Link test—A statistical method for finding prostate cancer biomarkers

Deng, Xutao; Geng, Huimin; Bastola, Dhundy; Ali, Hesham

doi:10.1016/j.compbiolchem.2006.09.002

Cited by 20 publications

(17 citation statements)

References 24 publications

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“…COL1A1 was the only microarray-identified common gene, but no significant changes were observed in MeHg-treated male zebrafish by QPCR. In previous studies, the strategies for identifying biomarkers from microarray data have been based on robust expression (Gunnarsson, et al 2007), expression signature or patterns (Wang et al 2008), specific location of tissue (Tilton et al 2008), and linkage to the protein levels (Deng et al 2006). In the current project, we focused on the identification of conserved gene expression biomarkers based on common dysregulated genes in whole rainbow trout and zebrafish.…”

Section: Discussion and Summarymentioning

confidence: 99%

Differential gene expression associated with dietary methylmercury (MeHg) exposure in rainbow trout (Oncorhynchus mykiss) and zebrafish (Danio rerio)

et al. 2013

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The objective of this study was to identify and evaluate conserved biomarkers that could be used in most species of teleost fish at most life-stages. We investigated the effects of sublethal methylmercury (MeHg) exposure on developing rainbow trout and zebrafish. Juvenile rainbow trout and young adult zebrafish were fed food with MeHg added at 0, 0.5, 5 and 50 ppm. Atomic absorption spectrometry was applied to measure whole body total Hg levels, and pathologic analysis was performed to identify MeHg-induced toxicity. Fish at six weeks were sampled from each group for microarray analysis using RNA from whole fish. MeHg-exposed trout and zebrafish did not show overt signs of toxicity or pathology, nor were significant differences seen in mortality, length, mass, or condition factor. The accumulation of MeHg in trout and zebrafish exhibited dose- and time-dependent patterns during six weeks, and zebrafish exhibited greater assimilation of total Hg than rainbow trout. The dysregulated genes in MeHg-treated fish have multiple functional annotations, such as iron ion homeostasis, glutathione transferase activity, regulation of muscle contraction, troponin I binding and calcium-dependent protein binding. Genes were selected as biomarker candidates based on their microarray data and their expression was evaluated by QPCR. Unfortunately, these genes are not good consistent biomarkers for both rainbow trout and zebrafish from QPCR evaluation using individual fish. Our conclusion is that biomarker analysis for aquatic toxicant assessment using fish needs to be based on tissue-, sex- and species-specific consideration.

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Section: Discussion and Summarymentioning

confidence: 99%

Differential gene expression associated with dietary methylmercury (MeHg) exposure in rainbow trout (Oncorhynchus mykiss) and zebrafish (Danio rerio)

et al. 2013

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“…This suggests that most of the mass markers are fragmented peptides instead of intact proteins. [27] There are many homologous proteins represented by each peak, so further identification is necessary. Further functional characterization of these proteins will be important to reveal their roles in NACT of breast cancer.…”

Section: Discussionmentioning

confidence: 99%

“…[20,[26][27][28] UniProtKB/Swiss-Prot release 57.6 contains 20,330 human proteome entries, more than one third of which contain additional sequences representing isoforms generated by alternative splicing, alternative promoter usage and/or alternative translation initiation, resulting in almost 34,000 human protein sequences. [20] However, of all the human protein sequences from the SWISS-PROT database, only 2.78% of proteins (348 out of 12,484) have an m/z values less than 10,000 Da.…”

Section: Discussionmentioning

confidence: 99%

Identification of Potential Markers Related to Neoadjuvant Chemotherapy Sensitivity of Breast Cancer by SELDI-TOF MS

Zhang

Yuan

et al. 2011

Appl Biochem Biotechnol

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Neoadjuvant chemotherapy (NACT) is known to be beneficial for patients with locally advanced breast cancer. However, there is still no unified standard on the evaluation of NACT. To identify the potential markers related to NACT sensitivity of breast cancer, in the present study, we examined the protein spectrum of breast cancer tissues before and after NACT using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS). Totally, 87 protein samples were extracted from tissues of breast cancer, with 30 from patients before NACT, 30 from patients after NACT, and 27 from patients without any treatment. To eliminate confounding factors a couple of tissue samples from the same patient were mixed. SELDI-TOF MS analysis demonstrated that the intensities of eight different protein peaks, i.e., 26,055.46, 17,898.94, 8,949.50, 11,652.02, 11,053.48, 38,546.56, 5,825.89, and 22,250.63 Da, were higher in samples after NACT than those before NACT. Although further experiments are needed to prove the reliability of the proteins identified in this study, our results will help the establishment of protein model based on drug resistance-related protein peaks to screen whether a patient is suitable for adopting NACT and to improve cancer treatment.

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“…For example, Deng et al, have developed a multi-platform strategy, link-test, to cross-link experimental datasets at both transcriptomic (microarray data) and proteomic (mass spectrometry data) levels in an effort to discover new prostate cancer biomarkers which could outperform the current biomarker, prostate specific antigen or PSA. Cross-validation results showed high prediction accuracy using the identified biomarker candidates, which were further validated by text mining of prostate-cancer-related genes from OMIM (Online Mendelian Inheritance in Man) [90]. Another example, PubMeth, is a freely accessible cancer methylation database that combines a text mining approach with manual reviewing and annotation.…”

Section: Knowledge-driven Approaches To Biomarker Identificationmentioning

confidence: 99%

Challenges in biomarker discovery: combining expert insights with statistical analysis of complex omics data

McDermott

Wang

Mitchell

et al. 2012

Expert Opinion on Medical Diagnostics

164

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Introduction The advent of high throughput technologies capable of comprehensive analysis of genes, transcripts, proteins and other significant biological molecules has provided an unprecedented opportunity for the identification of molecular markers of disease processes. However, it has simultaneously complicated the problem of extracting meaningful molecular signatures of biological processes from these complex datasets. The process of biomarker discovery and characterization provides opportunities for more sophisticated approaches to integrating purely statistical and expert knowledge-based approaches. Areas covered In this review we will present examples of current practices for biomarker discovery from complex omic datasets and the challenges that have been encountered in deriving valid and useful signatures of disease. We will then present a high-level review of data-driven (statistical) and knowledge-based methods applied to biomarker discovery, highlighting some current efforts to combine the two distinct approaches. Expert opinion Effective, reproducible and objective tools for combining data-driven and knowledge-based approaches to identify predictive signatures of disease are key to future success in the biomarker field. We will describe our recommendations for possible approaches to this problem including metrics for the evaluation of biomarkers.

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Link test—A statistical method for finding prostate cancer biomarkers

Cited by 20 publications

References 24 publications

Differential gene expression associated with dietary methylmercury (MeHg) exposure in rainbow trout (Oncorhynchus mykiss) and zebrafish (Danio rerio)

Differential gene expression associated with dietary methylmercury (MeHg) exposure in rainbow trout (Oncorhynchus mykiss) and zebrafish (Danio rerio)

Identification of Potential Markers Related to Neoadjuvant Chemotherapy Sensitivity of Breast Cancer by SELDI-TOF MS

Challenges in biomarker discovery: combining expert insights with statistical analysis of complex omics data

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