Gene expression profiling in acute lymphoblastic leukemia (ALL).
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Biomarkers, Tumor↗
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A serum glycomics approach to breast cancer biomarkers.
Because the glycosylation of proteins is known to change in tumor cells during the development of breast cancer, a glycomics approach is used here to find relevant biomarkers of breast cancer. These glycosylation changes are known to correlate with increasing tumor burden and poor prognosis. Current antibody-based immunochemical tests for cancer biomarkers of ovarian (CA125), breast (CA27.29 or CA15-3), pancreatic, gastric, colonic, and carcinoma (CA19-9) target highly glycosylated mucin proteins. However, these tests lack the specificity and sensitivity for use in early detection. This glycomics approach to find glycan biomarkers of breast cancer involves chemically cleaving oligosaccharides (glycans) from glycosylated proteins that are shed or secreted by breast cancer tumor cell lines. The resulting free glycan species are analyzed by MALDI-FT-ICR MS. Further structural analysis of the glycans can be performed in FTMS through the use of tandem mass spectrometry with infrared multiphoton dissociation. Glycan profiles were generated for each cell line and compared. These methods were then used to analyze sera obtained from a mouse model of breast cancer and a small number of serum samples obtained from human patients diagnosed with breast cancer or patients with no known history of breast cancer. In addition to the glycosylation changes detected in mice as mouse mammary tumors developed, glycosylation profiles were found to be sufficiently different to distinguish patients with cancer from those without. Although the small number of patient samples analyzed so far is inadequate to make any legitimate claims at this time, these promising but very preliminary results suggest that glycan profiles may contain distinct glycan biomarkers that may correspond to glycan "signatures of cancer."
Adult↗
ZBTB16-associated NK cell alterations reveal shared immunometabolic signatures linking primary Sjögren's syndrome and type 1 diabetes mellitus.
BACKGROUND: Primary Sjögren's syndrome (pSS) and type 1 diabetes mellitus (T1DM) share immune-inflammatory features, yet conserved pathogenic signatures linking these autoimmune disorders remain incompletely understood. The present research sought to uncover common molecular markers and dissect the underlying immune-metabolic cross-talk underlying pSS and T1DM. METHODS: Gene expression profiles of patients with pSS and T1DM were retrieved from the Gene Expression Omnibus database, normalized, and corrected for batch effects prior to downstream analyses. Overlapping potential biomarkers were screened by integrating differential expression analysis, weighted gene co-expression network analysis and least absolute shrinkage and selection operator regression. Functional enrichment based on Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases was implemented to interpret gene biological properties, and a protein-protein interaction network was further established afterwards. Diagnostic performance was evaluated using receiver operating characteristic analysis. Experimental validation was conducted in non-obese diabetic (NOD) mice using quantitative PCR, immunohistochemistry, and flow cytometry. The CIBERSORT algorithm was adopted to quantify immune cell infiltration levels. RESULTS: ZBTB16 was identified as a shared hub biomarker in both pSS and T1DM and exhibited favorable diagnostic performance. Experimental validation confirmed significantly reduced ZBTB16 expression in peripheral blood mononuclear cells, salivary gland tissues, and pancreatic tissues of NOD mice. Gene Set Enrichment Analysis indicated that ZBTB16-associated signatures were enriched in mitochondrial-related processes, neuroactive ligand-receptor interactions, and ribosome-related pathways. Immune infiltration analysis revealed that resting natural killer (NK) cells were positively correlated with ZBTB16 expression in both diseases. Flow cytometric analysis further confirmed a reduced proportion of resting NK cells in peripheral blood of NOD mice, consistent with the CIBERSORT-based prediction. CONCLUSION: This study identifies ZBTB16 as a shared biomarker linking pSS and T1DM. Reduced resting NK-cell abundance was consistently observed in both computational and experimental analyses, and bioinformatic correlation analysis suggested a positive association with ZBTB16 expression. These findings provide evidence for shared molecular and immunological signatures underlying the two autoimmune disorders and support further investigation of the biological role and diagnostic value of ZBTB16 in pSS and T1DM.
Sjogren's Syndrome↗
PSIP1::TBL1X: a recurrent gene fusion in pancreatic neuroendocrine tumors.
Effective treatment of metastatic neuroendocrine tumors (NETs) is limited by a lack of targeted therapies and clinically useful predictive biomarkers. We applied complementary genomic profiling technologies, including optical genome mapping (OGM) and whole exome sequencing (WES), to 70 liver metastases of NETs from multiple anatomical primary sites to identify actionable genomic alterations. We detected recurrent fusions involving TBL1X (PSIP1::TBL1X) and BEND2 (CHD7::BEND2 and NEO1::BEND2) by OGM in pancreatic neuroendocrine tumors (pNETs). The expression of the PSIP1::TBL1X fusion was confirmed by PacBio Iso-Seq long-read transcriptome sequencing and nested rtPCR, and fusion protein expression was established by western blotting. Expression of the PSIP1::TBL1X fusion was also assayed in a separate cohort of 31 specimens from 28 pNET cases by rtPCR. Across both cohorts, PSIP1::TBL1X was identified in 11% of pNET patients with available metastatic tissue, but was not detected in primary tumor specimens. All PSIP1::TBL1X fusion isoforms were found to retain early exons of PSIP1 and the complete coding sequence of TBL1X. Consistent with prior reports, BEND2 fusions were associated with high-grade tumors and may represent a clinically useful biomarker for aggressive disease. Notably, TBL1X and BEND2 fusions did not co-occur with ATRX/DAXX mutations, defining a distinct molecular subgroup of pNETs. This study highlights the importance of structural variant profiling in molecular profiling studies and supports a revised view of the role of gene fusions in neuroendocrine malignancies.
Humans↗
Inhibition profiles of human tissue kallikreins by serine protease inhibitors.
Accumulated evidence has shown that human tissue kallikreins (hKs), a group of 15 homologous secreted serine proteases, are novel cancer biomarkers. We report here the inhibition profiles of selected hKs, including hK5, hK7, hK8, hK11, hK12, hK13, and hK14, by several common serine protease inhibitors (serpins) found in plasma. The association constants for the binding of serpins to kallikreins were determined and compared. Protein C inhibitor was found to be the fastest-binding serpin for most of these hKs. alpha2-Antiplasmin, alpha1-antichymotrypsin, and alpha1-antitrypsin also showed rapid inhibition of certain hKs. Kallistatin exhibited fast inhibition only with hK7. Our data demonstrate that these hKs are specifically regulated by certain serpins and their distinct inhibition profiles will be valuable aids in various aspects of kallikrein research.
Cell Line, Tumor↗
Metabonomic deconvolution of embedded toxicity: application to thioacetamide hepato- and nephrotoxicity.
We present here the potential of an integrated metabonomic strategy to deconvolute the biofluid metabolic signatures in experimental animals following multiple organ toxicities, using the well-known hepato- and nephrotoxin, thioacetamide. Male Han-Wistar rats were dosed with thioacetamide (150 mg/kg, n = 25), and urine, plasma, liver, and kidney samples were collected postdose for conventional NMR and magic angle spinning (MAS) NMR spectroscopy. These data were correlated with histopathology and plasma clinical chemistry collected at all time points. 1H MAS NMR data from liver and kidney were related to sequential 1H NMR measurements in urine and plasma using pattern recognition methods. One-dimensional 1H NMR spectra were data-reduced and analyzed using principal components analysis (PCA) to show the time-dependent biochemical variations induced by thioacetamide toxicity. From the eigenvector loadings of the PCA, those regions of the 1H NMR spectra, and hence the combinations of endogenous metabolites marking the main phase of the toxic episode, were identified. The thioacetamide-induced biochemical manifestations included a renal and hepatic lipidosis accompanied by hypolipidaemia; increased urinary excretion of taurine and creatine concomitant with elevated creatine in liver, kidney, and plasma; a shift in energy metabolism characterized by depleted liver glucose and glycogen; reduced urinary excretion of tricarboxylic acid cycle intermediates and raised plasma ketone bodies; increased levels of tissue and plasma amino acids leading to amino aciduria verifying necrosis-enhanced protein degradation and renal dysfunction; and elevated hepatic and urinary bile acids indicating secondary damage to the biliary system. This integrated metabonomic approach has been able to identify the tissue of origin for biomarkers present in the metabolic profiles of biofluids, following the onset and progression of a multiorgan pathology, and as such highlights its potential in the evaluation of embedded toxicity in novel drug candidates.
Amino Acids↗
Discovery and identification of potential biomarkers in a prospective study of chronic lymphoid malignancies using SELDI-TOF-MS.
The accurate diagnosis of the different forms of chronic mature B-cell lymphocytic malignancies is of primary importance to determine an appropriate and efficient treatment. Usually, the diagnosis is achieved by morphology and immunophenotyping. Nevertheless, the diagnostic tools available are not able to discriminate pathologies with variable evolution, or to classify some of them. To discover new biomarkers, we used peptide and protein profiling SELDI-TOF-MS, to analyze 39 chronic B-cell malignancies and 20 control serum samples. Markers of interest were subsequently identified and characterized. In the obtained SELDI-MS profiles, most of the differences were observed in three mass ranges (m/z = 13 000; m/z = 9000; m/z < 2000). Identification of these biomarkers was achieved either by direct enrichment on the ProteinChip arrays followed by on-chip-MS/MS or by chromatographic fractionation, 1D-gel followed by nanoLC-MS/MS analysis. An increase of a sulfite form of transthyretin (13,841 Da) was observed in the patient group. A second set of markers at 8.6 and 8.9 kDa was identified as complement related fragment proteins, the C3a and C4a anaphylatoxins. In the low mass range, several peptides originating from N-terminal and C-terminal processing of the C3 alpha and C4 alpha chains were specifically observed in 38% of the patient sera, but in none of the control sera. This study emphasizes the usefulness of mass spectrometry studies in such malignancies.
Amino Acid Sequence↗
Prediction of nephrotoxicant action and identification of candidate toxicity-related biomarkers.
A vast majority of pharmacological compounds and their metabolites are excreted via the urine, and within the complex structure of the kidney,the proximal tubules are a main target site of nephrotoxic compounds. We used the model nephrotoxicants mercuric chloride, 2-bromoethylamine hydrobromide, hexachlorobutadiene, mitomycin, amphotericin, and puromycin to elucidate time- and dose-dependent global gene expression changes associated with proximal tubular toxicity. Male Sprague-Dawley rats were dosed via intraperitoneal injection once daily for mercuric chloride and amphotericin (up to 7 doses), while a single dose was given for all other compounds. Animals were exposed to 2 different doses of these compounds and kidney tissues were collected on day 1, 3, and 7 postdosing. Gene expression profiles were generated from kidney RNA using 17K rat cDNA dual dye microarray and analyzed in conjunction with histopathology. Analysis of gene expression profiles showed that the profiles clustered based on similarities in the severity and type of pathology of individual animals. Further, the expression changes were indicative of tubular toxicity showing hallmarks of tubular degeneration/regeneration and necrosis. Use of gene expression data in predicting the type of nephrotoxicity was then tested with a support vector machine (SVM)-based approach. A SVM prediction module was trained using 120 profiles of total profiles divided into four classes based on the severity of pathology and clustering. Although mitomycin C and amphotericin B treatments did not cause toxicity, their expression profiles were included in the SVM prediction module to increase the sample size. Using this classifier, the SVM predicted the type of pathology of 28 test profiles with 100% selectivity and 82% sensitivity. These data indicate that valid predictions could be made based on gene expression changes from a small set of expression profiles. A set of potential biomarkers showing a time- and dose-response with respect to the progression of proximal tubular toxicity were identified. These include several transporters (Slc21a2, Slc15, Slc34a2), Kim 1, IGFbp-1, osteopontin, alpha-fibrinogen, and Gstalpha.
Animals↗
Effect of garlic powder on C-reactive protein and plasma lipids in overweight and smoking subjects.
BACKGROUND: Epidemiologic studies suggest that garlic may have beneficial effects on risk factors associated with cardiovascular disease (CVD). However, these findings are not unambiguously supported by randomized placebo-controlled clinical trials. OBJECTIVE: We sought to investigate the effects of a chemically well-characterized garlic preparation on biomarkers for inflammation, endothelial function, and lipid metabolism in subjects with risk factors for CVD. DESIGN: This was a double-blind, randomized, placebo-controlled trial in 90 overweight [body mass index (in kg/m2) > 24.5] subjects aged 40-75 y who smoked >10 cigarettes/d. The subjects were randomly assigned to 3 parallel treatment groups: garlic powder (2.1 g/d), atorvastatin (40 mg/d), or placebo. Duplicate measurements were performed at baseline and after 1 and 3 mo of treatment. Treatments were compared with analysis of covariance with baseline as the covariate, and differences between the treatments were reported as mean percentage difference and corresponding 97.5% CI. RESULTS: None of the variables showed significant differences between the garlic-treated and the placebo groups. In contrast, compared with the placebo group, atorvastatin treatment resulted in significantly lower plasma concentrations of C-reactive protein (20.2%; 1.7%, 35.3%), total cholesterol (37.2%; 33.1%, 41.1%), LDL cholesterol (52.7%; 47.9%, 57.1%), triacylglycerols (31.9%; 20.8%, 41.5%), and tumor necrosis factor alpha (TNF-alpha; 41.9%; 19.0%, 58.3%) and increased the ratio of ex vivo whole blood lipopolysaccharide-stimulated to nonstimulated TNF-alpha concentrations (109.7%; 37.9%, 218.9%). CONCLUSION: We conclude that a chemically well-characterized garlic preparation has no significant effect on inflammatory biomarkers, endothelial function, or lipid profile in normolipidemic subjects with risk factors for CVD.
Adult↗
The state-of-the-art in predictive toxicogenomics.
Predictive toxicogenomics, ie, the acquisition of advanced knowledge of the safety profile of a compound using genomic biomarkers, is a technology that provides much optimism for improving early drug discovery decisions. Toxicogenomics creates an opportunity to shift attrition to earlier stages in drug development to a point where course-corrective action can be taken with relatively lower financial costs, thus improving the efficiency of the drug development process. This review will survey the current state-of-the-art in toxicogenomics for predicting toxicity, both in vivo and in vitro, with emphasis on the use of classification algorithms and the importance of toxicogenomic databases for biomarker discovery and validation.
Algorithms↗
Predicting Alzheimer dementia in mild cognitive impairment patients. Are biomarkers useful?
A correct clinical diagnosis in the early stage of Alzheimer disease is not only of importance given the current available treatment with acetylcholine esterase inhibitors, but would be the basis for disease-modifying therapy slowing down or arresting the degenerative process. Moreover, in the last years, several efforts have been made to determine if a patient with mild cognitive impairment has incipient Alzheimer disease, i.e. will progress to Alzheimer disease with dementia, or have a benign form of mild cognitive impairment. In this review, the recent published reports regarding progress in early and preclinical Alzheimer disease diagnosis are discussed and the role of peripheral and cerebrospinal fluid biomarkers highlighted. Approaches combining panels of different biomarkers show promise for discovering profiles that are characteristic of Alzheimer disease, even in the pre-symptomatic stage. More work is needed but available novel perspectives offered by recent introduced technologies shed some lights in identifying incipient Alzheimer disease in mild cognitive impairment subjects.
Alzheimer Disease↗
Serum amyloid A as a tumor marker in sera of nude mice with orthotopic human pancreatic cancer and in plasma of patients with pancreatic cancer.
We screened an orthotopic nude mouse model of human pancreatic cancer for candidate serum biomarkers and examined their presence in the plasma of pancreatic cancer patients. Nude mice were injected in the pancreas with L3.9pl human pancreatic cancer cells. One week later, the mice were randomized into 4 treatment groups: i) control, saline; ii) oral STI 571; iii) intraperitoneal gemcitabine; and iv) STI 571 and gemcitabine. After 1, 2, and 3 weeks of treatment, sera and tumors were collected from mice in each group as well as uninjected mice. All sera were analyzed by surface enhanced laser desorption ionization mass spectrometry using ProteinChip technology. Protein profiles were analyzed with the Biomarker Wizard software package. The concentration of candidate proteins was evaluated in mouse sera and plasma from 135 pancreatic cancer patients, 7 pancreatitis patients, and 113 healthy volunteers. The combination therapy inhibited tumor growth. A 11.7-kDa protein peak correlating with tumor weight was purified by gel filtration, separated by SDS-PAGE, and identified as mouse serum amyloid A (SAA) by amino acid sequencing and public database searches. The expression of SAA in mouse sera was confirmed by Western blotting and correlated with tumor weight. The level of SAA in plasma of pancreatic cancer patients correlated with clinical stage and was significantly higher than in normal volunteers (mean value: 180.1 microg/ml vs 27.9 microg/ml: P<0.01) or pancreatitis patients. For SAA used as a single tumor marker with a cut-off of 75 microg/ml, the sensitivity for pancreatic cancer was 96.5% and specificity was 31.9%. Our search for specific marker proteins to identify pancreatic cancer was unsuccessful. Although SAA is not specific for pancreatic cancer and not sensitive enough to detect stage I patients, it may be a candidate biomarker for detecting and monitoring the progressive growth of pancreatic cancer.
Animals↗
Safety and pharmacokinetics of the dual action Raf kinase and vascular endothelial growth factor receptor inhibitor, BAY 43-9006, in patients with advanced, refractory solid tumors.
PURPOSE: BAY 43-9006, a novel multikinase inhibitor, prevents tumor growth by combining two antitumor activities: inhibition of both tumor cell proliferation and tumor angiogenesis. This phase I, open-label, nonrandomized, noncontrolled, single-arm, dose escalation study was done to determine the maximum tolerated dose (MTD), safety profile, pharmacokinetic variables, effect on biomarkers, and tumor response with BAY 43-9006 in 19 patients with advanced, refractory solid tumors. EXPERIMENTAL DESIGN: BAY 43-9006 was given orally in repeated cycles of 1-week on/1-week off. The study comprised five dose levels, ranging from 100 mg twice daily (bid) to 800 mg bid. Treatment of each patient continued until unacceptable toxicity, tumor progression, or death. RESULTS: Rash and hypertension were the dose-limiting toxicities at the 800 mg bid dose requiring study drug discontinuation; therefore, the MTD of BAY 43-9006 in this study was determined to be 600 mg bid. BAY 43-9006 was generally well tolerated, with mild to moderate toxicities. Pharmacokinetic analysis showed early absorption followed by delayed secondary peaks and slow terminal elimination. Stable disease was achieved in five patients: one patient showed reduced tumor activity (positron emission tomography scan) and reduced mitogen-activated protein kinase signaling (lower phospho-ERK); one patient remained on treatment until study end point. CONCLUSIONS: The results confirm the favorable safety profile of BAY 43-9006 and support the development of this compound for the treatment of solid tumors.
Adult↗
Mechanisms and biomarkers of cardiovascular injury induced by phosphodiesterase inhibitor III SK&F 95654 in the spontaneously hypertensive rat.
The cardiovascular injury of the type III selective PDE inhibitor SK&F 95654 was investigated in SHR. Twenty-four hours after a single sc injection of 100 or 200 mg/kg of the drug, rats exhibited cardiomyocyte necrosis and apoptosis, interstitial inflammation, hemorrhage and edema, as well as mesenteric arterial hemorrhage and necrosis, periarteritis, EC and VSMC apoptosis, EC activation, and MC activation and degranulation. Elevated serum levels of cTnT and decreased cTnT immunoperoxidase staining on cardiomyocytes were detected in the drug-treated rats. Serum levels of alpha2-macroglobulin and IL-6 were significantly elevated following drug treatment. NMR spectral patterns of urine samples are significantly different between the drug-treated and control rats. These results indicate that measurement of serum cTnT, acute phase proteins, and cytokines as well as metabonomic urine profiles may serve as potential biomarkers for drug-induced cardiovascular injury in rats. Increased expression of CD63 on MC (tissue biomarker of MC), of nitrotyrosine on MC and EC (an indirect indicator of NO in vivo), and of iNOS on MC and EC (source of NO) suggest that NO produced by activated and degranulated MC as well as activated EC play an important role in SK&F 95654-induced mesenteric vascular injury.
Alanine Transaminase↗
MathDAMP: a package for differential analysis of metabolite profiles.
BACKGROUND: With the advent of metabolomics as a powerful tool for both functional and biomarker discovery, the identification of specific differences between complex metabolite profiles is becoming a major challenge in the data analysis pipeline. The task remains difficult, given the datasets' size, complexity, and common shifts in migration (elution/retention) times between samples analyzed by hyphenated mass spectrometry methods. RESULTS: We present a Mathematica (Wolfram Research, Inc.) package MathDAMP (Mathematica package for Differential Analysis of Metabolite Profiles), which highlights differences between raw datasets acquired by hyphenated mass spectrometry methods by applying arithmetic operations to all corresponding signal intensities on a datapoint-by-datapoint basis. Peak identification and integration is thus bypassed and the results are displayed graphically. To facilitate direct comparisons, the raw datasets are automatically preprocessed and normalized in terms of both migration times and signal intensities. A combination of dynamic programming and global optimization is used for the alignment of the datasets along the migration time dimension. The processed datasets and the results of direct comparisons between them are visualized using density plots (axes represent migration time and m/z values while peaks appear as color-coded spots) providing an intuitive overall view. Various forms of comparisons and statistical tests can be applied to highlight subtle differences. Overlaid electropherograms (chromatograms) corresponding to the vicinities of the candidate differences from any result may be generated in a descending order of significance for visual confirmation. Additionally, a standard library table (a list of m/z values and migration times for known compounds) may be aligned and overlaid on the plots to allow easier identification of metabolites. CONCLUSION: Our tool facilitates the visualization and identification of differences between complex metabolite profiles according to various criteria in an automated fashion and is useful for data-driven discovery of biomarkers and functional genomics.
Biomarkers↗
Evaluation of matrix-assisted laser desorption/ionization-time of flight mass spectrometry proteomic profiling: identification of alpha 2-HS glycoprotein B-chain as a biomarker of diet.
Biomarkers have the potential to impact a wide range of public health concerns, including early detection of diseases, drug discovery, and improved accuracy of monitoring effects of interventions. Given new technological developments, broad-based screening approaches will likely advance biomarker discovery at an accelerated pace. Matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) allows for the elucidation of individual protein masses from a complex mixture with high throughput. We have developed a method for identifying serum biomarkers using MALDI-TOF and statistical analysis. However, before applying this approach to screening of complex diseases, we evaluated the approach in a controlled dietary intervention study. In this study, MALDI-TOF spectra were generated using samples from a randomized controlled trial. During separate feeding periods, 38 participants ate a basal diet devoid of fruits and vegetables and a basal diet supplemented with cruciferous (broccoli) family vegetables. Serum samples were obtained at the end of each 7-day feeding period and treated to remove large, abundant proteins. MALDI-TOF spectra were analyzed using peak picking algorithms and logistic regression models. Our bioinformatics methods identified two significant peaks at m/z values of 2740 and 1847 that could classify participants based on diet (basal vs. cruciferous) with 76% accuracy. The 2740 m/z peak was identified as the B-chain of alpha 2-HS glycoprotein, a serum protein previously found to vary with diet and be involved in insulin resistance and immune function.
Adult↗
Practice guideline for cardiac profiling.
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Biomarkers↗