Methylation of NF-κB and its Role in Gene Regulation

The nuclear factor κB (NF-κB) is one of the most pivotal transcription factors in mammalian cells. In many pathologies NF-κB is activated abnormally. This contributes to the development of various disorders such as cancer, acute kidney injury, lung disease, chronic inflammatory diseases, cardiovascular disease, and diabetes. This book chapter focuses on how methylation of NF-κB regulates its target genes differentially. The knowledge from this chapter will provide scientific strategies for innovative therapeutic intervention of NF-κB in a wide range of diseases

Comprehensive comparison of molecular portraits between cell lines and tumors in breast cancer

Background: Proper cell models for breast cancer primary tumors have long been the focal point in the cancer’s research. The genomic comparison between cell lines and tumors can investigate the similarity and dissimilarity and help to select right cell model to mimic tumor tissues to properly evaluate the drug reaction in vitro. In this paper, a comprehensive comparison in copy number variation (CNV), mutation, mRNA expression and protein expression between 68 breast cancer cell lines and 1375 primary breast tumors is conducted and presented. Results: Using whole genome expression arrays, strong correlations were observed between cells and tumors. PAM50 gene expression differentiated them into four major breast cancer subtypes: Luminal A and B, HER2amp, and Basal-like in both cells and tumors partially. Genomic CNVs patterns were observed between tumors and cells across chromosomes in general. High C > T and C > G trans-version rates were observed in both cells and tumors, while the cells had slightly higher somatic mutation rates than tumors. Clustering analysis on protein expression data can reasonably recover the breast cancer subtypes in cell lines and tumors. Although the drug-targeted proteins ER/PR and interesting mTOR/GSK3/TS2/PDK1/ER_P118 cluster had shown the consistent patterns between cells and tumor, low protein-based correlations were observed between cells and tumors. The expression consistency of mRNA verse protein between cell line and tumors reaches 0.7076. These important drug targets in breast cancer, ESR1, PGR, HER2, EGFR and AR have a high similarity in mRNA and protein variation in both tumors and cell lines. GATA3 and RP56KB1 are two promising drug targets for breast cancer. A total score developed from the four correlations among four molecular profiles suggests that cell lines, BT483, T47D and MDAMB453 have the highest similarity with tumors. Conclusions: The integrated data from across these multiple platforms demonstrates the existence of the similarity and dissimilarity of molecular features between breast cancer tumors and cell lines. The cell lines only mirror some but not all of the molecular properties of primary tumors. The study results add more evidence in selecting cell line models for breast cancer research

Novel Serine 176 Phosphorylation of YBX1 Activates NF-κB in Colon Cancer

Y box protein 1 (YBX1) is a well known oncoprotein that has tumor-promoting functions. YBX1 is widely considered to be an attractive therapeutic target in cancer. To develop novel therapeutics to target YBX1, it is of great importance to understand how YBX1 is finely regulated in cancer. Previously, we have shown that YBX1 could function as a tumor promoter through phosphorylation of its Ser-165 residue, leading to the activation of the NF-κB signaling pathway (1). In this study, using mass spectrometry analysis, we discovered a distinct phosphorylation site, Ser-176, on YBX1. Overexpression of the YBX1-S176A (serine-to-alanine) mutant in either HEK293 cells or colon cancer HT29 cells showed dramatically reduced NF-κB-activating ability compared with that of WT-YBX1, confirming that Ser-176 phosphorylation is critical for the activation of NF-κB by YBX1. Importantly, the mutant of Ser-176 and the previously reported Ser-165 sites regulate distinct groups of NF-κB target genes, suggesting the unique and irreplaceable function of each of these two phosphorylated serine residues. Our important findings could provide a novel cancer therapy strategy by blocking either Ser-176 or Ser-165 phosphorylation or both of YBX1 in colon cancer

The Role and Therapeutic Potential of miRNAs in Colorectal Liver Metastasis

Colorectal cancer (CRC) is the fourth leading cause of cancer-related deaths worldwide. Liver metastasis is the major cause of CRC patient mortality, occurring in 60% patients with no effective therapies. Although studies have indicated the role of miRNAs in CRC, an in-depth miRNA expression analysis is essential to identify clinically relevant miRNAs and understand their potential in targeting liver metastasis. Here we analyzed miRNA expressions in 405 patient tumors from publicly available colorectal cancer genome sequencing project database. Our analyses showed miR-132, miR-378f, miR-605 and miR-1976 to be the most significantly downregulated miRNAs in primary and CRC liver metastatic tissues, and CRC cell lines. Observations in CRC cell lines indicated that ectopic expressions of miR-378f, -605 and -1976 suppress CRC cell proliferation, anchorage independent growth, metastatic potential, and enhance apoptosis. Consistently, CRC patients with higher miR-378f and miR-1976 levels exhibited better survival. Together, our data suggests an anti-tumorigenic role of these miRNAs in CRC and warrant future in vivo evaluation of the molecules for developing biomarkers or novel therapeutic strategies

Investigation of phytoplankton community structure and formation mechanism: a case study of Lake Longhu in Jinjiang

In order to explore the species composition, spatial distribution and relationship between the phytoplankton community and environmental factors in Lake Longhu, the phytoplankton community structures and environmental factors were investigated in July 2020. Clustering analysis (CA) and analysis of similarities (ANOSIM) were used to identify differences in phytoplankton community composition. Generalized additive model (GAM) and variance partitioning analysis (VPA) were further analyzed the contribution of spatial distribution and environmental factors in phytoplankton community composition. The critical environmental factors influencing phytoplankton community were identified using redundancy analysis (RDA). The results showed that a total of 68 species of phytoplankton were found in 7 phyla in Lake Longhu. Phytoplankton density ranged from 4.43 × 105 to 2.89 × 106 ind./L, with the average density of 2.56 × 106 ind./L; the biomass ranged from 0.58–71.28 mg/L, with the average biomass of 29.38 mg/L. Chlorophyta, Bacillariophyta and Cyanophyta contributed more to the total density, while Chlorophyta and Cryptophyta contributed more to the total biomass. The CA and ANOSIM analysis indicated that there were obvious differences in the spatial distribution of phytoplankton communities. The GAM and VPA analysis demonstrated that the phytoplankton community had obvious distance attenuation effect, and environmental factors had spatial autocorrelation phenomenon, which significantly affected the phytoplankton community construction. There were significant distance attenuation effects and spatial autocorrelation of environmental factors that together drove the composition and distribution of phytoplankton community structure. In addition, pH, water temperature, nitrate nitrogen, nitrite nitrogen and chemical oxygen demand were the main environmental factors affecting the composition of phytoplankton species in Lake Longhu

The Role and Therapeutic Potential of miRNAs in Colorectal Liver Metastasis

poster abstractColorectal cancer (CRC) is the third most common malignancy worldwide. Liver metastasis occurs in 60% of CRC patients and responds poorly to the available treatments making it the major cause of their mortality. MicroRNAs (miRNAs) are highly conserved, endogenously encoded small, non-coding RNA molecules that regulate global gene expression. The role of microRNAs in cancer pathogenesis, including CRC, has been well documented. However, in-depth miRNA expression analysis on a large cohort of CRC tumors is needed to identify the clinically relevant miRNAs and explore their potential to target liver metastases. To this purpose, we analyzed miRNA expression data of 406 CRC tumors from the publicly available colorectal cancer genome sequencing project and identified 58 miRNAs that were significantly downregulated. 10 miRNAs were selected for further analyses that were either known to target genes in cellular pathways or located within the commonly lost chromosomal loci associated with CRC liver metastases. Of these 10 miRNAs, miR-132, miR-378f, miR-605 and miR-1976 showed significant downregulation with >2 fold change (p>0.05) in primary and CRC liver metastasis tissues and in CRC cell lines. To investigate their anti-tumorigenic and metastatic properties, we transfected 3 different CRC cell lines (SW620, HCT-116 and CT-26) with miR-mimics and subjected them to cell proliferation, apoptosis and cell transformation assays. Ectopic expression of miR-378f, -605 and -1976 suppressed CRC cell proliferation, anchorage independent growth, migration and invasion and induced apoptosis. Interestingly, CRC patients with high miR-378f and miR-1976 had better survival compared to low expressing patients (p<0.044). Our in vitro data suggest the anti-tumorigenic/metastatic properties of miR-378f, -605 and -1976 in CRC. Further understanding of their functions and in vivo therapeutic evaluations may help in developing novel therapeutic strategies for this malignancy

Computational Analysis of Drought Stress-Associated miRNAs and miRNA Co-Regulation Network in Physcomitrella patens.

miRNAs are non-coding small RNAs that involve diverse biological processes. Until now, little is known about their roles in plant drought resistance. Physcomitrella patens is highly tolerant to drought; however, it is not clear about the basic biology of the traits that contribute P. patens this important character. In this work, we discovered 16 drought stress-associated miRNA (DsAmR) families in P. patens through computational analysis. Due to the possible discrepancy of expression periods and tissue distributions between potential DsAmRs and their targeting genes, and the existence of false positive results in computational identification, the prediction results should be examined with further experimental validation. We also constructed an miRNA co-regulation network, and identified two network hubs, miR902a-5p and miR414, which may play important roles in regulating drought-resistance traits. We distributed our results through an online database named ppt-miRBase, which can be accessed at http://bioinfor.cnu.edu.cn/ppt_miRBase/index.php. Our methods in finding DsAmR and miRNA co-regulation network showed a new direction for identifying miRNA functions

Highly robust model of transcription regulator activity predicts breast cancer overall survival

Background: While several multigene signatures are available for predicting breast cancer prognosis, particularly in early stage disease, effective molecular indicators are needed, especially for triple-negative carcinomas, to improve treatments and predict diagnostic outcomes. The objective of this study was to identify transcriptional regulatory networks to better understand mechanisms giving rise to breast cancer development and to incorporate this information into a model for predicting clinical outcomes. Methods: Gene expression profiles from 1097 breast cancer patients were retrieved from The Cancer Genome Atlas (TCGA). Breast cancer-specific transcription regulatory information was identified by considering the binding site information from ENCODE and the top co-expressed targets in TCGA using a nonlinear approach. We then used this information to predict breast cancer patient survival outcome. Result: We built a multiple regulator-based prediction model for breast cancer. This model was validated in more than 5000 breast cancer patients from the Gene Expression Omnibus (GEO) databases. We demonstrated our regulator model was significantly associated with clinical stage and that cell cycle and DNA replication related pathways were significantly enriched in high regulator risk patients. Conclusion: Our findings demonstrate that transcriptional regulator activities can predict patient survival. This finding provides additional biological insights into the mechanisms of breast cancer progression