S. C. Cesar Wong

MiR-30a-5p Overexpression May Overcome EGFR-Inhibitor Resistance through Regulating PI3K/AKT Signaling Pathway in Non-small Cell Lung Cancer Cell Lines

Lung cancer is one of the most common deadly diseases worldwide, most of which is non-small cell lung cancer (NSCLC). The epidermal growth factor receptor (EGFR) mutant NSCLCs frequently respond to the EGFR tyrosine kinase inhibitors (EGFR-TKIs) treatment, such as Gefitinib and Erlotinib, but the development of acquired resistance limits the utility. Multiple resistance mechanisms have been explored, e.g., the activation of alternative tyrosine kinase receptors (TKRs) sharing similar downstream pathways to EGFR. MicroRNAs (miRNAs) are short, endogenous and non-coding RNA molecules, regulating the target gene expression. In this study, we explored the potential of miR-30a-5p in targeting the EGFR and insulin-like growth factor receptor-1 (IGF-1R) signaling pathways to overcome the drug resistance. IGF-1R is one of the tyrosine kinase receptors that share the same EGFR downstream molecules, including phosphatidylinositol 3 kinase (PI3K) and protein kinase B (AKT). In this work, an in vitro study was designed using EGFR inhibitor (Gefitinib), IGF-1R inhibitor (NVP-AEW541), and miRNA mimics in two Gefitinib-resistant NSCLC cell lines, H460 and H1975. We found that the combination of EGFR and IGF-1R inhibitors significantly decreased the phosphorylated AKT (p-AKT) expression levels compared to the control group in these two cell lines. Knockdown of phosphoinositide-3-kinase regulatory subunit 2 (PIK3R2) had the same effect with the dual inhibition of EGFR and IGF-1R to reduce the expression of p-AKT in the signaling pathway. Overexpression of miR-30a-5p significantly reduced the expression of the PI3K regulatory subunit (PIK3R2) to further induce cell apoptosis, and inhibit cell invasion and migration properties. Hence, miR-30a-5p may play vital roles in overcoming the acquired resistance to EGFR-TKIs, and provide useful information for establishing novel cancer treatment.

Circulating Plasma MicroRNAs As Diagnostic Markers for NSCLC

Lung cancer is the most common cause of cancer deaths all over the world, in which non-small cell lung cancer (NSCLC) accounts for ~85% of cases. It is well known that microRNAs (miRNAs) play a critical role in various cellular processes, mediating post-transcriptional silencing either by mRNA degradation through binding the 3′ UTR of target mRNA or by translational inhibition of the protein. In the past decade, miRNAs have also been increasingly identified in biological fluids such as human serum or plasma known as circulating or cell-free miRNAs, and may function as non-invasive diagnostic markers for various cancer types including NSCLC. Circulating tumor cells (CTCs) are those cells that are shed from solid tumors and then migrate into the circulation. However, reports concerning the roles of CTCs are quite rare, which may be attributed to the difficulties in the enrichment and detection of CTCs in the circulation. Although, there have been reassuring advances in identifying circulating miRNA-panels, which are assumed to be of diagnostic value in NSCLC early stage, some issues remain concerning the reliability of using miRNA panels as a diagnostic tool for NSCLC. In the current review, we are aiming at providing insights into the miRNAs biology, the mechanisms of miRNAs release into the bloodstream, cell-free miRNAs as the diagnostic markers for NSCLC and the current limitations of CTCs as diagnostic markers in NSCLC.

Exploring microRNA-mediated alteration of EGFR signaling pathway in non-small cell lung cancer using an mRNA:miRNA regression model supported by target prediction databases

EGFR signaling pathway and microRNAs (miRNAs) are two important factors for development and treatment in non-small cell lung cancer (NSCLC). Microarray analysis enables the genome-wide expression profiling. However, the information from microarray data may not be fully deciphered through the existing approaches. In this study we present an mRNA:miRNA stepwise regression model supported by miRNA target prediction databases. This model is applied to explore the roles of miRNAs in the EGFR signaling pathway. The results show that miR-145 is positively associated with epidermal growth factor (EGF) in the pre-surgery NSCLC group and miR-199a-5p is positively associated with EGF in the post-surgery NSCLC group. Surprisingly, miR-495 is positively associated with protein tyrosine kinase 2 (PTK2) in both groups. The coefficient of determination (R(2)) and leave-one-out cross-validation (LOOCV) demonstrate good performance of our regression model, indicating that it can identify the miRNA roles as oncomirs and tumor suppressor mirs in NSCLC.

Multiple regression analysis of mRNA-miRNA associations in colorectal cancer pathway

Background. MicroRNA (miRNA) is a short and endogenous RNA molecule that regulates posttranscriptional gene expression. It is an important factor for tumorigenesis of colorectal cancer (CRC), and a potential biomarker for diagnosis, prognosis, and therapy of CRC. Our objective is to identify the related miRNAs and their associations with genes frequently involved in CRC microsatellite instability (MSI) and chromosomal instability (CIN) signaling pathways. Results. A regression model was adopted to identify the significantly associated miRNAs targeting a set of candidate genes frequently involved in colorectal cancer MSI and CIN pathways. Multiple linear regression analysis was used to construct the model and find the significant mRNA-miRNA associations. We identified three significantly associated mRNA-miRNA pairs: BCL2 was positively associated with miR-16 and SMAD4 was positively associated with miR-567 in the CRC tissue, while MSH6 was positively associated with miR-142-5p in the normal tissue. As for the whole model, BCL2 and SMAD4 models were not significant, and MSH6 model was significant. The significant associations were different in the normal and the CRC tissues. Conclusion. Our results have laid down a solid foundation in exploration of novel CRC mechanisms, and identification of miRNA roles as oncomirs or tumor suppressor mirs in CRC.

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.

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.

Disease Biomarkers for Precision Medicine: Challenges and Future Opportunities

Center for Health Genomics and Informatics, University of Calgary Cumming School of Medicine, Calgary, AB T2N 4N1, Canada Department of Clinical Oncology, Queen Elizabeth Hospital, Hong Kong Special Administrative Region Department of Health Technology and Informatics, Faculty of Health and Social Sciences, Hong Kong Polytechnic University, Hong Kong Special Administrative Region CAS Key Laboratory of Genome Sciences and Information, Beijing Institute of Genomics, Chinese Academy of Sciences, Beijing 100101, China

Associations of mRNA:microRNA for the Shared Downstream Molecules of EGFR and Alternative Tyrosine Kinase Receptors in Non-small Cell Lung Cancer

Lung cancer is the top cancer killer worldwide with high mortality rate. Majority belong to non-small cell lung cancers (NSCLCs). The epidermal growth factor receptor (EGFR) has been broadly explored as a drug target for therapy. However, the drug responses are not durable due to the acquired resistance. MicroRNAs (miRNAs) are small non-coding and endogenous molecules that can inhibit mRNA translation initiation and degrade mRNAs. We wonder if some downstream molecules shared by EGFR and the other tyrosine kinase receptors (TKRs) further transduce the signals alternatively, and some miRNAs play the key roles in affecting the expression of these downstream molecules. In this study, we investigated the mRNA:miRNA associations for the direct EGFR downstream molecules in the EGFR signaling pathway shared with the other TKRs, including c-MET (hepatocyte growth factor receptor), Ron (a protein tyrosine kinase related to c-MET), PDGFR (platelet-derived growth factor receptor), and IGF-1R (insulin-like growth factor receptor-1). The multiple linear regression and support vector regression (SVR) models were used to discover the statistically significant and the best weighted miRNAs regulating the mRNAs of these downstream molecules. These two models revealed the similar mRNA:miRNA associations. It was found that the miRNAs significantly affecting the mRNA expressions in the multiple regression model were also those with the largest weights in the SVR model. To conclude, we effectively identified a list of meaningful mRNA:miRNA associations: phospholipase C, gamma 1 (PLCG1) with miR-34a, phosphoinositide-3-kinase, regulatory subunit 2 (PIK3R2) with miR-30a-5p, growth factor receptor-bound protein 2 (GRB2) with miR-27a, and Janus kinase 1 (JAK1) with miR-302b and miR-520e. These associations could make great contributions to explore new mechanism in NSCLCs. These candidate miRNAs may be regarded as the potential drug targets for treating NSCLCs with acquired drug resistance.

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.

Association Patterns of Ontological Features Signify Electronic Health Records in Liver Cancer

Electronic Health Record (EHR) system enables clinical decision support. In this study, a set of 112 abdominal computed tomography imaging examination reports, consisting of 59 cases of hepatocellular carcinoma (HCC) or liver metastases (so-called HCC group for simplicity) and 53 cases with no abnormality detected (NAD group), were collected from four hospitals in Hong Kong. We extracted terms related to liver cancer from the reports and mapped them to ontological features using Systematized Nomenclature of Medicine (SNOMED) Clinical Terms (CT). The primary predictor panel was formed by these ontological features. Association levels between every two features in the HCC and NAD groups were quantified using Pearsons correlation coefficient. The HCC group reveals a distinct association pattern that signifies liver cancer and provides clinical decision support for suspected cases, motivating the inclusion of new features to form the augmented predictor panel. Logistic regression analysis with stepwise forward procedure was applied to the primary and augmented predictor sets, respectively. The obtained model with the new features attained 84.7% sensitivity and 88.4% overall accuracy in distinguishing HCC from NAD cases, which were significantly improved when compared with that without the new features.