Discovery of prostate cancer biomarkers by microarray gene expression profiling

Advance computational tools for multiomics data learning

The burgeoning field of bioinformatics has seen a surge in computational tools tailored for omics data analysis driven by the heterogeneous and high-dimensional nature of omics data. In biomedical and plant science research multi-omics data has become pivotal for predictive analytics in the era of big data necessitating sophisticated computational methodologies. This review explores a diverse array of computational approaches which play crucial role in processing, normalizing, integrating, and analyzing omics data. Notable methods such similarity-based methods, network-based approaches, correlation-based methods, Bayesian methods, fusion-based methods and multivariate techniques among others are discussed in detail, each offering unique functionalities to address the complexities of multi-omics data. Furthermore, this review underscores the significance of computational tools in advancing our understanding of data and their transformative impact on research.

Loss of miR-936 leads to acquisition of androgen-independent metastatic phenotype in prostate cancer

Prostate cancer (PCa) progresses from a hormone-sensitive, androgen-dependent to a hormone-refractory, androgen-independent metastatic phenotype. Among the many genes implicated, ANXA2, a calcium-dependent phospholipid binding protein, has been found to have a critical role in the progression of PCa into more invasive metastatic phenotype. However, the molecular mechanisms underlying the absence of ANXA2 in early PCa and its recurrence in advanced stage are yet unknown. Moreover, recent studies have observed the deregulation of microRNAs (miRNAs) are involved in the development and progression of PCa. In this study, we found the down-regulation of miR-936 in metastatic PCa wherein its target ANXA2 was overexpressed. Subsequently, it has been shown that the downregulation of miRNA biogenesis by siRNA treatment in ANXA2-null LNCaP cells could induce the expression of ANXA2, indicating the miRNA mediated regulation of ANXA2 expression. Additionally, we demonstrate that miR-936 regulates ANXA2 expression by direct interaction at coding as well as 3'UTR region of ANXA2 mRNA by luciferase reporter assay. Furthermore, the overexpression of miR-936 suppresses the cell proliferation, cell cycle progression, cell migration, and invasion abilities of metastatic PCa PC-3 cells in vitro and tumor forming ability in vivo. These results indicate that miR-936 have tumor suppressor properties by regulating the over expression of ANXA2 in hormone-independent metastatic PCa. Moreover, our results suggest that this tumor suppressor miR-936 could be developed as a targeted therapeutic molecule for metastatic PCa control and to improve the prognosis in PCa patients.

EZH2 Mediates Proliferation, Migration, and Invasion Promoted by Estradiol in Human Glioblastoma Cells

Glioblastomas (GBM) are the most frequent and aggressive brain tumors. 17β-estradiol (E2) increases proliferation, migration, and invasion of human GBM cells; however underlying mechanisms are no fully understood. Zeste 2 Enhancer Homologous enzyme (EZH2) is a methyltransferase part of Polycomb 2 repressor complex (PRC2). In GBM, EZH2 is overexpressed and involved in the cell cycle, migration, and invasion processes. We studied the role of EZH2 in the pro-oncogenic actions of E2 in human GBM cells. EZH2 gene silencing and pharmacological inhibition of EZH2 blocked proliferation, migration, and invasion of GBM cells induced by E2. We identified in silico additional putative estrogen response elements (EREs) at the EZH2 promoter, but E2 did not modify EZH2 expression. In silico analysis also revealed that among human GBM samples, EZH2 expression was homogeneous; in contrast, the heterogeneous expression of estrogen receptors (ERs) allowed the classification of the samples into groups. Even in the GBM cluster with high expression of ERs and those of their target genes, the expression of PCR2 target genes did not change. Overall, our data suggest that in GBM cells, pro-oncogenic actions of E2 are mediated by EZH2, without changes in EZH2 expression and by mechanisms that appear to be unrelated to the transcriptional activity of ERs.

MicroRNA In Situ Hybridization in Paraffin-Embedded Cultured Cells

MicroRNA-21 (miR-21) is one of the most abundant microRNAs in cancer tissues and is considered a strong prognostic biomarker. In situ hybridization (ISH) analyses using locked nucleic acid (LNA) probes have shown that miR-21 is expressed in stromal fibroblastic cells and in subsets of cancer cells. Image analysis of the miR-21 ISH signal has shown that increased expression estimate is associated with poor prognosis in colon cancer. However, assessment of the ISH signal by image analysis to obtain quantitative estimates has been done in retrospective studies without normalization of the expression estimates to reference parameters. The ISH signal output is sensitive to several experimental parameters, including hybridization temperature, probe concentration, and pretreatment, and therefore improved standardized procedures are warranted. We considered the use of paraffin-embedded cultured cells (PECCs) as reference standards that potentially can accompany staining of clinical cancer samples. We found that the cancer cell lines HT-29, CACO-2, and HeLa cells express miR-21 when measured by ISH, and used those cell lines to obtain PECCs. In this methods chapter we present a fixation and embedding procedure to obtain PECCs suitable for microRNA ISH and a double-fluorescence protocol to stain microRNAs together with protein markers in the PECCs.

A modern era of personalized medicine in the diagnosis, prognosis, and treatment of prostate cancer

The present era is witnessing rapid advancements in the field of medical informatics and modern healthcare management. The role of translational bioinformatics (TBI), an infant discipline in the field of medical informatics, is pivotal in this revolution. The development of high-throughput technologies [e.g., microarrays, next-generation sequencing (NGS)] has propelled TBI to the next stage in this modern era of medical informatics. In this review, we assess the promising translational outcomes of microarray- and NGS-based discovery of genes, proteins, micro RNAs, and other active biological compounds aiding in the diagnosis, prognosis, and therapy of prostate cancer (PCa) to improve treatment strategies at the localized and/or metastatic stages in patients. Several promising candidate biomarkers in circulating blood (miR-25-3p and miR-18b-5p), urine (miR-95, miR-21, miR-19a, and miR-19b), and prostatic secretions (miR-203) have been identified. AURKA and MYCN, novel candidate biomarkers, were found to be specifically expressed in neuroendocrine PCa. The use of BTNL2 gene mutations and inflammasomes as biomarkers in immune function-mediated, inherited PCa has also been elucidated based on NGS data. Although TBI discoveries can benefit clinical performance metrics, the translational potential and the in vivo performance of TBI outcomes need to be verified. In conclusion, TBI aids in the effective clinical management of PCa; furthermore, the fate of personalized/precision medicine mostly relies on the enhanced diagnostic, prognostic, and therapeutic potential of TBI.

Serum Metabolomics of Early Postoperative Cognitive Dysfunction in Elderly Patients Using Liquid Chromatography and Q-TOF Mass Spectrometry

Postoperative cognitive dysfunction (POCD) is a common postoperative complication observed in elderly patients. However, the diagnosis of POCD is not very satisfactory as no specific biomarkers have been classified. It is necessary to identify new diagnostic markers to better understand the pathogenesis of POCD. We performed liquid chromatography with a time-of-flight mass spectrometer- (LC/Q-TOF-MS-) based metabolomics study to investigate POCD. A total of 40 metabolites were differentially expressed between POCD and non-POCD patients. In this study, we investigated whether phosphatidylserine (PS) (17:2/0:0), with an area under the curve value of 0.966, was a potential sensitive and specific biomarker for the diagnosis and prognosis of POCD. Pathway analysis showed that fatty acid metabolism, lipid metabolism, and carnitine metabolism were significantly altered in POCD. Network analysis indicated that nitric oxide signaling, PI3K-AKT signaling, mTOR signaling, and mitochondrial dysfunction were related to the pathogenesis of POCD. This study showed that metabolic profiling was meaningful when studying the diagnosis and pathogenesis of POCD.

Combined MicroRNA In Situ Hybridization and Immunohistochemical Detection of Protein Markers

MicroRNAs are short (18-23 nucleotides) noncoding RNAs involved in posttranscriptional regulation of gene expression through their specific binding to the 3'UTR of mRNAs. MicroRNAs can be detected in tissues using specific locked nucleic acid (LNA)-enhanced probes. The characterization of microRNA expression in tissues by in situ detection is often crucial following a microRNA biomarker discovery phase in order to validate the candidate microRNA biomarker and allow better interpretation of its molecular functions and derived cellular interactions. The in situ hybridization data provides information about contextual distribution and cellular origin of the microRNA. By combining microRNA in situ hybridization with immunohistochemical staining of protein markers, it is possible to precisely characterize the microRNA-expressing cells and to identify the potential microRNA targets. This combined technology can also help to monitor changes in the level of potential microRNA targets in a therapeutic setting. In this chapter, we present a fluorescence-based detection method that allows the combination of microRNA in situ hybridization with immunohistochemical staining of one and, in this updated version of the paper, two protein markers detected with primary antibodies raised in the same host species.

Gene-expression analysis of gleason grade 3 tumor glands embedded in low- and high-risk prostate cancer

The Gleason score (GS) of prostate cancer on diagnostic biopsies is an important parameter for therapeutic decision-making. Biopsy GS under-estimates the actual GS at radical prostatectomy in a significant number of patients due to sampling artifact. The aim of this study was to identify markers that are differentially expressed in Gleason grade 3 (GG3) tumor glands embedded in GS 4 + 3 = 7 and GS 3 + 3 = 6 prostate cancer using laser capture microdissection and RNA sequencing.

GG3 tumor glands embedded in nine GS 3 + 3 = 6 and nine GS 4 + 3 = 7 prostate cancers were isolated by laser capture microdissection of frozen radical prostatectomy specimens. After RNA amplification and RNA sequencing, differentially expressed genes in both GG3 components were identified by a 2log fold change > 1.0 and p-value < 0.05. We applied immunohistochemistry on a tissue micro-array representing 481 radical prostatectomy samples for further validation on protein level.

A total of 501 genes were up-regulated and 421 down-regulated in GG3 glands embedded in GS 4 + 3 = 7 as compared to GS 3 + 3 = 6 prostate cancer. We selected HELLS, ZIC2 and ZIC5 genes for further validation. ZIC5 mRNA was up-regulated 17 fold (p = 8.4E–07), ZIC2 8 fold (p = 1.3E–05) and HELLS 2 fold (p = 0.006) in GG3 glands derived from GS 4 + 3 = 7. HELLS expression of ≥ 1% occurred in 10% GS < 7, 17% GS 7 and 43% GS >7 prostate cancer (p < 0.001). Using a cut-off of ≥ 1%, protein expression of ZIC5 was present in 28% GS < 7, 43% GS 7 and 57% GS > 7 cancer (p < 0.001). ZIC2 was neither associated with GS nor outcome in our validation set. HELLS was independently predictive for biochemical-recurrence after radical prostatectomy (HR 2.3; CI 1.5–3.6; p < 0.01).

In conclusion, HELLS and ZIC5 might be promising candidate markers for selection of biopsy GS 6 prostate cancer being at risk for up-grading at prostatectomy.

Construction of an initial microRNA regulation network in breast invasive carcinoma by bioinformatics analysis

INTRODUCTION

microRNAs (miRNA) are involved in many biological processes. They repress target gene expression and play a vital role in breast invasive carcinoma (BRCA). Although many miRNAs are identified to be aberrantly expressed in BRCA and deemed as tumor markers, only sporadic individual studies report their target genes and the pathways involved.

METHODS

miRNA and mRNA expression data were collected from the Cancer Genome Atlas (TCGA) pilot project. Aberrantly expressed miRNAs and mRNAs in BRCA were identified by comparing tumor samples with normal adjacent tissues. Differentially expressed miRNAs and mRNAs in different breast cancer subtypes were also analyzed. miRNA/target correlations were predicted by calculating the spearman correlation coefficients between miRNA and mRNA, and validated by luciferase assay.

RESULTS

31 up-regulated miRNAs, 37 down-regulated miRNAs, 1105 up-regulated mRNAs and 1222 down-regulated mRNAs were identified in BRCA; 125 miRNA/target correlations were predicted, 6 of them were validated. In addition, we also found 9 miRNAs and 143 mRNAs differently expressed between estrogen receptor positive and negative breast cancers, and 4 miRNAs and 46 mRNAs differently expressed between progesterone receptor positive and negative breast cancers. Twelve miRNA/target correlations determined the breast cancer subtypes.

CONCLUSION

We developed a new systematic analytic method for analyzing TCGA database, which took into account both miRNA and mRNA data to dissect the miRNA regulation network in BRCA.

PINCAGE: probabilistic integration of cancer genomics data for perturbed gene identification and sample classification

MOTIVATION

Cancer development and progression is driven by a complex pattern of genomic and epigenomic perturbations. Both types of perturbations can affect gene expression levels and disease outcome. Integrative analysis of cancer genomics data may therefore improve detection of perturbed genes and prediction of disease state. As different data types are usually dependent, analysis based on independence assumptions will make inefficient use of the data and potentially lead to false conclusions.

MODEL

Here, we present PINCAGE (Probabilistic INtegration of CAncer GEnomics data), a method that uses probabilistic integration of cancer genomics data for combined evaluation of RNA-seq gene expression and 450k array DNA methylation measurements of promoters as well as gene bodies. It models the dependence between expression and methylation using modular graphical models, which also allows future inclusion of additional data types.

RESULTS

We apply our approach to a Breast Invasive Carcinoma dataset from The Cancer Genome Atlas consortium, which includes 82 adjacent normal and 730 cancer samples. We identify new biomarker candidates of breast cancer development (PTF1A, RABIF, RAG1AP1, TIMM17A, LOC148145) and progression (SERPINE3, ZNF706). PINCAGE discriminates better between normal and tumour tissue and between progressing and non-progressing tumours in comparison with established methods that assume independence between tested data types, especially when using evidence from multiple genes. Our method can be applied to any type of cancer or, more generally, to any genomic disease for which sufficient amount of molecular data is available.

AVAILABILITY AND IMPLEMENTATION

R scripts available at http://moma.ki.au.dk/prj/pincage/

CONTACT

: michal.switnicki@clin.au.dk or jakob.skou@clin.au.dk

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

MiR-141 Inhibits Gastric Cancer Proliferation by Interacting with Long Noncoding RNA MEG3 and Down-Regulating E2F3 Expression

BACKGROUND

MiR-141 and long noncoding RNA MEG3 have been independently reported to be tumor suppressor genes in various cancers. However, their expression has never been previously associated with gastric cancer (GC).

AIMS

To investigate the interaction of miR-141 and MEG3 in GC.

METHODS

QRT-PCR was used to detect miR-141, MEG3, and E2F3 in gastric tissues and cells. CCK-8 and flow cytometry analysis were used to detect cell functions. Western blot and luciferase activity were used to identify E2F3 as one of the direct targets of miR-141.

RESULTS

We found that expression of both miR-141 and MEG3 was significantly reduced in GC compared with levels in matched nonmalignant tissues. Positive correlation between miR-141 and MEG3 was found in both tumor tissues and control tissues. Furthermore, the over-expression of either miR-141 or MEG3 in 7901 and MKN45 cells inhibited cell proliferation and cell cycle progression and promoted cell apoptosis. E2F3 was identified as a target of miR-141, and its inhibition significantly reduced MEG3 expression. E2F3 expression was also found to be negatively associated with both MEG3 and miR-141. E2F3 over-expression partly reversed the changes caused by transfection of miR-141 mimic, and inhibition of miR-141 or MEG3 overrides MEG3- or miR-141-induced modulation of cell growth in GC.

CONCLUSIONS

These findings together suggested that miR-141 could be interacting with MEG3 and targeting E2F3, and these factors may play important anti-tumor effects in GC pathogenesis and provide therapeutic targets in the clinics.

Impact of a Genomic Classifier of Metastatic Risk on Postprostatectomy Treatment Recommendations by Radiation Oncologists and Urologists

OBJECTIVE

To evaluate how a genomic classifier (GC) that predicts the risk of metastasis after prostatectomy would impact adjuvant treatment recommendations made by radiation oncologists and urologists. The 2 specialties often disagree about postprostatectomy adjuvant treatment recommendations.

MATERIALS AND METHODS

Twenty-six radiation oncologists and 20 urologists with genitourinary oncology expertise reviewed de-identified clinical results from 11 patients after radical prostatectomy and made adjuvant treatment recommendations. The same cases were later randomized and reassigned, and treatment recommendations were made using the clinical information and GC test results together.

RESULTS

Using clinical information alone, observation was recommended in 42% of decisions made by urologists vs 23% by radiation oncologists (P < .0001). The GC test results altered 35% and 45% of treatment recommendations made by radiation oncologists and urologists, respectively. Multivariate analysis showed GC risk was the strongest factor influencing treatment recommendations by both specialties, with an adjusted odds ratio of 4.17 (95% confidence interval [CI], 2.26-7.70) and 6.51 (95% CI, 4.29-9.88) for radiation oncologists and urologists, respectively. GC results indicating high metastatic risk resulted in intensification of treatment, whereas low metastatic risk resulted in less aggressive recommendations. The GC results increased interdisciplinary agreement in treatment recommendations, as the odds of a recommendation for adjuvant treatment by urologists vs radiation oncologists increased from 0.27 (95% CI, 0.17-0.44) to 0.46 (95% CI, 0.29-0.75) after results of the GC test were available.

CONCLUSION

The GC test significantly influenced adjuvant postprostatectomy treatment recommendations, reduced disagreement between radiation oncologists and urologists, and has the potential to enhance personalization of postprostatectomy care.

Biomarkers of postoperative delirium and cognitive dysfunction

Elderly surgical patients frequently experience postoperative delirium (POD) and the subsequent development of postoperative cognitive dysfunction (POCD). Clinical features include deterioration in cognition, disturbance in attention and reduced awareness of the environment and result in higher morbidity, mortality and greater utilization of social financial assistance. The aging Western societies can expect an increase in the incidence of POD and POCD. The underlying pathophysiological mechanisms have been studied on the molecular level albeit with unsatisfying small research efforts given their societal burden. Here, we review the known physiological and immunological changes and genetic risk factors, identify candidates for further studies and integrate the information into a draft network for exploration on a systems level. The pathogenesis of these postoperative cognitive impairments is multifactorial; application of integrated systems biology has the potential to reconstruct the underlying network of molecular mechanisms and help in the identification of prognostic and diagnostic biomarkers.

Identifications of genetic differences between metastatic and non-metastatic osteosarcoma samples based on bioinformatics analysis

To investigate the differences in gene expression level between metastatic and non-metastatic osteosarcoma (OS) samples and the potential mechanism. Gene expression profile data GSE9508 were downloaded from Gene Expression Omnibus database to identify the differentially expressed genes (DEGs) between metastatic, non-metastatic OS samples, and normal control samples via SAM method. Function expression matrix of the DEGs was constructed by calculating the functional node scores based on the genes sets collected from the pathways recorded in MsigDB database. Next, t test was applied to screen the differentially expressed functional nodes between each two kinds of samples. Finally, we compared the significant genes between selected DEGs and genes in differentially expressed functional nodes. There were 79 up-regulated DEGs between non-metastatic OS and normal samples, 380 up-regulated and 134 down-regulated DEGs between the metastatic OS and normal samples, and 761 up-regulated plus 186 down-regulated DEGs between metastatic and non-metastatic OS samples. A total of 3846 functional gene sets were collected to form the function expression profile matrix. The numbers of differentially expressed functional nodes between non-metastatic OS and normal samples, metastatic OS and normal samples, and metastatic and non-metastatic OS samples were 8, 39, and 5, respectively. The gene level difference between metastatic and non-metastatic OS samples can be distinguished using bioinformatics analysis. TGFB1, LFT3, KDM1A, and KRAS genes have the potential to be used as biomarkers for OS; however, further analysis is needed to verify the current results.

Clinically relevant genetic characterization of prostate tumors: how close are we to the goal?

Substantial efforts are being made in research on the molecular genetic characterization of prostate cancer. The number of fundamental research programs in prostate cancer molecular biology and genetics is overwhelming. However, a significant gap appears to exist between the huge number of studies on the genetic characterization of prostate cancer, which often have limited translation into clinical practice or simply were not conceived to be so translated, and clinical practice. From a clinical point of view, this balance should be urgently shifted towards rapid translation into urological practice. However, prostate cancer is characterized by prominent genetic heterogeneity, which could be a very difficult barrier to overcome. In this review, we discuss the possible clinical applications of scientific data from fundamental studies of prostate cancer genetics, the main problems with the translation of these data to clinics, and future perspectives.

Translationally controlled tumor protein in prostatic adenocarcinoma: correlation with tumor grading and treatment-related changes

Prostate cancer is the second leading cause of cancer-related death. The androgen deprivation therapy is the standard treatment for advanced stages. Unfortunately, virtually all tumors become resistant to androgen withdrawal. The progression to castration-resistance is not fully understood, although a recent paper has suggested translationally controlled tumor protein to be implicated in the process. The present study was designed to investigate the role of this protein in prostate cancer, focusing on the correlation between its expression level with tumor differentiation and response to treatment. We retrieved 292 prostatic cancer specimens; of these 153 had been treated only by radical prostatectomy and 139 had undergone radical prostatectomy after neoadjuvant treatment with combined androgen blockade therapy. Non-neoplastic controls were represented by 102 prostatic peripheral zone specimens. In untreated patients, the expression of the protein, evaluated by RT-qPCR and immunohistochemistry, was significantly higher in tumor specimens than in non-neoplastic control, increasing as Gleason pattern and score progressed. In treated prostates, the staining was correlated with the response to treatment. An association between protein expression and the main clinicopathological factors involved in prostate cancer aggressiveness was identified. These findings suggest that the protein may be a promising prognostic factor and a target for therapy.

Effect of a genomic classifier test on clinical practice decisions for patients with high-risk prostate cancer after surgery

Objectives

To evaluate the impact of a genomic classifier (GC) test for predicting metastasis risk after radical prostatectomy (RP) on urologists' decision-making about adjuvant treatment of patients with high-risk prostate cancer.

Subjects and Methods

Patient case history was extracted from the medical records of each of the 145 patients with pT3 disease or positive surgical margins (PSMs) after RP treated by six high-volume urologists, from five community practices. GC results were available for 122 (84%) of these patients. US board-certified urologists (n = 107) were invited to provide adjuvant treatment recommendations for 10 cases randomly drawn from the pool of patient case histories. For each case, the study participants were asked to make an adjuvant therapy recommendation without (clinical variables only) and with knowledge of the GC test results. Recommendations were made without knowledge of other participants' responses and the presentation of case histories was randomised to minimise recall bias.

Results

A total of 110 patient case histories were available for review by the study participants. The median patient age was 62 years, 71% of patients had pT3 disease and 63% had PSMs. The median (range) 5-year predicted probability of metastasis by the GC test for the cohort was 3.9 (1–33)% and the GC test classified 72% of patients as having low risk for metastasis. A total of 51 urologists consented to the study and provided 530 adjuvant treatment recommendations without, and 530 with knowledge of the GC test results. Study participants performed a mean of 130 RPs/year and 55% were from community-based practices. Without GC test result knowledge, observation was recommended for 57% (n = 303), adjuvant radiation therapy (ART) for 36% (n = 193) and other treatments for 7% (n = 34) of patients. Overall, 31% (95% CI: 27–35%) of treatment recommendations changed with knowledge of the GC test results. Of the ART recommendations without GC test result knowledge, 40% (n = 77) changed to observation (95% CI: 33–47%) with this knowledge. Of patients recommended for observation, 13% (n = 38 [95% CI: 9–17%]) were changed to ART with knowledge of the GC test result. Patients with low risk disease according to the GC test were recommended for observation 81% of the time (n = 276), while of those with high risk, 65% were recommended for treatment (n = 118; P < 0.001). Treatment intensity was strongly correlated with the GC-predicted probability of metastasis (P < 0.001) and the GC test was the dominant risk factor driving decisions in multivariable analysis (odds ratio 8.6, 95% CI: 5.3–14.3%; P < 0.001).

Conclusions

Knowledge of GC test results had a direct effect on treatment strategies after surgery. Recommendations for observation increased by 20% for patients assessed by the GC test to be at low risk of metastasis, whereas recommendations for treatment increased by 16% for patients at high risk of metastasis. These results suggest that the implementation of genomic testing in clinical practice may lead to significant changes in adjuvant therapy decision-making for high-risk prostate cancer.

DNA methylation status is more reliable than gene expression at detecting cancer in prostate biopsy

Background:

We analysed critically the potential usefulness of RNA- and DNA-based biomarkers in supporting conventional histological diagnostic tests for prostate carcinoma (PCa) detection.

Methods:

Microarray profiling of gene expression and DNA methylation was performed on 16 benign prostatic hyperplasia (BPH) and 32 cancerous and non-cancerous prostate samples extracted by radical prostatectomy. The predictive value of the selected biomarkers was validated by qPCR-based methods using tissue samples extracted from the 58 prostates and, separately, using 227 prostate core biopsies.

Results:

HOXC6, AMACR and PCA3 expression showed the best discrimination between PCa and BPH. All three genes were previously reported as the most promising mRNA-based markers for distinguishing cancerous lesions from benign prostate lesions; however, none were sufficiently sensitive and specific to meet the criteria for a PCa diagnostic biomarker. By contrast, DNA methylation levels of the APC, TACC2, RARB, DGKZ and HES5 promoter regions achieved high discriminating sensitivity and specificity, with area under the curve (AUCs) reaching 0.95−1.0. Only a small overlap was detected between the DNA methylation levels of PCa-positive and PCa-negative needle biopsies, with AUCs ranging between 0.854 and 0.899.

Conclusions:

DNA methylation-based biomarkers reflect the prostate malignancy and might be useful in supporting clinical decisions for suspected PCa following an initial negative prostate biopsy.

How to get the most from microarray data: advice from reverse genomics

BACKGROUND

Whole-genome profiling of gene expression is a powerful tool for identifying cancer-associated genes. Genes differentially expressed between normal and tumorous tissues are usually considered to be cancer associated. We recently demonstrated that the analysis of interindividual variation in gene expression can be useful for identifying cancer associated genes. The goal of this study was to identify the best microarray data-derived predictor of known cancer associated genes.

RESULTS

We found that the traditional approach of identifying cancer genes--identifying differentially expressed genes--is not very efficient. The analysis of interindividual variation of gene expression in tumor samples identifies cancer-associated genes more effectively. The results were consistent across 4 major types of cancer: breast, colorectal, lung, and prostate. We used recently reported cancer-associated genes (2011-2012) for validation and found that novel cancer-associated genes can be best identified by elevated variance of the gene expression in tumor samples.

CONCLUSIONS

The observation that the high interindividual variation of gene expression in tumor tissues is the best predictor of cancer-associated genes is likely a result of tumor heterogeneity on gene level. Computer simulation demonstrates that in the case of heterogeneity, an assessment of variance in tumors provides a better identification of cancer genes than does the comparison of the expression in normal and tumor tissues. Our results thus challenge the current paradigm that comparing the mean expression between normal and tumorous tissues is the best approach to identifying cancer-associated genes; we found that the high interindividual variation in expression is a better approach, and that using variation would improve our chances of identifying cancer-associated genes.

Biobanking of derivatives from radical retropubic and robot-assisted laparoscopic prostatectomy tissues as part of the prostate cancer biorepository network

BACKGROUND

The goal of the Prostate Cancer Biorepository Network (PCBN) is to develop a biorepository with high-quality, well-annotated specimens obtained in a systematic, reproducible fashion using optimized and standardized protocols, and an infrastructure to facilitate the growth of the resource and its wide usage by the prostate cancer research community. An emerging area of concern in the field of prostate cancer biobanking is an apparent shift in the proportion of surgical procedures performed for prostate cancer treatment from radical retropubic prostatectomy (RRP) to robot-assisted laparoscopic prostatectomy (RALP). Our study aimed to determine the potential impact of the RALP procedure on the detection of known prostate cancer biomarkers, and the subsequent suitability of RALP-derived specimens for prostate cancer biomarker studies.

METHODS

DNA and RNA were extracted from RRP and RALP specimens. Quality assessment was conducted using spectrophotometric analysis and RNA was analyzed for RNA integrity number (RIN) and by real-time reverse-transcription PCR (qRT-PCR) for racemase, hepsin, ERG, TMPRSS2-ERG gene fusions, and the microRNAs miR-26a, miR-26b, miR-141, and miR-221.

RESULTS

We demonstrate that extraction of derivatives from frozen tissues from RRP and RALP specimens yields samples of equally high quality as assessed by spectrophotometric and RIN analysis. Likewise, expression levels of genes analyzed by qRT-PCR did not differ between RRP and RALP-derived tissues.

CONCLUSIONS

Our studies indicate that samples obtained from RALP specimens may be suitable for prostate cancer biomarker studies-an important finding given the current shift in surgical procedures for prostate cancer treatment.

Comparative microRNA profiling of prostate carcinomas with increasing tumor stage by deep sequencing

MicroRNAs (miRNA) posttranscriptionally regulate gene expression and are important in tumorigenesis. Previous deep sequencing identified the miRNA profile of prostate carcinoma versus nonmalignant prostate tissue. Here, we generated miRNA expression profiles of prostate carcinoma by deep sequencing, with increasing tumor stage relative to corresponding nonmalignant and healthy prostate tissue, and detected clearly changed miRNA expression patterns. The miRNA profiles of the healthy and nonmalignant tissues were consistent with our previous findings, indicating a high fidelity of the method employed. In the tumors, quantitative real-time PCR (qRT-PCR) analysis of 40 paired samples of prostate carcinoma versus normal tissue revealed significant upregulation of miR-20a, miR-148a, miR-200b, and miR-375 and downregulation of miR-143 and miR-145. Hereby, miR-375 increased from normal to organ-confined tumors (pT2 pN0), slightly decreased in tumors with extracapsular growth (pT3 pN0), but was then expressed again at higher levels in lymph node metastasizing (pN1) tumors. The sequencing data for miR-375 were confirmed by Northern blotting and qRT-PCR. The regulation for other selected miRNAs could, however, not be confirmed by qRT-PCR in individual tumor stages. MiR-200b, in addition to miR-200c and miR-375 reduced the expression of SEC23A. Interestingly, miR-375, found by sequencing in pT2 upregulated by us and others in tumor versus normal tissue, and miR-15a, found by sequencing in pT2 and pT3 and in the metastasizing tumors, target the phosphatases PHLPP1 and PHLPP2, respectively. PHLPP1 and PHLPP2 dephosphorylate members of the AKT family of signal transducers, thereby inhibiting cell growth. Coexpression of miR-15a and miR-375 resulted in downregulation of PHLPP1/2 and strongly increased prostate carcinoma cell growth.

IMPLICATIONS

These genomic data reveal relevant miRNAs in prostate cancer that may have biomarker and therapeutic potential.

Validation of a genomic classifier that predicts metastasis following radical prostatectomy in an at risk patient population

PURPOSE

Patients with locally advanced prostate cancer after radical prostatectomy are candidates for secondary therapy. However, this higher risk population is heterogeneous. Many cases do not metastasize even when conservatively managed. Given the limited specificity of pathological features to predict metastasis, newer risk prediction models are needed. We report a validation study of a genomic classifier that predicts metastasis after radical prostatectomy in a high risk population.

MATERIALS AND METHODS

A case-cohort design was used to sample 1,010 patients after radical prostatectomy at high risk for recurrence who were treated from 2000 to 2006. Patients had preoperative prostate specific antigen greater than 20 ng/ml, Gleason 8 or greater, pT3b or a Mayo Clinic nomogram score of 10 or greater. Patients with metastasis at diagnosis or any prior treatment for prostate cancer were excluded from analysis. A 20% random sampling created a subcohort that included all patients with metastasis. We generated 22-marker genomic classifier scores for 219 patients with available genomic data. ROC and decision curves, competing risk and weighted regression models were used to assess genomic classifier performance.

RESULTS

The genomic classifier AUC was 0.79 for predicting 5-year metastasis after radical prostatectomy. Decision curves showed that the genomic classifier net benefit exceeded that of clinical only models. The genomic classifier was the predominant predictor of metastasis on multivariable analysis. The cumulative incidence of metastasis 5 years after radical prostatectomy was 2.4%, 6.0% and 22.5% in patients with low (60%), intermediate (21%) and high (19%) genomic classifier scores, respectively (p<0.001).

CONCLUSIONS

Results indicate that genomic information from the primary tumor can identify patients with adverse pathological features who are most at risk for metastasis and potentially lethal prostate cancer.

Expression profiling of cervical cancers in Indian women at different stages to identify gene signatures during progression of the disease

Cervical cancer is the second most common cancer among women worldwide, with developing countries accounting for >80% of the disease burden. Although in the West, active screening has been instrumental in reducing the incidence of cervical cancer, disease management is hampered due to lack of biomarkers for disease progression and defined therapeutic targets. Here we carried out gene expression profiling of 29 cervical cancer tissues from Indian women, spanning International Federation of Gynaecology and Obstetrics (FIGO) stages of the disease from early lesion (IA and IIA) to progressive stages (IIB and IIIA–B), and identified distinct gene expression signatures. Overall, metabolic pathways, pathways in cancer and signaling pathways were found to be significantly upregulated, while focal adhesion, cytokine–cytokine receptor interaction and WNT signaling were downregulated. Additionally, we identified candidate biomarkers of disease progression such as SPP1, proliferating cell nuclear antigen (PCNA), STK17A, and DUSP1 among others that were validated by quantitative real-time polymerase chain reaction (qRT-PCR) in the samples used for microarray studies as well in an independent set of 34 additional samples. Integrative analysis of our results with other cervical cancer profiling studies could facilitate the development of multiplex diagnostic markers of cervical cancer progression.

Multiplexed detection of molecular biomarkers with phase-change nanoparticles

This review describes a new biosensing method based on nanoparticles of solid-to-liquid phase-change materials, in which a panel of metallic nanoparticles (metals and eutectic alloys) that have different compositions and melting temperatures are used as thermal reporters. Each type of nanoparticle will be conjugated to a ligand that can specifically bind to one type of molecular biomarker (protein or DNA) and then immobilized onto a substrate that is comodified with multiple ligands by forming sandwiched antibody-antigen complexes or DNA double helices. After removing unbound nanoparticles by washing, the nature and concentration of the biomarkers are determined by detecting the melting temperature and fusion enthalpy of the nanoparticles using differential scanning calorimetry. Furthermore, an even larger panel of thermal barcodes can be formed by encapsulating selected phase-change nanoparticles inside non-melting shells, such as silica, where each microparticle will have a characteristic signature that can be determined from its thermal signatures.

Differentially expressed androgen-regulated genes in androgen-sensitive tissues reveal potential biomarkers of early prostate cancer

Background

Several data favor androgen receptor implication in prostate cancer initiation through the induction of several gene activation programs. The aim of the study is to identify potential biomarkers for early diagnosis of prostate cancer (PCa) among androgen-regulated genes (ARG) and to evaluate comparative expression of these genes in normal prostate and normal prostate-related androgen-sensitive tissues that do not (or rarely) give rise to cancer.

Methods

ARG were selected in non-neoplastic adult human prostatic epithelial RWPE-1 cells stably expressing an exogenous human androgen receptor, using RNA-microarrays and validation by qRT-PCR. Expression of 48 preselected genes was quantified in tissue samples (seminal vesicles, prostate transitional zones and prostate cancers, benign prostatic hypertrophy obtained from surgical specimens) using TaqMan® low-density arrays. The diagnostic performances of these potential biomarkers were compared to that of genes known to be associated with PCa (i.e. PCA3 and DLX1).

Results and Discussion

By crossing expression studies in 26 matched PCa and normal prostate transitional zone samples, and 35 matched seminal vesicle and PCa samples, 14 genes were identified. Similarly, 9 genes were overexpressed in 15 benign prostatic hypertrophy samples, as compared to PCa samples. Overall, we selected 8 genes of interest to evaluate their diagnostic performances in comparison with that of PCA3 and DLX1. Among them, 3 genes: CRYAB, KCNMA1 and SDPR, were overexpressed in all 3 reference non-cancerous tissues. The areas under ROC curves of these genes reached those of PCA3 (0.91) and DLX1 (0.94).

Conclusions

We identified ARG with reduced expression in PCa and with significant diagnostic values for discriminating between cancerous and non-cancerous prostatic tissues, similar that of PCA3. Given their expression pattern, they could be considered as potentially protective against prostate cancer. Moreover, they could be complementary to known genes overexpressed in PCa and included along with them in multiplex diagnostic tools.

UVB suppresses PTEN expression by upregulating miR-141 in HaCaT cells

MicroRNAs (miRNAs) are 21 to 24 nucleotide, non-coding RNA molecules that post-transcriptionally regulate the expression of target genes. Ultraviolet B (UVB) radiation has been shown to inhibit phosphatase and tensin homolog deleted on chromosome 10 (PTEN) expression in HaCaT cells through an unknown mechanism. In this study, we investigated whether miR-141 can regulate UVB exposure-mediated inhibition of PTEN expression. Real-time RT-PCR, annexin V/fluorescein isothiocyanate staining, Western blotting and anti-miRNA oligonucleotide transfection were employed in this study. We found that upregulation of miR-141 expression after UVB irradiation was inversely correlated with PTEN expression levels in HaCaT cells. Furthermore, miR-141 expression increased apoptosis, while anti-miR-141 partly restored PTEN expression and reversed the pro-apoptosis effect of UVB. UVB suppresses the expression of PTEN by upregulating miR-141 in HaCaT cells. Therefore, miR-141 is a potential gene therapy target for UVB-induced photodamage.

Exosomal miRNAs as Biomarkers for Prostate Cancer

miRNAs are small non-coding RNAs that finely regulate gene expression in cells. Alterations in miRNA expression have been associated with development of cancer, and miRNAs are now being investigated as biomarkers for cancer as well as other diseases. Recently, miRNAs have been found outside cells in body fluids. Extracellular miRNAs exist in different forms – associated with Ago2 proteins, loaded into extracellular vesicles (exosomes, microvesicles, or apoptotic bodies) or into high density lipoprotein particles. These extracellular miRNAs are probably products of distinct cellular processes, and might therefore play different roles. However, their functions in vivo are currently unknown. In spite of this, they are considered as promising, non-invasive diagnostic, and prognostic tools. Prostate cancer is the most common cancer in men in the Western world, but the currently used biomarker (prostate specific antigen) has low specificity. Therefore, novel biomarkers are highly needed. In this review we will discuss possible biological functions of extracellular miRNAs, as well as the potential use of miRNAs from extracellular vesicles as biomarkers for prostate cancer.

Combined microRNA in situ hybridization and immunohistochemical detection of protein markers

MicroRNAs are short (18-23 nucleotides) non-coding RNAs involved in posttranscriptional regulation of gene expression through their specific binding to the 3'UTR of mRNAs. MicroRNAs can be detected in tissues using specific locked nucleic acid (LNA)-enhanced probes. The characterization of microRNA expression in tissues by in situ detection is often crucial following a microRNA biomarker discovery phase in order to validate the candidate microRNA biomarker and allow better interpretation of its molecular functions and derived cellular interactions. The in situ hybridization data provides information about contextual distribution and cellular origin of the microRNA. By combining microRNA in situ hybridization with immunohistochemical staining of protein markers, it is possible to precisely characterize the microRNA expressing cells and to identify the potential microRNA targets. This combined technology can also help to monitor changes in the level of potential microRNA targets in a therapeutic setting. In this chapter we present a fluorescence-based technology that allows the combination of microRNA in situ hybridization with immunohistochemistry exemplified by the in situ detection of miR-21 and miR-205 in combination with PDCD4 and smooth muscle a-actin.

Down-regulation of calcium/calmodulin-dependent protein kinase kinase 2 by androgen deprivation induces castration-resistant prostate cancer

BACKGROUND

Conversion into androgen-hypersensitive state and adaptation to the low concentration of androgen during ADT cause relapse of prostate cancer (PCa). It is important to identify differentially expressed genes between PCa and normal prostate tissues and to reveal the function of these genes that are involved in progression of PCa.

METHODS

We performed cDNA microarray analysis to identify differentially expressed genes, calcium/calmodulin-dependent protein kinase kinase 2 (CAMKK2). Immunohistochemical analysis was conducted to investigate the relationship between the CAMKK2 expression level and prognosis. The function of CAMKK2 was assessed by generating CAMKK2 overexpressed LNCaP cells and by knockdown of CAMKK2.

RESULTS

We identified CAMKK2 overexpressed six times in PCa more than normal prostate by cDNA microarray analysis. Immunohistochemical analysis of CAMKK2 protein showed that CAMKK2 protein was expressed more in PCa than normal tissue. However, the expression in the high-grade PCa diminished. Moreover, the narrowness of CAMKK2-positive area before ADT was a poor prognostic factor. Androgen-deprivation treatment from the medium in which LNCaP cells were cultured in the presence of 10 nM DHT repressed CAMKK2 expression. CAMKK2 overexpressed LNCaP cells (LNCaP/GFP-CAMKK2) attenuated androgen-sensitivity. Tumorigenesis of LNCaP/GFP-CAMKK2 cells in male SCID mice was decreased compared with control cells irrespective of castration. Finally, knockdown of CAMKK2 mRNA in LNCaP cells induced androgen-hypersensitivity and stimulated LNCaP cell proliferation.

CONCLUSIONS

Induction of androgen-hypersensitivity after ADT may be involved in down-regulation of CAMKK2. This result may provide new therapeutic approach to keep androgen-sensitivity of PCa after ADT.

Whole-exome sequencing reveals recurrent somatic mutation networks in cancer

The second-generation sequencing technologies have been extensively used to reveal the mechanism of tumorigenesis and find critical genes in cancer progression that can be potential targets of clinic treatment. Exome is a part of genome formed by exons which are the protein-coding portions of genes. The whole-exome sequencing information can reflect the mutations of the protein-coding region in the genome and depict the causal relationship between the mutations and phenotypes. Now, many network-based methods have been developed to identify cancer driver modules or pathways, which not only provide new insights into molecular mechanism of disease progression at network level but also can avoid low coverage or lowly recurrent on disease samples in contrast to individual driver genes. In this review, we focus on the recent advances on network-based methods for identifying cancer driver modules or pathways, including methods of whole-exome sequencing, somatic mutation detection, driver mutation identification, and mutation network reconstruction.

Profiling of microRNAs in exosomes released from PC-3 prostate cancer cells

Exosomes are small extracellular vesicles released to the extracellular milieu through fusion of multivesicular bodies with the plasma membrane. These vesicles contain microRNAs and might therefore be vehicles transferring genetic information between cells. The aim of this study was to investigate whether there was a sorting of microRNAs into exosomes in the prostate cancer cell line PC-3. In addition, microRNAs in PC-3 cells and in the non-cancerous prostate cell line RWPE-1 were compared. Exosomes were isolated from the conditioned media from PC-3 cells by ultracentrifugation and inspected by electron microscopy. Total RNA was isolated and microRNAs were analyzed by microarray analysis and real time RT-PCR. MicroRNA microarray analysis revealed that the microRNA profile of PC-3 released exosomes was similar to the profile of the corresponding parent cells. Nevertheless, a sorting of certain microRNAs into exosomes was observed, and low number microRNAs (microRNAs with a low number in their name) were found to be underrepresented in these vesicles. Moreover, the miRNA profile of PC-3 cells resembled the miRNA profile of RWPE-1 cells, though some miRNAs were found to be differently expressed in these cell lines. These results show that exosomes from PC-3 cells, in agreement with previous reports from other cell types, contain microRNAs. Furthermore, this study supports the idea that there is a sorting of microRNAs into exosomes and adds a new perspective by pointing at the underrepresentation of low number miRNAs in PC-3 released exosomes.

Current challenges in development of differentially expressed and prognostic prostate cancer biomarkers

Introduction. Predicting the aggressiveness of prostate cancer at biopsy is invaluable in making treatment decisions. In this paper we review the differential expression of genes and microRNAs identified through microarray analysis as potentially useful markers for prostate cancer prognosis and discuss some of the challenges associated with their development. Methods. A review of the literature was conducted through Medline. Articles were identified through searches of the following terms: "prostate cancer AND differential expression", "prostate cancer prognosis", and "prostate cancer AND microRNAs". Results. Though numerous differentially expressed genes and microRNAs were identified as possible prognostic markers, the significance of several of these genes is either debated due to conflicting results or is not validated in other study populations. A few of the articles constructed predictive nomograms using a panel of biomarkers which require further validation. Challenges to the development of useful markers include different methodology, cancer heterogeneity, and sampling error. These can be overcome by categorizing prognostic factors into particular gene pathways or by supplementing biopsy information with blood or urine-based biomarkers. Conclusion. Though biomarkers based on differential expression offer the potential to improve decision making concerning prostate cancer, further validation of their utility and accuracy at the biopsy level is needed.

Prostate-specific antigen: its relationship with alcohol intake and tobacco

To determine the influence of alcohol and tobacco consumption on serum prostate-specific antigen (PSA) levels. 59 men participated in this study: 20 with prostate tumors (PT) and 39 without tumor diagnosis (prostate controls, PC) (mean 66 and 58 years, respectively). PSA was analyzed in serum samples and its values were compared through the Kruskal-Wallis nonparametric test. Alcohol and tobacco consumption was also considered. PSA mean value was higher than 4 ng/ml in PT, whereas in PC it was lower than that value. Statistically significant differences were found when comparing PSA between PT and PC (P < 0.05). PSA was higher in alcohol and tobacco consumers than in non-consumers in PT group (P < 0.05). For PC, PSA mean values were higher in non-smokers than in smokers. Statistically significant differences were observed for serum PSA when compared between PT and PC groups considering alcohol and tobacco consumption (P < 0.05). Serum PSA values appear to be influenced by alcohol and tobacco consumption.

Genomic "Dark Matter" in Prostate Cancer: Exploring the Clinical Utility of ncRNA as Biomarkers

Prostate cancer is the most diagnosed cancer among men in the United States. While the majority of patients who undergo surgery (prostatectomy) will essentially be cured, about 30–40% men remain at risk for disease progression and recurrence. Currently, patients are deemed at risk by evaluation of clinical factors, but these do not resolve whether adjuvant therapy will significantly attenuate or delay disease progression for a patient at risk. Numerous efforts using mRNA-based biomarkers have been described for this purpose, but none have successfully reached widespread clinical practice in helping to make an adjuvant therapy decision. Here, we assess the utility of non-coding RNAs as biomarkers for prostate cancer recurrence based on high-resolution oligonucleotide microarray analysis of surgical tissue specimens from normal adjacent prostate, primary tumors, and metastases. We identify differentially expressed non-coding RNAs that distinguish between the different prostate tissue types and show that these non-coding RNAs can predict clinical outcomes in primary tumors. Together, these results suggest that non-coding RNAs are emerging from the “dark matter” of the genome as a new source of biomarkers for characterizing disease recurrence and progression. While this study shows that non-coding RNA biomarkers can be highly informative, future studies will be needed to further characterize the specific roles of these non-coding RNA biomarkers in the development of aggressive disease.

Multiscale integration of -omic, imaging, and clinical data in biomedical informatics

This paper reviews challenges and opportunities in multiscale data integration for biomedical informatics. Biomedical data can come from different biological origins, data acquisition technologies, and clinical applications. Integrating such data across multiple scales (e.g., molecular, cellular/tissue, and patient) can lead to more informed decisions for personalized, predictive, and preventive medicine. However, data heterogeneity, community standards in data acquisition, and computational complexity are big challenges for such decision making. This review describes genomic and proteomic (i.e., molecular), histopathological imaging (i.e., cellular/tissue), and clinical (i.e., patient) data; it includes case studies for single-scale (e.g., combining genomic or histopathological image data), multiscale (e.g., combining histopathological image and clinical data), and multiscale and multiplatform (e.g., the Human Protein Atlas and The Cancer Genome Atlas) data integration. Numerous opportunities exist in biomedical informatics research focusing on integration of multiscale and multiplatform data.

siRNA knockdown of ribosomal protein gene RPL19 abrogates the aggressive phenotype of human prostate cancer

We provide novel functional data that posttranscriptional silencing of gene RPL19 using RNAi not only abrogates the malignant phenotype of PC-3M prostate cancer cells but is selective with respect to transcription and translation of other genes. Reducing RPL19 transcription modulates a subset of genes, evidenced by gene expression array analysis and Western blotting, but does not compromise cell proliferation or apoptosis in-vitro. However, growth of xenografted tumors containing the knocked-down RPL19 in-vivo is significantly reduced. Analysis of the modulated genes reveals induction of the non-malignant phenotype principally to involve perturbation of networks of transcription factors and cellular adhesion genes. The data provide evidence that extra-ribosomal regulatory functions of RPL19, beyond protein synthesis, are critical regulators of cellular phenotype. Targeting key members of affected networks identified by gene expression analysis raises the possibility of therapeutically stabilizing a benign phenotype generated by modulating the expression of an individual gene and thereafter constraining a malignant phenotype while leaving non-malignant tissues unaffected.

Effectiveness of Social Networks for Studying Biological Agents and Identifying Cancer Biomarkers

Social networks form phenomena that exist and evolve; they are dynamic. These phenomena have been realized and studied by the anthropology and sociology research communities since 1930. However, the recent rapid development in information technology and the internet has increased the interest in social networks and as a model they have been adapted to more applications and domains. Though researchers first studied social networks of humans, for our study described in this chapter we argue that genes and proteins act collaboratively and exist in communities analogous to humans, animals, insects, etc. They complement each other and collectively achieve specific tasks where some would have major roles appearing upfront and others may play minor background roles. However, molecules turn into aggressive actors when their internal structure is augmented; consequently, they may deviate from their target, change camp, and disturb other molecules leading to disaster. Such mutations may be uncontrolled and unintentionally occur inside a body, or they may be intentional and controlled by humans to serve one of two purposes, treatment or bioterrorism. In other words, mutation in the molecules (genes) can lead to a change in behavior. This may lead to good or bad effect, e.g., recovery from illness or diseases that may severely affect the body causing disability or death. Once mutated outside the body, molecules may turn into harmful biological weapons of mass destruction. The latter process does not require sophisticated equipment and hence is extremely dangerous with the uprising global terrorism activities. Bioterrorism is therefore a serious concern for humanity. One could say that mutated biological agents outside the body once misused could be way more dangerous than mutated molecules within the body. In this chapter, we will elaborate on bioterrorism and its consequences; we will also propose a model to study social networks of genes within the body leading to the identification of disease biomarkers.

Insights into cancer mechanisms from genomic research on urological cancers

Molecular mechanisms driving cancer development and progression are rarely unique to one cancer type. Rather, recent genomic studies of urological cancers suggest that common mechanisms recur with variations. Examples include alterations in hypoxia response regulation, epigenetic regulator proteins, and signal transduction pathways in renal, prostatic and urothelial carcinomas. Consideration of these variations alongside the common basic cancer mechanisms might be important for the successful development of targeted therapies.

Cysteine-rich secretory protein 3 and β-microseminoprotein on prostate cancer needle biopsies do not have predictive value for subsequent prostatectomy outcome

OBJECTIVES

• To investigate whether cysteine-rich secretory protein 3 (CRISP-3) and/or β-microseminoprotein (β-MSP) expression in diagnostic prostate needle biopsies have predictive value for prostate cancer (PC) on radical prostatecomy (RP). • To evaluate their potential clinical implementation in a preoperative setting.

PATIENTS AND METHODS

• In total, 174 participants from the European Randomized Study of Screening for Prostate Cancer, Rotterdam section, treated by RP for PC were included in the present study. • CRISP-3 and β-MSP immunohistochemistry was performed on corresponding diagnostic needle biopsies. • Outcome was correlated with clinicopathological parameters (prostate-specific-antigen, PSA; number of positive biopsies; Gleason score, GS; pT-stage; surgical margins at RP) and significant PC at RP (pT3/4, or GS > 6, or tumour volume ≥ 0.5 mL) in the total cohort (n= 174) and in a subgroup with low-risk features at biopsy (PSA ≤ 10 ng/ml, cT ≤ 2, PSA density <0.20 ng/mL/g, GS < 7 and ≤ 2 positive biopsy cores; n= 87).

RESULTS

• β-MSP and CRISP-3 expression in PC tissue was heterogeneous, with variable staining intensities occurring in the same tissue specimen. • High expression of β-MSP significantly correlated with GS < 7 at RP; it was not a predictor for significant PC at RP neither in the total group (n= 174; odds ratio, OR, 0.319; 95% confidence interval, CI, 0.060-1.695; P= 0.180), nor in the low-risk group (n= 87; OR, 0.227; 95% CI, 0.040-1.274; P= 0.092). • CRISP-3 expression was not related to clinicopathological parameters, and did not predict significant PC at RP in the total group (n= 174; OR, 1.056; 95% CI, 0.438-2.545; P= 0.904) or the low-risk group (n= 87; OR, 1.856; 95% CI, 0.626-5.506; P= 0.265).

CONCLUSIONS

• High β-MSP expression correlated with low GS in subsequent RP specimens, supporting the view that β-MSP exerts a tumour-suppressive effect. • No significant prognostic value of β-MSP or CRISP-3 in prostate needle biopsies for significant PC at RP was found. • β-MSP or CRISP-3 do not have additional value in the therapeutic stratification of patients with PC.

Ten questions about systems biology

In this paper we raise 'ten questions' broadly related to 'omics', the term systems biology, and why the new biology has failed to deliver major therapeutic advances for many common diseases, especially diabetes and cardiovascular disease. We argue that a fundamentally narrow and reductionist perspective about the contribution of genes and genetic variants to disease is a key reason 'omics' has failed to deliver the anticipated breakthroughs. We then point out the critical utility of key concepts from physiology like homeostasis, regulated systems and redundancy as major intellectual tools to understand how whole animals adapt to the real world. We argue that a lack of fluency in these concepts is a major stumbling block for what has been narrowly defined as 'systems biology' by some of its leading advocates. We also point out that it is a failure of regulation at multiple levels that causes many common diseases. Finally, we attempt to integrate our critique of reductionism into a broader social framework about so-called translational research in specific and the root causes of common diseases in general. Throughout we offer ideas and suggestions that might be incorporated into the current biomedical environment to advance the understanding of disease through the perspective of physiology in conjunction with epidemiology as opposed to bottom-up reductionism alone.

The activity and expression of microRNAs in prostate cancers

Recent studies have shown that microRNA (miRNA) inhibitory activity can be quantified by examining their target mRNA expression levels. The accumulated evidence of differential miRNA activities between cancer subtypes necessitates the systematical comparison of miRNA expressions and activities. In this study, we integrated 8 mRNA microarray datasets to infer and compare the miRNA activities between prostate cancers (PCs) and normal tissues (NTs). Gene expression analyses show that miRNA activity is stronger in PCs. This conclusion is consolidated by target protein expression. We simultaneously collected 6 independent miRNA expression datasets, where great inconsistency is present in the expression difference between PCs and NTs. The overall correlation between miRNA activity and expression is very weak. However, meta-analysis demonstrated that the expressions of 114 individual miRNAs agree with their activities. Additionally, we detected two other factors associated with higher miRNA activity in PCs. One is deregulation of some key miRNA-repression related genes, such as the over-expression of Dicer, TRBP and Ago2, and the under-expression of IRP1 in PCs. The other is that miRNA-mRNA binding site efficacy has significant positive correlation with miRNA activity, whereas no correlation with miRNA expression. Furthermore, miRNA activity is more reproducible than miRNA expression across different datasets, which allows miRNA activity to be a good feature for the classification of cancer subtypes. We expect our analysis can improve the methods for inferring miRNA activity and further, provide some clues to the role of miRNA in tumorigenesis.

Biomarkers for colorectal cancer

Colorectal cancer (CRC) is the third most common epithelial malignancy in the world. Since CRC develops slowly from removable precancerous lesions, detection of the lesion at an early stage by regular health examinations can reduce the incidence and mortality of this malignancy. Colonoscopy significantly improves the detection rate of CRC, but the examination is expensive and inconvenient. Therefore, we need novel biomarkers that are non-invasive to enable us to detect CRC quite early. A number of validation studies have been conducted to evaluate genetic, epigenetic or protein markers for identification in the stool and/or serum. Currently, the fecal occult blood test is the most widely used method of screening for CRC. However, advances in genomics and proteomics will lead to the discovery of novel non-invasive biomarkers.