Methods of Novel Therapeutic Candidate Identification Through Gene Expression Analysis in Vascular-Related Diseases

Information

  • Patent Application
  • 20210010082
  • Publication Number
    20210010082
  • Date Filed
    June 22, 2020
    4 years ago
  • Date Published
    January 14, 2021
    3 years ago
Abstract
Multiple treatment regimens for vascular-related diseases and disorders. Methods of treating vascular-related disorders based on gene expression studies from samples collected from individuals having symptoms of vascular-related disorders. Additionally, methods for diagnostic techniques to focus treatment regimens. Finally, methods of treating vascular-related disorders involving targeting microRNAs.
Description
FIELD OF THE INVENTION

The present invention relates to assessment and identification of expression of genes related to vascular-related diseases. The present invention also includes methods of comparing gene expression patterns with respect to various disease states.


BACKGROUND OF THE INVENTION

Pulmonary arterial hypertension (PAH) is an occlusive disease of the pulmonary arteries leading to serious hemodynamic abnormality, right heart failure, and premature death. The molecular mechanisms behind PAH are still unclear. Without a more complete understanding of PAH and how its complex vascular dysfunctions relate to one another, patients will suffer from imprecise diagnosis and drug therapy that may be less than optimal. Despite recent advances and introduction of new clinically approved drugs, the 5-year survival from pulmonary hypertension remains an estimated 50% (Archer and Rich, 2000). Consequently, treatment for PAH, while recently improved, still offers significant and long-lasting improvement in only a minority of patients. A methodology to elucidate the molecular pathways associated with PAH could guide the development of new therapies for this disease.


Though platelets and other cells may have a role in PAH, pulmonary endothelial cells and pulmonary smooth muscle cells appear to be the primary sites of disease progression (Humbert et al 2004). Molecular pathways that show abnormality in pulmonary endothelial cells and pulmonary smooth muscle cells during PAH include endothelin-1 (Giaid et al 1993), serotonin & serotonin transporter (Marcos et al 2003), thromboxane (Walmrath et al 1997), nitric oxide synthase (Kobs and Chesler 2006), prostacyclins (Gailes, et al 2001), potassium channels (Mandegar et al 2002), BMP signaling (Eddahibi et al 2002), and survivin (McMurtry et al 2005). PAH impairs normal signaling and growth in both pulmonary endothelial and pulmonary smooth muscle cells, yet the cellular abnormalities seem to shift over time in unpredictable patterns that has thus far escaped concise definition (Michelakis, 2006).


PAH may be understood as proceeding in phases. In early PAH, endothelial apoptosis occurs, probably resulting in pulmonary arteriole plugging and an increase in pulmonary vascular pressure (Michelakis, 2006). In late PAH, chronic exposure to elevated pulmonary artery pressure together with dysfunctional endothelial signaling initiates hyperproliferation of smooth muscle cells (McMurtry et al 2005). Increased concentric pulmonary smooth muscle cell proliferation leads to ever increasing pulmonary artery pressure, right ventricular failure, and death.


Lung pathology in all PAH patients show thickening throughout the arterial wall of the pulmonary vascular bed. In some forms of the disease, the pulmonary vascular lesions are reversible (e.g. in newborns with congenital heart defects). In other patients, such as those with the idiopathic form, the lesions are irreversible. It is unknown how these variations in PAH relate to one another on a molecular basis (Pearl et al 2002).


Current therapies for PAH patients primarily target vascular tone. Treatments that aim at correcting potassium channel dysfunction (Machado et al 2001), nitric oxide impairment (Humbert et al 2004), prostacyclin impairment (Tuder et al 1999, Christman et al 1992), and endothelin-1 expression (Giaid et al 1993) have all been clinically available for several years. These therapies offer some relief from hemodynamic symptoms, but most patients show only a transient response. The proliferative disease continues to progress in most PAH patients, resulting in a five year mortality rate that remains at around 50% (Newman et al 2004).


Currently, there are no clinically available routine means to obtain endothelial and smooth muscle samples from the pulmonary arteries of pulmonary hypertension patients for diagnosis, disease staging or drug discovery. Applicant's earlier invention, described in U.S. Pat. No. 5,406,959, describes an endoarterial biopsy catheter that has demonstrated its safety and effectiveness in normal canines (Rothman, Mann et al., 1996), canines with experimentally-induced pulmonary hypertension (Rothman, Mann et al., 1998), and canines with single-sided lung transplant rejection (Rothman, Mann et al., 2003). Preliminary studies have also demonstrated the safety and efficacy of a catheter-based method to obtain endovascular samples from a porcine model of PAH.


Percutaneously-obtained pulmonary endoarterial biopsy samples were found to be of sufficient quantity and quality for porcine whole genome mRNA microarray analysis and microRNA analysis. Whole genome microarray analysis revealed time-sensitive variations in gene expression values as PAH progressed in the subject animal model. Genes previously shown to be associated with PAH displayed changes characteristic of the disease, and genes previously unassociated with PAH also displayed expression level dysregulation. These findings raise the possibility that the endoarterial biopsy catheter combined with microarray analysis may provide a valuable platform for the discovery of novel drug and biomarker targets in pulmonary hypertension and a platform to deliver individualized pharmacotranscriptomics.


MicroRNA analysis revealed pressure sensitive changes in microRNA expression. As our surgical shunt model of pulmonary hypertension progressed from a high flow low pressure (HFLP) manifestation to a high flow high pressure (HFHP) manifestation, different microRNAs became dysregulated either increasing or decreasing in expression relative to our baseline normal values.


Most new therapies promise to focus on arresting either the endothelial apoptosis that characterizes early PAH (angiopoetin-1 & endothelial nitric oxide synthase cell-base gene transfer (Zhao et al 2003; 2005), caspase inhibitors (Taraseviciene-Stewart et al 2001)) or the smooth muscle cell proliferation typical of late PAH (dichloroacetate (McMurtry et al 2004), simvastatin (Nishimura et al 2003), sidenafil (Wharton et al 2005), imatinib (Schermuly et al 2005), anti-survivin (McMurtry et al 2005), K+ channel replacement gene therapy (Pozeg et al 2003)).


Before administering therapies, however, it would be extremely valuable to determine which genes are dysregulated in each PAH patient at any stage of their individual disease progression. Without knowing what genes are aberrant during any point in the patient's disease course, targeted therapies may miss the mark in some patients. Life threatening side effects may emerge if the wrong cells, at the wrong time, are encouraged to die or proliferate in patients with compromised pulmonary vascular health.


A powerful method for determining the gene expression levels of thousands of genes simultaneously are DNA microarrays. Initially used for the classification of cancers that were difficult to discriminate histologically (Golub et al 1999, Bhattacharjee et al 2001, and Ramaswamy et al 2001), microarrays have been more recently applied to PAH (Geraci et al 2001). PAH microarray studies have been performed on whole lung homogenates in humans (Fantozzi et al 2005) and rats (Hoshikawa et al 2003), surgically-dissected pulmonary arteries in pigs (Medhora et al 2002), laser-microdissected pulmonary arteries in rats (Kwapiszewska et al 2005), and mononuclear peripheral blood in humans (Bull et al 2004). These studies have been performed to discover potentially novel PAH disease pathways, biomarkers, therapeutic targets and patient classification gene expression profiles.


To advance PAH microarray studies into practical clinical use, tissue procurement methodologies are required that do not require surgical explant or postmortem procurement, and peripheral blood has thus far proven to be inadequate to discriminate gene expression signatures between subgroups of PAH patients (Bull et al 2004; Bull et al 2007). To take advantage of the full power of microarray technologies in PAH patients, a safe and effective minimally invasive means for the repeat procurement of endovascular samples from living PAH patients is required.


The present invention provides for the use of a novel interventional catheter, an endoarterial biopsy catheter, to obtain serial biopsy specimens from hypertensive pulmonary vessels for analysis. The ability to procure endothelial and smooth muscle samples in a minimally invasive manner will allow physicians to use microarray profiling and other techniques to classify patients upon initial presentation according to their gene expression signatures, prescribe therapies that target genes empirically found to be dysregulated in each individual patient, and monitor and adjust PAH patient therapy according to subsequent biopsy findings. A greater understanding of the complex molecular pathways underlying each patient's PAH should enable more precise diagnosis and the delivery of more effective therapies. Also of importance is the ability to discover new uses for existing drugs as well as discovering new drug targets.


Individualized pharmacotranscriptomics based on endoarterial biopsy and microarray analysis represents a reasonable choice for researchers struggling with the complexities and contradictions of PAH and other vascular diseases. The huge literature generated from in vitro and animal studies falls short, at times, in addressing the actual facts of patient health. Many commentators describe this dilemma as the “bench-to-bedside gap”, where in vitro and animal laboratory data fails to model human disease circumstances (Aird, 2004). Bridging that gap through catheter-based access to the vasculature in a model that recapitulates the clinical and histopathological manifestations of a form of human pulmonary hypertension will likely enable closer correlations between animal studies and patient care, and serve as a model for other vascular-based diseases such as atherosclerosis, congestive heart failure, sickle cell disease, organ transplant rejection, connective tissue diseases, chronic obstructive pulmonary disease, pulmonary embolism, asthma, systemic inflammatory response, battlefield trauma, cancer, sepsis and acute respiratory distress syndrome. There is a need in the art to provide data from gene expression analyses in order to target novel candidates for use in treating or preventing PAH.


SUMMARY OF THE INVENTION

One aspect of the present invention provides for methods of treating an individual suffering from a vascular-related disease comprising the steps of:


a) obtaining a biopsy sample from the individual's pulmonary artery;


b) analyzing gene expression levels of the biopsy sample from the pulmonary artery of the individual and a non-diseased control;


c) comparing the gene expression levels between the biopsy sample from the pulmonary artery of the individual and the non-diseased control;


d) identifying at least one gene from step c) that is upregulated or downregulated in the biopsy sample based on the non-diseased control;


e) obtaining gene products from the genes identified in step c); and


f) selecting pharmaceutical agents which are known inhibitors of the gene products from the at least one upregulated gene or known promoters of the gene products from the at least one downregulated gene. An additional aspect to the present invention provides for the pharmaceutical agents selected for administration to the individual suffering from the vascular-related disease. In yet another aspect, the individual is categorized based on progression of the vascular-related disease, with the treatment being based on the timing of the disease.


Another aspect of the present invention provides for a means of comparing varying levels of gene expression based on an animal model for pulmonary arterial hypertension. In a preferred embodiment, the genes expressed in the animal model are genes found to be either upregulated or downregulated. In a more preferred embodiment, the upregulated or downregulated genes are time-dependent based on the time after exposure to the PAH.


Another aspect of the present invention provides for methods of identifying genes involved in the pathway of PAH based on differential gene expression studies in a time-dependent animal model for PAH. In one embodiment, the genes are compared to other known genes which are upregulated or downregulated in the known PAH pathway.


Yet another aspect of the present invention provides for methods of diagnosing a vascular-related disease in an individual comprising the steps of:


a) identifying at least one gene that is upregulated or downregulated in the vascular-related disease comprising the steps of:

    • 1) obtaining a biopsy sample from the individual's pulmonary artery during progression of the vascular-related disease;
    • 2) obtaining a pulmonary artery sample from a non-diseased control;
    • 3) extracting RNA from the samples in steps 1) and 2);
    • 4) obtaining gene products from the RNA extracted in step 3); and
    • 5) comparing gene expression levels from the biopsy sample with the non-diseased control, and


b) associating the genes upregulated in the biopsy sample with an inhibitor of the gene products for administration to the individual and genes downregulated in the biopsy sample with a promoter of the gene products for administration to the individual.


Another aspect of the present invention provides for methods of treating an individual having a vascular-related disease by targeting microRNAs comprising the following steps:


a) assessing a stage of the vascular-related disease in the individual;


b) identifying whether microRNAs are upregulated or downregulated;


c) selecting the microRNAs to target based on the stage of the vascular-related disease and whether the microRNAs are upregulated or downregulated; and


d) administering an agent known to inhibit an upregulated microRNA or an agent known to promote a downregulated microRNA to the individual. A variation of this embodiment provides for the stage of the vascular-related disease being based on flow rates and blood pressure within an artery of the individual.


Another aspect of the present invention provides for methods of therapeutically targeting microRNA dysregulated in PAH comprising the steps of:

    • (a) obtaining a biopsy sample from the pulmonary artery during the progression of PAH;
    • (b) obtaining a pulmonary artery sample from a non-diseased control;
    • (c) extracting RNA from the artery samples;
    • (d) converting the RNA to cDNA;
    • (e) comparing levels of microRNA expression at the two differing times;
    • (f) identifying microRNA dysregulated in PAH relative to baseline; and
    • (g) inhibiting upregulated microRNA or promoting downregulated microRNA identified in PAH biopsies.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 depicts a surgical shunt model of PAH and its association with congenital heart disease (CHD).



FIG. 2 depicts the endoarterial biopsy procedural configuration.



FIG. 3 depicts biopsies: normal vessels at baseline, hypertensive LPA at 7, 21, 60 and 180 days post shunt.



FIG. 4 depicts GeneSpring downstream analysis of microarray data.





DETAILED DESCRIPTION OF THE INVENTION

The model described in the present invention is surgically-induced PAH in pigs. Our model mimics human Eisenmenger syndrome (a form of PAH related to congenital heart malformation) in both symptoms and pathology (Corno et al 2003). The size of the animals makes the pulmonary vessels available to the catheter, providing a ready transition to human clinical use. And finally, the commercial availability of whole genome porcine microarrays (Bai et al 2003) makes the species ideal for our purposes in the study, and renders the use of cross species microarrays unnecessary (Medhora et al 2002).


By obtaining pulmonary endovascular samples at early, intermediate and late time points in PAH progression, and analyzing these samples using porcine whole genome microarrays, a time-sensitive microarray based map of the underlying molecular biology of PAH may be obtained. Improved knowledge of the molecular mechanisms underlying PAH progression can lead to the identification of stage-specific biomarkers, new therapeutic targets for drug intervention, and novel signaling pathways involved in the pathogenesis of PAH. These novel target genes can then be validated using quantitative PCR and immunohistochemical stains on porcine endoarterial biopsy samples procured concurrently. At the same time, the combination of minimally invasive endoarterial biopsy and whole genome microarray analysis can serve as an animal model for subsequent studies in PAH patients.


The following examples provided in this disclosure provide a profile gene expression in pulmonary hypertensive pigs by surgical anastomosis of the left pulmonary artery to the descending aorta. Endoarterial biopsy samples are collected from animals with a surgical shunt model of pulmonary hypertension at multiple time points over a 6-month time course. Gene expression analysis of the biopsy samples was performed on porcine microarrays. Microarray analysis was performed to detect dysregulated genes previously unassociated with PAH, discover novel biomarkers of pulmonary hypertension and novel targets for therapeutic intervention and advance knowledge of the molecular mechanisms of pulmonary hypertension. These studies will also help validate a new platform for PAH diagnosis and drug discovery, endoarterial biopsy and microarray analysis, for eventual clinical practice.


EXAMPLES
Example I: Construction of a Microarray-Based Map of Changes in Gene Expression During the Progression of PAH and the Identification of Novel Therapeutic Candidates

In an animal model of PAH created by Antonio Corno and colleagues, pigs undergo surgery that redirects systemic circulation into the left pulmonary artery mimicking pulmonary hypertension secondary to congenital heart disease. The surgery elevates PA pressure and creates the same hemodynamic conditions that PAH patients experience. The present study investigates how the elevated pressure remodels the pulmonary vasculature. In Corno's studies, histology on necropsy confirmed intimal hyperplasia in the pulmonary arteries, evidence that the surgical shunt surgery described will cause endovascular remodeling (Corno et al 2003).


Biopsy Extraction and Surgery Protocol

20-30 kg Yucatan Micropigs (Sus scrofa, Yucatan micro breed) underwent surgical anastomosis of the left pulmonary artery to the descending aorta, resulting in left pulmonary arterial hypertension of at least systemic levels. Animals are penned in the laboratory for no less than one week prior to surgery and fed normal chow. On surgery day, animals were premedicated with 20 mg/kg intramuscular ketamine and 0.1 mg/kg intramuscular midazolam. After 0.25 mg of intramuscular atropine, anesthesia was induced with 1 mg/kg intravenous midazolam and 0.1 mg/kg intravenous fentanyl and maintained with 0.1 mg/kg/hr intravenous pancuronium bromide. Pigs were ventilated with an inspired oxygen fraction (FiO2) of 0.4, a tidal volume of 15 ml/kg, and a respiratory rate of 12 breaths/minute. One gram of intravenous cefazolin was given before and 2 hours after the surgical procedure. Surgical and catheter procedures were performed under general anesthesia with endo-tracheal intubation. Sedation medications and anesthetics were administered by an anesthesiologist. Intra-cardiac and intravascular pressures, EKG, and blood oxygen saturations were monitored continuously.


Under sterile conditions (the thoracic area was shaved and prepared with betadine, a left thoracotomy was performed through the fourth intercostal space, about 5 centimeters, to expose the great arteries. The main pulmonary artery (MPA) and its branches were identified and freed from surrounding tissue. Two clamps were placed on the proximal left pulmonary artery (LPA). The proximal LPA was sutured closed, using prolene, and the distal LPA was sutured end to side in a clamped region in the descending aorta (FIG. 1), using cardiovascular prolene. Pieces of LPA endoarterial tissue were taken for histology. The clamps were removed and an IV dose of 1 mg/kg Furosemide immediately given. Hemostasis was obtained with sutures and cautery. Direct needle blood pressures were recorded in the main pulmonary artery and in the newly anastomosed left pulmonary artery. The chest was closed with sutures, both subcutaneous and cutaneous layers, using prolene and surgical wire. The animals then were weaned from anesthesia and mechanical ventilation. Postoperative analgesia was provided with morphine four times a day and a 1-2 mg/kg dose from 0.25% solution of IV Bupivacaine, a local anesthetic. A circulating warming blanket was used during surgery and recovery.


Endoarterial biopsies were performed at baseline prior to surgery to obtain unaffected tissue, and at post-shunt timepoints to obtain hypertensive biopsy samples (FIG. 2). Follow up endoarterial biopsy procedures were scheduled 7, 21, and 180 days after surgery. On each catheterization day, animals were premedicated with 10 mg/kg of IV propofol, were intubated and ventilated at a rate of 12 breaths/min and were maintained under anesthesia with 1.5% halpthane. A femoral artery line was placed for monitoring. To obtain biopsies from the hypertensive left lung, an 8F introducer is placed in a carotid artery, and a 7F endhole catheter is advanced into the aorta. An angiogram is performed to visualize the LPA-aortic anastomosis. The 7F endhole catheter is then threaded through the anastomosis with X-ray fluroscopic guidance. An angiogram of the hypertensive left pulmonary vascular tree is then performed, and the catheter is advanced to the distal pulmonary artery selected for biopsy. A 0.038 in, 260 cm extra stiff Amplatz exchange guide wire will then be passed through the end-hole catheter. The end-hole catheter was exchanged for a long flexible 8F introducer sheath that is adapted with a radio opaque band at the distal end and shaped to conform to the vascular pathway. A 7F angiographic catheter was advanced through the sheath in to a 2.5 mm to 3.0 mm distal pulmonary artery branch, where an angiogram was obtained. The angiographic catheter will serve as a guide to advance the stiff sheath into a small vessel targeted for biopsy and will then be exchanged for the endoarterial biopsy catheter.


The endoarterial biopsy catheter has an external diameter of 2.5 mm and is composed of two flexible polymeric tubes that slide relative to each other. The inner tube has a stainless steel distal end with a beveled opening that is designed to accommodate arterial tissue. A vacuum is coupled to the inner tube and channeled to the beveled opening. The outer tube terminates in a stainless steel cutting tube. The proximal ends of the two tubes are with a spring powered operating mechanism. To obtain the biopsy sample a vacuum is transmitted to the beveled opening of the inner tube, causing a tissue sample to be drawn in. The outer tube is then advanced over the inner tube, severing the tissue sample. With this design, the area of artery contacted by the outer periphery of the beveled opening is larger than the inner aperture connected to the vacuum, this maintaining the tissue sample with its orientation preserved. After each biopsy, the catheter was removed and the tissue sample was placed in the appropriate solution for further processing and analysis. After the biopsy procedures were completed, repeated angiograms were obtained to assess the degree of vascular injury. At the end of the procedure, the biopsy catheter and introducer sheath were removed and hemostasis was obtained by surgical repair of the carotid artery. The animals will then be weaned from anesthesia and mechanical ventilation. Postoperative analgesia was provided with morphine four times a day and or fentanyl patches and non-steroidal anti-inflammatory drugs four times a day.


Tissue Processing

For microarray analysis, biopsy samples are placed in a test tube containing RNAlater (Qiagen), flash frozen in dry ice, and kept frozen until RNA extraction. Additional samples are preserved in formalin, OCT freezing solution, or Bouin's solution for subsequent immunohistochemical and quantitative PCR analysis.


Porcine Genome Arrays

The Affymetrix GeneChip® Porcine Genome Array provides comprehensive coverage of the Sus scrofa transcriptome. The array contains 23,937 probe sets that interrogate approximately 23,256 transcripts from 20,201 Sus scrofa genes.


The sequence information for this array was selected from public data sources including UniGene Build 28 (August 2004), GenBank® mRNAs up to Aug. 24, 2004, and GenBank® porcine mitochondrial and rRNA sequences. Probe sets consist of up to eleven probe pairs. The array format consists of eleven micron features synthesized on the 100 format.


RNA Extraction from Endoarterial Biopsy Samples


RNA was prepared from fresh frozen endoarterial biopsy samples in a segregated laboratory, specially prepared and cleaned regularly to destroy nucleases. Specimens were homogenized using QIAshredder columns (Qiagen, Valencia, Calif.) utilized in a FastPrep FP120 Homogenizer (Thermo Electron Corporation, Waltham, Mass.). RNA was isolated using RNeasy Mini columns (Qiagen, Valencia, Calif.) as per manufacturer's protocol. All total RNA was eluted in nuclease free water, and quantity was established by UV spectrophotometer. Final RNA integrity was evaluated by capillary electrophoresis on the Agilent 2100 Bioanalyzer (Agilent, Palo Alto, Calif.).


Gene Expression

Before target production, the quality and quantity of each RNA sample was assessed using a 2100 BioAnalyzer (Agilent). Target was prepared and hybridized according to the “Affymetrix Technical Manual”. Total RNA (ug) was converted into cDNA using Reverse Transcriptase (Invitrogen) and a modified oligo (dT)24 primer that contains T7 promoter sequences (GenSet). After first strand synthesis, residual RNA was degraded by the addition of RNaseH and a double-stranded cDNA molecule was generated using DNA Polymerase I and DNA Ligase. The cDNA will then be purified and concentrated using a phenol:chloroform extraction followed by ethanol precipitation. The cDNA products will then be incubated with T7 RNA Polymerase and biotinylated ribonucleotides using an In Vitro Transcription kit (Enzo Diagnostics). One-half of the cRNA product was purified using an RNeasy column (Qiagen) and quantified with a spectrophotometer. The cRNA target (20 ug) was incubated at 94° C. for 35 minutes in fragmentation buffer (Tris, MgOAc, KOAc). The fragmented cRNA was diluted in hybridization buffer (MES, NaCl, EDTA, Tween 20, Herring Sperm DNA, Acetylated BSA) containing biotin-labeled OligoB2 and Eukaryotic Hybridization Controls (Affymetrix). The hybridization cocktail was denatured at 99° C. for 5 minutes, incubated at 45° C. for 5 minutes and then injected into a GeneChip® cartridge. The GeneChip® array was incubated at 42° C. for at least 16 hours in a rotating oven at 60 rpm. GeneChips® were washed with a series of nonstringent (25° C.) and stringent (50° C.) solutions containing variable amounts of MES, Tween20 and SSPE. The microarrays will then be stained with Streptavidin Phycoerythrin and the fluorescent signal was amplified using a biotinylated antibody solution. Fluorescent images were detected in a GeneChip® Scanner 3000 and expression data was extracted using the GeneChip® Operating System v 1.1 (Affymetrix). All GeneChips® were scaled to a median intensity setting of 500. Gene expression levels were compared between biopsy samples taken from the control distal pulmonary vasculature (baseline LPA and RPA) and PAH distal pulmonary arteries (surgical shunt LPA).


Gene Expression Analysis

After RNA preparation, array hybridization and scanning of the Porcine GeneChips® exactly as recommended by Affymetrix, the data produced are processed using the Affymetrix tools in the R-Bioconductor package called /Affy/. This tool set allows for various probe level analyses of the data as well as probe level quality control. The MASS algorithm was used, taking into account both the MM and PM probe data, and generating “Present” or “Absent” calls for each gene on each chip. If boxplots of the porcine probe level data reveal that any of the hybridizations are of low quality, the data from these chips was removed from any downstream analysis. MASS with the non-linear Quantiles normalization (Affy package /normalize.quantiles)/ was used with this data set to produce data almost free of artificial correlations. The Present/Absent calls are also used to remove from the analysis the genes that were never expressed in any of the samples examined (this is analogous to using a P-value for gauging a gene's data quality on a chip, and then filtering).


Based on the first dozen chips processed, after normalization and quality control ˜19,000 genes were moved on to the next stage of the analysis. The commercial package GeneSpring was used to assess differential gene expression and perform tests using clustering algorithms. Thus far, hierarchical clustering has revealed that the time-point replicates have the greatest similarity to one another.


Gene expression fold changes for 7, 21 60 and 180 days post-surgery relative to baseline were then loaded into GSEA (gene set enrichment analysis) or specially written PERL scripts which carry out KS (Kolmogorov-Smirnov) statistical analysis in order to identify novel therapeutic candidates.


Novel Therapeutic Identification

During PAH the best therapeutic targets are those which are upregulated as the disease state progresses. Thus drugs which are known to counter the action of any upregulated genes and their products would be of the greatest potential therapeutic value. Therefore, lists of upregulated genes were then matched to drugs which target their gene products.


In addition, many drugs interact with multiple targets in the body's tissues. Lists of the targets (called genesets) for each of ˜2000 characterized drugs were obtained from the literature and online databases. These genesets were then used to search for drugs which would be most likely to have therapeutic value in PAH.


This was done by using KS statistics which computes the Kolmogorov-Smirnov score for a geneset for a particular drug within an ordered list. The KSscore task is used to examine the enrichment of a set of genes at the top of an ordered list. The KS score is high when the tags appear early (i.e. near the top) of the ordered list. The significance of the KS score for a particular test may be examined by computing KS scores for multiple sets of X query genes selected at random from the dataset (note that the KS score is not independent of the number of members of the query gene set). Using this approach we were able to identify in our messenger RNA expression dataset drugs which are currently used as therapeutics for PAH (see FIG. 1A). Importantly, using the same approach we were also able to identify additional potential therapeutics, within the existing pool of characterized drugs. This process identified existing drugs as novel therapeutics for PAH.


Example II: Gene Expression Analysis from Porcine Animal Model Data
Gene Expression Analysis

The porcine studies indicate that single endoarterial biopsy samples obtained in the porcine model of surgical shunt PAH contain sufficient RNA for microarray analysis, as we were able to analyze the mRNAs in whole genome porcine microarrays. We obtained endoarterial biopsies and measured pulmonary arterial pressure (PAP) at baseline prior to surgery, and at approximately 7, 21, 60 and 180 days post-PAH surgery from several animals. Porcine whole genome expression values were obtained for biological replicates with 2 samples from each time point. These replicates produced 5 sets of high quality replicated expression data (baseline, day 7, day 21, day 60 and day 180; see Table 1 for PAP data). Downstream data analysis was carried out using commercial (Ingenuity; GeneSpring) and free/open source software (R; Bioconductor; GSEA).


Mean expression values were obtained for each gene by averaging the gene expression values of the two biopsies at each timepoint. The resulting gene expression mean values were used to calculate fold changes between day 7, 21, 60 and day 180 gene expression relative to baseline.


Validity of the model was confirmed by examining the gene expression changes for selected genes previously found to be dysregulated in PAH (Table 2). Endothelin 1 and protein-tyrosine kinase Tie2 both displayed upregulation in accordance with explanted tissue from IPAH transplant recipients (Dewatcher et al 2006), and platelet-derived growth factor receptor alpha, serotonin receptors 2B and 1D, calmodulin, transcription factor STAT5b, voltage-dependent anion channels 1, 2 and 3, and RAS p21 protein activator 1 also increased in our model while tumor necrosis factor and plasminogen activator inhibitor-1 were found to be downregulated in our model in a similar fashion with IPAH explant tissue results (Fantozzi et al 2005). Survivin was upregulated in our model in a similar fashion to published findings (McMurtry et al 2005), and FYN and VAV-1 oncogenes, requiem homolog, inward rectifier K+ channel, and chloride channel 1 also increased while DEAD/H box polypeptide 3 and angiopoietin 1 displayed decreased expression in agreement with patient findings (Geraci et al 2001). We also observed decreased expression of peroxisome proliferator-activated receptor gamma (Ameshima et al 2003), and downregulated vascular endothelial growth factor B (Louzier et al 2003) in correspondence with previous results. The concordance between genes previously found to be aberrant in published PAH studies and altered gene expression in our model attest to the validity and potential usefulness of gene expression data derived from endoarterial biopsies. The time dependent nature of gene expression dysregulation found in our model further demonstrates the utility of obtaining endoarterial biopsies at multiple time points in PAH progression.


While several of these genes have been previously associated with PAH (for example, KCBN1, CASP3, TLR4, IL1B, IL6, HMGCR, TOP1, FYN, PRKCA, EDNRB, PDGFRA, and HRT2B), several have not (for example, HSPE, YES1, CFTR, MAOA, MAOB, and CACND21), raising the intriguing possibility that known existing drugs that target upregulated genes previously unassociated with PAH may be effective in treatment of the disease.


Example III: Identification of Dysregulated microRNA During the Progression of PAH

Endoarterial biopsy samples percutaneously obtained during the progression of PAH were analyzed to correlate changes in microRNA expression to disease progression.


microRNA Expression Data Analysis


Data analysis was done in three stages. First, expression intensities were calculated for each miRNA probed on the array for all hybridizations (12 in total) using illumina's Beadstudio Version 3.0 software. Second, intensity values were quality controlled and normalized: quality control was carried out by using the illumina Beadstudio detection P-value set to <0.05 as a cutoff. This removed miRNAs which were effectively absent from the arrays (that is, were never detected). After this step, the initial 1145 miRNAs were reduced to 1094. All the arrays were then normalized using the normalize.quantiles routine from the Affy package in Bioconductor. This procedure accounted for any variation in hybridization intensity between the individual arrays


Finally, these normalized data were imported into GeneSpring and analysed for differentially expressed miRNAs. The groups of biological replicates were described to the software and significantly differentially expressed genes determined on the basis of Welch t-tests and fold difference changes in expression level. The determination of miRNA targets genes was done using a publicly available database of miRNA target sequences and a specially written PERL programming script.


miRNA Pressure Related Analysis


The data was also looked at to reflect the stages of the disease (based on blood pressure and flow rates), as opposed to the time point or the individual pigs. Three groups were defined (1) Normal (baseline); (2) High Flow Low Pressure ‘HFLP’ and (3) High Flow High Pressure ‘HFHP’ (see Table 11). The groups were compared back to the baseline and the statistically significantly differentially regulated miRNAs determined (Tables 12, 13, 14 & 15).


Using illumina microRNA expression microarrays, fluctuations in the level of expression of ˜1200 microRNAs were determined during the onset and progression of PAH. Porcine and Homo sapiens miRNA sequences are very often highly conserved. Expression comparisons were done on a timepoint basis, taking in account the available replicates and the statistical significance of the expression changes. The data was also looked at to reflect the stages of the disease (based on blood pressure and flow rates), as opposed to the time point or the individual pigs. Three groups were defined (1) Normal (baseline); (2) High Flow Low Pressure ‘HFLP’ and (3) High Flow High Pressure ‘HFHP’. The groups were compared back to the baseline and the statistically significantly differentially regulated miRNAs determined.


Finding Micro RNAs with Potential as Therapeutic Targets


The messenger RNA expression data set was analysed looking for expression changes in sets of genes with known target sites for particular miRNAs. miRNAs are known to negatively regulate gene expression at the level of translation by binding to upstream regions of mRNA and blocking events required for translation of the mRNA into protein. This was again done using Gene Set Enrichment Analysis (GSEA) and the publicly available miRNA genesets. “Cross-talk” is seen between the messenger RNA gene expression changes and the microRNA expression changes. The messenger RNA expression analysis directly revealed the differential expression of groups of genes competent to be regulated by these miRNA.


Example IV: Personalizing Therapeutic Regimens for Vascular-Based Diseases

The use of gene expression data to shape individual drug therapies has been postulated as the next phase in personalized medicine. The bioinformatic processing of an individual's gene expression data can be used to generate a ranked list of therapies suitable for that individual. PAH disease pathology varies greatly over time, and is also likely to be specific for particular individuals. The analysis of the RNA in the PAH biopsy samples allows therapies to be tailored to the individual at that particular stage of the diseases progression.


The genes and biochemical pathways changing the most at the level of gene expression can be determined by comparing the PAH biopsy samples to a baseline control of normal healthy vasculature tissue. Observations show time-dependent extensive changes in gene expression with the progression of PAH. Known targets for approved PAH therapeutics can be seen Up-regulated in the diseased state.


Drug therapies can be ranked by using the known targets of drugs as genesets. These drug signature lists can then be used in a process such as Gene Set Enrichment Analysis, or KS statistics. KS Statistics returns a score for how well ranked a particular drug would be for a particular patient.


A drug is represented as the set of its known target genes; this can be in the dozens for some bioactive compounds. Genesets for ˜2000 drugs were assembled. KS Statistics yields a value (‘KS score’) representing the positional distribution of the set of query genes (here, the drug targets) within an ordered list of genes (genes induced in PAH). The ordered list is produced by looking at the fold change in a mRNAs expression between time X and the baseline, and sorting on this value. The gene with the greatest fold change is ranked as #1, second greatest fold change is ranked as #2, etc. KS score is computed in accordance with the Kolmogorov-Smirnov non-parametric rank statistic where X is the number of genes in the query gene set, Z is the number of genes in the ordered list, and Y=Z−X. A suitable baseline is generated using gene expression from artery samples from non-diseased controls. These samples can be obtained surgically, percutaneously or post-mortem.


This process can be repeated for all the PAH time points and the resulting table of KS scores for each drug hierarchically clustered. This reveals which drugs are potentially of the greatest therapeutic value for a patient.


This supports the idea of achieving personalized treatments for vascular-based diseases by generating individualized drug prescriptions based on the bioinformatic processing of gene expression data from endoarterial biopsy samples obtained from diseased arteries. Similarly, this enables personalized treatments for vascular-based diseases by generating lists of dysregulated microRNA from the bioinformatic processing of microRNA expression data from endoarterial biopsy samples from diseased arteries.









TABLE 1







Pulmonary arterial pressures obtained during endoarterial biopsy


catheterization for biopsy samples used in microarray analysis.









Pulmonary Arterial Pressure mmHg










Biopsy Sample
Systolic
Diastolic
Mean





Baseline Pig #9
22
11
17


Baseline Pig #10
25
16
18


Day 21 Pig #2
95
66
82


Day 21 Pig #6
41
26
33


Day 60 Pig #6
87
59
74


Day 60 Pig #5
49
27
38
















TABLE 2







Selected genes previously associated with PAH similarly dysregulated in the porcine model.
























Fold
Fold
Fold
Fold









Change
Change
Change
Change


Gene






Day 7/
Day 21/
Day 60/
Day 180/


Symbol
Name
Baseline
Day 7
Day 21
Day 60
Day 180
Base
Base
Base
Base




















VAV1
vav 1
32.56
21.65
237.16
138.29
15.39
−1.50
7.28
4.25
−2.12



oncogene


RASA1
RAS p21
73.23
388.68
280.27
704.56
361.25
5.31
3.83
9.62
4.93



protein



activator 1


TIE2
protein-
20.92
2.59
32.46
702.68
218.34
−8.08
1.55
33.59
10.44



tyrosine



kinase Tie2


FYN
fyn proto-
43.33
180.38
404.77
531.03
166.17
4.16
9.34
12.26
3.83



oncogene


VDAC1
voltage-
1176.57
2350.33
6629.76
3144.14
2277.10
2.00
5.63
2.67
1.94



dependent



anion



channel 1


PDGFRA
platelet-
69.46
152.75
10.45
611.81
18.80
2.20
−6.64
8.81
−3.69



derived



growth



factor



receptor



alpha


5-HT2B
serotonin 2B
49.96
19.03
166.45
142.91
488.77
−2.63
3.33
2.86
9.78



receptor


KCNJ2
inwardly
389.66
83.23
1059.11
212.29
84.28
−4.68
2.72
−1.84
−4.62



rectifying



potassium



channel



KIR6.1


5-HT1D
serotonin 1D
14.17
42.48
8.32
61.48
4.95
3.00
−1.70
4.34
−2.86



receptor


DPF2
requiem,
140.95
123.89
140.90
195.55
93.92
−1.14
−1.00
1.39
−1.50



apoptosis



response zinc



finger gene


VDAC2
Voltage-
5683.09
2665.62
1620.37
4940.32
3643.38
−2.13
−3.51
−1.15
−1.56



dependent



anion



channel 2


STAT5B
signal
469.40
571.47
1327.53
808.09
626.07
1.22
2.83
1.72
1.33



transducer



and activator



of transcription



5b


AGPT
angiopoietin 1
17.825026
50.240685
11.806807
70.12715
3.4479218
2.82
−1.51
3.93
−5.17


BIRC5
apoptosis
169.33
751.37
140.45
31.26
44.69
4.44
−1.21
−5.42
−3.79



inhibitor



survivin


VDAC3
voltage-
4092.99
750.86
5013.26
959.72
2018.55
−5.45
1.22
−4.26
−2.03



dependent



anion



channel 3


PLANH1
plasminogen
27760.742
43007.71
23685.375
28771.838
36086.305
1.55
−1.17
1.04
1.30



activator



inhibitor I


PPARG
peroxisome
177.80
12.86
18.96
194.20
62.40
−13.83
−9.38
1.09
−2.85



proliferator-



activated



receptor



gamma 2


CALM1
Calmodulin
3092.78
2436.23
867.25
1401.38
2252.81
−1.27
−3.57
−2.21
−1.37


APOE
apolipoprotein
358.91
206.34
94.35
129.60
288.79
−1.74
−3.80
−2.77
−1.24



E
















TABLE 3







Day 7 prescription.
















Fold
Fold
Fold
Fold






Change
Change
Change
Change




D 7/
D 21/
D 60/
D 180/
Gene


Probe ID
Name
Base
Base
Base
Base
Symbol
DRUGS

















Ssc.11018.1.A1_at
Mitogen-activated protein
39.80
−5.02
−17.27
−20.43
MAPK14
SCIO-469, RO-3201195



kinase 14


Ssc.15986.1.S1_at
Insulin receptor
29.28
−16.85
−17.70
−19.01
INSR
insulin, insulin aspart,









insulin glulisine, insulin









lispro, insulin glargine


Ssc.873.1.S1_at
Cell division control protein
27.38
−2.37
−4.66
−7.76
CDC2
flavopiridol



2


Ssc.29928.1.A1_at
Histone deacetylase 11 (HD11)
21.56
−3.17
−2.91
−10.50
HDAC11
tributyrin, PXD101,









pyroxamide, vorinostat, FR









901228


Ssc.100.1.S1_at
Tumor necrosis factor
18.41
−1.70
−9.62
−3.15
TNF
adalimumab, etanercept,



precursor (TNF-alpha)





infliximab, CDP870, golimumab,









thalidomide


Ssc.19672.1.S1_at
RAC-alpha serine/threonine-
17.77
1.25
−19.82
−2.11
AKT1
enzastaurin



protein kinase


Ssc.14475.3.S1_a_at
Peroxisome proliferator
13.83
−9.38
1.09
−2.85
PPARG
rosiglitazone, GI262570,



activated receptor gamma





pioglitazone, tesaglitazar,



(PPAR-gamma)





troglitazone


Ssc.14326.1.A1_at
Mitogen-activated protein
12.63
1.56
−1.80
−7.24
MAPK13
SCIO-469



kinase 13


Ssc.25843.1.S1_at
Chloride channel protein 2
11.77
−17.04
−21.97
−9.92
CLCN2
lubiprostone



(ClC-2


Ssc.16201.1.A1_at
Metabotropic glutamate
10.79
−35.68
−33.34
−47.92
GRM7
fasoracetam



receptor


Ssc.11381.1.S1_at
Interferon-alpha/beta receptor
10.45
8.08
2.61
−1.30
IFNAR1
interferon beta-1a, interferon



alpha chain





alfa-2b, interferon alfacon-1,









PEG-interferon alfa-2a,









interferon alfa-2a/ribavirin,









pegintron, interferon beta-1b,









IFNA2A


Ssc.5371.1.S1_a_at
DNA polymerase epsilon subunit
10.16
1.68
−1.37
−3.14
POLE2
gemcitabine



B (DNA polymerase II subunit



B)


Ssc.14471.1.S1_at
B-lymphocyte antigen CD19
9.54
3.30
−10.32
3.04
CD19
combotox, HD37-dgRTA, MT103


Ssc.24856.1.A1_at
phosphodiesterase 11A; cyclic
9.36
−2.70
−3.68
−2.68
PDE11A
dyphylline, nitroglycerin,



nucleotide phosphodiesterase





aminophylline, dipyridamole,



11A1





tolbutamide, tadalafil,









theophylline, pentoxifylline


Ssc.189.1.S1_at
Diacylglycerol O-
9.16
−4.21
−36.07
−24.06
DGAT1
omacor



acyltransferase 1


Ssc.16186.1.S1_at
T-cell surface glycoprotein
9.00
3.12
2.12
−5.66
CD3E
visilizumab, MT103, muromonab-



CD3 epsilon





CD3


Ssc.15601.1.A1_s_at
Interleukin-1 beta precursor
8.18
4.65
−14.71
−2.84
IL1B
IL-1 trap



(IL-1 beta)


Ssc.5538.1.S1_at
Carbonic anhydrase II
8.09
1.39
−2.25
−1.35
CA2
methazolamide,



(Carbonate dehydratase II)





hydrochlorothiazide,



(CA-II) (Carbonic anhydrase





acetazolamide,



C)]





trichloromethiazide,









dorzolamide, chlorothiazide,









dorzolamide/timolol,









brinzolamide, chlorthalidone,









benzthiazide, sulfacetamide,









topiramate


Ssc.113.1.S1_at
Interleukin-1 alpha (IL-1
8.01
−2.65
−1.59
−7.73
ILIA
IL-1 trap



alpha)


Ssc.2895.1.S1_at
Serine/threonine-protein
7.48
−2.02
−2.45
−1.81
AURKB
AZD-1152



kinase


Ssc.8219.1.A1_at
Histone deacetylase 8 (HD8)
7.21
−2.18
−12.09
−29.63
HDAC8
tributyrin, PXD101,









pyroxamide, vorinostat, FR









901228


Ssc.13473.1.A1_at
Ceramide glucosyltransferase
7.13
−2.88
−4.17
−6.14
UGCG
N-









butyldeoxygalactonojirimycin,









N-butyldeoxynojirimycin


Ssc.14129.1.A1_at
4-aminobutyrate
6.91
2.56
−21.17
−3.35
ABAT
valproic acid



aminotransferase,



mitochondrial (GABA



transaminase)


Ssc.15379.1.S1_at
diacylglycerol O-
6.60
−1.51
−3.49
−2.13
DGAT2
omacor



acyltransferase homolog 2;



GS1999full


Ssc.15830.1.A1_at
Retinoic acid receptor beta
6.60
−3.28
−1.83
−1.10
RARB
etretinate, adapalene, 13-cis-









retinoic acid, tazarotene,









acitretin, retinoic acid, 9-









cis-retinoic acid, fenretinide


Ssc.17928.1.A1_at
helicase (DNA) B; helicase B
6.40
−2.65
−4.38
−1.06
HELB
epirubicin


Ssc.19673.1.S1_at
T-cell surface glycoprotein
6.40
2.70
2.03
−11.77
CD3D
visilizumab, MT103



CD3 delta


Ssc.17222.1.A1_at
mucin 1, transmembrane;
6.31
−6.10
−5.94
−13.48
MUC1
HuHMFG1


Ssc.55.1.S1_at
Epidermal growth factor
6.09
−5.46
−4.68
−4.52
EGFR
cetuximab, AEE 788,



receptor





panitumumab, BMS-599626, ARRY-









334543, XL647, canertinib,









gefitinib, HKI-272, PD 153035,









lapatinib, vandetanib,









erlotinib


Ssc.19059.1.A1_at
Type-1 angiotensin II receptor
5.57
−2.57
1.50
−11.08
AGTR1
amlodipine/olmes artan



(AT1) (AT1AR





medoxomil,









losartan/hydrochlorothiazide,









valsartan/hydrochlorothiazide,









candesartan cilexetil,









olmesartan medoxomil,









irbesartan, losartan potassium,









telmisartan, eprosartan,









candesartan









cilexetil/hydrochlorothiazide,









hydrochlorothiazide/irbesartan,









eprosartan/hydrochlorothiazide,









hydrochlorothiazide/telmisartan,









hydrochlorothiazide/olmesartan









medoxomil, valsartan


Ssc.16162.1.S1_at
4-hydroxyphenylpyruvate
5.43
−8.93
−8.65
−3.84
HPD
nitisinone



dioxygenase


Ssc.27603.1.S1_at
Endothelin B receptor
5.30
−3.27
15.99
1.23
EDNRB
bosentan, sitaxsentan,









atrasentan


Ssc.16333.1.A1_at
Multidrug resistance protein 1
4.94
−2.99
−3.50
−22.89
ABCB1
XR9576, OC 144-093, valspodar


Ssc.12769.1.A1_at
Amiloride-sensitive cation
4.82
−13.74
−9.59
−10.72
ACCN1
amiloride,



channel 1, neuronal





amiloride/hydrochlorothiazide


Ssc.17155.1.A1_at
heparanase; heparanase-1
4.81
5.38
2.98
−1.83
HPSE
heparanase inhibitor PI-88


Ssc.15933.1.S1_s_at
Cytotoxic T-lymphocyte protein
4.76
−5.14
−6.63
−26.39
CTLA4
ipilimumab, ticilimumab



4 (Cytotoxic T-lymphocyte-



associated antigen 4) (CTLA-4)



(CD152 antigen)


Ssc.15965.1.S1_at
Inward rectifier potassium
4.68
2.72
−1.84
−4.62
KCNJ2
nicorandil, amiodarone



channel 2 (IRK1)


Ssc.26351.1.S1_at
cAMP-specific 3′,5′-cyclic
4.67
4.99
3.61
−1.15
PDE4D
dyphylline, nitroglycerin,



phosphodiesterase 4D





arofylline, tetomilast, L









869298, aminophylline,









anagrelide, cilomilast,









milrinone, rolipram,









dipyridamole, L-826, 141,









roflumilast, tolbutamide,









theophylline, pentoxifylline,









caffeine


Ssc.15990.1.A1_at
Retinoic acid receptor RXR-
4.42
−4.18
−18.45
−24.58
RXRA
bexarotene, retinoic acid, 9-



alpha





cis-retinoic acid


Ssc.2605.1.A1_at
Protein farnesyltransferase
4.39
−2.62
−7.00
−2.74
FNTB
lonafarnib, tipifarnib



beta


Ssc.30373.1.A1_at
cGMP-specific 3′,5′-cyclic
4.27
1.52
2.34
4.09
PDE5A
dyphylline, nitroglycerin, DA-



phosphodiesterase





8159, aminophylline,









sildenafil, dipyridamole,









aspirin/dipyridamole,









vardenafil, tolbutamide,









tadalafil, theophylline,









pentoxifylline


Ssc.19233.1.S1_at
Collagen alpha 2(IX) chain
4.23
−1.14
−22.83
−2.12
COL9A2
collagenase


Ssc.1147.1.A1_at
Lipoprotein lipase
4.05
−5.49
3.78
−8.08
LPL
nicotinic acid,









lovastatin/niacin


Ssc.13160.1.A1_at
Voltage-dependent L-type
4.03
−4.75
−1.11
−2.77
CACNA1F
MEM-1003, mibefradil,



calcium channel alpha-1F





bepridil, nisoldipine,



subunit





isradipine, nicardipine


Ssc.12748.1.A1_at
Catechol O-methyltransferase,
4.03
−3.20
−5.82
−21.93
COMT
carbidopa/entacapone/levodopa,



membrane-bound form





BIA-3-202, tolcapone,









entacapone


Ssc.24986.1.S1_at
Aldehyde dehydrogenase 1A1
4.00
−3.76
−2.17
−9.20
ALDH1A1
disulfiram, chlorpropamide


Ssc.15972.1.S1_at
Peroxisome proliferator
3.83
−1.07
−2.73
−1.60
PPARD
GW501516



activated receptor delta



(PPAR-delta)


Ssc.24509.1.A1_at
Gamma-aminobutyric-acid
3.76
−1.28
−1.98
−1.23
GABRP
alphadolone, sevoflurane,



receptor pi subunit





isoflurane, isoniazid,









felbamate, etomidate,









halothane,









fluoxetine/olanzapine,









eszopiclone, zolpidem,









lorazepam, olanzapine,









zaleplon, secobarbital,









phenobarbital, pentobarbital,









desflurane, methoxyflurane,









enflurane


Ssc.7176.1.A1_at
C-X-C chemokine receptor type
3.74
10.91
8.15
1.68
CXCR4
JM 3100



4 (CXC-R4) (


Ssc.6570.1.S1_at
Delta-aminolevulinic acid
3.71
−3.43
−3.05
−1.66
ALAD
delta-aminolevulinic acid



dehydratase]


Ssc.17485.1.S1_at
Guanylate cyclase soluble,
3.57
−38.82
−1.77
−7.04
GUCY1A2
nitroglycerin, isosorbide-5-



alpha-2 chain





mononitrate, isosorbide









dinitrate, nitroprusside,









isosorbide









dinit rate/hydralazine


Ssc.26200.1.S1_at
Thyroid hormone receptor beta-
3.49
−1.56
7.96
2.52
THRB
3,5-diiodothyropropionic acid,



1





amiodarone, thyroxine, L-









triiodothyronine


Ssc.9595.1.S1_at
Beta platelet-derived growth
3.48
−3.60
1.40
1.65
PDGFRB
dasatinib, sunitinib,



factor receptor





axitinib, KRN-951, imatinib,









sorafenib, becaplermin


Ssc.108.1.S1_at
Oxytocin receptor (OT-R)
3.44
−8.53
−16.69
−4.47
OXTR
TT-235


Ssc.15801.1.A1_at
Protein kinase C, beta
3.36
6.36
3.53
−4.98
PRKCB1
enzastaurin, ruboxistaurin


Ssc.27928.1.S1_at
Opioid growth factor receptor
3.34
−3.33
−2.89
−3.51
OGFR
enkephalin, methionine



(OGFr)


Ssc.12791.1.A1_at
3-hydroxy-3-methylglutaryl-
3.27
2.77
1.77
−2.56
HMGCR
aspirin/pravastatin,



coenzyme A reductase (HMG-CoA





lovastatin/niacin,



reductase





ezetimibe/simvastatin,









amlodipine/atorvastatin,









fluvastatin, cerivastatin,









atorvastatin, pravastatin,









simvastatin, lovastatin,









rosuvastatin


Ssc.7933.1.A1_at
Cell division protein kinase 8
3.26
−1.63
−1.78
−3.05
CDK8
flavopiridol


Ssc.11147.1.S1_at
Aldehyde dehydrogenase,
3.18
1.13
2.00
−1.68
ALDH2
disulfiram, chlorpropamide



mitochondrial (ALDH class 2)



(ALDHI) (ALDH-E2)


Ssc.19608.1.S1_at
Retinoic acid receptor RXR-
3.15
−1.39
−1.73
−3.97
RXRG
bexarotene, retinoic acid, 9-



gamma





cis-retinoic acid


Ssc.29260.1.A1_at
Granulocyte colony stimulating
3.15
−2.50
−4.36
−4.68
CSF3R
pegfilgrastim, filgrastim



factor receptor (G-CSF-R)



(CD114 antigen)]


Ssc.22797.1.S1_at
DNA topoisomerase II, beta
3.15
−1.87
1.02
−2.91
TOP2B
novobiocin, etoposide, CPI-



isozyme





0004Na, pixantrone,









becatecarin, elsamitrucin,









AQ4N, BN 80927, tafluposide,









mitoxantrone, norfloxacin,









dexrazoxane, tirapazamine, TAS-









103, XK469, gatifloxacin,









valrubicin, gemifloxacin,









moxifloxacin, nemorubicin,









nalidixic acid, epirubicin,









doxorubicin, daunorubicin


Ssc.16121.1.A1_at
Corticotropin releasing factor
3.03
−4.50
−17.00
−4.36
CRHR1
Crh, CRA0165, CRA1001,



receptor 1





SSR125543A


Ssc.12630.1.A1_at
Sodium/potassium-transporting
2.97
2.81
−7.30
−2.03
ATP1Al
digoxin, omeprazole,



ATPase alpha-1 chain





ethacrynic acid, perphenazine


Ssc.13254.1.A1_at
Metabotropic glutamate
2.95
−15.40
−9.66
−3.57
GRM8
fasoracetam



receptor 8


Ssc.30888.1.S1_at
Voltage-dependent L-type
2.92
−2.72
1.90
−7.82
CACNA1D
MEM-1003, mibefradil,



calcium channel alpha-1D





bepridil, nisoldipine,









isradipine, nicardipine


Ssc.9565.1.S1_at
Interferon-gamma receptor
2.92
1.63
1.41
−1.23
IFNGR1
interferon gamma-1b



alpha


Ssc.15880.1.S1_at
Cysteinyl leukotriene receptor
2.86
1.14
−2.12
−3.42
CYSLTR2
montelukast, zafirlukast



2 (CysLTR2)


Ssc.2753.1.S1_at
Serine/threonine-protein
2.77
−4.42
−7.50
−4.52
PLK1
BI 2536



kinase PLK1


Ssc.16123.1.A1_at
cAMP-specific 3′,5′-cyclic
2.75
−3.97
−3.49
−1.46
PDE4A
arofylline, tetomilast, L



phosphodiesterase 4A





869298, anagrelide, cilomilast,









milrinone, rolipram, L-826, 141,









amrinone, roflumilast,









pentoxifylline, caffeine


Ssc.11383.1.A1_at
Glutamate receptor 3
2.61
1.85
−1.87
−2.43
GRIA3
talampanel, Org 24448,









LY451395, tezampanel


Ssc.14403.1.S1_at
Sodium/potassium-transporting
2.61
−1.95
−8.51
−6.43
ATP1A2
digoxin, omeprazole,



ATPase alpha-2 chain





ethacrynic acid, perphenazine


Ssc.21754.1.A1_at
Collagen alpha 1(VI) chain
2.57
−47.00
−5.79
−4.37
COL6A1
collagenase


Ssc.6498.1.A1_at
Mitogen-activated protein
2.41
−10.79
−5.78
−3.26
MAPK12
SCIO-469



kinase 12 (Mitogen-activated



protein kinase p38 gamma)


Ssc.16167.1.S1_at
Rho-associated protein kinase
2.40
2.32
2.83
3.00
ROCK1
fasudil, Y-27632



1


Ssc.12781.1.A1_at
Toll-like receptor 4
2.39
1.83
−1.52
−6.10
TLR4
TAK-242


Ssc.29366.1.A1_at
DNA topoisomerase I
2.37
−2.30
−2.87
−10.72
TOP1
elsamitrucin, T 0128, CT-2106,









BN 80927, tafluposide, TAS-103,









beta-lapachone, irinotecan,









topotecan, 9-amino-20-









camptothecin, rubitecan,









gimatecan, karenitecin


Ssc.14485.1.S1_at
Parathyroid
2.28
−1.62
−3.40
−6.83
PTHR1
teriparatide



hormone/parathyroid hormone-



related peptide receptor


Ssc.12238.1.A1_at
Cysteinyl leukotriene receptor
2.28
−1.73
−1.34
−6.96
CYSLTR1
zeneca ZD 3523, montelukast,



1 (CysLTR1)





zafirlukast


Ssc.3607.1.S1_at
Interferon-alpha/beta receptor
2.28
4.65
1.11
−1.56
IFNAR2
interferon beta-1a, interferon



beta chain





alfa-2b, interferon alfacon-1,









PEG-interferon alfa-2a,









interferon alfa-2a/ribavirin,









pegintron, interferon beta-1b,









IFNA2A


Ssc.2548.1.S1_at
DNA polymerase epsilon p17]
2.27
1.93
−1.67
−1.21
POLE3
gemcitabine


Ssc.19706.1.A1_at
Mitogen-activated protein
2.25
−4.27
−2.31
−4.98
MAPK8
aplidine



kinase 8


Ssc.15382.1.S1_at
Cannabinoid receptor 2 (CB2)
2.22
3.48
−1.37
−4.69
CNR2
BAY 38-7271, delta-9-



(CB-2) (CX5)





tetrahydrocannabinol


Ssc.4756.1.A1_at
Adenosine A3 receptor
2.15
2.10
1.88
−1.81
ADORA3
adenosine, dyphylline,









aminophylline, clofarabine,









theophylline, caffeine


Ssc.23261.1.A1_at
Trifunctional purine
2.15
−3.54
−3.66
−5.67
GART
LY231514



biosynthetic protein



adenosine-3


Ssc.27293.1.A1_at
Hypoxanthine-guanine
2.15
−1.16
1.63
−7.14
HPRT1
6-mercaptopurine, thioguanine,



phosphoribosyltransferase





azathioprine


Ssc.14476.1.S1_at
Interleukin-2 receptor alpha
2.07
−8.52
−8.73
−5.00
IL2RA
LMB-2, daclizumab,









basiliximab, aldesleukin,









denileukin diftitox


Ssc.27232.1.S1_at
Succinate semialdehyde
2.06
1.12
−2.84
−5.73
ALDH5A1
valproic acid



dehydrogenase, mitochondrial


Ssc.10142.1.A1_at
Dihydropyrimidine
2.06
2.17
1.13
−2.68
DPYD
eniluracil



dehydrogenase [NADP+]


Ssc.1908.1.S1_at
FKBP-rapamycin associated
1.99
1.13
−1.88
−1.46
FRAP1
AP23573, temsirolimus,



protein (FRAP)





tacrolimus, everolimus


Ssc.204.1.S1_at
Cytochrome P450 3A4
1.97
−3.35
2.16
−1.42
CYP3A4
ketoconazole


Ssc.18459.1.S1_at
Amiloride-sensitive sodium
1.97
−2.41
1.43
−1.93
SCNN1A
triamterene/hydrochlorothiazide,



channel alpha-





amiloride,









amiloride/hydrochlorothiazide,









triamterene


Ssc.24889.1.S1_at
Arachidonate 12-lipoxygenase,
1.97
2.83
−1.18
−2.78
ALOX12
sulfasalazine, balsalazide, 5-



12S-type





aminosalicylic acid,









masoprocol, verteporfin


Ssc.15748.2.S2_at
T lymphocyte activation
1.95
−1.24
1.54
−3.12
CD80
abatacept



antigen CD80


Ssc.5826.1.A1_at
Macrophage colony stimulating
1.93
−4.97
−13.18
1.61
CSF1R
sunitinib



factor I receptor (CD115



antigen)


Ssc.15822.1.S1_at
Coagulation factor V
1.92
3.76
1.89
−1.75
F5
drotrecogin alfa


Ssc.9262.1.A1_at
Histamine H1 receptor
1.91
−4.10
−3.91
−1.86
HRH1
nitisinone


Ssc.62.2.S1_a_at
Interleukin-6 (IL-6) (
1.89
−6.32
2.77
−1.04
IL6
tocilizumab


Ssc.14258.1.S1_at
Amyloid beta A4 protein
1.87
3.33
1.34
−1.02
APP
AAB-001


Ssc.15878.1.S1_at
Serine/threonine protein
1.85
3.22
3.62
−1.49
PPP3CA
ISAtx-247, tacrolimus,



phosphatase 2B





pimecrolimus, cyclosporin A


Ssc.19379.1.A1_at
Voltage-dependent L-type
1.83
−1.34
1.07
−3.27
CACNA1C
clevidipine, MEM-1003,



calcium channel alpha-1C





amlodipine/olmesartan



subunit





medoxomil,









amlodipine/benazepril,









diltiazem, verapamil,









mibefradil, bepridil,









enalapril/felodipine,









amlodipine/atorvastatin,









nisoldipine, isradipine,









felodipine, nimodipine,









nitrendipine, amlodipine,









nicardipine, nifedipine,









trandolapril/verapamil,









diltiazem/enalapril


Ssc.10215.1.A1_at
High-affinity cAMP-specific
1.83
1.12
−8.48
−15.51
PDE8A
dyphylline, nitroglycerin,



and IBMX-insensitive 3′,5′-





aminophylline, anagrelide,



cyclic phosphodiesterase 8A





milrinone, dipyridamole,









tolbutamide, theophylline,









pentoxifylline


Ssc.20944.1.S1_at
Carbonic anhydrase XIV
1.82
−3.49
−5.34
−12.64
CA14
methazolamide,









hydrochlorothiazide,









acetazolamide,









trichloromethiazide,









chlorothiazide, chlorthalidone,









benzthiazide, sulfacetamide,









topiramate


Ssc.4125.1.A1_at
Histone deacetylase 5 (HD5)
1.82
−4.64
−4.18
−2.74
HDAC5
tributyrin, PXD101,









pyroxamide, vorinostat, FR









901228


Ssc.9272.1.S1_at
Tumor-associated calcium
1.81
3.94
176.50
2.07
TACSTD1
tucotuzumab celmoleukin



signal transducer 1 (EPCAM



antigen)


Ssc.6301.1.S1_at
Aromatic-L-amino-acid
1.76
1.80
−4.91
−1.88
DDC
carbidopa/entacapone/levodopa,



decarboxylase





carbidopa/levodopa, S(−)-









carbidopa, L-dopa


Ssc.15995.1.S1_at
Potassium voltage-gated
1.74
−26.30
−13.45
−2.79
KCNE1
nicorandil, amiodarone,



channel subfamily E member 1





azimilide


Ssc.7581.1.A1_at
FL cytokine receptor precursor
1.69
1.04
−1.81
1.01
FLT3
CHIR-258, sorafenib,









lestaurtinib, CGP 41251


Ssc.26325.1.S1_at
Cystic fibrosis transmembrane
1.60
−5.71
4.77
−8.99
CFTR
SP 303



conductance regulator (CFTR)


Ssc.19691.1.S1_at
Platelet-activating factor
1.59
1.16
3.01
1.47
PLA2 G7
darapladib



acetylhydrolase


Ssc.24714.1.A1_at
Excitatory amino acid
1.58
−2.29
−7.61
−3.45
SLC1A2
riluzole



transporter 2 (Sodium-



dependent glutamate/aspartate



transporter 2)


Ssc.22477.1.S1_at
Collagen alpha 1(IV) chain
1.58
−5.08
−1.78
1.04
COL4A1
collagenase


Ssc.227.1.S1_at
Potassium-transporting ATPase
1.56
−5.89
−51.53
−15.60
ATP4B
ilaprazole, TAK-390MR,



beta





tenatoprazole, AGN 201904, AR-









H047108, esomeprazole









magnesium, omeprazole,









lansoprazole,









amoxicillin/clarithromycin/lans









oprazole, rabeprazole,









pantoprazole


Ssc.30147.1.A1_at
Fibroblast growth factor
1.56
1.13
−1.05
−1.18
FGFR2
palifermin



receptor 2


Ssc.9523.1.A1_at
Methylated-DNA--protein-
1.55
−1.17
3.35
1.47
MGMT
O6-benzylguanine



cysteine methyltransferase


Ssc.26466.1.A1_at
Integrin beta-3 (CD61 antigen
1.55
−1.49
−4.11
−2.73
ITGB3
TP 9201, EMD121974, tirofiban


Ssc.5592.1.S1_at
Protein
1.49
−3.49
−2.81
−3.68
FNTA
lonafarnib, tipifarnib



famesyltransferase/geranylger



anyltransferase type I alpha


Ssc.17986.1.A1_at
Poly [ADP-ribose] polymerase-1
1.47
−6.14
−4.64
−5.80
PARP1
INO-1001


Ssc.11051.1.S1_at
Cell division protein kinase 4
1.44
−7.67
−4.96
23.75
CDK4
PD-0332991, flavopiridol


Ssc.20818.1.S1_at
Interleukin-2 receptor beta
1.43
6.35
−1.17
−5.23
IL2RB
humanized MiK-Beta-1,



chain





aldesleukin, denileukin









diftitox


Ssc.16489.1.S1_at
Interleukin-7 receptor alpha
1.42
2.34
1.86
−6.31
IL7R
recombinant human interleukin-



chain





7


Ssc.10287.1.A1_at
Transforming growth factor
1.41
−4.54
1.43
1.67
TGFB2
AP-12009



beta 2


Ssc.14375.1.A1_at
ribonucleotide reductase M2 B
1.40
−2.19
−5.17
−2.28
RRM2B
triapine, hydroxyurea


Ssc.16823.1.S1_at
P2Y purinoceptor 12 (P2Y12)
1.38
1.19
1.41
1.11
P2RY12
prasugrel, AZD 6140



(P2Y12 platelet ADP receptor)





(Ticagrelor), clopidogrel



(P2Y(ADP))


Ssc.11164.1.A1_at
DNA polymerase gamma subunit 1
1.37
−1.33
−3.67
−3.60
POLG
stavudine, vidarabine,









zalcitabine


Ssc.10219.1.A1_at
Excitatory amino acid
1.36
1.24
−3.38
−1.03
SLC1A6
riluzole



transporter 4


Ssc.3815.1.S1_at
RAC-beta serine/threonine-
1.35
−3.13
−3.28
−3.19
AKT2
enzastaurin



protein kinase


Ssc.19619.1.S1_at
Proto-oncogene tyrosine-
1.35
−1.51
−3.32
−2.41
LCK
dasatinib



protein kinase LCK


Ssc.2926.1.S1_at
Heme oxygenase 2
1.34
−1.43
−4.13
−1.81
HMOX2
tin mesoporphyrin


Ssc.11171.1.S1_at
Adenosine deaminase
1.32
−2.04
−3.23
1.12
ADA
pentostatin, vidarabine


Ssc.16621.1.A1_at
Excitatory amino acid
1.27
−7.18
−3.04
−8.29
SLC1A1
riluzole



transporter 3


Ssc.11549.1.A1_at
Dual specificity mitogen-
1.25
−33.67
−11.33
−6.48
MAP2K1
PD 0325901



activated protein kinase



kinase 1


Ssc.6356.1.S1_at
Ornithine decarboxylase
1.24
−1.36
−1.74
−1.84
ODC1
tazarotene, eflornithine


Ssc.15999.1.A1_at
Vascular endothelial growth
1.24
1.24
18.52
−11.02
KDR
AEE 788 , sunitinib, AZD 2171,



factor receptor 2 (VEGFR-2)





pazopanib, XL647, CEP 7055,









BMS-582664, KRN-951, vatalanib,









sorafenib, vandetanib,









pegaptanib


Ssc.9669.1.S1_at
Cell division protein kinase 5
1.21
−2.68
−17.06
−1.65
CDK5
flavopiridol


Ssc.115.1.S1_s_at
Heme oxygenase 1
1.18
−2.09
−3.40
−3.55
HMOX1
tin mesoporphyrin


Ssc.17224.1.S1_at
Toll-like receptor 8
1.17
6.49
3.13
−1.52
TLR8
resiquimod


Ssc.8046.1.A1_at
peptidylprolyl isomerase A
1.16
−1.08
1.39
1.26
PPIA
N-methyl-4-Ile-cyclosporin



isoform 1


Ssc.7297.1.S1_at
Amine oxidase [flavin-
1.16
6.42
7.02
−1.13
MAOB
safinamide, ladostigil,



containing] B (MAO-B)





rasagiline, selegiline,









dextroamphetamine,









procainamide, tranylcypromine,









phenelzine, isocarboxazid,









benzphetamine


Ssc.28329.1.S1_at
DNA polymerase beta
1.14
1.19
1.07
5.25
POLB
nelarabine, clofarabine,









stavudine, trifluridine,









vidarabine, zalcitabine,









entecavir


Ssc.12202.2.S1_at
Farnesyl pyrophosphate
1.12
−1.26
−2.68
−1.13
FDPS
YM 529, alendronic acid,



synthetase





pamidronic acid


Ssc.19700.1.S1_at
Serine/threonine protein
1.11
1.13
1.34
1.09
PPP3CB
ISAtx-247, tacrolimus,



phosphatase 2B catalytic





pimecrolimus, cyclosporin A



subunit, beta


Ssc. 8549.1.A1_at
Guanylate cyclase soluble,
1.11
1.84
−2.00
−2.59
GUCY1A3
nitroglycerin, isosorbide-5-



alpha-3 chain





mononitrate, isosorbide









dinitrate, nitroprusside,









isosorbide









dinitrate/hydralazine


Ssc.15374.1.S1_at
COL14A1 protein
1.10
−17.71
3.79
2.24
COL14A1
collagenase


Ssc.15901.1.S1_at
cGMP-inhibited 3′,5′-cyclic
1.10
−13.33
−3.16
−1.41
PDE3A
dyphylline, nitroglycerin,



phosphodiesterase A





medorinone, aminophylline,









cilostazol, dipyridamole,









amrinone, tolbutamide,









theophylline, pentoxifylline


Ssc.16000.1.A1_at
Vascular endothelial growth
1.08
−3.40
3.34
1.72
FLT1
sunitinib, axitinib, CEP 7055



factor receptor 1


Ssc.20987.1.S1_at
Thrombopoietin receptor]
1.06
−1.58
−3.97
−5.87
MPL
SB-497115


Ssc.11149.1.S1_at
Carbonic anhydrase IX
1.04
−1.91
−1.33
−1.26
CA9
cG250, I 131 chimeric G250, Y









90 chimeric G250,









methazolamide,









hydrochlorothiazide,









acetazolamide,









trichloromethiazide,









chlorothiazide, chlorthalidone,









benzthiazide, sulfacetamide,









topiramate


Ssc.8726.1.A1_at
Amidophosphoribosyltransferase
1.03
1.24
4.16
−1.11
PPAT
6-mercaptopurine, thioguanine,









azathioprine


Ssc.11406.1.A1_a_at
Interleukin-1 receptor, type I
1.03
2.70
−2.44
1.42
IL1R1
anakinra


Ssc.14506.1.S1_at
DNA topoisomerase II, alpha
1.01
3.80
−1.18
−14.30
TOP2A
novobiocin, etoposide, CPI-









0004Na, pixantrone,









becatecarin, elsamitrucin,









AQ4N, BN 80927, tafluposide,









mitoxantrone, norfloxacin,









dexrazoxane, tirapazamine, TAS-









103, gatifloxacin, valrubicin,









gemifloxacin, moxifloxacin,









nemorubicin, nalidixic acid,









epirubicin, doxorubicin,









daunorubicin
















TABLE 4







Day 21 prescription.
















Fold
Fold
Fold
Fold






Change
Change
Change
Change




D 7/
D 21/
D 60/
D 180/
Gene


Probe ID
Name
Base
Base
Base
Base
Symbol
Drugs

















Ssc.23793.1.S1_at
T-cell surface antigen CD2
−3.27
79.25
93.34
5.20
CD2
alefacept, siplizumab


SscAffx.20.1.S1_at
T-cell surface glycoprotein
−2.19
14.07
10.96
3.62
CD3G
visilizumab, MT103



CD3 gamma chain


Ssc.19532.1.S1_at
Guanylate cyclase soluble,
−4.28
12.74
3.04
2.13
GUCY1B3
nitroglycerin, isosorbide-5-



beta-1 chain





mononitrate, isosorbide









dinitrate, nitroprusside,









isosorbide









dinitrate/hydralazine


Ssc.7176.1.A1_at
C-X-C chemokine receptor type
3.74
10.91
8.15
1.68
CXCR4
JM 3100



4 (CXC-R4) (CXCR-4) (CD184



antigen).


Ssc.2714.1.S1_a_at
Proto-oncogene tyrosine-
−4.26
9.56
12.54
3.93
FYN
dasatinib



protein kinase FYN


Ssc.15739.1.S1_at
Cytokine receptor common gamma
−1.12
9.42
1.90
−1.28
IL2RG
aldesleukin, denileukin



chain (Interleukin- 2





diftitox



receptor gamma chain) (IL-2R



gamma chain) (CD132 antigen).


Ssc.11381.1.S1_at
Interferon-alpha/beta receptor
10.45
8.08
2.61
−1.30
IFNAR1
interferon beta-1a, interferon



alpha chain





alfa-2b, interferon alfacon-1,









PEG-interferon alfa-2a,









interferon alfa-2a/ribavirin,









pegintron, interferon beta-1b,









IFNA2A


Ssc.10256.1.A1_at
cAMP-specific 3′,5′-cyclic
−1.89
6.74
2.20
2.44
PDE4B
dyphylline, nitroglycerin,



phosphodiesterase 4B





arofylline, tetomilast, L









869298, aminophylline,









anagrelide, cilomilast,









milrinone, rolipram,









dipyridamole, L-826, 141,









roflumilast, tolbutamide,









theophylline, pentoxifylline,









caffeine


Ssc.17224.1.S1_at
Toll-like receptor 8
1.17
6.49
3.13
−1.52
TLR8
resiquimod


Ssc.7297.1.S1_at
Amine oxidase [flavin-
1.16
6.42
7.02
−1.13
MAOB
safinamide, ladostigil,



containing] B (Monoamine





rasagiline, selegiline,



oxidase) (MAO-B).





dextroamphetamine,









procainamide, tranylcypromine,









phenelzine, isocarboxazid,









benzphetamine


Ssc.15801.1.A1_at
Protein kinase C, beta
3.36
6.36
3.53
−4.98
PRKCB1
enzastaurin, ruboxistaurin


Ssc.20818.1.S1_at
Interleukin-2 receptor beta
1.43
6.35
−1.17
−5.23
IL2RB
humanized MiK-Beta-1,



chain (IL-2 receptor)





aldesleukin, denileukin









diftitox


Ssc.12937.1.S1_at
Presenilin 1 (PS-1) (S182
−14.09
6.21
2.48
3.79
PSEN1
(R)-flurbiprofen



protein).


Ssc.15932.1.S1_at
Integrin alpha-V
−6.15
5.79
2.94
3.14
ITGAV
abciximab, CNTO 95, EMD121974


Ssc.26328.1.S1_at
C-C chemokine receptor type 5
−2.53
5.61
3.25
1.29
CCR5
maraviroc, vicriviroc, SCH



(CCR5) (CD195 antigen).





351125


Ssc.12845.1.S1_at
Cell division protein kinase 6
−6.56
5.40
4.77
5.13
CDK6
PD-0332991, flavopiridol


Ssc.17155.1.A1_at
heparanase; heparanase-1
4.81
5.38
2.98
−1.83
HPSE
heparanase inhibitor PI-88


Ssc.13460.1.A1_at
Histone deacetylase 9 (HD9)
−6.40
5.13
−1.79
5.72
HDAC9
tributyrin, PXD101,



(HD7B) (HD7)





pyroxamide, vorinostat, FR









901228


Ssc.24528.1.S1_at
Angiotensin-converting enzyme
−1.61
5.01
2.33
4.76
ACE
pentopril, perindoprilat,









amlodipine/benazepril,









lisinopril/hydrochlorothiazide,









benazepril, enalapril,









perindopril, captopril,









enalapril/felodipine,









hydrochlorothiazide/moexipril,









benazepril/hydrochlorothiazide,









hydrochlorothiazide/quinapril,









fosinopril/hydrochlorothiazide,









captopril/hydrochlorothiazide,









enalapril/hydrochlorothiazide,









ramipril, moexipril, quinapril,









lisinopril, enalaprilat,









trandolapril,









trandolapril/verapamil,









diltiazem/enalapril, fosinopril


Ssc.26351.1.S1_at
cAMP-specific 3′,5′-cyclic
4.67
4.99
3.61
−1.15
PDE4D
dyphylline, nitroglycerin,



phosphodiesterase 4D





arofylline, tetomilast, L









869298, aminophylline,









anagrelide, cilomilast,









milrinone, rolipram,









dipyridamole, L-826,141,









roflumilast, tolbutamide,









theophylline, pentoxifylline,









caffeine


Ssc.15601.1.A1_s_at
Interleukin-1 beta precursor
8.18
4.65
−14.71
−2.84
IL1B
IL-1 trap



(IL-1 beta)


Ssc.3607.1.S1_at
Interferon-alpha/beta receptor
2.28
4.65
1.11
−1.56
IFNAR2
interferon beta-1a, interferon



beta chain





alfa-2b, interferon alfacon-1,









PEG-interferon alfa-2a,









interferon alfa-2a/ribavirin,









pegintron, interferon beta-1b,









IFNA2A


Ssc.20841.1.S1_at
Proto-oncogene tyrosine-
−1.13
4.37
−2.59
−1.93
SRC
dasatinib, AZM-475271



protein kinase Src


Ssc.11200.1.S1_a_at
Proto-oncogene tyrosine-
−1.15
4.28
−3.41
−1.18
ABL1
imatinib, temozolomide



protein kinase ABL1


Ssc.22974.1.A1_at
Metabotropic glutamate
−1.05
4.28
−2.05
−5.66
GRM1
fasoracetam



receptor 1


Ssc.7111.1.A1_at
Ribonucleoside-diphosphate
−13.13
4.08
1.37
1.67
RRM2
gemcitabine, triapine,



reductase M2 chain





hydroxyurea, fludarabine



(Ribonucleotide reductase





phosphate



small chain)


Ssc.9272.1.S1_at
Tumor-associated calcium
1.81
3.94
176.50
2.07
TACSTD1
tucotuzumab celmoleukin



signal transducer 1 (EPCAM



antigen)


Ssc.16160.1.S1_at
T lymphocyte activation
−1.55
3.88
−1.37
1.18
CD86
abatacept



antigen CD86


Ssc.14506.1.S1_at
DNA topoisomerase II, alpha
1.01
3.80
−1.18
−14.30
TOP2A
novobiocin, etoposide, CPI-



isozyme





0004Na, pixantrone,









becatecarin, elsamitrucin,









AQ4N, BN 80927, tafluposide,









mitoxantrone, norfloxacin,









dexrazoxane, tirapazamine, TAS-









103, gatifloxacin, valrubicin,









gemifloxacin, moxifloxacin,









nemorubicin, nalidixic acid,









epirubicin, doxorubicin,









daunorubicin


Ssc.15822.1.S1_at
Coagulation factor V
1.92
3.76
1.89
−1.75
F5
drotrecogin alfa



(Activated protein C



cofactor).


Ssc.9034.1.A1_at
Proteinase activated receptor
−1.29
3.75
−1.40
1.37
F2R
chrysalin, argatroban,



1 precursor (PAR-1) (Thrombin





bivalirudin



receptor)


Ssc.15886.1.S1_at
Apopain precursor (Caspase-3)
−3.02
3.64
2.31
2.29
CASP3
IDN-6556



(CASP-3)


Ssc.17518.1.S1_at
Adenosine A1 receptor
−3.16
3.44
−1.56
1.58
ADORA1
adenosine, dyphylline,









aminophylline, clofarabine,









theophylline, caffeine,









tecadenoson


Ssc.14258.1.S1_at
Amyloid beta A4 protein
1.87
3.33
1.34
−1.02
APP
AAB-001



precursor (APP) (ABPP)


Ssc.14471.1.S1_at
B-lymphocyte antigen CD19
9.54
3.30
−10.32
3.04
CD19
combotox, HD37-dgRTA, MT103



precursor (Differentiation



antigen CD19


Ssc.15878.1.S1_at
Serine/threonine protein
1.85
3.22
3.62
−1.49
PPP3CA
ISAtx-247, tacrolimus,



phosphatase 2B catalytic





pimecrolimus, cyclosporin A



subunit, alpha


Ssc.21108.1.S1_at
Complement C5
−17.35
3.21
618.80
9.28
C5
eculizumab


Ssc.16186.1.S1_at
T-cell surface glycoprotein
9.00
3.12
2.12
−5.66
CD3E
visilizumab, MT103, muromonab-



CD3 epsilon chain (T-cell





CD3



surface antigen T3/Leu-4



epsilon chain)


Ssc.24966.1.S1_at
Purine nucleoside
−3.34
3.12
3.46
−1.14
NP
forodesine, 9-deaza-9-(3-



phosphorylase (Inosine





thienylmethyl)guanine



phosphorylase) (PNP).


Ssc.19873.1.S1_at
Collagen alpha 1(XVII) chain
−2.37
3.02
−1.55
2.18
COL17A1
collagenase



(Bullous pemphigoid antigen 2)


Ssc.20904.1.A1_at
RAC-gamma serine/threonine-
−1.34
3.01
−2.18
1.23
AKT3
enzastaurin



protein kinase (RAC-PK-gamma)



(Protein kinase Akt-3)



(Protein kinase B, gamma) (PKB



gamma) (STK-2)


Ssc.26646.1.S1_at
Glutamate receptor 1
−1.10
2.91
−5.42
−3.43
GRIA1
talampanel, Org 24448,









LY451395, tezampanel


Ssc.15312.1.S1_at
Histone deacetylase 4 (HD4)
−1.93
2.85
−2.41
1.20
HDAC4
tributyrin, PXD101,









pyroxamide, vorinostat, FR









901228


Ssc.24889.1.S1_at
Arachidonate 12-lipoxygenase,
1.97
2.83
−1.18
−2.78
ALOX12
sulfasalazine, balsalazide, 5-



12S-type





aminosalicylic acid,









masoprocol, verteporfin


Ssc.12630.1.A1_at
Sodium/potassium-transporting
2.97
2.81
−7.30
−2.03
ATP1A1
digoxin, omeprazole,



ATPase alpha-1 chain





ethacrynic acid, perphenazine


Ssc.3040.1.S1_at
Histone deacetylase 2 (HD2)
−3.24
2.79
4.94
4.72
HDAC2
tributyrin, PXD101,









pyroxamide, vorinostat, FR









901228


Ssc.12791.1.A1_at
3-hydroxy-3-methylglutaryl-
3.27
2.77
1.77
−2.56
HMGCR
aspirin/pravastatin,



coenzyme A reductase (HMG-CoA





lovastatin/niacin,



reductase)





ezetimibe/simvastatin,









amlodipine/atorvastatin,









fluvastatin, cerivastatin,









atorvastatin, pravastatin,









simvastatin, lovastatin,









rosuvastatin


Ssc.20685.1.S1_at
Apoptosis regulator Bcl-2
−2.22
2.77
2.58
3.25
BCL2
oblimersen, (−)-gossypol


Ssc.15965.1.S1_at
Inward rectifier potassium
4.68
2.72
−1.84
−4.62
KCNJ2
nicorandil, amiodarone



channel 2 (Potassium channel,



inwardly rectifying, subfamily



J, member 2) (Inward rectifier



K+ channel Kir2.1) (Cardiac



inward rectifier potassium



channel) (IRK1).


Ssc.19673.1.S1_at
T-cell surface glycoprotein
6.40
2.70
2.03
−11.77
CD3D
visilizumab, MT103



CD3 delta chain precursor (T-



cell receptor T3 delta chain)


Ssc.16127.1.S1_at
Adrenocorticotropic hormone
−1.67
2.70
−2.51
−1.10
MC2R
cosyntropin, ACTH



receptor (ACTH receptor)



(ACTH-R)


Ssc.11406.1.A1_a_at
Interleukin-1 receptor, type I
1.03
2.70
−2.44
1.42
IL1R1
anakinra



precursor (IL-1R-1) (IL-1R-



alpha) (P80) (Antigen CD121a)


Ssc.19937.1.S1_at
Inosine-5′-monophosphate
1.00
2.69
−1.47
3.65
IMPDH2
thioguanine, VX-944,



dehydrogenase 2 (IMP





interferon alfa-2a/ribavirin,



dehydrogenase 2)





mycophenolic acid, ribavirin


Ssc.818.1.S1_at
RAF proto-oncogene
−1.40
2.56
1.58
1.98
RAF1
sorafenib



serine/threonine-protein



kinase


Ssc.14129.1.A1_at
4-aminobutyrate aminotransferase,
6.91
2.56
−21.17
−3.35
ABAT
valproic acid



mitochondrial precursor



(Gamma-amino-N-butyrate



transaminase) (GABA



transaminase)


Ssc.13186.1.S1_at
Cell division protein kinase 7
−1.08
2.38
4.34
1.24
CDK7
BMS-387032, flavopiridol


Ssc.16167.1.S1_at
Rho-associated protein kinase
2.40
2.32
2.83
3.00
ROCK1
fasudil, Y-27632



1


Ssc.6418.1.S1_at
Farnesyl-diphosphate
−1.25
2.31
1.33
1.08
FDFT1
TAK-475, zoledronic acid



farnesyltransferase


Ssc.15829.1.S1_at
Retinoic acid receptor alpha
−1.73
2.23
−1.33
−1.16
RARA
etretinate, adapalene, arsenic









trioxide, 13-cis-retinoic acid,









tazarotene, acitretin, retinoic









acid, 9-cis-retinoic acid


Ssc.10142.1.A1_at
Dihydropyrimidine
2.06
2.17
1.13
−2.68
DPYD
eniluracil



dehydrogenase [NADP+] (DPD)



(DHPDHase) (Dihydrouracil



dehydrogenase) (Dihydrothymine



dehydrogenase).


Ssc.23505.1.S1_at
Amine oxidase [flavin-
−1.86
2.17
1.08
1.20
MAOA
ladostigil, 1-



containing] A (Monoamine





ethylphenoxathiin 10,10-



oxidase) (MAO-A)





dioxide, dextroamphetamine,









procainamide, tranylcypromine,









phenelzine, isocarboxazid,









benzphetamine, N-(2-









indanyl)glycinamide


Ssc.20438.1.S1_at
Prostaglandin F2-alpha
−3.20
2.13
5.28
−38.97
PTGFR
tafluprost, travoprost,



receptor (Prostanoid FP





isopropyl unoprostone,



receptor) (PGF receptor) (PGF2





bimatoprost, latanoprost



alpha receptor).


Ssc.4756.1.A1_at
Adenosine A3 receptor
2.15
2.10
1.88
−1.81
ADORA3
adenosine, dyphylline,









aminophylline, clofarabine,









theophylline, caffeine


Ssc.11302.1.S1_at
Collagen alpha 1(III) chain
−1.80
2.02
2.06
1.26
COL3A1
collagenase


Ssc.19400.2.A1_at
Presenilin 2 (PS-2) (STM-2)
−2.32
1.99
−5.30
−3.44
PSEN2
(R)-flurbiprofen



(E5-1) (AD3LP) (AD5)


Ssc.3059.1.S1_at
Aldose reductase (AR)
−1.74
1.98
−1.66
2.49
AKR1B1
sorbinil, Zopolrestat (Alond,



(Aldehyde reductase).





Pfizer), zenarestat (Fujisawa,









Parke-Davis)


Ssc.18051.1.S1_at
cGMP-inhibited 3′,5′-cyclic
−3.16
1.96
3.41
2.32
PDE3B
dyphylline, nitroglycerin,



phosphodiesterase B (Cyclic





medorinone, aminophylline,



GMP inhibited





cilostazol, dipyridamole,



phosphodiesterase B) (CGI-PDE





amrinone, tolbutamide,



B) (CGIPDE1) (CGIP1)





theophylline, pentoxifylline


Ssc.2548.1.S1_at
DNA polymerase epsilon p17
2.27
1.93
−1.67
−1.21
POLE3
gemcitabine



subunit (DNA polymerase



epsilon subunit 3) (Chromatin



accessibility complex 17)



(HuCHRAC17) (CHRAC-17).


Ssc.11383.1.A1_at
Glutamate receptor 3 precursor
2.61
1.85
−1.87
−2.43
GRIA3
talampanel, Org 24448,



(GluR-3) (GluR-C) (GluR-K3)





LY451395, tezampanel



(Glutamate receptor



ionotropic, AMPA 3)


Ssc.8549.1.A1_at
Guanylate cyclase soluble,
1.11
1.84
−2.00
−2.59
GUCY1A3
nitroglycerin, isosorbide-5-



alpha-3 chain (GCS-alpha-3)





mononitrate, isosorbide



(Soluble guanylate cyclase





dinitrate, nitroprusside,



large subunit) (GCS-alpha-1).





isosorbide









dinitrate/hydralazine


Ssc.12781.1.A1_at
Toll-like receptor 4
2.39
1.83
−1.52
−6.10
TLR4
TAK-242


Ssc.6301.1.S1_at
Aromatic-L-amino-acid
1.76
1.80
−4.91
−1.88
DDC
carbidopa/entacapone/levodopa,



decarboxylase (AADC) (DOPA





carbidopa/levodopa, S(−)-



decarboxylase)





carbidopa, L-dopa


Ssc.6801.1.S1_at
Proto-oncogene tyrosine-
−1.06
1.69
2.36
−1.82
YES1
dasatinib



protein kinase YES


Ssc.5371.1.S1_a_at
DNA polymerase epsilon subunit
10.16
1.68
−1.37
−3.14
POLE2
gemcitabine



B (DNA polymerase II subunit B).


Ssc.11572.1.A1_at
Histone deacetylase 3 (HD3)
−1.65
1.67
−1.55
2.36
HDAC3
tributyrin, PXD101,



(RPD3-2) (SMAP45)





pyroxamide, MGCD0103,









vorinostat, FR 901228


Ssc.23234.1.S1_at
collagen, type XXIV, alpha 1
−1.43
1.66
1.16
1.76
COL24A1
collagenase


Ssc.9565.1.S1_at
Interferon-gamma receptor
2.92
1.63
1.41
−1.23
IFNGR1
interferon gamma-1b



alpha chain precursor (IFN-



gamma-R1) (CD119 antigen)


Ssc.5021.1.S1_at
Glutamate decarboxylase, 65
−29.44
1.62
−10.79
−5.61
GAD2
valproic acid



kDa isoform (GAD-65) (65 kDa



glutamic acid decarboxylase)


Ssc.14326.1.A1_at
Mitogen-activated protein
12.63
1.56
−1.80
−7.24
MAPK13
SCIO-469



kinase 13 (Stress-activated



protein kinase-4) (Mitogen-



activated protein kinase p38



delta) (MAP kinase p38 delta)


Ssc.10591.1.A1_at
Metabotropic glutamate
−7.83
1.54
−1.31
1.40
GRM5
fasoracetam



receptor 5 precursor (mGluR5)


Ssc.30373.1.A1_at
cGMP-specific 3′,5′-cyclic
4.27
1.52
2.34
4.09
PDE5A
dyphylline, nitroglycerin, DA-



phosphodiesterase





8159, aminophylline,









sildenafil, dipyridamole,









aspirin/dipyridamole,









vardenafil, tolbutamide,









tadalafil, theophylline,









pentoxifylline


Ssc.6710.1.A1_at
Ribonucleoside-diphosphate
−1.90
1.44
2.01
−1.01
RRM1
gemcitabine, clofarabine,



reductase M1 chain





fludarabine phosphate



(Ribonucleotide reductase



large chain)


Ssc.7139.1.S1_at
Dihydrofolate reductase
−1.13
1.41
−1.12
2.06
DHFR
pyrimethamine, trimethoprim,









iclaprim, methotrexate,









sulfisoxazole, triamterene,









folic acid, trimetrexate,









LY231514, PT 523


Ssc.5538.1.S1_at
Carbonic anhydrase II
8.09
1.39
−2.25
−1.35
CA2
methazolamide,



(Carbonate dehydratase II)





hydrochlorothiazide,



(CA-II) (Carbonic anhydrase C)





acetazolamide,









trichloromethiazide,









dorzolamide, chlorothiazide,









dorzolamide/timolol,









brinzolamide, chlorthalidone,









benzthiazide, sulfacetamide,









topiramate


Ssc.5569.1.S1_at
Thyroid hormone receptor alpha
−10.22
1.26
1.26
6.49
THRA
3,5-diiodothyropropionic acid,



(C-erbA-alpha) (c-erbA-1)





amiodarone, thyroxine, L-



(EAR-7) (EAR7)





triiodothyronine


Ssc.10360.1.S1_at
B-Raf proto-oncogene
−2.15
1.26
3.09
1.36
BRAF
sorafenib



serine/threonine-protein



kinase


Ssc.19672.1.S1_at
RAC-alpha serine/threonine-
17.77
1.25
−19.82
−2.11
AKT1
enzastaurin



protein kinase (RAC-PK-alpha)



(Protein kinase B) (PKB) (C-



AKT)


Ssc.21011.1.S1_at
Collagen alpha 2(I) chain
−2.70
1.24
3.12
−1.01
COL1A2
collagenase


Ssc.5045.1.S1_at
3-beta-hydroxysteroid-
−1.55
1.24
2.19
2.08
EBP
SR 31747



delta(8),delta(7)-isomerase



(Cholestenol delta-isomerase)



(Delta8-delta7 sterol



isomerase) (D8-D7 sterol



isomerase) (Emopamil-binding



protein)


Ssc.8726.1.A1_at
Amidophosphoribosyltransferase
1.03
1.24
4.16
−1.11
PPAT
6-mercaptopurine, thioguanine,



precursor (Glutamine





azathioprine



phosphoribosylpyrophosphate



amidotransferase) (ATASE)



(GPAT)


Ssc.10219.1.A1_at
Excitatory amino acid
1.36
1.24
−3.38
−1.03
SLC1A6
riluzole



transporter 4 (Sodium-



dependent glutamate/aspartate



transporter)


Ssc.15999.1.A1_at
Vascular endothelial growth
1.24
1.24
18.52
−11.02
KDR
AEE 788, sunitinib, AZD 2171,



factor receptor 2 precursor





pazopanib, XL647, CEP 7055,



(VEGFR-2) (Kinase insert





BMS-582664, KRN-951, vatalanib,



domain receptor) (Protein-





sorafenib, vandetanib,



tyrosine kinase receptor Flk-





pegaptanib



1)


Ssc.9348.1.S1_at
Peroxisome proliferator
−1.05
1.22
−3.05
−1.52
PPARA
NS-220, tesaglitazar,



activated receptor alpha





clofibrate, fenofibrate,



(PPAR-alpha)





docosahexaenoic acid,









gemfibrozil


Ssc.1498.1.S1_at
Proteasome subunit beta type 5
−1.81
1.19
1.38
5.94
PSMB5
bortezomib



precursor (Proteasome epsilon



chain) (Macropain epsilon



chain) (Multicatalytic



endopeptidase complex epsilon



chain) (Proteasome subunit X)



(Proteasome chain 6)



(Proteasome subunit MB1)


Ssc.6934.1.A1_at
Thymidylate synthase (EC
−1.13
1.19
−1.11
−2.81
TYMS
flucytosine, 5-fluorouracil,



2.1.1.45) (TS) (TSase) (OK/SW-





plevitrexed, nolatrexed,



cl.29)





capecitabine, trifluridine,









floxuridine, LY231514


Ssc.28329.1.S1_at
DNA polymerase beta
1.14
1.19
1.07
5.25
POLB
nelarabine, clofarabine,









stavudine, trifluridine,









vidarabine, zalcitabine,









entecavir


Ssc.16823.1.S1_at
P2Y purinoceptor 12 (P2Y12)
1.38
1.19
1.41
1.11
P2RY12
prasugrel, AZD 6140



(P2Y12 platelet ADP receptor)





(Ticagrelor), clopidogrel



(P2Y(ADP)) (ADP-glucose



receptor) (ADPG-R) (P2Y(AC))



(P2Y(cyc)) (P2T(AC)) (SP1999


Ssc.19691.1.S1_at
Platelet-activating factor
1.59
1.16
3.01
1.47
PLA2G7
darapladib



acetylhydrolase precursor (EC



3.1.1.47) (PAF



acetylhydrolase) (PAF 2-



acylhydrolase) (LDL-associated



phospholipase A2) (LDL-PLA(2))



(2-acetyl-1-



alkylglycerophosphocholine



esterase) (1-alkyl-2-



acetylglycerophosphocholine



esterase)


Ssc.15880.1.S1_at
Cysteinyl leukotriene receptor
2.86
1.14
−2.12
−3.42
CYSLTR2
montelukast, zafirlukast



2 (CysLTR2) (PSEC0146) (HG57)



(HPN321) (hGPCR21)


Ssc.11147.1.S1_at
Aldehyde dehydrogenase,
3.18
1.13
2.00
−1.68
ALDH2
disulfiram, chlorpropamide



mitochondrial precursor (EC



1.2.1.3) (ALDH class 2)



(ALDHI) (ALDH-E2)


Ssc.1908.1.S1_at
FKBP-rapamycin associated
1.99
1.13
−1.88
−1.46
FRAP1
AP23573, temsirolimus,



protein (FRAP) (Rapamycin





tacrolimus, everolimus



target protein)


Ssc.19700.1.S1_at
Serine/threonine protein
1.11
1.13
1.34
1.09
PPP3CB
ISAtx-247, tacrolimus,



phosphatase 2B catalytic





pimecrolimus, cyclosporin A



subunit, beta


Ssc.30147.1.A1_at
Fibroblast growth factor
1.56
1.13
−1.05
−1.18
FGFR2
palifermin



receptor 2 precursor (FGFR-2)



(Keratinocyte growth factor



receptor 2)


Ssc.27232.1.S1_at
Succinate semialdehyde
2.06
1.12
−2.84
−5.73
ALDH5A1
valproic acid



dehydrogenase, mitochondrial



precursor (NAD(+)-dependent



succinic semialdehyde



dehydrogenase)


Ssc.10215.1.A1_at
High-affinity cAMP-specific
1.83
1.12
−8.48
−15.51
PDE8A
dyphylline, nitroglycerin,



and IBMX-insensitive 3′,5′-





aminophylline, anagrelide,



cyclic phosphodiesterase 8A





milrinone, dipyridamole,









tolbutamide, theophylline,









pentoxifylline


Ssc.2767.2.S1_a_at
Prostaglandin E2 receptor, EP3
2.30
1.12
−1.59
−6.78
PTGER3
prostaglandin E1



subtype (Prostanoid EP3



receptor) (PGE receptor, EP3



subtype)


Ssc.15955.1.S1_at
Antithrombin-III precursor
−1.89
1.12
−2.06
−2.42
SERPINC1
enoxaparin, SR-123781A,



(ATIII) (PRO0309)





fondaparinux


Ssc.25040.1.S1_at
Serine/threonine-protein
−3.75
1.11
1.06
−2.45
CHEK1
UCN-01 (7-



kinase Chk1





hydroxystaurosporine)


Ssc.14488.1.S1_at
Glutamate carboxypeptidase II
−1.04
1.10
1.02
1.69
FOLH1
capromab pendetide



(Membrane glutamate



carboxypeptidase)


Ssc.1.1.S1_at
3-oxo-5-alpha-steroid 4-
−1.77
1.05
−4.11
−1.09
SRD5A2
finasteride, dutasteride



dehydrogenase 2 (Steroid 5-



alpha-reductase 2) (SR type 2)



(5 alpha-SR2)


Ssc.7581.1.A1_at
FL cytokine receptor precursor
1.69
1.04
−1.81
1.01
FLT3
CHIR-258, sorafenib,



(Tyrosine-protein kinase





lestaurtinib, CGP 41251



receptor FLT3) (Stem cell



tyrosine kinase 1) (STK-1)



(CD135 antigen)
















TABLE 5







Day 60 prescription.
















Fold
Fold
Fold
Fold






Change
Change
Change
Change




D 7/
D 21/
D 60/
D 180/
Gene


Probe ID
Name
Base
Base
Base
Base
Symbol
DRUGS

















Ssc.21108.1.S1_at
Complement C5
−17.35
3.21
618.80
9.28
C5
eculizumab


Ssc.9272.1.S1_at
Tumor-associated calcium
1.81
3.94
176.50
2.07
TACSTD1
tucotuzumab celmoleukin



signal transducer 1 (EPCAM



antigen)


Ssc.23793.1.S1_at
T-cell surface antigen CD2
−3.27
79.25
93.34
5.20
CD2
alefacept, siplizumab


Ssc.17245.1.S1_at
Interleukin-13 receptor alpha-
−1.99
23.04
21.92
7.16
IL13RA1
cintredekin besudotox



1 chain


Ssc.15999.1.A1_at
Vascular endothelial growth
1.24
1.24
18.52
−11.02
KDR
AEE 788, sunitinib, AZD 2171,



factor receptor 2





pazopanib, XL647, CEP 7055, BMS-









582664, KRN-951, vatalanib,









sorafenib, vandetanib, pegaptanib


Ssc.27603.1.S1_at
Endothelin B receptor
5.30
−3.27
15.99
1.23
EDNRB
bosentan, sitaxsentan,



precursor (ET-B) (Endothelin





atrasentan



receptor Non- selective type)


Ssc.2714.1.S1_a_at
Proto-oncogene tyrosine-
−4.26
9.56
12.54
3.93
FYN
dasatinib



protein kinase FYN


SscAffx.20.1.S1_at
T-cell surface glycoprotein
−2.19
14.07
10.96
3.62
CD3G
visilizumab, MT103



CD3 gamma chain


Ssc.7176.1.A1_at
C-X-C chemokine receptor type
3.74
10.91
8.15
1.68
CXCR4
JM 3100



4 (CXC-R4) (CXCR-4)


Ssc.26200.1.S1_at
Thyroid hormone receptor beta-
3.49
−1.56
7.96
2.52
THRB
3,5-diiodothyropropionic acid,



1





amiodarone, thyroxine, L-









triiodothyronine


Ssc.7297.1.S1_at
Amine oxidase [flavin-
1.16
6.42
7.02
−1.13
MAOB
safinamide, ladostigil,



containing] B(Monoamine





rasagiline, selegiline,



oxidase) (MAO-B).





dextroamphetamine, procainamide,









tranylcypromine, phenelzine,









isocarboxazid, benzphetamine


Ssc.9019.1.A1_at
Atrial natriuretic peptide
−1.09
−1.69
5.31
1.18
NPR3
nesiritide



clearance receptor precursor



(ANP-C) (ANPRC)


Ssc.20438.1.S1_at
Prostaglandin F2-alpha
−3.20
2.13
5.28
−38.97
PTGFR
tafluprost, travoprost,



receptor





isopropyl unoprostone,









bimatoprost, latanoprost


Ssc.3040.1.S1_at
Histone deacetylase 2 (HD2)
−3.24
2.79
4.94
4.72
HDAC2
tributyrin, PXD101, pyroxamide,









vorinostat, FR 901228


Ssc.26325.1.S1_at
Cystic fibrosis transmembrane
1.60
−5.71
4.77
−8.99
CFTR
SP 303



conductance regulator (CFTR)


Ssc.12845.1.S1_at
Cell division protein kinase 6
−6.56
5.40
4.77
5.13
CDK6
PD-0332991, flavopiridol


Ssc.13186.1.S1_at
Cell division protein kinase 7
−1.08
2.38
4.34
1.24
CDK7
BMS-387032, flavopiridol


Ssc.8726.1.A1_at
Amidophosphoribosyltransferase
1.03
1.24
4.16
−1.11
PPAT
6-mercaptopurine, thioguanine,









azathioprine


Ssc.15374.1.S1_at
COL14A1 protein
1.10
−17.71
3.79
2.24
COL14A1
collagenase


Ssc.1147.1.A1_at
Lipoprotein lipase
4.05
−5.49
3.78
−8.08
LPL
nicotinic acid,









lovastatin/niacin


Ssc.15878.1.S1_at
Serine/threonine protein
1.85
3.22
3.62
−1.49
PPP3CA
ISAtx-247, tacrolimus,



phosphatase 2B catalytic





pimecrolimus, cyclosporin A



subunit, alpha


Ssc.26351.1.S1_at
cAMP-specific 3′,5′-cyclic
4.67
4.99
3.61
−1.15
PDE4D
dyphylline, nitroglycerin,



phosphodiesterase 4D





arofylline, tetomilast, L 869298,









aminophylline, anagrelide,









cilomilast, milrinone, rolipram,









dipyridamole, L-826,141,









roflumilast, tolbutamide,









theophylline, pentoxifylline,









caffeine


Ssc.15801.1.A1_at
Protein kinase C, beta
3.36
6.36
3.53
−4.98
PRKCB1
enzastaurin, ruboxistaurin


Ssc.10055.1.A1_at
Alpha platelet-derived growth
−2.14
−1.46
3.52
−1.14
PDGFRA
sunitinib, axitinib, imatinib,



factor receptor





becaplermin


Ssc.24966.1.S1_at
Purine nucleoside
−3.34
3.12
3.46
−1.14
NP
forodesine, 9-deaza-9-(3-



phosphorylase





thienylmethyl)guanine


Ssc.18051.1.S1_at
cGMP-inhibited 3′,5′-cyclic
−3.16
1.96
3.41
2.32
PDE3B
dyphylline, nitroglycerin,



phosphodiesterase B





medorinone, aminophylline,









cilostazol, dipyridamole,









amrinone, tolbutamide,









theophylline, pentoxifylline


Ssc.9523.1.A1_at
Methylated-DNA--protein-
1.55
−1.17
3.35
1.47
MGMT
O6-benzylguanine



cysteine methyltransferase


Ssc.16000.1.A1_at
Vascular endothelial growth
1.08
−3.40
3.34
1.72
FLT1
sunitinib, axitinib, CEP 7055



factor receptor 1


Ssc.26328.1.S1_at
C-C chemokine receptor type 5
−2.53
5.61
3.25
1.29
CCR5
maraviroc, vicriviroc, SCH



(CCR5) (CD195 antigen).





351125


Ssc.17224.1.S1_at
Toll-like receptor 8
1.17
6.49
3.13
−1.52
TLR8
resiquimod


Ssc.21011.1.S1_at
Collagen alpha 2(I) chain
−2.70
1.24
3.12
−1.01
COL1A2
collagenase


Ssc.10360.1.S1_at
B-Raf proto-oncogene
−2.15
1.26
3.09
1.36
BRAF
sorafenib



serine/threonine-protein



kinase


Ssc.19532.1.S1_at
Guanylate cyclase soluble,
−4.28
12.74
3.04
2.13
GUCY1B3
nitroglycerin, isosorbide-5-



beta-1 chain





mononitrate, isosorbide









dinitrate, nitroprusside,









isosorbide dinitrate/hydralazine


Ssc.19691.1.S1_at
Platelet-activating factor
1.59
1.16
3.01
1.47
PLA2G7
darapladib



acetylhydrolase precursor


Ssc.17155.1.A1_at
heparanase; heparanase-1
4.81
5.38
2.98
−1.83
HPSE
heparanase inhibitor PI-88


Ssc.15932.1.S1_at
Integrin alpha-V precursor
−6.15
5.79
2.94
3.14
ITGAV
abciximab, CNTO 95, EMD121974


Ssc.16167.1.S1_at
Rho-associated protein kinase 1
2.40
2.32
2.83
3.00
ROCK1
fasudil, Y-27632


Ssc.62.2.S1_a_at
Interleukin-6 (IL-6)
1.89
−6.32
2.77
−1.04
IL6
tocilizumab


Ssc.11246.1.A1_at
Protein kinase C, alpha
−5.96
−4.78
2.68
2.46
PRKCA
L-threo-safingol


Ssc.11381.1.S1_at
Interferon-alpha/beta receptor
10.45
8.08
2.61
−1.30
IFNAR1
interferon beta-1a, interferon



alpha





alfa-2b, interferon alfacon-1,









PEG-interferon alfa-2a,









interferon alfa-2a/ribavirin,









pegintron, interferon beta-1b,









IFNA2A


Ssc.20685.1.S1_at
Apoptosis regulator Bcl-2
−2.22
2.77
2.58
3.25
BCL2
oblimersen, (−)-gossypol


Ssc.12937.1.S1_at
Presenilin 1 (PS-1) (S182
−14.09
6.21
2.48
3.79
PSEN1
(R)-flurbiprofen



protein)


Ssc.8500.1.A1_at
Glutamate receptor 4 precursor
−1.04
−1.13
2.39
−7.80
GRIA4
talampanel, Org 24448, LY451395,



(GluR-4) (GluR4) (GluR-D)





tezampanel



(Glutamate receptor



ionotropic, AMPA 4)


Ssc.6801.1.S1_at
Proto-oncogene tyrosine-
−1.06
1.69
2.36
−1.82
YES1
dasatinib



protein kinase YES


Ssc.30373.1.A1_at
cGMP-specific 3′,5′-cyclic
4.27
1.52
2.34
4.09
PDE5A
dyphylline, nitroglycerin, DA-



phosphodiesterase





8159, aminophylline, sildenafil,









dipyridamole,









aspirin/dipyridamole, vardenafil,









tolbutamide, tadalafil,









theophylline, pentoxifylline


Ssc.15886.1.S1_at
Apopain precursor (Caspase-3)
−3.02
3.64
2.31
2.29
CASP3
IDN-6556



(CASP-3)


Ssc.16114.1.S1_at
Dihydropyridine-sensitive L-
−1.96
−4.18
2.24
3.65
CACNA2D1
bepridil, amlodipine, pregabalin



type, calcium channel alpha-



2/delta subunits


Ssc.10256.1.A1_at
cAMP-specific 3′,5′-cyclic
−1.89
6.74
2.20
2.44
PDE4B
dyphylline, nitroglycerin,



phosphodiesterase 4B (EC





arofylline, tetomilast, L 869298,



3.1.4.17) (DPDE4) (PDE32)





aminophylline, anagrelide,









cilomilast, milrinone, rolipram,









dipyridamole, L-826,141,









roflumilast, tolbutamide,









theophylline, pentoxifylline,









caffeine


Ssc.5045.1.S1_at
3-beta-hydroxysteroid-
−1.55
1.24
2.19
2.08
EBP
SR 31747



delta(8),delta(7)-isomerase



(Emopamil-binding protein)


Ssc.204.1.S1_at
Cytochrome P450 3A4
1.97
−3.35
2.16
−1.42
CYP3A4
ketoconazole


Ssc.16186.1.S1_at
T-cell surface glycoprotein
9.00
3.12
2.12
−5.66
CD3E
visilizumab, MT103, muromonab-



CD3 epsilon chain





CD3


Ssc.1091.1.S1_at
Collagen alpha 1(I) chain
−3.27
−17.59
2.07
1.03
COL1A1
collagenase


Ssc.11302.1.S1_at
Collagen alpha 1(III) chain
−1.80
2.02
2.06
1.26
COL3A1
collagenase


Ssc.19673.1.S1_at
T-cell surface glycoprotein
6.40
2.70
2.03
−11.77
CD3D
visilizumab, MT103



CD3 delta chain


Ssc.6710.1.A1_at
Ribonucleoside-diphosphate
−1.90
1.44
2.01
−1.01
RRM1
gemcitabine, clofarabine,



reductase M1 chain





fludarabine phosphate



(Ribonucleotide reductase



large chain)


Ssc.11147.1.S1_at
Aldehyde dehydrogenase,
3.18
1.13
2.00
−1.68
ALDH2
disulfiram, chlorpropamide



mitochondrial precursor



((ALDHI)


Ssc.1520.1.A1_at
Proto-oncogene tyrosine-
−1.05
−1.88
2.00
2.39
RET
sunitinib



protein kinase receptor ret


Ssc.30888.1.S1_at
Voltage-dependent L-type
2.92
−2.72
1.90
−7.82
CACNA1D
MEM-1003, mibefradil, bepridil,



calcium channel alpha-1D





nisoldipine, isradipine,



subunit





nicardipine


Ssc.15739.1.S1_at
Cytokine receptor common gamma
−1.12
9.42
1.90
−1.28
IL2RG
aldesleukin, denileukin diftitox



chain (IL-2R gamma chain)



(CD132 antigen)


Ssc.15822.1.S1_at
Coagulation factor V
1.92
3.76
1.89
−1.75
F5
drotrecogin alfa



(Activated protein C cofactor)


Ssc.4756.1.A1_at
Adenosine A3 receptor.
2.15
2.10
1.88
−1.81
ADORA3
adenosine, dyphylline,









aminophylline, clofarabine,









theophylline, caffeine


Ssc.12791.1.A1_at
3-hydroxy-3-methylglutaryl-
3.27
2.77
1.77
−2.56
HMGCR
aspirin/pravastatin,



coenzyme A reductase (HMG-CoA





lovastatin/niacin,



reductase)





ezetimibe/simvastatin,









amlodipine/atorvastatin,









fluvastatin, cerivastatin,









atorvastatin, pravastatin,









simvastatin, lovastatin,









rosuvastatin


Ssc.27293.1.A1_at
Hypoxanthine-guanine
2.15
−1.16
1.63
−7.14
HPRT1
6-mercaptopurine, thioguanine,



phosphoribosyltransferase





azathioprine



(HGPRT)


Ssc.16189.1.S1_at
Endothelin-1 receptor
−1.11
−2.54
1.58
−2.91
EDNRA
bosentan, avosentan,



(Endothelin A receptor) (ET-A)





clazosentan, ambrisentan,









sitaxsentan, ZD4054, SB 234551,









TBC 3214, BSF 302146, PD 180988,









atrasentan


Ssc.818.1.S1_at
RAF proto-oncogene
−1.40
2.56
1.58
1.98
RAF1
sorafenib



serine/threonine-protein



kinase


Ssc.15748.2.S2_at
T lymphocyte activation
1.95
−1.24
1.54
−3.12
CD80
abatacept



antigen CD80


Ssc.19059.1.A1_at
Type-1 angiotensin II receptor
5.57
−2.57
1.50
−11.08
AGTR1
amlodipine/olmesartan medoxomil,



(AT1) (AT1AR)





losartan/hydrochlorothiazide,









valsartan/hydrochlorothiazide,









candesartan cilexetil, olmesartan









medoxomil, irbesartan, losartan









potassium, telmisartan,









eprosartan, candesartan









cilexetil/hydrochlorothiazide,









hydrochlorothiazide/irbesartan,









eprosartan/hydrochlorothiazide,









hydrochlorothiazide/telmisartan,









hydrochlorothiazide/olmesartan









medoxomil, valsartan


Ssc.18459.1.S1_at
Amiloride-sensitive sodium
1.97
−2.41
1.43
−1.93
SCNN1A
triamterene/hydrochlorothiazide,



channel alpha-subunit





amiloride,









amiloride/hydrochlorothiazide,









triamterene


Ssc.10287.1.A1_at
Transforming growth factor
1.41
−4.54
1.43
1.67
TGFB2
AP-12009



beta 2 precursor (TGF-beta 2)


Ssc.16823.1.S1_at
P2Y purinoceptor 12 (P2Y12)
1.38
1.19
1.41
1.11
P2RY12
prasugrel, AZD 6140, clopidogrel



(P2Y12 platelet ADP receptor)



(P2Y(ADP))


Ssc.9565.1.S1_at
Interferon-gamma receptor
2.92
1.63
1.41
−1.23
IFNGR1
interferon gamma-1b



alpha chain


Ssc.9595.1.S1_at
Beta platelet-derived growth
3.48
−3.60
1.40
1.65
PDGFRB
dasatinib, sunitinib, axitinib,



factor receptor





KRN-951, imatinib, sorafenib,









becaplermin


Ssc.8046.1.A1_at
peptidylprolyl isomerase A
1.16
−1.08
1.39
1.26
PPIA
N-methyl-4-Ile-cyclosporin



isoform 1; cyclophilin A;


Ssc.1498.1.S1_at
Proteasome subunit beta type 5
−1.81
1.19
1.38
5.94
PSMB5
bortezomib


Ssc.7111.1.A1_at
Ribonucleoside-diphosphate
−13.13
4.08
1.37
1.67
RRM2
gemcitabine, triapine,



reductase M2 chain





hydroxyurea, fludarabine



(Ribonucleotide reductase





phosphate



small chain)


Ssc.19700.1.S1_at
Serine/threonine protein
1.11
1.13
1.34
1.09
PPP3CB
ISAtx-247, tacrolimus,



phosphatase 2B catalytic





pimecrolimus, cyclosporin A



subunit, beta


Ssc.14258.1.S1_at
Amyloid beta A4 protein
1.87
3.33
1.34
−1.02
APP
AAB-001



precursor (APP) (ABPP)


Ssc.6418.1.S1_at
Farnesyl-diphosphate
−1.25
2.31
1.33
1.08
FDFT1
TAK-475, zoledronic acid



farnesyltransferase


Ssc.16096.2.S1_a_at
Mast/stem cell growth factor
−1.28
−2.63
1.30
−4.71
KIT
dasatinib, sunitinib, KRN-951,



receptor





imatinib, sorafenib


Ssc.29149.1.A1_at
Mineralocorticoid receptor
−2.18
−2.78
1.28
−11.66
NR3C2
hydrochlorothiazide/spironolactone,



(MR)





fludrocortisone acetate,









drospirenone, spironolactone,









eplerenone


Ssc.5569.1.S1_at
Thyroid hormone receptor alpha
−10.22
1.26
1.26
6.49
THRA
3,5-diiodothyropropionic acid,









amiodarone, thyroxine, L-









triiodothyronine


Ssc.26215.1.S1_at
DNA polymerase epsilon p12
−1.23
−2.71
1.19
−1.04
POLE4
gemcitabine



subunit (DNA polymerase



epsilon subunit 4)


Ssc.23234.1.S1_at
collagen, type XXIV, alpha 1
−1.43
1.66
1.16
1.76
COL24A1
collagenase


Ssc.10142.1.A1_at
Dihydropyrimidine
2.06
2.17
1.13
−2.68
DPYD
eniluracil



dehydrogenase [NADP+]


Ssc.3607.1.S1_at
Interferon-alpha/beta receptor
2.28
4.65
1.11
−1.56
IFNAR2
interferon beta-1a, interferon



beta





alfa-2b, interferon alfacon-1,









PEG-interferon alfa-2a,









interferon alfa-2a/ribavirin,









pegintron, interferon beta-1b,









IFNA2A


Ssc.14475.3.S1_a_at
Peroxisome proliferator
13.83
−9.38
1.09
−2.85
PPARG
rosiglitazone, GI262570,



activated receptor gamma





pioglitazone, tesaglitazar,



(PPAR-gamma)





troglitazone


Ssc.5000.1.A1_at
Receptor protein-tyrosine
−1.04
−4.15
1.08
2.25
ERBB2
trastuzumab, BMS-599626, ARRY-



kinase erbB-2





334543, XL647, CP-724,714, HKI-









272, lapatinib, erlotinib


Ssc.23505.1.S1_at
Amine oxidase [flavin-
−1.86
2.17
1.08
1.20
MAOA
ladostigil, 1-ethylphenoxathiin



containing] A (Monoamine





10,10-dioxide, dextroamphetamine,



oxidase) (MAO-A)





procainamide, tranylcypromine,









phenelzine, isocarboxazid,









benzphetamine, N-(2-









indanyl)glycinamide


Ssc.19379.1.A1_at
Voltage-dependent L-type
1.83
−1.34
1.07
−3.27
CACNA1C
clevidipine, MEM-1003,



calcium channel alpha-1C





amlodipine/olmesartan medoxomil,









amlodipine/benazepril, diltiazem,









verapamil, mibefradil, bepridil,









enalapril/felodipine,









amlodipine/atorvastatin,









nisoldipine, isradipine,









felodipine, nimodipine,









nitrendipine, amlodipine,









nicardipine, nifedipine,









trandolapril/verapamil,









diltiazem/enalapril


Ssc.6713.1.S1_at
Androgen receptor
−1.47
−11.56
1.07
−2.36
AR
estradiol valerate/testosterone



(Dihydrotestosterone receptor)





enanthate, estradiol









cypionate/testosterone cypionate,









bicalutamide, flutamide,









nandrolone decanoate,









testosterone cypionate,









medroxyprogesterone acetate,









oxandrolone, danazol, stanozolol,









spironolactone, testosterone,









oxymetholone, testosterone









propionate, testosterone









enanthate


Ssc.28329.1.S1_at
DNA polymerase beta
1.14
1.19
1.07
5.25
POLB
nelarabine, clofarabine,









stavudine, trifluridine,









vidarabine, zalcitabine,









entecavir


Ssc.25040.1.S1_at
Serine/threonine-protein
−3.75
1.11
1.06
−2.45
CHEK1
UCN-01 (7-hydroxystaurosporine)



kinase Chk1


Ssc.9781.1.S1_at
Plasminogen activator
−1.55
−1.17
1.04
1.30
SERPINE1
drotrecogin alfa



inhibitor-1 (PAI-1)



(Endothelial plasminogen



activator inhibitor) (PAI)


Ssc.16532.1.S1_at
Cell division protein kinase 2
−1.83
−1.51
1.04
1.35
CDK2
BMS-387032, flavopiridol



(p33 protein kinase).


Ssc.22797.1.S1_at
DNA topoisomerase II, beta
3.15
−1.87
1.02
−2.91
TOP2B
novobiocin, etoposide, CPI-









0004Na, pixantrone, becatecarin,









elsamitrucin, AQ4N, BN 80927,









tafluposide, mitoxantrone,









norfloxacin, dexrazoxane,









tirapazamine, TAS-103, XK469,









gatifloxacin, valrubicin,









gemifloxacin, moxifloxacin,









nemorubicin, nalidixic acid,









epirubicin, doxorubicin,









daunorubicin


Ssc.14488.1.S1_at
Glutamate carboxypeptidase II
−1.04
1.10
1.02
1.69
FOLH1
capromab pendetide
















TABLE 6







Day 180 prescription.
















Fold
Fold
Fold
Fold






Change
Change
Change
Change




D 7/
D 21/
D 60/
D 180/
Gene


Probe ID
Name
Base
Base
Base
Base
Symbol
DRUGS

















Ssc.11051.1.S1_at
Cell division protein kinase 4
1.44
−7.67
−4.96
23.75
CDK4
PD-0332991, flavopiridol


Ssc.28690.1.A1_at
Histone deacetylase 6 (HD6)
−1.92
−1.57
−3.58
20.60
HDAC6
tributyrin, PXD101, pyroxamide,









vorinostat, FR 901228


Ssc.21108.1.S1_at
Complement C5
−17.35
3.21
618.80
9.28
C5
eculizumab


Ssc.5569.1.S1_at
Thyroid hormone receptor alpha
−10.22
1.26
1.26
6.49
THRA
3,5-diiodothyropropionic acid,









amiodarone, thyroxine, L-









triiodothyronine


Ssc.1498.1.S1_at
Proteasome subunit beta type 5
−1.81
1.19
1.38
5.94
PSMB5
bortezomib


Ssc.13460.1.A1_at
Histone deacetylase 9 (HD9)
−6.40
5.13
−1.79
5.72
HDAC9
tributyrin, PXD101, pyroxamide,



(HD7B) (HD7).





vorinostat, FR 901228


Ssc.28329.1.S1_at
DNA polymerase beta
1.14
1.19
1.07
5.25
POLB
nelarabine, clofarabine,









stavudine, trifluridine,









vidarabine, zalcitabine,









entecavir


Ssc.23793.1.S1_at
T-cell surface antigen CD2
−3.27
79.25
93.34
5.20
CD2
alefacept, siplizumab


Ssc.12845.1.S1_at
Cell division protein kinase 6
−6.56
5.40
4.77
5.13
CDK6
PD-0332991, flavopiridol


Ssc.24528.1.S1_at
Angiotensin-converting enzyme
−1.61
5.01
2.33
4.76
ACE
pentopril, perindoprilat,









amlodipine/benazepril,









lisinopril/hydrochlorothiazide,









benazepril, enalapril,









perindopril, captopril,









enalapril/felodipine,









hydrochlorothiazide/moexipril,









benazepril/hydrochlorothiazide,









hydrochlorothiazide/quinapril,









fosinopril/hydrochlorothiazide,









captopril/hydrochlorothiazide,









enalapril/hydrochlorothiazide,









ramipril, moexipril, quinapril,









lisinopril, enalaprilat,









trandolapril,









trandolapril/verapamil,









diltiazem/enalapril, fosinopril


Ssc.3040.1.S1_at
Histone deacetylase 2 (HD2)
−3.24
2.79
4.94
4.72
HDAC2
tributyrin, PXD101, pyroxamide,









vorinostat, FR 901228


Ssc.30373.1.A1_at
cGMP-specific 3′,5′-cyclic
4.27
1.52
2.34
4.09
PDE5A
dyphylline, nitroglycerin, DA-



phosphodiesterase





8159, aminophylline, sildenafil,









dipyridamole,









aspirin/dipyridamole,









vardenafil, tolbutamide,









tadalafil, theophylline,









pentoxifylline


Ssc.2714.1.S1_a_at
Proto-oncogene tyrosine-
−4.26
9.56
12.54
3.93
FYN
dasatinib



protein kinase FYN


Ssc.12937.1.S1_at
Presenilin 1 (PS-1) (S182
−14.09
6.21
2.48
3.79
PSEN1
(R)-flurbiprofen



protein).


Ssc.19937.1.S1_at
Inosine-5′-monophosphate
1.00
2.69
−1.47
3.65
IMPDH2
thioguanine, VX-944, interferon



dehydrogenase 2





alfa-2a/ribavirin, mycophenolic









acid, ribavirin


Ssc.16114.1.S1_at
Dihydropyridine-sensitive L-
−1.96
−4.18
2.24
3.65
CACNA2D
bepridil, amlodipine,



type, calcium channel alpha-




1
pregabalin



2/delta


SscAffx.20.1.S1_at
T-cell surface glycoprotein
−2.19
14.07
10.96
3.62
CD3G
visilizumab, MT103



CD3 gamma chain


Ssc.20685.1.S1_at
Apoptosis regulator Bcl-2
−2.22
2.77
2.58
3.25
BCL2
oblimersen, (−)-gossypol


Ssc.11443.1.A1_at
Transcription factor p65
−1.43
−2.45
−3.96
3.24
RELA
NF-kappaB decoy


Ssc.26290.1.S1_at
Integrin beta-5
−1.06
−1.51
−5.43
3.24
ITGB5
EMD121974


Ssc.15932.1.S1_at
Integrin alpha-V
−6.15
5.79
2.94
3.14
ITGAV
abciximab, CNTO 95, EMD121974


Ssc.14471.1.S1_at
B-lymphocyte antigen CD19
9.54
3.30
−10.32
3.04
CD19
combotox, HD37-dgRTA, MT103


Ssc.16167.1.S1_at
Rho-associated protein kinase
2.40
2.32
2.83
3.00
ROCK1
fasudil, Y-27632



1


Ssc.26200.1.S1_at
Thyroid hormone receptor beta-
3.49
−1.56
7.96
2.52
THRB
3,5-diiodothyropropionic acid,



1.





amiodarone, thyroxine, L-









triiodothyronine


Ssc.3059.1.S1_at
Aldose reductase (Aldehyde
−1.74
1.98
−1.66
2.49
AKR1B1
sorbinil, Zopolrestat (Alond,



reductase).





Pfizer), zenarestat (Fujisawa,









Parke-Davis)


Ssc.11246.1.A1_at
Protein kinase C, alpha
−5.96
−4.78
2.68
2.46
PRKCA
L-threo-safingol


Ssc.10256.1.A1_at
cAMP-specific 3′,5′-cyclic
−1.89
6.74
2.20
2.44
PDE4B
dyphylline, nitroglycerin,



phosphodiesterase 4B





arofylline, tetomilast, L









869298, aminophylline,









anagrelide, cilomilast,









milrinone, rolipram,









dipyridamole, L-826, 141,









roflumilast, tolbutamide,









theophylline, pentoxifylline,









caffeine


Ssc.1598.1.S1_at
Retinoic acid receptor RXR-
−2.21
−1.13
−4.20
2.42
RXRB
bexarotene, retinoic acid, 9-



beta





cis-retinoic acid


Ssc.1520.1.A1_at
Proto-oncogene tyrosine-
−1.05
−1.88
2.00
2.39
RET
sunitinib



protein kinase receptor ret


Ssc.11572.1.A1_at
Histone deacetylase 3 (HD3)
−1.65
1.67
−1.55
2.36
HDAC3
tributyrin, PXD101, pyroxamide,



(RPD3-2) (SMAP45).





MGCD0103, vorinostat, FR 901228


Ssc.18051.1.S1_at
cGMP-inhibited 3′,5′-cyclic
−3.16
1.96
3.41
2.32
PDE3B
dyphylline, nitroglycerin,



phosphodiesterase B





medorinone, aminophylline,









cilostazol, dipyridamole,









amrinone, tolbutamide,









theophylline, pentoxifylline


Ssc.15886.1.S1_at
Apopain precursor (Caspase-3)
−3.02
3.64
2.31
2.29
CASP3
IDN-6556



(CASP-3)


Ssc.5000.1.A1_at
Receptor protein-tyrosine
−1.04
−4.15
1.08
2.25
ERBB2
trastuzumab, BMS-599626, ARRY-



kinase erbB-2





334543, XL647, CP-724,714, HKI-









272, lapatinib, erlotinib


Ssc.15374.1.S1_at
COL14A1 protein
1.10
−17.71
3.79
2.24
COL14A1
collagenase


Ssc.19873.1.S1_at
Collagen alpha 1(XVII) chain
−2.37
3.02
−1.55
2.18
COL17A1
collagenase


Ssc.19532.1.S1_at
Guanylate cyclase soluble,
−4.28
12.74
3.04
2.13
GUCY1B3
nitroglycerin, isosorbide-5-



beta-1 chain





mononitrate, isosorbide









dinitrate, nitroprusside,









isosorbide dinitrate/hydralazine


Ssc.5045.1.S1_at
3-beta-hydroxysteroid-
−1.55
1.24
2.19
2.08
EBP
SR 31747



delta(8),delta(7)-isomerase



(EC 5.3.3.5) (Cholestenol



delta-isomerase) (Emopamil-



binding protein).


Ssc.9272.1.S1_at
Tumor-associated calcium
1.81
3.94
176.50
2.07
TACSTD1
tucotuzumab celmoleukin



signal transducer 1 (EPCAM



antigen)


Ssc.7139.1.S1_at
Dihydrofolate reductase
−1.13
1.41
−1.12
2.06
DHFR
pyrimethamine, trimethoprim,









iclaprim, methotrexate,









sulfisoxazole, triamterene,









folic acid, trimetrexate,









LY231514, PT 523


Ssc.818.1.S1_at
RAF proto-oncogene
−1.40
2.56
1.58
1.98
RAFI
sorafenib



serine/threonine-protein



kinase


Ssc.25168.1.S1_a_at
Collagen alpha 1(XVI) chain
−7.23
−3.61
−4.45
1.87
COL16A1
collagenase


Ssc.3737.1.S1_at
Tubulin gamma-1 chain (Gamma-1
−1.24
−1.88
−1.29
1.82
TUBG1
epothilone B, ixabepilone,



tubulin) (





colchicine/probenecid, XRP9881,









E7389, AL 108, EC145, NPI-2358,









milataxel, TPI 287, TTI-237,









docetaxel, vinflunine,









vinorelbine, vincristine,









vinblastine, paclitaxel,









podophyllotoxin, colchicine


Ssc.23234.1.S1_at
collagen, type XXIV, alpha 1
−1.43
1.66
1.16
1.76
COL24A1
collagenase


Ssc.16000.1.A1_at
Vascular endothelial growth
1.08
−3.40
3.34
1.72
FLT1
sunitinib, axitinib, CEP 7055



factor receptor 1


Ssc.14488.1.S1_at
Glutamate carboxypeptidase II
−1.04
1.10
1.02
1.69
FOLH1
capromab pendetide


Ssc.7176.1.A1_at
C-X-C chemokine receptor type
3.74
10.91
8.15
1.68
CXCR4
JM 3100



4 (CXC-R4) (CXCR-4)


Ssc.10287.1.Al_at
Transforming growth factor
1.41
−4.54
1.43
1.67
TGFB2
AP-12009



beta 2


Ssc.7111.1.A1_at
Ribonucleos ide-diphosphate
−13.13
4.08
1.37
1.67
RRM2
gemcitabine, triapine,



reductase M2 chain





hydroxyurea, fludarabine









phosphate


Ssc.9595.1.S1_at
Beta platelet-derived growth
3.48
−3.60
1.40
1.65
PDGFRB
dasatinib, sunitinib, axitinib,



factor receptor





KRN-951, imatinib, sorafenib,









becaplermin


Ssc.5826.1.A1_at
Macrophage colony stimulating
1.93
−4.97
−13.18
1.61
CSF1R
sunitinib



factor I receptor


Ssc.17518.1.S1_at
Adenosine A1 receptor
−3.16
3.44
−1.56
1.58
ADORA1
adenosine, dyphylline,









aminophylline, clofarabine,









theophylline, caffeine,









tecadenos on


Ssc.19691.1.S1_at
Platelet-activating factor
1.59
1.16
3.01
1.47
PLA2G7
darapladib



acetylhydrolase


Ssc.9523.1.A1_at
Methylated-DNA-protein-
1.55
−1.17
3.35
1.47
MGMT
O6-benzylguanine



cysteine methyltransferase


Ssc.11406.1.A1_a_at
Interleukin-1 receptor, type I
1.03
2.70
−2.44
1.42
IL1R1
anakinra


Ssc.11085.1.S1_at
Glucagon-like peptide 2
−1.08
−1.17
−1.26
1.40
GLP2R
teduglutide



receptor


Ssc.10591.1.A1_at
Metabotropic glutamate
−7.83
1.54
−1.31
1.40
GRM5
fasoracetam



receptor 5


Ssc.9034.1.A1_at
Proteinase activated receptor
−1.29
3.75
−1.40
1.37
F2R
chrysalin, argatroban,



1





bivalirudin


Ssc.10360.1.S1_at
B-Raf proto-oncogene
−2.15
1.26
3.09
1.36
BRAF
sorafenib



serine/threonine-protein



kinase


Ssc.16532.1.S1_at
Cell division protein kinase 2
−1.83
−1.51
1.04
1.35
CDK2
BMS-387032, flavopiridol


Ssc.9781.1.S1_at
Plasminogen activator
−1.55
−1.17
1.04
1.30
SERPINE
drotrecogin alfa



inhibitor-1 precursor (PAI-1)




1



(Endothelial plasminogen



activator inhibitor) (PAI)


Ssc.26328.1.S1_at
C-C chemokine receptor type 5
−2.53
5.61
3.25
1.29
CCR5
maraviroc, vicriviroc, SCH



(CCR5) (CD195 antigen)





351125


Ssc.8046.1.A1_at
peptidylprolyl isomerase A
1.16
−1.08
1.39
1.26
PPIA
N-methyl-4-Ile-cyclosporin



isoform 1; cyclophilin A;


Ssc.11302.1.S1_at
Collagen alpha 1(III) chain
−1.80
2.02
2.06
1.26
COL3A1
collagenase


Ssc.13186.1.S1_at
Cell division protein kinase 7
−1.08
2.38
4.34
1.24
CDK7
BMS-387032, flavopiridol


Ssc.27603.1.S1_at
Endothelin B receptor
5.30
−3.27
15.99
1.23
EDNRB
bosentan, sitaxsentan,









atrasentan


Ssc.27093.1.A1_at
cAMP-specific 3′,5′-cyclic
−6.34
−2.27
−7.97
1.23
PDE4C
dyphylline, nitroglycerin,



phosphodiesterase 4C





arofylline, tetomilast, L









869298, aminophylline,









anagrelide, cilomilast,









milrinone, rolipram,









dipyridamole, L-826, 141,









roflumilast, tolbutamide,









theophylline, pentoxifylline,









caffeine


Ssc.20904.1.A1_at
RAC-gamma serine/threonine-
−1.34
3.01
−2.18
1.23
AKT3
enzastaurin



protein kinase


Ssc.23505.1.S1_at
Amine oxidase [flavin-
−1.86
2.17
1.08
1.20
MAOA
ladostigil, 1-ethylphenoxathiin



containing] A (Monoamine





10,10-dioxide,



oxidase) (MAO-A)





dextroamphetamine, procainamide,









tranylcypromine, phenelzine,









isocarboxazid, benzphetamine, N-









(2-indanyl)glycinamide


Ssc.15312.1.S1_at
Histone deacetylase 4 (HD4)
−1.93
2.85
−2.41
1.20
HDAC4
tributyrin, PXD101, pyroxamide,









vorinostat, FR 901228


Ssc.9019.1.Al_at
Atrial natriuretic peptide
−1.09
−1.69
5.31
1.18
NPR3
nesiritide



clearance receptor


Ssc.16160.1.S1_at
T lymphocyte activation
−1.55
3.88
−1.37
1.18
CD86
abatacept



antigen CD86


Ssc.1844.1.S1_at
Atrial natriuretic peptide
−1.94
−1.06
−1.63
1.13
NPR2
nesiritide



receptor B


Ssc.11171.1.S1_at
Adenosine deaminase
1.32
−2.04
−3.23
1.12
ADA
pentostatin, vidarabine


Ssc.16823.1.S1_at
P2Y purinoceptor 12 (P2Y12)
1.38
1.19
1.41
1.11
P2RY12
prasugrel, AZD 6140,



(P2Y12 platelet ADP receptor)





clopidogrel


Ssc.19700.1.S1_at
Serine/threonine protein
1.11
1.13
1.34
1.09
PPP3CB
ISAtx-247, tacrolimus,



phosphatase 2B catalytic





pimecrolimus, cyclosporin A



subunit, beta


Ssc.26752.1.S1_at
5-hydroxytryptamine
−3.57
1.22
1.60
1.08
HTR3B
cisapride, granisetron,



(serotonin) receptor 3B





ondansetron, fenfluramine,









palonosetron, mirtazapine,









alosetron, D-tubocurarine,









ergotamine, dolasetron


Ssc.6418.1.S1_at
Farnesyl-diphosphate
−1.25
2.31
1.33
1.08
FDFT1
TAK-475, zoledronic acid



farnesyltransferase


Ssc.22477.1.S1_at
Collagen alpha 1(IV) chain
1.58
−5.08
−1.78
1.04
COL4A1
collagenase


Ssc.31192.1.S1_at
Collagen alpha 1(XVIII) chain
−1.89
−1.36
−19.06
1.03
COL18A1
collagenase


Ssc.1091.1.S1_at
Collagen alpha 1(I) chain
−3.27
−17.59
2.07
1.03
COL1A1
collagenase


Ssc.7581.1.A1_at
FL cytokine receptor
1.69
1.04
−1.81
1.01
FLT3
CHIR-258, sorafenib,









lestaurtinib, CGP 41251
















TABLE 7







Upregulated gene targets at all timepoints (Days 7, 21, 60, and 180 relative to baseline) of PAH progression with available drugs
















Fold
Fold
Fold
Fold






Change
Change
Change
Change




D 7/
D 21/
D 60/
D 180/
Gene


Probe ID
Name
Base
Base
Base
Base
Symbol
Drugs

















Ssc.28329.1.S1_at
DNA polymerase beta
1.14
1.19
1.07
5.25
POLB
nelarabine, clofarabine,









stavudine, trifluridine,









vidarabine, zalcitabine,









entecavir


Ssc.9272.1.S1_at
Tumor-associated
1.81
3.94
176.50
2.07
TACSTD1
tucotusumab celmoleukin



calcium signal



transducer 1 (EPCAM



antigen)


Ssc.7176.1.A1_at
C-X-C chemokine
3.74
10.91
8.15
1.68
CXCR4
JM 3100 (1,1′-(1,4-



receptor type 4





phenylenebis{methylene)}bis(1,4,8,11-



(CXC-R4) (CXCR-4)



(CD184 antigen)





tetraazacyclotetradecane)octahydrochloride









dihydrate)


Ssc.19691.1.S1_at
Platelet-activating
1.59
1.16
3.01
1.47
PLA2G7
darapladib



factor



acetylhydrolase


Ssc.16823.1.S1_at
P2Y purinoceptor 12
1.38
1.19
1.41
1.11
P2RY12
prasugrel, AZD 6140



(P2Y12)





(Ticagrelor), clopidogrel


Ssc.19700.1.S1_at
Serine/threonine
1.11
1.13
1.34
1.09
PPP3CB
ISAtx-247, tacrolimus,



protein phosphatase





pimecrolimus, cyclosporin A



2B catalytic



subunit, beta



isoform


Ssc.14258.1.S1_at
Amyloid beta A4
1.87
3.33
1.34
−1.02
APP
Bapineuzumab (AAB-001)



protein


Ssc.8726.1.A1_at
Amidophosphoribosyltransferase
1.03
1.24
4.16
−1.11
PPAT
thioguanine, azathioprine, 6-









mercaptopurine,
















TABLE 8







Upregulated gene targets at Days 21 and 60 (relative to baseline) of PAH progression with available drugs
















Fold
Fold
Fold
Fold






Change
Change
Change
Change




D 7/
D 21/
D 60/
D 180/
Gene


Probe ID
Name
Base
Base
Base
Base
Symbol
Drugs

















Ssc.21108.1.S1_at
Complement C5
−17.35
3.21
618.80
9.28
C5
eculizumab


Ssc.9272.1.S1_at
Tumor-associated
1.81
3.94
176.50
2.07
TACSTD1
tucctuzumab celmoleukin



calcium signal



transducer 1


Ssc.23793.1.S1_at
T-cell surface
−3.27
79.25
93.34
5.20
CD2
alefacept, siplizumab



antigen CD2


Ssc.17245.1.S1_at
Interleukin-13
−1.99
23.04
21.92
7.16
IL13RA1
cintredekin besudotox



receptor alpha-1



chain


Ssc.15999.1.A1_at
Vascular endothelial
1.24
1.24
18.52
−11.02
KDR
AEE 788, sunitinib, AZD 2171,



growth factor





pazopanib, XL647, CEP 7055,









BMS-582664, KRN-951,









vatalanib, sorafenib, vandetanib,



receptor 2





pegaptanib


Ssc.2714.1.S1_a_at
Proto-oncogene
−4.26
9.56
12.54
3.93
FYN
dasatinib



tyrosine-protein



kinase FYN


SscAffx.20.1.S1_at
T-cell surface
−2.19
14.07
10.96
3.62
CD3G
visilizumab, MT103



glycoprotein CD3



gamma chain


Ssc.7176.1.A1_at
C-X-C chemokine
3.74
10.91
8.15
1.68
CXCR4
JM 3100



receptor type 4



(CXC-R4) (CXCR-4) (


Ssc.7297.1.S1_at
Amine oxidase
1.16
6.42
7.02
−1.13
MAOB
safinamide, ladostigil, rasagiline,



[flavin-containing]





selegiline, dextroamphetamine,



B (EC 1.4.3.4)





procainamide, tranylcypromine,



(Monoamine oxidase)





phenelzine, isocarboxazid,



(MAO-B).





benzphetamine


Ssc.20438.1.S1_at
Prostaglandin F2-
−3.20
2.13
5.28
−38.97
PTGFR
tafluprost, travoprost, isopropyl



alpha receptor (PGF2





unoprostone, bimatoprost, latanoprost



alpha receptor).


Ssc.3040.1.S1_at
Histone deacetylase
−3.24
2.79
4.94
4.72
HDAC2
tributyrin, PXD101, pyroxamide,



2 (HD2).





vorinostat, FR 901228


Ssc.12845.1.S1_at
Cell division
−6.56
5.40
4.77
5.13
CDK6
PD-0332991, flavopiridol



protein kinase 6 (E


Ssc.13186.1.S1_at
Cell division
−1.08
2.38
4.34
1.24
CDK7
BMS-387032, flavopiridol



protein kinase 7


Ssc.8726.1.A1_at
Amidophosphoribosyl-
1.03
1.24
4.16
−1.11
PPAT
6-mercaptopurine, thioguanine,



transferase





azathioprine


Ssc.15878.1.S1_at
Serine/threonine
1.85
3.22
3.62
−1.49
PPP3CA
ISAtx-247, tacrolimus, pimecrolimus,



protein phosphatase





cyclosporin A



2B catalytic



subunit, alpha



isoform


Ssc.26351.1.S1_at
cAMP-specific 3′,5′-
4.67
4.99
3.61
−1.15
PDE4D
dyphylline, nitroglycerin, arofylline,



cyclic





tetomilast, L 869298, aminophylline,



phosphodiesterase 4D





anagrelide, cilomilast, milrinone,



(EC 3.1.4.17)





rolipram, dipyridamole, L-826,141,



(DPDE3) (PDE43).





roflumilast, tolbutamide, theophylline,



[Source: Uniprot/





pentoxifylline, caffeine



SWISSPROT; Acc:



Q08499]


Ssc.15801.1.A1_at
Protein kinase C,
3.36
6.36
3.53
−4.98
PRKCB1
enzastaurin, ruboxistaurin



beta type (EC



2.7.1.37) (PKC-beta)



(PKC-B).



[Source: Uniprot/



SWISSPROT; Acc:



P05771]


Ssc.24966.1.S1_at
Purine nucleoside
−3.34
3.12
3.46
−1.14
NP
forodesine, 9-deaza-9-(3-



phosphorylase





thiethylmethyl)guanine


Ssc.18051.1.S1_at
cGMP-inhibited
−3.16
1.96
3.41
2.32
PDE3B
syphylline, nitroglycerin, medorinone,



3′,5′-cyclic





aminophylline, cilostazol, dipyridamole,



phosphodiesterase B





amrinone, tolbutamide, theophylline,









pentoxifylline


Ssc.26328.1.S1_at
C-C chemokine
−2.53
5.61
3.25
1.29
CCR5
maraviroc, vicriviroc, SCH 351125



receptor type 5 (C-C



CKR-5) (CC-CKR-5)



(CCR-5) (CCR5) (HIV-



1 fusion coreceptor)



(CHEMR13) (CD195



antigen).



[Source: Uniprot/



SWISSPROT; Acc:



P51681]


Ssc.17224.1.S1_at
Toll-like receptor 8
1.17
6.49
3.13
−1.52
TLR8
resiquimod



precursor.



[Source: Uniprot/



SWISSPROT; Acc:



Q9NR97]


Ssc.21011.1.S1_at
Collagen alpha 2(I)
−2.70
1.24
3.12
−1.01
COL1A2
collagenase



chain precursor.



[Source: Uniprot/



SWISSPROT; Acc:



P08123]


Ssc.10360.1.S1_at
B-Raf proto-oncogene
−2.15
1.26
3.09
1.36
BRAF
sorafenib



serine/threonine-



protein kinase (v-



Raf murine sarcoma



viral oncogene



homolog B1).


Ssc.19532.1.S1_at
Guanylate cyclase
−4.28
12.74
3.04
2.13
GUCY1B3
nitroglycerin, isosorbide-5-mononitrate,



soluble, beta-1





isosorbide dinitrate, nitroprusside,









isosorbide dinitrate/hydralazine


Ssc.19691.1.S1_at
Platelet-activating
1.59
1.16
3.01
1.47
PLA2G7
darapladib



factor



acetylhydrolase


Ssc.17155.1.A1_at
heparanase;
4.81
5.38
2.98
−1.83
HPSE
heparanase inhibitor PI-88



heparanase-1


Ssc.15932.1.S1_at
Integrin alpha-V
−6.15
5.79
2.94
3.14
ITGAV
abciximab, CNTO 95, EMD121974









(Cilengitide)


Ssc.11381.1.S1_at
Interferon-
10.45
8.08
2.61
−1.30
IFNAR1
interferon beta-1a, interferon alfa-2b,



alpha/beta receptor





interferon alfacon-1, PEG-interferon alfa-



alpha chain





2a, interferon alfa-2a/ribavirin,



precursor (IFN-





pegintron, interferon beta-1b, IFNA2A



alpha-REC).



[Source: Uniprot/



SWISSPROT; Acc:



P17181]


Ssc.20685.1.S1_at
Apoptosis regulator
−2.22
2.77
2.58
3.25
BCL2
Oblimersen (Augmerosen),



Bcl-2.



[Source: Uniprot/



SWISSPROT; Acc:



P10415]


Ssc.12937.1.S1_at
Presenilin 1 (PS-1)
−14.09
6.21
2.48
3.79
PSEN1
(R)-flurbiprofen (Tarenflurbil)



(S182 protein).


Ssc.6801.1.S1_at
Proto-oncogene
−1.06
1.69
2.36
−1.82
YES1
dasatinib



tyrosine-protein



kinase YES


Ssc.24528.1.S1_at
Angiotensin-
−1.61
5.01
2.33
4.76
ACE
pentopril, perindoprilat,



converting enzyme





amlodipine/benazepril,









lisinopril/hydrochlorothiazide,









benazepril, enalapril, perindopril,









captopril, enalapril/felodipine,









hydrochlorothiazide/moexipril,









benazepril/hydrochlorothiazide,









hydrochlorothiazide/quinapril,









fosinopril/hydrochlorothiazide,









captopril/hydrochlorothiazide,









enalapril/hydrochlorothiazide









moexipril, quinapril, lisinopril,









enalaprilat, trandolapril,









trandolapril/verapamil,









diltiazem/enalapril, fosinopril


Ssc.15886.1.S1_at
Apopain (Caspase-3)
−3.02
3.64
2.31
2.29
CASP3
IDN-6556



(CASP-3


Ssc.10256.1.A1_at
cAMP-specific 3′,5′-
−1.89
6.74
2.20
2.44
PDE4B
dyphylline, nitroglycerin, arofylline,



cyclic





tetomilast, L 869298, aminophylline,



phosphodiesterase 4B





anagrelide, cilomilast, milrinone,









rolipram, dipyridamole, L-826, 141,









roflumilast, tolbutamide, theophylline,









pentoxifylline, caffeine


Ssc.5045.1.S1_at
3-beta-
−1.55
1.24
2.19
2.08
EBP
SR 31747



hydroxysteroid-



delta(8),delta(7)-



isomerase


Ssc.16145.1.A1_at
5-hydroxytryptamine
1.08
2.10
2.15
5.45
HTR2B
risperidone, buspirone, blonanserin,



2B receptor (5-HT-





asenapine, eletriptan, epinastine,



2B) (Serotonin





fenfluramine, quetiapine, nefazodone,



receptor 2B).





mirtazapine, dihydroergotamine,









apomorphine, ergotamine


Ssc.16186.1.S1_at
T-cell surface
9.00
3.12
2.12
−5.66
CD3E
visilizumab, MT103, muromonab-CD3



glycoprotein CD3



epsilon chain


Ssc.11302.1.S1_at
Collagen alpha
−1.80
2.02
2.06
1.26
COL3A1
collagenase



1(III) chain



precursor.


Ssc.19673.1.S1_at
T-cell surface
6.40
2.70
2.03
−11.77
CD3D
visilizumab, MT103



glycoprotein CD3



delta chain



precursor (T-cell



receptor T3 delta



chain).


Ssc.6710.1.A1_at
Ribonucleoside-
−1.90
1.44
2.01
−1.01
RRM1
gemcitabine, clofarabine, fludarabine



diphosphate





phosphate



reductase M1 chain



(Ribonucleotide



reductase large



chain


Ssc.11147.1.S1_at
Aldehyde
3.18
1.13
2.00
−1.68
ALDH2
disulfiram, chlorpropamide



dehydrogenase,



mitochondrial



precursor (ALDH



class 2) (ALDHI)



(ALDH-E2).


Ssc.15739.1.S1_at
Cytokine receptor
−1.12
9.42
1.90
−1.28
IL2RG
aldesleukin, denileukin diftitox



common gamma chain



(Interleukin-2



receptor gamma



chain) (IL-2R gamma



chain) (CD132



antigen).


Ssc.15822.1.S1_at
Coagulation factor V
1.92
3.76
1.89
−1.75
F5
drotrecogin alfa



precursor (Activated



protein C cofactor).


Ssc.4756.1.A1_at
Adenosine A3
2.15
2.10
1.88
−1.81
ADORA3
adenosine, dyphylline, aminophylline,



receptor.





clofarabine, theophylline, caffeine


Ssc.12791.1.A1_at
3-hydroxy-3-
3.27
2.77
1.77
−2.56
HMGCR
aspirin/pravastatin, lovastatin/niacin,



methylglutaryl-





ezetimibe/simvastatin,



coenzyme A reductase





amlodipine/atorvastatin, fluvastatin,









cerivastatin, atorvastatin, pravastatin,









simvastatin, lovastatin, rosuvastatin


Ssc.818.1.S1_at
RAF proto-oncogene
−1.40
2.56
1.58
1.98
RAF1
sorafenib



serine/threonine-



protein kinase


Ssc.16823.1.S1_at
P2Y purinoceptor 12
1.38
1.19
1.41
1.11
P2RY12
prasugrel, AZD 6140 (Ticagrelor),



(P2Y12) (P2Y12





clopidogrel



platelet ADP



receptor)


Ssc.9565.1.S1_at
Interferon-gamma
2.92
1.63
1.41
−1.23
IFNGR1
interferon gamma-1b



receptor alpha chain



(CD119 antigen)


Ssc.1498.1.S1_at
Proteasome subunit
−1.81
1.19
1.38
5.94
PSMB5
bortezomib



beta type 5


Ssc.7111.1.A1_at
Ribonucleoside-
−13.13
4.08
1.37
1.67
RRM2
gemcitabine, triapine, hydroxyurea,



diphosphate





fludarabine phosphate



reductase M2 chain


Ssc.19700.1.S1_at
Serine/threonine
1.11
1.13
1.34
1.09
PPP3CB
ISAtx-247, tacrolimus, pimecrolimus,



protein phosphatase





cyclosporin A



2B catalytic



subunit, beta


Ssc.14258.1.S1_at
Amyloid beta A4
1.87
3.33
1.34
−1.02
APP
AAB-001 (Bapineuzumab)



protein


Ssc.6418.1.S1_at
Farnesyl-diphosphate
−1.25
2.31
1.33
1.08
FDFT1
TAK-475, zoledronic acid



farnesyltransferase


Ssc.5569.1.S1_at
Thyroid hormone
−10.22
1.26
1.26
6.49
THRA
3,5-diiodothyropropionic acid,



receptor alpha (C-





amiodarone, thyroxine, L-triiodothyronine



erbA-alpha) (c-erbA-



1)


Ssc.23234.1.S1_at
collagen, type XXIV,
−1.43
1.66
1.16
1.76
COL24A1
collagenase



alpha 1


Ssc.10142.1.A1_at
Dihydropyrimidine
2.06
2.17
1.13
−2.68
DPYD
eniluracil



dehydrogenase



[NADP+]


Ssc.3607.1.S1_at
Interferon-
2.28
4.65
1.11
−1.56
IFNAR2
interferon beta-1a, interferon alfa-2b,



alpha/beta receptor





interferon alfacon-1, PEG-interferon alfa-



beta chain





2a, interferon alfa-2a/ribavirin,









pegintron, interferon beta-1b, IFNA2A


Ssc.23505.1.S1_at
Amine oxidase
−1.86
2.17
1.08
1.20
MAOA
ladostigil, 1-ethylphenoxathiin 10,10-



[flavin-containing] A





dioxide, dextroamphetamine, procainamide,









tranylcypromine, phenelzine,









isocarboxazid, benzphetamine, N-(2-









indanyl)glycinamide


Ssc.28329.1.S1_at
DNA polymerase
1.14
1.19
1.07
5.25
POLB
nelarabine, clofarabine, stavudine,









trifluridine, vidarabine, zalcitabine,









entecavir


Ssc.25040.1.S1_at
Serine/threonine-
−3.75
1.11
1.06
−2.45
CHEK1
UCN-01 (7-hydroxystaurosporine)



protein kinase Chk1


Ssc.26379.1.S1_at
Glutamate [NMDA]
−1.32
1.37
1.03
−2.59
GRIN2C
dextromethorphan/guaifenesin,



receptor subunit





morphine/dextromethorphan, neramexane,



epsilon 3





SPM 927, bicifadine, delucemine, CR









2249, besonprodil, UK-240455, ketamine,









felbamate, memantine, orphenadrine,









cycloserine, N-(2-indanyl)glycinamide,









dextromethorphan, brompheniramine/









dextromethorphan/pseudoephedrine,









chlorpheniramine/dextromethorphan/









phenylephrine, carbinoxamine/









dextromethorphan/pseudoephedrine,









dextromethorphan/promethazine, 1-









aminocyclopropane-1-carboxylic acid


Ssc.14488.1.S1_at
Glutamate
−1.04
1.10
1.02
1.69
FOLH1
capromab pendetide



carboxypeptidase II
















TABLE 9







Upregulated gene targets at Days 21, 60 and 180 (relative to baseline) of PAH progression with available drugs
















Fold
Fold
Fold
Fold






Change
Change
Change
Change




D 7/
D 21/
D 60/
D 180/
Gene


Probe ID
Name
Base
Base
Base
Base
Symbol
Drugs

















Ssc.23793.1.S1_at
T-cell surface
−3.27
79.25
93.34
5.20
CD2
alefacept, siplizumab



antigen CD2


SscAffx.20.1.S1_at
T-cell surface
−2.19
14.07
10.96
3.62
CD3G
visilizumab, MT103



glycoprotein CD3



gamma chain


Ssc.19532.1.S1_at
Guanylate cyclase
−4.28
12.74
3.04
2.13
GUCY1B3
nitroglycerin, isosorbide-5-mononitrate,



soluble, beta-1





isosorbide dinitrate, nitroprusside,



chain





isosorbide dinitrate/hydralazine


Ssc.7176.1.A1_at
C-X-C chemokine
3.74
10.91
8.15
1.68
CXCR4
JM 3100 (1,1′-(1,4-



receptor type 4





phenylenebis(methylene))bis(1,4,8,11-



(CXC-R4) (CXCR-4)





tetraazacyclotetradecane)octahydrochloride









dihydrate)


Ssc.2714.1.S1_a_at
Proto-oncogene
−4.26
9.56
12.54
3.93
FYN
dasatinib



tyrosine-protein



kinase FYN


Ssc.10256.1.A1_at
cAMP-specific
−1.89
6.74
2.20
2.44
PDE4B
dyphylline, nitroglycerin, arofylline,



3′,5′-cyclic





tetomilast, L 869298, aminophylline,



phosphodiesterase





anagrelide, cilomilast, milrinone,



4B





rolipram, dipyridamole, L-826,141,









roflumilast, tolbutamide, theophylline,









pentoxifylline, caffeine


Ssc.12937.1.S1_at
Presenilin 1 (PS-1)
−14.09
6.21
2.48
3.79
PSEN1
(R)-flurbiprofen



(S182 protein).


Ssc.15932.1.S1_at
Integrin alpha-V
−6.15
5.79
2.94
3.14
ITGAV
abciximab, CNTO 95, EMD121974









(Cilengitide)


Ssc.26328.1.S1_at
C-C chemokine
−2.53
5.61
3.25
1.29
CCR5
maraviroc, vicriviroc, SCH 351125



receptor type 5



(CCR5)


Ssc.12845.1.S1_at
Cell division
−6.56
5.40
4.77
5.13
CDK6
PD-0332991, flavopiridol



protein kinase 6


Ssc.24528.1.S1_at
Angiotensin-
−1.61
5.01
2.33
4.76
ACE
pentopril, perindoprilat,



converting enzyme





amlodipine/benazepril,









lisinopril/hydrochlorothiazide,









benazepril, enalapril, perindopril,









captopril, enalapril/felodipine,









hydrochlorothiazide/moexipril,









benazepril/hydrochlorothiazide,









hydrochlorothiazide/quinapril,









fosinopril/hydrochlorothiazide,









captopril/hydrochlorothiazide,









enalapril/hydrochlorothiazide, ramipril,









moexipril, quinapril, lisinopril,









enalaprilat, trandolapril,









trandolapril/verapamil,









diltiazem/enalapril, fosinopril


Ssc.7130.1.S1_at
Phenylalanine-4-
4.70
4.71
11.30
1.48
PAH
(6R)-tetrahydrobiopterin



hydroxylase


Ssc.7111.1.A1_at
Ribonucleoside-
−13.13
4.08
1.37
1.67
RRM2
gemcitabine, triapine, hydroxyurea,



diphosphate





fludarabine phosphate



reductase M2 chain



(Ribonucleotide



reductase small



chain).


Ssc.9272.1.S1_at
Tumor-associated
1.81
3.94
176.50
2.07
TACSTD1
tucotuzumab celmoleukin



calcium signal



transducer 1 (EPCAM



antigen)


Ssc.15886.1.S1_at
Apopain (Caspase-
−3.02
3.64
2.31
2.29
CASP3
IDN-6556



3) (CASP-3)


Ssc.21108.1.S1_at
Complement C5
−17.35
3.21
618.80
9.28
C5
eculizumab


Ssc.3040.1.S1_at
Histone deacetylase
−3.24
2.79
4.94
4.72
HDAC2
tributyrin, PXD101, pyroxamide,



2 (HD2).





vorinostat, FR 901228


Ssc.20685.1.S1_at
Apoptosis regulator
−2.22
2.77
2.58
3.25
BCL2
oblimersen, (−)-gossypol



Bcl-2


Ssc.818.1.S1_at
RAF proto-oncogene
−1.40
2.56
1.58
1.98
RAF1
sorafenib



serine/threonine-



protein kinase


Ssc.13186.1.S1_at
Cell division
−1.08
2.38
4.34
1.24
CDK7
BMS-387032, flavopiridol



protein kinase 7


Ssc.6418.1.S1_at
Farnesyl-
−1.25
2.31
1.33
1.08
FDFT1
TAK-475, zoledronic acid



diphaosphate



farnesyltransferase


Ssc.23505.1.S1_at
Amine oxidase
−1.86
2.17
1.08
1.20
MAOA
ladostigil, 1-ethylphenoxathiin 10,10-



(flavin-containing)





dioxide, dextroamphetamine, procainamide,



A (Monoamine





tranylcypromine, phenelzine,



oxidase) (MAO-A).





isocarboxazid, benzphetamine, N-(2-









indanyl)glycinamide


Ssc.11302.1.S1_at
Collagen alpha
−1.80
2.02
2.06
1.26
COL3A1
collagenase



1(III) chain



precursor.


Ssc.18051.1.S1_at
cGMP-inhibited
−3.16
1.96
3.41
2.32
PDE3B
dyphylline, nitroglycerin, medorinone,



3′,5′-cyclic





aminophylline, cilostazol, dipyridamole,



phosphodiesterase B





amrinone, tolbutamide, theophylline,









pentoxifylline


Ssc.23234.1.S1_at
collagen, type
−1.43
1.66
1.16
1.76
COL24A1
collagenase



XXIV, alpha 1


Ssc.5569.1.S1_at
Thyroid hormone
−10.22
1.26
1.26
6.49
THRA
3,5-diiodothyropropionic acid,



receptor alpha





amiodarone, thyroxine, L-triiodothyronine


Ssc.10360.1.S1_at
B-Raf proto-
−2.15
1.26
3.09
1.36
BRAF
sorafenib



oncogene



serine/threonine-



protein kinase


Ssc.5045.1.S1_at
3-beta-
−1.55
1.24
2.19
2.08
EBP
SR 31747



hydroxysteroid-



delta(8),delta(7)-



isomerase


Ssc.1498.1.S1_at
Proteasome subunit
−1.81
1.19
1.38
5.94
PSMB5
bortezomib



beta type 5


Ssc.28329.1.S1_at
DNA polymerase beta
1.14
1.19
1.07
5.25
POLB
nelarabine, clofarabine, stavudine,









trifluridine, vidarabine, zalcitabine,









entecavir


Ssc.16823.1.S1_at
P2Y purinoceptor 12
1.38
1.19
1.41
1.11
P2RY12
prasugrel, AZD 6140, clopidogrel



(P2Y12) (P2Y12



platelet ADP



receptor)



(P2Y(ADP))


Ssc.19691.1.S1_at
Platelet-activating
1.59
1.16
3.01
1.47
PLA2G7
darapladib



factor



acetylhydrolase


Ssc.19700.1.S1_at
Serine/threonine
1.11
1.13
1.34
1.09
PPP3CB
ISAtx-247, tacrolimus, pimecrolimus,



protein phosphatase





cyclosporin A



2B catalytic



subunit, beta


Ssc.14488.1.S1_at
Glutamate
−1.04
1.10
1.02
1.69
FOLH1
capromab pendetide



carboxypeptidase II
















TABLE 10







Upregulated gene targets at both Days 7 and 21 (relative to baseline) of PAH progression with available drugs
















Fold
Fold
Fold
Fold






Change
Change
Change
Change




D 7/
D 21/
D 60/
D 180/
Gene


Probe ID
Name
Base
Base
Base
Base
Symbol
Drugs

















Ssc.11381.1.S1_at
Interferon-alpha/beta receptor
10.45
8.08
2.61
−1.30
IFNAR1
interferon beta-1a,



alpha chain





interferon alfa-2b,









interferon alfacon-1, PEG-









interferon alfa-2a,









interferon alfa-2a/ribavirin,









pegintron, interferon beta-









1b, IFNA2A


Ssc.16186.1.S1_at
T-cell surface glycoprotein
9.00
3.12
2.12
−5.66
CD3E
visilizumab, MT103,



CD3 epsilon chain





muromonab-CD3


Ssc.19673.1.S1_at
T-cell surface glycoprotein
6.40
2.70
2.03
−11.77
CD3D
visilizumab, MT103



CD3 delta chain


Ssc.17155.1.A1_at
heparanase; heparanase-1
4.81
5.38
2.98
−1.83
HPSE
heparanase inhibitor PI-88


Ssc.7130.1.S1_at
Phenylalanine-4-hydroxylase
4.70
4.71
11.30
1.48
PAH
(6R)-tetrahydrobiopterin


Ssc.26351.1.S1_at
cAMP-specific 3′,5′-cyclic
4.67
4.99
3.61
−1.15
PDE4D
dyphylline, nitroglycerin,



phosphodiesterase 4D





arofylline, tetomilast, L869298,









aminophylline,









anagrelide, cilomilast,









milrinone, rolipram,









dipyridamole, L-826,141,









roflumilast, tolbutamide,









theophylline, pentoxifylline,









caffeine


Ssc.7176.1.A1_at
C-X-C chemokine receptor
3.74
10.91
8.15
1.68
CXCR4
JM 3100



type 4 (CXC-R4) (CXCR-4)


Ssc.15801.1.A1_at
Protein kinase C, beta
3.36
6.36
3.53
−4.98
PRKCB1
enzastaurin, ruboxistaurin


Ssc.12791.1.A1_at
3-hydroxy-3-methylglutaryl-
3.27
2.77
1.77
−2.56
HMGCR
aspirin/pravastatin,



coenzyme A reductase





lovastatin/niacin,









ezetimibe/simvastatin,









amlodipine/atorvastatin,









fluvastatin, cerivastatin,









atorvastatin, pravastatin,









simvastatin, lovastatin,









rosuvastatin


Ssc.11147.1.S1_at
Aldehyde dehydrogenase,
3.18
1.13
2.00
−1.68
ALDH2
disulfiram, chlorpropamide



mitochondrial


Ssc.9565.1.S1_at
Interferon-gamma receptor
2.92
1.63
1.41
−1.23
IFNGR1
interferon gamma-1b



alpha chain


Ssc.3607.1.S1_at
Interferon-alpha/beta receptor
2.28
4.65
1.11
−1.56
IFNAR2
interferon beta-1a,



beta





interferon alfa-2b,









interferon alfacon-1, PEG-









interferon alfa-2a,









interferon alfa-2a/ribavirin,









pegintron, interferon beta-









1b, IFNA2A


Ssc.4756.1.A1_at
Adenosine A3 receptor.
2.15
2.10
1.88
−1.81
ADORA3
adenosine, dyphylline,









aminophylline, clofarabine,









theophylline, caffeine


Ssc.10142.1.A1_at
Dihydropyrimidine
2.06
2.17
1.13
−2.68
DPYD
eniluracil



dehydrogenase [NADP+]


Ssc.15822.1.S1_at
Coagulation factor V
1.92
3.76
1.89
−1.75
F5
drotrecogin alfa


Ssc.14258.1.S1_at
Amyloid beta A4 protein
1.87
3.33
1.34
−1.02
APP
AAB-001



precursor (APP) (ABPP)


Ssc.15878.1.S1_at
Serine/threonine protein
1.85
3.22
3.62
−1.49
PPP3CA
ISAtx-247, tacrolimus,



phosphatase 2B catalytic





pimecrolimus, cyclosporin A



subunit, alpha


Ssc.9272.1.S1_at
Tumor-associated calcium
1.81
3.94
176.50
2.07
TACSTD1
tucotuzumab celmoleukin



signal transducer 1 (EPCAM



antigen)


Ssc.19691.1.S1_at
Platelet-activating factor
1.59
1.16
3.01
1.47
PLA2G7
darapladib



acetylhydrolase


Ssc.30147.1.A1_at
Fibroblast growth factor
1.56
1.13
−1.05
−1.18
FGFR2
palifermin



receptor 2


Ssc.16823.1.S1_at
P2Y purinoceptor 12 (P2Y12)
1.38
1.19
1.41
1.11
P2RY12
prasugrel, AZD 6140,



(P2Y12 platelet ADP receptor)





clopidogrel


Ssc.15999.1.A1_at
Vascular endothelial growth
1.24
1.24
18.52
−11.02
KDR
AEE 788, sunitinib, AZD



factor receptor 2





2171, pazopanib, XL647, CEP









7055, BMS-582664, KRN-951,









vatalanib, sorafenib,









vandetanib, pegaptanib


Ssc.17224.1.S1_at
Toll-like receptor 8
1.17
6.49
3.13
−1.52
TLR6
resiquimod


Ssc.7297.1.S1_at
Amine oxidase
1.16
6.42
7.02
−1.13
MAOB
safinamide, ladostigil,









rasagiline, selegiline,









dextroamphetamine,









procainamide,









tranylcypromine, phenelzine,









isocarboxazid, benzphetamine


Ssc.28329.1.S1_at
DNA polymerase beta
1.14
1.19
1.07
5.25
POLB
nelarabine, clofarabine,









stavudine, trifluridine,









vidarabine, zalcitabine,









entecavir


Ssc.19700.1.S1_at
Serine/threonine protein
1.11
1.13
1.34
1.09
PPP3CB
ISAtx-247, tacrolimus,



phosphatase 2B catalytic





pimecrolimus, cyclosporin A



subunit, beta


Ssc.8726.1.A1_at
Amidophosphoribosyltransferase
1.03
1.24
4.16
−1.11
PPAT
6-mercaptopurine,



precursor





thioguanine, azathioprine
















TABLE 11







Animal number, days after post-shunt PAH creation


surgery, and pulmonary arterial pressure (PAP).












Animal
Day
PAP
PAP mean











Pig 19 Timecourse












P19
Day 0
28/1 
26



P19
Day 10
22/17
19



P19
Day 24
76/29
47



P19
Day 59
89/50
58



P19
Day 94
70/18
54







Pig 20 Timecourse












P20
Day 0
20/11
16



P20
Day 6
19/15
16



P20
Day 21
20/15
17



P20
Day 55
23/15
19



P20
Day 83
62/17
45



P20
Day 104
116/72 
104



P20
Day 140
92/40
81







Normal (Normal Pressure & Flow)












P19
Day 0
28/1 
26



P20
Day 0
20/11
16







HFLP (High Flow Low Pressure)












P19
Day 10
22/17
19



P20
Day 6
19/15
16



P20
Day 21
20/15
17



P20
Day 55
23/15
19







HFHP (High Flow High Pressure)












P19
Day 24
76/29
47



P19
Day 59
89/50
58



P19
Day 94
70/18
54



P20
Day 83
62/17
45



P20
Day 104
116/72 
104



P20
Day 140
92/40
81

















TABLE 12







Significantly differently expressed downregulated microRNAs HFHP


(High Flow High Pressure) vs. normal.


Downregulated microRNA HFHP vs. Norm (p < .05)











Illumina ID
Normal
HFHP
HFLP
miRNA Symbol














ILMN_3167128
32.58
−2.36
2.75
solexa-603-






1846


ILMN_3167515
4183.74
42.62
142.81
hsa-miR-586


ILMN_3168604
31.83
−2.01
0.90
hsa-miR-1201


ILMN_3167691
127.02
1.76
1358.98
hsa-miR-33a


ILMN_3167249
229.25
18.22
511.84
HS_56


ILMN_3167753
114.97
14.32
66.23
hsa-miR-






520d:9.1


ILMN_3168215
37.30
8.98
3110.35
hsa-miR-521


ILMN_3168168
32.58
1.72
28.59
hsa-miR-519a


ILMN_3168054
3916.21
79.38
14.02
HS_134


ILMN_3168235
58.82
6.34
2.94
HS_169


ILMN_3168335
15.54
−2.85
26.65
HS_221


ILMN_3167393
90.38
5.18
5.54
hsa-miR-496


ILMN_3168678
837.14
14.23
777.94
hsa-miR-935


ILMN_3167175
8796.46
1274.47
88.95
hsa-miR-542-5p


ILMN_3168905
92.30
5.07
33.55
solexa-5620-






151


ILMN_3168648
593.72
46.29
812.05
hsa-miR-99a


ILMN_3167761
37.30
16.59
0.17
hsa-miR-212


ILMN_3168709
1281.24
218.10
80.10
hsa-let-7f-2


ILMN_3168446
8875.62
343.70
546.81
hsa-miR-494


ILMN_3168663
31.00
3.29
18.23
hsa-miR-1321


ILMN_3168597
99.25
14.28
43.96
hsa-miR-219-2-






3p


ILMN_3166971
1310.30
311.18
924.85
hsa-miR-95


ILMN_3167491
3060.68
925.46
1647.50
hsa-miR-






128b:9.1


ILMN_3168654
740.78
96.90
957.01
hsa-miR-33a


ILMN_3167052
370.00
45.81
234.11
hsa-miR-495


ILMN_3167337
177.30
43.83
27.93
hsa-miR-1229


ILMN_3168827
569.48
117.37
51.85
hsa-miR-1205


ILMN_3167328
6444.52
2162.76
2119.65
hsa-miR-524-3p


ILMN_3167952
8724.37
2076.18
926.06
HS_150


ILMN_3168798
376.77
151.44
1348.57
hsa-miR-135a


ILMN_3168558
211.48
68.62
28.31
hsa-miR-483-5p


ILMN_3168039
9629.83
3219.90
7248.74
hsa-miR-






124a:9.1


ILMN_3168755
233.36
82.45
332.03
hsa-miR-29b-1


ILMN_3168540
493.90
161.33
304.45
hsa-miR-548c-






5p


ILMN_3168265
11306.19
5572.32
6108.39
hsa-miR-551a


ILMN_3168481
8687.78
4563.60
5504.04
hsa-miR-377


ILMN_3168882
12023.57
6677.06
8627.69
hsa-miR-1304
















TABLE 13







Significantly differently expressed upregulated microRNAs HFHP


(High Flow High Pressure) vs. normal.


Upregulated microRNA HFHP vs. Norm (p < .05)











Illumina ID
Normal
HFHP
HFLP
miRNA Symbol














ILMN_3168350
−6.40
2772.39
12.69
hsa-miR-520g


ILMN_3168706
−3.62
1700.55
8.11
hsa-miR-331-5p


ILMN_3167244
−4.11
1534.57
−4.19
hsa-miR-410


ILMN_3168710
−3.08
1499.40
2147.63
hsa-let-7d


ILMN_3168167
−4.14
1144.02
558.78
hsa-miR-187


ILMN_3168672
−4.20
941.07
162.41
hsa-miR-16-2


ILMN_3168870
−8.25
912.52
8.99
hsa-miR-130a


ILMN_3168639
−4.96
728.32
−3.51
hsa-miR-548n


ILMN_3168719
−1.17
380.69
−2.12
hsa-miR-127-5p


ILMN_3168890
−4.11
343.04
530.05
solexa-2580-






353


ILMN_3168217
−5.60
304.34
−1.25
HS_206


ILMN_3167088
−5.06
303.57
−0.34
hsa-miR-663


ILMN_3168911
−1.32
235.62
61.24
solexa-7534-






111


ILMN_3168732
−0.63
216.74
12.96
hsa-let-7g


ILMN_3167993
−6.45
192.76
237.96
HS_157


ILMN_3167193
−7.25
151.36
2130.07
hsa-miR-610


ILMN_3167879
−4.09
111.71
11.99
HS_251.1


ILMN_3168031
−4.54
52.02
15.76
hsa-miR-519e


ILMN_3168818
−4.09
20.75
−0.83
hsa-miR-1237


ILMN_3168241
−2.10
18.57
649.52
hsa-miR-1185


ILMN_3167470
−4.18
12.39
7.90
HS_151.1


ILMN_3167512
−1.69
11.79
9.99
HS_135


ILMN_3168895
−2.86
7.81
0.75
solexa-3126-






285


ILMN_3167158
−0.63
3.36
739.08
hsa-miR-30a


ILMN_3168722
1.26
529.41
430.69
hsa-miR-192


ILMN_3167039
17.25
1036.96
883.92
hsa-miR-568


ILMN_3168680
2.62
148.59
54.43
hsa-miR-1203


ILMN_3167223
381.67
5756.85
4105.59
hsa-miR-28-5p


ILMN_3167361
21.39
259.94
255.04
HS_262.1


ILMN_3167684
11.78
80.14
21.38
HS_170


ILMN_3168760
11.78
80.09
26.17
hsa-miR-1273


ILMN_3167275
39.19
146.84
1900.87
hsa-miR-602


ILMN_3168240
1613.60
5725.95
4943.62
hsa-miR-374a


ILMN_3168589
597.66
1739.42
928.77
hsa-miR-29a
















TABLE 14







Significantly differently expressed downregulated microRNAs HFLP


(High Flow Low Pressure) vs. normal.


Downregulated microRNA HFLP vs. Norm (p < .05)











Illumina ID
Normal
HFLP
HFHP
Gene Symbol














ILMN_3167209
27.46
−3.19
1350.01
HS_104


ILMN_3168537
38.77
−0.76
57.24
hsa-miR-548a-5p


ILMN_3167655
351.30
0.20
74.35
hsa-miR-556-5p


ILMN_3168235
58.82
2.94
6.34
HS_169


ILMN_3167800
13.08
−2.83
1036.31
HS_140


ILMN_3167175
8796.46
88.95
1274.47
hsa-miR-542-5p


ILMN_3168054
3916.21
14.02
79.38
HS_134


ILMN_3167761
37.30
0.17
16.59
hsa-miR-212


ILMN_3167509
17.25
−1.53
17.72
hsa-miR-363


ILMN_3167707
130.17
1.49
42.39
HS_59


ILMN_3167515
4183.74
142.81
42.62
hsa-miR-586


ILMN_3168446
8875.62
546.81
343.70
hsa-miR-494


ILMN_3168827
569.48
51.85
117.37
hsa-miR-1205


ILMN_3168709
1281.24
80.10
218.10
hsa-let-7f-2


ILMN_3168558
211.48
28.31
68.62
hsa-miR-483-5p


ILMN_3167952
8724.37
926.06
2076.18
HS_150


ILMN_3167337
177.30
27.93
43.83
hsa-miR-1229


ILMN_3168305
31.00
5.36
34.52
HS_156


ILMN_3168490
67.94
18.69
106.29
hsa-miR-619


ILMN_3168573
776.09
190.47
805.44
hsa-miR-10b


ILMN_3168586
887.48
304.35
617.25
hsa-miR-371-5p
















TABLE 15







Significantly differently expressed upregulated microRNAs HFLP


(High Flow Low Pressure) vs. normal.


Upregulated microRNA HFLP vs. Norm (p < .05)











Illumina ID
Normal
HFLP
HFHP
miRNA Symbol














ILMN_3168010
−9.81
2363.55
689.66
HS_70


ILMN_3168710
−3.08
2147.63
1499.40
hsa-let-7d


ILMN_3168167
−4.14
558.78
1144.02
hsa-miR-187


ILMN_3168890
−4.11
530.05
343.04
solexa-2580-353


ILMN_3167993
−6.45
237.96
192.76
HS_157


ILMN_3168911
−1.32
61.24
235.62
solexa-7534-111


ILMN_3168870
−8.25
8.99
912.52
hsa-miR-130a


ILMN_3167512
−1.69
9.99
11.79
HS_135


ILMN_3168722
1.26
430.69
529.41
hsa-miR-192


ILMN_3167720
2.62
145.01
147.62
hsa-miR-154


ILMN_3167062
78.98
2184.01
1423.21
hsa-miR-151:9.1


ILMN_3168680
2.62
54.43
148.59
hsa-miR-1203


ILMN_3167778
24.39
206.06
81.33
hsa-miR-525-3p


ILMN_3167749
37.30
226.26
272.25
HS_199
















TABLE 16







Significantly differently expressed upregulated


microRNAs HFHP vs. HFLP.


Upregulated microRNA HFHP vs. HFLP (p < .05)











Illumina ID
Normal
HFHP
HFLP
miRNA Symbol














ILMN_3167244
−4.11
1534.57
−4.19
has-miR-410


ILMN_3168639
−4.96
728.32
−3.51
has-miR-548n


ILMN_3168537
38.77
57.24
−0.76
has-miR-548a-5p


ILMN_3168613
4.53
18.13
−0.99
has-miR-185


ILMN_3168047
34.59
10.25
−4.94
HS_3


ILMN_3167440
71.49
−0.51
−4.89
HS_67


ILMN_3168585
45.00
97.09
2.43
has-miR-1250


ILMN_3168543
140.56
2778.92
47.17
has-miR-5481


ILMN_3168221
52.52
216.12
13.76
has-miR-548c-3p


ILMN_3167831
31.83
186.98
12.94
has-miR-520d-5p


ILMN_3167105
292.19
174.71
25.34
has-miR-208b


ILMN_3167313
475.92
793.85
135.08
HS_200


ILMN_3168634
892.54
1830.74
479.17
has-miR-218-1


ILMN_3168247
390.00
300.41
111.54
has-miR-643
















TABLE 17







Significantly differently expressed downregulated


microRNAs HFHP vs. HFLP.


Downregulated microRNA HFHP vs. HFLP (p < .05)











Illumina ID
Normal
HFHP
HFLP
miRNA Symbol














ILMN_3167778
24.39
81.33
206.06
hsa-miR-525-3p


ILMN_3167052
370.00
45.81
234.11
hsa-miR-495


ILMN_3168052
176.33
116.43
480.71
HS_250


ILMN_3168863
9.59
1.11
46.30
hsa-miR-933


ILMN_3168848
13.53
8.90
475.98
hsa-miR-1287


ILMN_3168750
784.33
2850.15
8118.48
hsa-miR-1308


ILMN_3168348
10.81
9.66
553.87
hsa-miR-133b


ILMN_3166995
1.97
1.33
254.82
HS_215


ILMN_3167545
42.85
10.92
23.89
HS_115


ILMN_3168819
756.53
1345.27
5334.48
hsa-miR-151-5p


ILMN_3167249
229.25
18.22
511.84
HS_56


ILMN_3168010
−9.81
689.66
2363.55
HS_70


ILMN_3168215
37.30
8.98
3110.35
hsa-miR-521








Claims
  • 1. A method of diagnosing a vascular-related disease in an individual comprising the steps of: a) identifying at least one gene that is upregulated or downregulated in the vascular-related disease comprising the steps of: 1) obtaining a biopsy sample from the individual's artery during progression of the vascular-related disease;2) obtaining an artery sample from a non-diseased control;3) extracting RNA from the samples in steps 1) and 2);4) obtaining gene products from the RNA extracted in steps 3); and5) comparing gene expression levels from the biopsy sample with the non-diseased control; andb) associating the genes upregulated in the biopsy sample with an inhibitor of the gene products for administration to the individual and genes downregulated in the biopsy sample with a promoter of the gene products for administration to the individual.
  • 2. The method of claim 1, wherein the vascular-related disease is pulmonary arterial hypertension.
  • 3. The method of claim 1, wherein the biopsy sample is extracted using an endoarterial catheter.
  • 4. A method of identifying microRNA dysregulated in an individual having a vascular-related disease comprising the steps of: a) obtaining a biopsy sample from the individual's artery during progression of the vascular-related disease;b) obtaining an artery sample from a non-diseased control;c) extracting RNA from the samples in steps a) and b);d) converting the RNA to cDNA;e) comparing levels of microRNA expression from the biopsy sample with the non-diseased control; andf) identifying the microRNA dysregulated in the vascular-related disease relative to baseline.
  • 5. The method of claim 4, wherein the vascular-related disease is pulmonary arterial hypertension.
  • 6. The method of claim 4, wherein the microRNA is measured according to stages of progression of the vascular-related disease.
  • 7. A use of targeting microRNAs in the preparation of a medicament for the treatment of a vascular-related disease comprising the following steps: a) assessing a stage of the vascular-related disease in the individual;b) identifying whether microRNAs are upregulated or downregulated;c) selecting the microRNAs to target based on the stage of the vascular-related disease and whether the microRNAs are upregulated or downregulated; andd) administering an agent known to inhibit an upregulated microRNA or an agent known to promote downregulated microRNA to the individual,
  • 8. The use of claim 7, wherein the vascular-related disease is pulmonary arterial hypertension.
  • 9. The use of claim 7, wherein the microRNAs to target are selected from the group consisting of Tables 12-17.
  • 10. The use of claim 7, wherein the stage of the vascular-related disease of one of high flow and high pressure within the artery of the individual.
  • 11. The use of claim 10, wherein the upregulated microRNAs to inhibit under the stage of high flow and high pressure comprise at least one member selected from the group consisting of hsa-miR-520g, hsa-miR-331-5p, hsa-miR-410, has-let-7d, hsa-miR-187, hsa-miR-16-2, hsa-miR-130a, hsa-miR-548n, hsa-miR-127-5p, solexa-2580-353, HS_206, hsa-miR-663, solexa-7534-111, hsa-let-7g, HS_157, hsa-miR-610, HS_251.1, hsa-miR-519e, hsa-miR-1237, hsa-miR-1185, HS_151.1, HS_135, solexa-3126-285, hsa-miR-30a, hsa-miR-192, hsa-miR-568, hsa-miR-1203, hsa-miR-28-5p, HS_262.1, HS_170, hsa-miR-1273, hsa-miR-602, hsa-miR-374a and hsa-miR-29a.
  • 12. The use of claim 7, wherein the stage of the vascular-related disease is one of high flow and low pressure within the artery of the individual.
  • 13. The use of claim 12, wherein the upregulated microRNAs to inhibit under the stage of high flow and low pressure comprise at least one member selected from the group consisting of HS_70, hsa-let-7d, hsa-miR-187, solexa-2580-353, HS_157, solexa-7534-111, hsa-miR-130a, HS_135, hsa-miR-192, hsa-miR-154, hsa-miR-151:9.1, hsa-miR-1203, hsa-miR-525-3p, and HS_199.
  • 14. The use of claim 10, wherein the downregulated microRNAs to promote under the stage of high flow and high pressure comprise at least one member selected from the group consisting of solexa-603-1846, hsa-miR-586, hsa-miR-1201, hsa-miR-33a, HS_56, hsa-miR-520d:9.1, hsa-miR-521, hsa-miR-519a, HS_134, HS_169, HS_221, hsa-miR-496, hsa-miR-935, hsa-miR-542-5p, solexa-5620-151, hsa-miR-99a, hsa-miR-212, hsa-let-7f-2, hsa-miR-494, hsa-miR-1321, hsa-miR-219-2-3p, hsa-miR-95, hsa-miR-128b:9.1, hsa-miR-33a, hsa-miR-495, hsa-miR-1229, hsa-miR-1205, hsa-miR-524-3p, HS_150, hsa-miR-135a, hsa-miR-483-5p, hsa-miR-124a:9.1, hsa-miR-29b-1, hsa-miR548c-5p, hsa-miR-551a, hsa-miR-377 and hsa-mir-1304.
  • 15. The use of claim 12, wherein the downregulated microRNAs to promote under the stage of high flow and low pressure comprise at least one member selected from the group consisting of HS_104, hsa-miR-548a-5p, hsa-miR-556-5p, HS_169, HS_140, hsa-miR-542-5p, HS_134, hsa-miR-212, hsa-miR-363, HS_59, hsa-miR-586, hsa-miR-494, hsa-miR-1205, hsa-let-7f-2, hsa-miR-483-5p, HS_150, hsa-miR-1229, HS_156, hsa-miR-619, hsa-miR-10b and hsa-miR-371-5p.
  • 16. A method of diagnosing an individual having a vascular-related disease according to claim 1, further wherein the individual is categorized based on progression of the vascular-related disease.
  • 17. The method of claim 16, wherein the progression of the vascular-related disease is selected from the group consisting of early stage, mid stage and late stage.
  • 18. The method of claim 1, wherein the diagnosing of the individual may be modified over the course of disease progression.
CROSS-REFERENCES

This application claims the benefit of priority of U.S. Provisional Application Ser. No. 61/040,065, filed on Mar. 27, 2008, the disclosure of which is hereby incorporated by referenced in its entirety.

Provisional Applications (1)
Number Date Country
61040065 Mar 2008 US
Divisions (2)
Number Date Country
Parent 14294329 Jun 2014 US
Child 15354303 US
Parent 12934950 Dec 2010 US
Child 14294329 US
Continuations (1)
Number Date Country
Parent 15354303 Nov 2016 US
Child 16908540 US