SYSTEMS AND METHODS FOR IMPROVING BIOMARKER AVAILABILITY
Systems and Methods for Improving Biomarker Availability. In at least one embodiment of a computer-implemented method of improving diagnostic marker availability, the method comprises the steps of introducing a predetermined diagnostic marker for cancer into a plurality of detection sites of a detection platform, introducing a stabilization agent into each of the plurality of detection sites containing the predetermined diagnostic marker for cancer, introducing a detection agent into each of the plurality of detection sites having a stabilized diagnostic agent, determining a binding characteristic of the detection agent and the stabilized diagnostic agent in each of the plurality of detection sites with a processor, and computationally comparing the binding characteristic among each of the plurality of detection sites with the processor, wherein the comparison of binding characteristics is capable of determining the stabilizing agent with the greater effect on the binding characteristic between the detection agent and the diagnostic agent.
1 . A computer-implemented method of improving diagnostic marker availability, the method comprising the steps of:
introducing a predetermined diagnostic marker for cancer into a plurality of detection sites of a detection platform;
introducing a stabilization agent into each of the plurality of detection sites containing the predetermined diagnostic marker for cancer, wherein the stabilization agent in each of the plurality of detection sites is capable of completely or substantially preventing the degradation or inactivation of the diagnostic marker;
introducing a detection agent into each of the plurality of detection sites having a stabilized diagnostic agent;
determining a binding characteristic of the detection agent and the stabilized diagnostic agent in each of the plurality of detection sites with a processor; and
computationally comparing the binding characteristic among each of the plurality of detection sites with the processor, wherein the comparison of binding characteristics is capable of determining the stabilizing agent with the greater effect on the binding characteristic between the detection agent and the diagnostic agent.
2 . The method of claim 1 , wherein the detection platform is selected from the group consisting of a microtitre plate, a microarray, and a multi-well plate.
3 . The method of claim 1 , further comprising the step of computationally comparing the binding characteristics to at least one stored binding characteristic contained in the computer database in communication with the processor.
4 . The method of claim 1 , wherein the diagnostic marker is selected from the group consisting of a protein, a glycoprotein, a nucleic acid, an enzyme, an enzyme inhibitor, and a metabolite.
5 . The method of claim 1 , wherein the stabilizing agent is useful to completely or substantially inactivate an enzyme selected from the group consisting of an amylase, a lysozyme, a peroxidase, a glycosidase, an esterase, a protease, and a peptidase.
6 . The method of claim 1 , wherein the stabilizing agent is selected from the group consisting of Fixanal® Buffer 6.0 (Sigma-Aldrich Co.), acetic acid, aluminum hydroxide bentonite, aluminum sulfate hydrate, aluminum potassium sulfate dodecahydrate, benzoic acid, caffeine, and 3-tert-butyl-hydroxyanisole, or a combination thereof.
7 . The method of claim 1 , wherein the stabilizing agent comprises a plurality of stabilizing agents each present in approximately the same concentration.
8 . The method of claim 1 , wherein the diagnostic marker is selected from the group consisting of Aldose reductase, Angiogenin, Annexin A1, B-cell activating factor (BAFF), B-cell lymphoma 2 (BCL2)-like 2, Beta Human chorionic gonadotropin, Ca15-3, Calcyclin, Calvasculin, Cancer Antigen CA 19-9, Cancer Antigen CA 15-3, Cathepsin D, Caveolin-1, Chromogranin A, Alpha-crystallin B chain (CRYAB), Endostatin, Eotaxin-2, Epithelial cell adhesion molecule (EpCAM), Ezrin, fatty acid binding protein 4 (FABP4), Galectin-3, γ-glutamylcysteine ligase regulatory chain (GCLR), Gelsolin, Glucose 6-phosphate (G6P), Glycoprotein 130 (gp130), Glutathione S-transferase Mu 1 (GSTM1), Hepsin, High-mobility group protein B1 (HMGB-1), Insulin-like growth factor binding protein 1 (IGFBP-1), Insulin-like growth factor binding protein 4 (IGFBP-4), Insulin-like growth factor binding protein 5 (IGFBP-5), Insulin-like growth factor binding protein 6 (IGFBP-6), LGL, latency associated peptide (LAP), macrophage stimulating protein (MSP), MHC class I polypeptide-related sequence A (MICA), Nucleoside diphosphate kinase B (NME2), Neuron-specific Enolase (NSE), Osteopontin, Osteoprotegerin, Pepsinogen, Peroxiredoxin, Phosphoserine aminotransferase (PSAT1), Prostate Specific Antigen, Receptor tyrosine-protein kinase erbB-3 (ErbB3), Serpin B3, Vascular smooth muscle cell growth factor R2 (VSGF R2/KDR), Vascular endothelial growth factor R3 (VEGF R3/Flt-4), Thyroglobulin, Tyrosine kinase with immunoglobulin-like and EGF-like domains 2 (TIE-2), Tissue plasminogen activator (tPA), Transforming growth factor beta (TGF-β1), Tumor necrosis factor receptor 1 (TNF-R1), urokinase-type Plasminogen Activator (uPA), urokinase-type Plasminogen Activator Receptor (uPAR), BrcaI, BrcaII, kallikreins, e-cadherin, Hox peptide, and Engrailed-2.
9 . A system of improving diagnostic marker availability, the system comprising:
a detection platform comprising a plurality of detection sites each capable of receiving a diagnostic marker, a stabilization agent, and a detection agent;
a computer database capable of receiving a plurality of binding characteristics, the plurality of binding characteristics comprising at least one binding property of a diagnostic marker to a detection agent;
a processor operably coupled to the computer database and the detection platform, the processor having and executing a software program operational to:
determine a binding characteristic between the detection agent and a stabilized diagnostic agent in each of the plurality of detection sites;
compare the binding characteristic among each of the plurality of detection sites, wherein the comparison of binding characteristics is capable of determining the stabilizing agent with the greatest effect on the binding characteristic between the detection agent and the diagnostic agent;
generate a binding record using the compared binding characteristics; and
deliver the binding record to a recipient.
10 . The system of claim 9 , wherein the software is further operational to compare the binding characteristic with at least one of a plurality of stored binding characteristics in the computer database.
11 . The system of claim 9 , wherein the diagnostic marker is selected from the group consisting of a protein, a glycoprotein, a nucleic acid, an enzyme, an enzyme inhibitor, and a metabolite.
12 . The system of claim 9 , wherein the stabilizing agent is useful to completely or substantially inactivate an enzyme selected from the group consisting of an amylase, a lysozyme, a peroxidase, a glycosidase, an esterase, a protease, and a peptidase.
13 . The system of claim 9 , wherein the stabilizing agent is selected from the group consisting of Fixanal® Buffer 6.0 (Sigma-Aldrich Co.), acetic acid, aluminum hydroxide bentonite, aluminum sulfate hydrate, aluminum potassium sulfate dodecahydrate, benzoic acid, caffeine, and 3-tert-butyl-hydroxyanisole, or a combination thereof.
14 . The system of claim 13 , wherein the stabilizing agent comprises a plurality of stabilizing agents each present in approximately the same concentration.
15 . The system of claim 9 , wherein the diagnostic marker is selected from the group consisting of Aldose reductase, Angiogenin, Annexin Al, B-cell activating factor (BAFF), B-cell lymphoma 2 (BCL2)-like 2, Beta Human chorionic gonadotropin, Ca15-3, Calcyclin, Calvasculin, Cancer Antigen CA 19-9, Cancer Antigen CA 15-3, Cathepsin D, Caveolin-1, Chromogranin A, Alpha-crystallin B chain (CRYAB), Endostatin, Eotaxin-2, Epithelial cell adhesion molecule (EpCAM), Ezrin, fatty acid binding protein 4 (FABP4), Galectin-3, γ-glutamylcysteine ligase regulatory chain (GCLR), Gelsolin, Glucose 6-phosphate (G6P), Glycoprotein 130 (gp130), Glutathione S-transferase Mu 1 (GSTM1), Hepsin, High-mobility group protein B1 (HMGB-1), Insulin-like growth factor binding protein 1 (IGFBP-1), Insulin-like growth factor binding protein 4 (IGFBP-4), Insulin-like growth factor binding protein 5 (IGFBP-5), Insulin-like growth factor binding protein 6 (IGFBP-6), LGL, latency associated peptide (LAP), macrophage stimulating protein (MSP), MHC class I polypeptide-related sequence A (MICA), Nucleoside diphosphate kinase B (NME2), Neuron-specific Enolase (NSE), Osteopontin, Osteoprotegerin, Pepsinogen, Peroxiredoxin, Phosphoserine aminotransferase (PSAT1), Prostate Specific Antigen, Receptor tyrosine-protein kinase erbB-3 (ErbB3), Serpin B3, Vascular smooth muscle cell growth factor R2 (VSGF R2/KDR), Vascular endothelial growth factor R3 (VEGF R3/Flt-4), Thyroglobulin, Tyrosine kinase with immunoglobulin-like and EGF-like domains 2 (TIE-2), Tissue plasminogen activator (tPA), Transforming growth factor beta (TGF-β1), Tumor necrosis factor receptor 1 (TNF-R1), urokinase-type Plasminogen Activator (uPA), urokinase-type Plasminogen Activator Receptor (uPAR), BrcaI, BrcaII, kallikreins, e-cadherin, Hox peptide, and Engrailed-2.