Combinations of gene ontology and pathway characterize and predict prognosis genes for recurrence of gastric cancer after surgery

A Novel Prediction of Quaternary Structural Type of Proteins with Gene Ontology

BACKGROUND

The information of quaternary structure attributes of proteins is very important because it is closely related to the biological functions of proteins. With the rapid development of new generation sequencing technology, we are facing a challenge: how to automatically identify the four-level attributes of new polypeptide chains according to their sequence information (i.e., whether they are formed as just as a monomer, or as a hetero-oligomer, or a homo-oligomer).

OBJECTIVE

In this article, our goal is to find a new way to represent protein sequences, thereby improving the prediction rate of protein quaternary structure.

METHODS

In this article, we developed a prediction system for protein quaternary structural type in which a protein sequence was expressed by combining the Pfam functional-domain and gene ontology. turn protein features into digital sequences, and complete the prediction of quaternary structure through specific machine learning algorithms and verification algorithm.

RESULTS

Our data set contains 5495 protein samples. Through the method provided in this paper, we classify proteins into monomer, or as a hetero-oligomer, or a homo-oligomer, and the prediction rate is 74.38%, which is 3.24% higher than that of previous studies. Through this new feature extraction method, we can further classify the four-level structure of proteins, and the results are also correspondingly improved.

CONCLUSION

After the applying the new prediction system, compared with the previous results, we have successfully improved the prediction rate. We have reason to believe that the feature extraction method in this paper has better practicability and can be used as a reference for other protein classification problems.

Replication-dependent histone isoforms: a new source of complexity in chromatin structure and function

Replication-dependent histones are expressed in a cell cycle regulated manner and supply the histones necessary to support DNA replication. In mammals, the replication-dependent histones are encoded by a family of genes that are located in several clusters. In humans, these include 16 genes for histone H2A, 22 genes for histone H2B, 14 genes for histone H3, 14 genes for histone H4 and 6 genes for histone H1. While the proteins encoded by these genes are highly similar, they are not identical. For many years, these genes were thought to encode functionally equivalent histone proteins. However, several lines of evidence have emerged that suggest that the replication-dependent histone genes can have specific functions and may constitute a novel layer of chromatin regulation. This Survey and Summary reviews the literature on replication-dependent histone isoforms and discusses potential mechanisms by which the small variations in primary sequence between the isoforms can alter chromatin function. In addition, we summarize the wealth of data implicating altered regulation of histone isoform expression in cancer.

A feature-based analysis identifies COL1A2 as a regulator in pancreatic cancer

This study aimed to identify genetic biomarkers in pancreatic cancer (PC) and explore its function in PC via a feature-base analysis of bioinformatics. OMIM and DisGeNET databases discovered 209 PC connected genes and then 516 connected genes were identified. We selected 29 genes according to optimal features and chose COL1A2, which had the highest expression, for the following experiment. The expression of COL1A2 was determined by qRT-PCR; cell proliferation was determined by MTT assay; migration and invasion after COL1A2 and miR-25-3p transfection was evaluated by Transwell assay. COL1A2 presented the highest expression in PC tissues, which was validated in functional experiments. MiR-25-3p suppressed the expression of COL1A2 in cell lines and inhibited migration, invasion and proliferation of PC cells. MiR-25-3p could suppress the expression of COL1A2 and inhibit the proliferation, migration and invasion of PC cells which provided a new idea for the detection and treatment of PC.

Overexpression of long noncoding RNA HOTTIP promotes tumor invasion and predicts poor prognosis in gastric cancer

Purpose

Long noncoding RNAs have been proved to play important roles in the tumorigenesis and development of human gastric cancer (GC). Our study aims to investigate the expression and function of Homeobox A transcript at the distal tip (HOTTIP) in GC.

Methods

HOTTIP expression was detected in GC tissues and cell lines by using quantitative reverse transcription polymerase chain reaction. Association between HOTTIP levels and clinicopathological factors and patient prognosis was also analyzed. MTT, flow cytometry, and transwell invasion and migration assays were used to investigate the role of HOTTIP in the regulation of biological behaviors of GC cells.

Results

HOTTIP expression was remarkably increased in GC tissues and cell lines compared with that in the normal control. Clinicopathologic analysis revealed that high HOTTIP expression correlated with larger tumor size, deeper invasion depth, positive lymph node metastasis, advanced TNM stage, and shorter overall survival. Multivariate regression analysis identified HOTTIP overexpression as an independent unfavorable prognostic factor in GC patients. Moreover, HOTTIP downregulation by si-HOTTIP transfection impaired GC cell proliferation, promoted cell apoptosis, and reduced cell invasion and migration.

Conclusion

These findings suggested that HOTTIP may contribute to GC initiation and progression, and would be not only a novel prognostic marker but also a potential therapeutic target for this disease.

Decreased miR-198 expression and its prognostic significance in human gastric cancer

Background

MicroRNAs (miRNAs) have been proved to play important roles in the tumorigenesis and development of human gastric cancer (GC). Our study aims to investigate the expression and clinical significance of miR-198 in GC patients.

Methods

Quantitative real-time polymerase chain reaction (RT-PCR) was performed to evaluate miR-198 levels in 106 pairs of GC specimens and adjacent noncancerous tissues. Then, the associations of miR-198 expression with clinicopathological factors and patient’s survival were determined.

Results

The expression levels of miR-198 in GC tissues were significantly lower than those in corresponding noncancerous tissues (p < 0.01). Decreased miR-198 expression was significantly associated with larger tumor size, deeper invasion depth, positive lymph node metastasis, advanced tumor-node-metastasis (TNM) stage, and shorter overall survival. Moreover, multivariate regression analysis identified low miR-198 expression as an independent predictor of poor survival.

Conclusions

These findings suggested that miR-198 downregulation may be associated with progression of GC and that this miR may be an independent prognostic marker for GC patients.

Differential expression profiles of long non-coding RNAs reveal potential biomarkers for identification of human gastric cancer

Gastric cancer (GC) is one of the most lethal malignancies worldwide. To reduce its high mortality, sensitive and specific biomarkers for early detection are urgently needed. Recent studies have reported that tumor-specific long non-coding RNAs (lncRNAs) seem to be potential biomarkers for the early diagnosis and treatment of cancer. In the present study, lncRNA and mRNA expression profiling of GC specimens and their paired adjacent non-cancerous tissues was performed. Differentially expressed lncRNAs and mRNAs were identified through microarray analysis. The function of differential mRNA was determined by gene ontology and pathway analysis and the functions of lncRNAs were studied by constructing a co-expression network to find the relationships with corresponding mRNAs. We connected the co-expression network, mRNA functions, and the results of the microarray profile differential expression and selected 14 significantly differentially expressed key lncRNAs and 21 key mRNAs. Quantitative RT-PCR (qRT-PCR) was conducted to verify these key RNAs in 50 newly diagnosed GC patients. The data showed that RP5-919F19, CTD-2541M15 and UCA1 was significantly higher expressed. AP000459, LOC101928316, RP11-167N4 and LINC01071 expression was significantly lower in 30 advanced GC tumor tissues than adjacent non-tumor tissues P<0.05. Then, we further validated the above significant differential expression candidate lncRNAs in 20 early stage GC patients. Results showed that CTD-2541M15 and UCA1 were significantly higher expressed, AP000459, LINC01071 and MEG3 expression was significantly lower in 20 early stage GC patient tumor tissues than adjacent non-tumor tissues (P<0.05). In addition, expression of these lncRNAs shows gradual upward trend from early stage GC to advanced GC. Furthermore, conditional logistic regression analysis revealed the aberrant expression of CTD-2541M15, UCA1 and MEG3 closely linked with GC. There is a set of differentially expressed lncRNAs in GC which may be associated with the progression and development of GC. The differential expression profiles of lncRNAs in GC may be promising biomarkers for the early detection and early screening of high‑risk populations.