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A Rapid Poly(ethylene glycol)-Assisted Magnetic Isolation Approach for High-Throughput Extracellular Vesicle Isolation and Subsequent Biomarker Analysis.

Extracellular vesicles (EVs) are crucial mediators of intercellular communication and have the potential to serve as biomarkers for disease diagnosis and therapeutic monitoring. However, most EV isolation methods often require large sample volumes and specialized instruments or involve trade-offs between purity, yield, cost, and scalability. We developed MagPEG, a workflow that combines poly(ethylene glycol) (PEG)-mediated EV aggregation with magnetic beads to provide a simple, reproducible alternative to ultracentrifugation, size-exclusion chromatography, and commercial precipitation kits. Our optimization experiments clarified the PEG concentration, ionic strength, and bead surface chemistry that collectively influence EV aggregation, capture efficiency, and contaminant coprecipitation, allowing us to define conditions that improve purity while maintaining high recovery. Compared with commonly used methods, MagPEG produced EVs with comparable size distribution, EV markers, and proteomic profiles while relying only on standard laboratory supplies. A key feature of the platform is that EVs and EV-associated DNA, RNA, and proteins can be sequentially extracted from the same bead-bound material, reducing sample loss and hands-on time and enabling multiomic analysis for limited clinical or small animal samples. MagPEG is compatible with downstream applications including proteomics, bead-based assays, and miRNA quantification. When applied to human serum, the method supported high-throughput EV proteomic profiling and enabled the identification of Alzheimer's disease-associated protein signatures, illustrating its utility for biomarker discovery. Overall, our results establish MagPEG as a powerful, rapid, scalable, and high-throughput solution for translational applications in biomarker discovery.

Polyethylene Glycols↗

Multiparametric flow cytometry immune profiling of pulmonary and extra-pulmonary tuberculosis reveals distinct blood-based biomarker signatures.

This study investigated immune cell distributions, cell-specific immune markers, and selected biomarker targets in pulmonary tuberculosis (PTB) and extrapulmonary tuberculosis (EPTB) using multiparametric flow cytometry (MFC). Whole blood was collected from 45 individuals, including healthy controls (HC), EPTB, and PTB patients (n&#x202f;=&#x202f;15/group). Peripheral blood leukocytes were analysed by MFC to characterize CD4+ and CD8+ T cells, natural killer (NK), invariant NKT (iNKT) and NKT cells, classical (CM), intermediate (IM) and non-classical monocytes (NCM), and activated monocytes (AM). Expression of GBP1, CALCOCO2, IFIT3, SNX10, ARG1, PD-1, and PD-L1 was assessed across these immune subsets. Increased frequencies of NK, NKT, and monocytes were observed in PTB and EPTB compared with HC, while CD4+, CD8+, iNKT, and AM were reduced. Monocyte-to-lymphocyte ratios were incrementally elevated in EPTB and PTB compared with HC. Despite variability of expression within groups, median biomarker fold-change expression changes were found between HC, EPTB and PTB groups; (i) (>2.0FC) for ARG1 in CD4, CD8, CM and AM, for CALCOCO2 in AM, GBP1 in CD8 and NCM, PD-1 in CD4, CD8, NK, IM and AM, PD-L1 in CD4, CD8, iNKT and NKT, NK, IM and AM and SNX10 in CD4, CD8, NCM, IM and AM (ii) (<2.0FC) in TB vs HC for CALCOCO2 in iNKT and NKT, IFIT3 in NCM, PD-1 in NK and NCM, PD-L1 in NCM, IM and AM and SNX10 in AM. Statistical significance was achieved for ARG1 (P&#x202f;=&#x202f;0.017) in CD4 cells. Our findings highlight distinct immune cell and biomarker signatures in PTB and EPTB.

Humans↗

[Proteomic profiling: the potential of Seldi-Tof for the identification of new cancer biomarkers].

Recent advances in proteomics offer opportunities to rapidly identify new biomarkers or pattern of markers for the early detection and diagnosis of cancer and to monitor the therapeutic efficacy and toxicity of treatments used to improve long-term survival of patients. The surfaced-enhanced laser desorption ionization/time-of-flight (Seldi-Tof) mass spectrometry is certainly one of the most promising approaches to achieve these goals. In this paper we will provide an overview of the studies that have used this new technology for the early diagnosis of human cancer.

Biomarkers, Tumor↗

Gene expression profiling of mouse bladder inflammatory responses to LPS, substance P, and antigen-stimulation.

Inflammatory bladder disorders such as interstitial cystitis (IC) deserve attention since a major problem of the disease is diagnosis. IC affects millions of women and is characterized by severe pain, increased frequency of micturition, and chronic inflammation. Characterizing the molecular fingerprint (gene profile) of IC will help elucidate the mechanisms involved and suggest further approaches for therapeutic intervention. Therefore, in the present study we used established animal models of cystitis to determine the time course of bladder inflammatory responses to antigen, Escherichia coli lipopolysaccharide (LPS), and substance P (SP) by morphological analysis and cDNA microarrays. The specific aim of the present study was to compare bladder inflammatory responses to antigen, LPS, and SP by morphological analysis and cDNA microarray profiling to determine whether bladder responses to inflammation elicit a specific universal gene expression response regardless of the stimulating agent. During acute bladder inflammation, there was a predominant infiltrate of polymorphonuclear neutrophils into the bladder. Time-course studies identified early, intermediate, and late genes that were commonly up-regulated by all three stimuli. These genes included: phosphodiesterase 1C, cAMP-dependent protein kinase, iNOS, beta-NGF, proenkephalin B and orphanin, corticotrophin-releasing factor (CRF) R, estrogen R, PAI2, and protease inhibitor 17, NFkB p105, c-fos, fos-B, basic transcription factors, and cytoskeleton and motility proteins. Another cluster indicated genes that were commonly down-regulated by all three stimuli and included HSF2, NF-kappa B p65, ICE, IGF-II and FGF-7, MMP2, MMP14, and presenilin 2. Furthermore, we determined gene profiles that identify the transition between acute and chronic inflammation. During chronic inflammation, the urinary bladder presented a predominance of monocyte/macrophage infiltrate and a concomitant increase in the expression of the following genes: 5-HT 1c, 5-HTR7, beta 2 adrenergic receptor, c-Fgr, collagen 10 alpha 1, mast cell factor, melanocyte-specific gene 2, neural cell adhesion molecule 2, potassium inwardly-rectifying channel, prostaglandin F receptor, and RXR-beta cis-11-retinoic acid receptor. We conclude that microarray analysis of genes expressed in the bladder during experimental inflammation may be predictive of outcome. Further characterization of the inflammation-induced gene expression profiles obtained here may identify novel biomarkers and shed light into the etiology of cystitis.

Animals↗

Comprehensive quality profiling and comparative metabolic characterization of seven dominant fresh-eating Chinese olive (Canarium album Lour.) cultivars in Southern China.

Fresh-eating Chinese olive (Canarium album Lour.) is a subtropical fruit endemic to southern China with considerable commercial value, yet systematic quality characterization of dominant cultivars remains scarce. This study established a multi-dimensional quality dataset for seven dominant cultivars from Fujian and Guangdong provinces, integrating nutritional components, soluble sugars, organic acids, mineral elements, volatile profiles, and non-targeted metabolomics. Significant cultivar-specific differences were observed across all evaluated dimensions: "Lingfeng" exhibited a sugar-dominant low-acid profile, whereas "Sanleng" showed elevated phenolic constituents accumulation. Volatile profiling identified terpenoid-based candidate discriminatory biomarkers, and metabolomic analysis revealed phenylpropanoid biosynthesis, tryptophan metabolism, and starch and sucrose metabolism as the most variable pathways. Correlations between untargeted profiling and targeted absolute quantification validated untargeted result reliability and revealed their complementarity in nutritional evaluation. These findings provide baseline data for FECO germplasm evaluation and targeted industrial utilization.

China↗

Discovering clinical biomarkers of ionizing radiation exposure with serum proteomic analysis.

In this study, we sought to explore the merit of proteomic profiling strategies in patients with cancer before and during radiotherapy in an effort to discover clinical biomarkers of radiation exposure. Patients with a diagnosis of cancer provided informed consent for enrollment on a study permitting the collection of serum immediately before and during a course of radiation therapy. High-resolution surface-enhanced laser desorption and ionization-time of flight (SELDI-TOF) mass spectrometry (MS) was used to generate high-throughput proteomic profiles of unfractionated serum samples using an immobilized metal ion-affinity chromatography nickel-affinity chip surface. Resultant proteomic profiles were analyzed for unique biomarker signatures using supervised classification techniques. MS-based protein identification was then done on pooled sera in an effort to begin to identify specific protein fragments that are altered with radiation exposure. Sixty-eight patients with a wide range of diagnoses and radiation treatment plans provided serum samples both before and during ionizing radiation exposure. Computer-based analyses of the SELDI protein spectra could distinguish unexposed from radiation-exposed patient samples with 91% to 100% sensitivity and 97% to 100% specificity using various classifier models. The method also showed an ability to distinguish high from low dose-volume levels of exposure with a sensitivity of 83% to 100% and specificity of 91% to 100%. Using direct identity techniques of albumin-bound peptides, known to underpin the SELDI-TOF fingerprints, 23 protein fragments/peptides were uniquely detected in the radiation exposure group, including an interleukin-6 precursor protein. The composition of proteins in serum seems to change with ionizing radiation exposure. Proteomic analysis for the discovery of clinical biomarkers of radiation exposure warrants further study.

Biomarkers, Tumor↗

Serum peptidome for cancer detection: spinning biologic trash into diagnostic gold.

The low molecular weight region of the serum peptidome contains protein fragments derived from 2 sources: (a) high-abundance endogenous circulating proteins and (b) cell and tissue proteins. While some researchers have dismissed the serum peptidome as biological trash, recent work using mass spectrometry-based (MS-based) profiling has indicated that the peptidome may reflect biological events and contain diagnostic biomarkers. In this issue of the JCI, Villanueva et al. report on MS-based peptide profiling of serum samples from patients with advanced prostate, bladder, or breast cancer as well as from healthy controls. Surprisingly, the peptides identified as cancer-type-specific markers proved to be products of enzymatic breakdown generated after patient blood collection. The impact of these results on cancer biomarker discovery efforts is significant because it is widely believed that proteolysis occurring ex vivo should be suppressed because it destroys endogenous biomarkers. Villanueva et al. now suggest that this suppression may in fact be preventing biomarker generation.

Biomarkers↗

Proteomic approaches to tumor marker discovery.

CONTEXT: Current tumor markers for ovarian cancer still lack adequate sensitivity and specificity to be applicable in large populations. High-throughput proteomic profiling and bioinformatics tools allow for the rapid screening of a large number of potential biomarkers in serum, plasma, or other body fluids. OBJECTIVE: To determine whether protein profiles of plasma can be used to identify potential biomarkers that improve the detection of ovarian cancer. DESIGN: We analyzed plasma samples that had been collected between 1998 and 2001 from patients with sporadic ovarian serous neoplasms before tumor resection at various International Federation of Gynecology and Obstetrics stages (stage I [n = 11], stage II [n = 3], and stage III [n = 29]) and from women without known neoplastic disease (n = 38) using proteomic profiling and bioinformatics. We compared results between the patients with and without cancer and evaluated their discriminatory performance against that of the cancer antigen 125 (CA125) tumor marker. RESULTS: We selected 7 biomarkers based on their collective contribution to the separation of the 2 patient groups. Among them, we further purified and subsequently identified 3 biomarkers. Individually, the biomarkers did not perform better than CA125. However, a combination of 4 of the biomarkers significantly improved performance (P < or =.001). The new biomarkers were complementary to CA125. At a fixed specificity of 94%, an index combining 2 of the biomarkers and CA125 achieves a sensitivity of 94% (95% confidence interval, 85%-100.0%) in contrast to a sensitivity of 81% (95% confidence interval, 68%-95%) for CA125 alone. CONCLUSIONS: The combined use of bioinformatics tools and proteomic profiling provides an effective approach to screen for potential tumor markers. Comparison of plasma profiles from patients with and without known ovarian cancer uncovered a panel of potential biomarkers for detection of ovarian cancer with discriminatory power complementary to that of CA125. Additional studies are required to further validate these biomarkers.

Adult↗

Real-time PCR technology for cancer diagnostics.

BACKGROUND: Advances in the biological sciences and technology are providing molecular targets for diagnosing and treating cancer. Current classifications in surgical pathology for staging malignancies are based primarily on anatomic features (e.g., tumor-node-metastasis) and histopathology (e.g., grade). Microarrays together with clustering algorithms are revealing a molecular diversity among cancers that promises to form a new taxonomy with prognostic and, more importantly, therapeutic significance. The challenge for pathology will be the development and implementation of these molecular classifications for routine clinical practice. APPROACH: This article discusses the benefits, challenges, and possibilities for solid-tumor profiling in the clinical laboratory with an emphasis on DNA-based PCR techniques. CONTENT: Molecular markers can be used to provide accurate prognosis and to predict response, resistance, or toxicity to therapy. The diversity of genomic alterations involved in malignancy necessitates a variety of assays for complete tumor profiling. Some new molecular classifications of tumors are based on gene expression, requiring a paradigm shift in specimen processing to preserve the integrity of RNA for analysis. More stable markers (i.e., DNA and protein) are readily handled in the clinical laboratory. Quantitative real-time PCR can determine gene duplications or deletions. Furthermore, melting curve analysis immediately after PCR can identify small mutations, down to single base changes. These techniques are becoming easier and faster and can be multiplexed. Real-time PCR methods are a favorable option for the analysis of cancer markers. SUMMARY: There is a need to translate recent discoveries in oncology research into clinical practice. This requires objective, robust, and cost-effective molecular techniques for clinical trials and, eventually, routine use. Real-time PCR has attractive features for tumor profiling in the clinical laboratory.

Biomarkers, Tumor↗

Assessing the utility of SELDI-TOF and model averaging for serum proteomic biomarker discovery.

The SELDI-TOF technique was used to profile serum proteins from Type 1 diabetes (T1D) patients and healthy autoantibody-negative (AbN) controls. Univariate and multivariate analyses were performed to identify putative biomarkers for T1D and to assess the reproducibility of the SELDI technique. We found 146 protein/peptide peaks (581 total peaks discovered) in human serum showing statistical differences in expression levels between T1D patients and controls, with 84% of these peaks showing technical replication. Because individual proteins did not offer great power for disease prediction, we used our model averaging approach that combines the information from multiple multivariate models to accurately classify T1D and control subjects (88.9% specificity and 90.0% sensitivity). Analyses of a test subset of the data showed less accuracy (82.8% specificity and 76.2% sensitivity), although the results are still positive. Unfortunately, no multivariate model could be replicated using the same samples. This first attempt of high throughput analyses of the human serum proteome in T1D patients suggests that model averaging is a viable method for developing biomarkers; however, the reproducibility of SELDI-TOF is currently not sufficient to be used for classification of complex diseases like T1D.

Adolescent↗

Constitutive androstane receptor (CAR) as a potential sensing biomarker of persistent organic pollutants (POPs) in aquatic mammal: molecular characterization, expression level, and ligand profiling in Baikal seal (Pusa sibirica).

To characterize the function of constitutive active/androstane receptor (CAR) in aquatic mammals, CAR complementary DNA (cDNA) was cloned from the liver of Baikal seal (Pusa sibirica) from Lake Baikal, Russia, and the messenger RNA (mRNA) expression levels in various tissues/organs of the wild population and the CAR ligand profiles were investigated. The seal CAR cDNA had an open reading frame of 1047 bp encoding 348 amino acids that revealed 74-84% amino acid identities with CARs from rodents and human. The mRNA expression profile of tissues/organs represented that Baikal seal CAR was predominantly expressed in the liver followed by heart and intestine. The expression analysis of hepatic CAR mRNA showed no correlation with expression of cytochrome P450 (CYP) 1A, 1B, 2B, 2C, and 3A-like proteins, indicating that the CAR expression level may not be the sole determinant of the regulation of these CYP expressions in the seal liver. There was no significant correlation between CAR expression and any of the persistent organic pollutants (POPs) levels. Furthermore, we performed an in vitro CAR transactivation assay using MCF-7 cells transfected with Baikal seal CAR expression plasmid and (NR1)(3)-luciferase reporter gene plasmid. In the transactivation analysis of Baikal seal CAR, neither repression by androstanol and androstenol, nor activation by estrone and estradiol, which are recognized as endogenous ligands for mouse and human CARs, was detected. On the other hand, bile acids such as chenodeoxycholic acid, deoxycholic acid, and lithocholic acid activated the seal CAR as well as mouse CAR. As for exogenous chemicals, the seal CAR was transactivated by a human CAR agonist, 6-(4-chlorophenyl)imidazo[2,1-b][1,3]thiazole-5-carbaldehyde O-(3,4-dichlorobenzyl)oxime), but not by a mouse CAR agonist, (1,4-bis[2-(3,5-dichloropyridyloxy)]benzene). In addition, the seal CAR was also activated by polychlorinated biphenyls (PCBs) (Kanechlor-500, International Union of Pure and Applied Chemistry No. PCB153; 2,2',4,4',5,5'-hexachlorobiphenyl and PCB180; 2,2',3,4,4',5,5'-heptachlorobiphenyl), and 1,1,1-trichloro-2,2-bis(p-chlorophenyl)ethane (p,p'-DDT) and its metabolite, 1,1-dichloro-2,2-bis(p-chlorophenyl)ethylene (p,p'-DDE). The seal CAR responded more sensitively to PCBs than the mouse CAR. Based on the results of CAR transactivation assay, the lowest observable effect levels of Kanechlor-500, PCB153, PCB180, p,p'-DDT, and p,p'-DDE in Baikal seal were estimated to be 10, 20, 20, 10, and 10 ppm on wet weight basis, respectively. These results suggest that CAR is conserved in diverse mammalian species including seals. Whereas the seal CAR-mediated gene transcription may potentially be a sensitive response to the exposure of certain POPs, the ligand profile of seal CAR may be different from those of other mammalian CARs. This study indicates that CAR-mediated responses may be useful information to assess the ecotoxicological risk of xenobiotics such as POPs in wildlife but the previous results derived from rodent and human CAR may not be applicable to the risk assessment in wild species.

Amino Acid Sequence↗

Probing gender-specific metabolism differences in humans by nuclear magnetic resonance-based metabonomics.

The measurement of metabolite profiles that are interpreted to yield biomarkers using multivariate data analysis is now a well-established approach for gaining an improved understanding of the impact of genetic modifications, toxicological and therapeutic interventions, and exposure to stimuli (e.g., noxious agents, stressors, nutrients) on the network of transcripts, proteins, and metabolites present in cells, tissues, or whole organisms. This has been termed metabonomics. In this study, multivariate analysis of (1)H nuclear magnetic resonance (NMR) spectra of metabolite profiles of urine and plasma from 150 healthy humans revealed that in young people and/or individuals with low body mass indexes, females had higher rates of lipid biosynthesis than did males, whereas males had higher rates of protein turnover than did females. With increasing age, overall lipid biosynthesis decreased in females, whereas metabolism increasingly favored lipid synthesis over protein turnover in males. By relating the derived metabonomic data to known metabolic pathways and published biochemical data, it appears that females synthesize relatively more lipoproteins and unsaturated lipids than do males. Furthermore, the changes in lipid biosynthesis and urinary citrate excretion in females showed a positive correlation. Estrogen most likely plays an essential role in the regulation of, and communication between, protein and lipid biosynthesis by controlling pH in mitochondria and the cytoplasm and hence the observed altered citrate levels.

Adolescent↗

Pan-cancer analysis identifies KANSL2 as a cell-cycle-associated regulator of tumor progression and immunity in liver hepatocellular carcinoma.

KANSL2, a core component of the NSL histone acetyltransferase complex, has been implicated in tumorigenesis. However, its pan-cancer relevance and functional role in liver hepatocellular carcinoma (LIHC) remain unclear. Multi-omics data from TCGA, GEO, and HPA were integrated to systematically evaluate KANSL2 expression, clinical significance, genomic alterations, and immune associations across cancers. Functional enrichment, immune infiltration analyses, and single-cell transcriptomics were performed. In vitro assays were conducted to validate the biological effects of KANSL2 in LIHC cells. KANSL2 is broadly upregulated across cancers and exhibits strong diagnostic performance. Elevated KANSL2 expression correlates with unfavorable prognosis, particularly in LIHC. Mechanistically, KANSL2 and its co-expressed genes are enriched in cell-cycle progression. KANSL2 expression is also closely associated with immune infiltration and immunoregulatory signaling within the tumor microenvironment, with single-cell data indicating preferential expression in proliferative T-cell subsets. Functional experiments demonstrate that KANSL2 silencing suppresses proliferation, migration, and invasion, and induces G2/M phase arrest in LIHC cells. Notably, its effects on apoptosis are limited, suggesting that KANSL2 primarily drives tumor progression through cell-cycle-dependent mechanisms. This study identifies KANSL2 as a key regulator of tumor progression and immune remodeling in LIHC. By promoting malignancy predominantly via cell-cycle control, KANSL2 represents a promising biomarker for diagnosis and prognosis, and a potential therapeutic target.

Carcinoma, Hepatocellular↗

Changes of urinary and blood porphyrin profiles by exposure to PCBs, lead or diazinon in rats.

Porphyrin profiles in excreta or blood have been useful biomarkers for monitoring exposure of hazardous xenobiotics to human or animals. We evaluated and compared the changes in urinary and blood copro-, uro-, and protoporphyrins during and after the exposure of Aroclor1254 (PCBs), lead (Pb) or diazinon to rats. PCBs (10, 50 and 100 mg/kg bw), Pb (62.5, 250 and 1,000 ppm) and diazinon (10, 30 and 90 mg/k bw) were administered to rats via gavage (PCBs and diazinon) or via drinking water (Pb) daily for 5 w. Urine and blood were collected weekly for the 5 w of exposure and for 5 w after withdrawal. Three urinary porphyrins and blood protoporphyrin increased gradually with PCB dose in a time dependent manner and remained elevated for 5 w after withdrawal. Urinary porphyrins were increased rapidly by Pb and then returned to normal immediately after Pb withdrawal while blood protoporphyrin remained high but gradualy decreased during the 5 w after withdrawal. Diazinon did not affect blood and urinary porphyrins as did PCBs and Pb, but just induced a weak increase of urinary coproporphyrin. Urinary and blood porphyrin profiles can be used as biomarkers for exposure assessment to PCBs and Pb. The normal ranges of blood porphyrins in cattle, pigs, chickens and rats were also established for use as biomarkers.

Administration, Oral↗

Precision periodontology in clinical practice: bridging omics and clinical decision-making.

BACKGROUND: Precision periodontology integrates molecular diagnostics, genomics, and advanced imaging into clinical decision-making. Despite major advances in microbiome characterisation, host genetics, and inflammatory biomarkers, their translation into routine care remains limited. OBJECTIVES: To critically appraise current evidence on microbiome-based profiling, genetic and epigenetic markers, host-response biomarkers, and three-dimensional imaging in periodontology, and to propose a conceptual decision-support framework linking diagnostic outputs to potential therapeutic actions and future implementation research. MATERIALS AND METHODS: A narrative review searching PubMed/MEDLINE, Scopus, Embase, and the Cochrane Library (2010-2025) using terms related to precision periodontology, subgingival microbiome, periodontitis genetics and epigenetics, salivary and GCF biomarkers, aMMP-8, CBCT, risk assessment, and artificial intelligence. Priority was given to meta-analyses, systematic reviews, longitudinal studies, and guideline documents. RESULTS: Microbiological testing has defined but narrow indications; single-SNP genotyping has not demonstrated clinical utility commensurate with cost; aMMP-8 point-of-care testing is among the most extensively investigated host-response tools and may have adjunctive value in selected monitoring and peri-implant scenarios; however, current evidence remains insufficient to support routine diagnostic implementation. CBCT may directly influence surgical decision-making through defect morphology characterisation. AI-based models show promise but lack prospective clinical validation. These conclusions are consistent with the 20th EFP Workshop Consensus Report. CONCLUSIONS: Precision periodontology currently operates in addition to, rather than in replacement of, conventional staging and grading. We propose a conceptual decision-threshold framework for the selective consideration of molecular and advanced imaging tools when their additive contribution may meaningfully inform management. This framework should be regarded as a research-oriented decision-support model rather than a validated clinical algorithm. CLINICAL RELEVANCE: Clinicians are provided with a structured, evidence-based framework that identifies specific clinical scenarios where molecular diagnostics, host-response biomarkers, and three-dimensional imaging may meaningfully modify periodontal treatment decisions, supporting the operationalisation of precision approaches in daily practice.

Humans↗

Algorithmic fusion of gene expression profiling for diffuse large B-cell lymphoma outcome prediction.

Many different methods and techniques have been investigated for the processing and analysis of microarray gene expression profiling datasets. It is noted that the accuracy and reliability of the results are often dependent on the measurement approaches applied, and no single measurement so far is guaranteed to generate a satisfactory result. In this paper, an algorithmic fusion approach is presented for extracting genes that are predictive to clinical outcomes (survival-fatal) of diffuse large B-cell lymphoma on a set of microarray data for gene expression profiling. The approach integrates a set of measurements from different aspects in terms of the discrepancy indications and merit expectations of the gene expression patterns with respect to the clinical outcomes. A combination of statistical and non-statistical criteria, continuous and discrete parameterizations, as well as model-based and modeless evaluations is applied in the approach. By integrating these measurements, a set of genes that are indicative to the clinical outcomes are better captured from the gene expression profiling dataset.

Algorithms↗

Overview of biomarkers and surrogate endpoints in drug development.

There are numerous factors that recommend the use of biomarkers in drug development including the ability to provide a rational basis for selection of lead compounds, as an aid in determining or refining mechanism of action or pathophysiology, and the ability to work towards qualification and use of a biomarker as a surrogate endpoint. Examples of biomarkers come from many different means of clinical and laboratory measurement. Total cholesterol is an example of a clinically useful biomarker that was successfully qualified for use as a surrogate endpoint. Biomarkers require validation in most circumstances. Validation of biomarker assays is a necessary component to delivery of high-quality research data necessary for effective use of biomarkers. Qualification is necessary for use of a biomarker as a surrogate endpoint. Putative biomarkers are typically identified because of a relationship to known or hypothetical steps in a pathophysiologic cascade. Biomarker discovery can also be effected by expression profiling experiment using a variety of array technologies and related methods. For example, expression profiling experiments enabled the discovery of adipocyte related complement protein of 30 kD (Acrp30 or adiponectin) as a biomarker for in vivo activation of peroxisome proliferator-activated receptors (PPAR) gamma activity.

Adiponectin↗

Developmental expression profiles of Xenopus laevis reference genes.

Cell differentiation depends mainly on specific mRNA expression. To quantify the expression of a particular gene, the normalisation with respect to the expression of a reference gene is carried out. This is based on the assumption that the expression of the reference gene is constant during development, in different cells or tissues or after treatment. Xenopus laevis studies have frequently used eEF-1 alpha, GAPDH, ODC, L8, and H4 as reference genes. The aim of this work was to examine, by real-time RT-PCR, the expression profiles of the above-mentioned five reference genes during early development of X. laevis. It is shown that their expression profiles vary greatly during X. laevis development. The developmental changes of mRNA expression can thus significantly compromise the relative mRNA quantification based on these reference genes, when different developmental stages are to be compared. The normalisation against total RNA is recommended instead.

Animals↗