchoring protein 5 Plasma membrane Other CAPZA2 1.31 0.011 Capping actin protein of muscle Z-line alpha subunit 2 Cytoplasm Other COX6C 1.31 <0.001 Cytochrome c oxidase subunit 6C Cytoplasm Enzyme DCAF8 1.31 <0.001 DDB1- and CUL4-associated factor 8 Nucleus Other EGLN3 1.31 0.017 egl-9 Family hypoxia inducible factor 3 Cytoplasm Enzyme HOGA1 1.31 <0.001 4-Hydroxy-2-oxoglutarate aldolase 1 Cytoplasm Enzyme IDH3B 1.31 0.037 Isocitrate dehydrogenase 3 [NAD(+)] beta Cytoplasm Enzyme PAIP2 1.31 0.038 Poly(A)-binding protein interacting protein 2 Cytoplasm Translation regulator SMAD7 1.31 0.013 SMAD family member 7 Nucleus Transcription regulator TESK1 1.31 <0.001 Testis-specific kinase 1 Nucleus Kinase Open in new tab Table 2: Human orthologues to differentially expressed porcine genes (list truncated to first 50 genes) Gene ID . Expression fold change . Expression P-value . Entrez gene name . Cellular location . Function . TAF7 −3.11 <0.001 TATA-box-binding protein-associated factor 7 Nucleus Transcription regulator DTL −1.48 <0.001 Denticleless E3 ubiquitin protein ligase homolog Nucleus Other ITK −1.48 <0.001 IL2 inducible T cell kinase Cytoplasm Kinase FBXL8 −1.44 <0.001 F-box and leucine rich repeat protein 8 Cytoplasm Enzyme OR13C4 −1.42 <0.001 Olfactory receptor family 13 subfamily C member 4 Other Other SNN −1.42 <0.001 Stannin Plasma Membrane Other ZNF510 −1.40 0.020 Zinc finger protein 510 Nucleus Other ATG12 −1.37 0.013 Autophagy related 12 Cytoplasm Other KCNN1 −1.37 0.019 Potassium calcium-activated channel subfamily N member 1 Plasma membrane Ion channel LIPN −1.37 0.018 Lipase family member N Extracellular space Enzyme SKOR2 −1.37 <0.001 SKI family transcriptional corepressor 2 Nucleus Transcription regulator BARD1 −1.36 <0.001 BRCA1-associated RING domain 1 Nucleus Transcription regulator ANKRD22 −1.35 <0.001 Ankyrin repeat domain 22 Nucleus Transcription regulator KPNA5 −1.35 <0.001 Karyopherin subunit alpha 5 Cytoplasm Other KRT14 −1.35 0.016 Keratin 14 Cytoplasm Other NPPA −1.35 0.019 Natriuretic peptide A Extracellular space Other ARMC12 −1.34 <0.001 Armadillo repeat containing 12 Nucleus Other HIST1H2AJ −1.34 <0.001 Histone cluster 1 H2A family member j Nucleus Other KISS1R −1.34 <0.001 KISS1 receptor Plasma membrane G protein-coupled receptor GPR6 −1.33 <0.001 G protein-coupled receptor 6 Plasma membrane G protein-coupled receptor CENPS −1.32 0.015 Centromere protein S Nucleus Other OPTC −1.32 0.018 Opticin Extracellular space Other OR9K2 −1.32 0.012 Olfactory receptor family 9 subfamily K member 2 Plasma membrane G protein-coupled receptor SYNDIG1 −1.32 0.019 Synapse differentiation inducing 1 Plasma membrane Other CACNA1I −1.31 0.032 Calcium voltage-gated channel subunit alpha1 I Plasma membrane Ion channel OR4X2 −1.31 0.029 Olfactory receptor family 4 subfamily X member 2 (gene/pseudogene) Plasma membrane Other FBXL12 −1.30 0.019 F-box and leucine rich repeat protein 12 Cytoplasm Enzyme GCNT4 −1.30 <0.001 Glucosaminyl (N-acetyl) transferase 4, core 2 Cytoplasm Enzyme LIPE −1.30 <0.001 Lipase E, hormone sensitive type Cytoplasm Enzyme LRP2 −1.30 <0.001 LDL receptor related protein 2 Plasma membrane Transporter SEC14L5 −1.30 0.011 SEC14 like lipid binding 5 Other Other SLC28A2 −1.30 0.012 Solute carrier family 28 member 2 Plasma membrane Transporter CNOT11 1.30 <0.001 CCR4-NOT transcription complex subunit 11 Cytoplasm Other KLF1 1.30 <0.001 Kruppel like factor 1 Nucleus Transcription regulator KLF10 1.30 <0.001 Kruppel like factor 10 Nucleus Transcription regulator MEF2D 1.30 <0.001 Myocyte enhancer factor 2D Nucleus Transcription regulator NDUFS8 1.30 0.033 NADH: ubiquinone oxidoreductase core subunit S8 Cytoplasm Enzyme NDUFV1 1.30 0.033 NADH: ubiquinone oxidoreductase core subunit V1 Cytoplasm Enzyme NFX1 1.30 0.014 Nuclear transcription factor, X-box binding 1 Nucleus Transcription regulator TMEM109 1.30 0.015 Transmembrane protein 109 Cytoplasm Other AKAP5 1.31 <0.001 A-kinase anchoring protein 5 Plasma membrane Other CAPZA2 1.31 0.011 Capping actin protein of muscle Z-line alpha subunit 2 Cytoplasm Other COX6C 1.31 <0.001 Cytochrome c oxidase subunit 6C Cytoplasm Enzyme DCAF8 1.31 <0.001 DDB1- and CUL4-associated factor 8 Nucleus Other EGLN3 1.31 0.017 egl-9 Family hypoxia inducible factor 3 Cytoplasm Enzyme HOGA1 1.31 <0.001 4-Hydroxy-2-oxoglutarate aldolase 1 Cytoplasm Enzyme IDH3B 1.31 0.037 Isocitrate dehydrogenase 3 [NAD(+)] beta Cytoplasm Enzyme PAIP2 1.31 0.038 Poly(A)-binding protein interacting protein 2 Cytoplasm Translation regulator SMAD7 1.31 0.013 SMAD family member 7 Nucleus Transcription regulator TESK1 1.31 <0.001 Testis-specific kinase 1 Nucleus Kinase Gene ID . Expression fold change . Expression P-value . Entrez gene name . Cellular location . Function . TAF7 −3.11 <0.001 TATA-box-binding protein-associated factor 7 Nucleus Transcription regulator DTL −1.48 <0.001 Denticleless E3 ubiquitin protein ligase homolog Nucleus Other ITK −1.48 <0.001 IL2 inducible T cell kinase Cytoplasm Kinase FBXL8 −1.44 <0.001 F-box and leucine rich repeat protein 8 Cytoplasm Enzyme OR13C4 −1.42 <0.001 Olfactory receptor family 13 subfamily C member 4 Other Other SNN −1.42 <0.001 Stannin Plasma Membrane Other ZNF510 −1.40 0.020 Zinc finger protein 510 Nucleus Other ATG12 −1.37 0.013 Autophagy related 12 Cytoplasm Other KCNN1 −1.37 0.019 Potassium calcium-activated channel subfamily N member 1 Plasma membrane Ion channel LIPN −1.37 0.018 Lipase family member N Extracellular space Enzyme SKOR2 −1.37 <0.001 SKI family transcriptional corepressor 2 Nucleus Transcription regulator BARD1 −1.36 <0.001 BRCA1-associated RING domain 1 Nucleus Transcription regulator ANKRD22 −1.35 <0.001 Ankyrin repeat domain 22 Nucleus Transcription regulator KPNA5 −1.35 <0.001 Karyopherin subunit alpha 5 Cytoplasm Other KRT14 −1.35 0.016 Keratin 14 Cytoplasm Other NPPA −1.35 0.019 Natriuretic peptide A Extracellular space Other ARMC12 −1.34 <0.001 Armadillo repeat containing 12 Nucleus Other HIST1H2AJ −1.34 <0.001 Histone cluster 1 H2A family member j Nucleus Other KISS1R −1.34 <0.001 KISS1 receptor Plasma membrane G protein-coupled receptor GPR6 −1.33 <0.001 G protein-coupled receptor 6 Plasma membrane G protein-coupled receptor CENPS −1.32 0.015 Centromere protein S Nucleus Other OPTC −1.32 0.018 Opticin Extracellular space Other OR9K2 −1.32 0.012 Olfactory receptor family 9 subfamily K member 2 Plasma membrane G protein-coupled receptor SYNDIG1 −1.32 0.019 Synapse differentiation inducing 1 Plasma membrane Other CACNA1I −1.31 0.032 Calcium voltage-gated channel subunit alpha1 I Plasma membrane Ion channel OR4X2 −1.31 0.029 Olfactory receptor family 4 subfamily X member 2 (gene/pseudogene) Plasma membrane Other FBXL12 −1.30 0.019 F-box and leucine rich repeat protein 12 Cytoplasm Enzyme GCNT4 −1.30 <0.001 Glucosaminyl (N-acetyl) transferase 4, core 2 Cytoplasm Enzyme LIPE −1.30 <0.001 Lipase E, hormone sensitive type Cytoplasm Enzyme LRP2 −1.30 <0.001 LDL receptor related protein 2 Plasma membrane Transporter SEC14L5 −1.30 0.011 SEC14 like lipid binding 5 Other Other SLC28A2 −1.30 0.012 Solute carrier family 28 member 2 Plasma membrane Transporter CNOT11 1.30 <0.001 CCR4-NOT transcription complex subunit 11 Cytoplasm Other KLF1 1.30 <0.001 Kruppel like factor 1 Nucleus Transcription regulator KLF10 1.30 <0.001 Kruppel like factor 10 Nucleus Transcription regulator MEF2D 1.30 <0.001 Myocyte enhancer factor 2D Nucleus Transcription regulator NDUFS8 1.30 0.033 NADH: ubiquinone oxidoreductase core subunit S8 Cytoplasm Enzyme NDUFV1 1.30 0.033 NADH: ubiquinone oxidoreductase core subunit V1 Cytoplasm Enzyme NFX1 1.30 0.014 Nuclear transcription factor, X-box binding 1 Nucleus Transcription regulator TMEM109 1.30 0.015 Transmembrane protein 109 Cytoplasm Other AKAP5 1.31 <0.001 A-kinase anchoring protein 5 Plasma membrane Other CAPZA2 1.31 0.011 Capping actin protein of muscle Z-line alpha subunit 2 Cytoplasm Other COX6C 1.31 <0.001 Cytochrome c oxidase subunit 6C Cytoplasm Enzyme DCAF8 1.31 <0.001 DDB1- and CUL4-associated factor 8 Nucleus Other EGLN3 1.31 0.017 egl-9 Family hypoxia inducible factor 3 Cytoplasm Enzyme HOGA1 1.31 <0.001 4-Hydroxy-2-oxoglutarate aldolase 1 Cytoplasm Enzyme IDH3B 1.31 0.037 Isocitrate dehydrogenase 3 [NAD(+)] beta Cytoplasm Enzyme PAIP2 1.31 0.038 Poly(A)-binding protein interacting protein 2 Cytoplasm Translation regulator SMAD7 1.31 0.013 SMAD family member 7 Nucleus Transcription regulator TESK1 1.31 <0.001 Testis-specific kinase 1 Nucleus Kinase Open in new tab Signalling pathways involving differentially expressed genes To further illustrate the relationships and patterns of expression of key differentially expressed genes in animals without functional deficits, network diagrams show the key role of integrated pathways and cellular regulators of responses to ischaemia and hypoxic injury. Relationships between CXCL, VEGF and other mediators of cell signalling cascades involved in arteriogenesis and angiogenesis (Fig. 4) are highlighted to reinforce associations previously described in the literature [21–23], as well as emphasize potential areas for novel exploration. Figure 4: Open in new tabDownload slide Network diagram of subcellular localization of focus molecules participating in CXCL12 signalling cascade (blue lines) including genes participating in cell signalling and molecular transport. Red colouration indicates up-regulation in gene expression. MMP: matrix metallopeptidase; MYD88: myeloid differentiation primary response 88; OPTC: opticin; TNMD: tenomodulin; VEGFA: vascular endothelial growth factor A. Figure 4: Open in new tabDownload slide Network diagram of subcellular localization of focus molecules participating in CXCL12 signalling cascade (blue lines) including genes participating in cell signalling and molecular transport. Red colouration indicates up-regulation in gene expression. MMP: matrix metallopeptidase; MYD88: myeloid differentiation primary response 88; OPTC: opticin; TNMD: tenomodulin; VEGFA: vascular endothelial growth factor A. DISCUSSION In spite of previous studies indicating functional and neuroprotective benefits in staging TAAA repair [16–18, 24], there remains a need to further describe the molecular underpinnings of the regional angiogenesis and vessel rearrangement induced by extensive SA occlusion. Translational and basic science investigations have begun to uncover the molecular signature of aortic pathologies [25, 26] and gene expression patterns in SCI [27, 28], but there have been no studies to date specifically characterizing the transcriptomic profile of acute phase responses to the surgically induced changes in spinal cord perfusion. The present study offers a preliminary demonstration of the feasibility of applying microarray-based profiling techniques to identify the cellular and molecular responses accompanying functional changes in the PM harvested utilizing our experimental model. The work at hand emphasizes the nature of changes in gene expression and demonstrates a high degree of variability and dimensionality in the patterns of expression and enriched cellular pathways. These findings additionally highlight the activation of multiple expression cascades, likely occurring during the preconditioning of the spinal collateral circulation during the ligation of SA up to 10 days before stent placement. This study shows that, with an increasing number of coils, there is an associated increase in the expression of many genes participating in transcriptional regulation, cytokine responses, hypoxia signalling and cytoskeletal arrangement and development. The decreased incidence in paralysis associated with these increases in gene expression (see group 3 expression patterns) suggests a disruption in the activation of responsive pathways stimulated by the massive occlusion of vessels in single-staged procedures. Specifically, this study demonstrates the essential nature of mediators related to cell signalling and molecular transport, inflammatory responses, cardiovascular system development and cellular growth and proliferation significantly down-regulated in paralysed subjects compared to those recovering function; these findings demonstrate the important cellular and molecular pathways up-regulated with preconditioning associated with staged endovascular coiling before TAAA repair. Overall, the data support the use of expression profiling—and subsequent application of relevant hierarchical and canonical pathways of expression—to guide the identification of novel effect-directed methodologies for monitoring and manipulating the changes in the CN vasculature. As there are no biomarkers available to assess changes in the CN as a result of embolization or staged endovascular procedures, applying such transcriptomic tools could enhance clinical practice by revealing mechanisms contributing to SCI in the setting of TAAA repair. With the timing of SA coiling and staging of procedures remaining arbitrary in current surgical practice, confirming the role of mediators of physiological processes essential in the regulation of vascular homeostasis and expansion of the CN through the processes of angiogenesis and arteriogenesis will provide insight into more individualized and precise waiting periods between staged procedures beyond the 5- to 7-day wait that previous studies have indicated might be beneficial. In light of recent successes with minimally invasive controlled release systems to deliver encapsulated proteins, such as CXCL12 to promote arteriogenesis in the setting of ischaemic injury [22], the potential therapeutic application of the findings of this study remains to be further explored. The ability to deliver upstream regulators of arteriogenesis and angiogenesis in the setting of staged interventions could potentially mediate the changes in blood flow accompanying endovascular interventions and significantly impact clinical patient outcomes. Limitations Notable limitations to the present study include small sample size and the use of FFPE tissue for assay. Given evidence that formalin fixation of tissues leads to chemical modifications of biomolecules—notably, the fragmentation of templates for downstream polymerase chain reaction amplification, reduction in efficiency of cDNA synthesis from RNA and the generation of sequence artefacts [29, 30]—subsequent studies will employ extractions from reagent stabilized and fresh frozen specimens to increase the efficiency of downstream applications and improve the detection of differential signals across intervention. Such modifications should support the development of a more robust body of transcriptomic knowledge and, considering the ever-increasing annotation of previously unknown genes, it is anticipated that subsequent studies integrating such genomic tools will be more capable of identifying the molecular underpinnings of mechanisms at play. Presented at the 32nd Annual Meeting of the European Association for Cardio-Thoracic Surgery, Milan, Italy, 18–20 October 2018. ACKNOWLEDGEMENTS Donations of stents from W.L. Gore & Associates, Inc. (Flagstaff, AZ, USA) and embolization coils from Cook Medical (Bloomington, ID, USA) were used to create the animal models from which the tissues used for this study were derived. Funding This work was supported by extramural funding from the New Jersey Commission on Spinal Cord Research [#CSCR15IRG012]. Conflict of interest: none declared. REFERENCES 1 Ullery BW , Cheung AT , Fairman RM , Jackson BM , Woo EY , Bavaria J et al. 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Google Scholar Crossref Search ADS PubMed WorldCat © The Author(s) 2019. Published by Oxford University Press on behalf of the European Association for Cardio-Thoracic Surgery. All rights reserved. This article is published and distributed under the terms of the Oxford University Press, Standard Journals Publication Model (https://academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model)

Journal

European Journal of Cardio-Thoracic SurgeryOxford University Press

Published: Jan 1, 2020

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