Biomedical subjects

Kyle A Furge

Publications and source records attributed to Kyle A Furge.

11 recordsLinked to original sources

PubMed2005

Array-based comparative genomic hybridization reveals recurrent chromosomal aberrations and Jab1 as a potential target for 8q gain in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the major malignancies worldwide. We have previously characterized global gene expression patterns in HCC using microarrays. Here, we report the analysis of genomic DNA copy number among 49 HCC samples using BAC array-based comparative genomic hybridization (CGH). We observed recurrent and characteristic chromosomal aberrations, including frequent DNA copy number gains of 1q, 6p, 8q and 20q, and losses of 4q, 8p, 13q, 16q and 17p. We correlated gene expression with array CGH data, and identified a set of genes whose expression levels correlated with common chromosomal aberrations in HCC. Especially, we noticed that high expression of Jab1 in HCC significantly correlated with DNA copy number gain at 8q. Quantitative microsatellite analysis further confirmed DNA copy number gain at the Jab1 locus. Overexpression of Jab1 in HCC was also validated using real-time RT-PCR, and Jab1 protein levels were studied by immunohistochemistry on tissue microarrays. Functional analysis in HCC cell lines demonstrated that Jab1 may regulate HCC cell proliferation, thereby having a potential role in HCC development. In conclusion, this study shows that array-based CGH provides high resolution mapping of chromosomal aberrations in HCC, and demonstrates the feasibility of correlating array CGH data with gene expression data to identify novel oncogenes and tumor suppressor genes.

COP9 Signalosome Complex↗

PubMed2005

A molecular classification of papillary renal cell carcinoma.

Despite the moderate incidence of papillary renal cell carcinoma (PRCC), there is a disproportionately limited understanding of its underlying genetic programs. There is no effective therapy for metastatic PRCC, and patients are often excluded from kidney cancer trials. A morphologic classification of PRCC into type 1 and 2 tumors has been recently proposed, but its biological relevance remains uncertain. We studied the gene expression profiles of 34 cases of PRCC using Affymetrix HGU133 Plus 2.0 arrays (54,675 probe sets) using both unsupervised and supervised analyses. Comparative genomic microarray analysis was used to infer cytogenetic aberrations, and pathways were ranked with a curated database. Expression of selected genes was validated by immunohistochemistry in 34 samples with 15 independent tumors. We identified two highly distinct molecular PRCC subclasses with morphologic correlation. The first class, with excellent survival, corresponded to three histologic subtypes: type 1, low-grade type 2, and mixed type 1/low-grade type 2 tumors. The second class, with poor survival, corresponded to high-grade type 2 tumors (n = 11). Dysregulation of G1-S and G2-M checkpoint genes were found in class 1 and 2 tumors, respectively, alongside characteristic chromosomal aberrations. We identified a seven-transcript predictor that classified samples on cross-validation with 97% accuracy. Immunohistochemistry confirmed high expression of cytokeratin 7 in class 1 tumors and of topoisomerase IIalpha in class 2 tumors. We report two molecular subclasses of PRCC, which are biologically and clinically distinct and may be readily distinguished in a clinical setting.

Adult↗

PubMed2005

Comparison of array-based comparative genomic hybridization with gene expression-based regional expression biases to identify genetic abnormalities in hepatocellular carcinoma.

BACKGROUND: Regional expression biases (REBs) are genetic intervals where gene expression is coordinately changed. For example, if a region of the genome is amplified, often the majority of genes that map within the amplified region show increased expression when compared to genes located in cytogenetically normal regions. As such, REBs have the potential to act as surrogates for cytogenetic data traditionally obtained using molecular technologies such as comparative genomic hybridization. However as REBs are identified using transcriptional information, detection of REBs may also identify local transcriptional abnormalities produced by both genetic and epigenetic mechanisms. RESULTS: REBs were identified from a set of hepatocellular carcinoma (HCC) gene expression profiles using a multiple span moving binomial test and compared to genetic abnormalities identified using array-based comparative genomic hybridization (aCGH). In the majority of cases, REBs overlapped genetic abnormalities as determined by aCGH. For example, both methods identified narrow regions of frequent amplification on chromosome 1p and narrow regions of frequent deletion on 17q. In a minority of cases, REBs were identified in regions not determined to be abnormal via other cytogenetic technologies. Specifically, expression biases reflective of cell proliferation were frequently identified on chromosome 6p21-23. CONCLUSION: Identification of REBs using a multiple span moving binomial test produced reasonable approximations of underlying cytogenetic abnormalities. However, caution should be used when attributing REBs identified on chromosome 6p to cytogenetic events in rapidly proliferating cells.

Carcinoma, Hepatocellular↗

PubMed2004

Gene expression profiling of renal cell carcinoma.

Renal cell carcinoma (RCC) is a histologically diverse disease, with variable and often unpredictable clinical behavior. The prognosis worsens dramatically with the onset of clinical metastasis, and current regimens of systemic therapy yield only modest benefits for metastatic RCC. Gene expression profiling is a promising technique for refining the diagnosis and staging of RCC, as well as for highlighting potential therapeutic targets. We review the recent advances in expression profiling of RCC and discuss the clinical and biological insights obtained from these studies.

Carcinoma, Renal Cell↗

PubMed2004

Robust classification of renal cell carcinoma based on gene expression data and predicted cytogenetic profiles.

Renal cell carcinoma (RCC) is a heterogeneous disease that includes several histologically distinct subtypes. The most common RCC subtypes are clear cell, papillary, and chromophobe, and recent gene expression profiling studies suggest that classification of RCC based on transcriptional signatures could be beneficial. Traditionally, however, patterns of chromosomal alterations have been used to assist in the molecular classification of RCC. The purpose of this study was to determine whether it was possible to develop a classification model for the three major RCC subtypes that utilizes gene expression profiles as the bases for both molecular genetic and cytogenetic classification. Gene expression profiles were first used to build an expression-based RCC classifier. The RCC gene expression profiles were then examined for the presence of regional gene expression biases. Regional expression biases are genetic intervals that contain a disproportionate number of genes that are coordinately up- or down-regulated. The presence of a regional gene expression bias often indicates the presence of a chromosomal abnormality. In this study, we demonstrate an expression-based classifier can distinguish between the three most common RCC subtypes in 99% of cases (n = 73). We also demonstrate that detection of regional expression biases accurately identifies cytogenetic features common to RCC. Additionally, the in silico-derived cytogenetic profiles could be used to classify 81% of cases. Taken together, these data demonstrate that it is possible to construct a robust classification model for RCC using both transcriptional and cytogenetic features derived from a gene expression profile.

Carcinoma, Renal Cell↗

PubMed2004

Gene expression profiling of early- and late-relapse nonseminomatous germ cell tumor and primitive neuroectodermal tumor of the testis.

PURPOSE: To better understand the molecular mechanisms that underlay the development and progression of nonseminomatous germ cell tumor of testis (NSGCTT) as well as malignant transformation of teratoma and primitive neuroectodermal tumor (PNET). EXPERIMENTAL DESIGN: We studied the gene expression profiles of 17 retroperitoneal NSGCTTs (10 yolk sac tumors, 3 embryonal carcinomas, 4 teratomas) and 2 PNETs obtained from patients with two clinical outcomes. Tissue samples were obtained from the Indiana University. One group of NSGCTT and PNET patients developed metastases within 2 years (early-relapse) of initial successful treatment, and the other group developed metastases after 2 years (late-relapse). Gene expression in these groups of patients was quantified using cDNA microarrays and real-time relative quantitative PCR. RESULTS: We demonstrate that the gene expression profiles of these tumors correlate with histological type. In addition, we identify type-specific genes that may serve as novel diagnostic markers. We also identify a gene set that can distinguish between early-relapse and late-relapse yolk sac tumors. The expression differences of these genes may underlie the differences in clinical outcome and drug response of these tumors. CONCLUSION: This is the first study that used gene expression profiling to examine the molecular characteristics of the NSGCTTs and drug response in early- and late-relapse tumors. These results suggest that two molecularly distinct forms of NSGCTTs exist and that the integration of expression profile data with clinical parameters could enhance the diagnosis and prognosis of NSGCTTs. More importantly, the identified genes provide insight into the molecular mechanisms of aggressive NSGCTTs and suggest intervention strategies.

Cell Transformation, Neoplastic↗

PubMed2004

Diminished transcription of chromosome arm 4q is inversely related to local spreading of hepatocellular carcinoma.

To identify transcriptional features associated with local spreading of hepatocellular carcinoma (HCC), regional expression biases were determined from the gene expression profiles of solitary HCC tumors and of HCC tumors associated with additional intrahepatic lesions and/or portal vein involvement. Regional expression biases are genetic intervals in which gene expression is coordinately changed. Often, but not always, a regional expression bias indicates an underlying chromosomal aberration. This study demonstrated that the presence or absence of a regional expression bias on chromosome arm 4q can predict the presence or absence of intrahepatic spread/portal vein involvement in 83% of cases analyzed (n = 40). These results suggest that the transcriptional state of 4q may be a marker for local spreading of HCC and that a more detailed genetic/epigenetic characterization of this locus may provide additional insights into HCC development.

Carcinoma, Hepatocellular↗

PubMed2003

Molecular subclassification of kidney tumors and the discovery of new diagnostic markers.

We analysed the expression profiles of 70 kidney tumors of different histological subtypes to determine if these subgroups can be distinguished by their gene expression profiles, and to gain insights into the molecular mechanisms underlying each subtype. In all, 39 clear cell renal cell carcinomas (RCC), seven primary and one metastatic papillary RCC, six granular RCC from old classification, five chromophobe RCC, five sarcomatoid RCC, two oncocytomas, three transitional cell carcinomas (TCC) of the renal pelvis and five Wilms' tumors were compared with noncancerous kidney tissues using microarrays containing 19,968 cDNAs. Based on global gene clustering of 3560 selected cDNAs, we found distinct molecular signatures in clear cell, papillary, chromophobe RCC/oncocytoma, TCC and Wilms' subtypes. The close clustering in each of these subtypes points to different tumorigenic pathways as reflected by their histological characteristics. In the clear cell RCC clustering, two subgroups emerged that correlated with clinical outcomes, confirming the potential use of gene expression signatures as a predictor of survival. In the so-called granular cell RCC (terminology for a subtype that is no longer preferred), none of the six cases clusters together, supporting the current view that they do not represent a single entity. Blinded histological re-evaluation of four cases of 'granular RCC' led to their reassignment to other existing histological subtypes, each compatible with our molecular classification. Finally, we found gene sets specific to each subtype. In order to establish the use of some of these genes as novel subtype markers, we selected four genes and performed immunohistochemical analysis on 40 cases of primary kidney tumors. The results were consistent with the gene expression microarray data: glutathione S-transferase alpha was highly expressed in clear cell RCC, alpha methylacyl racemase in papillary RCC, carbonic anhydrase II in chromophobe RCC and K19 in TCC. In conclusion, we demonstrated that molecular profiles of kidney cancers closely correlated with their histological subtypes. We have also identified in these subtypes differentially expressed genes that could have important diagnostic and therapeutic implications.

Biomarkers, Tumor↗

PubMed2002

Identification of frequent cytogenetic aberrations in hepatocellular carcinoma using gene-expression microarray data.

BACKGROUND: Hepatocellular carcinoma (HCC) is a leading cause of death worldwide. Frequent cytogenetic abnormalities that occur in HCC suggest that tumor-modifying genes (oncogenes or tumor suppressors) may be driving selection for amplification or deletion of these particular genetic regions. In many cases, however, the gene(s) that drive the selection are unknown. Although techniques such as comparative genomic hybridization (CGH) have traditionally been used to identify cytogenetic aberrations, it might also be possible to identify them indirectly from gene-expression studies. A technique we have called comparative genomic microarray analysis (CGMA) predicts regions of cytogenetic change by searching for regional gene-expression biases. CGMA was applied to HCC gene-expression profiles to identify regions of frequent cytogenetic change and to identify genes whose expression is misregulated within these regions. RESULTS: Using CGMA, 104 HCC gene-expression microarray profiles were analyzed. CGMA identified 13 regions of frequent cytogenetic change in the HCC samples. Ten of these regions have been detected in previous CGH studies (+lq, -4q, +6p, -8p, +8q, -13q, -16q, -17p, +17q, +20q). CGMA identified three additional regions that have not been previously identified by CGH (+5q, +12q, +19p). Genes located in regions of frequent cytogenetic change were examined for changed expression in the HCC samples. CONCLUSIONS: Our results suggest that CGMA predictions using gene-expression microarray datasets are a practical alternative to CGH profiling. In addition, CGMA might be useful for identifying candidate genes within cytogenetically abnormal regions.

Carcinoma, Hepatocellular↗

PubMed2002

Gene expression profiling of favorable histology Wilms tumors and its correlation with clinical features.

The aims of this study were to understand the underlying molecular mechanisms of favorable histology Wilms tumors (WTs) and to classify them based on their molecular signatures. We studied a total of 15 favorable histology WTs using microarrays containing 19,968 cDNAs. First, we found commonly altered genes in WT. A total of 267 cDNAs were significantly overexpressed at least 3-fold in all of the tumors compared with noncancerous kidney and contained known WT-related genes such as IGF II and WT1. The gene with the highest expression change compared with noncancerous kidney was topoisomerase IIalpha. By hierarchical clustering, there was a clear distinction between high-stage and low-stage tumors. A total of 30 cDNAs were found differentially expressed between the high- and low-stage groups. One of them, Stathmin 1, which is involved in the microtubule system, was highly expressed in high-stage tumors compared with the low-stage tumors. The present chemotherapy regimens for WT consist mainly of topoisomerase II inhibitors (i.e., actinomycin D, doxorubicin, and etoposide) and antimicrotubule agents (i.e., vincristine and paclitaxel). Our data suggest that high expression of topoisomerase IIalpha and microtubule-related genes such as tubulin and stathmin 1 may be related to the high chemosensitivity of WT. In addition, retinol-related genes such as CRABP2 and retinol-binding protein 1 were overexpressed in WT, and CRABP2 was more highly expressed in the poor outcome patients, which suggests that retinoid acid may be a potential drug. In summary, our findings suggest that the integration of gene expression data and clinical parameters could aid in detecting aggressive tumors among favorable histology WT and lead to the discovery of new drugs for WT.

Antigens, Neoplasm↗

PubMed2002

CIT: identification of differentially expressed clusters of genes from microarray data.

Cluster Identification Tool (CIT) is a microarray analysis program that identifies differentially expressed genes. Following division of experimental samples based on a parameter of interest, CIT uses a statistical discrimination metric and permutation analysis to identify clusters of genes or individual genes that best differentiate between the experimental groups. CIT integrates with the freely available CLUSTER and TREEVIEW programs to form a more complete microarray analysis package.

Algorithms↗