Biomedical subjects

Javed Khan

Publications and source records attributed to Javed Khan.

At least 19 recordsLinked to original sources

PubMed2007

Credentialing preclinical pediatric xenograft models using gene expression and tissue microarray analysis.

Human tumor xenografts have been used extensively for rapid screening of the efficacy of anticancer drugs for the past 35 years. The selection of appropriate xenograft models for drug testing has been largely empirical and has not incorporated a similarity to the tumor type of origin at the molecular level. This study is the first comprehensive analysis of the transcriptome of a large set of pediatric xenografts, which are currently used for preclinical drug testing. Suitable models representing the tumor type of origin were identified. It was found that the characteristic expression patterns of the primary tumors were maintained in the corresponding xenografts for the majority of samples. Because a prerequisite for developing rationally designed drugs is that the target is expressed at the protein level, we developed tissue arrays from these xenografts and corroborated that high mRNA levels yielded high protein levels for two tested genes. The web database and availability of tissue arrays will allow for the rapid confirmation of the expression of potential targets at both the mRNA and the protein level for molecularly targeted agents. The database will facilitate the identification of tumor markers predictive of response to tested agents as well as the discovery of new molecular targets.

Cell Line, Tumor↗

PubMed2007

The pediatric preclinical testing program: description of models and early testing results.

BACKGROUND: The Pediatric Preclinical Testing Program (PPTP) is an initiative supported by the National Cancer Institute (NCI) to identify novel therapeutic agents that may have significant activity against childhood cancers. The PPTP has established panels of childhood cancer xenografts and cell lines to be used for in vivo and in vitro testing. These include panels for Wilms tumor, sarcomas (rhabdomyosarcoma, Ewing sarcoma, and osteosarcoma), neuroblastoma, brain tumors (glioblastoma, ependymoma, and medulloblastoma), rhabdoid tumors (CNS and renal), and acute lymphoblastic leukemia (ALL). Here, we describe the characteristics of the in vivo tumor panels and report results for the in vivo evaluation of two standard agents, vincristine and cyclophosphamide. PROCEDURES: Solid tumors were grown subcutaneously in immune-deficient mice and tumor dimensions were measured weekly. ALL xenografts were inoculated intravenously and human CD45-positive cells were enumerated weekly. RESULTS: Vincristine-induced objective responses in 6 of 24 (25%) and cyclophosphamide-induced objective responses in 18 of 28 (64%) solid tumor models. Comparable assessments of high levels of activity for these two agents were obtained using a tumor growth delay (TGD) measure. Both agents induced regressions in each of the ALL models evaluated. CONCLUSIONS: We have established 51 solid tumor and 10 ALL in vivo models. The models identify vincristine and cyclophosphamide as having broad-spectrum activity. The PPTP tumor panels appear to generally recapitulate the activity of these agents against specific childhood cancers and to have the potential for identifying novel agents having significant clinical activity.

Animals↗

PubMed2006

Reduced expression of CAMTA1 correlates with adverse outcome in neuroblastoma patients.

PURPOSE: A distal portion of 1p is frequently deleted in human neuroblastomas, and it is generally assumed that this region harbors at least one gene relevant for neuroblastoma development. A 1p36.3 commonly deleted region, bordered by D1S2731 and D1S214 has been defined. The present study surveys whether expression of genes mapping to this region is associated with tumor behavior. EXPERIMENTAL DESIGN: Candidate genes localized within the deleted region were identified by sequence data analysis. Their expression was assessed in a cohort of 49 primary neuroblastomas using cDNA microarray analysis. Gene expression patterns associated with known prognostic markers and patient outcome were further evaluated by quantitative real-time reverse transcription-PCR in a cohort of 102 neuroblastomas. RESULTS: The commonly deleted region spans 261 kb and encompasses two genes, FLJ10737 and CAMTA1. We found no evidence for an association of FLJ10737 expression with established prognostic variables or outcome. In contrast, low CAMTA1 expression characterized tumors with 1p deletion, MYCN amplification, and advanced tumor stages 3 and 4. Moreover, low CAMTA1 expression was significantly associated with poor outcome (P < 0.001). In multivariate analysis of event-free survival, the prognostic information of low CAMTA1 expression was independent of 1p status, MYCN status, tumor stage, and age of the patient at diagnosis (hazard ratio, 3.52; 95% confidence interval, 1.21-10.28; P = 0.02). CONCLUSIONS: Our data suggest that assessment of CAMTA1 expression may improve the prognostic models for neuroblastoma and that it will be important to define the biological function of CAMTA1 in this disease.

Age Factors↗

PubMed2006

Increased WSB1 copy number correlates with its over-expression which associates with increased survival in neuroblastoma.

Gain of chromosome 17 is the most prevalent genetic abnormality identified in neuroblastoma (NB) and distal 17q gain has prognostic significance in NB. In this report, we have combined array-based comparative genomic hybridization (A-CGH) and gene expression analysis to investigate gene copy number changes and its impact on the gene expression level as well as their association with prognosis genes located on chromosome 17 in NB tumors. We observed differential gains of chromosome 17 between Stages 4- and 4S tumors. We found that WSB1, mapping to 17q11.1, which was frequently gained in 4S- tumors and not changed in 4- tumors, showed strong correlations between expression level and copy number. Furthermore, the increase of WSB1 gene expression is associated with good outcome in patients with NB of all stages. WSB1 also enhances the prognostic prediction when combined with other current prognostic factors in NB. Our results demonstrate that WSB1 copy number correlates with its expression level and that its high expression associates with good prognosis suggesting a possible role of this gene in the biology of favorable outcome NB. This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045-2257/suppmat.

Cell Line, Tumor↗

PubMed2005

BBC3 mediates fenretinide-induced cell death in neuroblastoma.

Fenretinide (4-HPR) is a synthetic retinoid whose apoptosis-inducing effects have been demonstrated in many tumor types. The precise mechanism of its apoptotic action is not fully understood. To further study the mechanism by which 4-HPR exerts its biological effects in neuroblastoma (NB) and to identify the genes that contribute to the induction of apoptosis, we determined the sensitivity of eight NB cell lines to 4-HPR. Additionally, cDNA microarray analysis was performed on a 4-HPR-sensitive cell line to investigate the temporal changes in gene expression, primarily focusing on the induction of proapoptotic genes. BBC3, a transcriptionally regulated proapoptotic member of the BCL2 family, was the most highly induced proapoptotic gene. Western analysis confirmed the induction of BBC3 protein by 4-HPR. Furthermore, the induction of BBC3 was associated with the sensitivity to this agent in the cell lines tested. Finally we demonstrated that BBC3 alone is sufficient to induce cell death in the 4-HPR-sensitive and resistant NB cell lines, and that siRNA against BBC3 significantly decreases apoptosis induced by 4-HPR. Our results indicate that BBC3 mediates cell death in NB cells in response to 4-HPR.

Antineoplastic Agents↗

PubMed2005

High-resolution cDNA microarray-based comparative genomic hybridization analysis in neuroblastoma.

Neuroblastoma (NB) is one of the most common pediatric solid tumors and displays a broad variety of genomic alterations. Array-based comparative genomic hybridization (A-CGH) is a novel technology enabling the high-resolution detection of DNA copy number aberrations. In this article, we outline features of this new technology and approaches of data analysis. We focus on stage specific DNA copy number variations in neuroblastoma detected by cDNA array-based comparative genomic hybridization (A-CGH). We also discuss hypothetic evolutionary models of neuroblastoma progression that can be derived from A-CGH data.

DNA, Complementary↗

PubMed2005

Inferring a tumor progression model for neuroblastoma from genomic data.

PURPOSE: The knowledge of the key genomic events that are causal to cancer development and progression not only is invaluable for our understanding of cancer biology but also may have a direct clinical impact. The task of deciphering a model of tumor progression by requiring that it explains (or at least does not contradict) known clinical and molecular evidence can be very demanding, particularly for cancers with complex patterns of clinical and molecular evidence. MATERIALS AND METHODS: We formalize the process of model inference and show how a progression model for neuroblastoma (NB) can be inferred from genomic data. The core idea of our method is to translate the model of clonal cancer evolution to mathematical testable rules of inheritance. Seventy-eight NB samples in stages 1, 4S, and 4 were analyzed with array-based comparative genomic hybridization. RESULTS: The pattern of recurrent genomic alterations in NB is strongly stage dependent and it is possible to identify traces of tumor progression in this type of data. CONCLUSION: A tumor progression model for neuroblastoma is inferred, which is in agreement with clinical evidence, explains part of the heterogeneity of the clinical behavior observed for NB, and is compatible with existing empirical models of NB progression.

Child↗

PubMed2005

Gene expression profiles associated with response to chemotherapy in epithelial ovarian cancers.

PURPOSE: The goal of this study was to determine whether distinct gene expression profiles are associated with intrinsic and/or acquired chemoresistance in epithelial ovarian carcinoma. EXPERIMENTAL DESIGN: Gene expression profiles were generated from 21 primary chemosensitive tumors and 24 primary chemo-resistant tumors using cDNA-based microarrays. Gene expression profiles of both groups of primary tumors were then compared with those of 15 ovarian carcinomas obtained following platinum-based chemotherapy ("post-chemotherapy" tumors). A theme discovery tool was used to identify functional categories of genes involved in drug resistance. RESULTS: Comparison of primary chemosensitive and chemo-resistant tumors revealed differential expression of 85 genes (P < 0.001). Comparison of gene expression profiles of primary chemosensitive tumors and post-chemotherapy tumors revealed more robust differences with 760 genes differentiating the two groups (P < 0.001). In contrast, only 230 genes were differentially expressed between primary chemo-resistant and post-chemotherapy groups (P < 0.001). Common to both gene lists were 178 genes representing transcripts differentially expressed between post-chemotherapy tumors and all primary tumors irrespective of intrinsic chemosensitivity. The gene expression profile of post-chemotherapy tumors compared with that of primary tumors revealed statistically significant overrepresentation of genes encoding extracellular matrix-related proteins. CONCLUSIONS: These data show that gene expression profiling can discriminate primary chemo-resistant from primary chemosensitive ovarian cancers. Gene expression profiles were also identified that correlate with states of intrinsic and acquired chemoresistance and that represent targets for future investigation and potential therapeutic interventions.

Adult↗

PubMed2005

Altered expression of cell cycle genes distinguishes aggressive neuroblastoma.

In this study, gene expression profiling was performed on 103 neuroblastoma (NB) tumors, stages 1-4 with and without MYCN amplification, using cDNA microarrays containing 42,578 elements. Using principal component analysis (PCA) to analyse the relationships among these samples, we confirm that the global patterns of gene expression reflect the phenotype of the tumors. To explore the biological processes that may contribute to increasing aggressive phenotype of the tumors, we utilized a statistical approach based on PCA. We identified a specific subset of the cell cycle and/or chromosome segregation genes that distinguish stage 4 NB tumors from all lower stage tumors, including stage 3. Furthermore, the control of the kinetochore assembly emerges from the Gene Ontology analysis as one of the key biological processes associated with an aggressive NB phenotype. Finally, we establish that these genes are further upregulated in the most aggressive MYCN-amplified tumors.

Cell Cycle↗

PubMed2005

Database of mRNA gene expression profiles of multiple human organs.

Genome-wide expression profiling of normal tissue may facilitate our understanding of the etiology of diseased organs and augment the development of new targeted therapeutics. Here, we have developed a high-density gene expression database of 18,927 unique genes for 158 normal human samples from 19 different organs of 30 different individuals using DNA microarrays. We report four main findings. First, despite very diverse sample parameters (e.g., age, ethnicity, sex, and postmortem interval), the expression profiles belonging to the same organs cluster together, demonstrating internal stability of the database. Second, the gene expression profiles reflect major organ-specific functions on the molecular level, indicating consistency of our database with known biology. Third, we demonstrate that any small (i.e., n approximately 100), randomly selected subset of genes can approximately reproduce the hierarchical clustering of the full data set, suggesting that the observed differential expression of >90% of the probed genes is of biological origin. Fourth, we demonstrate a potential application of this database to cancer research by identifying 19 tumor-specific genes in neuroblastoma. The selected genes are relatively underexpressed in all of the organs examined and belong to therapeutically relevant pathways, making them potential novel diagnostic markers and targets for therapy. We expect this database will be of utility for developing rationally designed molecularly targeted therapeutics in diseases such as cancer, as well as for exploring the functions of genes.

Cluster Analysis↗

PubMed2005

Expression of genes encoding innate host defense molecules in normal human monocytes in response to Candida albicans.

Little is known about the regulation and coordinated expression of genes involved in the innate host response to Candida albicans. We therefore examined the kinetic profile of gene expression of innate host defense molecules in normal human monocytes infected with C. albicans using microarray technology. Freshly isolated peripheral blood monocytes from five healthy donors were incubated with C. albicans for 0 to 18 h in parallel with time-matched uninfected control cells. RNA from monocytes was extracted and amplified for microarray analysis, using a 42,421-gene cDNA chip. Expression of genes encoding proinflammatory cytokines, including tumor necrosis factor alpha, interleukin 1 (IL-1), IL-6, and leukemia inhibitory factor, was markedly enhanced during the first 6 h and coincided with an increase in phagocytosis. Expression of these genes returned to near baseline by 18 h. Genes encoding chemokines, including IL-8; macrophage inflammatory proteins 1, 3, and 4; and monocyte chemoattractant protein 1, also were strongly up-regulated, with peak expression at 4 to 6 h, as were genes encoding chemokine receptors CCR1, CCR5, CCR7, and CXCR5. Expression of genes whose products may protect monocyte viability, such as BCL2-related protein, metallothioneins, CD71, and SOCS3, was up-regulated at 4 to 6 h and remained elevated throughout the 18-h time course. On the other hand, expression of genes encoding T-cell-regulatory molecules (e.g., IL-12, gamma interferon, and transforming growth factor beta) was not significantly affected during the 18-h incubation. Moreover, genes encoding IL-15, the IL-13 receptor (IL-13Ra1), and CD14 were suppressed during the 18-h exposure to C. albicans. Thus, C. albicans is a potent inducer of a dynamic cascade of expression of genes whose products are related to the recruitment, activation, and protection of neutrophils and monocytes.

Antigens, CD↗

PubMed2004

Detection of low level genomic alterations by comparative genomic hybridization based on cDNA micro-arrays.

MOTIVATION: The accumulation of genomic alterations is an important process in tumor formation and progression. Comparative genomic hybridization performed on cDNA arrays (cDNA aCGH) is a common method to investigate the genomic alterations on a genome-wide scale. However, when detecting low-level DNA copy number changes this technology requires the use of noise reduction strategies due to a low signal to noise ratio. RESULTS: Currently a running average smoothing filter is the most frequently used noise reduction strategy. We analyzed this strategy theoretically and experimentally and found that it is not sensitive to very low level genomic alterations. The presence of systematic errors in the data is one of the main reasons for this failure. We developed a novel algorithm which efficiently reduces systematic noise and allows for the detection of low-level genomic alterations. The algorithm is based on comparison of the biological relevant data to data from so-called self-self hybridizations, additional experiments which contain no biological information but contain systematic errors. We find that with our algorithm the effective resolution for +/-1 DNA copy number changes is about 2 Mb. For copy number changes larger than three the effective resolution is on the level of single genes.

Algorithms↗

PubMed2004

Prediction of clinical outcome using gene expression profiling and artificial neural networks for patients with neuroblastoma.

Currently, patients with neuroblastoma are classified into risk groups (e.g., according to the Children's Oncology Group risk-stratification) to guide physicians in the choice of the most appropriate therapy. Despite this careful stratification, the survival rate for patients with high-risk neuroblastoma remains <30%, and it is not possible to predict which of these high-risk patients will survive or succumb to the disease. Therefore, we have performed gene expression profiling using cDNA microarrays containing 42,578 clones and used artificial neural networks to develop an accurate predictor of survival for each individual patient with neuroblastoma. Using principal component analysis we found that neuroblastoma tumors exhibited inherent prognostic specific gene expression profiles. Subsequent artificial neural network-based prognosis prediction using expression levels of all 37,920 good-quality clones achieved 88% accuracy. Moreover, using an artificial neural network-based gene minimization strategy in a separate analysis we identified 19 genes, including 2 prognostic markers reported previously, MYCN and CD44, which correctly predicted outcome for 98% of these patients. In addition, these 19 predictor genes were able to additionally partition Children's Oncology Group-stratified high-risk patients into two subgroups according to their survival status (P = 0.0005). Our findings provide evidence of a gene expression signature that can predict prognosis independent of currently known risk factors and could assist physicians in the individual management of patients with high-risk neuroblastoma.

Antineoplastic Combined Chemotherapy Protocols↗

PubMed2004

cDNA array-CGH profiling identifies genomic alterations specific to stage and MYCN-amplification in neuroblastoma.

BACKGROUND: Recurrent non-random genomic alterations are the hallmarks of cancer and the characterization of these imbalances is critical to our understanding of tumorigenesis and cancer progression. RESULTS: We performed array-comparative genomic hybridization (A-CGH) on cDNA microarrays containing 42,000 elements in neuroblastoma (NB). We found that only two chromosomes (2p and 12q) had gene amplifications and all were in the MYCN amplified samples. There were 6 independent non-contiguous amplicons (10.4-69.4 Mb) on chromosome 2, and the largest contiguous region was 1.7 Mb bounded by NAG and an EST (clone: 757451); the smallest region was 27 Kb including an EST (clone: 241343), NCYM, and MYCN. Using a probabilistic approach to identify single copy number changes, we systemically investigated the genomic alterations occurring in Stage 1 and Stage 4 NBs with and without MYCN amplification (stage 1-, 4-, and 4+). We have not found genomic alterations universally present in all (100%) three subgroups of NBs. However we identified both common and unique patterns of genomic imbalance in NB including gain of 7q32, 17q21, 17q23-24 and loss of 3p21 were common to all three categories. Finally we confirm that the most frequent specific changes in Stage 4+ tumors were the loss of 1p36 with gain of 2p24-25 and they had fewer genomic alterations compared to either stage 1 or 4-, indicating that for this subgroup of poor risk NB requires a smaller number of genomic changes are required to develop the malignant phenotype. CONCLUSIONS: cDNA A-CGH analysis is an efficient method for the detection and characterization of amplicons. Furthermore we were able to detect single copy number changes using our probabilistic approach and identified genomic alterations specific to stage and MYCN amplification.

Cell Line, Tumor↗

PubMed2004

Tumor classification using phylogenetic methods on expression data.

Tumor classification is a well-studied problem in the field of bioinformatics. Developments in the field of DNA chip design have now made it possible to measure the expression levels of thousands of genes in sample tissue from healthy cell lines or tumors. A number of studies have examined the problems of tumor classification: class discovery, the problem of defining a number of classes of tumors using the data from a DNA chip, and class prediction, the problem of accurately classifying an unknown tumor, given expression data from the unknown tumor and from a learning set. The current work has applied phylogenetic methods to both problems. To solve the class discovery problem, we impose a metric on a set of tumors as a function of their gene expression levels, and impose a tree structure on this metric, using standard tree fitting methods borrowed from the field of phylogenetics. Phylogenetic methods provide a simple way of imposing a clear hierarchical relationship on the data, with branch lengths in the classification tree representing the degree of separation witnessed. We tested our method for class discovery on two data sets: a data set of 87 tissues, comprised mostly of small, round, blue-cell tumors (SRBCTs), and a data set of 22 breast tumors. We fit the 87 samples of the first set to a classification tree, which neatly separated into four major clusters corresponding exactly to the four groups of tumors, namely neuroblastomas, rhabdomyosarcomas, Burkitt's lymphomas, and the Ewing's family of tumors. The classification tree built using the breast cancer data separated tumors with BRCA1 mutations from those with BRCA2 mutations, with sporadic tumors separated from both groups and from each other. We also demonstrate the flexibility of the class discovery method with regard to standard resampling methodology such as jackknifing and noise perturbation. To solve the class prediction problem, we built a classification tree on the learning set, and then sought the optimal placement of each test sample within the classification tree. We tested this method on the SRBCT data set, and classified each tumor successfully.

Algorithms↗

PubMed2004

Expression profiling identifies the cytoskeletal organizer ezrin and the developmental homeoprotein Six-1 as key metastatic regulators.

Patients presenting with metastatic rhabdomyosarcoma (RMS), the most common soft-tissue sarcoma in children, have a very poor clinical prognosis. This is due, in large part, to our rudimentary knowledge of the molecular events that dictate metastatic potential. We used cDNA microarray analysis of RMS cell lines, derived from Ink4a/Arf-deficient mice transgenic for hepatocyte growth factor/scatter factor (HGF/SF), to identify a set of genes whose expression was significantly different between highly and poorly metastatic cells. Subsequent in vivo functional studies revealed that the actin filament-plasma membrane linker ezrin (encoded by Vil2) and the homeodomain-containing transcription factor Six-1 (sine oculis-related homeobox-1 homolog) had essential roles in determining the metastatic fate of RMS cells. VIL2 and SIX1 expression was enhanced in human RMS tissue, significantly correlating with clinical stage. The identification of ezrin and Six-1 as critical regulators of metastasis in RMS provides new mechanistic and therapeutic insights into this pediatric cancer.

Animals↗

PubMed2004

Prognostic classification of relapsing favorable histology Wilms tumor using cDNA microarray expression profiling and support vector machines.

Treatment of Wilms tumor has a high success rate, with some 85% of patients achieving long-term survival. However, late effects of treatment and management of relapse remain significant clinical problems. If accurate prognostic methods were available, effective risk-adapted therapies could be tailored to individual patients at diagnosis. Few molecular prognostic markers for Wilms tumor are currently defined, though previous studies have linked allele loss on 1p or 16q, genomic gain of 1q, and overexpression from 1q with an increased risk of relapse. To identify specific patterns of gene expression that are predictive of relapse, we used high-density (30 k) cDNA microarrays to analyze RNA samples from 27 favorable histology Wilms tumors taken from primary nephrectomies at the time of initial diagnosis. Thirteen of these tumors relapsed within 2 years. Genes differentially expressed between the relapsing and nonrelapsing tumor classes were identified by statistical scoring (t test). These genes encode proteins with diverse molecular functions, including transcription factors, developmental regulators, apoptotic factors, and signaling molecules. Use of a support vector machine classifier, feature selection, and test evaluation using cross-validation led to identification of a generalizable expression signature, a small subset of genes whose expression potentially can be used to predict tumor outcome in new samples. Similar methods were used to identify genes that are differentially expressed between tumors with and without genomic 1q gain. This set of discriminators was highly enriched in genes on 1q, indicating close agreement between data obtained from expression profiling with data from genomic copy number analyses.

Adolescent↗

PubMed2004

Proceedings: the Applications of Bioinformatics in Cancer Detection Workshop.

The Division of Cancer Prevention of the National Cancer Institute sponsored and organized the Applications of Bioinformatics in Cancer Detection Workshop on August 6-7, 2002. The goal of the workshop was to evaluate the state of the science of bioinformatics and determine how it may be used to assist early cancer detection, risk identification, risk assessment, and risk reduction. This paper summarizes the proceedings of this conference and points out future directions for research.

Computational Biology↗