Micro-proteome analysis using micro-chromatofocusing in intact protein separations

The high-density lipoprotein binding protein HDLBP is an unusual RNA-binding protein with multiple roles in cancer and disease

The high-density lipoprotein binding protein (HDLBP) is the human member of an evolutionarily conserved family of RNA-binding proteins, the vigilin protein family. These proteins are characterized by 14 or 15 RNA-interacting KH (heterologous nuclear ribonucleoprotein K homology) domains. While mainly present at the cytoplasmic face of the endoplasmic reticulum, HDLBP and its homologs are also found in the cytosol and nucleus. HDLBP is involved in various processes, including translation, chromosome segregation, cholesterol transport and carcinogenesis. Especially, its association with the latter two has attracted specific interest in the HDLBP's molecular role. In this review, we give an overview of some of the functions of the protein as well as introduce its impact on different kinds of cancer, its connection to lipid metabolism and its role in viral infection. We also aim at addressing the possible use of HDLBP as a drug target or biomarker and discuss its future implications.

Prognostic value of a novel glycolysis-related gene expression signature for gastrointestinal cancer in the Asian population

BACKGROUND

Globally, gastrointestinal (GI) cancer is one of the most prevalent malignant tumors. However, studies have not established glycolysis-related gene signatures that can be used to construct accurate prognostic models for GI cancers in the Asian population. Herein, we aimed at establishing a novel glycolysis-related gene expression signature to predict the prognosis of GI cancers.

METHODS

First, we evaluated the mRNA expression profiles and the corresponding clinical data of 296 Asian GI cancer patients in The Cancer Genome Atlas (TCGA) database (TCGA-LIHC, TCGA-STAD, TCGA-ESCA, TCGA-PAAD, TCGA-COAD, TCGA-CHOL and TCGA-READ). Differentially expressed mRNAs between GI tumors and normal tissues were investigated. Gene Set Enrichment Analysis (GSEA) was performed to identify glycolysis-related genes. Then, univariate, LASSO regression and multivariate Cox regression analyses were performed to establish a key prognostic glycolysis-related gene expression signature. The Kaplan-Meier and receiver operating characteristic (ROC) curves were used to evaluate the efficiency and accuracy of survival prediction. Finally, a risk score to predict the prognosis of GI cancers was calculated and validated using the TCGA data sets. Furthermore, this risk score was verified in two Gene Expression Omnibus (GEO) data sets (GSE116174 and GSE84433) and in 28 pairs of tissue samples.

RESULTS

Prognosis-related genes (NUP85, HAX1, GNPDA1, HDLBP and GPD1) among the differentially expressed glycolysis-related genes were screened and identified. The five-gene expression signature was used to assign patients into high- and low-risk groups (p < 0.05) and it showed a satisfactory prognostic value for overall survival (OS, p = 6.383 × 10^-6). The ROC curve analysis revealed that this model has a high sensitivity and specificity (0.757 at 5 years). Besides, stratification analysis showed that the prognostic value of the five-gene signature was independent of other clinical characteristics, and it could markedly discriminate between GI tumor tissues and normal tissues. Finally, the expression levels of the five prognosis-related genes in the clinical tissue samples were consistent with the results from the TCGA data sets.

CONCLUSIONS

Based on the five glycolysis-related genes (NUP85, HAX1, GNPDA1, HDLBP and GPD1), and in combination with clinical characteristics, this model can independently predict the OS of GI cancers in Asian patients.

Vigilin is overexpressed in hepatocellular carcinoma and is required for HCC cell proliferation and tumor growth

Vigilin contains multiple KH domains and is an evolutionarily conserved RNA-binding protein from yeast to the human. Its reported roles in human carcinogenesis are controversial in different types of human cancers. To obtain the specific expression profiles of vigilin in human hepatocellular carcinomas (HCCs), we examined vigilin protein levels in normal human liver, liver cirrhosis, adjacent non-tumor liver and HCC tumor tissues as well as in several HCC cell lines. We discovered that vigilin expression increased progressively from the liver cirrhosis tissue to adjacent non-tumor liver tissue and then to HCC tumor cells. Vigilin protein was also overexpressed in all three HCC cell lines examined, HepG2, BEL7402 and SMMC7721, when compared with the vigilin expression level in the L-02 human embryonic hepatocyte cell line. We further investigated the impact of vigilin knockdown on HCC cell proliferation, survival, motility, tumor growth and sensitivity to chemotherapy. We found that knockdown of vigilin in the BEL7402 HCC cells significantly inhibited their proliferation, colony formation and migration, but largely enhanced the cisplatin treatment-induced growth inhibition of these cells in culture. We also found that vigilin knockdown effectively inhibited the growth of BEL7402 cell-derived xenograft tumors in nude mice by decreasing the proliferation and increasing the apoptosis of the BEL7402 HCC cells. Taken together, these results suggest that progressively upregulated vigilin may serve as a molecular risk marker for HCC development, and targeting vigilin may help to inhibit HCC cell growth, survival and migration.

Proteomic study of human glioblastoma multiforme tissue employing complementary two-dimensional liquid chromatography- and mass spectrometry-based approaches

An extensive data set comprising 2660 unique protein identifications was obtained for the proteome of a human brain tumor (glioblastoma multiforme) by combining the results of two complementary analytical strategies based on two-dimensional chromatography and mass spectrometry. A bottom-up method, performing peptide separation in both chromatographic dimensions was employed as well as a semi-top-down method, in which intact proteins were separated in the first and tryptic peptides in the second dimension. The identified proteins were assigned to their molecular functions and compared to previously identified proteins of glioblastoma multiforme (= astrocytoma WHO grade IV), lower WHO grade astrocytomas (grade II and III), and nontumor brain tissue. With the use of a subset of 104 identified membrane proteins, the properties of intact protein fractionation in the first dimension of the semi-top-down approach were elucidated in detail. The benefit of the semi-top-down approach was further demonstrated by the identification of a set of endogenous glioblastoma multiforme expressed proteins. These proteins correspond to recombinant antigens which were recently found to be reactive against autoantibodies in glioblastoma multiforme patients. The results indicate the usefulness of the semi-top-down approach for the investigation of immunogenic antigens in human tumor tissue samples.