Expression of La Ribonucleoprotein Domain Family Member 4B (LARP4B) in Liver Cancer and Their Clinical and Prognostic Significance. Dis Markers. 2019;2019:1569049. [PMID: 31772683 PMCID: PMC6854232 DOI: 10.1155/2019/1569049]

The RNA binding proteins LARP4A and LARP4B promote sarcoma and carcinoma growth and metastasis

RNA-binding proteins (RBPs) are emerging as important regulators of cancer pathogenesis. We reveal that the RBPs LARP4A and LARP4B are differentially overexpressed in osteosarcoma and osteosarcoma lung metastases, as well as in prostate cancer. Depletion of LARP4A and LARP4B reduced tumor growth and metastatic spread in xenografts, as well as inhibiting cell proliferation, motility, and migration. Transcriptomic profiling and high-content multiparametric analyses unveiled a central role for LARP4B, but not LARP4A, in regulating cell cycle progression in osteosarcoma and prostate cancer cells, potentially through modulating key cell cycle proteins such as Cyclins B1 and E2, Aurora B, and E2F1. This first systematic comparison between LARP4A and LARP4B assigns new pro-tumorigenic functions to LARP4A and LARP4B in bone and prostate cancer, highlighting their similarities while also indicating distinct functional differences. Uncovering clear biological roles for these paralogous proteins provides new avenues for identifying tissue-specific targets and potential druggable intervention.

LARP4A and LARP4B in cancer: The new kids on the block

Recent developments have mounted a stunning body of evidence underlying the importance of RNA binding proteins (RBPs) in cancer research. In this minireview we focus on LARP4A and LARP4B, two paralogs belonging to the superfamily of La-related proteins, and provide a critical overview of current research, including their roles in cancer pathogenesis and cell proliferation, migration, cell cycle and apoptosis. We highlight current controversies surrounding LARP4A and LARP4B and conclude that their complex roles in tumorigenesis are cell-, tissue- and context-dependent, warning that caution must be exercised before categorising either protein as an oncoprotein or tumour-suppressor. We also reveal that LARP4A and LARP4B have often been confused with one another, adding uncertainty in delineating their functions. We suggest that further functional and mechanistic studies of LARP4 proteins present significant challenges for future investigations to recognise the vital contributions of these RBPs in cancer research.

Characterization of glycosylation regulator-mediated glycosylation modification patterns and tumor microenvironment infiltration in hepatocellular carcinoma

Background: Previous studies have shown that glycosylation of proteins ofen plays an important role in HCC. However, the potential mechanism of glycosylation in HCC has not been described systematically. Methods: We comprehensively evaluated the glycosylation patterns in HCC samples based on 43 glycosylation regulators, and annotated the modification patterns with the enrichment of immune cells and stromal cells. Considering the heterogeneity of HCC patients, the glycosylation score was constructed using single-sample gene set enrichment analysis (ssGSEA). We also explored the drugs that different HCC patients were sensitive to based on glycosylation mode and score. Results: We identified three glycosylation-regulated gene subtypes. By annotating the subtypes, it was found that the glycosylation regulated gene subtypes was highly matched with three immunophenotypes of HCC (immune-inflamed, immune-excluded, and immune-desert), regardless of the characteristics of immune cell infiltration or prognosis. Based on the characteristic genes of glycosylation-regulated gene subtypes, we constructed a glycosylation-related model, and found that glycosylation-related model was highly consistent with the glycosylation regulated gene subtypes. The glycosylation score that evaluates the glycosylation characteristics of a single HCC sample has high prognostic value, and the prognosis of patients with high glycosylation score is significantly worse. Interestingly, we found that the glycosylation score was closely related to tumor node metastasis (TNM) staging. By applying glycosylation-regulated gene subtypes and glycosylation score to explore the sensitivity of different patients to anticancer drugs, it was found that the sensitivity of Thapsigargin, Shikonin, Embelin and Epothilone. B was closely related to the glycosylation mode. Conclusion: This study reveals that the diversity of glycosylation patterns plays an important role in HCC. Therefore, evaluating the glycosylation patterns of patients with HCC will be helpful in identifying the characteristics of immune cell infiltration and selecting accurate treatment methods.

KLRK1 as a prognostic biomarker for lung adenocarcinoma cancer

Lung cancer is one of the most common malignancy worldwide and causes estimated 1.6 million deaths each year. Cancer immunosurveillance has been found to play an important role in lung cancer and may be related with its prognosis. KLRK1, encoding NKG2D, is a homodimeric lectin-like receptor. However, there has not been one research of KLRK1 as a biomarker in lung cancer. Data including patients` clinical characteristics and RNAseq information of KLRK1 from TCGA were downloaded. A total of 1019 patients with lung cancer were included in this study, among which 407 patients were female and 611 patients were male. Evaluations of mRNA expression, diagnostic value by ROC (receiver operating characteristic) curves and prognostic value by survival curve, Cox model and subgroup analysis were performed. The level of KLRK1 expression in lung adenocarcinoma cancer tissues and normal lung tissues was detected by qRT-PCR. The CCK-8 assay investigated the proliferation rate and the wound healing assay assessed the migratory ability in vitro. The expression of KLRK1 in tumor was lower than that in normal tissue. KLRK1 expression was associated with gender, histologic grade, stage, T classification and vital status. Patients with high KLRK1 expression presented an improved overall survival (P = 0.0036) and relapse free survival (P = 0.0031). KLRK1 was found to have significant prognostic value in lung adenocarcinoma (P = 0.015), stage I/II (P = 0.03), older patients (P = 0.0052), and male (P = 0.0047) by subgroup overall survival analysis, and in lung adenocarcinoma (P = 0.0094), stage I/II (P = 0.0076), older patients (P = 0.0072), and male (P = 0.0033) by subgroup relapse free survival analysis. Lung adenocarcinoma cancer patients with high KLRK1 expression presented an improved overall survival (P = 0.015) and relapse free survival (P = 0.0094). In vitro studies indicated that KLRK1 inhibited tumor cell proliferation and migration. KLRK1 was an independent prognostic factor and high KLRK1 expression indicated a better overall and relapse free survival. KLRK1 may be a prognostic biomarker for lung adenocarcinoma cancer.

HN1 as a diagnostic and prognostic biomarker for liver cancer

Background: The present study aimed to examine the diagnostic and prognostic value of HN1 in terms of overall survival (OS) and recurrence-free survival (RFS) in liver cancer and its potential regulatory signaling pathway.

Methods: We obtained clinical data and HN1 RNA-seq expression data of liver cancer patients from The Cancer Genome Atlas database, and analyzed the differences and clinical association of HN1 expression in different clinical features. We uesd receiver-operating characteristic curve to evaluate the diagnosis capability of HN1. We analyzed and evaluated the prognostic significance of HN1 by Kaplan–Meier curves and Cox analysis. Gene Set Enrichment Analysis (GSEA) was used to identify signaling pathways related to HN1 expression.

Results: HN1 mRNA was up-regulated in liver cancer, and was associated with age, histologic grade, stage, T classification, M classification, and vital status. HN1 mRNA had ideal specificity and sensitivity for the diagnosis (AUC = 0.855). Besides, the analysis of Kaplan–Meier curves and Cox model showed that HN1 mRNA was strongly associated with the overall survival and could be well-predicted liver cancer prognosis, as an independent prognostic variable. GSEA analysis identified three signaling pathways that were enriched in the presence of high HN1 expression.

Conclusion: HN1 serves as a biomarker of diagnosis and prognosis in liver cancer.

DNA Primase Subunit 1 Expression in Hepatocellular Carcinoma and Its Clinical Implication

DNA Primase Subunit 1 (PRIM1) is crucial for cancer development and progression. However, there remains a lack of comprehension concerning the clinical implication of PRIM1 in HCC. Here, aberrant expression of PRIM1 was identified in HCC according to available databases. The prognostic value of PRIM1 in patients presenting with HCC was further assessed based on TCGA data. Gene set enrichment analysis (GSEA) was subsequently conducted to investigate the potential function of PRIM1. Additionally, the correlations between tumor-infiltrating immune cells (TIICs) and PRIM1 expression were evaluated. The data from TCGA, GEO, ONCOMINE, and HCCDB databases illustrated that PRIM1 was overexpressed in HCC tissues, compared to normal liver tissues (all p < 0.05). Kaplan-Meier analysis revealed that high PRIM1 expression in HCC was closely correlated with worse overall survival (p < 0.05). The univariate and multivariate analyses illustrated that PRIM1 expression was an independent novel prognostic indicator in HCC. Additionally, the area under the receiver operating characteristic (AUROC) curve for PRIM1 reached 0.8651, indicating the diagnostic significance of PRIM1 in patients with HCC. GSEA showed that PRIM1 overexpression was significantly enriched in several tumor-related signaling pathways. Besides, TIIC analysis clarified the association between PRIM1 expression and TIICs in HCC. The findings disclose that PRIM1 profoundly implicated in promoting tumorigenesis might work as a desirable biomarker for HCC.

Discovering Biomarkers in Peritoneal Metastasis of Gastric Cancer by Metabolomics

Background and Objective

Metabolomics has recently been applied in the field of oncology. In this study, we aimed to use metabolomics to explore biomarkers in peritoneal metastasis of gastric cancer.

Methods

Peritoneal lavage fluid (PLF) of 65 gastric cancer patients and related clinical data were collected from the First Hospital of Jilin University. The metabolic components were identified by liquid chromatography-mass spectrometry (LC-MS). Total ion current (TIC) spectra, principal component analysis (PCA), and the Student's t-test were used to identify differential metabolites in PLF. A support vector machine (SVM) was used to screen the differential metabolites in PLF with a weight of 100%. Cluster analysis was used to evaluate the similarity between samples. Receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic ability of the metabolites. Univariate and multivariate logistic regression analyses were used to identify potential risk factors for peritoneal metastasis of gastric cancer.

Results

We found the differential levels of PLF metabolites by LC-MS, TIC spectra, PCA and the t-test. Cluster analysis showed the co-occurrence of metabolites in the peritoneal metastasis group (p<0.05). ROC analysis showed the diagnostic ability of metabolites (p<0.05). Univariate and multivariate logistic regression analyses showed the potential independent risk factors for peritoneal metastasis in gastric cancer patients (p<0.05).

Conclusion

Through the statistical analysis of metabolomics, we found that TG (54:2), G3P, α-aminobutyric acid, α-CEHC, dodecanol, glutamyl alanine, 3-methylalanine, sulfite, CL (63:4), PE-NMe (40:5), TG (53:4), retinol, 3-hydroxysterol, tetradecanoic acid, MG (21:0/0:0/0:0), tridecanoic acid, myristate glycine and octacosanoic acid may be biomarkers for peritoneal metastasis of gastric cancer.

SLC25A11 serves as a novel prognostic biomarker in liver cancer

Liver cancer is a disease with high mortality; it is often diagnosed at intermediate and advanced stages and has a high recurrence rate. ROS restriction and adequate energy supply play significant roles in liver cancer. SLC25A11, a member of the malate-aspartate shuttle (MAS), regulates electroneutral exchange between 2-oxoglutarate and other dicarboxylates. It transports glutathione (GSH) from the cytoplasm into mitochondria to maintain GSH levels to limit ROS production. Moreover, SLC25A11 is essential for ATP generation in cancers as it regulates NADH transportation from the cytoplasm to mitochondria. The purpose of this research was to investigate the prognostic value of SLC25A11 in liver cancer. The Cancer Genome Atlas database was used to analyze the levels of SLC25A11 in liver cancer. Fisher's exact and chi-square tests were used to evaluate the relationship between SLC25A11 expression and clinical characteristics. Finally, we explored the value of SLC25A11 in prognosis by Cox analysis and Kaplan-Meier curves. Our results revealed that SLC25A11 was downregulated in liver cancer compared to normal controls. Low expression of SLC25A11 was associated with clinical stage, vital status, histologic grade, overall survival (OS) and relapse-free survival (RFS). Liver cancer patients with low SLC25A11 expression had shorter OS and RFS than patients with high SLC25A11 expression. Multivariate analysis showed that the expression of SLC25A11 was an independent predictor of RFS and OS. In conclusion, this study identified that SLC25A11 serves as a new prognostic marker for liver cancer.

Expression of eukaryotic translation initiation factor 3 subunit B in liver cancer and its prognostic significance

Liver cancer is one of the major malignancies with the worst prognosis among all solid tumor types. It is therefore ponderable to explore prognostic biomarkers and therapeutic targets for liver cancer. Eukaryotic translation initiation factor 3 subunit B (EIF3B) is closely linked to the transcription initiation of cancer-associated genes. In the present study, EIF3B was indicated to be a potential prognostic biomarker of liver cancer. The mRNA expression level of EIF3B in liver cancer was assessed by analyzing the Cancer Genome Atlas dataset. χ² and Fisher's exact tests were used to assess the association of EIF3B expression with clinical parameters. Receiver-operating characteristic curve analysis was used for evaluating the diagnostic value of EIF3B. Overall and relapse-free survival were assessed using Kaplan-Meier curves to determine the association between EIF3B expression and survival. Univariate and multivariate Cox regression analysis were performed to identify the factors affecting overall/relapse-free survival. Gene set enrichment analysis (GSEA) was used to identify signaling pathways associated with EIF3B in liver cancer. It was revealed that EIF3B was highly expressed in liver cancer tissues and it had a promising diagnostic ability. Furthermore, the survival analysis indicated that patients with high EIF3B expression generally had shorter overall as well as relapse-free survival. Univariate and multivariate Cox analysis suggested that high EIF3B mRNA expression may serve as an independent biomarker for the prognostication of patients with liver cancer. GSEA suggested that MYC-V1 (HALLMARK_MYC_TARGETS_V1 geneset; P=0.009), MYC-V2 (HALLMARK_MYC_TARGETS_V2 geneset; P=0.004) and DNA repair pathways (HALLMARK_DNA_REPAIR geneset; P<0.001) were differentially enriched in high EIF3B expression and low EIF3B expression groups. In conclusion, high EIF3B expression was indicated to be an independent prognostic biomarker for patients with liver cancer.

The prognostic value of lncRNA SNHG4 and its potential mechanism in liver cancer

BACKGROUND AND OBJECT

Emerging evidence shows that non-coding RNA functions as new gene regulators and prognostic markers in several cancers, including liver cancer. Here, we focused on the small nucleolar RNA host gene 4 (SNHG4) in liver cancer prognosis based on The Cancer Genome Atlas (TCGA) data.

METHODS

The expression data and clinical information were downloaded from TCGA. Chi-square tests evaluated the correlation between SNHG4 expression and clinical parameters. Differences in survival between high and low expression groups (optic cutoff value determined by ROC) from Cox regression analysis were compared, and P-value was calculated by a log-rank test. Kaplan-Meier curves were compared with the log-rank test. GSEA and ceRNA network were conducted to explore the potential mechanism.

RESULTS

Data mining of lncRNA expression data for 371 patients with primary tumor revealed overexpression of SNHG4 in liver cancer. High SNHG4 expression was correlated with histological type (P = 0.01), histologic grade (P = 0.001), stage (P = 0.01), T classification (P = 0.004) and survival status (P = 0.013). Patients with high SNHG4 expression had poor overall survival and relapse-free survival compared with those with low SNHG4 expression. Multivariate analysis identified SNHG4 as an independent prognostic factor of poor survival in liver cancer. GSEA revealed related signaling pathway and ceRNA network explored the further mechanism.

CONCLUSION

High SNHG4 expression is an independent predictor of poor prognosis in liver cancer.

Comprehensive multi-omics analysis identified core molecular processes in esophageal cancer and revealed GNGT2 as a potential prognostic marker

BACKGROUND

Esophageal cancer is one of the most poorly diagnosed and fatal cancers in the world. Although a series of studies on esophageal cancer have been reported, the molecular pathogenesis of the disease remains elusive.

AIM

To investigate comprehensively the molecular process of esophageal cancer.

METHODS

Differential expression analysis was performed to identify differentially expressed genes (DEGs) in different stages of esophageal cancer from The Cancer Genome Atlas data. Exacting gene interaction modules were generated, and hub genes in the module interaction network were found. Further, through survival analysis, methylation analysis, pivot analysis, and enrichment analysis, some important molecules and related functions/pathways were identified to elucidate potential mechanisms in esophageal cancer.

RESULTS

A total of 7457 DEGs and 14 gene interaction modules were identified. These module genes were significantly involved in the positive regulation of protein transport, gastric acid secretion, insulin-like growth factor receptor binding, and other biological processes as well as p53 signaling pathway, epidermal growth factor signaling pathway, and epidermal growth factor receptor signaling pathway. Transcription factors (including hypoxia inducible factor 1A) and non-coding RNAs (including colorectal differentially expressed and hsa-miR-330-3p) that significantly regulate dysfunction modules were identified. Survival analysis showed that G protein subunit gamma transducin 2 (GNGT2) was closely related to survival of esophageal cancer. DEGs with strong methylation regulation ability were identified, including SST and SH3GL2. Furthermore, the expression of GNGT2 was evaluated by quantitative real time polymerase chain reaction, and the results showed that GNGT2 expression was significantly upregulated in esophageal cancer patient samples and cell lines. Moreover, cell counting kit-8 assay revealed that GNGT2 could promote the proliferation of esophageal cancer cell lines.

CONCLUSION

This study not only revealed the potential regulatory factors involved in the development of esophageal cancer but also deepens our understanding of its underlying mechanism.