TAZ AS A REGULATOR OF MESENCHYMAL TRANSFORMATION AND CLINICAL AGGRESSIVENESS IN GLIOMAS

Glioblastoma multiforme (GBM) is an aggressive, high grade brain tumor. Microarray studies have shown a subset of GBMs with a mesenchymal gene signature. This subset is associated with poor clinical outcome and resistance to treatment. To establish the molecular drivers of this mesenchymal transition, we correlated transcription factor expression to the mesenchymal signature and identified transcriptional co-activator with PDZ-binding motif (TAZ) to be highly associated with the mesenchymal shift. High TAZ expression correlated with worse clinical outcome and higher grade. These data led to the hypothesis that TAZ is critical to the mesenchymal transition and aggressive clinical behavior seen in GBM. We investigated the expression of TAZ, its binding partner TEAD, and the mesenchymal marker FN1 in human gliomas. Western analyses demonstrated increased expression of TAZ, TEAD4, and FN1 in GBM relative to lower grade gliomas. We also identified CpG islands in the TAZ promoter that are methylated in most lower grade gliomas, but not in GBMs. TAZ-methylated glioma stem cell (GSC) lines treated with a demethylation agent showed an increase in mRNA and protein TAZ expression; therefore, methylation may be another novel way TAZ is regulated since TAZ is epigenetically silenced in tumors with a better clinical outcome. To further characterize the role of TAZ in gliomagenesis, we stably silenced or over-expressed TAZ in GSCs. Silencing of TAZ decreased invasion, self-renewal, mesenchymal protein expression, and tumor-initiating capacity. Over-expression of TAZ led to an increase in invasion, mesenchymal protein expression, mesenchymal differentiation, and tumor-initiating ability. These actions are dependent on TAZ interacting with TEAD since all these effects were abrogated with TAZ could not bind to TEAD. We also show that TAZ and TEAD directly bind to mesenchymal gene promoters. Thus, TAZ-TEAD interaction is critically important in the mesenchymal shift and in the aggressive clinical behavior of GBM. We identified TAZ as a regulator of the mesenchymal transition in gliomas. TAZ could be used as a biomarker to both estimate prognosis and stratify patients into clinically relevant subgroups. Since mesenchymal transition is correlated to tumor aggressiveness, strategies to target and inhibit TAZ-TEAD and the downstream gene targets may be warranted in alternative treatment.

Rb-Sr and K-Ar data for Upper Vendian clayey rocks of the Russian Platform

Geochemical behavior of Rb-Sr and K-Ar systems in Upper Vendian clayey rocks of the Russian Platform is under consideredation. The use of additional data on grain size fractions of sedimentary rocks recovered from boreholes drilled in the Gavrilov Yam area made it possible to confirm the previous conclusion on two stages of epigenetic matter transformation (approximately 600 and 400 Ma ago). Distortions are related to transformation of sediments due to interaction in the water-rock system. Interaction degree was more intense in the upper part of the sedimentary section relative to its lower strata. These conclusions are substantiated by materials from boreholes that characterize different types of Vendian sections and different tectonic zones.

Lithology, biostratigraphy, and geochemistry of the Black Sea sediments, DSDP Leg 42 (pt. 2) data

The monograph presents results of deep-sea drilling in the Black Sea carried out in 1975. Detailed lithological, biostratigraphic and geochemical studies of Miocene-Holocene sediments have been carried out by specialists from institutes of the USSR Academy of Sciences, Moscow State University and other organizations. Drilling results are compared with geophysical data. Geological history of the Black Sea basin is considered as well.

(Table 1) Geochemical and geothermometry data from fibrous calcite vein fills in the Dabashan Fold Belt, China

Fibrous calcite veins with organic inclusions have been widely considered as indicators of oil and gas generation and migration under overpressure. Abundant fibrous calcite veins containing organic-bearing inclusions occur in faulted Lower Paleozoic through Triassic hydrocarbon source rocks in the Dabashan Foreland Belt (DBF). d13CPDB and d18OPDB values of the fibrous calcite range from - 4.8 to -1.9 to per mil and - 12.8 to - 8.4 per mil respectively, which is lighter than that of associated carbonate host rocks ranging from - 1.7 to + 3.1 per mil and - 8.7 to - 4.5 per mil. A linear relationship between d13CPDB and d18OPDB indicates that the calcite veins were precipitated from a mixture of basinal and surface fluids. The fibrous calcite contains a variety of inclusions, such as solid bitumen, methane bearing all-liquid inclusions, and vapor-liquid aqueous inclusions. Homogenization temperatures of aqueous inclusions range from 140 to 196° with an average of 179°. Salinities of aqueous inclusions average 9.7 wt% NaCl. Independent temperatures from bitumen reflectance and inclusion phase relationships of aqueous and methane inclusions were used to determine fluid pressures. Results indicate high pressures, elevated above typical lithostatic confining pressure, from 150 to 200 MPa. The elevated salinity and high temperature and pressure conditions of the fibrous calcite veins argue against an origin solely from burial overpressure resulting from clay transformation and dehydration reactions. Instead fluid inclusion P-T data and geochemistry results and regional geology indicate abnormally high pressures during fluid migration. These findings indicate that tectonic stress generated fracture and fault fluid pathways and caused migration of organic bearing fluids from the DBF during the Yanshan orogeny.

Geochemical data and magnetic measurements of IODP Expedition 308, Hole U1319A from the Gulf of Mexico

A 160 m mostly turbiditic late Pleistocene sediment sequence (IODP Expedition 308, Hole U1319A) from the Brazos-Trinity intraslope basin system off Texas was investigated with paleo- and rock magnetic methods. Numerous layers depleted in iron oxides and enriched by the ferrimagnetic iron-sulfide mineral greigite (Fe3S4) were detected by diagnostic magnetic properties. From the distribution of these layers, their stratigraphic context and the present geochemical zonation, we develop two conceptual reaction models of greigite formation in non-steady depositional environments. The "sulfidization model" predicts single or twin greigite layers by incomplete transformation of iron monosulfides with polysulfides around the sulfate methane transition (SMT). The "oxidation model" explains greigite formation by partial oxidation of iron monosulfides near the iron redox boundary during periods of downward shifting oxidation fronts. The stratigraphic record provides evidence that both these greigite formation processes act here at typical depths of about 12-14 mbsf and 3-4 mbsf. Numerous "fossil" greigite layers most likely preserved by rapid upward shifts of the redox zonation denote past SMT and sea floor positions characterized by stagnant hemipelagic sedimentation conditions. Six diagenetic stages from a pristine magnetite-dominated to a fully greigite-dominated magnetic mineralogy were differentiated by combination of various hysteresis and remanence parameters.

Global macrozoobenthos production and energy budget data base V150731, with link to database

I developed a new model for estimating annual production-to-biomass ratio P/B and production P of macrobenthic populations in marine and freshwater habitats. Self-learning artificial neural networks (ANN) were used to model the relationships between P/B and twenty easy-to-measure abiotic and biotic parameters in 1252 data sets of population production. Based on log-transformed data, the final predictive model estimates log(P/B) with reasonable accuracy and precision (r2 = 0.801; residual mean square RMS = 0.083). Body mass and water temperature contributed most to the explanatory power of the model. However, as with all least squares models using nonlinearly transformed data, back-transformation to natural scale introduces a bias in the model predictions, i.e., an underestimation of P/B (and P). When estimating production of assemblages of populations by adding up population estimates, accuracy decreases but precision increases with the number of populations in the assemblage.

Results of biogeochemical studies in the Russian Arctic seas: isotope and radioisotope data

Comprehensive biogeochemical studies including determination of isotopic composition of organic carbon in both suspended matter and surface layer (0-1 cm) bottom sediments (more than 260 determinations of d13C-Corg) were carried out for five Arctic shelf seas: White, Barents, Kara, East Siberian, and Chukchi Seas. The aim of this study is to elucidate causes that change isotopic composition of particulate organic carbon at the water-sediment boundary. It is shown that isotopic composition of organic carbon in sediments from seas with high river run-off (White, Kara, and East Siberian Seas) does not inherit isotopic composition of organic carbon in particles precipitating from the water column, but is enriched in 13C. Seas with low river run-off (Barents and Chukchi Seas) show insignificant difference between d13C-Corg values in both suspended load and sediments because of low content of isotopically light allochthonous organic matter in suspended matter. Biogeochemical studies with radioisotope tracers (14CO2, 35S, and 14CH4) revealed existence of specific microbial filter formed from heterotrophic and autotrophic organisms at the water-sediment boundary. This filter prevents mass influx of products of organic matter decomposition into the water column, as well as reduces influx of OM contained in suspended matter from water into sediments.

Hydrostatic pressure affects aggregate transformation and organic carbon transport: in and beyond the twilight zone: Experiment December 2010

This work aimed to explore evaluated the effects of the increased of hydrostatic pressure on a defined bacterial community on aggregates formed from an axenic culture of marine diatoms by simulating sedimentation to the deep sea by increase of hydrostatic pressure up to 30 bar (equivalent to 3000 m water depth) against control at ambient surface pressure. Our hypothesis was that microbial colonization and community composition and thus microbial OM turnover is greatly affected by changes in hydrostatic pressure during sinking to the deep ocean.

Restoration of micro data of John Lossing Buck's survey and analysis of the inverse relationship between yield and farm size in rural China in the 1930's

A large scale Chinese agricultural survey was conducted at the direction of John Lossing Buck from 1929 through 1933. At the end of the 1990’s, some parts of the original micro data of Buck’s survey were discovered at Nanjing Agricultural University. An international joint study was begun to restore micro data of Buck’s survey and construct parts of the micro database on both the crop yield survey and special expenditure survey. This paper includes a summary of the characteristics of farmlands and cropping patterns in crop yield micro data that covered 2,102 farmers in 20 counties of 9 provinces. In order to test the classical hypothesis of whether or not an inverse relationship between land productivity and cultivated area may be observed in developing countries, a Box-Cox transformation test was conducted for functional forms on five main crops of Buck’s crop yield survey. The result of the test shows that the relationship between land productivity and cultivated areas of wheat and barley is linear and somewhat negative; those of rice, rapeseed, and seed cotton appear to be slightly positive. It can be tentatively concluded that the relationship between cultivated area and land productivity are not the same among crops, and the difference of labor intensity and the level of commercialization of each crop may be strongly related to the existence or non-existence of inverse relationships.

Automatic motion compensation of free breathing acquired myocardial perfusion data by using independent component analysis

Images acquired during free breathing using first-pass gadolinium-enhanced myocardial perfusion magnetic resonance imaging (MRI) exhibit a quasiperiodic motion pattern that needs to be compensated for if a further automatic analysis of the perfusion is to be executed. In this work, we present a method to compensate this movement by combining independent component analysis (ICA) and image registration: First, we use ICA and a time?frequency analysis to identify the motion and separate it from the intensity change induced by the contrast agent. Then, synthetic reference images are created by recombining all the independent components but the one related to the motion. Therefore, the resulting image series does not exhibit motion and its images have intensities similar to those of their original counterparts. Motion compensation is then achieved by using a multi-pass image registration procedure. We tested our method on 39 image series acquired from 13 patients, covering the basal, mid and apical areas of the left heart ventricle and consisting of 58 perfusion images each. We validated our method by comparing manually tracked intensity profiles of the myocardial sections to automatically generated ones before and after registration of 13 patient data sets (39 distinct slices). We compared linear, non-linear, and combined ICA based registration approaches and previously published motion compensation schemes. Considering run-time and accuracy, a two-step ICA based motion compensation scheme that first optimizes a translation and then for non-linear transformation performed best and achieves registration of the whole series in 32 ± 12 s on a recent workstation. The proposed scheme improves the Pearsons correlation coefficient between manually and automatically obtained time?intensity curves from .84 ± .19 before registration to .96 ± .06 after registration

Estudio de las posibilidades de los datos abiertos enlazados (Linked Open Data) para la realización de mashups de ámbito geográfico.

La web ha sufrido una drástica transformación en los últimos años, debido principalmente a su popularización y a la enorme cantidad de información que alberga. Debido a estos factores se ha dado el salto de la denominada Web de Documentos, a la Web Semántica, donde toda la información está relacionada con otra. Las principales ventajas de la información enlazada estriban en la facilidad de reutilización, accesibilidad y disponibilidad para ser encontrada por el usuario. En este trabajo se pretende poner de manifiesto la utilidad de los datos enlazados aplicados al ámbito geográfico y mostrar como pueden ser empleados hoy en día. Para ello se han explotado datos enlazados de carácter espacial provenientes de diferentes fuentes, a través de servidores externos o endpoints SPARQL. Además de eso se ha trabajado con un servidor privado capaz de proporcionar información enlazada almacenada en un equipo personal. La explotación de información enlazada se ha implementado en una aplicación web en lenguaje JavaScript, tratando de abstraer totalmente al usuario del tratamiento de los datos a nivel interno de la aplicación. Esta aplicación cuenta además con algunos módulos y opciones capaces de interactuar con las consultas realizadas a los servidores, consiguiendo un entorno más intuitivo y agradable para el usuario. ABSTRACT: In recent years the web has suffered a drastic transformation because of the popularization and the huge amount of stored information. Due to these factors it has gone from Documents web to Semantic web, where the data are linked. The main advantages of Linked Data lie in the ease of his reuse, accessibility and availability to be located by users. The aim of this research is to highlight the usefulness of the geographic linked data and show how can be used at present time. To get this, the spatial linked data coming from several sources have been managed through external servers or also called endpoints. Besides, it has been worked with a private server able to provide linked data stored in a personal computer. The use of linked data has been implemented in a JavaScript web application, trying completely to abstract the internally data treatment of the application to make the user ignore it. This application has some modules and options that are able to interact with the queries made to the servers, getting a more intuitive and kind environment for users.

Extracción de conocimientos de la diabetes tipo 1 utilizando la metodología de "Data Mining"

La diabetes mellitus es un trastorno en la metabolización de los carbohidratos, caracterizado por la nula o insuficiente segregación de insulina (hormona producida por el páncreas), como resultado del mal funcionamiento de la parte endocrina del páncreas, o de una creciente resistencia del organismo a esta hormona. Esto implica, que tras el proceso digestivo, los alimentos que ingerimos se transforman en otros compuestos químicos más pequeños mediante los tejidos exocrinos. La ausencia o poca efectividad de esta hormona polipéptida, no permite metabolizar los carbohidratos ingeridos provocando dos consecuencias: Aumento de la concentración de glucosa en sangre, ya que las células no pueden metabolizarla; consumo de ácidos grasos mediante el hígado, liberando cuerpos cetónicos para aportar la energía a las células. Esta situación expone al enfermo crónico, a una concentración de glucosa en sangre muy elevada, denominado hiperglucemia, la cual puede producir a medio o largo múltiples problemas médicos: oftalmológicos, renales, cardiovasculares, cerebrovasculares, neurológicos… La diabetes representa un gran problema de salud pública y es la enfermedad más común en los países desarrollados por varios factores como la obesidad, la vida sedentaria, que facilitan la aparición de esta enfermedad. Mediante el presente proyecto trabajaremos con los datos de experimentación clínica de pacientes con diabetes de tipo 1, enfermedad autoinmune en la que son destruidas las células beta del páncreas (productoras de insulina) resultando necesaria la administración de insulina exógena. Dicho esto, el paciente con diabetes tipo 1 deberá seguir un tratamiento con insulina administrada por la vía subcutánea, adaptado a sus necesidades metabólicas y a sus hábitos de vida. Para abordar esta situación de regulación del control metabólico del enfermo, mediante una terapia de insulina, no serviremos del proyecto “Páncreas Endocrino Artificial” (PEA), el cual consta de una bomba de infusión de insulina, un sensor continuo de glucosa, y un algoritmo de control en lazo cerrado. El objetivo principal del PEA es aportar al paciente precisión, eficacia y seguridad en cuanto a la normalización del control glucémico y reducción del riesgo de hipoglucemias. El PEA se instala mediante vía subcutánea, por lo que, el retardo introducido por la acción de la insulina, el retardo de la medida de glucosa, así como los errores introducidos por los sensores continuos de glucosa cuando, se descalibran dificultando el empleo de un algoritmo de control. Llegados a este punto debemos modelar la glucosa del paciente mediante sistemas predictivos. Un modelo, es todo aquel elemento que nos permita predecir el comportamiento de un sistema mediante la introducción de variables de entrada. De este modo lo que conseguimos, es una predicción de los estados futuros en los que se puede encontrar la glucosa del paciente, sirviéndonos de variables de entrada de insulina, ingesta y glucosa ya conocidas, por ser las sucedidas con anterioridad en el tiempo. Cuando empleamos el predictor de glucosa, utilizando parámetros obtenidos en tiempo real, el controlador es capaz de indicar el nivel futuro de la glucosa para la toma de decisones del controlador CL. Los predictores que se están empleando actualmente en el PEA no están funcionando correctamente por la cantidad de información y variables que debe de manejar. Data Mining, también referenciado como Descubrimiento del Conocimiento en Bases de Datos (Knowledge Discovery in Databases o KDD), ha sido definida como el proceso de extracción no trivial de información implícita, previamente desconocida y potencialmente útil. Todo ello, sirviéndonos las siguientes fases del proceso de extracción del conocimiento: selección de datos, pre-procesado, transformación, minería de datos, interpretación de los resultados, evaluación y obtención del conocimiento. Con todo este proceso buscamos generar un único modelo insulina glucosa que se ajuste de forma individual a cada paciente y sea capaz, al mismo tiempo, de predecir los estados futuros glucosa con cálculos en tiempo real, a través de unos parámetros introducidos. Este trabajo busca extraer la información contenida en una base de datos de pacientes diabéticos tipo 1 obtenidos a partir de la experimentación clínica. Para ello emplearemos técnicas de Data Mining. Para la consecución del objetivo implícito a este proyecto hemos procedido a implementar una interfaz gráfica que nos guía a través del proceso del KDD (con información gráfica y estadística) de cada punto del proceso. En lo que respecta a la parte de la minería de datos, nos hemos servido de la denominada herramienta de WEKA, en la que a través de Java controlamos todas sus funciones, para implementarlas por medio del programa creado. Otorgando finalmente, una mayor potencialidad al proyecto con la posibilidad de implementar el servicio de los dispositivos Android por la potencial capacidad de portar el código. Mediante estos dispositivos y lo expuesto en el proyecto se podrían implementar o incluso crear nuevas aplicaciones novedosas y muy útiles para este campo. Como conclusión del proyecto, y tras un exhaustivo análisis de los resultados obtenidos, podemos apreciar como logramos obtener el modelo insulina-glucosa de cada paciente. ABSTRACT. The diabetes mellitus is a metabolic disorder, characterized by the low or none insulin production (a hormone produced by the pancreas), as a result of the malfunctioning of the endocrine pancreas part or by an increasing resistance of the organism to this hormone. This implies that, after the digestive process, the food we consume is transformed into smaller chemical compounds, through the exocrine tissues. The absence or limited effectiveness of this polypeptide hormone, does not allow to metabolize the ingested carbohydrates provoking two consequences: Increase of the glucose concentration in blood, as the cells are unable to metabolize it; fatty acid intake through the liver, releasing ketone bodies to provide energy to the cells. This situation exposes the chronic patient to high blood glucose levels, named hyperglycemia, which may cause in the medium or long term multiple medical problems: ophthalmological, renal, cardiovascular, cerebrum-vascular, neurological … The diabetes represents a great public health problem and is the most common disease in the developed countries, by several factors such as the obesity or sedentary life, which facilitate the appearance of this disease. Through this project we will work with clinical experimentation data of patients with diabetes of type 1, autoimmune disease in which beta cells of the pancreas (producers of insulin) are destroyed resulting necessary the exogenous insulin administration. That said, the patient with diabetes type 1 will have to follow a treatment with insulin, administered by the subcutaneous route, adapted to his metabolic needs and to his life habits. To deal with this situation of metabolic control regulation of the patient, through an insulin therapy, we shall be using the “Endocrine Artificial Pancreas " (PEA), which consists of a bomb of insulin infusion, a constant glucose sensor, and a control algorithm in closed bow. The principal aim of the PEA is providing the patient precision, efficiency and safety regarding the normalization of the glycemic control and hypoglycemia risk reduction". The PEA establishes through subcutaneous route, consequently, the delay introduced by the insulin action, the delay of the glucose measure, as well as the mistakes introduced by the constant glucose sensors when, decalibrate, impede the employment of an algorithm of control. At this stage we must shape the patient glucose levels through predictive systems. A model is all that element or set of elements which will allow us to predict the behavior of a system by introducing input variables. Thus what we obtain, is a prediction of the future stages in which it is possible to find the patient glucose level, being served of input insulin, ingestion and glucose variables already known, for being the ones happened previously in the time. When we use the glucose predictor, using obtained real time parameters, the controller is capable of indicating the future level of the glucose for the decision capture CL controller. The predictors that are being used nowadays in the PEA are not working correctly for the amount of information and variables that it need to handle. Data Mining, also indexed as Knowledge Discovery in Databases or KDD, has been defined as the not trivial extraction process of implicit information, previously unknown and potentially useful. All this, using the following phases of the knowledge extraction process: selection of information, pre- processing, transformation, data mining, results interpretation, evaluation and knowledge acquisition. With all this process we seek to generate the unique insulin glucose model that adjusts individually and in a personalized way for each patient form and being capable, at the same time, of predicting the future conditions with real time calculations, across few input parameters. This project of end of grade seeks to extract the information contained in a database of type 1 diabetics patients, obtained from clinical experimentation. For it, we will use technologies of Data Mining. For the attainment of the aim implicit to this project we have proceeded to implement a graphical interface that will guide us across the process of the KDD (with graphical and statistical information) of every point of the process. Regarding the data mining part, we have been served by a tool called WEKA's tool called, in which across Java, we control all of its functions to implement them by means of the created program. Finally granting a higher potential to the project with the possibility of implementing the service for Android devices, porting the code. Through these devices and what has been exposed in the project they might help or even create new and very useful applications for this field. As a conclusion of the project, and after an exhaustive analysis of the obtained results, we can show how we achieve to obtain the insulin–glucose model for each patient.

Oncogenic transformation induced by the Qin protein is correlated with transcriptional repression

The retroviral oncogene qin codes for a protein that belongs to the family of the winged helix transcription factors. The viral Qin protein, v-Qin, differs from its cellular counterpart, c-Qin, by functioning as a stronger transcriptional repressor and a more efficient inducer of tumors. This observation suggests that repression may be important in tumorigenesis. To test this possibility, chimeric proteins were constructed in which the Qin DNA-binding domain was fused to either a strong repressor domain (derived from the Drosophila Engrailed protein) or a strong activator domain (from the herpes simplex virus VP16 protein). The chimeric transcriptional repressor, Qin–Engrailed, transformed chicken embryo fibroblasts in culture and induced sarcomas in young chickens. The chimeric activator, Qin–VP16, failed to transform cells in vitro or in vivo and caused cellular resistance to oncogenic transformation by Qin. These data support the conclusion that the Qin protein induces oncogenic transformation by repressing the transcription of genes which function as negative growth regulators or tumor suppressors.

p19Arf induces p53-dependent apoptosis during Abelson virus-mediated pre-B cell transformation

The Ink4a/Arf locus encodes p16Ink4a and p19Arf and is among the most frequently mutated tumor suppressor loci in human cancer. In mice, many of these effects appear to be mediated by interactions between p19Arf and the p53 tumor-suppressor protein. Because Tp53 mutations are a common feature of the multistep pre-B cell transformation process mediated by Abelson murine leukemia virus (Ab-MLV), we examined the possibility that proteins encoded by the Ink4a/Arf locus also play a role in Abelson virus transformation. Analyses of primary transformants revealed that both p16Ink4a and p19Arf are expressed in many of the cells as they emerge from the apoptotic crisis that characterizes the transformation process. Analyses of primary transformants from Ink4a/Arf null mice revealed that these cells bypassed crisis. Because expression of p19Arf but not p16 Ink4a induced apoptosis in Ab-MLV-transformed pre-B cells, p19Arf appears to be responsible for these events. Consistent with the link between p19Arf and p53, Ink4a/Arf expression correlates with or precedes the emergence of cells expressing mutant p53. These data demonstrate that p19Arf is an important part of the cellular defense mounted against transforming signals from the Abl oncoprotein and provide direct evidence that the p19Arf–p53 regulatory loop plays an important role in lymphoma induction.

Protein tyrosine phosphatase PTP1B suppresses p210 bcr-abl-induced transformation of Rat-1 fibroblasts and promotes differentiation of K562 cells

The bcr-abl chimeric oncoprotein exhibits deregulated protein tyrosine kinase activity and is implicated in the pathogenesis of Philadelphia chromosome (Ph)-positive human leukemias, such as chronic myelogenous leukemia (CML). Recently we have shown that the levels of the protein tyrosine phosphatase PTP1B are enhanced in p210 bcr-abl-expressing cell lines. Furthermore, PTP1B recognizes p210 bcr-abl as a substrate, disrupts the formation of a p210 bcr-abl/Grb2 complex, and inhibits signaling events initiated by this oncoprotein PTK. In this report, we have examined whether PTP1B effects transformation induced by p210 bcr-abl. We demonstrate that expression of either wild-type PTP1B or the substrate-trapping mutant form of the enzyme (PTP1B-D181A) in p210 bcr-abl-transformed Rat-1 fibroblasts diminished the ability of these cells to form colonies in soft agar, to grow in reduced serum, and to form tumors in nude mice. In contrast, TCPTP, the closest relative of PTP1B, did not effect p210 bcr-abl-induced transformation. Furthermore, neither PTP1B nor TCPTP inhibited transformation induced by v-Abl. In addition, overexpression of PTP1B or treatment with CGP57148, a small molecule inhibitor of p210 bcr-abl, induced erythroid differentiation of K562 cells, a CML cell line derived from a patient in blast crisis. These data suggest that PTP1B is a selective, endogenous inhibitor of p210 bcr-abl and is likely to be important in the pathogenesis of CML.