Edison T. Liu

Breast cancer classification and prognosis based on gene expression profiles from a population-based study

Comprehensive gene expression patterns generated from cDNA microarrays were correlated with detailed clinico-pathological characteristics and clinical outcome in an unselected group of 99 node-negative and node-positive breast cancer patients. Gene expression patterns were found to be strongly associated with estrogen receptor (ER) status and moderately associated with grade, but not associated with menopausal status, nodal status, or tumor size. Hierarchical cluster analysis segregated the tumors into two main groups based on their ER status, which correlated well with basal and luminal characteristics. Cox proportional hazards regression analysis identified 16 genes that were significantly associated with relapse-free survival at a stringent significance level of 0.001 to account for multiple comparisons. Of 231 genes previously reported by others [vant Veer, L. J., et al. (2002) Nature 415, 530-536] as being associated with survival, 93 probe elements overlapped with the set of 7,650 probe elements represented on the arrays used in this study. Hierarchical cluster analysis based on the set of 93 probe elements segregated our population into two distinct subgroups with different relapse-free survival (P < 0.03). The number of these 93 probe elements showing significant univariate association with relapse-free survival (P < 0.05) in the present study was 14, representing 11 unique genes. Genes involved in cell cycle, DNA replication, and chromosomal stability were consistently elevated in the various poor prognostic groups. In addition, glutathione S-transferase M3 emerged as an important survival marker in both studies. When taken together with other array studies, our results highlight the consistent biological and clinical associations with gene expression profiles.

High-fidelity mRNA amplification for gene profiling.

The completion of the Human Genome Project has made possible the comprehensive analysis of gene expression, and cDNA microarrays are now being employed for expression analysis in cancer cell lines or excised surgical specimens. However, broader application of cDNA microarrays is limited by the amount of RNA required: 50–200 μg of total RNA (T-RNA) and 2–5 μg poly(A) RNA. To broaden the use of cDNA microarrays, some methods aiming at intensifying fluorescence signal have resulted in modest improvement. Methods devoted to amplifying starting poly(A) RNA or cDNA show promise, in that detection can be increased by orders of magnitude. However, despite the common use of these amplification procedures, no systematic assessment of their limits and biases has been documented. We devised a procedure that optimizes amplification of low-abundance RNA samples by combining antisense RNA (aRNA) amplification with a template-switching effect (Clonetech, Palo Alto, CA). The fidelity of aRNA amplified from 1:10,000 to 1:100,000 of commonly used input RNA was comparable to expression profiles observed with conventional poly(A) RNA- or T-RNA-based arrays.

Comparative full-length genome sequence analysis of 14 SARS coronavirus isolates and common mutations associated with putative origins of infection

n Summaryn n Backgroundn The cause of severe acute respiratory syndrome (SARS) has been identified as a new coronavirus. Whole genome sequence analysis of various isolates might provide an indication of potential strain differences of this new virus. Moreover, mutation analysis will help to develop effective vaccines.n n n Methodsn We sequenced the entire SARS viral genome of cultured isolates from the index case (SIN2500) presenting in Singapore, from three primary contacts (SIN2774, SIN2748, and SIN2677), and one secondary contact (SIN2679). These sequences were compared with the isolates from Canada (TOR2), Hong Kong (CUHK-W1 and HKU39849), Hanoi (URBANI), Guangzhou (GZ01), and Beijing (BJ01, BJ02, BJ03, BJ04).n n n Findingsn We identified 129 sequence variations among the 14 isolates, with 16 recurrent variant sequences. Common variant sequences at four loci define two distinct genotypes of the SARS virus. One genotype was linked with infections originating in Hotel M in Hong Kong, the second contained isolates from Hong Kong, Guangzhou, and Beijing with no association with Hotel M (p<0.0001). Moreover, other common sequence variants further distinguished the geographical origins of the isolates, especially between Singapore and Beijing.n n n Interpretationn Despite the recent onset of the SARS epidemic, genetic signatures are emerging that partition the worldwide SARS viral isolates into groups on the basis of contact source history and geography. These signatures can be used to trace sources of infection. In addition, a common variant associated with a non-conservative aminoacid change in the S1 region of the spike protein, suggests that immunological pressures might be starting to influence the evolution of the SARS virus in human populations.n Published online May 9, 2003 http://image.thelancet.com/extras/03art4454web.pdfn n

Gene expression profiles derived from fine needle aspiration correlate with response to systemic chemotherapy in breast cancer

BackgroundDrug resistance in breast cancer is a major obstacle to successful chemotherapy. In this study we used cDNA microarray technology to examine gene expression profiles obtained from fine needle aspiration (FNA) of primary breast tumors before and after systemic chemotherapy. Our goal was to determine the feasibility of obtaining representative expression array profiles from limited amounts of tissue and to identify those expression profiles that correlate with treatment response.MethodsRepeat presurgical FNA samples were taken from six patients who were to undergo primary surgical treatment. Additionally, a group of 10 patients who were to receive neoadjuvant chemotherapy underwent two FNAs before chemotherapy (adriamycin 60 mg/m2 and cyclophosphamide 600 mg/m2) followed by another FNA on day 21 after the first cycle. Total RNA was amplified with T7 Eberwines procedure and labeled cDNA was hybridized onto a 7600-feature glass cDNA microarray.ResultsWe identified candidate gene expression profiles that might distinguish tumors with complete response to chemotherapy from tumors that do not respond, and found that the number of genes that change after one cycle of chemotherapy was 10 times greater in the responding group than in the non-responding group.ConclusionThis study supports the suitability of FNA-derived cDNA microarray expression profiling of breast cancers as a comprehensive genomic approach for studying the mechanisms of drug resistance. Our findings also demonstrate the potential of monitoring post-chemotherapy changes in expression profiles as a measure of pharmacodynamic effect and suggests that these approaches might yield useful results when validated by larger studies.

Cellular reprogramming by the conjoint action of ERα, FOXA1, and GATA3 to a ligand-inducible growth state.

Despite the role of the estrogen receptor α (ERα) pathway as a key growth driver for breast cells, the phenotypic consequence of exogenous introduction of ERα into ERα‐negative cells paradoxically has been growth inhibition. We mapped the binding profiles of ERα and its interacting transcription factors (TFs), FOXA1 and GATA3 in MCF‐7 breast carcinoma cells, and observed that these three TFs form a functional enhanceosome that regulates the genes driving core ERα function and cooperatively modulate the transcriptional networks previously ascribed to ERα alone. We demonstrate that these enhanceosome occupied sites are associated with optimal enhancer characteristics with highest p300 co‐activator recruitment, RNA Pol II occupancy, and chromatin opening. Most importantly, we show that the transfection of all three TFs was necessary to reprogramme the ERα‐negative MDA‐MB‐231 and BT‐549 cells to restore the estrogen‐responsive growth resembling estrogen‐treated ERα‐positive MCF‐7 cells. Cumulatively, these results suggest that all the enhanceosome components comprising ERα, FOXA1, and GATA3 are necessary for the full repertoire of cancer‐associated effects of the ERα.

Comparison of HER2 status by fluorescence in situ hybridization and immunohistochemistry to predict benefit from dose escalation of adjuvant doxorubicin-based therapy in node-positive breast cancer patients

PURPOSEnHER2 is a clinically important tumor marker in breast cancer; however, there is controversy regarding which method reliably measures HER2 status. We compared three HER2 laboratory methods: immunohistochemistry (IHC), fluorescence in situ hybridization (FISH) and polymerase chain reaction (PCR), to predict disease-free survival (DFS) and overall survival (OS) after adjuvant doxorubicin-based therapy in node-positive breast cancer patients.nnnMETHODSnThis is a Cancer and Leukemia Group B (CALGB) study, using 524 tumor blocks collected from breast cancer patients registered to clinical trial CALGB 8541. IHC employed CB11 and AO-11-854 monoclonal antibodies; FISH used PathVysion HER2 DNA Probe kit; PCR utilized differential PCR (D-PCR) methodology.nnnRESULTSnCases HER2 positive by IHC, FISH and D-PCR were 24%, 17%, and 18%, respectively. FISH and IHC were clearly related (kappa = 64.8%). All three methods demonstrated a similar relationship for DFS and OS. By any method, for patients with HER2-negative tumors, there was little or no effect of dose of adjuvant doxorubicin-based therapy. For patients with HER2-positive tumors, all three methods predicted a benefit from dose-intense (high-dose) compared with low- or moderate-dose adjuvant doxorubicin-based therapy.nnnCONCLUSIONnFISH is a reliable method to predict clinical outcome following adjuvant doxorubicin-based therapy for stage II breast cancer patients. There is a moderate level of concordance among the three methods (IHC, FISH, PCR). None of the methods is clearly superior. Although IHC-positive/FISH-positive tumors yielded the greatest interaction with dose of therapy in predicting outcome, no combination of assays tested was statistically superior.

Identification of discriminators of hepatoma by gene expression profiling using a minimal dataset approach

The severity of hepatocellular carcinoma (HCC) and the lack of good diagnostic markers and treatment strategies have rendered the disease a major challenge. Previous microarray analyses of HCC were restricted to the selected tissue sample sets without validation on an independent series of tissue samples. We describe an approach to the identification of a composite discriminator cassette by intersecting different microarray datasets. We studied the global transcriptional profiles of matched HCC tumor and nontumor liver samples from 37 patients using cDNA (cDNA) microarrays. Application of nonparametric Wilcoxon statistical analyses (P < 1 × 10−6) and the criteria of 1.5‐fold differential gene expression change resulted in the identification of 218 genes, including BMI‐1, ERBB3, and those involved in the ubiquitin‐proteasome pathway. Elevated ERBB2 and epidermal growth factor receptor (EGFR) expression levels were detected in ERBB3‐expressing tumors, suggesting the presence of ERBB3 cognate partners. Comparison of our dataset with an earlier study of approximately 150 tissue sets identified multiple overlapping discriminator markers, suggesting good concordance of data despite differences in patient populations and technology platforms. These overlapping discriminator markers could distinguish HCC tumor from nontumor liver samples with reasonable precision and the features were unlikely to appear by chance, as measured by Monte Carlo simulations. More significantly, validation of the discriminator cassettes on an independent set of 58 liver biopsy specimens yielded greater than 93% prediction accuracy. In conclusion, these data indicate the robustness of expression profiling in marker discovery using limited patient tissue specimens as well as identify novel genes that are highly likely to be excellent markers for HCC diagnosis and treatment. Supplementary material for this article can be found on the HEPATOLOGY website (http://interscience.wiley.com/jpages/0270‐9139/suppmat/index.html). (HEPATOLOGY 2004;39:944–953.)

Gene array of VHL mutation and hypoxia shows novel hypoxia-induced genes and that cyclin D1 is a VHL target gene

Gene expression analysis was performed on a human renal cancer cell line (786-0) with mutated VHL gene and a transfectant with wild-type VHL to analyse genes regulated by VHL and to compare with the gene programme regulated by hypoxia. There was a highly significant concordance of the global gene response to hypoxia and genes suppressed by VHL. Cyclin D1 was the most highly inducible transcript and 14-3-3 epsilon was downregulated. There were some genes regulated by VHL but not hypoxia in the renal cell line, suggesting a VHL role independent of hypoxia. However in nonrenal cell lines they were hypoxia regulated. These included several new pathways regulated by hypoxia, including RNase 6PL, collagen type 1 alpha 1, integrin alpha 5, ferritin light polypeptide, JM4 protein, transgelin and L1 cell adhesion molecule. These were not found in a recent SAGE analysis of the same cell line. Hypoxia induced downregulation of Cyclin D1 in nonrenal cells via an HIF independent pathway. The selective regulation of Cyclin D1 by hypoxia in renal cells may therefore contribute to the tissue selectivity of VHL mutation.

De-Novo Identification of PPARγ/RXR Binding Sites and Direct Targets during Adipogenesis

Background The pathophysiology of obesity and type 2 diabetes mellitus is associated with abnormalities in endocrine signaling in adipose tissue and one of the key signaling affectors operative in these disorders is the nuclear hormone transcription factor peroxisome proliferator-activated receptor-γ (PPARγ). PPARγ has pleiotropic functions affecting a wide range of fundamental biological processes including the regulation of genes that modulate insulin sensitivity, adipocyte differentiation, inflammation and atherosclerosis. To date, only a limited number of direct targets for PPARγ have been identified through research using the well established pre-adipogenic cell line, 3T3-L1. In order to obtain a genome-wide view of PPARγ binding sites, we applied the pair end-tagging technology (ChIP-PET) to map PPARγ binding sites in 3T3-L1 preadipocyte cells. Methodology/Principal Findings Coupling gene expression profile analysis with ChIP-PET, we identified in a genome-wide manner over 7700 DNA binding sites of the transcription factor PPARγ and its heterodimeric partner RXR during the course of adipocyte differentiation. Our validation studies prove that the identified sites are bona fide binding sites for both PPARγ and RXR and that they are functionally capable of driving PPARγ specific transcription. Our results strongly indicate that PPARγ is the predominant heterodimerization partner for RXR during late stages of adipocyte differentiation. Additionally, we find that PPARγ/RXR association is enriched within the proximity of the 5′ region of the transcription start site and this association is significantly associated with transcriptional up-regulation of genes involved in fatty acid and lipid metabolism confirming the role of PPARγ as the master transcriptional regulator of adipogenesis. Evolutionary conservation analysis of these binding sites is greater when adjacent to up-regulated genes than down-regulated genes, suggesting the primordial function of PPARγ/RXR is in the induction of genes. Our functional validations resulted in identifying novel PPARγ direct targets that have not been previously reported to promote adipogenic differentiation. Conclusions/Significance We have identified in a genome-wide manner the binding sites of PPARγ and RXR during the course of adipogenic differentiation in 3T3L1 cells, and provide an important resource for the study of PPARγ function in the context of adipocyte differentiation.

Molecular determinants of tumor differentiation in papillary serous ovarian carcinoma

In epithelial ovarian cancer, tumor grade is an independent prognosticator whose molecular determinants remain unknown. We investigated patterns of gene expression in well‐ and poorly differentiated serous papillary ovarian and peritoneal carcinomas with cDNA microarrays. A 6500‐feature cDNA microarray was used for comparison of the molecular profiles of eight grade III and four grade I stage III serous papillary adenocarcinomas. With a modified F‐test in conjunction with random permutations, 99 genes whose expression was significantly different between grade I and grade III tumors were identified (Pu2009<u20090.01). A disproportionate number of these differentially expressed genes were located on the chromosomal regions 20q13 and all exhibited higher expression in grade III tumors. Interphase fluorescent in situ hybridization demonstrated 20q13 amplification in two of the four grade III and none of the three grade I tumors available for evaluation. Several centrosome‐related genes also showed higher expression in grade III tumors. We propose a model in which tumor differentiation is inversely correlated with the overexpression of several oncogenes located on 20q13, a common amplicon in ovarian and numerous other cancers. Dysregulation of centrosome function is one potential mechanistic link between genetic/epigenetic changes and the poorly differentiated phenotype in ovarian cancer. Published 2003 Wiley‐Liss, Inc.