Hepatitis C virus 3'X region interacts with human ribosomal proteins

To identify proteins that can bind the 3' untranslated region (UTR) of hepatitis C virus (HCV) we screened human cDNA libraries using the Saccharomyces cerevisiae three-hybrid system. Screening with an RNA sequence derived from the 3'-terminal 98 nucleotides (3'X region) of an infectious clone of HCV (H77c) yielded clones of human ribosomal proteins L22, L3, S3, and mL3, a mitochondrial homologue of L3. We performed preliminary characterization of the binding between the 3'X region and these proteins by a three-hybrid mating assay using mutant 3'X sequences. We have further characterized the interaction between 3'X and L22, since this protein is known to be associated with two small Epstein-Barr virus (EBV)-encoded RNA species (EBERs) which are abundantly produced in cells latently infected with EBV. The EBERs, which have similar predicted secondary structure to the HCV 3'X, assemble into ribonucleoprotein particles that include L22 and La protein. To confirm that L22 binds HCV 3'X we performed in vitro binding assays using recombinant L22 (expressed as a glutathione S-transferase [GST] fusion protein) together with a 3'X riboprobe. The 3'X region binds to the GST-L22 fusion protein (but not to GST alone), and this interaction is subject to competition with unlabeled 3'X RNA. To establish the functional role played by L22 in internal ribosome entry site (IRES)-mediated translation of HCV sequences we performed translational analysis in HuH-7 cells using monocistronic and bicistronic reporter constructs. The relative amount of core-chloramphenicol acetyltransferase reporter protein translated under the control of the HCV IRES was stimulated in the presence of L22 and La when these proteins were supplied in trans.

A network of protein-protein interactions in yeast

A global analysis of 2,709 published interactions between proteins of the yeast Saccharomyces cerevisiae has been performed, enabling the establishment of a single large network of 2,358 interactions among 1,548 proteins. Proteins of known function and cellular location tend to cluster together, with 63% of the interactions occurring between proteins with a common functional assignment and 76% occurring between proteins found in the same subcellular compartment. Possible functions can be assigned to a protein based on the known functions of its interacting partners. This approach correctly predicts a functional category for 72% of the 1,393 characterized proteins with at least one partner of known function, and has been applied to predict functions for 364 previously uncharacterized proteins.

Constitutive activation of the Saccharomyces cerevisiae transcriptional regulator Ste12p by mutations at the amino-terminus

The transcriptional activator Ste12p is required for the expression of genes induced by mating pheromone in the yeast Saccharomyces cerevisiae. We identified mutations in the amino-terminal DNA-binding domain of Ste12p that lead to constitutively high-level transcription of pheromone-induced genes. The behaviour of these mutant proteins is consistent with an enhanced DNA-binding ability. Cells carrying these hyperactive proteins retain their sensitivity to pheromone treatment, and their phenotype is largely dependent on the presence of at least one of the MAP kinases (Fus3p or Kss1p) and the scaffold protein Ste5p. Deletion of either FUS3 or KSS1 leads to a marked increase in Ste12p activity, consistent with a negative regulatory role for Fus3p, similar to that described for Kss1p. The properties of the constitutive mutants support the idea that the pheromone response pathway plays a role in basal as well as pheromone-induced transcription.

Optimizing parameters for computer-aided diagnosis of microcalcifications at mammography

RATIONALE AND OBJECTIVES

The purpose of this study was to optimize selection of the mammographic features most useful in discriminating benign from malignant clustered microcalcifications.

MATERIALS AND METHODS

The computer-aided diagnosis (CAD) system automatically extracted from digitized mammograms 13 quantitative features characterizing microcalcification clusters. Archival cases (n = 134; patient age range, 31-77 years; mean age, 56.8 years) with known histopathologic results (79 malignant, 55 benign) were selected. Three radiologists at three facilities independently analyzed the microcalcifications by using the CAD system. Stepwise discriminant analysis selected the features best discriminating benign from malignant microcalcifications. A classification scheme was constructed on the basis of these optimized features, and its performance was evaluated by using receiver operating characteristic (ROC) analysis.

RESULTS

Six of the 13 variables extracted by the CAD system were selected by stepwise determinant analysis for generating the classification scheme, which yielded an ROC curve with an area (Az) of 0.98, specificity of 83.64%, positive predictive value of 89.53%, and accuracy of 91.79% for 98% sensitivity. When patient age was an additional variable, the scheme's performance improved, but this was not statistically significant (Az = 0.98). The ROC curve of the classifier (without age as an additional variable) yielded a high Az of 0.96 for patients younger than 50 years and an even higher (P < .02) Az of 0.99 for those 50 years or older.

CONCLUSION

Stepwise discriminant analysis optimized performance of a classification scheme for microcalcifications by selecting six optimized features. Scheme performance was significantly (P < .02) higher for women 50 years or older, but the addition of patient age as a variable did not produce a statistically significant increase in performance.

Quantitative characterization of mass lesions on digitized mammograms for computer-assisted diagnosis

RATIONALE AND OBJECTIVES

To investigate features for discriminating benign from malignant mammographic findings by using computer-aided diagnosis (CAD) and to test the accuracy of CAD interpretations of mass lesions.

METHODS

Fifty-five sequential, mammographically detected mass lesions, referred for biopsy, were digitized for computerized reevaluation with a CAD system. Quantitative features that characterize spiculation were automatically extracted by the CAD system. Data generated by 271 known retrospective cases were used to set reference values indicating the range for malignant and benign lesions. After conventional interpretation of the 55 prospective cases, they were evaluated a second time by the radiologist using the extracted features and the reference ranges. In addition, a pattern-recognition scheme based on the extracted features was used to classify the prospective cases. Accuracy of interpretation with and without the CAD system was evaluated using receiver operating characteristic (ROC) curve analysis.

RESULTS

Sensitivity of the CAD diagnosis for the prospective cases improved from 92% to 100%. Specificity improved significantly from 26.7% to 66.7%. This was accompanied by a significant increase in the accuracy of diagnosis from 56.4% to 81.8% and in the positive predictive value from 51.1% to 71.4%. The Az for the CAD ROC curve significantly increased from 0.73 to 0.90. The performance of the classification scheme was slightly lower than that of the radiologists' interpretation with the CAD system.

CONCLUSIONS

Use of the CAD system significantly improved the accuracy of diagnosis. The findings suggest that the classification scheme may improve the radiologist's ability to differentiate benign from malignant mass lesions in the interpretation of mammograms.

Genome-wide analysis of vaccinia virus protein-protein interactions

To detect interactions between proteins of vaccinia virus, we carried out a comprehensive two-hybrid analysis to assay every pairwise combination. We constructed an array of yeast transformants that contained each of the 266 predicted viral ORFs as Gal4 activation domain hybrid proteins. The array was individually mated to transformants containing each ORF as a Gal4-DNA-binding domain hybrid, and diploids expressing the two-hybrid reporter gene were identified. Of the approximately 70,000 combinations, we found 37 protein-protein interactions, including 28 that were previously unknown. In some cases, e.g., late transcription factors, both proteins were known to have related roles although there was no prior evidence of physical associations. For some other interactions, neither protein had a known role. In the majority of cases, however, one of the interacting proteins was known to be involved in DNA replication, transcription, virion structure, or host evasion, thereby providing a clue to the role of the other uncharacterized protein in a specific process.

Path analysis on the risk of mortality in very low birth weight infants

OBJECTIVE

The purpose of this work is to clarify by path analysis which of the predictor factors of mortality in a cohort of 423 singletons VLBW infants born at Beilinson Medical Center during the years 1980-1990 (pre-surfactant era) exert direct or indirect effect on mortality. A direct risk factor was defined as a factor having an immediate effect on the outcome without working through an intermediate variable. By contrast, an indirect risk factor was defined as a factor that does not have a direct effect on the risk of mortality but instead works through an intermediate variable. Evaluation of mortality was done at three points over time (pre-delivery, at birth and post-delivery).

RESULTS

In the pre-delivery model, gestational age, appropriateness for gestational age, mother's age and fetal distress work directly on mortality in VLBW infants. At birth, mother's age, birth weight and Apgar score at the fifth minute work directly on the risk of mortality. When the assessment of the risk of death was done post-delivery, mother's age, birth weight, Apgar score at the fifth minute and seizures influence directly on mortality risk, and fetal distress, gestational age and pre-natal induced hypertension (PIH) operate indirectly on the risk of mortality.

CONCLUSION

The methodology we have used can be adopted in other investigations to distinguish and measure the effect of prognostic factors on the risk of an outcome.

Improved mammographic interpretation of masses using computer-aided diagnosis

The aim of this study was to evaluate the effectiveness of computerized image enhancement, to investigate criteria for discriminating benign from malignant mammographic findings by computer-aided diagnosis (CAD), and to test the role of quantitative analysis in improving the accuracy of interpretation of mass lesions. Forty sequential mammographically detected mass lesions referred for biopsy were digitized at high resolution for computerized evaluation. A prototype CAD system which included image enhancement algorithms was used for a better visualization of the lesions. Quantitative features which characterize the spiculation were automatically extracted by the CAD system for a user-defined region of interest (ROI). Reference ranges for malignant and benign cases were acquired from data generated by 214 known retrospective cases. The extracted parameters together with the reference ranges were presented to the radiologist for the analysis of 40 prospective cases. A pattern recognition scheme based on discriminant analysis was trained on the 214 retrospective cases, and applied to the prospective cases. Accuracy of interpretation with and without the CAD system, as well as the performance of the pattern recognition scheme, were analyzed using receiver operating characteristics (ROC) curves. A significant difference (p < 0.005) was found between features extracted by the CAD system for benign and malignant cases. Specificity of the CAD-assisted diagnosis improved significantly (p < 0.02) from 14 % for the conventional assessment to 50 %, and the positive predictive value increased from 0.47 to 0.62 (p < 0.04). The area under the ROC curve (A(z)) increased significantly (p < 0. 001) from 0.66 for the conventional assessment to 0.81 for the CAD-assisted analysis. The A(z) for the results of the pattern recognition scheme was higher (0.95). The results indicate that there is an improved accuracy of diagnosis with the use of the mammographic CAD system above that of the unassisted radiologist. Our findings suggest that objective quantitative features extracted from digitized mammographic findings may help in differentiating between benign and malignant masses, and can assist the radiologist in the interpretation of mass lesions.

CT-guided aspiration core needle biopsy of gastrointestinal wall lesions

PURPOSE

The purpose of this work was to examine the accuracy and safety of CT-guided core biopsy of gastrointestinal wall lesions.

METHOD

We reviewed over 1,200 CT-guided abdominal core biopsy results from 1989 through 1998. Forty-five were from gastrointestinal wall lesions (16 gastric, 3 duodenal, 7 small intestine, and 19 colon).

RESULTS

A definitive histologic diagnosis was obtained from the core biopsy in 41 patients (91%) without complication. The gastric lesion diagnoses were mesenchymal tumor of smooth muscle origin (eight), lymphoma (one), adenocarcinoma (three), and normal (one). Duodenal core biopsy diagnoses were inflammation (one) and normal (one). Small intestinal core biopsy diagnoses were non-Hodgkin lymphoma (four), metastatic leiomyosarcoma (one), carcinoma (one), and tuberculosis (one). Colon core biopsy diagnoses were carcinoma (11), lymphoma (2), actinomycosis (2), granulomatous inflammation (1), metastatic squamous cell carcinoma (1), chronic abscess (1), and mesenchymal tumor of smooth muscle origin (1).

CONCLUSION

Percutaneous CT-guided core needle biopsy from gastrointestinal wall lesions is safe and accurate, especially in submucosal lesions, and should be considered in selected cases with negative endoscopic biopsy or in which endoscopic biopsy is not possible.

A comprehensive analysis of protein-protein interactions in Saccharomyces cerevisiae

Two large-scale yeast two-hybrid screens were undertaken to identify protein-protein interactions between full-length open reading frames predicted from the Saccharomyces cerevisiae genome sequence. In one approach, we constructed a protein array of about 6,000 yeast transformants, with each transformant expressing one of the open reading frames as a fusion to an activation domain. This array was screened by a simple and automated procedure for 192 yeast proteins, with positive responses identified by their positions in the array. In a second approach, we pooled cells expressing one of about 6,000 activation domain fusions to generate a library. We used a high-throughput screening procedure to screen nearly all of the 6,000 predicted yeast proteins, expressed as Gal4 DNA-binding domain fusion proteins, against the library, and characterized positives by sequence analysis. These approaches resulted in the detection of 957 putative interactions involving 1,004 S. cerevisiae proteins. These data reveal interactions that place functionally unclassified proteins in a biological context, interactions between proteins involved in the same biological function, and interactions that link biological functions together into larger cellular processes. The results of these screens are shown here.

Grass-roots genomics

In these heady days of genomic enterprise, the wet-bench geneticist may wonder what the future holds in store for those who explore biology in the laboratory. We argue that the goal of genomics is to serve geneticists.

A biochemical genomics approach for identifying genes by the activity of their products

For the identification of yeast genes specifying biochemical activities, a genomic strategy that is rapid, sensitive, and widely applicable was developed with an array of 6144 individual yeast strains, each containing a different yeast open reading frame (ORF) fused to glutathione S-transferase (GST). For the identification of ORF-associated activities, strains were grown in defined pools, and GST-ORFs were purified. Then, pools were assayed for activities, and active pools were deconvoluted to identify the source strains. Three previously unknown ORF-associated activities were identified with this strategy: a cyclic phosphodiesterase that acts on adenosine diphosphate-ribose 1"-2" cyclic phosphate (Appr>p), an Appr-1"-p-processing activity, and a cytochrome c methyltransferase.

Functional genomics

Complete genome sequences are providing a framework to allow the investigation of biological processes by the use of comprehensive approaches. Genome analysis also is having a dramatic impact on medicine through its identification of genes and mutations involved in disease and the elucidation of entire microbial gene sets. Studies of the sequences of model organisms, such as that of the nematode worm Caenorhabditis elegans, are providing extraordinary insights into development and differentiation that aid the study of these processes in humans. The field of functional genomics seeks to devise and apply technologies that take advantage of the growing body of sequence information to analyze the full complement of genes and proteins encoded by an organism.

Genetic selection of peptide inhibitors of biological pathways

Genetic selections were used to find peptides that inhibit biological pathways in budding yeast. The peptides were presented inside cells as peptamers, surface loops on a highly expressed and biologically inert carrier protein, a catalytically inactive derivative of staphylococcal nuclease. Peptamers that inhibited the pheromone signaling pathway, transcriptional silencing, and the spindle checkpoint were isolated. Putative targets for the inhibitors were identified by a combination of two-hybrid analysis and genetic dissection of the target pathways. This analysis identified Ydr517w as a component of the spindle checkpoint and reinforced earlier indications that Ste50 has both positive and negative roles in pheromone signaling. Analysis of transcript arrays showed that the peptamers were highly specific in their effects, which suggests that they may be useful reagents in organisms that lack sophisticated genetics as well as for identifying components of existing biological pathways that are potential targets for drug discovery.

The use of an interactive software program for quantitative characterization of microcalcifications on digitized film-screen mammograms

RATIONALE AND OBJECTIVES

Mammography is relatively nonspecific for the early detection of breast cancer. This study evaluates the accuracy of mammographic interpretation using quantitative features characterizing microcalcifications, which are extracted by a computerized system.

METHODS

A computer-aided diagnosis (CAD) system enabling digitization of film-screen mammograms and automatic feature extraction was developed. A classification scheme (discriminant analysis) based on these features was constructed and trained on 217 cases with known pathology. The diagnostic performance of the classification scheme was tested against the radiologist's conventional interpretation on 45 additional cases of microcalcifications, each analyzed independently by four radiologists.

RESULTS

The sensitivity of the CAD system analysis (95.7%) was significantly better than that of conventional interpretation (84.8%). The positive predictive value of interpretation increased significantly, as did the area under the receiver operating characteristic curve.

CONCLUSIONS

This classification scheme for microcalcifications, based on quantitative features characterizing the lesion, significantly improved the accuracy of mammographic interpretation.

Identification of RNAs that bind to a specific protein using the yeast three-hybrid system

We have adapted the yeast three-hybrid system to identify RNA ligands for an RNA-binding protein. In this assay system, a protein-RNA interaction is detected by the reconstitution of a transcriptional activator using two hybrid proteins and a hybrid RNA. The RNA molecule is tethered to the promoter of a reporter gene by binding to a hybrid protein consisting of the bacteriophage MS2 coat protein fused to the DNA-binding protein LexA; the RNA-binding domain to be analyzed is fused to the transcriptional activation domain of the yeast Gal4 protein; and the bifunctional RNA consists of binding sites for the coat protein and for the other RNA-binding domain. We built an RNA library such that short fragments of genomic DNA from yeast were transcribed in yeast together with binding sites for the coat protein. We screened this hybrid RNA library for RNAs that bound to the yeast Snp1 protein, a homolog of the human U1-70K protein. The screen yielded as the strongest positive the fragment of U1 RNA that contains loop I, which is known to bind to Snp1 in U1 snRNP. We also identified four other RNA ligands that produced weaker three-hybrid signals, suggesting lower affinities for Snp1 as compared to U1 RNA. In addition, this search also yielded a set of RNA sequences that can activate transcription on their own when bound to a promoter through a protein interaction.

Caspase-3 inhibits growth in Saccharomyces cerevisiae without causing cell death

Caspase-3, a member of the caspase family of cell death proteases, cleaves cytoplasmic and nuclear substrates and promotes apoptotic cell death in mammalian cells. Although yeast homologs of apoptotic genes have not been identified, some components of apoptotic pathways retain function in yeast. Here we show that the expression of caspase-3 delays cell growth in Saccharomyces cerevesiae without causing cell death. Mutation of the caspase-3 QACRG active site abolished effects on yeast growth. Co-expression of caspase inhibitors alleviated growth inhibition in yeast as did the tripeptide caspase inhibitor ZVAD-fmk. These results suggest that substrates for caspase-3 are present in S. cerevesiae and may participate in the normal cell growth and division processes.

Topotecan treatment of adults with primary malignant glioma. The Brain Tumor Center at Duke

BACKGROUND

Topotecan activity was evaluated for the treatment of malignant glioma.

METHODS

Sixty-three patients with newly diagnosed (n = 25) or recurrent (n = 38) malignant glioma were treated with topotecan [AU: Please verify all dosages here and throughout text.]at a dose of 2.6 mg/m2 over a 72-hour period weekly. Recurrent tumors included glioblastoma multiforme (GBM) (n = 28) and anaplastic astrocytoma (AA) (n = 10). Newly diagnosed tumors included GBM (n = 14), AA (n = 8), and anaplastic oligodendroglioma (n = 3).

RESULTS

Partial responses were observed in 2 of 14 evaluable patients with newly diagnosed GBM, 1 of 8 patients with newly diagnosed AA, 3 of 10 patients with recurrent AA, and none of 28 patients with recurrent GBM. Four patients with recurrent AA and 7 patients with recurrent GBM demonstrated stable disease (range, 8-52 weeks; median, 21 weeks). Toxicity was limited to infrequent National Cancer Institute Common Toxicity Criteria Grade 3 myelosuppression.

CONCLUSIONS

These results suggest that topotecan has modest activity against malignant glioma and continued evaluation of its effectiveness may be warranted when alternative schedules or combination regimens are used.