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PubMed2003

Direct comparison of microarray gene expression profiles between non-amplification and a modified cDNA amplification procedure applicable for needle biopsy tissues.

Global gene expression profiling by cDNA microarray analysis has been used to discover the biomarkers for early diagnosis of various cancers, subclassing cancer type, and prediction of patient's treatment outcome. The information provided by gene expression profiling may contribute to the design of molecular mechanism-based strategies for cancer prevention and/or treatment. However, the standard procedure for cDNA microarray analysis requires 5mug of good quality total RNA as starting material for each target preparation reaction. Thus, there is a limit for needle biopsy samples, laser capture microdissected tissues, or flow-sorted cells to successfully utilize the microarray technology. In order to profile the gene expression of needle biopsy tissue, we have modified the standard protocol by carrying out cDNA amplification after cDNA synthesis. We compared percentage present calls, absent calls, reproducibility, and concordance in needle biopsy samples processed by standard microarray protocol (cDNA non-amplification method) and our modified protocol (cDNA amplification method). The results showed that cDNA amplification method provided high reproducibility, representation, and concordance with the standard cDNA non-amplification method. We have successfully analyzed the gene expression profiles of needle biopsy tissues using the modified method without significantly changing the expression profiles. These results suggest that the global gene expression profiles of small biopsy samples can be achieved by our modified method to facilitate the analysis of gene expression profiles for clinical application.

Biopsy, Needle↗
PubMed2002

Proteomics and bioinformatics approaches for identification of serum biomarkers to detect breast cancer.

BACKGROUND: Surface-enhanced laser desorption/ionization (SELDI) is an affinity-based mass spectrometric method in which proteins of interest are selectively adsorbed to a chemically modified surface on a biochip, whereas impurities are removed by washing with buffer. This technology allows sensitive and high-throughput protein profiling of complex biological specimens. METHODS: We screened for potential tumor biomarkers in 169 serum samples, including samples from a cancer group of 103 breast cancer patients at different clinical stages [stage 0 (n = 4), stage I (n = 38), stage II (n = 37), and stage III (n = 24)], from a control group of 41 healthy women, and from 25 patients with benign breast diseases. Diluted serum samples were applied to immobilized metal affinity capture Ciphergen ProteinChip Arrays previously activated with Ni2+. Proteins bound to the chelated metal were analyzed on a ProteinChip Reader Model PBS II. Complex protein profiles of different diagnostic groups were compared and analyzed using the ProPeak software package. RESULTS: A panel of three biomarkers was selected based on their collective contribution to the optimal separation between stage 0-I breast cancer patients and noncancer controls. The same separation was observed using independent test data from stage II-III breast cancer patients. Bootstrap cross-validation demonstrated that a sensitivity of 93% for all cancer patients and a specificity of 91% for all controls were achieved by a composite index derived by multivariate logistic regression using the three selected biomarkers. CONCLUSIONS: Proteomics approaches such as SELDI mass spectrometry, in conjunction with bioinformatics tools, could greatly facilitate the discovery of new and better biomarkers. The high sensitivity and specificity achieved by the combined use of the selected biomarkers show great potential for the early detection of breast cancer.

Adult↗
PubMed2005

Prostate cancer and the genomic revolution: Advances using microarray analyses.

The emerging technology of microarray analysis allows the establishment of molecular portraits of prostate cancer and the discovery of novel genes involved in the carcinogenesis process. Many novel genes have already been identified using this technique, and functional analyses of these genes are currently being tested. The combination of microarray analysis with other recently developed high-throughput techniques, such as proteomics, tissue arrays, and gene promoter-methylation, especially using tissue microdissection methods, will provide us with more comprehensive insights into how prostate cancer develops and responds to gene-targeted therapies. Animal models of prostate cancer are being characterized by high throughput techniques to better define the similarities and differences between those models and the human disease, and to determine whether particular models may be useful for specific targeted therapies in pre-clinical studies. Although profiling of mRNA expression provides important information of gene expression, the development of proteomic technologies will allow for an even more precise global insight into cellular signaling and structural alterations during prostate carcinogenesis. Not only will the "omic" revolution change basic science, but it will lead to a new era of molecular medicine.

Animals↗
PubMed2005

Roadmap for developing and validating therapeutically relevant genomic classifiers.

Oncologists need improved tools for selecting treatments for individual patients. The development of therapeutically relevant prognostic markers has traditionally been slowed by poor study design, inconsistent findings, and lack of proper validation studies. Microarray expression profiling provides an exciting new technology for relating tumor gene expression to patient outcome, but it also provides increased challenges for translating initial research findings into robust diagnostics that benefit patients and physicians in therapeutic decision making. This article attempts to clarify some of the misconceptions about the development and validation of multigene expression signature classifiers and highlights the steps needed to move genomic signatures into clinical application as therapeutically relevant and robust diagnostics.

Biomarkers, Tumor↗
PubMed2006

From genome to proteome in tumor profiling: molecular events in colorectal cancer genesis.

Biomedical research has advanced rapidly in recent years with the sequencing of the human genome and the availability of technologies such as global gene and protein expression profiling using different chip platforms. However, this progress has not yet been transferred to the bedside. While detection of cancer at early stages is critical for curative treatment interventions, efficient diagnostic and therapeutic markers for the majority of malignancies still seem to be lacking. Comprehensive tumor profiling has therefore become a field of intensive research aiming at identifying biomarkers relevant for improved diagnostics and therapeutics. This chapter will demonstrate a genomic and proteomic approach while focusing on tumor profiling during colorectal cancer development.

Animals↗
PubMed2005

Quantitative determination of sterols and other alcohols in overland flow from grazing land and possible source materials.

Organic marker compounds (biomarkers) can be used to identify the sources of waterborne pollutants. This paper examines sterols and other alcohols in overland flow from pasture-based grazing systems, possible agricultural source materials and water extracts of these source materials as a preliminary step to developing chemical profiles that can be used for tracing pollutants. The biomarkers were quantified using gas chromatography and gas chromatography-mass spectrometry techniques. Analyses of plant material show that some pasture species contain unique compounds, enabling their identification. For example, Arctotheca calendula (capeweed) contains an as yet unidentified compound (Arctotheca m/z 163). Other pasture species that do not contain unique compounds do contain unique ratios of phytol, hexacosanol, octacosanol and 24-ethylcholesterol, enabling their identification. Analyses of faecal samples show that the ratios of sterols to stanols enable faeces to be distinguished from the pasture species, e.g. the ratio of 24-ethylcholesterol to 24-ethylcoprostanol was <1, generally <0.25 for faeces, while for most pasture species this ratio was >4. Using this ratio, qualitative apportioning of the sources of pollutants in overland flow to vegetation or faeces could be performed, but only in extreme cases (i.e. when the ratio <1 or >4). Decaying organic matter and surface soil appear to contain a composite of plant and faecal sterols. Sterols, being sparingly soluble in water and surface active, were not expected to be present in overland flow samples. Surprisingly, cholesterol and 24-ethylcoprostanol were found in both the particulate and filtrate fractions of most overland flow and water extracts of most source materials. Using the ratios of sterols to stanols, particulate organic material in water could be traced back to its broader source, i.e. vegetation or faeces.

Alcohols↗
PubMed2001

Estimating toxic damage to soil ecosystems from soil organic matter profiles.

Concentrations of particulate and total organic matter were measured in upper soil profiles at 26 sites as a potential means to identify toxic damage to soil ecosystems. Because soil organic matter plays a role in cycling nutrients, aerating soil, retaining water, and maintaining tilth, a significant reduction in organic matter content in a soil profile is not just evidence of a change in ecosystem function, but of damage to that soil ecosystem. Reference sites were selected for comparison to contaminated sites, and additional sites were selected to illustrate how variables other than environmental contaminants might affect the soil organic matter profile. The survey was undertaken on the supposition that environmental contaminants and other stressors reduce the activity of earthworms and other macrofauna, inhibiting the incorporation of organic matter into the soil profile. The profiles of the unstressed soils showed a continuous decrease in organic matter content from the uppermost mineral soil layer (0-2.5 cm) down to 15 cm. Stressed soils showed an abrupt decrease in soil organic matter content below a depth of 2.5 cm. The 2.5-5.0 cm layer of stressed soils--such as found in a pine barren, an orchard, sites contaminated with zinc, and a site with compacted soil--had less than 4% total organic matter and less than 1% particulate organic matter. However, damaged soil ecosystems were best identified by comparison of their profiles to the profiles of closely matched reference soils, rather than by comparison to these absolute values. The presence or absence of earthworms offered a partial explanation of observed differences in soil organic matter profiles.

Animals↗
PubMed2004

[Subclinical hypothyroidism].

Subclinical hypothyroidism is defined as normal serum free thyroxine and tri-iodothyronine concentrations and a slightly eleveted serum thyrotropin (TSH) concentration. Only laboratory results can detect this disorder. The causes of this disease are the same as those of overt hypothyroidism. Most patients with subclinical hypothyroidism should be treated with thyroxine aiming to reduce the patient's serum TSH concentration to normal. Treatment will prevent progression to overt hypothyroidism and in some cases ameliorate non specific symptoms and lipid profile.

Biomarkers↗
PubMed2004

Molecular classification of scrapie strains in mice using gene expression profiling.

Transmissible spongiform encephalopathy strains demonstrate specific prion characteristics, each with specific incubation times, and strain-specific patterns of deposition of the misfolded isoform of prion, PrPSc, in the brains of infected individuals. Different biochemical properties, including glycosylation profiles and the degree of proteinase resistance, have been shown to be strain-specific. However, no relationship between these properties and the phenotypic differences in the subsequent diseases has as yet been determined. Here we explore the utility of gene expression profiles to identify differences in the host response to different strains of prion agent. We identify 114 genes that exhibit significantly different levels of expression in mice infected with three strains of scrapie. These genes represent a pool of genes involved in a strain-specific response to prion disease. We have identified the most discriminatory genes from this list utilizing a wrapper-based feature selection algorithm with external cross-validation.

Algorithms↗
PubMed2005

Multiplexed analysis of serum cytokines as biomarkers in squamous cell carcinoma of the head and neck patients.

OBJECTIVE: Our objective was to characterize cytokine profiles in the systemic circulation of patients with active squamous cell carcinoma of the head and neck (SCCHN) compared with long-term tobacco smokers as controls. Furthermore, we hypothesized that persistent immune dysregulation in patients cured of their disease may be reflected in altered cytokine profiles in the systemic circulation. STUDY DESIGN: Retrospective, case-control study. METHODS: Using three well-defined clinical cohorts of SCCHN patients and smoker controls, we analyzed 100 microL of serum for a panel of 10 cytokines to determine whether serum cytokine profiles could distinguish clinically defined groups of SCCHN patients. Statistical analysis of multiplexed cytokine profiles was applied to classify three clinically defined groups: active SCCHN patients, treated SCCHN patients with no evidence of disease for over 3 years, and matched disease-free controls. Discrimination of outcome status was accomplished using classification trees, and 10-fold cross-validation was implemented to assess classification accuracy using independent data. RESULTS: We show that multiplexed cytokine and chemokine profiling may be performed to reflect the immune status of SCCHN patients. Selected cytokine profiles indicate that immunologic responses to carcinogenesis may not normalize even in the absence of tumor for over 3 years. CONCLUSION: Multiplexed serum cytokine profiles may be applicable to early detection, for screening those at high risk for SCCHN, and as clinically predictive biomarkers of disease status in successfully treated patients.

Biomarkers↗
PubMed2000

Functional foods: the US perspective.

Widespread interest in the possibility that selected foods might promote health has resulted in the coining of the term functional food, although agreement about what is and what is not a functional food is lacking. Public interest in functional foods is increasing because of higher health care costs; the passage of federal legislation affecting many food categories, including the expanded category of dietary supplements; and recent scientific discoveries linking dietary habits with the development of many diseases, including coronary heart disease and some cancers. A variety of foods have been proposed as providing health benefits by altering one or more physiologic processes. Biomarkers are needed to assess the ability of functional foods or their bioactive components to modify disease and to evaluate the ability of these foods to promote health, growth, and well-being. Evidence suggests that several biomarkers may be useful for distinguishing between diseased and nondiseased states and even for predicting future susceptibility to disease. A variety of biomarkers will probably be needed to develop a profile for an individual that reflects the impact of diet on performance and health. Another area of interest is the interaction of nutrients and their association with genetics. These interactions may account for the inconsistent interrelations observed between specific dietary constituents and the incidence of disease. Greater understanding of how diet influences a person's genetic potential, overall performance, and susceptibility to disease can have enormous implications for society. As new discoveries are made in this area, consumers will need access to this information so that they can make informed decisions.

Biological Availability↗
PubMed2006

cDNA microarray analysis reveals fundamental differences in the expression profiles of primary human monocytes, monocyte-derived macrophages, and alveolar macrophages.

We report the systematic use of large-scale cDNA microarrays to study the gene expression profiles of primary human peripheral blood monocytes (MONO) in comparison with in vitro-differentiated, M-CSF-induced MONO-derived macrophages (MAC) and primary human alveolar MAC (AM), obtained by bronchoalveolar lavage from the lungs of normal volunteers. These studies revealed large-scale differences in the gene expression profile between both MAC types (MAC and AM) and MONO. In addition, large differences were observed in the gene expression profiles of the two MAC types. Specifically, 21% of genes on the array (2904 out of 13,582) were differentially expressed between AM and MONO, and 2229 out of 13,583 probes were differentially expressed between MAC and AM. Our expression data show remarkable differences in gene expression between different MAC subpopulations and emphasize the heterogeneity of different MAC populations. This study underscores the need to scrutinize models of MAC biology for relevance to specific disease processes.

Adult↗
PubMed2006

Molecular profiling of ADAM12 in human bladder cancer.

PURPOSE: We have previously found ADAM12, a disintegrin and metalloprotease, to be an interesting biomarker for breast cancer. The purpose of this study was to determine the gene and protein expression profiles of ADAM12 in different grades and stages of bladder cancer. EXPERIMENTAL DESIGN: ADAM12 gene expression was evaluated in tumors from 96 patients with bladder cancer using a customized Affymetrix GeneChip. Gene expression in bladder cancer was validated using reverse transcription-PCR, quantitative PCR, and in situ hybridization. Protein expression was evaluated by immunohistochemical staining on tissue arrays of bladder cancers. The presence and relative amount of ADAM12 in the urine of cancer patients were determined by Western blotting and densitometric measurements, respectively. RESULTS: ADAM12 mRNA expression was significantly up-regulated in bladder cancer, as determined by microarray analysis, and the level of ADAM12 mRNA correlated with disease stage. Reverse transcription-PCR, quantitative PCR, and in situ hybridization validated the gene expression results. Using immunohistochemistry, we found ADAM12 protein expression correlated with tumor stage and grade. Finally, ADAM12 could be detected in the urine by Western blotting; ADAM12 was present in higher levels in the urine from patients with bladder cancer compared with urine from healthy individuals. Significantly, following removal of tumor by surgery, in most bladder cancer cases examined, the level of ADAM12 in the urine decreased and, upon recurrence of tumor, increased. CONCLUSIONS: ADAM12 is a promising biomarker of bladder cancer.

ADAM Proteins↗
PubMed2006

Identification of serum proteins discriminating colorectal cancer patients and healthy controls using surface-enhanced laser desorption ionisation-time of flight mass spectrometry.

AIM: To detect the new serum biomarkers for colorectal cancer (CRC) by serum protein profiling with surface-enhanced laser desorption ionisation--time of flight mass spectrometry (SELDI-TOF MS). METHODS: Two independent serum sample sets were analysed separately with the ProteinChip technology (set A: 40 CRC+49 healthy controls; set B: 37 CRC+31 healthy controls), using chips with a weak cation exchange moiety and buffer pH 5. Discriminative power of differentially expressed proteins was assessed with a classification tree algorithm. Sensitivities and specificities of the generated classification trees were obtained by blindly applying data from set A to the generated trees from set B and vice versa. CRC serum protein profiles were also compared with those from breast, ovarian, prostate, and non-small cell lung cancer. RESULTS: Mass-to-charge ratios (m/z) 3.1x10(3), 3.3x10(3), 4.5x10(3), 6.6x10(3) and 28x10(3) were used as classifiers in the best-performing classification trees. Tree sensitivities and specificities were between 65% and 90%. Most of these discriminative m/z values were also different in the other tumour types investigated. M/z 3.3x10(3), main classifier in most trees, was a doubly charged form of the 6.6x10(3)-Da protein. The latter was identified as apolipoprotein C-I. M/z 3.1x10(3) was identified as an N-terminal fragment of albumin, and m/z 28x10(3) as apolipoprotein A-I. CONCLUSION: SELDI-TOF MS followed by classification tree pattern analysis is a suitable technique for finding new serum markers for CRC. Biomarkers can be identified and reproducibly detected in independent sample sets with high sensitivities and specificities. Although not specific for CRC, these biomarkers have a potential role in disease and treatment monitoring.

Algorithms↗
PubMed2026

Exploration and experimental verification of triaptosis-related prognostic genes and cells in gastric cancer.

BACKGROUND: Triaptosis is a recently characterized form of programmed cell death with unclear implications in cancer. This study aimed to investigate the prognostic significance and biological relevance of triaptosis in gastric cancer (GC). METHODS: Transcriptomic and clinical data from TCGA-STAD and GSE62254, and single-cell RNA sequencing data from GSE183904 were analyzed. Triaptosis-related gene (TRG) scores were calculated using single-sample gene set enrichment analysis. Differentially expressed genes identified in TRG-score and GC-versus-normal comparisons underwent functional enrichment, Cox regression, and least absolute shrinkage and selection operator regression to develop an externally validated signature. Immune profiles, pathway activity, somatic mutations, tumor mutational burden (TMB), predicted drug sensitivity, and clinical features were compared by risk group. Single-cell analyses assessed TRG activity, prognostic gene expression, cell-cell communication, and pseudotime. Reverse transcription-quantitative PCR and Western blotting assessed mRNA expression and protein levels, respectively. RESULTS: A TRG-based prognostic model comprising ASPN, GRB14, and VTN was developed and externally validated, effectively distinguishing patients into two distinct risk groups with notably different survival outcomes. mRNA expression of all three genes and their protein levels were significantly higher in SGC-7901 cells than in GES-1 cells. High-risk patients had higher stromal scores and distinct immune profiles; 15 immune cell types differed between groups. Single-cell analysis revealed fibroblasts and pericytes among high-TRG-active cell types. Prognostic genes were significantly overexpressed in fibroblasts, which also showed high TRG activity. Fibroblasts demonstrated enhanced communication with pericytes, whereas tumor-derived fibroblasts showed weaker communication with macrophages, indicating immune microenvironment remodeling. CONCLUSION: The three-gene prognostic signature predicted GC prognosis and was associated with distinct immune and genomic features, suggesting potential value for risk stratification and personalized treatment.

Humans↗
PubMed2001

Transcriptional profiling in cancer: the path to clinical pharmacogenomics.

Cancer is a major source of morbidity and mortality, second only to heart disease as the leading cause of death in most developed countries. Our ability to treat the disease depends heavily on our understanding its aetiology. Different types of cancer often respond best to different courses of treatment, yet our understanding of cancer classification remains imperfect. Novel expression-monitoring technology provides unique opportunities to learn more about cancer at the molecular level, to improve classification methods, and to progress towards personalised cancer treatment. This review describes the techniques that make such advances possible, summarises recent work in the area, and discusses future developments needed to realise the potential of a thorough molecular classification of cancer.

Animals↗
PubMed2005

A novel technique to specifically analyze the secretome of cells and tissues.

The secretome of cells and tissues may reflect a broad variety of pathological conditions and thus represents a rich source of biomarkers. The identity of secreted proteins, usually isolated from cell supernatants or body fluids, is hardly accessible by direct proteome analysis, because these proteins are often masked by high amounts of proteins actually not secreted by the investigated cells. Here, we present a novel method for the specific detection of proteins secreted by human tissue specimen as well as cultured cells and chose liver as a model. The method is based on the metabolic labelling of proteins synthesized during a limited incubation period. Then, the cell supernatant is filtered, precipitated, and subjected to two-dimensional gel electrophoresis. Whereas fluorography detected a large number of proteins derived from residual plasma and dead cells, the autoradiographs selectively displayed genuinely secreted proteins. We demonstrate the feasibility of this approach by means of the secretomes of the hepatocellular carcinoma-derived cell line HepG2 and human liver slices. The selective identification of cell- and tissue-specific protein secretion profiles may help to identify novel sets of biomarkers for wide clinical applications.

Amino Acid Sequence↗
PubMed2003

Plasminogen activator inhibitor-2: a molecular biomarker for head and neck cancer progression.

Head and neck squamous cell carcinoma (HNSCC) is an aggressive epithelial malignancy in which the early diagnosis of premalignant lesions is known to directly correlate with increased survival. However, only a portion of biopsies showing dysplasia will progress to cancer, and there are no currently accepted criteria for predicting which lesions will progress. Therefore, diagnostic protocols that can identify the lesions that are likely to become HNSCC are required. RNA was isolated from normal keratinocytes, the immortalized but nontumorigenic HaCat cell line, and the tumor cell lines SCC-4, SCC-9, SCC-25, and OSCC-3. The RNA was then labeled and used to probe nylon microarray filters that contained a total of 9184 genes (5295 named and 3889 Expression Sequence Tags). Genes whose expression demonstrated a 3-fold or greater change were considered significant. Comparison of expression profiles from normal, HaCat, and four tumor cell lines revealed changes in gene expression in a total of 508 genes. Of these, 16 genes showed a consistent loss of expression when comparing normal to immortalized keratinocytes. In addition, 10 genes demonstrated a consistent loss of expression in the tumor cell lines only. In this latter group of genes, plasminogen activator inhibitor-2 (PAI-2), a gene whose expression has been linked to cell invasion, was additionally investigated. Altered expression of PAI-2 in the different cultured cells was validated via real-time quantitative-PCR. In addition, immunohistochemical evaluation of biopsy samples revealed a high expression of PAI-2 in both normal and dysplastic epithelium with a marked decrease of expression in areas of the biopsies containing HNSCC. These data demonstrate that genomic profiling can then be used to identify potential genotypic/phenotypic biomarkers that may predict which dysplastic lesions are most likely to progress to HNSCC.

Biomarkers, Tumor↗