E2F transcription factor 1 overexpression as a poor prognostic factor in patients with nasopharyngeal carcinomas

AbstractNasopharyngeal carcinoma (NPC) is an endemic head and neck epithelial malignancy in Southeastern Asia and Taiwan. The E2 factor (E2F) family of transcription factors is downstream targets of the retinoblastoma protein 1. The E2F family of transcription factors is the key regulator of genes involved in cell cycle progression, cell fate determination, DNA damage repair and apoptosis. E2F1 is unique in that it contributes both to the control of cellular proliferation and cellular death. However, the expression of E2F1 protein and its clinicopathological associations in patients with NPC are yet to be evaluated. Immunoexpression of E2F1 was retrospectively assessed in biopsies of 124 consecutive NPC patients without initial distant metastasis and treated with consistent guidelines. The outcomes were correlated with clinicopathological features and patient survivals. Results indicated that high E2F1 protein level (50%) was correlated with primary tumor (p < 0.001) and stage (p = 0.002; 7th American Joint Committee on Cancer). In multivariate analyses, high E2F1 expression emerged as an independent prognosticator for worse disease-specific survival (p = 0.003), distal metastasis-free survival (p = 0.003), and local recurrence-free survival (p = 0.039). In conclusion, high E2F1 protein level is common, associated with adverse prognosticators, and might confer tumor aggressiveness through tumor cell proliferation and metastasis

A Comparative Gene Map of the Horse (Equus caballus)

A comparative gene map of the horse genome composed of 127 loci was assembled based on the new assignment of 68 equine type I loci and on data published previously. PCR primers based on consensus gene sequences conserved across mammalian species were used to amplify markers for assigning 68 equine type I loci to 27 horse synteny groups established previously with a horse-mouse somatic cell hybrid panel (SCHP, UC Davis). This increased the number of coding genes mapped to the horse genome by over 2-fold and allowed refinements of the comparative mapping data available for this species. In conjunction with 57 previous assignments of type I loci to the horse genome map, these data have allowed us to confirm the assignment of 24 equine synteny groups to their respective chromosomes, to provisionally assign nine synteny groups to chromosomes, and to further refine the genetic composition established with Zoo-FISH of two horse chromosomes. The equine type I markers developed in this study provide an important resource for the future development of the horse linkage and physical genome maps

The biological impacts of CEBPD on urothelial carcinoma development and progression

Urothelial carcinoma (UC), which includes urinary bladder urothelial carcinoma (UBUC) and upper tract urothelial carcinoma (UTUC), is one of the most common malignancies worldwide. Accordingly, a comprehensive understanding of the underlying mechanism governing UC development is compulsory. Aberrant CCAAT/enhancer-binding protein delta (CEBPD), a transcription factor, displays an oncogene or tumor suppressor depending on tumor type and microenvironments. However, CEBPD has been reported to possess a clear oncogenic function in UC through multiple regulation pathways. Genomic amplification of CEBPD triggered by MYC-driven genome instability is frequently examined in UC that drives CEBPD overexpression. Upregulated CEBPD transcriptionally suppresses FBXW7 to stabilize MYC protein and further induces hexokinase II (HK2)-related aerobic glycolysis that fuels cell growth. Apart from the MYC-dependent pathway, CEBPD also downregulates the level of hsa-miR-429 to enhance HK2-associated glycolysis and induce angiogenesis driven by vascular endothelial growth factor A (VEGFA). Additionally, aggressive UC is attributed to the tumor metastasis regulated by CEBPD-induced matrix metalloproteinase-2 (MMP2) overexpression. Furthermore, elevated CEBPD induced by cisplatin (CDDP) is identified to have dual functions, namely, CDDP-induced chemotherapy resistance or drive CDDP-induced antitumorigenesis. Given that the role of CEBPD in UC is getting clear but pending a more systemic reappraisal, this review aimed to comprehensively discuss the underlying mechanism of CEBPD in UC tumorigenesis

REG3A overexpression functions as a negative predictive and prognostic biomarker in rectal cancer patients receiving CCRT

Background. Concurrent chemoradiotherapy (CCRT) is suggested before resection surgery in the control of rectal cancer. Unfortunately, treatment outcomes are widely variable and highly patientspecific. Notably, rectal cancer patients with distant metastasis generally have a much lower survival rate. Accordingly, a better understanding of the genetic background of patient cohorts can aid in predicting CCRT efficacy and clinical outcomes for rectal cancer before distant metastasis. Methods. A published transcriptome dataset (GSE35452) (n=46) was utilized to distinguish prospective genes concerning the response to CCRT. We recruited 172 rectal cancer patients, and the samples were collected during surgical resection after CCRT. Immunohistochemical (IHC) staining was performed to evaluate the expression level of regenerating family member 3 alpha (REG3A). Pearson's chi-squared test appraised the relevance of REG3A protein expression to clinicopathological parameters. The Kaplan-Meier method was utilized to generate survival curves, and the log-rank test was performed to compare the survival distributions between two given groups. Results. Employing a transcriptome dataset (GSE35452) and focusing on the inflammatory response (GO: 0006954), we recognized that REG3A is the most significantly upregulated gene among CCRT nonresponders (log2 ratio=1.2472, p=0.0079). Following IHC validation, high immunoexpression of REG3A was considerably linked to advanced post-CCRT tumor status (p<0.001), post-CCRT lymph node metastasis (p=0.042), vascular invasion (p=0.028), and low-grade tumor regression (p=0.009). In the multivariate analysis, high immunoexpression of REG3A was independently correlated with poor disease-specific survival (DSS) (p=0.004) and metastasis-free survival (MeFS) (p=0.045). The results of the bioinformatic analysis also supported the idea that REG3A overexpression is implicated in rectal carcinogenesis. Conclusion. In the current study, we demonstrated that REG3A overexpression is correlated with poor CCRT effectiveness and inferior patient survival in rectal cancer. The predictive and prognostic utility of REG3A expression may direct patient stratification and decisionmaking more accurately for those patients

HuR cytoplasmic expression is associated with increased cyclin A expression and poor outcome with upper urinary tract urothelial carcinoma

BACKGROUND: HuR is an RNA-binding protein that post-transcriptionally modulates the expressions of various target genes implicated in carcinogenesis, such as CCNA2 encoding cyclin A. No prior study attempted to evaluate the significance of HuR expression in a large cohort with upper urinary tract urothelial carcinomas (UTUCs). METHODS: In total, 340 cases of primary localized UTUC without previous or concordant bladder carcinoma were selected. All of these patients received ureterectomy or radical nephroureterectomy with curative intents. Pathological slides were reviewed, and clinical findings were collected. Immunostaining for HuR and cyclin A was performed and evaluated by using H-score. The results of cytoplasmic HuR and nuclear cyclin A expressions were correlated with disease-specific survival (DSS), metastasis-free survival (MeFS), urinary bladder recurrence-free survival (UBRFS), and various clinicopathological factors. RESULTS: HuR cytoplasmic expression was significantly related to the pT status, lymph node metastasis, a higher histological grade, the pattern of invasion, vascular and perineurial invasion, and cyclin A expression (p = 0.005). Importantly, HuR cytoplasmic expression was strongly associated with a worse DSS (p < 0.0001), MeFS (p < 0.0001), and UBRFS (p = 0.0370) in the univariate analysis, and the first two results remained independently predictive of adverse outcomes (p = 0.038, relative risk [RR] = 1.996 for DSS; p = 0.027, RR = 1.880 for MeFS). Cyclin A nuclear expression was associated with a poor DSS (p = 0.0035) and MeFS (p = 0.0015) in the univariate analysis but was not prognosticatory in the multivariate analyses. High-risk patients (pT3 or pT4 with/without nodal metastasis) with high HuR cytoplasmic expression had better DSS if adjuvant chemotherapy was performed (p = 0.015). CONCLUSIONS: HuR cytoplasmic expression was correlated with adverse phenotypes and cyclin A overexpression and also independently predictive of worse DSS and MeFS, suggesting its roles in tumorigenesis or carcinogenesis and potentiality as a prognostic marker of UTUC. High HuR cytoplasmic expression might identify patients more likely to be beneficial for adjuvant chemotherapy

Detection of the inferred interaction network in hepatocellular carcinoma from EHCO (Encyclopedia of Hepatocellular Carcinoma genes Online)

BACKGROUND: The significant advances in microarray and proteomics analyses have resulted in an exponential increase in potential new targets and have promised to shed light on the identification of disease markers and cellular pathways. We aim to collect and decipher the HCC-related genes at the systems level. RESULTS: Here, we build an integrative platform, the Encyclopedia of Hepatocellular Carcinoma genes Online, dubbed EHCO , to systematically collect, organize and compare the pileup of unsorted HCC-related studies by using natural language processing and softbots. Among the eight gene set collections, ranging across PubMed, SAGE, microarray, and proteomics data, there are 2,906 genes in total; however, more than 77% genes are only included once, suggesting that tremendous efforts need to be exerted to characterize the relationship between HCC and these genes. Of these HCC inventories, protein binding represents the largest proportion (~25%) from Gene Ontology analysis. In fact, many differentially expressed gene sets in EHCO could form interaction networks (e.g. HBV-associated HCC network) by using available human protein-protein interaction datasets. To further highlight the potential new targets in the inferred network from EHCO, we combine comparative genomics and interactomics approaches to analyze 120 evolutionary conserved and overexpressed genes in HCC. 47 out of 120 queries can form a highly interactive network with 18 queries serving as hubs. CONCLUSION: This architectural map may represent the first step toward the attempt to decipher the hepatocarcinogenesis at the systems level. Targeting hubs and/or disruption of the network formation might reveal novel strategy for HCC treatment

Multi-Omics Analyses to Identify FCGBP as a Potential Predictor in Head and Neck Squamous Cell Carcinoma

(Purpose) Previous studies have pointed out the significance of IgG Fc binding protein (FCGBP) in carcinogenesis, cancer progression, and tumor immunity in certain malignancies. However, its prognostic values, molecular interaction, and immune characteristics in the head and neck squamous cell carcinoma (HNSC) remained unclear. (Methods) To evaluate the potential role of the FCGBP gene, we used GEPIA2 and UALCAN platforms to explore the differential levels, survivals, and genetic alteration through cBioPortal (based on The Cancer Genome Atlas dataset). STRING, GeneMania, and TIMER2.0 identified the interacting networks. LinkedOmics performed Gene enrichment analysis, and TISIDB and TIMER2.0 evaluated the role of FCGBP in the tumor microenvironment. (Results) The expression level of FCGBP is lower in cancer tissues. A high FCGBP level is significantly associated with better overall- and disease-specific-survivals, regardless of human papillomavirus infection. Low FCGBP levels correlated to a higher tumor protein p53 (TP53) mutation rate (p = 0.018). FCGBP alteration significantly co-occurred with that of TP53 (q = 0.037). Interacting networks revealed a significant association between FGFBP and trefoil factor 3 (TFF3), a novel prognostic marker in various cancers, at transcriptional and translational levels. Enrichment analyses identified that the top gene sets predominantly related to immune and inflammatory responses. Further investigation found that the FCGBP mRNA level positively correlated to the infiltration rates of B cells, Th17/CD8+ T lymphocytes, T helper follicular cells, mast cells, and expression levels of various immune molecules and immune checkpoints in HNSC. (Conclusions) We found that the FCGBP mRNA level negatively correlated to TP53 mutation status while positively correlated to the TFF3 level. Additionally, FCGBP may regulate the tumor microenvironment. These findings support the FCGBP as a potential biomarker to estimate HNSC prognoses

Abstract Algorithms for Promoter Prediction in DNA Sequences

Nowadays, the prediction of promoters has attracted many researchers ’ attention. Unfortunately, most previous prediction algorithms did not provide high enough sensitivity and specificity. The goal of this paper is to develop an efficient prediction algorithm that can increase the detection power (power = 1- false negative). We present two methods that use the computer power to calculate all possible patterns which are the possible features of promoters. The first method we present FTSS (Fixed Transcriptional Start Site) uses the known TSS positions of promoter sequences to train the score file that helps us in promoter prediction. The other method is NTSS (Nonfixed TSS). The TSS positions of promoter sequences used in NTSS are assumed to be unknown, and NTSS will not take the absolute positions of TSSs into consideration. By the experimental results, our prediction has higher correct rate than other previous methods

The Design of Sorters Based on DNA for Bio-Computers

devoted to the study of molecular computing based on DNA in order to implement algorithms for solving some NP-complete problems and simulate logic gates in silicon-based computers. A great deal of effort has been made on using DNA to implement simple logic gates, such as simple 1-bit comparators and simple adders, or to solve NP-complete problems, such as the Hamiltonian path problem, the travelling salesperson problem and the satisfiability problem. All of the methods rely on the capability of DNA computing which could perform computation in huge parallelism to produce all possible solutions where the answer may be derived from. In this paper, we will first design a full bit-serial comparator that can perform the feedback operation. Then, we will design a word-parallel bit-serial sorter which uses our comparators as the elementary building components. Our design of sorters can be applied to any sorting network, such as bitonic sorter and odd-even merge sorter

Primer set selection in multiple pcr experiments

The selection of a suitable set of primers is crucial to the multiple PCR (polymerase chain reaction) experiment, which is one of the most important techniques in molecular biology. The minimum primer set (MPS) problem is to minimize the number of primers required to amplify a set of DNA sequences, so that the experimental costs and time will be reduced. However, the MPS problem has been proved to be NP-complete. In this paper, we propose an efficient heuristic algorithm for solving the MPS problem. In our algorithm, the kernel procedure is to choose a set of possible good primer candidates, each may be able to amplify more than one target DNA sequence. The kernel procedure is accomplished by the local motif finding method, which is based on the combination of the Gibbs sampler method, the ant colony optimization (ACO) strategy, and Liao’s algorithm for finding motifs. We add a new weight parameter to the method, which can guide us to find local motifs with the local view. Then, the complementary sequences of those local motifs (possible primer candidates) are input into the binary integer programming for getting the near optimal set. With the concept of possible primer candidates, the size of the solution space in the binary integer programming can be reduced drastically. We perform experiments on some artificial domains and two gene families. The experimental results show that the time required for our algorithm is reduced drastically, while the performance of our algorithm is comparable to that obtained by the exhaustive search