GenProMarkers™, Inc.

Microarray, Bioinformatics and Systems Biology for Discovery of Gene and Protein Biomarkers

Biomarkers

A biomarker in the biomedical field is a substance that has a characteristic feature as an objective indicator of a biological state, such as normal physiological processes, biochemical pathways, pathologic processes, or pharmacologic responses to a therapeutic intervention.  Gene and protein biomarkers refers DNA, RNA or protein with such characteristics.  Diseases are usually complex and characterized by multiple biomarkers in the cell-specific and stage-specific fashion.

 

Diagnostic Biomarkers in Brain Tissue

Posttraumatic Stress Disorder (PTSD) is a complex mental disorder that can develop in response to a traumatic event such as a motor vehicle accident, rape, combat exposure or natural disaster.  The National Vietnam Veterans Readjustment Study estimated that 53.4% of US male veterans of the Vietnam War developed full or partial PTSD and 15.2% still suffered from the disorder in 1990.  The application of conservative procedures for analysis led Dohrenwend et al to document that 18.7% of male veterans developed war-related PTSD during their life time and 9.1% were still suffering from PTSD 11 to 12 years after the war.  In the general population, the estimated lifetime prevalence of PTSD is 7.8% in adult Americans, with women having a 2.3-fold higher prevalence than men.  PTSD is associated with decreased activity in the dorsolateral prefrontal cortex (DLPFC), the brain region that regulates working memory and preparation and selection of fear responses.  We investigated gene expression profiles in DLPFC Brodmann area (BA) 46 of postmortem patients with and without PTSD using hMitChip3.  Our study revealed PTSD-specific expression fingerprints that can essentially distinguish the PTSD DLPFC BA46 brains from controls.

(A) Dendrogram of unsupervised cluster of the PTSD brain (P) and control samples (N); (B) Dendrograms and heat maps of 119 (±>1.25, p<0.05) and (C) 42 (±>1.60, p<0.05) dysregulated genes across all of these 12 BA46 samples. Green: down-regulation; red: up-regulation; black: no change.  The color map indicates degrees of up- and down-regulation of gene expression.

 

Diagnostic Biomarkers Specific to Infectious Agents

We used cDNA microarrays to identify signature genes and expression patterns, in mice in response to infections with influenza virus A/PR/8/34 (H1N1) and Streptococcus pneumoniae.  Expression microarray analysis showed up-regulation and down-regulation of many genes involved in the defense, inflammatory response and intracellular signaling pathways including chemokine, apoptosis, MAPK, Notch, Jak-STAT, T-cell receptor and complement and coagulation cascades.  Our results revealed signature patterns of gene expression in mice infected with two different classes of pathogens: influenza virus A and S. pneumoniae. Quantitative real-time RT-PCR results confirmed microarray results for most of the genes tested. These studies document clear differences in gene expression profiles between mice infected with influenza virus A and S. pneumoniae.  Identification of genes that are differentially expressed after respiratory infections can provide insights into the mechanisms by which the host interacts with different pathogens, useful information about stage of diseases and selection of suitable targets for early diagnosis and treatments.  The advantage of this novel approach is that the detection of pathogens is based on the differences in host gene expression profiles in response to different pathogens.

Distribution of functions of genes that were differentially expressed in response to infection of mice with influenza virus A/PR/8/34 or Streptococcus pneumoniae.

 

Signature patterns of gene expression in mice in response to influenza virus A/PR/8/34 and Streptococcus pneumonia. Twenty-eight differentially expressed genes were selected to show the difference of gene expression patterns between mice infected with influenza virus A/PR/8/34 and Streptococcus pneumoniae at day 1. The relative fold changes for each gene were used for comparison.

 

Diagnostic Biomarkers in Peripheral Lymphocytes

Age-related macular degeneration (AMD) is the leading cause of visual loss among elderly persons and has a significant social and economic impact.  Collaborating with the NIH/NEI investigators, our pilot study using peripheral lymphocytes from AMD patients and control subjects have successfully identified gene expression patterns that distinguish the patients from controls, even though more samples are needed to complete this study.

 

Dendrograms and heat maps that demonstrate the different expression patters of the genes in peripheral lymphocytes of patients with age-related macular degeneration.  (A) 55 differentially expressed genes between the patient lymphocytes and controls.   (B) 26 differentially expressed genes between these two groups.  Red: up-regulated genes; green: down-regulated genes; black: no change.

 












Therapeutic Biomarkers in Cancer Cells

Human malignant melanoma (MM) has poor prognosis because of resistance to apoptosis and therapy.  We identified the expression profile of 1,037 mitochondria-focused genes and 84 survival-apoptosis genes in 21 MM cell lines and 3 normal melanocyte controls using hMitChip3 cDNA microarrays.  Unsupervised hierarchical clustering analysis of 1,037 informative genes, and 84 survival-apoptosis genes as well, classified these MM cell lines into type A (n=12) and type B (n=9).  355 of 1,037 (34.2%) genes displayed significant (p£0.030, FDR£3.68%) differences (± ≥2.0-fold) in average expression, with 197 genes higher and 158 genes lower in type A than in type B.  Out of 84 genes with known survival-apoptosis functions, 38 (45.2%) displayed the significant (p<0.001, FDR <0.15%) difference.  Antiapoptotic (BCL2, BCL2A1, PPARD and RAF1), antioxidant (MT3, PRDX5, PRDX3, GPX4, GLRX2 and GSR) and proapoptotic (BAD, BNIP1, APAF1, BNIP3L, CASP7, CYCS, CASP1 and VDAC1) genes expressed at higher levels in type A than in type B; whereas the different set of antiapoptotic (PSEN1, PPP2CA, API5, PPP2R1B, PPP2R1A and FIS1), antioxidant (HSPD1, GSS, SOD1, ATOX1 and CAT) and proapoptotic (ENDOG, BAK1, CASP2, CASP4, PDCD5, HTRA2, SEPT4 TNFSF10 and PRODH,) genes expressed at lower levels in type A than in type B (Fig. 23).  Microarray data was validated by qRT-PCR.  These results demonstrated the presence of 2 types of MM, each with a specific set of dysregulated survival-apoptosis genes, which may prove useful for development of new molecular targets for therapeutic intervention and novel diagnostic biomarkers for treatment and prognosis of MM.

 

Biological process, molecular function, expression pattern and statistics of 38 dysregulated anti-apoptotic, antioxidant and pro-apoptotic genes that regulate survival-apoptosis of cells

 

Therapeutic Biomarkers in Brain Tissue

There is no effective therapeutic modality for posttraumatic stress disorder (PTSD).  Mitochondrial dysfunctions are believed to be key components in stress related mental disorders.  In the brain of PTSD patients, the decreased activity has been associated to the dorsolateral prefrontal cortex (DLPFC), the brain region that regulates working memory and preparation and selection of fear responses.  We investigated gene expression profiles in DLPFC Brodmann area (BA) 46 of postmortem patients with (n=6) and without PTSD (n=6) using human mitochondria-focused cDNA microarrays.  Our study revealed PTSD-specific expression fingerprints of 800 informative mitochondria-focused genes across all of these 12 BA46 samples, and 119 (±>1.25, p<0.05) and 42 (±>1.60, p<0.05) dysregulated genes between the PTSD and control samples.  Quantitative RT-PCR validated the microarray results.  These fingerprints can essentially distinguish the PTSD DLPFC BA46 brains from controls.  Of the 119 dysregulated genes (±≥125%, p<0.05), the highest percentages were associated with mitochondrial dysfunction (4.8%, p=6.61x10-6), oxidative phosphorylation (3.8%, p=9.04x10-4), cell survival-apoptosis (25.2%, p<0.05) and neurological diseases (23.5%, p<0.05).  Fifty (50) dysregulated genes were present in the molecular networks that are known to be involved in neuronal function-survival and contain 7 targets for neuropsychiatric drugs.  Thirty (30) of the dysregulated genes are associated with a number of neuropsychiatric disorders.  Our results indicate mitochondrial dysfunction in the PTSD DLPFC BA46 and provide the expression fingerprints that may ultimately serve as biomarkers for PTSD diagnosis and the drugs and molecular targets that may prove useful for development of remedies for prevention and treatment of PTSD

The molecular networks for neuron function and survival with seven targets of known neuropsychiatric drugs.  The networks have a total of 75 elements including 27 (36%) upregulated genes, 27 (36%) downregulated genes and 21 (28%) unchanged ones.  Twenty-one elements in white color include 7 genes present and 11 genes absent in the hMitChip3 microarray, and 3 small molecules.  The symbols in Legend illustrate the networks.  The genes in the blue boxes are the known targets for neuropsychiatric drugs.  For example: the ESR2 is a target of 17b-estradiol or related ligands.  The APP is a target for Bapineuzumab (AAB-001) that is currently used for the Phase 3 clinical trials for the treatment of patients with Alzheimer’s disease.    The ESR2 is a target for Tamoxifen that is used for the treatment of mania in patients with bipolar disorder.  The PRKCD is a target for both Tamoxifen, and rottlerin that has been used in preclinical treatment of Parkinson’s disease.  The PP2A is a target for Fostriecin that antagonize dopamine activities.  The VAMP1 is a target of the neurotoxin protein Dysport that is used in minute doses to treat painful muscle spasms.  The SLC1A6 is a target of Riluzole used to treat amyotrophic sclerosis.  The UCP2 is a target for protection of dopaminergic neurons from oxidative stress caused by 1,2,3,6-methyl-phenyl-tetrahydropyridine (MPTP) toxicity.