Evolution of network biomarkers from early to late stage bladder cancer samples

Development of the Mandarin Digit-in-Noise Test and Examination of the Effect of the Number of Digits Used in the Test

OBJECTIVES

The study aimed to develop and validate the Mandarin digit-in-noise (DIN) test using four digit (i.e., two-, three-, four-, and five-digit) sequences. Test-retest reliability and criterion validity were evaluated. How the number of digits affected the results was examined. The research might lead to more informed choice of DIN tests for populations with specific cognitive needs such as memory impairment.

DESIGN

The International Collegium of Rehabilitative Audiology guideline for developing the DIN was adapted to create test materials. The test-retest reliability and psychometric function of each digit sequence were determined among young normal-hearing adults. The criterion validity of each digit sequence was determined by comparing the measured performance of older adult hearing aid users with that obtained from two other well-established sentence-in-noise tests: the Mandarin hearing-in-noise test and the Mandarin Chinese matrix test. The relation between the speech reception thresholds (SRTs) of each digit sequence of the DIN test and working memory capacity measured using the digit span test and the reading span test were explored among older adult hearing aid users. Together, the study sample consisted of 54 young normal-hearing adults and 56 older adult hearing aid users.

RESULTS

The slopes associated with the two-, three-, four-, and five-digit DIN test were 16.58, 18.79, 20.42, and 21.09 %/dB, respectively, and the mean SRTs were -11.11, -10.99, -10.56, and -10.02 dB SNR, respectively. Test-retest SRTs did not differ by more than 0.74 dB across all digit sequences, suggesting good test-retest reliability. Spearman rank-order correlation coefficients between SRTs obtained using the DIN across the four digit (i.e., two-, three-, four-, and five-digit) sequences and the two sentence-in-noise tests were uniformly high ( rs = 0.9) across all participants, when data from all participants were considered. Results from the digit span test and reading span test correlated significantly with the results of the five-digit sequences ( rs = -0.37 and -0.42, respectively) but not with the results of the two-, three-, and four-digit sequences among older hearing aid users.

CONCLUSIONS

While the three-digit sequence was found to be appropriate for clinical use for assessment of auditory perception, the two-digit sequence could be used for hearing screening. The five-digit sequence could be difficult for older hearing aid users, and with its SRT related to working memory capacity, its use in the evaluation of speech perception should be investigated further. The Mandarin DIN test was found to be reliable, and the findings are in line with SRTs obtained using standardized sentence tests, suggesting good criterion validity.

Metallothionein 2A Expression in Cancer-Associated Fibroblasts and Cancer Cells Promotes Esophageal Squamous Cell Carcinoma Progression

Simple Summary

Cancer-associated fibroblasts (CAFs) are tumor promoters in various cancers. We previously reported a correlation between the high expression of the CAF marker fibroblast activation protein and poor prognosis of esophageal squamous cell carcinoma (ESCC). We also found that metallothionein 2A (MT2A) is highly expressed in CAF-like cells that we established. In the current study, we explored the role of MT2A in ESCC progression. MT2A expression in the CAF-like cells induced expression and secretion of insulin-like growth factor binding protein 2 (IGFBP2), which promoted the migration and invasiveness of ESCC cells through the NFκB, Akt, and Erk signaling pathways. Furthermore, MT2A was involved in ESCC cell growth, migration, and invasiveness. Moreover, high expression of MT2A in the cancer tissue correlated with poor prognosis of ESCC patients. Briefly, we demonstrate that MT2A and IGFBP2 are potential novel therapeutic targets in ESCC.

Abstract

Esophageal cancer has the sixth highest mortality rate worldwide. Cancer-associated fibroblasts (CAFs) are involved in the progression of various cancers. Previously, we demonstrated an association between high expression of the CAF marker, fibroblast activation protein, and poor prognosis of esophageal squamous cell carcinoma (ESCC). We also established CAF-like cells by indirect co-culture of bone marrow-derived mesenchymal stem cells with ESCC cell lines and found metallothionein 2A (MT2A) to be highly expressed in them. Here, to explore the function of MT2A in CAFs, we silenced MT2A in the CAF-like cells and ESCC cell lines using small interfering RNA. MT2A knockdown in the CAF-like cells suppressed expression and secretion of insulin-like growth factor binding protein 2 (IGFBP2); recombinant IGFBP2 promoted migration and invasiveness of ESCC cells via NFκB, Akt, and Erk signaling pathways. Furthermore, MT2A knockdown in the ESCC cell lines inhibited their growth, migration, and invasiveness. Immunohistochemistry demonstrated that high MT2A expression in the cancer stroma and cancer nest of ESCC tissues correlated with poor prognosis of ESCC patients. Hence, we report that MT2A in CAFs and cancer cells contributes to ESCC progression. MT2A and IGFBP2 are potential novel therapeutic targets in ESCC.

Overview of Evidence-Based Chemotherapy for Oral Cancer: Focus on Drug Resistance Related to the Epithelial-Mesenchymal Transition

The increasing incidence of resistance to chemotherapeutic agents has become a major issue in the treatment of oral cancer (OC). Epithelial-mesenchymal transition (EMT) has attracted a great deal of attention in recent years with regard to its relation to the mechanism of chemotherapy drug resistance. EMT-activating transcription factors (EMT-ATFs), such as Snail, TWIST, and ZEB, can activate several different molecular pathways, e.g., PI3K/AKT, NF-κB, and TGF-β. In contrast, the activated oncological signal pathways provide reciprocal feedback that affects the expression of EMT-ATFs, resulting in a peritumoral extracellular environment conducive to cancer cell survival and evasion of the immune system, leading to resistance to multiple chemotherapeutic agents. We present an overview of evidence-based chemotherapy for OC treatment based on the National Comprehensive Cancer Network (NCCN) Chemotherapy Order Templates. We focus on the molecular pathways involved in drug resistance related to the EMT and highlight the signal pathways and transcription factors that may be important for EMT-regulated drug resistance. Rapid progress in antitumor regimens, together with the application of powerful techniques such as high-throughput screening and microRNA technology, will facilitate the development of therapeutic strategies to augment chemotherapy.

The Post-Translational Regulation of Epithelial-Mesenchymal Transition-Inducing Transcription Factors in Cancer Metastasis

Epithelial-mesenchymal transition (EMT) is generally observed in normal embryogenesis and wound healing. However, this process can occur in cancer cells and lead to metastasis. The contribution of EMT in both development and pathology has been studied widely. This transition requires the up- and down-regulation of specific proteins, both of which are regulated by EMT-inducing transcription factors (EMT-TFs), mainly represented by the families of Snail, Twist, and ZEB proteins. This review highlights the roles of key EMT-TFs and their post-translational regulation in cancer metastasis.

Feature Selection for Colon Cancer Detection Using K-Means Clustering and Modified Harmony Search Algorithm

This paper proposes a feature selection method that is effective in distinguishing colorectal cancer patients from normal individuals using K-means clustering and the modified harmony search algorithm. As the genetic cause of colorectal cancer originates from mutations in genes, it is important to classify the presence or absence of colorectal cancer through gene information. The proposed methodology consists of four steps. First, the original data are Z-normalized by data preprocessing. Candidate genes are then selected using the Fisher score. Next, one representative gene is selected from each cluster after candidate genes are clustered using K-means clustering. Finally, feature selection is carried out using the modified harmony search algorithm. The gene combination created by feature selection is then applied to the classification model and verified using 5-fold cross-validation. The proposed model obtained a classification accuracy of up to 94.36%. Furthermore, on comparing the proposed method with other methods, we prove that the proposed method performs well in classifying colorectal cancer. Moreover, we believe that the proposed model can be applied not only to colorectal cancer but also to other gene-related diseases.

Anti-Cancer Effects of Glaucarubinone in the Hepatocellular Carcinoma Cell Line Huh7 via Regulation of the Epithelial-To-Mesenchymal Transition-Associated Transcription Factor Twist1

Hepatocellular carcinoma (HCC), the most common type of liver cancer, is a leading cause of cancer-related deaths. As HCC has a high mortality rate and its incidence is increasing worldwide, understanding and treating HCC are crucial for resolving major public health concerns. In the present study, wound healing screening assays were performed using natural product libraries to identify natural chemicals that can inhibit cancer cell migration. Glaucarubinone (GCB) showed a high potential for inhibiting cell migration. The anti-cancer effects of GCB were evaluated using the HCC cell line, Huh7. GCB showed anti-cancer effects, as verified by wound healing, cell migration, invasion, colony formation, and three-dimensional spheroid invasion assays. In addition, cells treated with GCB showed suppressed matrix metalloproteinase activities. Immunoblotting analyses of intracellular signaling pathways revealed that GCB regulated the levels of Twist1, a crucial transcription factor associated with epithelial-to-mesenchymal transition, and mitogen-activated protein kinase. The invasive ability of cancer cells was found to be decreased by the regulation of Twist1 protein levels. Furthermore, GCB downregulated phosphorylation of extracellular signal-regulated kinase. These results indicate that GCB exhibits anti-metastatic properties in Huh7 cells, suggesting that it could be used to treat HCC.

Competing Endogenous RNA Networks in the Epithelial to Mesenchymal Transition in Diffuse-Type of Gastric Cancer

Simple Summary

The diffuse-type of gastric cancer is associated with epithelial to mesenchymal transition. Loss of E-cadherin expression is the hallmark of this process and is largely due to the upregulation of the transcription factors ZEB1/2, Snail, Slug, and Twist1/2. However, miRNA and lncRNAs can also participate through these transcription factors which directly target E-cadherin. The competing endogenous RNA (ceRNA) network hypothesis state that lncRNA can sponge the miRNA pool that targets these transcripts. Based on the lack of said networks in the epithelial to mesenchymal transition, we performed a prediction analysis that resulted in novel ceRNA networks which will expand our knowledge of the molecular basis of the diffuse-type of gastric cancer.

Abstract

The diffuse-type of gastric cancer (DGC), molecularly associated with epithelial to mesenchymal transition (EMT), is increasing in incidence. Loss of E-cadherin expression is the hallmark of the EMT process and is largely due to the upregulation of the EMT-inducing transcription factors ZEB1/2, Snail, Slug, and Twist1/2. However, ncRNA, such as miRNA and lncRNAs, can also participate in the EMT process through the direct targeting of E-cadherin and other EMT-inducing transcription factors. Additionally, lncRNA can sponge the miRNA pool that targets these transcripts through competing endogenous RNA (ceRNA) networks. In this review, we focus on the role of ncRNA in the direct deregulation of E-cadherin, as well as EMT-inducing transcription factors. Based on the relevance of the ceRNA network hypothesis, and the lack of said networks in EMT, we performed a prediction analysis for all miRNAs and lncRNAs that target E-cadherin, as well as EMT-inducing transcription factors. This analysis resulted in novel predicted ceRNA networks for E-cadherin and EMT-inducing transcription factors (EMT-TFs), as well as the expansion of the molecular basis of the DGC.

DNA Methylome Distinguishes Head and Neck Cancer from Potentially Malignant Oral Lesions and Healthy Oral Mucosa

There is a strong need to find new, good biomarkers of head and neck squamous cell carcinoma (HNSCC) because of the bad prognoses and high mortality rates. The aim of this study was to identify the potential biomarkers in HNSCC that have differences in their DNA methylome and potentially premalignant oral lesions, in comparison to healthy oral mucosa. In this study, 32 oral samples were tested: nine healthy oral mucosae, 13 HNSCC, and 10 oral lesions for DNA methylation by the Infinium MethylationEPIC BeadChip. Our findings showed that a panel of genes significantly hypermethylated in their promoters or specific sites in HNSCC samples in comparison to healthy oral samples, which are mainly oncogenes, receptor, and transcription factor genes, or genes included in cell cycle, transformation, apoptosis, and autophagy. A group of hypomethylated genes in HNSCC, in comparison to healthy oral mucosa, are mainly involved in the host immune response and transcriptional regulation. The results also showed significant differences in gene methylation between HNSCC and potentially premalignant oral lesions, as well as differently methylated genes that discriminate between oral lesions and healthy mucosa. The given methylation panels point to novel potential biomarkers for early diagnostics of HNSCC, as well as potentially premalignant oral lesions.

A randomised controlled trial of hearing and vision support in dementia: Protocol for a process evaluation in the SENSE-Cog trial

BACKGROUND

Optimising hearing and vision function may be important in improving a range of outcomes for people living with dementia (PwD) and their companions. The SENSE-Cog cross-national randomised controlled trial (RCT) is evaluating the effectiveness of a sensory intervention (SI) to improve quality of life for PwD with concurrent hearing and/or vision impairment, in five European countries. To ascertain how or why the intervention will, or will not, achieve its outcomes, we have designed a process evaluation to explore potential discrepancies between expected and observed outcomes. This will also help us to understand how context may influence the outcomes. Here we describe the protocol for this process evaluation, which is embedded within the RCT.

METHODS/DESIGN

We will use a mixed methods approach with a theoretical framework derived from the UK Medical Research Council's' guidance on process evaluations. It will include the following: (1) evaluating how key aspects of the intervention will be delivered, which will be important to scale the intervention in real world populations; (2) characterising the contextual issues, which may shape the delivery and the impact of the intervention in different countries; and (3) investigating possible causal mechanisms through analyses of potential moderators and mediators. To avoid bias, we will analyse the process data before the analysis of the main effectiveness outcomes.

DISCUSSION

This evaluation will provide insight into how the complex SENSE-Cog SI will be tailored, enacted and received across the different European contexts, all of which have unique health and social care economies. The findings will provide insight into the causal mechanisms effecting change, and will determine whether we should implement the intervention, if effective, on a wider scale for PwD and concurrent sensory impairment.

TRIAL REGISTRATION

ISRCTN, ISRCTN17056211. Registered on 19 February 2018.

Molecular characterization of papillary thyroid carcinoma: a potential three-lncRNA prognostic signature

Purpose

Papillary thyroid carcinoma (PTC), the most frequent type of malignant thyroid tumor, lacks novel and reliable biomarkers of patients’ prognosis. In the current study, we mined The Cancer Genome Atlas (TCGA) to develop lncRNA signature of PTC.

Patients and methods

The intersection of PTC lncRNAs was obtained from the TCGA database using integrative computational method. By the univariate and multivariate Cox analysis, key lncRNAs were identified to construct the prognostic model. Then, all patients were divided into the high-risk group and low-risk group to perform the Kaplan–Meier (K–M) survival curves and time-dependent receiver operating characteristic (ROC) curve, estimating the prognostic power of the prognostic model. Functional enrichment analysis was also performed. Finally, we verified the results of the TCGA analysis by the Gene Expression Omnibus (GEO) databases and quantitative real-time PCR (qRT-PCR).

Results

After the comprehensive analysis, a three-lncRNA signature (PRSS3P2, KRTAP5-AS1 and PWAR5) was obtained. Interestingly, patients with low-risk scores tended to gain obviously longer survival time, and the area under the time-dependent ROC curve was 0.739. Furthermore, gene ontology (GO) and pathway analysis revealed the tumorigenic and prognostic function of the three lncRNAs. We also found three potential transcription factors to help understand the mechanisms of the PTC-specific lncRNAs. Finally, the GEO databases and qRT-PCR validation were consistent with our TCGA bioinformatics results.

Conclusion

We built a three-lncRNA signature by mining the TCGA database, which could effectively predict the prognosis of PTC.

Examining the key genes and pathways in hepatocellular carcinoma development from hepatitis B virus‑positive cirrhosis

To identify the key genes and pathways in the development of hepatocellular carcinoma (HCC) from hepatitis B virus (HBV)-positive liver cirrhosis, differentially expressed genes (DEGs) between HCC and liver cirrhosis tissue samples from the GSE17548 gene expression profile dataset were screened. A total of 1,845 DEGs were identified, including 1,803 upregulated and 42 downregulated genes. Gene Ontology, Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein-protein interaction (PPI) network analyses were performed. It was identified that the ‘cell cycle’ and ‘progesterone-mediated oocyte maturation’ KEGG pathways were significantly enriched in the DEGs. In addition, the high expression of the hub genes from the PPI network (including cyclin dependent kinase 1, cyclin B1, cyclin B2, mitotic arrest deficient 2 like 1, BUB1 mitotic checkpoint serine/threonine kinase and cyclin A2; P=0.00116, 0.00021, 0.04889, 0.00222, 0.00015 and 0.00647, respectively) was associated with a decrease in overall survival for patients with HCC as identified using survival and expression data from The Cancer Genome Atlas. The identified hub genes and pathways may help to elucidate the molecular mechanisms of HCC progression from HBV-positive liver cirrhosis. Additionally, they may be useful as therapeutic targets or serve as novel biomarkers for HCC prognosis prediction.

Identifying network-based biomarkers of complex diseases from high-throughput data

In this work, we review the main available computational methods of identifying biomarkers of complex diseases from high-throughput data. The emerging omics techniques provide powerful alternatives to measure thousands of molecules in cells in parallel manners. The generated genomic, transcriptomic, proteomic, metabolomic and phenomic data provide comprehensive molecular and cellular information for detecting critical signals served as biomarkers by classifying disease phenotypic states. Networks are often employed to organize these profiles in the identification of biomarkers to deal with complex diseases in diagnosis, prognosis and therapy as well as mechanism deciphering from systematic perspectives. Here, we summarize some representative network-based bioinformatics methods in order to highlight the importance of computational strategies in biomarker discovery.

Temporal Genetic Modifications after Controlled Cortical Impact--Understanding Traumatic Brain Injury through a Systematic Network Approach

Traumatic brain injury (TBI) is a primary injury caused by external physical force and also a secondary injury caused by biological processes such as metabolic, cellular, and other molecular events that eventually lead to brain cell death, tissue and nerve damage, and atrophy. It is a common disease process (as opposed to an event) that causes disabilities and high death rates. In order to treat all the repercussions of this injury, treatment becomes increasingly complex and difficult throughout the evolution of a TBI. Using high-throughput microarray data, we developed a systems biology approach to explore potential molecular mechanisms at four time points post-TBI (4, 8, 24, and 72 h), using a controlled cortical impact (CCI) model. We identified 27, 50, 48, and 59 significant proteins as network biomarkers at these four time points, respectively. We present their network structures to illustrate the protein–protein interactions (PPIs). We also identified UBC (Ubiquitin C), SUMO1, CDKN1A (cyclindependent kinase inhibitor 1A), and MYC as the core network biomarkers at the four time points, respectively. Using the functional analytical tool MetaCore™, we explored regulatory mechanisms and biological processes and conducted a statistical analysis of the four networks. The analytical results support some recent findings regarding TBI and provide additional guidance and directions for future research.

Identification of network-based biomarkers of cardioembolic stroke using a systems biology approach with time series data

BACKGROUND

Molecular signaling of angiogenesis begins within hours after initiation of a stroke and the following regulation of endothelial integrity mediated by growth factor receptors and vascular growth factors. Recent studies further provided insights into the coordinated patterns of post-stroke gene expressions and the relationships between neurodegenerative diseases and neural function recovery processes after a stroke.

RESULTS

Differential protein-protein interaction networks (PPINs) were constructed at 3 post-stroke time points, and proteins with a significant stroke relevance value (SRV) were discovered. Genes, including UBC, CUL3, APP, NEDD8, JUP, and SIRT7, showed high associations with time after a stroke, and Ingenuity Pathway Analysis results showed that these post-stroke time series-associated genes were related to molecular and cellular functions of cell death, cell survival, the cell cycle, cellular development, cellular movement, and cell-to-cell signaling and interactions. These biomarkers may be helpful for the early detection, diagnosis, and prognosis of ischemic stroke.

CONCLUSIONS

This is our first attempt to use our theory of a systems biology framework on strokes. We focused on 3 key post-stroke time points. We identified the network and corresponding network biomarkers for the 3 time points, further studies are needed to experimentally confirm the findings and compare them with the causes of ischemic stroke. Our findings showed that stroke-associated biomarker genes at different time points were significantly involved in cell cycle processing, including G2-M, G1-S and meiosis, which contributes to the current understanding of the etiology of stroke. We hope this work helps scientists reveal more hidden cellular mechanisms of stroke etiology and repair processes.

Applying NGS Data to Find Evolutionary Network Biomarkers from the Early and Late Stages of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a major liver tumor (~80%), besides hepatoblastomas, angiosarcomas, and cholangiocarcinomas. In this study, we used a systems biology approach to construct protein-protein interaction networks (PPINs) for early-stage and late-stage liver cancer. By comparing the networks of these two stages, we found that the two networks showed some common mechanisms and some significantly different mechanisms. To obtain differential network structures between cancer and noncancer PPINs, we constructed cancer PPIN and noncancer PPIN network structures for the two stages of liver cancer by systems biology method using NGS data from cancer cells and adjacent noncancer cells. Using carcinogenesis relevance values (CRVs), we identified 43 and 80 significant proteins and their PPINs (network markers) for early-stage and late-stage liver cancer. To investigate the evolution of network biomarkers in the carcinogenesis process, a primary pathway analysis showed that common pathways of the early and late stages were those related to ordinary cancer mechanisms. A pathway specific to the early stage was the mismatch repair pathway, while pathways specific to the late stage were the spliceosome pathway, lysine degradation pathway, and progesterone-mediated oocyte maturation pathway. This study provides a new direction for cancer-targeted therapies at different stages.