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PubMed2001

Cardiac markers and risk stratification: an integrated approach.

Risk stratification of patients with acute coronary syndromes (ACS) is pivotal for correct allocation of health resources and for maximizing the benefit of available treatment modalities. However, clinical and electrocardiographic indicators of high risk lack sufficient sensitivity for the detection of major cardiac events. The complementary information provided by the measurement of different biomarkers is believed to be very useful. Specifically, elevations of cardiac troponin I (cTnI) and T (cTnT) are strongly associated with a high-risk profile both at short- and long-term. This has been definitely demonstrated in many studies as well as in cumulative meta-analysis. The role of different biomarkers, such as those reflecting activation of hemostasis and the presence of inflammation, is however less defined. At the moment, no study has prospectively evaluated these biomarkers in the whole spectrum of unselected patients with ACS. It is also unclear whether these biomarkers add independent prognostic value to the clinical and electrocardiographic indicators of adverse outcome and whether they offer additional information when compared to each other. The Early Prognostic Value of Biochemical Markers of Myocardial Damage, Activation of Hemostatic Mechanism and Inflammation in Acute Ischemic Syndromes (EMAI) study has been prospectively designed to solve these issues. In this study, we have evaluated the prognostic value of cTnI and cTnT, D-dimer, prothrombin fragment 1+2 (F1+2), thrombin-antithrombin complex (TAT) and C-reactive protein (CRP) in patients with ACS at the time of admission. We have enrolled in 31 Italian Coronary Care Units 1971 patients with rest anginal pain within 12 h from admission and electrocardiographic evidence of myocardial ischemia. Of these, 730 patients resulted to have ST-segment elevation myocardial infarction eligible for a reperfusion strategy and 1241, an acute coronary syndrome without persisting ST-segment elevation. Primary outcome measure of the study is the composite of death and non-fatal MI within 30 days from admission, which has occurred in 8.9% of the study population.

Animals↗

PubMed2025

Genomic profiling of aggressive pathologic features in lung adenocarcinoma.

INTRODUCTION: Pathologic features involving LVI (lympho-vascular invasion), PNI (perineural invasion), STAS (spread through air spaces), and Grade 3 pattern (from the International Association for the Study of Lung Cancer grading system) are related to having an aggressive phenotype and linked to poor prognosis. However, few studies have conducted in-depth analyses of these features simultaneously with genomic profiling. METHODS: A total of 1559 sequencing of adenocarcinoma samples were included in the common driver mutations analysis, 1306 samples were brought into genomic mapping analysis. OncoSG's East Asian ancestry dataset was implemented for Tumor-Node-Metastasis-Biomarker (TNMB) classification and prognostic assessment. RESULTS: EGFR was more significantly prevalent in LVI negativity (P = 0.021), STAS negativity (P = 0.002), and moderate grade (P < 0.001). ALK was significantly interrelated with LVI (P = 0.028), STAS (P < 0.001), and poor grade (P < 0.001); ROS1 and STAS positivity (P = 0.031), poor grade (P = 0.016) were significantly related. KRAS (P = 0.003) and BRAF-V600E (P = 0.002) were only significantly intertwined with poor grade. Apart from common driver mutations, TP53, CHEK2, KEAP1, PTEN, RB1, NF1 were significantly enriched in LVI samples (P < 0.05). TP53, PTEN, CTNNB1, HGF, NF1 were more prominent in STAS (P < 0.01). TP53, LRP1B, NF1 were significantly more prevalent in Grade 3 pattern (P < 0.001). The mixture of STK11, PTEN, and TOP2A generated by exclusive mutations may be a potential predictor of TNMB categorization towards survival. The HR of stage II compared I of TNMB was 2.28 (95 % CI 1.36-3.86, P < 0.001), while stage III compared II was 1.95 (95 % CI 1.04-3.21, P = 0.031). CONCLUSIONS: This analysis demonstrated the correlation of pathologic features with common driver mutations, key mutations and canonical oncogenic signaling pathways. The data highlighted the similarities and differences among these features horizontally, and provide new insights in TNMB classification and prognostic assessment.

Humans↗

PubMed2004

Finding disease specific alterations in the co-expression of genes.

MOTIVATION: Standard analysis routines for microarray data aim at differentially expressed genes. In this paper, we address the complementary problem of detecting sets of differentially co-expressed genes in two phenotypically distinct sets of expression profiles. RESULTS: We introduce a score for differential co-expression and suggest a computationally efficient algorithm for finding high scoring sets of genes. The use of our novel method is demonstrated in the context of simulations and on real expression data from a clinical study.

Algorithms↗

PubMed2004

Cell protection, resistance and invasiveness of two malignant mesotheliomas as assessed by 10K-microarray.

Malignant pleural mesothelioma (MPM) is an aggressive serosal tumor, strongly associated with former exposure to asbestos fibers and for which there is currently no effective treatment available. In human, MPM is characterized by a high local invasiveness, poor prognosis and therapeutic outcomes. In order to assess molecular changes that specify this phenotype, we performed a global gene expression profiling of human MPM. Using a 10,000-element microarray, we analyzed mRNA relative gene expression levels by comparing a mesothelioma cell line to either a pleural cell line or tumor specimens. To analyze these gene expression data, we used various bioinformatics softwares. Hierarchical clustering methods were used to group genes and samples with similar expression in an unsupervised mode. Genes of known function were further sorted by enzyme, function and pathway clusters using a supervised software (IncyteGenomics). Taken together, these data defined a molecular fingerprint of human MPM with more than 700 up- or down-regulated genes related to several traits of the malignant phenotype, specially associated with MPM invasiveness, protection and resistance to anticancer defenses. This portrait is meaningful in disease classification and management, and relevant in finding new specific markers of MPM. These molecular markers should improve the accuracy of mesothelioma diagnosis, prognosis and therapy.

Biomarkers, Tumor↗

PubMed2006

The transcript expression profile of the leptin receptor-coding gene assayed with the oligonucleotide microarray technique--could this be an anorexia nervosa marker?

Anorexia nervosa is a serious eating disorder with the highest mortality rate of any psychiatric disorder. The DSM-IV classification differentiates two AN types: the restricting type (AN-R) and the binge-eating/purging type (AN-BP). Leptin (LEP) levels can be thought of as a signal to the body of its energy reserves. The leptin receptor (including all its mRNA isoforms) is expressed in many tissues. Our aim was to discover the transcript expression profile of the LEP receptor-coding gene in the peripheral blood mononuclears in AN-R and AN-BP patients. Three young women suffering from Anorexia nervosa (one with AN-BP and two with AN-R) took part in the study, along with three non-anorexic subjects as our reference group. LEP receptor gene expression was examined using the oligonucleotide microarray method (HG-U133A, Affymetrix). The results were normalized using RMAExpress. Next, the accumulation analysis method was used (clustering). Hierarchical clustering resulted in three groups of separate clusters. The first group (cluster I) consisted of AN-R patients. The next group (cluster II) consisted of reference group patients suffering from different psychic disorders not related to eating disorders. Cluster III consisted of two patients--the first with AN-BP and the second with an adaptive disorder.

Adolescent↗

PubMed2026

Candidate biomarkers for early Giardia duodenalis infection revealed by time-resolved secretome proteomics.

Giardia duodenalis is a zoonotic protozoan parasite that causes giardiasis in humans and other mammals. Early diagnosis remains challenging because current diagnostic methods, including microscopy and enzyme-linked immunosorbent assays (ELISAs), primarily detect established infections. Consequently, a critical diagnostic gap exists during the early stage of infection within the first 2-48 h following exposure. To address this limitation, we characterized the proteins released by in vitro-cultured G. duodenalis trophozoites under serum-free conditions and evaluated their potential as early diagnostic biomarkers. Proteomic analysis of culture supernatants collected during early trophozoite incubation identified 31,773 peptides corresponding to 2504 quantifiable proteins. Temporal profiling showed distinct secretion patterns, including proteins that peaked during the early stage, progressively accumulated over time, or remained persistently abundant throughout the incubation period. Based on their secretion characteristics and predicted immunogenic properties, five candidate biomarkers were selected for further evaluation. Polyclonal antibodies raised against selected candidates successfully detected the corresponding proteins in serum-free culture supernatants, providing preliminary evidence for their potential utility as early-stage diagnostic targets. These findings identify stage-associated candidate proteins that may serve as a resource for future early giardiasis diagnostic development, provide a valuable resource for investigating host-parasite interactions, and establish a foundation for future diagnostic assay development. However, further validation in clinical and biological samples is required to confirm their diagnostic applicability. SIGNIFICANCE: Giardiasis, caused by Giardia duodenalis, is a major diarrheal disease worldwide. Although enzyme-linked immunosorbent assays (ELISAs) provide rapid detection, their diagnostic utility is limited by the lack of biomarkers capable of identifying infection during its earliest stages, creating a critical gap in the detection of active infection within 2-48 h following exposure. Using data-independent acquisition proteomics, this study provides a time-resolved characterization of proteins released by G. duodenalis trophozoites into serum-free culture supernatants. Our findings reveal temporal secretion dynamics of protein secretion and identify candidate biomarkers with potential utility for the development of early-stage diagnostic assays pending rigorous biological and clinical validation. In addition, this proteomic resource provides a foundation for investigating host-parasite interactions and may facilitate the development of future point-of-care diagnostic strategies.

Giardiasis↗

PubMed2006

A search for genes that may confer divergent morphology and function in the carotid body between two strains of mice.

The carotid body (CB) is the primary hypoxic chemosensory organ. Its hypoxic response appears to be genetically controlled. We have hypothesized that: 1) genes related to CB function are expressed less in the A/J mice (low responder to hypoxia) compared with DBA/2J mice (high responder to hypoxia); and 2) gene expression levels of morphogenic and trophic factors of the CB are significantly lower in the A/J mice than DBA/2J mice. This study utilizes microarray analysis to test these hypotheses. Three sets of CBs were harvested from both strains. RNA was isolated and used for global gene expression profiling (Affymetrix Mouse 430 v2.0 array). Statistically significant gene expression was determined as a minimum six counts of nine pairwise comparisons, a minimum 1.5-fold change, and P <or= 0.05. Our results demonstrated that 793 genes were expressed less and that 568 genes were expressed more in the A/J strain vs. the DBA/2J strain. Analysis of individual genes indicates that genes encoding ion channels are differentially expressed between the two strains. Genes related to neurotransmitter metabolism, synaptic vesicles, and the development of neural crest-derived cells are expressed less in the A/J CB vs. the DBA/2J CB. Through pathway analysis, we have constructed a model that shows gene interactions and offers a roadmap to investigate CB development and hypoxic chemosensing/chemotransduction processes. Particularly, Gdnf, Bmp2, Kcnmb2, Tph1, Hif1a, and Arnt2 may contribute to the functional differences in the CB between the two strains. Bmp2, Phox2b, Dlx2, and Msx2 may be important for the morphological differences.

Animals↗

PubMed2004

Progression in cutaneous malignant melanoma is associated with distinct expression profiles: a tissue microarray-based study.

Cutaneous malignant melanoma remains the leading cause of skin cancer death in industrialized countries. Clinical and histological variables that predict survival, such as Breslow's index, tumor size, ulceration, or vascular invasion have been identified in malignant melanoma. Nevertheless, the potential relevance of biological variables still awaits an in-depth exploration. Using tissue microarrays (TMAs), we retrospectively analyzed 165 malignant melanoma samples from 88 patients corresponding to distinct histological progression phases, radial, vertical, and metastases. A panel of 39 different antibodies for cell cycle, apoptosis, melanoma antigens, transcription factors, DNA mismatch repair, and other proteins was used. Integrating the information, the study has identified expression profiles distinguishing specific melanoma progression stages. Most of the detected alterations were linked to the control of cell cycle G1/S transition; cyclin D1 was expressed in radial cases 48% (12 of 25) with significant lost of expression in vertical cases 14% (9 of 65), P = 0.002; whereas p16(INK4a) (89% in vertical versus 71% in metastatic cases, P = 0.009) and p27(KIP1) (76% in radial versus 45% in vertical cases, P = 0.010) were diminished in advanced stages. The study also defines a combination of biological markers associated with shorter overall survival in patients with vertical growth phase melanoma, that provided a predictor model with four antibodies (Ki67, p16(INK4a), p21(CIP1), and Bcl-6). This predictor model was validated using an independent series of 72 vertical growth phase melanoma patients.

Adult↗

PubMed2004

Detection of cancer-related gene expression profiles in severe cervical neoplasia.

The molecular signatures of 20 severe cervical intraepithelial neoplasia (CIN3) cases and 10 cervical squamous cell cancers were determined to define cancer-related gene expression profiles. RNAs extracted from microdissected tissues were amplified by SMART technology and used as probes for hybridization of commercially available cDNA array filters comprising 1,176 cancer-related genes. Ninety-two differentially expressed genes were identified by comparison of pooled cDNA from CIN3 vs. cervical cancer. Heterogeneity in expression of this subset of genes was then analyzed for each biopsy using an algorithm for self-organizing maps. For several gene clusters, the expression pattern for CIN3 differed significantly from that of cancer. Moreover, hierarchical clustering revealed significant differences in distribution of CIN and cancer. Several CIN cases were more strongly related to cancer, suggesting that gene expression profiling may be useful for subdividing pathologically indistinguishable precancers into different biologic entities. This approach also provides a basis for the identification of putative prognostic markers and for targeted molecular therapy.

Adult↗

PubMed2006

Discovering antibiotic efficacy biomarkers: toward mechanism-specific high content compound screening.

As current antibiotic therapy is increasingly challenged by emerging drug-resistant bacteria, new technologies are required to identify and develop novel classes of antibiotics. A major bottleneck in today's discovery efforts, however, is a lack of an efficient and standardized method for assaying the efficacy of a drug candidate. We propose a new high content screening approach for identifying efficacious molecules suitable for development of antibiotics. Key to our approach is a new microarray-based efficacy biomarker discovery strategy. We first produced a large dataset of transcriptional responses of Bacillus subtilis to numerous structurally diverse antibacterial drugs. Second we evaluated different protocols to optimize drug concentration and exposure time selection for profiling compounds of unknown mechanism. Finally we identified a surprisingly low number of gene transcripts (approximately 130) that were sufficient for identifying the mechanism of novel substances with reasonable accuracy (approximately 90%). We show that the statistics-based approach reveals a physiologically meaningful set of biomarkers that can be related to major bacterial defense mechanisms against antibiotics. We provide statistical evidence that a parallel measurement of the expression of the biomarkers guarantees optimal performance when using expression systems for screening libraries of novel substances. The general approach is also applicable to drug discovery for medical indications other than infectious diseases.

Anti-Bacterial Agents↗

PubMed2007

Prediction of metastasis from low-malignant breast cancer by gene expression profiling.

Promising results for prediction of outcome in breast cancer have been obtained by genome wide gene expression profiling. Some studies have suggested that an extensive overtreatment of breast cancer patients might be reduced by risk assessment with gene expression profiling. A patient group hardly examined in these studies is the low-risk patients for whom outcome is very difficult to predict with currently used methods. These patients do not receive adjuvant treatment according to the guidelines of the Danish Breast Cancer Cooperative Group (DBCG). In this study, 26 tumors from low-risk patients were examined with gene expression profiling. An intermediate risk group of 34 low-malignant T2 tumors that fulfilled all other low-risk criteria than tumor size was included to increase statistical power. A 32-gene classifier, HUMAC32, was identified and it predicted metastases with 80% sensitivity and 77% specificity. The classifier was also validated in an independent group of high-risk tumors resulting in comparable performance of HUMAC32 and a 70-gene classifier developed for this group. Furthermore, the 70-gene signature was tested in our low- and intermediate-risk samples. The results demonstrated high cross-platform consistency of the classifiers. Higher performance of HUMAC32 was demonstrated among the low-malignant cancers compared with the 70-gene classifier. This suggests that although the metastatic potential to some extend is determined by the same genes in groups of tumors with different characteristics and risk, expression-based classification specifically developed in low-risk patients have higher predictive power in this group.

Biomarkers, Tumor↗

PubMed2005

Genomics and circulating tumor cells: promising tools for choosing and monitoring adjuvant therapy in patients with early breast cancer?

PURPOSE OF REVIEW: Gene expression profiling using a class discovery approach has consistently shown that breast cancer emerges as a group of different disease entities: the basal-like, the human epidermal growth factor receptor 2 type, the normal breast-like, and at least two different hormone receptor positive or luminal types. Initial reports have also suggested that certain expression patterns are associated with relapse. Current data on adjuvant therapy are only beginning to consider this biologic heterogeneity (estrogen receptor and human epidermal growth factor receptor 2 status). Similarly, the search for isolated tumor cells in blood or bone marrow has been regarded as another approach for defining prognosis and tailoring adjuvant therapies. The purpose of this review is to highlight the recent data emerging from both approaches as a means of assessing prognosis and tailoring therapy in patients with early breast cancer. RECENT FINDINGS: The initial reports on prognosis assessment of breast cancer using the expression profile have been corroborated, but the differences between the actual genes selected for the different prognostic signatures remain difficult to explain. Others have introduced added signatures, such as those associated with proliferation or with wound healing, or selected subgroups on the basis of, for example, estrogen receptor level prior to class comparison. The data on the quantification of expression of a limited number of selected genes are promising for both prognosis and prediction. The segregation of histological grade 2 tumors into genetically defined grade 1 or 3 tumors and its associated prognostic significance is a critical observation. The standardization of methods for measuring isolated tumor cells in blood or bone marrow has resulted in validated data both on prognosis in early breast cancer and in the advanced setting. Methylation of circulating DNA might become another method for selecting patients for extended adjuvant regimens. SUMMARY: The new molecular knowledge must be incorporated into prospective clinical studies in patients with early breast cancer. This is the challenge for the years to come.

Biomarkers, Tumor↗

PubMed2004

Identification and proteomic profiling of exosomes in human urine.

Urine provides an alternative to blood plasma as a potential source of disease biomarkers. One urinary biomarker already exploited in clinical studies is aquaporin-2. However, it remains a mystery how aquaporin-2 (an integral membrane protein) and other apical transporters are delivered to the urine. Here we address the hypothesis that these proteins reach the urine through the secretion of exosomes [membrane vesicles that originate as internal vesicles of multivesicular bodies (MVBs)]. Low-density urinary membrane vesicles from normal human subjects were isolated by differential centrifugation. ImmunoGold electron microscopy using antibodies directed to cytoplasmic or anticytoplasmic epitopes revealed that the vesicles are oriented "cytoplasmic-side inward," consistent with the unique orientation of exosomes. The vesicles were small (<100 nm), consistent with studies of MVBs and exosomes from other tissues. Proteomic analysis of urinary vesicles through nanospray liquid chromatography-tandem mass spectrometry identified numerous protein components of MVBs and of the endosomal pathway in general. Full liquid chromatography-tandem MS analysis revealed 295 proteins, including multiple protein products of genes already known to be responsible for renal and systemic diseases, including autosomal dominant polycystic kidney disease, Gitelman syndrome, Bartter syndrome, autosomal recessive syndrome of osteopetrosis with renal tubular acidosis, and familial renal hypomagnesemia. The results indicate that exosome isolation may provide an efficient first step in biomarker discovery in urine.

Adult↗

PubMed2005

Comparative application of antibody and gene array for expression profiling in human squamous cell lung carcinoma.

Expression profiling by gene microarray techniques have been developed to predict malignant tissue but there are no experiences with the application of antibody arrays to identify malignancy-related proteins. Because altered protein patterns might also better interpret biological processes, we applied tumour samples from 12 patients with squamous cell lung carcinoma and individual lung tissue controls to antibody arrays spotted with 378 distinct monoclonal antibodies. Array analysis defined 20 proteins with higher and nine with lower abundance in lung tumours. Comparison with gene microarray data revealed that 31% of the differentially regulated proteins correlate with altered mRNA expression in squamous cell lung carcinomas, including PEX1, MKK7 and HDAC3 for up-regulated proteins. The histone deacetylase (HDAC) 3 was investigated in detail by immunoblot analysis showing that HDAC3 is indeed elevated in 92% of tumours (n=22/24; P<0.001). Thus, antibody microarrays can be useful for detection of some target proteins related to lung cancer.

Antibodies, Monoclonal↗

PubMed2006

Converting a breast cancer microarray signature into a high-throughput diagnostic test.

BACKGROUND: A 70-gene tumor expression profile was established as a powerful predictor of disease outcome in young breast cancer patients. This profile, however, was generated on microarrays containing 25,000 60-mer oligonucleotides that are not designed for processing of many samples on a routine basis. RESULTS: To facilitate its use in a diagnostic setting, the 70-gene prognosis profile was translated into a customized microarray (MammaPrint) containing a reduced set of 1,900 probes suitable for high throughput processing. RNA of 162 patient samples from two previous studies was subjected to hybridization to this custom array to validate the prognostic value. Classification results obtained from the original analysis were then compared to those generated using the algorithms based on the custom microarray and showed an extremely high correlation of prognosis prediction between the original data and those generated using the custom mini-array (p < 0.0001). CONCLUSION: In this report we demonstrate for the first time that microarray technology can be used as a reliable diagnostic tool. The data clearly demonstrate the reproducibility and robustness of the small custom-made microarray. The array is therefore an excellent tool to predict outcome of disease in breast cancer patients.

Biomarkers, Tumor↗

PubMed2006

Gene expression profiles in Ciona intestinalis stigmatal cells: insight into formation of the ascidian branchial fissures.

Gill slits, a series of openings in the pharyngeal epithelium, are characteristic features of the hemichordate and chordate body plans. In ascidians, these openings, called stigmata, are formed in the branchial sac during juvenile development. Multiple whole-mount in situ hybridization analyses based on approximately 1,500 genes expressed in Ciona intestinalis juveniles, identified 28 genes expressed predominantly in the stigmatal cells. Expression patterns of these stigmatal genes were classified into four different categories. On the basis of these findings, we have been able to show that the peripheral region of a stigma consists of at least three different regions. The expression of a Dlk1-like gene was detected in nonciliated cells during the stigma perforation and division and was maintained in the basal region of the elliptical stigma. Expression of meichroacidin, tektin A1, and tektin B1 orthologs during the differentiation of the ciliated stigmatal cells suggests that some of the molecular mechanisms involved in sperm differentiation might be recruited for the stigma development, or vice versa. Components of the cilia such as alpha-tubulin and rootletin were also expressed in the stigmatal cells. These genes might facilitate further analyses regarding the evolution of the branchial fissures and the development of the ascidian stigmata.

Amino Acid Sequence↗

PubMed2006

A perspective on the use of iTRAQ reagent technology for protein complex and profiling studies.

Proteomic research includes the characterization of protein mixtures in order to understand complex biological systems and determine relationships between proteins, their function, and protein-protein interactions. Often the goal of such research is to monitor changes of proteins in perturbed systems, a type of study referred to as differential expression analysis. To perform these studies requires the ability to execute some type of differential comparison of a given protein state in reference to some type of a control. The iTRAQ reagents are a set of isobaric reagents which are amine specific and allow for the identification and quantitation of up to four different samples simultaneously. The amine specificity of these reagents makes most peptides in a sample amenable to this labeling strategy with no loss of information from samples involving post-translational modifications, such as the scrutiny of signal transduction pathways that often involve phosphorylation phenomena. In addition, the multiplexing capacity of these reagents allows for information replication within certain LC-MS/MS experimental regimes, providing additional statistical validation within any given experiment. The results presented herein demonstrate a few examples of the wide variety of quantitative information that can be realized when undertaking such experimental approaches. These include temporal analysis of drug-induced-protein expression, discovery and elucidation of disease markers, and protein-protein interactions in multi-protein complexes.

Animals↗

PubMed2006

Genetic prognostic index influences patient outcome for node-positive breast cancer.

PURPOSE: To establish a novel genetic prognostic index among node-positive breast cancer patients. METHODS: Using a cDNA microarray, the gene expression profiles of 20 primary breast cancers that had metastasis to four or more axillary lymph nodes were examined. Ten patients survived disease-free for more than 5 years (5S), while ten patients died of breast cancer within 5 years of surgery (5D). RESULTS: A set of genes characterizing each group was identified. Sixteen genes were underexpressed in 5D compared to 5S, and 15 genes were underexpressed in 5S in comparison to 5D. The prognostic index (PI) was established, which could predict the postoperative outcome with five genes that were commonly underexpressed in the 5D group; these genes encoded granulin (GRN), heat shock 90 kDa protein 1 beta (HSPCB), large tumor suppressor homolog 1 (LATS1), valosin-containing protein (VCP), and LIM-and-SH3 protein1 (LASP1). CONCLUSION: These five genes might play an important role in deciding the behavior of node-positive breast cancer. The PI system could thus predict the prognosis of node-positive breast cancer, and might therefore be able to provide valuable information for the prognosis of breast cancer patients.

Adult↗