US20040224306A1 - Evaluating and predicting clinical outcomes by gene expression analysis - Google Patents

Evaluating and predicting clinical outcomes by gene expression analysis Download PDF

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US20040224306A1
US20040224306A1 US10/148,446 US14844602A US2004224306A1 US 20040224306 A1 US20040224306 A1 US 20040224306A1 US 14844602 A US14844602 A US 14844602A US 2004224306 A1 US2004224306 A1 US 2004224306A1
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Frederich-Wilhelm Kuhne
Michael McGrath
Stefan Meuer
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    • C12Q2600/158—Expression markers

Definitions

  • the present invention relates to methods for evaluating and predicting clinical outcomes in patients by measuring levels of gene expression. Methods are provided for quantitating gene expression levels, and the measured levels are compared against reference levels. Deviations from the reference levels can be correlated with clinical outcomes. For example, the type and extent of a patient's response to a therapeutic intervention can be determined, or the prognosis for a patient's survival can be estimated.
  • the gene expression levels can be measured in essentially any chosen body tissue or fluid. Surprisingly, it has been found that measurement of intracellular gene expression levels in blood are indicative of clinical outcomes.
  • the clinical specimen is a sample of blood, tissue, or cerebrospinal fluid.
  • the clinical specimen may be a sample of blood, and derived therefrom, such as plasma or serum sample or fraction.
  • the expression levels of at least three preselected genes are measured.
  • the expression level of at least one proinflammatory cytokine is measured.
  • the expression level of at least three preselected proinflammatory cytokines is measured.
  • the preselected proinflammatory cytokine genes are selected from the group consisting of TNF- ⁇ , IL-6, IL-1, IL-8, IP-10 and MIP-1 ⁇ .
  • the clinical condition or syndrome is an inflammatory disorder.
  • the inflammatory disorder is a chronic inflammatory disorder.
  • the chronic inflammatory disorder is selected from the group consisting of chronic hepatitis, hepatitis B and C, chronic obstructive pulmonary disease, inflammatory mucosal disease, autoimmune disease, dementia, cardiovascular disease, and cancer.
  • the inflammatory mucosal disease may be selected from the group consisting of inflammatory bowel disease, Crohn's disease, and colitis.
  • the dementia may be AIDS-related dementia or Alzheimer's disease.
  • the cancer may be selected from the group consisting of lymphoma, prostate cancer, and colon cancer.
  • the clinical condition is transplant rejection in a patient with an allograft.
  • the allograft may be a heart, liver, kidney, or other organ.
  • the clinical outcome that is determined is response to a therapeutic intervention.
  • the therapeutic intervention may be treatment with a drug.
  • the drug may be a stabilized chlorite solution.
  • the stabilized chlorite solution may be WF-10.
  • the clinical condition or syndrome is HIV infection.
  • the clinical condition or syndrome is AIDS.
  • the indicated clinical outcome is the probability of patient survival at a predetermined date. In one embodiment, the indicated clinical outcome is the probability of patient survival after six months.
  • the levels of gene expression are measured by a quantitative polymerase chain reaction.
  • the polymerase chain reaction may be a reverse transcriptase/polymerase chain reaction.
  • the polymerase chain reaction may be carried out using fluorescent detection of the amplification products.
  • the polymerase chain reaction may be carried out using a LightCycler® instrument, or using other appropriate technology.
  • FIG. 1 shows a schematic of a macrophage activation cycle wherein multiple steps occur during various forms of activation and recycling of macrophage function so as to achieve Balanced Macrophage Activation.
  • FIG. 2 shows the changes in gene expression of proinflammatory cytokines in a patient (#14) after treatment with WF10. The levels are reduced, indicating a good prognosis and good response to treatment.
  • FIG. 3 shows the changes in gene expression of proinflammatory cytokines in a patient (#15) after treatment with WF10. The levels are low to begin with, and are unchanged with treatment, indicating that therapy is unnecessary and that the patient has a good prognosis.
  • FIG. 4 summarizes characteristics of the patients studied in Example 2.
  • Patients were being enrolled in a prospective Phase II study evaluating the potential of WF10 for treatment of HCV disease.
  • Baseline blood specimens were available from these patients with paired liver biopsies for the study. All patient histories and specimens were obtained in accordance with standard Committee on Human Research approved protocols.
  • the acutely infected patient was not being evaluated for treatment by WF10 but presented to one of the study's referring physicians. That patient's specimens were evaluated with the same human subjects approval criteria.
  • the 8 patients with chronic HCV infection had baseline demographic and laboratory data obtained.
  • the patients were not selected by any criteria except that those patients had blood drawn before enrollment in the WF10 clinical trial and had a liver biopsy performed within 2 weeks of the blood draw.
  • FIG. 5 shows immune activation gene expression in PBMC from patients with acute and chronic HCV infection.
  • FIG. 6A shows the actual baseline gene expression values and GES for the patients whose data are summarized in FIG. 5.
  • FIG. 6B shows the actual induced gene expression values and GES for the patients whose data are summarized in FIG. 7.
  • FIG. 7 shows induced gene expression in PBMCs obtained from acute versus chronic HCV infected patients.
  • FIG. 8 shows the multigene expression score in unstimulated PBMC of patients with HCV disease.
  • FIG. 9 shows the scoring system used in MGES value calculations.
  • FIG. 10 shows multigene expression score in stimulated PBMC of patients with HCV disease.
  • the present invention provides methods of determining clinical outcomes in patients by measuring levels of expression of a preselected set of genes.
  • the gene expression levels are compared to reference standards and deviations from those standards are indicative of clinical outcomes.
  • the gene expression levels can be measured in essentially any clinical specimen, including tissue or fluid, such as cerebrospinal fluid.
  • tissue or fluid such as cerebrospinal fluid.
  • the inventors have discovered that gene expression levels measured in blood samples are indicative of clinical outcomes. This is surprising because the blood has typically been considered to be a quiescent organ of the body, and that measurement of gene expression levels in the blood has been thought to be an exercise of little or no value.
  • measurement of intracellular gene expression levels in blood cells can be used.
  • use of blood makes obtaining and analyzing clinical samples simple, convenient, and minimally invasive.
  • the gene expression levels used in the methods of the invention can be measured by any method now known or that is devised in the future that can provide quantitative information regarding the levels to be measured.
  • the methods preferably are highly sensitive and provide reproducible results.
  • methods based upon nucleic acid amplification technologies are used.
  • methods based upon the polymerase chain reaction (“PCR”) and related amplification technologies, such as NASBA and other isothermal amplification technologies may be used. More particularly, so called “RT-PCR” methods using reverse transcription of mRNA followed by amplification of the resulting cDNA are contemplated.
  • Primer sets for amplification of any known gene can be designed using methods that are well known in the art, for example, using gene sequences from public databases such as GENBANK and using primer design software such as OLIGO. Primer sets for many genes also are commercially available, for example from PE Applied Biosystems, Roche Molecular Biochemicals. Roche Diagnostics, and Search-LC (Heidelberg, Germany).
  • tissue sample from a patient can be used for measurement of gene expression levels.
  • the sample can be blood, cerebrospinal fluid, and cellular tissue derived from biopsy or from exfoliation such as from the cheek wall.
  • the sample is peripheral blood mononuclear cells, which are readily and easily available via minimally invasive methods. Methods for preparing the sample for gene expression analysis are well known in the art, and can be carried out using commercially available kits.
  • the gene expression levels obtained preferably are compared and normalized against reference genes in the same sample.
  • “housekeeping” genes such as actin, are used for this normalization.
  • Other “housekeeping” genes are well known in the art, such as HPRT, CPB, and G6PD.
  • the gene expression levels obtained from the clinical sample are compared to levels in reference samples.
  • the reference samples typically are obtained from healthy individuals who are disease free, or who are not suffering from the same pathological condition or syndrome as the test patient.
  • expression levels of the genes of interest are determined from a number of healthy individuals, and an average or mean is obtained.
  • the reference levels may be determined from individuals of the same sex and age as the test patient.
  • the reference levels may be obtained from tabulated data, where those data are compiled from healthy patients of appropriate sex and age.
  • the relative levels of gene expression that can be predictive (a type of indication) of clinical outcome can be higher or lower levels of expression.
  • proinflammatory cytokines such as TNF- ⁇ , IL-6, IL-1, IL-8, IP-10 and MIP-1 ⁇ are reflective of a poor clinical outcome (for example, reduced expectation for long-term survival) for patients infected with HIV.
  • the relative levels of the proinflammatory cytokines can be measured again. If the levels of the cytokines is reduced, this indicates that the patient is responding well to the treatment. In this case, the clinical outcome may be that the patient can cease anti-HIV therapy, or reduce the dose of the anti-HIV compound.
  • a lack of response can indicate that the patient will not respond to therapy, and therefore has a poor prognosis, or that the dose of anti-HIV compound must be increased, or additional therapeutic interventions must be used.
  • a lack of response also may indicate that the progression of the disease has not been halted or slowed by therapy.
  • the present invention specifically contemplates that the levels of proinflammatory cytokine expression can be measured and used to predict clinical outcome, the skilled artisan will recognize that the invention is not so limited.
  • methods for identifying changes in gene expression are well known in the art, as described supra. Even though these methods are not sufficiently quantitative for use in the present invention, they can be used to predict those genes whose expression is changed in a disease state. Quantitative measurements, such as quantitative RT-PCR can then be used to measure the changes in gene expression. Those changes can be tracked in patients and correlated with clinical outcomes by methods that are well known in the art.
  • a predictive method for determining clinical outcome can be developed.
  • the discussion below describes the gene expression levels in macrophage activation, and describes how those levels, and their change upon treatment with a particular drug (WF10) provide information regarding clinical outcomes in patients suffering from chronic inflammatory disease, such as chronic hepatitis, hepatitis B and C, chronic obstructive pulmonary disease, inflammatory mucosal disease, autoimmune disease, dementia, cardiovascular disease, and cancer.
  • the inflammatory mucosal disease may be selected from, for example, inflammatory bowel disease, Crohn's disease, and colitis.
  • the dementia may be, for example, AIDS-related dementia or Alzheimer's disease.
  • the cancer may be, for example, lymphoma, prostate cancer, or colon cancer.
  • Example 2 below also demonstrates that the methods of the invention can be used to predict clinical outcome in patients suffering from hepatitis C.
  • the methods of the invention may also be used to detect or predict clinical outcome of transplant rejection in patients receiving allografts, such as heart, liver, kidney, or other organs.
  • allografts such as heart, liver, kidney, or other organs.
  • measurement of altered, particularly increased, inflammatory cytokine gene expression is indicative of rejection of the allograft.
  • Particular gene expression levels that can be measured to detect allograft rejection include IP10, TNF ⁇ , ⁇ -IFN, and other macrophage inflammation genes.
  • WF10 is a stabilized chlorite matrix approved for clinical use in a systemic form (WF10) and in a more dilute topical form (Oxoferrin) See Kühne, Die erwünschte Sauerstoff15technik, actuiert am content der Wundheilung: der Wegzzy Oxoferin - Therapie . In: Elsmer E. F., Bors W., Wilmanns W. (eds.): Reassiette Sauerstoffspezies in der Medizin. Springer Verlag, Berlin 1986, pp. 5-15. WF10 has been approved in Thailand for systemic administration to patients with post-radiation syndrome and for supportive care in patients being treated for cancer. These indications have been studied extensively and reviewed.
  • FIG. 1 shows a schematic of a macrophage activation cycle wherein multiple steps occur during various forms of activation and recycling of macrophage function so as to achieve Balanced Macrophage Activation.
  • Each step in the macrophage activation cycle is numbered (1-5) and is described sequentially.
  • the first thing that occurs in a macrophage activation program is phagocytosis of foreign material. Macrophages engulf pathogenic organisms such as bacteria, fungi and viruses. This is one of the oldest and most important functions of macrophages and is how the macrophage derived its name. “Macro” meaning big, and “phage” meaning eater, thereby conferring on the macrophage the term “Big Eater.” Upon successful phagocytosis of a foreign substance, the macrophage processes this material through a proteolytic pathway, cutting individual proteins into small peptides that then are involved in the second step of macrophage activation.
  • Antigen presentation After foreign materials have been cut into peptides, macrophages present antigen to T lymphocytes utilizing the major histocompatibility antigens class 1 (HLA) and class 2 (DR) and initiate expansion of a normal immune response. T cell activation predominantly occurs through this antigen-presenting-cell function. Standard cytotoxic T cells specific for virus infected cells, cancers or fungi are developed that ultimately lead to successful immunologic clearance of those foreign processes. This is represented in FIG. 1 as an active immune response. Upon successful activation of an active immune response, T cells express various activation antigens such as CD38 and secrete factors such as interleukin-2 (IL-2). IL2 allows T cells to proliferate and gamma-interferon ( ⁇ -IFN) to cause further macrophage activation and step 3.
  • HLA major histocompatibility antigens class 1
  • DR class 2
  • Classical macrophage activation A product of T cell activation, gamma-interferon induces full inflammatory changes and classical macrophage activation. This activation causes upregulation of inflammatory cytokines such as IL1, IL6, and tumor necrosis factor (TNF). The macrophage in this state is extremely inflammatory and causes secondary effects such as fevers, and when chronically stimulated, weight loss and further non-specific activation of immunologic responses.
  • IL1 IL1, IL6, and tumor necrosis factor (TNF).
  • TNF tumor necrosis factor
  • TH1 to TH2 Activity to Inhibitor T
  • TH1 cell a second major class of T cell, the TH2 cell
  • Cytokines produced by the TH2 cells include IL4, IL5, IL6, and IL10. These factors cause B cell activation, B cell proliferation, hypergammaglobulinemia, up-regulation of IgE and allergic reactions and eosinophilia.
  • a net result of excess IL10 production is shutting off of step 2 in the response shown in FIG. 1.
  • TH1 and TH2 cell activation process occur virtually simultaneously in vitro (and likely in vivo), however classical immunologic responsiveness as measured by T cell proliferation in vitro predominantly measures the TH1-like response.
  • the TH2 response has as a key feature, the production of IL4, which is known to activate the alternative macrophage activation pathway (AMAP).
  • AMAP alternative macrophage activation pathway
  • AMAP The Alternative Macrophage Activation Pathway (reviewed in ref. 4) has the following features:
  • Balanced Macrophage Activation is disrupted by a variety of pathologic processes and Balanced Macrophage Activation imbalance is responsible for many manifestations of chronic disease. Examples of these imbalances are as follows:
  • Steps 2 and 3 in FIG. 1 are continually stimulated when a foreign virus cannot be cleared by a successful immune response that would re-establish Balanced Macrophage Activation.
  • This immunologic overstimulation would predictably lead to pathologic sequelae such as cirrhosis and hepatoma in chronic hepatitis B & C infections and profound immune dysregulation in HIV disease.
  • steps 2 and 3 are overemphasized, there would be a predicted shortage of cells to accomplish steps 5 and 1.
  • An overactivation of step 3 would clinically appear as chronic fever with associated weight loss.
  • a secondary byproduct of chronic viral disease would be the exhaustion of cells in steps 5 and 1 as noted above. This result would decrease the rate of wound healing and decrease associated angiogenesis and phagocytosis. Fewer cells capable of phagocytosing material would allow new infectious organisms such as bacteria and fungus to be poorly cleared by individuals with chronic viral diseases.
  • Autoimmune diseases are similar to chronic viral diseases in that there is an overstimulation of immunoreactive lymphocytes with associated inflammation. Autoimmune disease has for many years been thought of as a chronic viral-like disease, however no virus has to date been isolated as an initiator of these types of diseases. These diseases include systemic lupus (SLE), post-radiation syndrome, and a variety of autoimmune kidney diseases, etc. Features of some autoimmune diseases are the presence of hypergammaglobulinemia, elevated IgE and eosinophilia as described above in FIG. 1 step 4. This result may occur as the by-products of a compensatory TH1 to TH2 shift when the body attempts to reestablish Balanced Macrophage Activation.
  • SLE systemic lupus
  • IgE elevated IgE
  • eosinophilia as described above in FIG. 1 step 4. This result may occur as the by-products of a compensatory TH1 to TH2 shift when the body attempts to reest
  • Allergic reactions The most serious allergic reaction is asthma wherein overstimulation of step 2 with environmental antigens in the lung leads to inappropriate local macrophage inflammatory changes and T cell activation in lung tissues. These lung tissues are harmed by inflammatory mediators produced in step 3. Normally lung macrophages constitutively have the Alternative Macrophage Activation Pathway induced) (as shown in step 5) and they therefore are less susceptible to steps 2 and 3 as shown in FIG. 1. However, in patients with allergies these reactions (steps 2 & 3) are allowed to occur. Asthmatic patients also have a TH1 to TH2 shift with associated eosinophilia. This reaction is predicted by the Balanced Macrophage Activation theory to be compensatory when it attempts to shift lung macrophages from steps 2 & 3 through 4 into step 5.
  • Immune deficiency associated bacterial and fungal infections If steps 2 and 3 from FIG. 1 are increased, over time there will be fewer cells in steps 5 and 1 capable of phagocytosis and reinitiation of immune responses. The decreased number of cells capable of phagocytosing bacteria and fungus makes patient survival in the presence of immunodeficiency quite problematic. Antibiotic therapy directed against bacteria and fungus works inefficiently in vivo unless the invading organisms have been phagocytosed by macrophages or granulocytes. The most commonly used antifungal drug, amphotericin B, does not work at all unless fungus has been engulfed by a phagocytic cell.
  • Chronic wounds The best example of this class of disease is observed in patients with diabetes or those who are bedridden. Chronic diabetic and pressure ulcers develop and macrophages within those wounds exhibit changes consistent with step 3 in FIG. 1. Goerdt et al., Immunity 10:137-142 (1999). Wounds will not heal if step 3 cannot be shifted through step 5 wherein angiogenic factors are produced to allow blood vessel growth and healing. Similarly if macrophages within a chronic wound have been shifted from step 1 to 3, phagocytic cells will not be present to allow clearance of dead and dying material within wounds so as to speed the healing process.
  • Cancer A variety of cancers are outgrowths of chronic inflammation. Examples include lymphoma, which represents outgrowths of antigen-overdriven lymphocytes, and prostate cancer, which evolves from chronic prostatitis. In both cases steps 2 & 3 provide chronic growth stimuli.
  • WF10 completely blocked antigen activation of T cell responsiveness at levels easily achievable in vivo. McGrath et al., Transplantation Proceedings, 30: 4200-4204.(1998). This inhibition of T cell activation only occurred when T cells and macrophages were placed together with the foreign antigen, and occurred instantly or even when added at day 6 of a 7-day T cell activation assay. These data suggest that WF10 is extremely potent at inhibiting processes fundamental to normal T cell activation as shown in step 2 for FIG. 1.
  • WF10 caused downregulation of inflammatory cytokine production by inflammatory macrophages as described in step 3 for FIG. 1.
  • WF10 and Oxoferrin have been used extensively for many years to treat chronic disease in humans. Oxoferrin was approved for topical use in chronic wounds in the late 1980's. To date Oxoferrin has been successful in inducing rapid healing of chronic wounds including diabetic and pressure ulcers. Oxoferrin is thought to work through achieving Balanced Macrophage Activation with associated upregulation of angiogenic factors and macrophage phagocytosis. WF10 was approved in Thailand for systemic use in 1997 for treatment of post-radiation syndrome (PRS). Post-radiation syndrome occurs as a late complication in organs that have received X-ray therapy.
  • PRS post-radiation syndrome
  • a preferred embodiment of the treatment of this invention entails administration to a mammal in need thereof, an aqueous solution of a product that has been termed “tetrachlorodecaoxygen anion complex,” commonly abbreviated as “TCDO.”
  • TCDO tetrachlorodecaoxygen anion complex
  • This substance can be prepared using the procedures described in Example 1 of U.S. Pat. No. 4,507,285 (“the '285 patent”), and is a water clear liquid, miscible with alcohols, and has a melting point of ⁇ 3° C.
  • the Raman spectrum shows bands of 403, 802 (chlorite) and 1562 cm ⁇ 1 (activated oxygen).
  • chlorite solution can be used in the methods of the present invention, and that the scope of the invention is not limited to use of the product described in the '285 patent.
  • WF10 denotes an aqueous stabilized chlorite solution.
  • MNC Mononuclear cells
  • Target sequences were amplified using LightCycler® Primer Sets (Search-LC, Heidelberg, Germany) with the LightCycler FastStart DNA Sybr Green 1 Kit (Roche Diagnostics, Indianapolis, Ind.) according to the manufacturer's protocol. Input was normalized by the average expression of the four housekeeping genes ⁇ -actin, HPRT, G6PDH and Cyclophilin B.
  • eligible patients attend study visits on Days 1, 2, and 4. From Days 8 through 12, patients receive one cycle of WF10 0.5 mL per kg/bw diluted into 250-500 mL normal saline administered by intravenous infusion. Patients then attend study visits on Days 15, 17, 19, 22, 24, and 26.
  • Immune function measured on days 1, 8, 11, 15, 22, 29, 31, 40 and 47, is defined as the measurement of phagocytic index using fluorescein-labeled E. coli , T cell activation with phytohemagglutinin, lymphocyte immune phenotyping (detecting CD3, CD4, CD8, CD14, CD20, CD28, CD38, CD56, CD69), DR, TNF and monocyte quantitation.
  • FIG. 2 shows relative levels of a series of proinflammatory genes (to internal housekeeping genes, actin, G6PD, CPB, HPRT) in a patient (#14) who had a 50% decrease in the CD8/38+ cell subset compared to a patient (#15) who had no change of CD8/38 during the 47 days of the trial.
  • the gene expression levels in patient 15 are shown in FIG. 3.
  • WF10 was tested in vitro on PBMC's exposed to anti-CD2, anti-CD3 and PMA/ionomycin to determine effects of the drug on T cell activation.
  • WF10 was used at a final concentration of 1:300, a dose easily achieved during the clinical trial and PBMC's were harvested three hours and affinity purified CD14 cells 18 hours later for RNA extraction and RT-PCR.
  • WF10 effects on 11 normal blood donor PBMC's were expressed as LC-Index which represents up to a 5 fold change from baseline un(WF10) treated but stimulated specimens.
  • IL-1 ⁇ , IL-8, MIP-1a and thioredoxin (TRX) upregulation A consistent down regulation of induced lymphostimulatory cytokines IL-2 and IL-17 was observed, with a consistent pattern of IL-1 ⁇ , IL-8, MIP-1a and thioredoxin (TRX) upregulation. Because the upregulations appeared to be macrophage inflammatory mediators, purified CD14 cells were exposed to 1:300 WF10 for 18 hours and evaluated for increased gene expression. Three of the seven CD14 preparations had an approximate decrease in the 4 housekeeping gene levels of 90%. Three CD14 specimens also had dramatic upregulation of the 4 apoptosis genes evaluated and parallel PI uptake studies confirmed CD14 cell apoptosis occurring in those cultures.
  • TRX thioredoxin
  • Apoptotic cells are the most potent stimulus for macrophages to under alternative (anti-inflammatory) activation and phagocytosis.
  • Alternative activation has been associated with induction by the Th2 cytokine IL-4 and causes a complete block in inflammatory gene expression and antigen induced T cell activaton.
  • Purified macrophages were exposed to a 1:200 dilution of WF10 and AMAC-1 (specific for the alternative pathway, AMAP) gene expressioin was assessed up to 21 days later. WF10 dramatically augmented the AMAC-1 expression induced by macrophage treatment with IL-4.
  • WF10 administration changes expression of macrophage proinflammatory gene expression in a pattern that parallels changes in CD8/38 levels in vivo.
  • WF10 caused dramatic changes in a wide variety of immunologically active genes leading to apoptosis in CD14 cells in a subset of preactivated patient specimens and consistent down regulation of lymphostimulatory genes in PBMCs. It is apparent that WF10 regulates inappropriate inflammation associated with chronic inflammatory diseases such as HIV disease through overactivation induced CD14 cell death with compensatory induction of the alternative (anti-inflammatory) pathway of macrophage activation.
  • Activated PBMC's Down regulation of lymphostimulatory cytokines IL-2 and IL-17. Upregulation of macrophage inflammatory genes as well as the anti-apoptotic (antioxidant) gene thioredoxin (TRX)
  • b) Cultured CD14 cells Upregulation of apoptotic genes (BAX, BCL-X1, CD95, CD95L) in specimens containing elevated pre-treatment levels of inflammatory genes with associated apoptotic cell (CD14) death.
  • WF10 caused late upregulation of the alternative macrophage activation gene AMAC-1 in isolated CD14 cells.
  • WF10 induction of macrophage cell death in specimens containing elevated inflammatory gene expression leads to compensatory AMAP induction in macrophages in response to the acute apoptosis of inflammatory macrophages. Accordingly, WF10 causes downregulation of inflammation through acute upregulation of inflammatory gene expression, cell death through apoptosis, downregulation of lymphostimulatory genes and compensatory macrophage differentiation change to the AMAP, anti-inflammatory pathway.
  • Peripheral blood mononuclear cells were obtained from the 9 patients described in FIG. 4, as well as from 20 normal blood donors. Gene expression was assessed for baseline as well as PMA/ionomycin stimulated cells as described above. Quantitative evaluation was based on use of 2 housekeeping genes ( ⁇ -Actin, CPB) to serve as controls for overall cellular gene expression. “Test” gene expression was subsequently normalized to a standard “housekeeping gene” control level. Thirteen genes associated with macrophage and T cell activation were selected for evaluation in this study because of their function in primary immunologic responses and chronic inflammation.
  • the genes were IL-1, IL-2, IL-4, IL-8, IL-10, IP10, MCSF, TNF ⁇ , ⁇ -IFN, MIP-1 ⁇ , MIP-2 ⁇ , MRP-14, and TGF- ⁇ . Normal values for housekeeping genes as well as inflammatory genes were established by evaluating gene expression patterns from 20 normal blood donors (see FIG. 5).
  • the average gene expression values from blood of the 8 chronically infected patients showed a pattern of gene expression similar to the acute infection specimen consistent with an ongoing immunologic response.
  • the actual GES values varied widely from patient to patient with chronic HCV infection, however.
  • the average values for each gene are shown in FIG. 5.
  • the actual gene expression values and GES are shown in FIG. 6A (baseline) and FIG. 6B (PMA induced). This ongoing response detected in the blood, if present within the liver, could lead to progressive inflammatory damage consistent with that observed in progressive HCV liver disease.
  • FIGS. 6B and 7 contrast with prior reported experiments in patients with HCV liver disease that showed elevation of IL-2 levels and hyperactivity of T cells at the protein level. See Martin et al., Cytokine 11:267-73 (1999). To determine whether the observed gene expression patterns would correlate with degree of liver inflammation pathology, the corresponding liver biopsies were read and given inflammatory grade scores using standard assessment criteria.
  • FIG. 8 shows the correlation between liver inflammation score and a scoring system based on utilizing GES values from inflammatory genes as determined in the current study. (FIG. 9) A high degree of correlation was found between the MGES (multiple gene expression score) and the degree of liver inflammation.
  • FIG. 7 is the range from the lowest to the highest values for each of the genes evaluated for the 20 normal blood donor patients.
  • the data shown in FIG. 7 are broken into 2 categories: genes representing T cell activation as compared to genes representing macrophage activation.
  • the acute infection (A) is compared in FIG. 10 to the mean value of the 8 patients with chronic HCV infection.
  • the values for the chronically infected patients were highly variable and are shown in FIG. 6B.
  • the gene expression values shown in FIG. 6 with the deduced GES values were stratified based on the liver inflammation score obtained independently from a pathologist uninvolved in the gene expression evaluation.
  • a multiple gene expression score (MGES) was determined utilizing gene expression values from the following genes from the patients shown in FIG. 4 (TNF ⁇ , IP10, MIP-2 ⁇ , interferon- ⁇ , and MRP14).
  • the GES of each patient's expressed gene involved in the MGES calculation is shown in FIG. 9.
  • the MGES calculated scores for each patient were then plotted based on a liver inflammation score determined by independent pathologic evaluation and this data was plotted and are shown in FIG. 8.
  • the 20 normal patients were also given MGES scores represented in the figure as normal range which showed MGES from 0 to 2 with a mean of 1.
  • Patient with acute HCV infection is shown with an MGES score of 10.
  • the statistical relationship between the MGES score and liver inflammation score is shown as an r 2 value.
  • MGES was determined based on the induced GES scores as shown in FIG. 9. MGES determinations were based on the calculated GES evaluated for each individual gene being then converted into an MGES score combination, including all 3 genes. The normal range is shown and designated normal range with the mean of 1 with the range from ⁇ 3 to 0. Acute HCV infection is shown with a calculated MGES of ⁇ 2.5. The statistical relationship between the MGES score and liver inflammation score is shown as an r 2 value.

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Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20070099239A1 (en) * 2005-06-24 2007-05-03 Raymond Tabibiazar Methods and compositions for diagnosis and monitoring of atherosclerotic cardiovascular disease
US20080213751A1 (en) * 2006-12-20 2008-09-04 Manfred Schmolz Ilcs based pattern recognition of sepsis
US7666595B2 (en) 2005-02-25 2010-02-23 The Brigham And Women's Hospital, Inc. Biomarkers for predicting prostate cancer progression

Families Citing this family (32)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CA2393136A1 (en) * 1999-11-30 2001-06-07 Oxo Chemie Ag Evaluating and predicting clinical outcomes by gene expression analysis
ATE318935T1 (de) 2001-07-23 2006-03-15 Hoffmann La Roche Bewertungssystem für die vorhersage von krebsrezidiven
DE10143712A1 (de) * 2001-08-30 2003-04-10 Europroteome Ag Verfahren, Computersystem und Computerprogrammprodukt zur Datenauswertung
AU2002351505B2 (en) * 2001-10-19 2008-04-03 Genentech, Inc. Compositions and methods for the diagnosis and treatment of inflammatory bowel disorders
EP1319720A1 (en) * 2001-12-11 2003-06-18 Roche Diagnostics GmbH Method for detection of inflammatory processes
EP1319717A1 (en) * 2001-12-11 2003-06-18 Roche Diagnostics GmbH Method for detection of inflammatory processes
JP2005523688A (ja) * 2002-01-18 2005-08-11 ブリストル−マイヤーズ　スクイブ　カンパニー タンパク質チロシンキナーゼおよび／またはタンパク質チロシンキナーゼ経路と相互作用する化合物の活性を予測するためのポリヌクレオチドおよびポリペプチドの同定
US20030232396A1 (en) * 2002-02-22 2003-12-18 Biolife Solutions, Inc. Method and use of protein microarray technology and proteomic analysis to determine efficacy of human and xenographic cell, tissue and organ transplant
US20090149335A1 (en) * 2002-02-22 2009-06-11 Biolife Solutions Inc. Method and use of microarray technology and proteogenomic analysis to predict efficacy of human and xenographic cell, tissue and organ transplant
DK2799555T3 (en) 2002-03-13 2017-05-22 Genomic Health Inc Gene Expression Profiling in Tumor Tissue Biopsies
EP1361433A3 (en) * 2002-04-09 2005-02-23 Kabushiki Kaisha Hayashibara Seibutsu Kagaku Kenkyujo Method for estimating therapeutic efficacy of tumor necrosis factor (TNF)
EP1354963A1 (en) * 2002-04-15 2003-10-22 Health Research, Inc. Method for determining the prognosis of ovarian cancer
ITFI20030058A1 (it) * 2003-03-06 2004-09-07 Univ Firenze Formulazioni farmaceutiche contenenti tiazolidinedioni
US7191068B2 (en) * 2003-03-25 2007-03-13 Proteogenix, Inc. Proteomic analysis of biological fluids
US8068990B2 (en) * 2003-03-25 2011-11-29 Hologic, Inc. Diagnosis of intra-uterine infection by proteomic analysis of cervical-vaginal fluids
US7467119B2 (en) * 2003-07-21 2008-12-16 Aureon Laboratories, Inc. Systems and methods for treating, diagnosing and predicting the occurrence of a medical condition
US7505948B2 (en) * 2003-11-18 2009-03-17 Aureon Laboratories, Inc. Support vector regression for censored data
WO2005050563A2 (en) * 2003-11-17 2005-06-02 Aureon Biosciences Corporation Pathological tissue mapping
US7105183B2 (en) * 2004-02-03 2006-09-12 The Regents Of The University Of California Chlorite in the treatment of neurodegenerative disease
AU2011205095B2 (en) * 2004-02-03 2014-07-03 The Regents Of The University Of California Chlorite in the treatment of neurodegenerative disease
TW200532523A (en) * 2004-02-27 2005-10-01 Aureon Biosciences Corp Methods and systems for predicting occurrence of an event
US7761240B2 (en) * 2004-08-11 2010-07-20 Aureon Laboratories, Inc. Systems and methods for automated diagnosis and grading of tissue images
JP5629894B2 (ja) * 2004-12-07 2014-11-26 国立大学法人大阪大学 甲状腺乳頭癌を診断するための新規のマーカー
WO2007038375A2 (en) * 2005-09-22 2007-04-05 Prosanos Corporation Methods and systems for evaluating interaction of medical products and dependence on demographic variables
EP1979269A4 (en) 2005-12-22 2013-01-02 Taiji Biomedical Inc CHLORINE FORMULATIONS AND PROCESS FOR THE PREPARATION AND USE THEREOF
CN106086175B (zh) * 2006-04-24 2020-03-03 健泰科生物技术公司 用于检测自身免疫性病症的方法和组合物
EP2517713A3 (en) 2007-06-01 2013-01-30 Nuvo Research AG A method of treating allergic asthma, allergic rhinitis and atopic dermatitis
US20100029491A1 (en) * 2008-07-11 2010-02-04 Maike Schmidt Methods and compositions for diagnostic use for tumor treatment
WO2012012694A2 (en) * 2010-07-23 2012-01-26 President And Fellows Of Harvard College Methods of detecting autoimmune or immune-related diseases or conditions
WO2012170710A1 (en) * 2011-06-08 2012-12-13 Altheadx Incorporated Disease classification modules
US20140356452A1 (en) * 2012-01-19 2014-12-04 Ibt Usa Inc. Therapeutic Uses of Tetrachlorodecaoxygen (TCDO)
RU2018109574A (ru) 2015-08-20 2019-09-23 Оксо Чемие (Таиланд) Ко., Лтд Применение хлорита для лечения болезней красных кровяных телец и опосредованных ими симптомов

Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5877222A (en) * 1996-07-19 1999-03-02 The Regents Of The University Of California Method for treating aids-associated dementia
US5965421A (en) * 1997-11-26 1999-10-12 Human Genome Sciences, Inc. Human IRAK-2
US6703202B2 (en) * 1999-11-30 2004-03-09 Oxo Chemie Ag Evaluating and predicting clinical outcomes by gene expression analysis

Family Cites Families (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6548631B1 (en) 1997-09-16 2003-04-15 BIOMéRIEUX, INC. Macrophage derived chemokine (MDC) as an anti-viral agent for the treatment and prevention of lentivirus infection

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5877222A (en) * 1996-07-19 1999-03-02 The Regents Of The University Of California Method for treating aids-associated dementia
US5965421A (en) * 1997-11-26 1999-10-12 Human Genome Sciences, Inc. Human IRAK-2
US6703202B2 (en) * 1999-11-30 2004-03-09 Oxo Chemie Ag Evaluating and predicting clinical outcomes by gene expression analysis

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7666595B2 (en) 2005-02-25 2010-02-23 The Brigham And Women's Hospital, Inc. Biomarkers for predicting prostate cancer progression
US20100137164A1 (en) * 2005-02-25 2010-06-03 The Brigham And Women's Hospital, Inc. Biomarkers for predicting prostate cancer progression
US7803552B2 (en) 2005-02-25 2010-09-28 The Brigham & Women's Hospital, Inc. Biomarkers for predicting prostate cancer progression
US20070099239A1 (en) * 2005-06-24 2007-05-03 Raymond Tabibiazar Methods and compositions for diagnosis and monitoring of atherosclerotic cardiovascular disease
US20080213751A1 (en) * 2006-12-20 2008-09-04 Manfred Schmolz Ilcs based pattern recognition of sepsis
US8361730B2 (en) * 2006-12-20 2013-01-29 Edi Gmbh ILCS based pattern recognition of sepsis

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