Nancy Bo Yin Tsui

DECODE: an integrated differential co-expression and differential expression analysis of gene expression data

BackgroundBoth differential expression (DE) and differential co-expression (DC) analyses are appreciated as useful tools in understanding gene regulation related to complex diseases. The performance of integrating DE and DC, however, remains unexplored.ResultsIn this study, we proposed a novel analytical approach called DECODE (Differential Co-expression and Differential Expression) to integrate DC and DE analyses of gene expression data. DECODE allows one to study the combined features of DC and DE of each transcript between two conditions. By incorporating information of the dependency between DC and DE variables, two optimal thresholds for defining substantial change in expression and co-expression are systematically defined for each gene based on chi-square maximization. By using these thresholds, genes can be categorized into four groups with either high or low DC and DE characteristics. In this study, DECODE was applied to a large breast cancer microarray data set consisted of two thousand tumor samples. By identifying genes with high DE and high DC, we demonstrated that DECODE could improve the detection of some functional gene sets such as those related to immune system, metastasis, lipid and glucose metabolism. Further investigation on the identified genes and the associated functional pathways would provide an additional level of understanding of complex disease mechanism.ConclusionsBy complementing the recent DC and the traditional DE analyses, DECODE is a valuable methodology for investigating biological functions of genes exhibiting disease-associated DE and DC combined characteristics, which may not be easily revealed through DC or DE approach alone.DECODE is available at the Comprehensive R Archive Network (CRAN): http://cran.r-project.org/web/packages/decode/index.html.

Current and future molecular diagnostics in colorectal cancer and colorectal adenoma

Colorectal cancer (CRC) is one of the most prevalent cancers in developed countries. On the other hand, CRC is also one of the most curable cancers if it is detected in early stages through regular colonoscopy or sigmoidoscopy. Since CRC develops slowly from precancerous lesions, early detection can reduce both the incidence and mortality of the disease. Fecal occult blood test is a widely used non-invasive screening tool for CRC. Although fecal occult blood test is simple and cost-effective in screening CRC, there is room for improvement in terms of the accuracy of the test. Genetic dysregulations have been found to play an important role in CRC development. With better understanding of the molecular basis of CRC, there is a growing expectation on the development of diagnostic tests based on more sensitive and specific molecular markers and those tests may provide a breakthrough to the limitations of current screening tests for CRC. In this review, the molecular basis of CRC development, the characteristics and applications of different non-invasive molecular biomarkers, as well as the technologies available for the detection were discussed. This review intended to provide a summary on the current and future molecular diagnostics in CRC and its pre-malignant state, colorectal adenoma.

Novel structural co-expression analysis linking the NPM1-associated ribosomal biogenesis network to chronic myelogenous leukemia

Co-expression analysis reveals useful dysregulation patterns of gene cooperativeness for understanding cancer biology and identifying new targets for treatment. We developed a structural strategy to identify co-expressed gene networks that are important for chronic myelogenous leukemia (CML). This strategy compared the distributions of expressional correlations between CML and normal states, and it identified a data-driven threshold to classify strongly co-expressed networks that had the best coherence with CML. Using this strategy, we found a transcriptome-wide reduction of co-expression connectivity in CML, reflecting potentially loosened molecular regulation. Conversely, when we focused on nucleophosmin 1 (NPM1) associated networks, NPM1 established more co-expression linkages with BCR-ABL pathways and ribosomal protein networks in CML than normal. This finding implicates a new role of NPM1 in conveying tumorigenic signals from the BCR-ABL oncoprotein to ribosome biogenesis, affecting cellular growth. Transcription factors may be regulators of the differential co-expression patterns between CML and normal.

Current and future molecular diagnostics in non-small-cell lung cancer

The molecular investigation of lung cancer has opened up an advanced area for the diagnosis and therapeutic management of lung cancer patients. Gene alterations in cancer initiation and progression provide not only information on molecular changes in lung cancer but also opportunities in advanced therapeutic regime by personalized targeted therapy. EGFR mutations and ALK rearrangement are important predictive biomarkers for the efficiency of tyrosine kinase inhibitor treatment in lung cancer patients. Moreover, epigenetic aberration and microRNA dysregulation are recent advances in the early detection and monitoring of lung cancer. Although a wide range of molecular tests are available, standardization and validation of assay protocols are essential for the quality of the test outcome. In this review, current and new advancements of molecular biomarkers for non-small-cell lung cancer will be discussed. Recommendations on future development of molecular diagnostic services will also be explored.

Gene Network Exploration of Crosstalk between Apoptosis and Autophagy in Chronic Myelogenous Leukemia

Background. Gene expression levels change to adapt the stress, such as starvation, toxin, and radiation. The changes are signals transmitted through molecular interactions, eventually leading to two cellular fates, apoptosis and autophagy. Due to genetic variations, the signals may not be effectively transmitted to modulate apoptotic and autophagic responses. Such aberrant modulation may lead to carcinogenesis and drug resistance. The balance between apoptosis and autophagy becomes very crucial in coping with the stress. Though there have been evidences illustrating the apoptosis-autophagy interplay, the underlying mechanism and the participation of the regulators including transcription factors (TFs) and microRNAs (miRNAs) remain unclear. Results. Gene network is a graphical illustration for exploring the functional linkages and the potential coordinate regulations of genes. Microarray dataset for the study of chronic myeloid leukemia was obtained from Gene Expression Omnibus. The expression profiles of those genes related to apoptosis and autophagy, including MCL1, BCL2, ATG, beclin-1, BAX, BAK, E2F, cMYC, PI3K, AKT, BAD, and LC3, were extracted from the dataset to construct the gene networks. Conclusion. The network analysis of these genes explored the underlying mechanisms and the roles of TFs and miRNAs for the crosstalk between apoptosis and autophagy.

Novel approach for coexpression analysis of E2F1-3 and MYC target genes in chronic myelogenous leukemia.

Background. Chronic myelogenous leukemia (CML) is characterized by tremendous amount of immature myeloid cells in the blood circulation. E2F1–3 and MYC are important transcription factors that form positive feedback loops by reciprocal regulation in their own transcription processes. Since genes regulated by E2F1–3 or MYC are related to cell proliferation and apoptosis, we wonder if there exists difference in the coexpression patterns of genes regulated concurrently by E2F1–3 and MYC between the normal and the CML states. Results. We proposed a method to explore the difference in the coexpression patterns of those candidate target genes between the normal and the CML groups. A disease-specific cutoff point for coexpression levels that classified the coexpressed gene pairs into strong and weak coexpression classes was identified. Our developed method effectively identified the coexpression pattern differences from the overall structure. Moreover, we found that genes related to the cell adhesion and angiogenesis properties were more likely to be coexpressed in the normal group when compared to the CML group. Conclusion. Our findings may be helpful in exploring the underlying mechanisms of CML and provide useful information in cancer treatment.

Advanced technologies for studying circulating tumor cells at the protein level.

Metastasis is the main cause of cancer death. As the tumor progresses, cells from the primary tumor site are shed into the bloodstream as circulating tumor cells (CTCs). Eventually, these cells colonize other organs and form distant metastases. It is therefore imperative that we gain a better understanding of the biological characteristics of CTCs for development of novel treatment modalities to minimize metastasis-associated cancer deaths. In recent years, rapid developments in technologies for the study of CTCs have taken place. We now have a variety of tools for the isolation and examination of CTCs which were not available before. This review introduces some commonly used protein markers in CTC investigations and summarizes a few advanced technologies which have been successfully applied for studying CTC biology at the protein level.

Coexpression Pattern Analysis of NPM1-Associated Genes in Chronic Myelogenous Leukemia

Background. Nucleophosmin 1 (NPM1) plays an important role in ribosomal synthesis and malignancies, but NPM1 mutations occur rarely in the blast-crisis and chronic-phase chronic myelogenous leukemia (CML) patients. The NPM1-associated gene set (GCM_NPM1), in total 116 genes including NPM1, was chosen as the candidate gene set for the coexpression analysis. We wonder if NPM1-associated genes can affect the ribosomal synthesis and translation process in CML. Results. We presented a distribution-based approach for gene pair classification by identifying a disease-specific cutoff point that classified the coexpressed gene pairs into strong and weak coexpression structures. The differences in the coexpression patterns between the normal and the CML groups were reflected from the overall structure by performing two-sample Kolmogorov-Smirnov test. Our developed method effectively identified the coexpression pattern differences from the overall structure: P  value = 1.71 × 10−22 < 0.05 for the maximum deviation D = 0.109. Moreover, we found that genes involved in the ribosomal synthesis and translation process tended to be coexpressed in the CML group. Conclusion. Our developed method can identify the coexpression difference between two different groups. Dysregulation of ribosomal synthesis and translation process may be related to the CML disease. Our significant findings may provide useful information for the novel CML mechanism exploration and cancer treatment.

Population-Wide Genetic Risk Prediction of Complex Diseases: A Pilot Feasibility Study in Macau Population for Precision Public Healthcare Planning

The genetic bases of many common diseases have been identified through genome-wide association studies in the past decade. However, the application of this approach on public healthcare planning has not been well established. Using Macau with population of around 650,000 as a basis, we conducted a pilot study to evaluate the feasibility of population genomic research and its potential on public health decisions. By performing genome-wide SNP genotyping of over a thousand Macau individuals, we evaluated the population genetic risk profiles of 47 non-communicable diseases and traits, as well as two traits associated with influenza infection. We found that for most of the diseases, the genetic risks of Macau population were different from those of Caucasian, but with similar profile with mainland Chinese. We also identified a panel of diseases that Macau population may have a high or elevated genetic risks. This pilot study showed that (1) population genomic study is feasible in Asian regions like Macau; (2) Macau may have different profile of population-based genetic risks than Caucasians, (3) the different prevalence of genetic risk profile indicates the importance of Asian-specific studies for Asian populations; and (4) the results generated may have an impact for going forward healthcare planning.

Abstract 1862: Menstrual blood TAP1 I333V and D637G gene polymorphisms are associated with less risk to develop high-grade cervical intraepithelial neoplasia

Proceedings: AACR Annual Meeting 2014; April 5-9, 2014; San Diego, CA Objectives: Recent evidence has shown that single nucleotide polymorphisms (SNPs) in transporter associated with antigen processing 1 (TAP1) gene includes TAP1 I333V and TAP1 D637G are significantly associated with a protective effect for development of cervical cancer and its pre-malignant states. Hence, TAP1 polymorphisms may potentially be useful to identify women who have less chance to develop high-grade cervical intraepithelial neoplasia (HGCIN) and cervical cancer. Our latest breakthrough in detecting HPV genotypes in the menstrual blood (MB) from patients with CIN and condyloma acuminatum has generated a new era in non-invasive screening for HPV genotypes. Therefore, in this study, we further develop a non-invasive method to predict HGCIN risk in patients with CIN or HPV infection using MB collected in napkin by detecting TAP1 SNP. The information obtained would be important as cervical cancer and CIN are still serious public health problems worldwide especially in developing countries. Materials and Methods: Thirty-eight patients with HGCIN (CIN 2 or 3) and 42 patients with LGCIN (CIN 1) or HPV infection were recruited. MB collected in napkin was put inside ziplock plastic bag which was sent to the laboratory by mail or by hand. Small piece of the napkin was cut out (1 cm x 1 cm x 1 mm) using sterile scissor for DNA extraction. Two SNPs in TAP1 gene (I333V and D637G) were genotyped using polymerase chain reaction - restriction fragment length polymorphism (PCR-RFLP) technique. The amplified TAP1 gene fragments for I333V and D637G SNP detection were digested by BclI and AccI restriction enzymes, respectively and 3 different genotypes which interpreted as AA (wild type), AG (1 allele showed SNP), and GG (2 alleles showed SNP) were detected at each polymorphic site. Reactions were performed in duplicates and each result was confirmed by DNA sequencing. Results: Both TAP1 polymorphisms in the MB were successfully detected. Their patterns were summarized as a) 3 genotypes at each polymorphic site were detected in our patient cohort (Figure 1, Table 1A); b) the risk to develop HGCIN was significantly reduced for AG and GG genotypes when compared to AA genotype (TAP1 I333V: chi-square test, p = 0.003, odds ratio (OR) = 0.23, 95% confidence interval (CI) = 0.08 to 0.63; TAP1 D637G: chi-square test, p = 0.01, OR = 0.30, 95% CI = 0.12 to 0.76); c) the risk to develop HGCIN was significantly reduced for carriers with a G allele when compared to those with an A allele (Table 1B, TAP1 I333V: chi-square test, p = 0.001, OR = 0.27, 95% CI = 0.12 to 0.62; TAP1 D637G: chi-square test, p = 0.007, OR = 0.36, 95% CI = 0.17 to 0.76). Conclusions: This study is the first to show that MB TAP1 I333V and D637G gene polymorphisms are significantly associated with less risk to develop HGCIN. Acknowledgements: This project was supported by the Direct Grant 2010, The Chinese University of Hong Kong. Citation Format: Sze Chuen Cesar Wong, Thomas Chi Chuen Au, Sammy Chung Sum Chan, Charles Ming Lok Chan, Nancy Bo Yin Tsui, Lawrence Wing Chi Chan, Benjamin Yat Ming Yung. Menstrual blood TAP1 I333V and D637G gene polymorphisms are associated with less risk to develop high-grade cervical intraepithelial neoplasia. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 1862. doi:10.1158/1538-7445.AM2014-1862