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Jonathan R Pollack

Publications and source records attributed to Jonathan R Pollack.

At least 19 recordsLinked to original sources
PubMed2007

Target discovery and validation in pancreatic cancer.

Pancreatic cancer is a lethal disease and rational strategies for early detection and targeted therapies are urgently required to alleviate the dismal prognosis of this neoplasm. The use of global RNA and protein expression-profiling technologies, such as DNA microarrays, serial analysis of gene expression, and mass spectrometric analysis of proteins, have led to identification of cellular targets with considerable potential for clinical application and patient care. These studies underscore the importance of pursuing large-scale profiling of human cancers not only for furthering our understanding of the pathogenesis of these malignancies but also for developing strategies to improve patient outcomes.

Drug Design↗
PubMed2006

Expression of tumor-associated antigens in acute myeloid leukemia: Implications for specific immunotherapeutic approaches.

The expression of tumor-associated antigens (TAAs) might play a critical role in the control of minimal residual disease (MRD) in acute myeloid leukemia (AML), and therefore might be associated with clinical outcome in AML. In a DNA microarray analysis of 116 AML samples, we found a significant correlation between high mRNA levels of G250/CA9 and longer overall survival (P = .022), a similar trend with high mRNA levels of PRAME (P = .103), and a hint for RHAMM/HMMR. In contrast, for other TAAs like WT1, TERT, PRTN3, BCL2, and LAMR1, we found no correlation with clinical outcome. High expression of at least 1 of the 3 TAAs, RHAMM/HMMR, PRAME, or G250/CA9, provided the strongest favorable prognostic effect (P = .005). Specific T-cell responses were detected in 8 (47%) of 17 patients with AML in complete remission for RHAMM/HMMR-R3 peptide, in 7 (70%) of 10 for PRAME-P3 peptide, and in 6 (60%) of 10 for newly characterized G250/CA9-G2 peptide, a significant increased immune response compared with patients with AML patients who had refractory disease (P < .001). Furthermore, we could demonstrate specific lysis of T2 cells presenting these epitope peptides. In conclusion, expression of the TAAs RHAMM/HMMR, PRAME, and G250/CA9 can induce strong antileukemic immune responses, possibly enabling MRD control. Thus, these TAAs represent interesting targets for polyvalent immunotherapeutic approaches in AML.

Animals↗
PubMed2006

Disclosure of candidate genes in acute myeloid leukemia with complex karyotypes using microarray-based molecular characterization.

PURPOSE: To identify novel genomic regions of interest in acute myeloid leukemia (AML) with complex karyotypes, we applied comparative genomic hybridization to microarrays (array-CGH), allowing high-resolution genome-wide screening of genomic imbalances. PATIENTS AND METHODS: Sixty AML cases with complex karyotypes were analyzed using array-CGH; parallel analysis of gene expression was performed in a subset of cases. RESULTS: Genomic losses were found more frequently than gains. The most frequent losses affected 5q (77%), 17p (55%), and 7q (45%), and the most frequent genomic gains 11q (40%) and 8q (38%). Critical segments could be delineated to genomic fragments of only 0.8 to a few megabase-pairs of DNA. In lost/gained regions, gene expression profiling detected a gene dosage effect with significant lower/higher average gene expression levels across the genes located in the respective regions. Furthermore, high-level DNA amplifications were identified in several regions: 11q23.3-q24.1 (n = 7), 21q22 (n = 6), 11q23.3 (n = 5), 13q12 (n = 3), 8q24 (n = 3), 9p24 (n = 2), 12p13 (n = 2), and 20q11 (n = 2). Parallel analysis of gene expression in critical amplicons displayed overexpressed candidate genes (eg, C8FW and MYC in 8q24). CONCLUSION: In conclusion, a large spectrum of genomic imbalances, including novel recurring changes in AML with complex karyotypes, was identified using array-CGH. In addition, the combined analysis of array-CGH data with gene expression profiles allowed the detection of candidate genes involved in the pathogenesis of AML.

Acute Disease↗
PubMed2006

RNA interference-based functional dissection of the 17q12 amplicon in breast cancer reveals contribution of coamplified genes.

DNA amplification is a frequent occurrence in cancer genomes. While tumor amplicons may harbor known oncogenes "driving" amplification, amplicons rarely comprise only single genes. The potential functional contribution of coamplified genes remains largely unexplored. In breast cancer, 20-30% of tumors exhibit amplification within chromosome band 17q12, containing the ERBB2 oncogene. Analysis of array-based comparative genomic hybridization and expression profiling data indicate that the minimum region of recurrent amplification (i.e., the amplicon "core") at 17q12 includes two other genes, GRB7 and STARD3, which exhibit elevated expression when amplified. Western blot analysis confirms overexpression of each at the protein level in breast cancer cell lines SKBR3 and BT474 harboring amplification. In these cell lines (but not in control MCF7 breast cancer cells lacking 17q12 amplification), targeted knockdown of ERBB2 expression using RNA interference (RNAi) methods results in decreased cell proliferation, decreased cell-cycle progression, and increased apoptosis. Notably, targeted knockdown of either GRB7 or STARD3 also leads to decreased cell proliferation and cell-cycle progression, albeit to a lesser extent compared with ERBB2 knockdown. We conclude that the amplification and resultant overexpression of genes coamplified with ERBB2 at 17q12 can contribute to proliferation levels of breast cancer cells. Our findings validate the utility of RNAi in the functional interrogation of tumor amplicons, and provide evidence for a contribution of coamplified genes to tumor phenotypes.

Breast Neoplasms↗
PubMed2006

Distinct patterns of DNA copy number alteration are associated with different clinicopathological features and gene-expression subtypes of breast cancer.

Breast cancer is a leading cause of cancer-death among women, where the clinicopathological features of tumors are used to prognosticate and guide therapy. DNA copy number alterations (CNAs), which occur frequently in breast cancer and define key pathogenetic events, are also potentially useful prognostic or predictive factors. Here, we report a genome-wide array-based comparative genomic hybridization (array CGH) survey of CNAs in 89 breast tumors from a patient cohort with locally advanced disease. Statistical analysis links distinct cytoband loci harboring CNAs to specific clinicopathological parameters, including tumor grade, estrogen receptor status, presence of TP53 mutation, and overall survival. Notably, distinct spectra of CNAs also underlie the different subtypes of breast cancer recently defined by expression-profiling, implying these subtypes develop along distinct genetic pathways. In addition, higher numbers of gains/losses are associated with the "basal-like" tumor subtype, while high-level DNA amplification is more frequent in "luminal-B" subtype tumors, suggesting also that distinct mechanisms of genomic instability might underlie their pathogenesis. The identified CNAs may provide a basis for improved patient prognostication, as well as a starting point to define important genes to further our understanding of the pathobiology of breast cancer. This article contains Supplementary Material available at http://www.interscience.wiley.com/jpages/1045-2257/suppmat

Breast Neoplasms↗
PubMed2006

Application of genomic technologies to human prostate cancer.

Prostate cancer is the most commonly diagnosed non-cutaneous malignancy in U.S. males and has a broad spectrum of clinical behavior ranging from indolent to lethal. Microarray technology has provided unprecedented opportunity to explore the genetic processes underlying prostate cancer by providing a comprehensive survey of a cell's transcriptional landscape. Prostate cancer, however, has posed significant challenges that have contributed to inconsistent results between studies and difficulty replicating findings. Despite these challenges, several important insights have been gained along with new clinical biomarkers of diagnosis and prognosis. Continued improvements in methods of tissue preparation, microarray technology and data analysis will overcome existing challenges and fuel future discoveries.

Gene Expression Profiling↗
PubMed2006

A genome-wide screen for promoter methylation in lung cancer identifies novel methylation markers for multiple malignancies.

BACKGROUND: Promoter hypermethylation coupled with loss of heterozygosity at the same locus results in loss of gene function in many tumor cells. The "rules" governing which genes are methylated during the pathogenesis of individual cancers, how specific methylation profiles are initially established, or what determines tumor type-specific methylation are unknown. However, DNA methylation markers that are highly specific and sensitive for common tumors would be useful for the early detection of cancer, and those required for the malignant phenotype would identify pathways important as therapeutic targets. METHODS AND FINDINGS: In an effort to identify new cancer-specific methylation markers, we employed a high-throughput global expression profiling approach in lung cancer cells. We identified 132 genes that have 5' CpG islands, are induced from undetectable levels by 5-aza-2'-deoxycytidine in multiple non-small cell lung cancer cell lines, and are expressed in immortalized human bronchial epithelial cells. As expected, these genes were also expressed in normal lung, but often not in companion primary lung cancers. Methylation analysis of a subset (45/132) of these promoter regions in primary lung cancer (n = 20) and adjacent nonmalignant tissue (n = 20) showed that 31 genes had acquired methylation in the tumors, but did not show methylation in normal lung or peripheral blood cells. We studied the eight most frequently and specifically methylated genes from our lung cancer dataset in breast cancer (n = 37), colon cancer (n = 24), and prostate cancer (n = 24) along with counterpart nonmalignant tissues. We found that seven loci were frequently methylated in both breast and lung cancers, with four showing extensive methylation in all four epithelial tumors. CONCLUSIONS: By using a systematic biological screen we identified multiple genes that are methylated with high penetrance in primary lung, breast, colon, and prostate cancers. The cross-tumor methylation pattern we observed for these novel markers suggests that we have identified a partial promoter hypermethylation signature for these common malignancies. These data suggest that while tumors in different tissues vary substantially with respect to gene expression, there may be commonalities in their promoter methylation profiles that represent targets for early detection screening or therapeutic intervention.

Adenocarcinoma↗
PubMed2005

A gene expression signature of genetic instability in colon cancer.

Genetic instability plays a central role in the development and progression of human cancer. Two major classes of genetic instability, microsatellite instability (MSI) and chromosome instability (microsatellite stable; MSS), are best understood in the context of colon cancer, where MSI tumors represent approximately 15% of cases, and compared with MSS tumors, more often arise in the proximal colon and display favorable clinical outcome. To further explore molecular differences, we profiled gene expression in a set of 18 colon cancer cell lines using cDNA microarrays representing approximately 21,000 different genes. Supervised analysis identified a robust expression signature distinguishing MSI and MSS samples. As few as eight genes predicted with high accuracy the underlying genetic instability in the original and in three independent sample sets, comprising 13 colon cancer cell lines, 61 colorectal tumors, and 87 gastric tumors. Notably, the MSI signature was retained despite genetically correcting the underlying instability, suggesting the signature reflects a legacy of the tumor having arisen from MSI, rather than sensing the ongoing state of MSI. Our findings support a model in which MSI and MSS preferentially target different genes and pathways in cancer. Further, among the MSI signature genes, our findings implicate a role of elevated metallothionein expression in the clinical behavior of MSI cancers.

Adaptor Proteins, Signal Transducing↗
PubMed2005

The retinoic acid synthesis gene ALDH1a2 is a candidate tumor suppressor in prostate cancer.

Prostate cancer is the most common cancer among men in the United States, and aberrant DNA methylation is known to be an early molecular event in its development. Here, we have used expression profiling to identify novel hypermethylated genes whose expression is induced by treatment of prostate cancer cell lines with the DNA methyltransferase inhibitor 5-Aza-2'-deoxycytidine (5-aza-dC). Of the 271 genes that were induced by 5-aza-dC treatment, 25 also displayed reduced expression in primary prostate tumors compared with normal prostate tissue, and the decreased expression of only one gene, aldehyde dehydrogenase 1 family, member A2 (ALDH1a2), was also associated with shorter recurrence-free survival. ALDH1a2 encodes an enzyme responsible for synthesis of retinoic acid (RA), a compound with prodifferentiation properties. By immunohistochemistry, we observed that ALDH1a2 was expressed in epithelia from normal prostate but not prostate cancer. Using bisulfite sequencing, we determined that the ALDH1a2 promoter region was significantly hypermethylated in primary prostate tumors compared with normal prostate specimens (P = 0.01). Finally, transfection-mediated reexpression of wild-type ALDH1a2 (but not a presumptive catalytically dead mutant) in the prostate cancer cell line DU145 resulted in decreased colony growth (P < 0.0001), comparable with treatment with either 5-aza-dC or RA. Taken together, our findings implicate ALDH1a2 as a candidate tumor suppressor gene in prostate cancer and further support a role of retinoids in the prevention or treatment of prostate cancer.

Aldehyde Dehydrogenase↗
PubMed2005

Comparative genomic hybridization on mouse cDNA microarrays and its application to a murine lymphoma model.

Microarray-based formats offer a high-resolution alternative to conventional, chromosome-based comparative genomic hybridization (CGH) methods for assessing DNA copy number alteration (CNA) genome-wide in human cancer. For murine tumors, array CGH should provide even greater advantage, since murine chromosomes are more difficult to individually discern. We report here the adaptation and evaluation of a cDNA microarray-based CGH method for the routine characterization of CNAs in murine tumors, using mouse cDNA microarrays representing approximately 14,000 different genes, thereby providing an average mapping resolution of 109 kb. As a first application, we have characterized CNAs in a set of 10 primary and recurrent lymphomas derived from a Myc-induced murine lymphoma model. In primary lymphomas and more commonly in Myc-independent relapses, we identified a recurrent genomic DNA loss at chromosome 3G3-3H4, and recurrent amplifications at chromosome 3F2.1-3G3 and chromosome 15E1/E2-15F3, the boundaries of which we defined with high resolution. Further, by profiling gene expression using the same microarray platform, we identified within CNAs the relevant subset of candidate cancer genes displaying comparably altered expression, including Mcl1 (myeloid cell leukemia sequence 1), a highly expressed antiapoptotic gene residing within the chr 3 amplicon peak. CGH on mouse cDNA microarrays therefore represents a reliable method for the high-resolution characterization of CNAs in murine tumors, and a powerful approach for elucidating the molecular events in tumor development and progression in murine models.

Animals↗
PubMed2005

Genomics in myeloid leukemias: an array of possibilities.

Myeloid leukemias are clonal hematopoietic stem cell disorders characterized either by proliferation of one or more of the myeloid lineages (chronic myelogenous leukemia) or by clonal expansion of myeloid blasts (acute myeloid leukemia). Over the past several years our knowledge of these hematologic malignancies has increased tremendously. The result is a classification that incorporates morphologic, immunophenotypic, genetic and clinical features in an attempt to define biologically and clinically relevant entities. Nevertheless, in many tumor subtypes the pathogenic event is still unknown. Furthermore, well-defined leukemia subgroups exhibit considerable heterogeneity, arousing the suspicion that several molecularly distinct subtypes might exist within the same cytogenetic category. Therefore, an ideal classification system would ultimately be based on the underlying molecular pathogenesis, but such knowledge is not yet available. However, by surveying the expression levels of thousands of genes in parallel, DNA microarrays have recently contributed to an increasingly refined molecular taxonomy of myeloid disorders. This powerful technology is becoming well established and has been used to diagnosis cancer and predict clinical outcome, to discover novel tumor subclasses, to gain insights into pathogenesis, and to identify new therapeutic targets. While many challenges remain ahead, genomic technologies have already demonstrated tremendous potential. We expect whole genome approaches will significantly contribute to a better understanding of the pathogenesis and result in a refined molecular classification of myeloid leukemias.

Gene Expression Profiling↗
PubMed2005

An expression-based site of origin diagnostic method designed for clinical application to cancer of unknown origin.

Gene expression profiling offers a promising new technique for the diagnosis and prognosis of cancer. We have applied this technology to build a clinically robust site of origin classifier with the ultimate aim of applying it to determine the origin of cancer of unknown primary (CUP). A single cDNA microarray platform was used to profile 229 primary and metastatic tumors representing 14 tumor types and multiple histologic subtypes. This data set was subsequently used for training and validation of a support vector machine (SVM) classifier, demonstrating 89% accuracy using a 13-class model. Further, we show the translation of a five-class classifier to a quantitative PCR-based platform. Selecting 79 optimal gene markers, we generated a quantitative-PCR low-density array, allowing the assay of both fresh-frozen and formalin-fixed paraffin-embedded (FFPE) tissue. Data generated using both quantitative PCR and microarray were subsequently used to train and validate a cross-platform SVM model with high prediction accuracy. Finally, we applied our SVM classifiers to 13 cases of CUP. We show that the microarray SVM classifier was capable of making high confidence predictions in 11 of 13 cases. These predictions were supported by comprehensive review of the patients' clinical histories.

Gene Expression Profiling↗
PubMed2005

Genome-wide characterization of gene expression variations and DNA copy number changes in prostate cancer cell lines.

BACKGROUND: The aim of this study was to characterize gene expression and DNA copy number profiles in androgen sensitive (AS) and androgen insensitive (AI) prostate cancer cell lines on a genome-wide scale. METHODS: Gene expression profiles and DNA copy number changes were examined using DNA microarrays in eight commonly used prostate cancer cell lines. Chromosomal regions with DNA copy number changes were identified using cluster along chromosome (CLAC). RESULTS: There were discrete differences in gene expression patterns between AS and AI cells that were not limited to androgen-responsive genes. AI cells displayed more DNA copy number changes, especially amplifications, than AS cells. The gene expression profiles of cell lines showed limited similarities to prostate tumors harvested at surgery. CONCLUSIONS: AS and AI cell lines are different in their transcriptional programs and degree of DNA copy number alterations. This dataset provides a context for the use of prostate cancer cell lines as models for clinical cancers.

Cell Line, Tumor↗
PubMed2005

A DNA microarray survey of gene expression in normal human tissues.

BACKGROUND: Numerous studies have used DNA microarrays to survey gene expression in cancer and other disease states. Comparatively little is known about the genes expressed across the gamut of normal human tissues. Systematic studies of global gene-expression patterns, by linking variation in the expression of specific genes to phenotypic variation in the cells or tissues in which they are expressed, provide clues to the molecular organization of diverse cells and to the potential roles of the genes. RESULTS: Here we describe a systematic survey of gene expression in 115 human tissue samples representing 35 different tissue types, using cDNA microarrays representing approximately 26,000 different human genes. Unsupervised hierarchical cluster analysis of the gene-expression patterns in these tissues identified clusters of genes with related biological functions and grouped the tissue specimens in a pattern that reflected their anatomic locations, cellular compositions or physiologic functions. In unsupervised and supervised analyses, tissue-specific patterns of gene expression were readily discernable. By comparative hybridization to normal genomic DNA, we were also able to estimate transcript abundances for expressed genes. CONCLUSIONS: Our dataset provides a baseline for comparison to diseased tissues, and will aid in the identification of tissue-specific functions. In addition, our analysis identifies potential molecular markers for detection of injury to specific organs and tissues, and provides a foundation for selection of potential targets for selective anticancer therapy.

Cluster Analysis↗
PubMed2005

Aberrant epidermal growth factor receptor signaling and enhanced sensitivity to EGFR inhibitors in lung cancer.

Epidermal growth factor receptor (EGFR) is occasionally amplified and/or mutated in non-small cell lung cancer (NSCLC) and can be coexpressed with other members of the HER receptor family to form functional heterodimers. We therefore investigated lung cancer cell lines for alterations in EGFR gene copy number, enhanced expression of EGFR and other HER family members, and EGFR coding sequence mutations and correlated these findings with response to treatment with the EGFR inhibitors and the kinetics of ligand-induced signaling. We show here that somatic deletions in the tyrosine kinase domain of EGFR were associated with increased EGFR gene copy number in NSCLC. Treatment with the specific EGFR tyrosine kinase inhibitors (TKI) gefitinib or erlotinib or the EGFR inhibitory antibody cetuximab induced apoptosis of HCC827, a NSCLC cell line with EGFR gene amplification and an exon 19 deletion. H1819, a NSCLC cell line that expresses high levels of EGFR, ErbB2, and ErbB3 but has wild-type EGFR, showed intermediate sensitivity to TKIs. In both cell lines, ligand-induced receptor tyrosine phosphorylation was delayed and prolonged and AKT was constitutively phosphorylated (but remained inhibitable by EGFR TKI). Thus, in addition to EGFR mutations, other factors in NSCLC cells, such as high expression of ErbB family members, may constitutively activate AKT and sensitize cells to EGFR inhibitors.

Amino Acid Sequence↗
PubMed2005

Amplification of whole tumor genomes and gene-by-gene mapping of genomic aberrations from limited sources of fresh-frozen and paraffin-embedded DNA.

Sufficient quantity of genomic DNA can be a bottleneck in genome-wide analysis of clinical tissue samples. DNA polymerase Phi29 can be used for the random-primed amplification of whole genomes, although the amplification may introduce bias in gene dosage. We have performed a detailed investigation of this technique in archival fresh-frozen and formalin-fixed/paraffin-embedded tumor DNA by using cDNA microarray-based comparative genomic hybridization. Phi29 amplified DNA from matched pairs of fresh-frozen and formalin-fixed/paraffin-embedded tumor samples with similar efficiency. The distortion in gene dosage representation in the amplified DNA was nonrandom and reproducibly involved distinct genomic loci. Regional amplification efficiency was significantly linked to regional GC content of the template genome. The biased gene representation in amplified tumor DNA could be effectively normalized by using amplified reference DNA. Our data suggest that genome-wide gene dosage alterations in clinical tumor samples can be reliably assessed from a few hundred tumor cells. Therefore, this amplification method should lend itself to high-throughput genetic analyses of limited sources of tumor, such as fine-needle biopsies, laser-microdissected tissue, and small paraffin-embedded specimens.

Chromosome Aberrations↗
PubMed2005

Array-based comparative genomic hybridization identifies localized DNA amplifications and homozygous deletions in pancreatic cancer.

Pancreatic cancer, the fourth leading cause of cancer death in the United States, is frequently associated with the amplification and deletion of specific oncogenes and tumor-suppressor genes (TSGs), respectively. To identify such novel alterations and to discover the underlying genes, we performed comparative genomic hybridization on a set of 22 human pancreatic cancer cell lines, using cDNA microarrays measuring approximately 26,000 human genes (thereby providing an average mapping resolution of <60 kb). To define the subset of amplified and deleted genes with correspondingly altered expression, we also profiled mRNA levels in parallel using the same cDNA microarray platform. In total, we identified 14 high-level amplifications (38-4934 kb in size) and 15 homozygous deletions (46-725 kb). We discovered novel localized amplicons, suggesting previously unrecognized candidate oncogenes at 6p21, 7q21 (SMURF1, TRRAP), 11q22 (BIRC2, BIRC3), 12p12, 14q24 (TGFB3), 17q12, and 19q13. Likewise, we identified novel polymerase chain reaction-validated homozygous deletions indicating new candidate TSGs at 6q25, 8p23, 8p22 (TUSC3), 9q33 (TNC, TNFSF15), 10q22, 10q24 (CHUK), 11p15 (DKK3), 16q23, 18q23, 21q22 (PRDM15, ANKRD3), and Xp11. Our findings suggest candidate genes and pathways, which may contribute to the development or progression of pancreatic cancer.

Cell Line, Tumor↗