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At least 685 records · Page 38Linked to original sources
PubMed2005

Prognostic factors in acute myeloid leukemia.

PURPOSE OF REVIEW: Cytogenetics offers the most important prognostic information at both presentation and relapse. However, this classification appears to be insufficient, especially for patients presenting with standard-risk cytogenetics, whose relapse risk is variable. Other prognostic factors, stratifying this heterogeneous group of patients into more clearly defined risk groups, are warranted. RECENT FINDINGS: Several molecular markers have been described that predict for long-term outcome in this heterogeneous group of patients; however, there is as yet no consensus as to the prognostic significance of each. Time to morphologic and molecular remission may also be important; however, further studies are warranted to establish their prognostic role in acute myeloid leukemia. SUMMARY: Much has been learnt over the past decade and a better understanding of disease biology, determined by gene expression profiling and proteomic analyses, may help to target therapy and improve the outcome.

Biomarkers, Tumor↗
PubMed2007

Experiences with dose finding in patients in early drug development: the use of biomarkers in early decision making.

With the increasing cost and complexity of drug development, biomarkers will play an increasing role in the early phases. Biomarkers can be classified into target, mechanistic, or outcome with varying degrees of linkage to disease or treatment effect. They can be used to determine proof of concept by characterising the efficacy or safety profiles, or determining differentiation from any competitor drugs. PK/PD modelling of biomarker data for novel and marketed compounds can be used to predict outpatient dose response. Subsequent simulations may replace or reduce the size and cost of larger phase 2b outpatient studies. Two examples of biomarkers and PK/PD modelling used to characterise dose response are presented. Penile plethysmography (RigiScan Plus) in male erectile dysfunction and phenylephrine challenge urethral pressure in benign prostatic hyperplasia are used to reduce time and cost to reach major exploratory development decision points in these indications.

Biomarkers↗
PubMed2003

Identification of biomarkers for ovarian cancer using strong anion-exchange ProteinChips: potential use in diagnosis and prognosis.

One hundred eighty-four serum samples from patients with ovarian cancer (n = 109), patients with benign tumors (n = 19), and healthy donors (n = 56) were analyzed on strong anion-exchange surfaces using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry technology. Univariate and multivariate statistical analyses applied to protein-profiling data obtained from 140 training serum samples identified three biomarker protein panels. The first panel of five candidate protein biomarkers, termed the screening biomarker panel, effectively diagnosed benign and malignant ovarian neoplasia [95.7% sensitivity, 82.6% specificity, 89.2% accuracy, and receiver operating characteristic (ROC) area under the curve of 0.94]. The other two panels, consisting of five and four candidate protein biomarkers each, effectively distinguished between benign and malignant ovarian neoplasia and were therefore referred to as validation biomarker panel I (81.5% sensitivity, 94.9% specificity, 88.2% accuracy, and ROC = 0.94) and validation biomarker panel II (72.8% sensitivity, 94.9% specificity, 83.9% accuracy, and ROC = 0.90). The three ovarian cancer biomarker protein panels correctly diagnosed 41 of the 44 blinded test samples: 21 of 22 malignant ovarian neoplasias [10 of 11 early-stage ovarian cancer (I/II) and 11 of 11 advanced-stage ovarian cancer (III/IV)], 6 of 6 low malignant potential, 5 of the 6 benign tumors, and 9 of 10 normal patient samples. In conclusion, we have discovered three ovarian cancer biomarker protein panels that, when used together, effectively distinguished serum samples from healthy controls and patients with either benign or malignant ovarian neoplasia.

Biomarkers, Tumor↗
PubMed2004

Technology insight: Emerging techniques to predict response to preoperative chemotherapy in breast cancer.

During the past decade, several high-throughput analytical methods have been developed, and most of these are being explored as potential diagnostic tools. Gene expression profiling with DNA microarrays or with multiplex polymerase chain reaction are the methods closest to being of clinical use. Prediction of clinically meaningful response to particular chemotherapy regimens or drugs remains a persistent challenge. There are established clinical and histopathologic predictors of prognosis for breast cancer, but there is no test to assist in selecting the optimal chemotherapy regimen for patients. Here we review recent advances in the application of gene expression profiling to chemotherapy response prediction.

Biomarkers, Tumor↗
PubMed2001

Education, lifestyle factors and mortality from cardiovascular disease and cancer. A 25-year follow-up of Swedish 50-year-old men.

BACKGROUND: There is a well-established inverse relation between education and mortality from cardiovascular disease and cancer. The reasons for this are still in part unclear. We aimed to investigate whether differences in traditional vascular risk factors, adult height, physical activity, and biomarkers of fatty acid and antioxidant intake, could explain this association. METHODS: In all, 2301 50-year-old men in Uppsala, Sweden (82% of the background population) were examined with regard to educational level, blood pressure, blood glucose, body mass index, serum lipids, smoking, body height, physical activity, serum beta carotene, alpha tocopherol, selenium, and serum fatty acids in cholesterol esters. Cause-specific mortality was registered 25 years later. RESULTS: Low education was associated with a higher rate of mortality from cardiovascular disease (crude relative risk [RR] = 1.67, 95% CI : 1.17-2.39), and from cancer (crude RR = 1.94, 95% CI : 1.21-3.10), compared to high educational attainment. Men with high education had an overall more beneficial risk factor profile concerning traditional cardiovascular risk factors, physical activity, and biomarkers of dietary intake of antioxidants and fat. After adjustment for all examined risk factors, the inverse gradient between education and cardiovascular mortality disappeared (RR in low education = 1.01. 95% CI : 0.67-1.52). Controlling for smoking, physical activity and dietary biomarkers explained less than half of the excess cancer mortality in the lower educational groups. Smoking (adjusted RR = 1.89, 95% CI : 1.37-2.61), and high proportions of palmitoleic acid in serum cholesterol esters (adjusted RR per 1 SD = 1.39, 95% CI : 1.07-1.82) predicted cancer mortality, independently of all other factors. There were no independent relations between serum antioxidants and mortality. CONCLUSIONS: These data indicate that modifiable lifestyle factors mediate the inverse gradient between education and death from cerebro- and cardiovascular disease. Smoking, physical activity and dietary factors explained half of the excess cancer mortality in lower educated groups. Further studies are needed to explore the proposed association between palmitoleic acid, a marker of high intake of animal and dairy fat, and cancer.

Antioxidants↗
PubMed1997

Molecular epidemiology: carcinogen-DNA adducts and genetic susceptibility.

Molecular epidemiological studies assess individual chemical exposures and genetic susceptibility in order to identify cancer risk. Such studies incorporate the development, application, and validation of biomarkers of cancer risk in order to enhance cancer risk assessments, focus cancer prevention strategies, and elucidate mechanisms of carcinogenesis. Current studies of molecular epidemiology are based upon an understanding of the complex, multistage process of carcinogenesis and interindividual variations in response to carcinogenic exposures. Quantitative methods to measure human exposures to carcinogens continue to improve and have been successfully applied to a number of epidemiological studies. Genetic predispositions to cancer, both inherited and acquired, have been and continue to be identified. The combined approach of associating genetic polymorphisms with carcinogen-DNA adduct measurements, in order to assess cancer risk, is showing considerable promise. It is hoped that, in the future, molecular epidemiologists will be able to develop a risk profile for an individual that includes assessment of multiple biomarkers. The field has the near-term potential to have a significant impact on regulatory quantitative risk assessments, which may aid in the determination of allowable exposures. Molecular epidemiological data may also aid in the identification of individuals who will most benefit by cancer prevention strategies.

Biomarkers, Tumor↗
PubMed2003

Role of biologic markers in patient selection and application to disease prevention.

Aromatase inhibitors (AIs) are now under investigation for the treatment of early stage breast cancer and for disease prevention as alternatives to standard treatment with tamoxifen. Currently identified genetic risk factors of breast cancer include BRCA-1/BRCA-2 mutations, ATM mutations, and history of high estrogen levels, as evidenced by plasma analyses and/or dense bones. To date, estrogen receptor (ER) and progesterone receptor (PgR) status has predictive value for determining response to therapy in patients with hormone receptor-positive breast cancer (ER+ and/or PgR+ tumors). Recent studies have shown AIs to be safer and more effective than tamoxifen in postmenopausal women with advanced disease. Some data suggest that letrozole may be a more effective treatment than tamoxifen for patients with ER+ and/or PgR+ early breast cancers expressing ErbB-1 and/or ErbB-2. Changes in cell proliferation markers (e.g., S-phase fraction and Ki67 antigen), plasma lipid levels, and the bone resorption marker C-terminal peptide are biomarkers that have been evaluated for preventive and prognostic value in breast cancer patients and normal volunteers. Results from biomarker screens can be used to define inclusion criteria for clinical trials and eventually to individualize treatment. Gene expression profiling (microarray analysis), i.e., genomic and proteomic studies, will probably advance the discovery of new biomarkers for breast cancer prevention and treatment.

Antineoplastic Agents↗
PubMed2003

Multiplexed protein profiling on antibody-based microarrays by rolling circle amplification.

Multiplexed immunoassays on antibody-based protein microarrays are an attractive solution for analyzing biological responses in normal and diseased states. Recently, the feasibility and utility of these assays has been established as concerns about specificity and sensitivity are being overcome by careful quality control and amplification technologies such as rolling circle amplification (RCA). RCA-amplified protein chips can now profile up to 150 proteins in various substrates including serum, plasma, and supernatants with high sensitivity, broad dynamic range and good reproducibility. Diagnostic utility of RCA-amplified protein chips has been shown for multiplexed allergen testing. When allied with multivariate statistical analysis, RCA protein chips have the potential to identify multiplexed biomarker classifiers for disease diagnosis and drug response.

Amino Acid Sequence↗
PubMed1998

Quinone profiling of bacterial communities in natural and synthetic sewage activated sludge for enhanced phosphate removal.

Respiratory quinones were used as biomarkers to study bacterial community structures in activated sludge reactors used for enhanced biological phosphate removal (EBPR). We compared the quinone profiles of EBPR sludges and standard sludges, of natural sewage and synthetic sewage, and of plant scale and laboratory scale systems. Ubiquinone (Q) and menaquinone (MK) components were detected in all sludges tested at molar MK/Q ratios of 0.455 to 0.981. The differences in MK/Q ratios were much larger when we compared different wastewater sludges (i.e., raw sewage and synthetic sewage) than when we compared sludges from the EBPR and standard processes or plant scale and laboratory scale systems. In all sludges tested a Q with eight isoprene units (Q-8) was the most abundant quinone. In the MK fraction, either tetrahydrogenated MK-8 or MK-7 was the predominant type, and there was also a significant proportion of MK-6 to MK-8 in most cases. A numerical cluster analysis of the profiles showed that the sludges tested fell into two major clusters; one included all raw sewage sludges, and the other consisted of all synthetic sewage sludges, independent of the operational mode and scale of the reactors and the phosphate accumulation. These data suggested that Q-8-containing species belonging to the class Proteobacteria (i.e., species belonging to the beta subclass) were the major constituents of the bacterial populations in the EBPR sludge, as well as in standard activated sludge. Members of the class Actinobacteria (gram-positive bacteria with high DNA G+C contents) were the second most abundant group in both types of sludge. The bacterial community structures in activated sludge processes may be affected more by the nature of the influent wastewater than by the introduction of an anaerobic stage into the process or by the scale of the reactors.

Journal Article↗
PubMed2005

A proteomic analysis of mammalian preimplantation embryonic development.

Genetic studies on the mammalian preimplantation embryo are providing a wealth of information regarding gene expression. However, changes in the transcriptome do not always reflect cellular function or the complexity and diversity of the mammalian proteome with post-translational modifications or protein-protein interactions. To elucidate embryonic cellular function, a detailed understanding at the protein level is necessary. The aim of this study was to generate protein profiles of mammalian embryos throughout development, and to investigate the effects of oxygen concentration on the embryonic proteome. A protocol was developed to analyse small groups of embryos (n = 5) by time-of-flight mass spectrometry. F1 mice zygotes were cultured in G1/G2 sequential media with recombinant albumin (2.5 mg/ml) in 6% CO(2) and O(2) concentrations of either 5% or 20%. In vivo-developed embryos were flushed from the reproductive tract (day 4). Protein profiles were generated for all embryonic samples and statistical analysis revealed 32 potential proteins/biomarkers with significant changes (P < 0.05). Embryos generated under 5% O(2) more closely resembled in vivo-developed embryos. Under 20% O(2) conditions, embryos showed down-regulation of 10 proteins/biomarkers (masses between 4 to 20 kDa) (P < 0.05) confirming the pathological effects of oxygen during embryonic development. These data demonstrate for the first time the complexity of the mammalian preimplantation proteome. The unique protein profiles of in vivo-developed embryos and a panel of selected biomarkers represent optimal cellular function, against which comparisons can be made to facilitate improvements in mammalian assisted reproduction techniques procedures.

Animals↗
PubMed2026

A stem-like chromatin program in small-cell lung cancer is associated with poor outcomes after chemoimmunotherapy.

Small-cell lung cancer (SCLC) is an aggressive malignancy with substantial tumor heterogeneity and limited clinically actionable biomarkers beyond established features such as liver metastases. We profile tumor-intrinsic chromatin accessibility in a patient-derived xenograft biobank and identify three recurrent chromatin programs: neuroendocrine, marked by ASCL1/NEUROD1 activity; immunogenic, marked by IRF-associated activity; and stem-like, marked by TEAD/OCT activity. These programs are reproduced at the cohort level across bulk and single-cell transcriptomic datasets comprising more than 800 tumors, including 300 extensive-stage samples. In patients treated with chemoimmunotherapy, the stem-like program is associated with inferior survival, including a median overall survival of 7.41 months versus 15.9 and 12.6 months for immunogenic and neuroendocrine groups, respectively. This association remains significant after adjustment for liver metastases, brain metastases, and elevated lactate dehydrogenase. These findings support a high-risk stem-like SCLC chromatin program for prospective biomarker refinement and therapeutic investigation.

ATAC-seq↗
PubMed2006

Molecular diagnosis of chronic liver disease and hepatocellular carcinoma: the potential of gene expression profiling.

Gene expression profile analysis through DNA microarrays and other high-throughput technologies permit simultaneous investigation of all genes within a biologic sample, providing a snapshot of the transcriptional state of healthy or diseased tissue. Although most of the current applications are still geared toward research (study of disease mechanisms/signaling pathways involved, identification of novel oncogenes/tumor suppressor genes), clinical diagnostic applications of this approach are beginning to enter more routine molecular usage. There are clear examples where a group of genes, or "signature," can provide clinically useful information (e.g., cancer prognosis and response to treatment). Importantly, the identification of genes that are up-regulated during tumorigenesis is heralding a new era of targeted molecular therapies in oncology. In addition, the high capacity of the technologies available allow for the identification of new biomarkers for early diagnosis. In the future, gene expression profiling ("disease fingerprinting") is likely to complement liver biopsy in the molecular differential diagnosis of chronic liver diseases and hepatocellular carcinoma (HCC). There has already been some success in the identification of subtypes of HCC based on derived sets of signature gene clusters. Data recently reported have been able to provide the first molecular classification of HCC, although more comprehensive studies are required to confirm these results and translate them into the clinical practice. In fact, variations in gene expression in normal and diseased livers, as well technical factors, are obstacles to the routine use of microarray-based methods in the liver clinic. Continued progress is anticipated in the practical application of gene array methods to refine diagnosis and therapy of HCC.

Carcinoma, Hepatocellular↗
PubMed2001

Delineation of prognostic biomarkers in prostate cancer.

Prostate cancer is the most frequently diagnosed cancer in American men. Screening for prostate-specific antigen (PSA) has led to earlier detection of prostate cancer, but elevated serum PSA levels may be present in non-malignant conditions such as benign prostatic hyperlasia (BPH). Characterization of gene-expression profiles that molecularly distinguish prostatic neoplasms may identify genes involved in prostate carcinogenesis, elucidate clinical biomarkers, and lead to an improved classification of prostate cancer. Using microarrays of complementary DNA, we examined gene-expression profiles of more than 50 normal and neoplastic prostate specimens and three common prostate-cancer cell lines. Signature expression profiles of normal adjacent prostate (NAP), BPH, localized prostate cancer, and metastatic, hormone-refractory prostate cancer were determined. Here we establish many associations between genes and prostate cancer. We assessed two of these genes-hepsin, a transmembrane serine protease, and pim-1, a serine/threonine kinase-at the protein level using tissue microarrays consisting of over 700 clinically stratified prostate-cancer specimens. Expression of hepsin and pim-1 proteins was significantly correlated with measures of clinical outcome. Thus, the integration of cDNA microarray, high-density tissue microarray, and linked clinical and pathology data is a powerful approach to molecular profiling of human cancer.

Biomarkers, Tumor↗
PubMed2002

Evaluation of a potential epigenetic biomarker by quantitative methyl-single nucleotide polymorphism analysis.

Tumorigenesis is characterized by alterations of methylation profiles including loss and gain of 5-methylcytosine. Recently, we identified a single CpG, which seemed to be consistently hypomethylated in pilocytic astrocytomas but not in other gliomas. To evaluate its applicability as a biomarker, we examined its methylation status in a large panel of gliomas (n = 97). Methylation-dependent DNA sequence variation may be considered a kind of single nucleotide polymorphism (methylSNP). MethylSNPs can be easily converted into common SNPs of the C/T type by sodium bisulfite treatment of the DNA and afterwards subjected to conventional SNP typing. We adapted SnaPshot trade mark and Pyrosequencing trade mark to determine the methylation of our test CpG in a quantitative manner. The adapted methods, called SNaPmeth and PyroMeth, respectively, gave nearly identical results, however data obtained with PyroMeth showed less scattering. Furthermore, the integrated software for allele frequency determination from Pyrosequencing could be used directly for data analysis while SnaPmeth data had to be exported and processed manually. Although data did not confirm our previous result of a preferential hypomethylation of the tested CpG in pilocytic astrocytomas, we consider quantitative methylSNP analysis by SNaPmeth or PyroMeth a favorable alternative to existing high-throughput methylation assays. It combines single CpG analysis with accurate quantitation and is amenable to high throughput.

Adolescent↗
PubMed2005

SELDI-TOF MS profiling of serum for detection of the progression of chronic hepatitis C to hepatocellular carcinoma.

Proteomic profiling of serum is an emerging technique to identify new biomarkers indicative of disease severity and progression. The objective of our study was to assess the use of surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) to identify multiple serum protein biomarkers for detection of liver disease progression to hepatocellular carcinoma (HCC). A cohort of 170 serum samples obtained from subjects in the United States with no liver disease (n = 39), liver diseases not associated with cirrhosis (n = 36), cirrhosis (n = 38), or HCC (n = 57) were applied to metal affinity protein chips for protein profiling by SELDI-TOF MS. Across the four test groups, 38 differentially expressed proteins were used to generate multiple decision classification trees to distinguish the known disease states. Analysis of a subset of samples with only hepatitis C virus (HCV)-related disease was emphasized. The serum protein profiles of control patients were readily distinguished from each HCV-associated disease state. Two-way comparisons of chronic hepatitis C, HCV cirrhosis, or HCV-HCC versus healthy had a sensitivity/specificity range of 74% to 95%. For distinguishing chronic HCV from HCV-HCC, a sensitivity of 61% and a specificity of 76% were obtained. However, when the values of known serum markers alpha fetoprotein, des-gamma carboxyprothrombin, and GP73 were combined with the SELDI peak values, the sensitivity and specifity improved to 75% and 92%, respectively. In conclusion, SELDI-TOF MS serum profiling is able to distinguish HCC from liver disease before cirrhosis as well as cirrhosis, especially in patients with HCV infection compared with other etiologies.

Adult↗