Microarrays as cancer keys: an array of possibilities

Amphiregulin blockade decreases the levodopa-induced dyskinesia in a 6-hydroxydopamine Parkinson's disease mouse model

BACKGROUND

Levodopa (L-DOPA) is considered the most reliable drug for treating Parkinson's disease (PD) clinical symptoms. Regrettably, long-term L-DOPA therapy results in the emergence of drug-induced abnormal involuntary movements (AIMs) in most PD patients. The mechanisms underlying motor fluctuations and dyskinesia induced by L-DOPA (LID) are still perplexing.

METHODS

Here, we first performed the analysis on the microarray data set (GSE55096) from the gene expression omnibus (GEO) repository and identified the differentially expressed genes (DEGs) using linear models for microarray analysis (Limma) R packages from the Bioconductor project. 12 genes (Nr4a2, Areg, Tinf2, Ptgs2, Pdlim1, Tes, Irf6, Tgfb1, Serpinb2, Lipg, Creb3l1, Lypd1) were found to be upregulated. Six genes were validated on quantitative polymerase chain reaction and subsequently, Amphiregulin (Areg) was selected (based on log2 fold change) for further experiments to unravel its involvement in LID. Areg LV_shRNA was used to knock down Areg to explore its therapeutic role in the LID model.

RESULTS

Western blotting and immunofluorescence results show that AREG is significantly expressed in the LID group relative to the control. Dyskinetic movements in LID mice were alleviated by Areg knockdown, and the protein expression of delta FOSB, the commonly attributable protein in LID, was decreased. Moreover, Areg knockdown reduced the protein expression of P-ERK. In order to ascertain whether the inhibition of the ERK pathway (a common pathway known to mediate levodopa-induced dyskinesia) could also impede Areg, the animals were injected with an ERK inhibitor (PD98059). Afterward, the AIMs, AREG, and ERK protein expression were measured relative to the control group. A group treated with ERK inhibitor had a significant decrease of AREG and phosphorylated ERK protein expression relative to the control group.

CONCLUSION

Taken together, our results indicate unequivocal involvement of Areg in levodopa-induced dyskinesia, thus a target for therapy development.

Prostate-Specific Membrane Antigen (PSMA)-Positive Extracellular Vesicles in Urine-A Potential Liquid Biopsy Strategy for Prostate Cancer Diagnosis?

All cells release extracellular vesicles (EVs) to communicate with adjacent and distant cells. Consequently, circulating EVs are found in all bodily fluids, providing information applicable for liquid biopsy in early cancer diagnosis. Studies observed an overexpression of the membrane-bound prostate-specific membrane antigen (PSMA) on prostate cancer cells. To investigate whether EVs derived from communicating prostate cells allow for reliable conclusions on prostate cancer development, we isolated PSMA-positive, as well as CD9-positive, EVs from cell-free urine with the use of magnetic beads. These populations of EVs were subsequently compared to CD9-positive EVs isolated from female urine in Western blotting, indicating the successful isolation of prostate-derived and ubiquitous EVs, respectively. Furthermore, we developed a device with an adapted protocol that enables an automated immunomagnetic enrichment of EVs of large sample volumes (up to 10 mL), while simultaneously reducing the overall bead loss and hands-on time. With an in-house spotted antibody microarray, we characterized PSMA as well as other EV surface markers of a prostate cohort of 44 urine samples in a more simplified way. In conclusion, the automated and specific enrichment of EVs from urine has a high potential for future diagnostic applications.

In silico bioinformatics analysis for identification of differentially expressed genes and therapeutic drug molecules in Glucocorticoid-resistant Multiple myeloma

Multiple myeloma (MM), second most common hematological malignancy, still remains irremediable because of acquisition of drug resistance. Glucocorticoid (GC) therapy, which is used as one of the key therapies against MM, is hindered by the incidence of GC resistance. The underlying mechanism of this acquired GC resistance in MM is not fully elucidated. Therefore, the present study was aimed to identify the differentially expressed genes (DEGs), associated micro RNAs (miRNAs), and transcription factors (TFs) from the microarray datasets of GC-resistant and GC-sensitive MM cell lines, obtained from Gene Expression Omnibus (GEO) database. DEGs were identified using GEO2R tool from two datasets and common DEGs were obtained by constructing Venn diagram. Then the Gene ontology (GO) and pathway enrichment analysis were performed using DAVID database. Genetic alterations in DEGs were examined using COSMIC database. Protein-protein interaction (PPI) network of DEGs was constructed using STRING database and Cytoscape tool. Network of interaction of DEGs and miRNAs as well as TFs were obtained and constructed using mirDIP, TRRUST, and miRNet tools. Drug gene interaction was studied to identify potential drug molecules by DGIdb tool. Six common DEGs, CDKN1A, CDKN2A, NLRP11, BTK, CD52, and RELN, were found to be significantly upregulated in GC-resistant MM and selected for further analysis. miRNA analysis detected hsa-mir-34a-5p that could interact with maximum target DEGs. Two TFs, Sp1 and Sp3, were found to regulate the expression of selected DEGs. The entire study may provide a new understanding about the GC resistance in MM.

Spatial mapping of cancer tissues by OMICS technologies

Spatial mapping of heterogeneity in gene expression in cancer tissues can improve our understanding of cancers and help in the rapid detection of cancers with high accuracy and reliability. Significant advancements have been made in recent years in OMICS technologies, which possess the strong potential to be applied in the spatial mapping of biopsy tissue samples and their molecular profiling to a single-cell level. The clinical application of OMICS technologies in spatial profiling of cancer tissues is also advancing. The current review presents recent advancements and prospects of applying OMICS technologies to the spatial mapping of various analytes in cancer tissues. We benchmark the current state of the art in the field to advance existing OMICS technologies for high throughput spatial profiling. The factors taken into consideration include spatial resolution, types of biomolecules, number of different biomolecules that can be detected from the same assay, labeled versus label-free approaches, and approximate time required for each assay. Further advancements are still needed for the widespread application of OMICs technologies in performing fast and high throughput spatial mapping of cancer tissues as well as their effective use in research and clinical applications.

Identification of hub genes in bladder cancer based on weighted gene co-expression network analysis from TCGA database

Background

Muscular invasive bladder cancer (MIBC) is a common malignant tumor in the world. Because of their heterogeneity in prognosis and response to treatment, biomarkers that can predict survival or help make treatment decisions in patients with MIBC are essential for individualized treatment.

Aim

We aimed to integrate bioinformatics research methods to identify a set of effective biomarkers capable of predicting, diagnosing, and treating MIBC. To provide a new theoretical basis for the diagnosis and treatment of bladder cancer.

Methods and results

Gene expression profiles and clinical data of MIBC were obtained by downloading from the Cancer Genome Atlas database. A dataset of 129 MIBC cases and controls was included. 2084 up‐regulated genes and 2961 down‐regulated genes were identified by differentially expressed gene (DEG) analysis. Then, gene ontology analysis was performed to explore the biological functions of DEGs, respectively. The up‐regulated DEGs are mainly enriched in epidermal cell differentiation, mitotic nuclear division, and so forth. They are also involved in the cell cycle, p53 signaling pathway, PPAR signaling pathway, and so forth. The weighted gene co‐expression network analysis yielded five modules related to pathological stages and grading, of which blue and turquoise were the most relevant modules for MIBC. Next, Using Kaplan–Meier survival analysis to identify further hub genes, the screening criteria at p ≤ .05, we found CNKSR1, HIP1R, CFL2, TPM1, CSRP1, SYNM, POPDC2, PJA2, and RBBP8NL genes associated with the progression and prognosis of MIBC patients. Finally, immunohistochemistry experiments further confirmed that CNKSR1 plays a vital role in the tumorigenic context of MIBC.

Conclusion

The research suggests that CNKSR1, POPDC2, and PJA2 may be novel biomarkers as therapeutic targets for MIBC, especially we used immunohistochemical further to validate CNKSR1 as a therapeutic target for MIBC which may help to improve the prognosis for MIBC.

Identification of hub genes and small molecule therapeutic drugs related to breast cancer with comprehensive bioinformatics analysis

Breast cancer is one of the most common malignant tumors among women worldwide and has a high morbidity and mortality. This research aimed to identify hub genes and small molecule drugs for breast cancer by integrated bioinformatics analysis. After downloading multiple gene expression datasets from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database, 283 overlapping differentially expressed genes (DEGs) significantly enriched in different cancer-related functions and pathways were obtained using LIMMA, VennDiagram and ClusterProfiler packages of R. We then analyzed the topology of protein–protein interaction (PPI) network with overlapping DEGs and further obtained six hub genes (RRM2, CDC20, CCNB2, BUB1B, CDK1, and CCNA2) from the network via STRING and Cytoscape. Subsequently, we conducted genes expression verification, genetic alterations evaluation, immune infiltration prediction, clinicopathological parameters analysis, identification of transcriptional and post-transcriptional regulatory molecules, and survival analysis for these hub genes. Meanwhile, 29 possible drug candidates (e.g., Cladribine, Gallium nitrate, Alvocidib, 1β-hydroxyalantolactone, Berberine hydrochloride, Nitidine chloride) were identified from the DGIdb database and the GSE85871 dataset. In addition, some transcription factors and miRNAs (e.g., E2F1, PTTG1, TP53, ZBTB16, hsa-miR-130a-3p, hsa-miR-204-5p) targeting hub genes were identified as key regulators in the progression of breast cancer. In conclusion, our study identified six hub genes and 29 potential drug candidates for breast cancer. These findings may advance understanding regarding the diagnosis, prognosis and treatment of breast cancer.

EREG-driven oncogenesis of Head and Neck Squamous Cell Carcinoma exhibits higher sensitivity to Erlotinib therapy

Rationale: The oncogenesis of head and neck squamous cell carcinoma (HNSCC) is believed to result from oncogene activation and tumor suppressor inactivation. Here, we identified a new oncogenic role for the EREG gene in HNSCC. Methods: The TCGA database and immunohistochemistry assay were used to analyze expression of EREG in HNSCC tissues. Immunoblotting was performed to identify the EGFR-mediated pathways altered by EREG. The role of EREG in oncogenesis was investigated in vivo and in vitro. Results: Upregulated EREG expression predicted a poor prognosis and triggered HNSCC oncogenic transformation by activating the epidermal growth factor receptor (EGFR) signaling pathway. We also demonstrated the direct association of EREG with EGFR and that this binding required EGFR domains I and III and the N57 residue of EREG. Moreover, EREG overexpression was shown to promote HNSCC oncogenesis by inducing C-Myc expression, and the pharmacological inhibition of C-Myc rescued EREG-promoted HNSCC oncogenesis. Unlike other EGFR ligands, EREG could mimic EGFR mutations by sustaining the activation of the EGFR-Erk pathway, and high EREG expression was positively associated with the response to treatment with the EGFR inhibitor erlotinib. Furthermore, knockdown of EREG decreased sensitivity to erlotinib treatment in vitro and in vivo. Conclusions: These results identify the EREG-EGFR-C-Myc pathway as a crucial axis that drives HNSCC oncogenesis and show that EREG expression could be a predictive functional marker of sensitivity to erlotinib therapy in HNSCC.

Integrated bioinformatics analysis to identify 15 hub genes in breast cancer

The aim of the present study was to identify the hub genes and provide insight into the tumorigenesis and development of breast cancer. To examine the hub genes in breast cancer, integrated bioinformatics analysis was performed. Gene expression profiles were obtained from the Gene Expression Omnibus (GEO) database and the differentially expressed genes (DEGs) were identified using the ‘limma’ package in R. Gene Ontology enrichment analysis and Kyoto Encyclopedia of Genes and Genomes pathway analysis was used to determine the functional annotations and potential pathways of the DEGs. Subsequently, a protein-protein interaction network analysis and weighted correlation network analysis (WGCNA) were conducted to identify hub genes. To confirm the reliability of the identified hub genes, RNA gene expression profiles were obtained from The Cancer Genome Atlas (TCGA)-breast cancer database, and WGCNA was used to screen for genes that were markedly correlated with breast cancer. By combining the results from the GEO and TCGA datasets, 15 hub genes were identified to be associated with breast cancer pathophysiology. Overall survival analysis was performed to examine the association between the expression of hub genes and the overall survival time of patients with breast cancer. Higher expression of all hub genes was associated with significantly shorter overall survival in patients with breast cancer compared with patients with lower levels of expression of the respective gene.

Tissue and serum expression of TGM-3 may be prognostic marker in patients of oral squamous cell carcinoma undergoing chemo-radiotherapy

Radioresistance is one of the main determinants of treatment outcome in oral squamous cell carcinoma (OSCC), but its prediction is difficult. Several authors aimed to establish radioresistant OSCC cell lines to identify genes with altered expression in response to radioresistance. The development of OSCC is a multistep carcinogenic process that includes activation of several oncogenes and inactivation of tumour suppressor genes. TGM-3 is a tumour suppressor gene and contributes to carcinogenesis process. The aim of this study was to estimate serum and tissue expression of TGM-3 and its correlation with clinico-pathological factors and overall survival in patients of OSCC undergoing chemo-radiotherapy. Tissue expression was observed in formalin fixed tissue biopsies of 96 cases of OSCC and 32 healthy controls were subjected to immunohistochemistry (IHC) by using antibody against TGM-3 and serum level was estimated by ELISA method. mRNA expression was determined by using Real-Time PCR. Patients were followed for 2 year for chemo radiotherapy response. In OSCC, 76.70% cases and in controls 90.62% were positive for TGM-3 IHC expression. TGM-3 expression was cytoplasmic and nuclear staining expressed in keratinized layer, stratum granulosum and stratum spinosum in controls and tumour cells. Mean serum TGM-3 in pre chemo-radiotherapy OSCC cases were 1304.83±573.55, post chemo-radiotherapy samples were 1530.64±669.33 and controls were 1869.16±1377.36, but difference was significant in pre chemo-radiotherapy samples as compared to controls (p<0.018). This finding was also confirmed by real- time PCR analysis in which down regulation (-7.92 fold change) of TGM-3 in OSCC as compared to controls. TGM-3 expression was significantly associated with response to chemo-radiotherapy treatment (p<0.007) and overall survival (p<0.015). Patents having higher level of TGM-3 expression have good response to chemo-radiotherapy and also have better overall survival. TGM-3 may serve as a candidate biomarker for responsiveness to chemo-radiotherapy treatment in OSCC patients.

Identification of Key Genes and Pathways in Tongue Squamous Cell Carcinoma Using Bioinformatics Analysis

BACKGROUND Tongue squamous cell carcinoma (TSCC) is a major type of oral cancers and has remained an intractable cancer over the past decades. The aim of this study was to identify differentially expressed genes (DEGs) during TSCC and reveal their potential mechanisms. MATERIAL AND METHODS The gene expression profiles of GSE13601 were downloaded from the GEO database. The GSE13601 dataset contains 57 samples, including 31 tongue SCC samples and 26 matched normal mucosa samples. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analyses were performed; Cytoscape software was used for the protein-protein interaction (PPI) network and module analysis of the DEGs. RESULTS We identified a total of 1,050 upregulated DEGs (uDEGs) and 702 downregulated DEGs (dDEGs) of TSCC. The GO analysis results showed that uDEGs were significantly enriched in the following biological processes (BP): signal transduction, positive or negative regulation of cell proliferation, and negative regulation of cell proliferation. The dDEGs were significantly enriched in the following biological processes: signal transduction, cell adhesion, and apoptotic process. The KEGG pathway analysis showed that uDEGs were enriched in metabolic pathways, pathways in cancer, and PI3K-Akt signaling pathway, while the dDEGs were enriched in focal adhesion and ECM-receptor interaction. The top centrality hub genes RAC1, APP, EGFR, KNG1, AGT, and HRAS were identified from the PPI network. Module analysis revealed that TSCC was associated with significant pathways, including neuroactive ligand-receptor interaction, calcium signaling pathway, and chemokine signaling pathway. CONCLUSIONS The present study identified key genes and signal pathways, which deepen our understanding of the molecular mechanisms of carcinogenesis and development of the disease, and might be used as diagnostic and therapeutic molecular biomarkers for TSCC.

Transcriptomic profiles differentiate normal rectal epithelium and adenocarcinoma

Adenocarcinoma is a histologic diagnosis based on subjective findings. Transcriptional profiles have been used to differentiate normal tissue from disease and could provide a means of identifying malignancy. The goal of this study was to generate and test transcriptomic profiles that differentiate normal from adenocarcinomatous rectum. Comparisons were made between cDNA microarrays derived from normal epithelium and rectal adenocarcinoma. Results were filtered according to standard deviation to retain only highly dysregulated genes. Genes differentially expressed between cancer and normal tissue on two-groups t test (P < 0.05, Bonferroni P value adjustment) were further analyzed. Genes were rank ordered in terms of descending fold change. For each comparison (tumor versus normal epithelium), those 5 genes with the greatest positive fold change were grouped in a classifier. Five separate tests were applied to evaluate the discriminatory capacity of each classifier. Genetic classifiers derived comparing normal epithelium with malignant rectal epithelium from pooled stages had a mean sensitivity and specificity of 99.6% and 98.2%, respectively. The classifiers derived from comparing normal and stage I cancer had comparable mean sensitivities and specificities (97% and 98%, respectively). Areas under the summary receiver-operator characteristic curves for each classifier were 0.981 and 0.972, respectively. One gene was common to both classifiers. Classifiers were tested in an independent Gene Expression Omnibus-derived dataset. Both classifiers retained their predictive properties. Transcriptomic profiles comprising as few as 5 genes are highly accurate in differentiating normal from adenocarcinomatous rectal epithelium, including early-stage disease.

Genomic expression profiling and bioinformatics analysis of pancreatic cancer

Pancreatic cancer is a polygenic disease and the fourth leading cause of cancer-associated mortality worldwide; however, the tumorigenesis of pancreatic cancer remains poorly understood. Research at a molecular level, which includes the exploration of biomarkers for early diagnosis and specific targets for therapy, may effectively aid in the diagnosis of pancreatic cancer in its early stages and in the development of targeted molecular-biological approaches for treatment, thus improving prognosis. By conducting expression profiling in para-carcinoma, carcinoma and relapse of human pancreatic tissues, 319 genes or transcripts with differential expression levels >3-fold between these tissue types were identified. Further analysis with Gene Ontology and the Kyoto Encyclopedia of Genes and Genomes demonstrated that the translation, nucleus assembly processes and molecular functions associated with vitamin B6 and pyridoxal phosphate binding in pancreatic carcinoma were abnormal. Pancreatic cancer was additionally identified to be closely associated with certain autoimmune diseases, including type I diabetes mellitus and systemic lupus erythematosus.

Somatic mosaicism in the human genome

Somatic mosaicism refers to the occurrence of two genetically distinct populations of cells within an individual, derived from a postzygotic mutation. In contrast to inherited mutations, somatic mosaic mutations may affect only a portion of the body and are not transmitted to progeny. These mutations affect varying genomic sizes ranging from single nucleotides to entire chromosomes and have been implicated in disease, most prominently cancer. The phenotypic consequences of somatic mosaicism are dependent upon many factors including the developmental time at which the mutation occurs, the areas of the body that are affected, and the pathophysiological effect(s) of the mutation. The advent of second-generation sequencing technologies has augmented existing array-based and cytogenetic approaches for the identification of somatic mutations. We outline the strengths and weaknesses of these techniques and highlight recent insights into the role of somatic mosaicism in causing cancer, neurodegenerative, monogenic, and complex disease.

Global gene expression distribution in non-cancerous complex diseases

For gene expression in non-cancerous complex diseases, we systemically evaluated the sensitivities of biological discoveries to violation of the common normalization assumption. Our results indicated that gene expression may be widely up-regulated in digestive system and musculoskeletal diseases. However, global signal intensities showed little difference in other four disease types.

Molecular neuro-oncology and the development of targeted therapeutic strategies for brain tumors Part 4: p53 signaling pathway

Brain tumors are a diverse group of malignancies that remain refractory to conventional treatment approaches. Molecular neuro-oncology has now begun to clarify the transformed phenotype of brain tumors and identify oncogenic pathways that might be amenable to targeted therapy. Loss of the tumor suppressor gene p53 and its encoded protein are the most common genetic events in human cancer and are a frequent occurrence in brain tumors. p53 functions as a transcription factor and is responsible for the transactivation and repression of key genes involved in cell growth, apoptosis and the cell cycle. Mutation of the p53 gene or dysfunction of its signaling pathway are early events in the transformation process of astrocytic gliomas. The majority of mutations are missense and occur in the conserved regions of the gene, within exons 5 through 8. Molecular therapeutic strategies to normalize p53 signaling in cells with mutant p53 include pharmacologic rescue of mutant protein, gene therapy approaches, small-molecule agonists of downstream inhibitory genes, antisense approaches and oncolytic viruses. Other strategies include activation of normal p53 activity, inhibition of mdm2-mediated degradation of p53 and blockade of p53 nuclear export. Further development of targeted therapies designed to restore or enhance p53 function, and evaluation of these new agents in clinical trials, will be needed to improve survival and quality of life for patients with brain tumors.

Molecular neuro-oncology and development of targeted therapeutic strategies for brain tumors. Part 2: PI3K/Akt/PTEN, mTOR, SHH/PTCH and angiogenesis

Brain tumors are a diverse group of malignancies that remain refractory to conventional treatment approaches. Molecular neuro-oncology has now begun to clarify the transformed phenotype of brain tumors and identify oncogenic pathways that might be amenable to targeted therapy. Activity of the phosphoinositide 3; kinase (PI3K)/Akt pathway is often upregulated in brain tumors due to excessive stimulation by growth factor receptors and Ras. Loss of function of the tumor suppressor gene PTEN also frequently contributes to upregulation of PI3K/Akt. Several compounds, such as wortmannin and LY-294002, can target PI3K and inhibit activity of this pathway. The mammalian target of rapamycin (mTOR) is an important regulator of cell growth and metabolism and is often upregulated by Akt. Clinical trials of CCI-779, an inhibitor of mTOR, are ongoing in recurrent malignant glioma patients. The sonic hedgehog/PTCH pathway is involved in the tumorigenesis of some familial and sporadic medulloblastomas. This pathway can be targeted by cyclopamine, which is under evaluation in preclinical studies. Angiogenesis is a critical process for development and progression of brain tumors. Targeted approaches to inhibit angiogenesis include monoclonal antibodies, receptor tyrosine kinase inhibitors, antisense oligonucleotides and gene therapy. Clinical trials are ongoing for numerous angiogenesis inhibitors, including thalidomide, CC-5103 and PTK 787/ZK 222584. Further development of targeted therapies and evaluation of these new agents in clinical trials will be needed to improve survival and quality of life of patients with brain tumors.

TGM3, a candidate tumor suppressor gene, contributes to human head and neck cancer

BACKGROUND

In our previous study using oligonucleotide microarrays, we revealed that transglutaminase 3 (TGM3) was remarkably down-regulated in head and neck cancer (HNC). However, the potential of TGM3 as a useful biomarker or molecular target for HNC is unclear.

METHODS

The transcriptional and post-translational status of TGM3 in HNC cell lines and specimens was detected using real-time PCR and western blot analysis. Bisulfate-treated DNA sequencing was used to analyze the molecular mechanism of TGM3 gene silencing. In addition, the effects of TGM3 on the proliferation, colony formation and induction of apoptosis in vitro and tumorigenicity in vivo were investigated through exogenous expression of TGM3 in HNC cells. Immunohistochemistry was used to evaluate TGM3 expression in large HNC samples.

RESULTS

TGM3 was down-regulated in HNC samples and cell lines (P < 0.0001). The hypermethylation of a promoter CpG island was one of the mechanisms of silencing the TGM3 gene in HNC. Exogenous expression of TGM3 in HNC cells could inhibit the proliferation and enhance the apoptosis of HNC cells in vitro and suppress tumor growth in vivo. In addition, TGM3 protein levels were strongly associated with the pathological differentiation of HNC tissues (P = 0.0037). Survival analysis revealed that low TGM3 expression was associated with worse overall survival (P = 0.0002), and TGM3 expression level was an independent predictor in patients with HNC.

CONCLUSIONS

The studies prove that TGM3, as a candidate tumor suppressor, contributes to the carcinogenesis and development of HNC and may serve as a useful biomarker for patients with HNC.

Cumulative number of altered biomarkers in mammalian target of rapamycin pathway is an independent predictor of outcome in patients with clear cell renal cell carcinoma

OBJECTIVE

To evaluate the association of the altered expression of the mammalian target of rapamycin (mTOR) pathway components with oncologic outcomes in patients with nonmetastatic clear cell renal cell carcinoma (ccRCC).

MATERIALS AND METHODS

Immunohistochemistry for phosphorylated-S6, phosphorylated-mTOR, mTOR, phosphorylated-AKT, hypoxia inducible factor-1α, Raptor, phosphatase and tensin homolog (PTEN), phosphoinositide 3-kinase (PI3K), and phosphorylated 4E-binding protein-1 was performed on tissue microarray constructs of patients treated for nonmetastatic kidney cancer from 1997 to 2010. The relationship between individual altered marker expression and a prognostic marker score (low, intermediate, and high, defined as ≤ 3, 4-5, >5 altered biomarkers, respectively) and oncologic outcome was assessed.

RESULTS

The study included 419 patients with nonmetastatic ccRCC, with a median follow-up period of 26 months (range 6-150). The tumors were nonorgan confined (pT3-T4) in 86 (20.5%) and high Fuhrman nuclear grade (3-4) in 131 (31%). A low, intermediate, and high prognostic marker score was found in 214 (51%), 152 (36%), and 53 (13%) patients, respectively. Kaplan-Meier analysis demonstrated a statistically significant correlation between the risk groups and disease recurrence and cancer-specific survival. In a multivariate Cox regression analysis controlling for tumor stage and grade, a high marker score was an independent predictor of disease recurrence (hazard ratio 3.3, 95% confidence interval 1.33-8.39, P = .01), and a combination of a high and an intermediate score was an independent predictor of survival (hazard ratio 4.8, 95% confidence interval 1.27-4.78, P = .008).

CONCLUSION

The cumulative number of aberrantly expressed biomarkers correlated with aggressive tumor biology and inferior oncologic outcomes in patients with ccRCC. Our data support prospective pathway-based exploration of the mTOR signaling cascade to augment current clinicopathologic predictors of oncologic outcomes in patients with ccRCC.

Extensive up-regulation of gene expression in cancer: the normalised use of microarray data

Based on the assumption that only a few genes are differentially expressed in a disease and have balanced upward and downward expression level changes, researchers usually normalise microarray data by forcing all of the arrays to have the same probe intensity distributions to remove technical variations in the data. However, accumulated evidence suggests that gene expressions could be widely altered in cancer, so we need to evaluate the sensitivities of biological discoveries to violation of the normalisation assumption. Here, we show that the medians of the original probe intensities increase in most of the ten cancer types analyzed in this paper, indicating that genes may be widely up-regulated in many cancer types. Thus, at least for cancer study, normalising all arrays to have the same distribution of probe intensities regardless of the state (diseased vs. normal) tends to falsely produce many down-regulated differentially expressed (DE) genes while missing many truly up-regulated DE genes. We also show that the DE genes solely detected in the non-normalised data for cancers are highly reproducible across different datasets for the same cancers, indicating that effective biological signals naturally exist in the non-normalised data. Because the powers of current statistical analyses using the non-normalised data tend to be low, we suggest selecting DE genes in both normalised and non-normalised data and then filter out the false DE genes extracted from the normalised data that show opposite deregulation directions in the non-normalised data.

A Comprehensive Guide to Sleeping Beauty-Based Somatic Transposon Mutagenesis in the Mouse

Recent advances in whole genome analyses made possible by next-generation DNA sequencing, high-density array comparative genome hybridization (aCGH), and other technologies have made it apparent that cancers harbor numerous genomic changes. However, without functional correlation or validation, it has proven difficult to determine which genetic changes are necessary or sufficient to produce cancer. Thus, it is still necessary to perform unbiased functional studies using model organisms to help interpret the results of whole genome analyses of human tumors. To this end, a Sleeping Beauty (SB) transposon-based mutagenesis technology was developed to identify genes that, when mutated, can cause cancer. Herein a detailed methodology to initiate and carry out an SB transposon mutagenesis screen is described. Although this system might be used to identify genes involved with many cellular phenotypes, it has been primarily implemented for cancer. Thus, SB transposon somatic cell screens for cancer development are highlighted. Curr. Protoc. Mouse Biol. 1:347-368 © 2011 by John Wiley & Sons, Inc.

Extensive increase of microarray signals in cancers calls for novel normalization assumptions

When using microarray data for studying a complex disease such as cancer, it is a common practice to normalize data to force all arrays to have the same distribution of probe intensities regardless of the biological groups of samples. The assumption underlying such normalization is that in a disease the majority of genes are not differentially expressed genes (DE genes) and the numbers of up- and down-regulated genes are roughly equal. However, accumulated evidences suggest gene expressions could be widely altered in cancer, so we need to evaluate the sensitivities of biological discoveries to violation of the normalization assumption. Here, we analyzed 7 large Affymetrix datasets of pair-matched normal and cancer samples for cancers collected in the NCBI GEO database. We showed that in 6 of these 7 datasets, the medians of perfect match (PM) probe intensities increased in cancer state and the increases were significant in three datasets, suggesting the assumption that all arrays have the same median probe intensities regardless of the biological groups of samples might be misleading. Then, we evaluated the effects of three currently most widely used normalization algorithms (RMA, MAS5.0 and dChip) on the selection of DE genes by comparing them with LVS which relies less on the above-mentioned assumption. The results showed using RMA, MAS5.0 and dChip may produce lots of false results of down-regulated DE genes while missing many up-regulated DE genes. At least for cancer study, normalizing all arrays to have the same distribution of probe intensities regardless of the biological groups of samples might be misleading. Thus, most current normalizations based on unreliable assumptions may distort biological differences between normal and cancer samples. The LVS algorithm might perform relatively well due to that it relies less on the above-mentioned assumption. Also, our results indicate that genes may be widely up-regulated in most human cancer.

Epigenetic silencing of MAL, a putative tumor suppressor gene, can contribute to human epithelium cell carcinoma

BACKGROUND

To identify new and useful candidate biomarkers in head and neck squamous cell carcinoma (HNSCC), we performed a genome-wide survey and found that Myelin and lymphocyte-associated protein (MAL) was a gene that was markedly down-regulated in HNSCC. Hence, we investigated the mechanism of MAL silencing and the effects of MAL on the proliferation, invasion, and apoptotic potential in HNSCC.

RESULTS

MAL was significantly down-regulated in 91.7% of HNSCC specimens at the mRNA level as compared with adjacent normal tissues (P = 0.0004). Moreover, the relative transcript levels of the MAL gene were remarkably decreased by five-fold in nine HNSCC cell lines as compared with normal head and neck epithelium cells. MAL gene expression was restored in 44%, 67%, and 89% in HNSCC cell lines treated with TSA, 5-Aza-dC, and TSA plus 5-Aza-dC, respectively. Furthermore, bisulfate-treated DNA sequencing demonstrated that the two CpG islands (that is, M1 and M2) located in MAL promoter region were completely methylated in the HNSCC cell lines (CpG methylated ratio was more than 90%), and only one CpG island (that is, M1) was partially methylated in HNSCC tissues (CpG methylated ratio between 20% and 90%). A significant reduction in cell proliferation and a change in the cell cycle profile were also observed in MAL transfectants. Matrigel assay demonstrated that the invasiveness of HNSCC cells significantly decreased. A significant increase in the population of apoptotic cells was observed in MAL transfected cells. The exogenous expression of the MAL gene suppressed malignant phenotypes, while the cell death induced by MAL gene transfer was a result of apoptosis as demonstrated by the induction of cleavage of the poly (that is, ADP-ribose) polymerase. Additionally, tumor growth was suppressed in cells expressing MAL as compared with cells not expressing MAL.

CONCLUSION

Our data suggest that the epigenetic inactivation of MAL, as a candidate tumor suppressor gene, can contribute to human epithelial cell carcinoma and may be served as a biomarker in HNSCC.

Standards affecting the consistency of gene expression arrays in clinical applications

The use of microarray technology to measure gene expression has created optimism for the feasibility of using molecular assessments of tumors routinely in the clinical management of cancer. Gene expression arrays have been pioneers in the development of standards; both for research use and now for clinical application. Some of the existing standards have been driven by the early perception that microarray technology was inconsistent and perhaps unreliable. More recent experimentation has shown that reproducible data can be achieved and clinical standards are beginning to emerge. For the transcriptional assessment of tumors, this means a system that correctly samples a tumor, isolates RNA and processes this for microarray analysis, evaluates the data, and communicates findings in a consistent and timely fashion. The most important standard is to show that a clinically important assessment can be made with microarray data. The standards emerging from work on various parts of the entire process could guide the development of a workable system. However, the final standard for each component of the process depends on the accuracy required when the assay becomes part of the clinical routine: a routine that now includes the molecular evaluation of tumors.

3'-end sequencing for expression quantification (3SEQ) from archival tumor samples

Gene expression microarrays are the most widely used technique for genome-wide expression profiling. However, microarrays do not perform well on formalin fixed paraffin embedded tissue (FFPET). Consequently, microarrays cannot be effectively utilized to perform gene expression profiling on the vast majority of archival tumor samples. To address this limitation of gene expression microarrays, we designed a novel procedure (3′-end sequencing for expression quantification (3SEQ)) for gene expression profiling from FFPET using next-generation sequencing. We performed gene expression profiling by 3SEQ and microarray on both frozen tissue and FFPET from two soft tissue tumors (desmoid type fibromatosis (DTF) and solitary fibrous tumor (SFT)) (total n = 23 samples, which were each profiled by at least one of the four platform-tissue preparation combinations). Analysis of 3SEQ data revealed many genes differentially expressed between the tumor types (FDR<0.01) on both the frozen tissue (∼9.6K genes) and FFPET (∼8.1K genes). Analysis of microarray data from frozen tissue revealed fewer differentially expressed genes (∼4.64K), and analysis of microarray data on FFPET revealed very few (69) differentially expressed genes. Functional gene set analysis of 3SEQ data from both frozen tissue and FFPET identified biological pathways known to be important in DTF and SFT pathogenesis and suggested several additional candidate oncogenic pathways in these tumors. These findings demonstrate that 3SEQ is an effective technique for gene expression profiling from archival tumor samples and may facilitate significant advances in translational cancer research.

Natural products as inhibitors of carcinogenesis

BACKGROUND

Although carcinogenesis and cancer have been studied intensively for > 50 years, the rates of cancer incidence and mortality remain high. The most successful approach for reducing these rates has been primary prevention. For individuals at a high risk of developing cancer owing to certain genetic, environmental and occupational factors, cancer chemoprevention is a logical approach.

OBJECTIVE

This review discusses natural products as inhibitors of carcinogenesis.

CONCLUSION

Natural product chemopreventive agents are inherently biologically active and have been demonstrated to prevent and reverse the carcinogenic process in a pleiotropic manner. Derivatives of compounds discovered by screening natural products for chemopreventive agents have shown efficacy in clinical trials. Despite the obstacles that must be overcome before chemopreventive drugs become an integral component of standard medical practice for cancer prophylaxis, there is vast potential for significant improvement in cancer morbidity and mortality through the use of natural product chemopreventive drugs.

Drug metabolism by tumours: its nature, relevance and therapeutic implications

Drug-metabolising enzymes (DMEs) are present in tumours and are capable of biotransforming a variety of antineoplastics. Tumoural drug metabolism is both a potential mechanism of resistance and a means of achieving optimal therapy. This review addresses the classes of DMEs, their cytotoxic substrates and distribution in specific malignancies. The limitations of preclinical and clinical studies are highlighted. Their role in predicting therapeutic response, the activation of prodrugs and the potential for their modulation for gain is also addressed. The contribution of tumoural DMEs to cancer therapy can only be ascertained through large prospective studies and supported by new technologies. Only then can efforts be concentrated in the design of better prodrugs or combination therapy to optimise individual therapy.

Multiple biomarkers improve prediction of bladder cancer recurrence and mortality in patients undergoing cystectomy

BACKGROUND

Tested was whether the assessment of 5 established bladder cancer biomarkers (p53, pRB, p21, p27, and cyclin E1) could improve the ability to predict disease recurrence and cancer-specific survival after radical cystectomy in patients with pTa-3N0M0 urothelial carcinoma of the bladder (UCB).

METHODS

The study comprised 191 patients with pTa-3N0M0 UCB treated with radical cystectomy and bilateral lymphadenectomy (median follow-up, 3.1 years). Biomarker expression was assayed on serial tissue microarray slides using quantitative immunohistochemistry using advanced cell imaging and color detection software. Predictive accuracy was quantified using the concordance index and 200-bootstrap resamples were used to reduce overfit bias. Bootstrap-adjusted predictive accuracy estimates were compared using the Mantel-Haenszel test.

RESULTS

UCB recurred in 36 (18.8%) patients and 30 (15.7%) died of bladder cancer; 157 (82.2%) patients had altered expression of at least 1 biomarker. In univariate analyses the number of altered biomarkers had the highest predictive accuracy for both disease recurrence (76.8%, P< .001) and cancer-specific mortality (78.3%, P< .001). Addition of the number of altered biomarkers increased the predictive accuracy of nomograms based on the TNM staging system for disease recurrence and cancer-specific mortality by 10.9% (83.4% vs 72.5%, P< .001) and 8.6% (86.9% vs 78.3, P< .001), respectively.

CONCLUSIONS

Assessment of the number of altered biomarkers in the cystectomy specimen improves the prediction of bladder cancer recurrence and survival in patients with pTa-3N0M0 disease. Prospective evaluation of alteration in these biomarkers can help identify patients who would benefit from adjuvant treatment after radical cystectomy.

ImmunoCell-Array: a novel technology for pathway discovery and cell profiling

A major challenge in drug discovery is the definition of the activity of therapeutic compounds before they enter clinical trials. Currently, many tools are available to profile drug response at a multiparametric level. Furthermore, the novel discipline of systems biology is offering interpretative cues to the amount of data generated by the so-called omics technologies. Nonetheless, novel approaches are needed to comprehensively evaluate drug response. This review will describe a recent technology for protein profiling, the ImmunoCell-Array, which, in to the authors' opinion, can enter the scenario of profiling technologies with the goal of offering a comprehensive description of proteome dynamics in a cellular context.

Dissecting the molecular mechanisms of cancer through bioinformatics-based experimental approaches

Cancer is a disease of aberrant gene expression characterized by inappropriate (temporal or quantitative) expression of positive mediators of cell proliferation in conjunction with diminished expression of negative mediators of cell growth. Alteration of the normal balance of these positive and negative mediators leads to the abnormal growth of cells and tissues that typify neoplastic disease. Development of a better understanding of the genetic and epigenetic mechanisms that induce neoplastic transformation and drive the cancer phenotype is essential for continued progress towards the design of practical molecular diagnostics and effective treatment strategies. Over the past decades, molecular techniques that facilitate the assessment of gene expression, identification of gene mutations, and characterization of chromosome abnormalities (numeric and structural) have been established and applied to cancer research. However, many of these techniques are slow and labor-intensive. More recently, high-throughput technologies have emerged that generate large volumes of data related to the genetics and epigenetics of cancer (or other disorders). These advances in molecular genetic technology required the development of sophisticated bioinformatic tools to manage the large datasets generated. The combination of high-throughput molecular assays and bioinformatic-based data mining strategies has significantly impacted our understanding of the molecular pathogenesis of cancer, classification of tumors, and now the management of cancer patients in the clinic. This article will review basic molecular techniques and bioinformatic-based experimental approaches used to dissect the molecular mechanisms of carcinogenesis.

Prognostic value of syndecan-1 expression in patients treated with radical prostatectomy

OBJECTIVE

To investigate the association of syndecan-1 expression with pathological features and disease progression in patients treated with radical prostatectomy (RP) as syndecan-1 plays a role in the regulation of cell proliferation, migration, and differentiation and its expression is altered in various malignancies.

PATIENTS AND METHODS

Syndecan-1 immunostaining was performed on a tissue microarray containing cores from 232 consecutive patients treated with RP and bilateral lymphadenectomy for clinically localized prostatic adenocarcinoma. Patients were categorized as having features of aggressive progression if they had evidence of metastases, an after progression prostate-specific antigen (PSA) doubling time of < 10 months, and/or failure to respond to local salvage radiation therapy. Expression was defined as > or = 10% cells staining for syndecan-1.

RESULTS

Syndecan-1 was expressed in 86 patients (37.1%). Expression of syndecan-1 was associated with higher PSA levels (P = 0.004), higher pathological Gleason sum (P = 0.027) and lymph nodes metastases (P = 0.027). Patients with syndecan-1 expression were at significantly greater risk of PSA-progression after surgery (P = 0.034) in univariate but not in multivariate analysis. Patients with features of aggressive progression (n = 22) were more likely to express syndecan-1 than those with features of nonaggressive progression (63.6% vs 36.4%, P = 0.010). Patients with syndecan-1 expression were at significantly greater risk of aggressive progression after surgery (P = 0.005) in univariate but not in multivariate analysis.

CONCLUSIONS

Expression of syndecan-1 was associated with established features of biologically aggressive prostate cancer and PSA-progression in univariate analysis. These findings suggest a role for syndecan-1 in prostate carcinogenesis and progression.

Molecular restoration of archived transcriptional profiles by complementary-template reverse-transcription (CT-RT)

Gene expression profiling of formalin-fixed and paraffin-embedded (FFPE) specimens, banked from completed clinical trials and routine clinical care, has the potential to yield valuable information implicating and linking genes with clinical parameters. In order to prepare high-quality cDNA from highly fragmented FFPE-RNA, previously precluded from high-throughput analyses, we have designed a novel strategy based on the nucleic acid restoration of incomplete cDNA sequences prior to T7 in vitro transcription (IVT) amplification. We describe this strategy as complementary-template reverse-transcription (CT-RT) because short single-stranded T7-oligo-dT₂₄-VN-DNA sequences, obtained from FFPE-RNA, are used as primers for the RT of complementary RNA templates contained in a sense-RNA library. We validated our assay by determining the correlation between expression profiles of a matched 10-year-old frozen and FFPE breast cancer sample. We show that T7 IVT-amplification of cDNA transcripts restored by CT-RT is a specific and reliable process that allows recovery of transcriptional features undetectable by direct T7 IVT-amplification of FFPE-RNA. Furthermore, CT-RT restored 35–41% of the transcripts from archived breast and cervical specimens when compared to matched frozen tissue; and profiles included tissue-specific transcripts. Our results indicate that CT-RT allows microarray profiling of severely degraded RNA that could not be analyzed by previous methods.

Dual mitogen-activated protein kinase and epidermal growth factor receptor inhibition in biliary and pancreatic cancer

This study aimed to develop rational combinations of targeted agents against biliary and pancreatic cancers. To this end, we compared the global gene expression profile of biliary cancer cell lines with different degrees of sensibility to the epidermal growth factor receptor tyrosine kinase inhibitors gefitinib and erlotinib using the Affymetrix U133A microarray platform. A set of 32 genes, including genes involved in signal transduction pathways, cell cycle regulation, and angiogenesis, was highly overexpressed in resistant cells. Five of these genes encoded proteins in the Ras/Raf/mitogen-activated protein kinase (MAPK) pathway, a finding that was confirmed by Western blot and immunohistochemistry. Gefitinib failed to inhibit the MAPK pathway in resistant cell lines. Based on these data, we explored the activity of dual treatment with gefitinib in combination with CI-1040, a MAPK inhibitor. This strategy effectively resulted in inhibition of the MAPK signaling pathway and exerted antitumor effects in vitro and in vivo in tumors resistant to each of the agents alone. To further confirm these results, we tested the combined treatment in four tumor xenografts generated from patients with resected pancreatic cancer. Combined treatment was more effective than either single agent alone in this model. This study illustrates the value of global analysis of gene expression to rationally design combinations of mechanistic-based drugs. In addition, the data support the efficacy of combined epidermal growth factor receptor and MAPK inhibitors in biliary and pancreatic cancers, providing the basis to test this combination in the clinic.

Differential RNA expression profile by cDNA microarray in sporadic primary hyperparathyroidism (pHPT): primary parathyroid hyperplasia versus adenoma

BACKGROUND

Differential diagnosis between adenoma and hyperplasia in primary hyperparathyroidism (pHPT) remains a dilemma. The aim of this study was to assess differences in transcriptional genomic expression profiles between sporadic (nonfamilial) parathyroid hyperplasia (SPH), adenoma, and normal tissue.

METHODS

Parathyroid tissue from 12 patients with parathyroid adenoma, 3 with SPH, and 2 with normal glands was selected for analysis. Histopathology was reviewed in all cases, and all patients with adenomas presented normocalcemia for a minimum of 6 months after one gland resection. Hybridizations were performed in a microarray containing 19,968 human cDNA clones including contiguous replicates. Direct comparisons were performed with reverse labeling for every different pooled sample entity. Expression levels were analyzed using the SAM, SMA, LIMMA, Cluster, and PAM packages in the R environment for statistical computing.

RESULTS

There were significant statistical differences between SPH and adenomas. In the direct comparison, a total of 200 genes showed differential expression (P < 0.03): 61 genes were upregulated (> 1.65-fold increase) and 139 were downregulated (> 1.58-fold decrease) with a B value > 4.68 (99.08% probability of real differential expression). When SPH was compared to normal parathyroid tissue, 50 genes were differentially expressed: 42 were upregulated (> 1.89) and 8 were downregulated (> 1.7) with a B > 4.26 (98.6% probability of real differential expression). At least 17 genes were differentially expressed and able to discriminate SPH from adenoma or normal tissue. Upregulated genes were related to apoptosis inhibition, cell proliferation, transcriptional activity and cell adhesion, among other activities. Downregulated genes were mainly related to ion channel activity, lipopolysaccharides, prostaglandin-d synthase, and integral membrane proteins.

CONCLUSIONS

Our data suggest that SPH and adenoma have a singular molecular signature that, theoretically, could be used for the differential diagnosis of these entities and normal parathyroid tissue.

Analysis of orthologous gene expression between human pulmonary adenocarcinoma and a carcinogen-induced murine model

Human adenocarcinoma (AC) is the most frequently diagnosed human lung cancer, and its absolute incidence is increasing dramatically. Compared to human lung AC, the A/J mouse-urethane model exhibits similar histological appearance and molecular changes. We examined the gene expression profiles of human and murine lung tissues (normal or AC) and compared the two species' datasets after aligning approximately 7500 orthologous genes. A list of 409 gene classifiers (P value <0.0001), common to both species (joint classifiers), showed significant, positive correlation in expression levels between the two species. A number of previously reported expression changes were recapitulated in both species, such as changes in glycolytic enzymes and cell-cycle proteins. Unexpectedly, joint classifiers in angiogenesis were uniformly down-regulated in tumor tissues. The eicosanoid pathway enzymes prostacyclin synthase (PGIS) and inducible prostaglandin E(2) synthase (PGES) were joint classifiers that showed opposite effects in lung AC (PGIS down-regulated; PGES up-regulated). Finally, tissue microarrays identified the same protein expression pattern for PGIS and PGES in 108 different non-small cell lung cancer biopsies, and the detection of PGIS had statistically significant prognostic value in patient survival. Thus, the A/J mouse-urethane model reflects significant molecular details of human lung AC, and comparison of changes in orthologous gene expression may provide novel insights into lung carcinogenesis.

Proteomics in cancer research: Methods and application of array-based protein profiling technologies

With the human genome sequence now determined, the field of molecular medicine is moving beyond genomics to proteomics, the large-scale analysis of proteins. It is now possible to examine the expression of more than 1000 proteins using mass spectrometry technology coupled with various separation methods. Microarray technology is a new and efficient approach, for extracting relevant biomedical data and has a wide range of applications. It provides a versatile tool to study protein-protein, protein-nucleic acid, protein-lipid, enzyme-substrate and protein-drug interactions. This review paper will explore the key themes in proteomics and their application in clinical cancer research.

Molecular neuro-oncology and the development of targeted therapeutic strategies for brain tumors. Part 5: apoptosis and cell cycle

Brain tumors are a diverse group of malignancies that remain refractory to conventional treatment approaches. Molecular neuro-oncology has now begun to clarify the transformed phenotype of brain tumors and identify oncogenic pathways that might be amenable to targeted therapy. Abnormalities of the apoptotic and cell cycle signaling pathways are key molecular features of many brain tumors and are currently under evaluation for potential therapeutic intervention. The apoptosis pathway has numerous targets for molecular therapeutic development, including p53, Bax, Bcl-2, cFLIP, effector caspases, growth factor receptors, phosphatidylinositol-3-kinase, Akt and apoptosis inhibitors. Current molecular treatment approaches include antisense techniques, gene therapy and small-molecule modulators and inhibitors. Potential targets of the cell cycle pathway include the cyclins, cyclin-dependent kinases, p53, retinoblastoma, E2F and the cyclin-dependent kinase inhibitors. Developmental molecular therapeutics for this pathway include adenoviral and gene therapy, small-peptide cyclin-dependent kinase modulators, proteasomal inhibitors and small-molecule cyclin-dependent kinase inhibitors. Several of these recently identified agents have begun evaluation in clinical trials. Further development of targeted therapies designed to modulate apoptosis and the cell cycle, and evaluation of these new agents in clinical trials, will be needed to improve survival and quality of life for patients with brain tumors.

The clinical use of tumor makers in select cancers: are you confident enough to discuss them with your patients?

PURPOSE/OBJECTIVES

To review the clinical use of tumor markers in select cancers and highlight future directions in tumor marker development.

DATA SOURCES

Guidelines from national and international societies, scientific literature, and Internet resources.

DATA SYNTHESIS

Tumor markers are important tools in the management of cancer. Sequencing of the human genome has led to new tumor marker development in the fields of proteomics and DNA microarray technologies.

CONCLUSIONS

Tumor marker technology is expanding rapidly; almost a dozen tumor markers currently are being used in the oncology arena, with many more in development. The use of tumor markers can be controversial, particularly because guidelines have not been established for all of the markers.

IMPLICATIONS FOR NURSING

Oncology nurses need to be well versed in the use of tumor markers to educate and counsel patients with cancer.

Chaotic mixer improves microarray hybridization

Hybridization is an important aspect of microarray experimental design which influences array signal levels and the repeatability of data within an array and across different arrays. Current methods typically require 24h and use target inefficiently. In these studies, we compare hybridization signals obtained in conventional static hybridization, which depends on diffusional target delivery, with signals obtained in a dynamic hybridization chamber, which employs a fluid mixer based on chaotic advection theory to deliver targets across a conventional glass slide array. Microarrays were printed with a pattern of 102 identical probe spots containing a 65-mer oligonucleotide capture probe. Hybridization of a 725-bp fluorescently labeled target was used to measure average target hybridization levels, local signal-to-noise ratios, and array hybridization uniformity. Dynamic hybridization for 1h with 1 or 10ng of target DNA increased hybridization signal intensities approximately threefold over a 24-h static hybridization. Similarly, a 10- or 60-min dynamic hybridization of 10ng of target DNA increased hybridization signal intensities fourfold over a 24h static hybridization. In time course studies, static hybridization reached a maximum within 8 to 12h using either 1 or 10ng of target. In time course studies using the dynamic hybridization chamber, hybridization using 1ng of target increased to a maximum at 4h and that using 10ng of target did not vary over the time points tested. In comparison to static hybridization, dynamic hybridization reduced the signal-to-noise ratios threefold and reduced spot-to-spot variation twofold. Therefore, we conclude that dynamic hybridization based on a chaotic mixer design improves both the speed of hybridization and the maximum level of hybridization while increasing signal-to-noise ratios and reducing spot-to-spot variation.

DNA microarrays: from structural genomics to functional genomics. The applications of gene chips in dermatology and dermatopathology

The human genome project was successful in sequencing the entire human genome and ended earlier than expected. The vast genetic information now available will have far-reaching consequences for medicine in the twenty-first century. The knowledge gained from the mapping and sequencing of human genes on a genome-wide scale--commonly referred to as structural genomics--is prerequisite for studies that focus on the functional aspects of genes. A recently invented technique, known as gene chip, or DNA microarray, technology, allows the study of the function of thousands of genes at once, thereby opening the door to the new field of functional genomics. At its core, the DNA microarray utilizes a unique feature of DNA known as complementary hybridization. As such, it is not different from Southern (DNA) blot or northern (RNA) blot hybridizations, or the polymerase chain reaction, with the exception that it allows expression profiling of the entire human genome in a single hybridization experiment. The article highlights the principles, technology, and applications of DNA microarrays as they pertain to the field of dermatology and dermatopathology. The most important applications are the gene expression profiling of skin cancer, especially of melanoma. Other potential applications include gene expression profiling of inflammatory skin diseases, the mutational analysis of genodermatoses, and polymorphism screening, as well as drug development and chemosensitivity prediction. cDNA microarrays will shape the diagnostic approach of the dermatology and the dermatopathology of the future and may lead to new therapeutic options.

Casodex treatment induces hypoxia-related gene expression in the LNCaP prostate cancer progression model

Background

The changes in gene expression profile as prostate cancer progresses from an androgen-dependent disease to an androgen-independent disease are still largely unknown.

Methods

We examined the gene expression profile in the LNCaP prostate cancer progression model during chronic treatment with Casodex using cDNA microarrays consisting of 2305 randomly chosen genes.

Results

Our studies revealed a representative collection of genes whose expression was differentially regulated in LNCaP cells upon treatment with Casodex. A set of 15 genes were shown to be highly expressed in Casodex-treated LNCaP cells compared to the reference sample. This set of highly expressed genes represents a signature collection unique to prostate cancer since their expression was significantly greater than that of the collective pool of ten cancer cell lines of the reference sample. The highly expressed signature collection included the hypoxia-related genes membrane metallo-endopeptidase (MME), cyclin G2, and Bcl2/adenovirus E1B 19 kDa (BNIP3). Given the roles of these genes in angiogenesis, cell cycle regulation, and apoptosis, we further analyzed their expression and concluded that these genes may be involved in the molecular changes that lead to androgen-independence in prostate cancer.

Conclusion

Our data indicate that one of the mechanisms of Casodex action in prostate cancer cells is induction of hypoxic gene expression.

Validating the prognostic value of marker genes derived from a non-small cell lung cancer microarray study

We previously reported that our cDNA microarray analysis of primary non-small cell lung carcinoma (NSCLC) could predict for patients at increased risk of cancer recurrence. From the result of this analysis, we selected 11 genes that were considered candidate prognostic marker genes and used the realtime reverse transcription polymerase chain reaction (RT-PCR) to investigate their expression in the same set of NSCLC cases used in the microarray study. Cluster analysis of the realtime RT-PCR data separated these patients into two groups with significantly different disease-free survivals (log-rank test, P < 0.017). In contrast, cluster analysis failed to confirm the prognostic significance of the realtime RT-PCR results for these 11 genes in a validation series of 92 NSCLC cases. In univariate analysis, hypoxia inducible factor 1alpha, Rho-GDP dissociation inhibitor (GDI) alpha (RhoGDI) and Citron/rho-interacting serine-threonine kinase 21 (Citron K21) were significant prognostic factors for disease-free survival in the entire cohort of 130 NSCLC patients, but none were significant in multivariate analysis. The results demonstrate that the prognostic significance of microarray (SAM) results can be partially validated using realtime RT-PCR, but secondary validation using larger and independent series of tumors is necessary to identify true prognostic marker genes.

Molecular profiling of hepatocellular carcinomas by cDNA microarray

Hepatocellular carcinoma (HCC) is one of the most common cancers in the world. Conventional diagnosis and treatment of this malignancy have been dismal and should be complemented by novel tools. The development and progress of HCC are believed to be caused by the accumulation of genetic changes resulting in altered expression of thousands of cancer-related genes, which can be measured by globe genetic analysis. Gene expression profiling of HCC has been employed to elucidate hepatocarcinogenesis and disclose molecular mechanisms underlying complex clinical features. Identifying phenotype-associated genes/profiles has impacts on current diagnosis and management strategy of HCC. In spite of some pitfalls of this technology and challenges in improving the research process, scrutinous validation of profiling data of HCC combined with other approaches will eventually benefit the patients.