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PubMed2026

Accelerating Lung Cancer Management Through Previsit Liquid Biopsy: Results From the LUNG-FAST Pilot Study.

BACKGROUND: Timely molecular profiling is essential for treatment selection in non-small cell lung cancer (NSCLC), yet delays in biomarker testing remain common. We evaluated the feasibility and early clinical impact of a nurse navigator-driven workflow to initiate liquid biopsy before the initial oncology visit. METHODS: LUNG-FAST (Liquid Biopsy for Urgent Neoplastic Genomic Profiling Focused Accelerated Stratification and Testing) was a 4-month prospective pilot at a tertiary cancer center. Intake nurse navigators identified eligible patients with suspected or newly diagnosed lung cancer and facilitated previsit liquid biopsy ordering. Feasibility, turnaround times, genomic findings, and early clinical outcomes were assessed. RESULTS: Among 64 patients, intake nurse navigators identified 94% (60/64) of eligible cases. Liquid biopsy was ordered in 58 patients, with 62% (36/58) placed before the initial oncology visit. Median turnaround time from blood draw to results was 8.5 days for commercial testing and 12.5 days for institutional testing. FDA-actionable genomic alterations were identified in 34% (22/64) of patients, while an additional 11% (7/64) harbored clinically relevant, non-FDA-actionable alterations. Overall, FDA-actionable or clinically relevant alterations were identified in 45% (29/64), with 22% detected by liquid biopsy and an additional 23% by tissue-only profiling. Median time from new patient visit to systemic therapy was 26 days. CONCLUSIONS: A nurse navigator-driven workflow enabling previsit liquid biopsy is feasible and identifies actionable genomic alterations in a substantial proportion of patients with lung cancer. Plasma and tissue profiling are complementary, and earlier plasma-based testing may expedite treatment decision-making while highlighting opportunities to optimize biomarker testing workflows.

Humans↗
PubMed1998

Biomarkers in toxicology.

The use of biomarkers in toxicology is becoming increasingly important. This article briefly reviews some of the aspects in an attempt to give an overall view of the field. Some of the new developments, particularly in relation to biomarkers of exposure and response, are mentioned. Specific DNA and protein adducts can now be used as biomarkers of the effective exposure so incorporating variations in environmental levels and individual disposition. Analysis of urinary metabolite profiles by NMR can highlight novel markers and allow recognition of patterns of metabolite changes as biomarkers of a toxic response. Novel urinary markers for liver and testicular dysfunction are discussed. Finally, the acetylator phenotype as a biomarker of susceptibility is described.

Animals↗
PubMed2005

Exhaled volatile organic compounds in patients with non-small cell lung cancer: cross sectional and nested short-term follow-up study.

BACKGROUND: Non-invasive diagnostic strategies aimed at identifying biomarkers of lung cancer are of great interest for early cancer detection. The aim of this study was to set up a new method for identifying and quantifying volatile organic compounds (VOCs) in exhaled air of patients with non-small cells lung cancer (NSCLC), by comparing the levels with those obtained from healthy smokers and non-smokers, and patients with chronic obstructive pulmonary disease. The VOC collection and analyses were repeated three weeks after the NSCLC patients underwent lung surgery. METHODS: The subjects' breath was collected in a Teflon bulb that traps the last portion of single slow vital capacity. The 13 VOCs selected for this study were concentrated using a solid phase microextraction technique and subsequently analysed by means of gas cromatography/mass spectrometry. RESULTS: The levels of the selected VOCs ranged from 10(-12) M for styrene to 10(-9) M for isoprene. None of VOCs alone discriminated the study groups, and so it was not possible to identify one single chemical compound as a specific lung cancer biomarker. However, multinomial logistic regression analysis showed that VOC profile can correctly classify about 80% of cases. Only isoprene and decane levels significantly decreased after surgery. CONCLUSION: As the combination of the 13 VOCs allowed the correct classification of the cases into groups, together with conventional diagnostic approaches, VOC analysis could be used as a complementary test for the early diagnosis of lung cancer. Its possible use in the follow-up of operated patients cannot be recommended on the basis of the results of our short-term nested study.

Aged↗
PubMed2004

Proteomics for hepatocellular carcinoma marker discovery.

Refinements of serological markers and screening of patients at high risk for developing hepatocellular carcinoma (HCC) may lead to better HCC detection, earlier intervention, and successful treatment, improving long-term outcomes. Proteomics promises the discovery of biomarkers for early HCC detection and diagnosis. Proteomic-based profiling uniquely allows delineation of global changes in expression patterns resulting from transcriptional and posttranscriptional control, posttranslational modifications, and shifts in proteins between cellular compartments. Approaches to that effect include direct serum protein profiling and comparative analysis of protein expression in normal, precancerous, and early-stage tumor tissues. Identification of panels of tumor antigens that elicit a humoral response also may contribute to the discovery of new markers for HCC screening and diagnosis. Today, 2-dimensional polyacrylamide gel electrophoresis, multidimensional liquid chromatography, mass spectrometry, and protein microarrays are among the proteomic tools available for biomarker and drug target discovery. We review these technologies and their application to the study of HCC. Our objective is to provide a framework for appreciating the promise, while at the same time understanding the challenges behind translating proteomics discovery into novel diagnostic tests.

Biomarkers, Tumor↗
PubMedDate not supplied

Effects of estradiol with oral or intravaginal progesterone on risk markers for breast cancer in a postmenopausal monkey model.

OBJECTIVE: To evaluate the effects of oral estradiol given with either oral or intravaginal micronized progesterone (P4) on risk biomarkers for breast cancer in a postmenopausal monkey model. DESIGN: This experiment was a two-way crossover study in which 20 ovariectomized adult female cynomolgus macaques were treated (in equivalent doses for women) with oral estradiol (1 mg/d) + oral micronized P4 (200 mg/d) or intravaginal P4 delivered by Silastic rings (6- to 10-mg/d release rate). Hormone treatments lasted 2 months and were separated by a 1-month washout period. The primary outcome measure was breast epithelial proliferation. RESULTS: Serum P4 concentrations were significantly greater in subjects receiving oral P4 (10.9 ng/mL) compared with intravaginal P4 (3.8 ng/mL) at 2 to 3 hours after oral dosing (P<0.0001) but not at 24 to 28 hours after oral dosing (2.9 ng/mL for oral P4 vs 3.2 ng/mL for intravaginal P4 at 2 months, P=0.19). Serum estradiol concentrations were significantly lower after oral P4 than after intravaginal P4 (P<0.05 for all time points). Oral P4 resulted in significantly decreased body weight (-2.5%) compared with intravaginal P4 (+3.6%) (P=0.0001). Markers of breast proliferation, sex steroid receptor expression, and endometrial area did not differ significantly between oral P4 and intravaginal P4 treatments (P>0.1 for all). CONCLUSIONS: Despite different pharmacodynamic profiles, oral and intravaginal P4 had similar effects on biomarkers in the postmenopausal breast.

Administration, Intravaginal↗
PubMed2025

Uncovering potential biomarkers and metabolic pathways in systemic lupus erythematosus and lupus nephritis through integrated microbiome and metabolome analysis.

OBJECTIVE: This study aims to explore the relationship between gut microbiota and fecal metabolomic profiles in patients with systemic lupus erythematosus (SLE), with and without lupus nephritis (LN), in order to identify potentially relevant biomarkers and better understand their association with disease progression. METHODS: Fecal samples from 15 healthy controls (HC) and 36 SLE patients (18 SLE-nonLN and 18 SLE-LN) were analyzed using 16S rRNA gene sequencing and untargeted metabolomics. Differential microbial taxa and metabolites were identified using Linear Discriminant Analysis Effect Size (LEfSe) and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Receiver Operating Characteristic (ROC) curve analyses were used to assess the potential clinical relevance of selected metabolites. RESULTS: Beta diversity analysis demonstrated distinct microbial clustering between groups (p&#x2009;<&#x2009;0.05). SLE-LN samples showed an increased relative abundance of Proteobacteria and decreased Firmicutes compared to SLE-nonLN. Metabolomic profiling identified multiple differentially abundant metabolites, with notable enrichment in primary bile acid biosynthesis pathways (e.g., Glycocholic acid, AUC&#x2009;=&#x2009;0.951). In the SLE-nonLN group, increased Glycoursodeoxycholic acid levels (AUC&#x2009;=&#x2009;0.922) were observed in pathways related to taurine and hypotaurine metabolism. Correlation analysis indicated a negative association between Escherichia-Shigella and bile acid levels (p&#x2009;<&#x2009;0.01). CONCLUSION: This integrative analysis suggests that patients with SLE and LN harbor distinct gut microbiota and metabolomic profiles. The identified microbial taxa and metabolites may have potential as non-invasive biomarkers and could contribute to a better understanding of SLE pathogenesis and progression.

Humans↗
PubMed2006

[Microarray-based transcriptome analyses in infectious diseases. A new diagnostic method].

The complex interaction between a pathogen and a host is the molecular basis of infectious diseases. Microarray technology is a powerful tool to investigate the crosstalk between pathogen and the host as it assesses whole genome expression profiles in response to disease. Deciphering the molecular details on both sides of the host-pathogen interaction will increase our understanding of the pathogenesis of infectious diseases and offer improvements in their diagnosis, treatment, prognosis, and prevention.

Biomarkers↗
PubMed2006

Activation of aminoflavone (NSC 686288) by a sulfotransferase is required for the antiproliferative effect of the drug and for induction of histone gamma-H2AX.

Aminoflavone (AF) is entering clinical trials. We recently reported that AF induces DNA-protein cross-links (DPC) and gamma-H2AX in MCF-7 human breast cancer cells. To elucidate the mechanism of action of AF and provide biomarkers indicative of AF activity, we correlated AF activity profile (GI(50)) with gene expression patterns in the NCI-60 cell lines. Sulfotransferases (SULT) showed the highest positive correlation coefficients among approximately 14,000 probe sets analyzed (r = 0.537, P < 0.001). Stable transfection of SULT1A1 into AF-resistant MDA-MB-231 cells sensitized these cells to AF. AF produced DPCs, gamma-H2AX foci, and S-phase arrest in the SULT1A1-transfected but not in the parent MDA-MB-231 cells. Conversely, cells in which SULT1A1 was knocked down by small interfering RNA failed to induce gamma-H2AX. Inhibition of SULTs and cytochrome P450 (CYP) enzymes by natural flavonoids blocked the antiproliferative activity of AF and the formation of AF-DNA adducts. AF also induces SULT1A1 and CYP expression in MCF-7 cells, suggesting the existence of an aryl hydrocarbon receptor-mediated positive feedback for AF activation by CYP and SULT1A1. Metabolism studies showed that AF can be oxidized by CYP at two amino groups to form N-hydroxyl metabolites that are substrates for bioactivation by SULTs. We propose that both N-sulfoxy-groups can be further converted to nitrenium ions that form adducts with DNA and proteins. The results reported here show the importance of SULT1A1 and CYP for AF activation and anticancer activity. They also suggest using SULT1A1 and gamma-H2AX as biomarkers for prediction of AF activity during patient selection and monitoring of clinical trials.

Adenocarcinoma↗
PubMed2005

Tissue microarrays: applications in genomic research.

The widespread application of tissue microarrays in cancer research and the clinical pathology laboratory demonstrates a versatile and portable technology. The rapid integration of tissue microarrays into biomarker discovery and validation processes reflects the forward thinking of researchers who have pioneered the high-density tissue microarray. The precise arrangement of hundreds of archival clinical tissue samples into a composite tissue microarray block is now a proven method for the efficient and standardized analysis of molecular markers. With applications in cancer research, tissue microarrays are a valuable tool in validating candidate markers discovered in highly sensitive genome-wide microarray experiments. With applications in clinical pathology, tissue microarrays are used widely in immunohistochemistry quality control and quality assurance. The timeline of a biomarker implicated in prostate neoplasia, which was identified by complementary DNA expression profiling, validated by tissue microarrays and is now used as a prognostic immunohistochemistry marker, is reviewed. The tissue microarray format provides opportunities for digital imaging acquisition, image processing and database integration. Advances in digital imaging help to alleviate previous bottlenecks in the research pipeline, permit computer image scoring and convey telepathology opportunities for remote image analysis. The tissue microarray industry now includes public and private sectors with varying degrees of research utility and offers a range of potential tissue microarray applications in basic research, prognostic oncology and drug discovery.

Animals↗
PubMed2026

Protein Biomarkers in Risk and Prognosis of Amyotrophic Lateral Sclerosis.

BACKGROUND: Plasma and cerebrospinal fluid (CSF) protein biomarkers in amyotrophic lateral sclerosis (ALS) may provide insight into disease mechanisms and yield clinically useful biomarkers. METHODS: Overall, 363 proteins in plasma and CSF from 198 patients with ALS and 125 matched controls were profiled using Olink assays. Associations with disease status, survival, and functional decline, as well as longitudinal biomarker stability across the disease course were assessed, together with network and enrichment analyses. ALS risk-associated biomarkers were externally validated in the UK Biobank (UKB). RESULTS: Overall, 125 proteins were significantly associated with at least one outcome (i.e., case status, risk, survival, or functional decline), and 21 were associated with three or more outcomes. NEFL was the most robust biomarker in plasma and CSF, alongside TNFRSF12A in plasma and CSF, EDA2R in plasma, and FABP4 in plasma and CSF. Most biomarkers remained stable longitudinally across the disease course. ALS risk-associated biomarkers were replicated in UKB, in which >&#x2009;3000 plasma proteins were measured in 52,990 participants, including 298 with ALS. Network and enrichment analyses highlighted their roles in immune response and extracellular-matrix remodeling, and their enrichments in the brain and T-cell subsets. Construction of an ALS risk-prediction model achieved an ROC-AUC of 0.72 in the UKB validation cohort. CONCLUSIONS: These findings suggest candidate protein biomarkers for ALS risk stratification, early detection, and clinical therapeutic monitoring.

Humans↗
PubMed2006

A distinct inflammatory gene expression profile in patients with psoriatic arthritis.

Psoriatic arthritis (PsA) is a systemic inflammatory condition featuring polyarthritis associated with psoriasis. Apart from clinical indicators, few biomarkers exist to aid in the diagnosis and management of PsA. We hypothesized that whole blood gene expression profiling would provide new diagnostic markers and/or insights into pathogenesis of the disease. We compared whole blood gene expression profiles in PsA patients and in age-matched controls. We identified 310 differentially expressed genes, the majority of which are upregulated in PsA patients. The PsA expression profile does not significantly overlap with profiles derived from patients with rheumatoid arthritis or systemic lupus erythematosus. Logistic regression identified two lymphocyte-specific genes (zinc-finger protein 395 and phosphoinositide-3-kinase 2B) that discriminate PsA patients from normal controls. In addition, a highly coregulated cluster of overexpressed genes implicated in protein kinase A regulation strongly correlates with erythrocyte sedimentation rate. Other clusters of coregulated, yet suppressed genes in PsA patient blood include molecules involved in T-cell signaling. Finally, differentially expressed genes in PsA fall into diverse functional categories, but many downregulated genes belong to a CD40 signaling pathway. Together, the data suggest that gene expression profiles of PsA patient blood contain candidate novel disease markers and clues to pathogenesis.

Adolescent↗
PubMed2005

Multiclass cancer classification and biomarker discovery using GA-based algorithms.

MOTIVATION: The development of microarray-based high-throughput gene profiling has led to the hope that this technology could provide an efficient and accurate means of diagnosing and classifying tumors, as well as predicting prognoses and effective treatments. However, the large amount of data generated by microarrays requires effective reduction of discriminant gene features into reliable sets of tumor biomarkers for such multiclass tumor discrimination. The availability of reliable sets of biomarkers, especially serum biomarkers, should have a major impact on our understanding and treatment of cancer. RESULTS: We have combined genetic algorithm (GA) and all paired (AP) support vector machine (SVM) methods for multiclass cancer categorization. Predictive features can be automatically determined through iterative GA/SVM, leading to very compact sets of non-redundant cancer-relevant genes with the best classification performance reported to date. Interestingly, these different classifier sets harbor only modest overlapping gene features but have similar levels of accuracy in leave-one-out cross-validations (LOOCV). Further characterization of these optimal tumor discriminant features, including the use of nearest shrunken centroids (NSC), analysis of annotations and literature text mining, reveals previously unappreciated tumor subclasses and a series of genes that could be used as cancer biomarkers. With this approach, we believe that microarray-based multiclass molecular analysis can be an effective tool for cancer biomarker discovery and subsequent molecular cancer diagnosis.

Algorithms↗
PubMed2005

Altered expression of TFF-1 and CES-2 in Barrett's Esophagus and associated adenocarcinomas.

Identification of biomarkers to recognize individuals with Barrett's esophagus (BE) predisposed to develop malignancy is currently a pressing issue. We utilized gene expression profiling to compare molecular signatures of normal esophagus and stomach, BE, and adenocarcinoma (AC) to identify such potential biomarkers. Over 22,000 genes were analyzed by oligonucleotide microarrays on 38 unique RNA Unsupervised and supervised clusterings were performed on a subset of 2849 genes that varied most significantly across the specimens. Immunohistochemistry (IHC) for two of the significantly differentially expressed gene products was performed on tissue microarrays. Unsupervised clustering identified two discernable molecular BE profiles, one of which was similar to normal gastric tissue ("BE1"), and another that was shared by several of the AC specimens ("BE2"). The BE1 profile included expression of several genes that have been described as tumor-suppressor genes, most notably trefoil factor 1 (TFF-1). The BE2 profile included expression of genes previously found overexpressed in cancers, such as carboxylesterase-2 (CES-2). IHC demonstrated the loss of TFF-1 late in the progression of BE to AC. It also revealed CES-2 as being upregulated in AC documented to have arisen in the presence of BE. These potential biomarkers, as well as the relative expression of genes from BE1 versus those from BE2, may be validated in the future to aid in risk stratification and guide treatment protocols in patients with BE and associated AC.

Adenocarcinoma↗
PubMed2005

Absolute quantitation of cancer-related proteins using an MS-based peptide chip.

New technologies are needed that can diagnose cancer more rapidly and accurately. These technologies must also have the ability to identify the particular cellular abnormalities contributing to the malignancy, thus directing the appropriate treatments. Such technologies should permit absolute quantitation of specific tumor biomarkers and their level of posttranslational modifications. Quantitative molecular profiling of cancer signaling networks would provide a more detailed understanding of the contribution of protein expression and posttranslational modification levels to tumorigenesis. We have developed a unique approach for absolute quantitation of protein expression that integrates affinity capture of proteolytic peptides with mass spectrometry and thus provides detection, identification, and quantitation of their cognate proteins. We have previously shown the high sensitivity and specificity of this approach. Here we demonstrate the absolute quantitation of a model peptide using our technology. We have used this approach to capture epitope-containing peptides from proteolytically digested target proteins, including p53, epidermal growth factor receptor (EGFR), and prostate-specific antigen (PSA). Our technology can easily be extended to the absolute quantitation of protein modification levels, in addition to the determination of protein expression levels, and can be readily adapted for use in a microarray format. This method offers an improved approach to protein chip technology that should prove useful for clinical diagnosis and drug development applications.

Antibodies, Monoclonal↗
PubMed2006

Unique microRNA molecular profiles in lung cancer diagnosis and prognosis.

MicroRNA (miRNA) expression profiles for lung cancers were examined to investigate miRNA's involvement in lung carcinogenesis. miRNA microarray analysis identified statistical unique profiles, which could discriminate lung cancers from noncancerous lung tissues as well as molecular signatures that differ in tumor histology. miRNA expression profiles correlated with survival of lung adenocarcinomas, including those classified as disease stage I. High hsa-mir-155 and low hsa-let-7a-2 expression correlated with poor survival by univariate analysis as well as multivariate analysis for hsa-mir-155. The miRNA expression signature on outcome was confirmed by real-time RT-PCR analysis of precursor miRNAs and cross-validated with an independent set of adenocarcinomas. These results indicate that miRNA expression profiles are diagnostic and prognostic markers of lung cancer.

Adenocarcinoma↗
PubMed2006

Molecular characterization of human adenomyosis.

Adenomyosis is a common gynaecological disorder characterized by the abnormal growth of endometrium into the myometrium and myometrial hypertrophy/hyperplasia. Uterine fibroids are benign neoplasms of the myometrium, and they represent a diagnostic pitfall for adenomyosis. In this study, we have used the genome-wide Affymetrix U133 Plus 2.0 microarray platform to compare the gene expression patterns of adenomyosis, uterine fibroids, normal endometrium and myometrium. Unsupervised principal component analysis (PCA) revealed that these four tissue types could be segregated from one another solely based on their gene expression profiles. Analysis of variance (ANOVA), followed by Tukey means separation test, significance analysis of microarrays (SAM) and 2-fold change threshold, identified 7415 probe sets as differentially expressed among the four groups of samples. Supervised cluster analysis based on these probe sets clustered adenomyosis most closely with endometrium and uterine fibroids with myometrium, consistent with the anatomic origin of these two diseases. The Tukey means separation post hoc testing found 2073 probe sets altered between adenomyosis and normal endometrium or myometrium, and 2327 probe sets altered in expression when comparing uterine fibroids with myometrium. Using Ingenuity Pathways Analysis (IPA), we found 9 highly significant functional networks in adenomyosis and 10 in uterine fibroids. Notably, the top network in both cases was associated with functions implicated in cancer and cell death. Finally, we compared the gene expression profiles of adenomyosis and uterine fibroids and identified 471 differentially expressed probe sets that may represent potential biomarkers for the differential diagnosis of these diseases.

Analysis of Variance↗
PubMed2006

An ecotoxicoproteomic approach (SELDI-TOF mass spectrometry) to biomarker discovery in crab exposed to pollutants under laboratory conditions.

Ciphergen ProteinChip Technology is a proteomic tool, used for the discovery of new and sensitive biomarkers. This approach was used to evaluate the protein profile of crabs exposed to various pollutants. Two different exposure experiments were performed: spider crabs (Hyas araneus) were exposed for 3 weeks to diallyl phatalate (DAP), bisphenol A (BisA) and polybrominated diphenyl ether (PBDE-47), while shore crabs (Carcinus maeanas) were exposed to crude oil, crude oil spiked with alkylphenols (APs) and 4-nonylphenol (NP). Gender and species-related protein pattern alterations were observed and compared to controls. Results showed different responses to pollutants by the two species. Major disruption in protein peak expression was observed in samples exposed to mixtures of pollutants, i.e. oil spiked with APs. Compared to shore crab, spider crab species showed a lower degree of response in terms of number of altered protein peaks following exposure. In general, female individuals of both species showed a larger number of significantly altered proteins compared to males. Data analysis by non-metric multi-dimensional scaling (MDS) was performed. Bi-dimesional-MDS plots revealed a good separation of groups for both spider and shore crabs. In some cases, a good discrimination can also be observed between the two genders within each treatment. Results highlight the potential of crabs as sentinel organisms for the aquatic environment. The results indicate that SELDI-ToF technology is a powerful tool to discover protein expression signatures for different pollutants and sex dependent responses.

Animals↗