High Trophinin-Associated Protein Expression Is an Independent Predictor of Poor Survival in Liver Cancer

Sunitinib-resistant renal cell carcinoma cell-derived exosomes promote facilitation of tumor progression via secretion of the lncRNA SNHG16

Renal cell carcinoma (RCC) is one of the most common tumors of high malignancy in the urological system. Sunitinib is commonly used to treat RCC, while drug resistance severely limited the therapeutic efficacy. Tumor-derived exosomes play important roles in facilitating cancer development. However, the role of drug-resistant tumor-derived exosomes in tumorigenesis and resistance of RCC has not been elucidated. Here we isolated sunitinib-sensitive/resistant RCC cells-derived exosomes, characterized by transmission electron microscopy (TEM) and western blot. Furthermore, co-culture experiments were performed and we found that sunitinib-resistant RCC cells-derived exosomes (R-exos) promoted cell proliferation and upregulated proliferation-related genes cyclin D1 (CCND1) and proliferating cell nuclear antigen (PCNA) expression, and inhibited apoptosis and the expression of Bax and Caspase-3 of sunitinib-resistant RCC (RCC/R) cells by delivering lncRNA small nuclear RNA host gene 16 (SNHG16). In resistant cell-derived xenograft (CDX-R) models, R-exos induced tumor growth in vivo, while knockdown of SNHG16 effectively diminished the tumorigenesis of RCC. Moreover, SNHG16 positively regulated the expression of trophinin associated protein (TROAP) by sponging miR-106a-5p in RCC cells, whereas inhibition of miR-106a-5p or overexpression of TROAP greatly reversed the suppression of tumorigenesis and sunitinib resistant by silencing SNHG16. R-exos lncRNA SNHG16 promoted sunitinib resistant and malignant progress by regulating the miR-106a-5p/TROAP axis, and targeting SNHG16/miR-106a-5p/TROAP axis may be a novel therapeutic approach for sunitinib-treated patients of RCC.

Clinical significance of TROAP in endometrial cancer and the antiproliferative and proapoptotic effects of TROAP knockdown in endometrial cancer cells: integrated utilization of bioinformatic analysis and in vitro test verification

Trophinin-associated protein (TROAP), a cytoplasmic protein essential for spindle assembly and centrosome integrity during mitosis, has been reported to serve as an oncogene in various tumors. However, its role in endometrial cancer (EC) progression is still undefined. TROAP expression in EC was analyzed via GEPIA and HPA databases. The diagnostic and prognostic values of TROAP were examined by ROC curve analysis and Kaplan-Meier plotter, respectively. Cell proliferation was evaluated using CCK-8 and EdU incorporation assays. Apoptosis was assessed using TUNEL and flow cytometry assays. GSEA was performed to explore TROAP-related pathways in EC. Expression of TROAP, proliferating cell nuclear antigen (PCNA), Ki-67, cleaved-caspase-3 (cl-caspase-3), caspase-3, active β-catenin, and total β-catenin was detected using western blot analysis. TROAP was upregulated in EC. TROAP served as a potential diagnostic and prognostic marker in EC patients. TROAP silencing suppressed proliferation and enhanced apoptosis in EC cells. GSEA revealed that EC and Wnt signaling pathways were related to the expression of TROAP. We further demonstrated that TROAP knockout repressed the Wnt/β-catenin pathway in EC cells. Moreover, SKL2001, a Wnt/β-catenin activator, partially abrogated the effects of TROAP silencing on EC cell proliferation and apoptosis, while the signaling inhibitor XAV-939 had the opposite effect. In conclusion, TROAP knockout retarded proliferation and elicited apoptosis in EC cells by blocking the Wnt/β-catenin pathway.

Mirk/Dyrk1B Kinase Inhibitors in Targeted Cancer Therapy

During the last years, there has been an increased effort in the discovery of selective and potent kinase inhibitors for targeted cancer therapy. Kinase inhibitors exhibit less toxicity compared to conventional chemotherapy, and several have entered the market. Mirk/Dyrk1B kinase is a promising pharmacological target in cancer since it is overexpressed in many tumors, and its overexpression is correlated with patients' poor prognosis. Mirk/Dyrk1B acts as a negative cell cycle regulator, maintaining the survival of quiescent cancer cells and conferring their resistance to chemotherapies. Many studies have demonstrated the valuable therapeutic effect of Mirk/Dyrk1B inhibitors in cancer cell lines, mouse xenografts, and patient-derived 3D-organoids, providing a perspective for entering clinical trials. Since the majority of Mirk/Dyrk1B inhibitors target the highly conserved ATP-binding site, they exhibit off-target effects with other kinases, especially with the highly similar Dyrk1A. In this review, apart from summarizing the data establishing Dyrk1B as a therapeutic target in cancer, we highlight the most potent Mirk/Dyrk1B inhibitors recently reported. We also discuss the limitations and perspectives for the structure-based design of Mirk/Dyrk1B potent and highly selective inhibitors based on the accumulated structural data of Dyrk1A and the recent crystal structure of Dyrk1B with AZ191 inhibitor.

Role of Metabolomics in Pathogenesis and Prompt Diagnosis of Gastric Cancer Metastasis-A Systematic Review

INTRODUCTION

Gastric cancer is the fourth most frequently diagnosed form of cancer and the third leading cause of cancer-related mortality worldwide. The aim of this review is to identify individual metabolic biomarkers and their association with accurate diagnostic values, which can predict gastric cancer metastasis.

MATERIALS AND METHODS

After searching the keywords, 83 articles were found over a period of 13 years. One was eliminated because it was not written in English, and two were published outside the selected period. Seven scientific papers were qualified for this investigation after eliminating duplicates, non-related articles, systematic reviews, and restricted access studies.

RESULTS

New metabolic biomarkers with predictive value for gastric cancer metastasis and for elucidating metabolic pathways of the metastatic process have been found. The pathogenic processes can be outlined as follows: pro-oxidant capacity, T-cell inactivation, cell cycle arrest, energy production and mitochondrial enzyme impairment, cell viability and pro-apoptotic effect, enhanced degradation of collagen extracellular matrix, migration, invasion, structural protein synthesis, and tumoral angiogenesis.

CONCLUSION

Metabolic biomarkers have been recognized as independent risk factors in the molecular process of gastric cancer metastasis, with good diagnostic and prognostic value.

High trophinin-associated protein expression predicts good survival in acute myeloid leukemia with normal cytogenetics

BACKGROUND

Nearly half of adult acute myeloid leukemia (AML) patients were classified into cytogenetic normal acute myeloid leukemia (CN-AML). The expression level of Trophinin associated protein (TROAP) was proven to be associated with the prognosis of several cancers, but it is still unclear in the prognosis of patients with CN-AML.

METHODS

We integrated CN-AML patients samples from 4 datasets to analyze the relationship between TROAP expression and the survival of CN-AML. In addition, we investigated 92 AML patients of The Cancer Genome Atlas (TCGA) database to analyze the relationship between TROAP expression and the survival of AML patients received chemotherapy. We investigated the relationship between the expression of TROAP and drug sensitivity in AML cell lines.

RESULTS

CN-AML patients with high TROAP expression were related to good event-free survival (EFS) and overall survival (OS). In AML patients received chemotherapy, high TROAP expression was associated with good survival prognosis. Additionally, the expression of TROAP gene in leukemia stem cells (LSC) + group was lower. Among multiple drugs, the lower the expression of TROAP, the lower the IC50.

CONCLUSION

TROAP could serve as an independent predictor of CN-AML patients and could act as a potential biomarker for the prognosis of CN-AML. TROAP expression levels were closely correlated with the drug sensitivity of multiple drugs.

Tastin promotes non-small-cell lung cancer progression through the ErbB4, PI3K/AKT, and ERK1/2 pathways

Tastin might be involved in tumorigenesis, but its role in non-small-cell lung cancer (NSCLC) has not been adequately explored. This work aimed to examine tastin's role in NSCLC and to explore the underlying mechanism. The Gene Expression Omnibus (GEO), Gene Expression Database of Normal and Tumor tissues (GENT), and Cancer Genome Atlas (TCGA) databases were used. Four GEO datasets (GSE81089, GSE40419, GSE74706, and GSE19188) containing gene expression data for NSCLC and normal tissue samples were analyzed for tastin mRNA expression. Tastin expression levels in different tissues were compared using the GENT website. TCGA biolinks were used to download gene expression quantification (n = 594) and overall survival data (n = 535). In total, 30 lung adenocarcinoma and 25 lung squamous cell carcinoma cases were enrolled. In addition, four-week-old male BALB/c nude mice (n = 9/group) were used to establish xenograft mouse models. Furthermore, cultured HEK293T, A549, and NCI-H226 cells assessed. Immunoblot, hematoxylin and eosin (H&E) staining, immunohistochemistry, real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR), fluorescence microscopy, flow cytometry, lentiviral transduction, and MTT, colony formation, wound healing, and Transwell assays were carried out. Tastin expression levels were markedly increased in NSCLC tumor tissue specimens and correlated with a poorer prognosis. Silencing of tastin inhibited the proliferative and migratory abilities of NSCLC cells. Bioinformatic analysis suggested that tastin interacts with ErbB4. The PI3K/AKT and ERK1/2 downstream pathways were suppressed in tastin-deficient cells. In conclusion, tastin might be involved in NSCLC growth and invasion and is a potential therapeutic target in NSCLC.

Trophinin-associated protein expression correlates with shorter survival of patients with glioma: a study based on multiple data fusion analysis

BACKGROUND

Trophinin-associated protein (TROAP) mediates embryonic transfer, regulates microtubules, and is associated with the biological behavior of various cancers. However, there is limited information on the role of TROAP in glioma.

METHODS AND RESULTS

We obtained clinical information on 1948 patients with glioma from The Cancer Genome Atlas, Gene Expression Omnibus and the Chinese Glioma Genome Atlas. Basal assays were used to measure changes in TROAP expression levels in high-grade glioma cell lines and in normal human astrocytes. Quantitative reverse transcription polymerase chain reaction assays showed that TROAP expression was higher in glioma cell lines than in normal astrocytes. The expression level of TROAP in 749 glioma was significantly higher than that in 228 normal brain tissues using Student's t test. The expression of TROAP has a positive relationship with the clinical characteristics of poor prognosis, such as WHO grade, age and has negatively correlated with the indicators of beneficial prognosis, such as IDH mutation and 1p19q co-deletion. Kaplan-Meier survival curves, single multifactor analysis were used to analyze correlations between TROAP and clinical features and prognosis of gliomas. In addition, TROAP overexpression was an independent risk factor for glioma and was associated with reduced overall survival of patients with glioma particularly in patients with WHO grade III and grade IV glioma. Gene set enrichment analysis showed that homologous recombination, cell cycle, and p53 signaling pathways were enriched in samples overexpressing TROAP.

CONCLUSION

TROAP is a potential risk factor associated with poor prognosis in patients with glioma and may act as a highly specific biomarker, offering the possibility of individualized glioma treatment.

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.

Expression and clinical significance of BDH1 in liver cancer

Liver cancer is a deadly disease with generally poor patient outcomes. BDH1 is a key enzyme that regulates the metabolism and synthesis of ketone bodies. This study sought to explore the prognostic relevance of BDH1 mRNA expression in liver cancer.We utilized the Cancer Genome Atlas datasets to analyze the relationship between BDH1 expression and clinical outcomes. We used Kaplan-Meier curves and Cox analyses to explore the relevance of BDH1 mRNA levels to patient prognosis. Further gene set enrichment analysis was conducted as a means of comparing differences in gene expression as a function of BDH1 expression.Liver cancer samples exhibited significantly decreased BDH1 mRNA expression, and that this downregulation was correlated with a number of clinicopathological variables including gender, histologic grade, stage, TNM classification, and both overall and relapse-free survival. We further determined that BDH1 mRNA expression was an independent predictor of liver cancer patient prognosis. A subsequent gene set enrichment analysis found genes affected by BDH1 expression to be those enriched in pathways relating to MYC and wnt/β-catenin signaling.Our preliminary findings demonstrate for the first time that low expression of BDH1 mRNA is a potentially valuable independent prognostic indicator for liver cancer detection.

Overexpression of MAL2 Correlates with Immune Infiltration and Poor Prognosis in Breast Cancer

Background

Myelin and lymphocyte, T cell differentiation protein 2 (MAL2) is highly expressed in various cancers and associated with the development and prognosis of cancer. However, the relationship between MAL2 and breast cancer requires further investigation. This study aimed to explore the prognostic significance of MAL2 in breast cancer.

Methods

MAL2 expression was initially assessed using the Oncomine database and The Cancer Genome Atlas (TCGA) database and verified by quantitative real-time polymerase chain reaction (RT-qPCR). The chi-square test or Fisher's exact test was used to explore the association between clinical characteristics and MAL2 expression. The prognostic value of MAL2 in breast cancer was assessed by the Kaplan–Meier method and Cox regression analysis. Gene set enrichment analysis (GSEA) was performed to identify the biological pathways correlated with MAL2 expression in breast cancer. Besides, a single-sample GSEA (ssGSEA) was used to assess the relationship between the level of immune infiltration and MAL2 in breast cancer.

Results

Both bioinformatics and RT-qPCR results showed that MAL2 was expressed at high levels in breast cancer tissues compared with the adjacent tissues. The chi-square test or Fisher's exact test indicated that MAL2 expression was related to stage, M classification, and vital status. Kaplan–Meier curves implicated that high MAL2 expression was significantly associated with the poor prognosis. Cox regression models showed that high MAL2 expression could be an independent risk factor for breast cancer. GSEA showed that 14 signaling pathways were enriched in the high-MAL2-expression group. Besides, the MAL2 expression level negatively correlated with infiltrating levels of eosinophils and plasmacytoid dendritic cells in breast cancer.

Conclusion

Overexpression of MAL2 correlates with poor prognosis and lower immune infiltrating levels of eosinophils and plasmacytoid dendritic cells in breast cancer and may become a biomarker for breast cancer prognosis.

Trophinin Is an Important Biomarker and Prognostic Factor in Osteosarcoma: Data Mining from Oncomine and the Cancer Genome Atlas Databases

Osteosarcoma (OS) is a type of bone malignancy with a high rate of treatment failure. To date, few evident biomarkers for the prognostic significance of OS have been established. Oncomine was used to integrate RNA and DNA-seq data from the Gene Expression Omnibus (GEO), The Cancer Genome Atlas (TCGA), and the published literature. The correlation of the gene Trophinin (TRO) and different types of cancers was generated using the Cancer Cell Line Encyclopedia (CCLE) online tool. Prognostic values of featured Melanoma Antigen Gene (MAGE) members were further assessed by establishing the overall survival using the Kaplan-Meier plotter. Moreover, the online tool, Database for Annotation, Visualization and Integrated Discovery version (DAVID), was used to understand the biological meaning list of the genes. MAGEB10, MAGED2, TRO, MAGEH1, MAGEB18, MAGEB6, MAGEB4, MAGEB1, MAGED4B, MAGED1, MAGEB2, and MAGEB3 were significantly overexpressed in sarcoma. TRO was further demonstrated to be distinctively upregulated in osteosarcoma cell lines and associated with shorter overall survival. TRO may play an important role in the development of OS and may be a promising potential biomarker and prognostic factor.

Molecular subtypes based on CNVs related gene signatures identify candidate prognostic biomarkers in lung adenocarcinoma

The classical factors for predicting prognosis currently cannot meet the developing requirements of individualized and accurate prognostic evaluation in lung adenocarcinoma (LUAD). With the rapid development of high-throughput DNA sequencing technologies, genomic changes have been discovered. These sequencing data provide unprecedented opportunities for identifying cancer molecular subtypes. In this article, we classified LUAD into two distinct molecular subtypes (Cluster 1 and Cluster 2) based on Copy Number Variations (CNVs) and mRNA expression data from the Cancer Genome Atlas (TCGA) based on non-negative matrix factorization. Patients in Cluster 1 had worse outcomes than that in Cluster 2. Molecular features in subtypes were assessed to explain this phenomenon by analyzing differential expression genes expression pattern, which involved in cellular processes and environmental information processing. Analysis of immune cell populations suggested different distributions of CD4+ T cells, CD8+ T cells, and dendritic cells in the two subtypes. Subsequently, two novel genes, TROAP and RASGRF1, were discovered to be prognostic biomarkers in TCGA, which were confirmed in GSE31210 and Tianjin Medical University Cancer Institute and Hospital LUAD cohorts. We further proved their crucial roles in cancers by vitro experiments. TROAP mediates tumor cell proliferation, cycle, invasion, and migration, not apoptosis. RASGRF1 has a significant effect on tumor microenvironment. In conclusion, our study provides a novel insight into molecular classification based on CNVs related genes in LUAD, which may contribute to identify new molecular subtypes and target genes.

TROAP regulates cell cycle and promotes tumor progression through Wnt/β-Catenin signaling pathway in glioma cells

AIMS

Experimental evidence demonstrated a crucial role of TROAP (Trophinin-associated protein) in regulating the cell proliferation of multiple tumors, while TROAP expression and function were largely unknown in glioma. We aimed to investigate the oncogenic role of TROAP and its potential mechanisms in gliomagenesis.

METHODS

Four gene expression databases (GEO, TCGA, GTEx and CCLE) were enrolled in our study and used for TROAP expression and survival analysis. TROAP expression was quantified by qRT-PCR, western blot and immunohistochemistry assays in glioma tissues and cell lines. TROAP knockdown and overexpression vector were constructed and transfected into glioma cells. CCK-8, colony formation, transwell, and wound healing assays were used to evaluate cell viability, migration and invasion, flow cytometry to determine cell cycle arrest. Gene set enrichment analysis (GSEA) was conducted to screen the pathway involved in TROAP-high phenotype. The expression of cell cycle and Wnt/β-Catenin signaling proteins were analyzed by immunofluorescence and western blot.

RESULTS

Based on the bioinformatic analysis and a series of functional assays, we found the TROAP was enriched in glioma tissues and cell lines, its overexpression was correlated with the clinicopathologic characteristics and poor prognosis. TROAP knockdown inhibited cell proliferation, migration, invasion, and G1/S cell cycle arrest compared with control group in glioma. Mechanism analysis revealed that TROAP activated Wnt/β-Catenin pathway and upregulated its downstream targets expression, while silencing β-Catenin or Axin2 could reverse the tumor-promoting effects caused by TROAP, confirming that TROAP-induced malignant phenotype and tumorigenesis via Wnt/β-Catenin signaling pathway.

CONCLUSION

The present study found that TROAP accelerated the progression of gliomagenesis through Wnt/β-Catenin pathway, and TROAP might be considered as a novel target for glioma therapy.

EZH2-TROAP Pathway Promotes Prostate Cancer Progression Via TWIST Signals

Trophinin-associated protein (TROAP) has been shown to be overexpressed and promotes tumor progression in some tumors. We performed this study to assess the biological and clinical significance of TROAP in prostate cancer. We downloaded TROAP mRNA expression data from TCGA and GEO databases. We analyzed expressions of TROAP and other genes in prostate cancer tumors at different stages and assessed Gleason scores. We used Celigo image, Transwell, and rescue assays, and flow cytometry detection to assess growth, apoptosis, proliferation, migration, and invasion of the prostate cancer cells. We identified and validated up- and down-stream genes in the TROAP pathway. The mRNA data suggested that TROAP expression was markedly upregulated in prostate cancer compared with its expression in normal tissues, especially in cancers with high stages and Gleason scores. Moreover, a high TROAP expression was associated with poor patient survival. Results of our in vitro assay showed that TROAP knockdown inhibited DU145 and PC3 cell proliferation and viability via cell apoptosis and S phase cycle arrest. The Transwell assay showed that TROAP knockdown inhibited cell migration and invasion, probably through MMP-9 and E-Cadherin modulation. Overexpression of TWIST partially abrogated the inhibitory effects of TROAP knockdown on prostate cancer cells. Our integrative mechanism dissection revealed that TROAP is in a pathway downstream of EZH2 and that it activates the TWIST/c-Myc pathway to regulate prostate cancer progression. In all, we identified TROAP as a driver of prostate cancer development and progression, providing a novel target for prostate cancer treatments.

Downregulated mRNA Expression of ZNF385B Is an Independent Predictor of Breast Cancer

BACKGROUND

ZNF385B, a zinc finger protein, has been known as a potential biomarker in some neurological and hematological studies recently. Although numerous studies have demonstrated the potential function of zinc finger proteins in tumor progression, the effects of ZNF385B in breast cancer (BC) are less studied.

METHODS

The Oncomine database and "ESurv" tool were used to explore the differential expression of ZNF385B in pan-cancer. Furthermore, data of patients with BC were downloaded from The Cancer Genome Atlas (TCGA). The receiver operating characteristic (ROC) curve of ZNF385B expression was established to explore the diagnostic value of ZNF385B and to obtain the cut-off value of high or low ZNF385B expression in BC. The chi-square test as well as Fisher exact test was used for identification of the relationships between clinical features and ZNF385B expression. Furthermore, the effects of ZNF385B on BC patients' survival were evaluated by the Kaplan-Meier and Cox regression. Data from the Gene Expression Omnibus (GEO) database were employed to validate the results of TCGA. Protein expression of ZNF385B in BC patient specimens was detected by immunohistochemistry (IHC) staining.

RESULTS

ZNF385B expression was downregulated in most types of cancer including BC. Low ZNF385B expression was related with survival status, overall survival (OS), and recurrence of BC. ZNF385B had modest diagnostic value, which is indicated by the area under the ROC curve (AUC = 0.671). Patients with lower ZNF385B expression had shorter OS and RFS (relapse-free survival). It had been demonstrated that low ZNF385B expression represented independent prognostic value for OS and RFS by multivariate survival analysis. The similar results were verified by datasets from the GEO database as well. The protein expression of ZNF385B was decreased in patients' samples compared with adjacent tissues by IHC.

CONCLUSIONS

Low ZNF385B expression was an independent predictor for worse prognosis of BC patients.

TROAP switches DYRK1 activity to drive hepatocellular carcinoma progression

Hepatocellular carcinoma (HCC) is one of the common malignancy and lacks effective therapeutic targets. Here, we demonstrated that ectopic expression of trophinin-associated protein (TROAP) dramatically drove HCC cell growth assessed by foci formation in monolayer culture, colony formation in soft agar and orthotopic liver transplantation in nude mice. Inversely, silencing TROAP expression with short-hairpin RNA attenuated the malignant proliferation of HCC cells in vitro and in vivo. Next, mechanistic investigation revealed that TROAP directly bound to dual specificity tyrosine phosphorylation regulated kinase 1A/B (DYRK1A/B), resulting in the cytoplasmic retention of proteins DYRK1A/B and promoting cell cycle process via activation of Akt/GSK-3β signaling. Combination of cisplatin with an inhibitor of DYRK1 AZ191 effectively inhibited tumor growth in mouse model for HCC cells with high level of TROAP. Clinically, TROAP was significantly upregulated by miR-142-5p in HCC tissues, which predicted the poor survival of patients with HCC. Therefore, TROAP/DYRK1/Akt axis may be a promising therapeutic target and prognostic indicator for patients with HCC.

Long non-coding RNA BACE1-AS is an independent unfavorable prognostic factor in liver cancer

Liver cancer is one of the leading causes of cancer-associated deaths with incidence rates continuously on the rise. Biomarkers are urgently required for early diagnosis and better prognostic classification, which is essential for risk stratification and optimizing treatment strategies in clinical settings. By analyzing the data extracted from The Cancer Genome Atlas database using R, the long noncoding RNA (lncRNA) β-site APP-cleaving enzyme 1 antisense (BACE1-AS) was discovered to have both high diagnostic and prognostic values in liver cancer, which could serve as a promising biomarker in clinical settings. Precisely, lncRNA BACE1-AS is significantly overexpressed in liver cancer and its levels vary within different subgroups, suggesting its tumorigenic role. Furthermore, higher BACE1-AS predicts poorer overall survival and relapse-free survival outcomes. Overall, the present study demonstrated that BACE1-AS may be involved in liver cancer progression and could serve as a promising biomarker for diagnosis and prognostic evaluation.

Diagnostic and prognostic value of HABP2 as a novel biomarker for endometrial cancer

BACKGROUND

Endometrial cancer is the fifth most common malignant disorder in women, with its incidence increasing. A biomarker with diagnostic and prognostic value remains to be found. The HABP2 protein, or Factor VII-activating protease, encodes a hyaluronic acid-binding protein.

METHODS

Patient data including clinical characteristics and RNAseq information of HABP2 was obtained from The Cancer Genome Atlas (TCGA), and analyzed by R statistic packages. A total of 370 women with endometrial cancer were enrolled in the study. To study the diagnostic value of HABP2 in patients with endometrial cancer, receiver operating characteristic (ROC) curves were plotted by the pROC package. To study the prognostic value of HABP2 in patients with endometrial cancer, the survival package in R was used and the Cox model was established.

RESULTS

HABP2 expression was lower in endometrial cancer compared with normal endometrial tissues. HABP2 showed moderate diagnostic value for endometrial cancer, with HBP2 expression associated with vital status, histologic grade, and residual tumor. HABP2 was an independent prognostic factor, with low HABP2 expression indicating a better overall survival.

CONCLUSIONS

HABP2 has diagnostic and prognostic value and maybe a novel biomarker for endometrial 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.

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.

Lipocalin-1 Expression as a Prognosticator Marker of Survival in Breast Cancer Patients

PURPOSE

LCN1 (lipocalin-1), a gene that encodes tear lipocalin (or von Ebner's gland protein), is mainly expressed in secretory glands and tissues, such as the lachrymal and lingual gland, and nasal, mammary, and tracheobronchial mucosae. Analysis of the Cancer Genome Atlas (TCGA) Breast Carcinoma (BRCA) level 3 data revealed a relationship between LCN1 expression and survival in breast cancer patients.

METHODS

The χ2 test and Fisher exact test were applied to analyze the clinical data and RNA sequencing expression data, and the association between LCN1 expression and clinicopathologic features was determined. The receiver-operating characteristic (ROC) curve of LCN1 was drawn to assess its ability as a diagnostic marker, and the optimal cutoff value was obtained from the ROC curve to distinguish groups with high and low LCN1 expression. Cox regression was used to compare both groups, and a log-rank test was applied to calculate p values and compare the -Kaplan-Meier curves. Furthermore, GEO datasets were employed for external data validation.

RESULTS

Analysis of 1,104 breast cancer patients with a primary tumor revealed that LCN1 was overexpressed in breast cancer. High LCN1 expression was associated with clinicopathologic features and poor survival. Analyzing the area under the ROC curve (AUC) of LCN1, it was found that its diagnostic ability was limited. Multivariate analysis indicated that LCN1 expression is an independent predictor of survival in breast cancer patients. Through validation in GEO datasets, LCN1 expression was higher in tumor than normal tissue of the breast. High LCN1 expression was associated with poor survival in breast cancer patients.

CONCLUSIONS

High LCN1 expression is an independent prognosticator of a poor prognosis in breast 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 Prediction and Prognostic Significance of INPP5K Expression in Patients with Liver Cancer

Liver cancer is a devastating disease for humans with poor prognosis. Although the survival rate of patients with liver cancer has improved in the past decades, the recurrence and metastasis of liver cancer are still obstacles for us. Inositol polyphosphate-5-phosphatase K (INPP5K) belongs to the family of phosphoinositide 5-phosphatases (PI 5-phosphatases), which have been reported to be associated with cell migration, polarity, adhesion, and cell invasion, especially in cancers. However, there have been few studies on the correlation of INPP5K and liver cancer. In this study, we explored the prognostic significance of INPP5K in liver cancer through bioinformatics analysis of data collected from The Cancer Genome Atlas (TCGA) database. Chi-square and Fisher exact tests were used to evaluate the relationship between INPP5K expression and clinical characteristics. Our results showed that low INPP5K expression was correlated with poor outcomes in liver cancer patients. Univariate and multivariate Cox analyses demonstrated that low INPP5K mRNA expression played a significant role in shortening overall survival (OS) and relapse-free survival (RFS), which might serve as the useful biomarker and prognostic factor for liver cancer. In conclusion, low INPP5K mRNA expression is an independent risk factor for poor prognosis in liver cancer.

Ubiquitin-like modifier-activating enzyme 7 as a marker for the diagnosis and prognosis of breast cancer

Ubiquitin-like modifier-activating enzyme 7 (UBA7) is a specific E1-like ubiquitin-activating enzyme involved in interferon-stimulated gene 15 (ISG15) conjugation. UBA7 expression has been reported to be notably decreased in lung cancer. The present study aimed to investigate the changes in UBA7 expression in breast cancer and the association between UBA7 expression and clinical characteristics, and to elucidate the diagnostic and prognostic significance of UBA7 in breast cancer. The clinical data and RNA-sequencing expression values of 1,104 patients with breast cancer were downloaded from The Cancer Genome Atlas database. The associations between UBA7 expression and clinical characteristics were determined using χ2 and Fisher's exact tests. UBA7 expression values were divided into low and high groups using the optimal cut-off value, as determined by the overall survival (OS) value identified via a receiver operating characteristic (ROC) curve analysis, to further study the association between UBA7 expression and clinical characteristics. The diagnostic capability of UBA7 was assessed via ROC analysis, and Kaplan-Meier curve and Cox regression analyses were performed to determine the prognostic value of UBA7. The results demonstrated that UBA7 expression was decreased in breast cancer, and significant differences were observed between groups with regards to vital status, tumor classification, metastasis classification, histological type, sex, molecular subtype, and expression levels of progesterone receptor, estrogen receptor (ER) and human epidermal growth factor receptor 2. Low and high UBA7 expression levels were associated with age, ER expression, menopause status, Tumor-Node-Metastasis classification stage, margin status, vital status, radiation therapy use, OS and relapse-free survival. Furthermore, patients with low UBA7 expression levels had a poor prognosis. UBA7 expression also demonstrated an ability to diagnose patients at all clinical stages. Taken together, the results indicated that UBA7 expression was significantly decreased in breast cancer, and was associated with clinical characteristics and prognosis. Thus, UBA7 can be deemed as a potential biomarker in breast cancer, and may serve as a target in treatment.

Small Nucleolar RNA Host Gene 1 (SNHG1) and Chromosome 2 Open Reading Frame 48 (C2orf48) as Potential Prognostic Signatures for Liver Cancer by Constructing Regulatory Networks

Background

Liver cancer is a common malignant tumor with poor prognosis. The present study sought to identify potential signatures that can predict the prognosis of patients with liver cancer.

Material/Methods

The RNA sequencing (RNA-seq) and clinical information of liver cancer patients were obtained from the Cancer Genome Atlas (TCGA) database. Differentially expressed long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and messenger RNAs (mRNAs) were identified between liver cancer and adjacent normal tissues. After predicting lncRNA–miRNA and miRNA–mRNA pairs using online databases, the competing endogenous RNA (ceRNA) networks were constructed. Furthermore, the prognostic value of these differentially expressed genes was evaluated using univariate and multivariate Cox regression analyses.

Results

After constructing the ceRNA network, 2 lncRNAs small nucleolar RNA host gene 1 (SNHG1) and chromosome 2 open reading frame 48 (C2orf48) with the most nodes were identified. Correlation analysis revealed that SNHG1 was correlated with miR-195 and C2orf48 was correlated with miR-195 and miR-93. High expression of SNHG1, C2orf48, and miR-93 can contribute to poorer clinical outcomes compared to low expression. Furthermore, low miR-195 expression was correlated with shorter survival time than was high expression. SNHG1 and C2orf48 were closely associated with histology grade. Univariate and multivariate Cox regression analyses confirmed that SNHG1 and C2orf48 are risk factors for liver cancer.

Conclusions

Our findings revealed that SNHG1 and C2orf48 possess potential prognostic value and should be considered as possible biomarkers for predicting clinical outcomes for patients with liver cancer.

Comprehensive evaluation of SPATS2 expression and its prognostic potential in liver cancer

Spermatogenesis associated serine rich 2 (SPATS2) has been reported to be dysregulated in few types of cancer; however, no reports have investigated SPATS2 in liver cancer. The aim of the present study was to investigate SPATS2 expression in liver cancer and to analyze its association with the prognosis of liver cancer patients.We examined the differential expression of SPATS2 in liver cancer by exploring The Cancer Genome Atlas (TCGA) database. The diagnostic efficiency of SPATS2 was obtained by Receiver Operating Characteristic (ROC) curve. The Chi-Squared test was used to assess clinical relevance. Survival analysis and Cox regression model were used to detect the effect of SPATS2 on the survival of liver cancer patients. Gene Set Enrichment Analysis (GSEA) was used to identify signaling pathways related to SPATS2 expression.SPATS2 is highly expressed in liver cancer (P < 2.2e-16) and has the high diagnostic ability (AUC = 0.964). Survival analysis showed that patients with high SPATS2 expression have an apparently shorter overall survival (OS, P < .0001) and relapse-free survival (RFS, P < .0001). Cox regression analysis showed that high SPATS2 expression might be an independent risk factor for liver cancer (OS, HR = 2.41, P = .000; RFS, HR = 1.90, P < .001). GSEA analysis identified 3 signaling pathways (Mitotic spindle, G2 M checkpoint, E2F targets) that were enriched in the presence of high SPATS2 expression.SPATS2 expression could be a novel diagnostic and prognostic biomarker in 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.

Clinical characteristics and prognostic value of MEX3A mRNA in liver cancer

BACKGROUND

MEX3A is an RNA-binding proteins (RBPs) that promotes the proliferation, invasion, migration and viability of cancer cells. The aim of this study was to explore the clinicopathological characteristics and prognostic significance of MEX3A mRNA expression in liver cancer.

METHODS

RNA-Seq and clinical data were collected from The Cancer Genome Atlas (TCGA). Boxplots were used to represent discrete variables of MEX3A. Chi-square tests were used to analyze the correlation between clinical features and MEX3A expression. Receiver operating characteristic (ROC) curves were used to confirm diagnostic ability. Independent prognostic ability and values were assessed using Kaplan-Meier curves and Cox analysis.

RESULTS

We acquired MEX3A RNA-Seq from 50 normal liver tissues and 373 liver cancer patients along with clinical data. We found that MEX3A was up-regulated in liver cancer which increased according to histological grade (p < 0.001). MEX3A showed moderate diagnostic ability for liver cancer (AUC = 0.837). Kaplan-Meier curves and Cox analysis revealed that the high expression of MEX3A was significantly associated with poor survival (OS and RFS) (p < 0.001). Moreover, MEX3A was identified as an independent prognostic factor of liver cancer (p < 0.001).

CONCLUSIONS

MEX3A expression shows promise as an independent predictor of liver cancer prognosis.

Elevated high mobility group A2 expression in liver cancer predicts poor patient survival

BACKGROUND

liver cancer is a malignant tumor with a high morbidity and mortality that endangers human health. High mobility group A2 (HMGA2) is a chromosome associated protein that participates in embryogenesis, tissue development, tumorigenesis and development.

OBJECTIVE

to explore the relationship between HMGA2 expression and the clinicopathological parameters and survival of liver cancer patients using The Cancer Genome Atlas Liver Hepatocellular Carcinoma (HCC) data.

METHODS

RNA-sequencing data and the corresponding clinical characteristics of the patients were downloaded from the Atlas database. The Chi-squared test was used to assess the relationship between HMGA2 expression and clinical variables. Cox regression analysis was used to compare survival rates between the high- and low-expressing groups; the p-values and Kaplan-Meier survival curves were compared using the log-rank test.

RESULTS

RNA-seq data from 373 cases of liver cancer cases were analyzed. HMGA2 was overexpressed in liver cancer and significantly associated with gender (p = 0.0357), T classification (p = 0.0063), clinical classification (p = 0.0026) and overall survival (p = 0.0386). According to the multivariate analysis, HMGA2 could independently predict overall survival in liver cancer.

CONCLUSIONS

HMGA2 independently predicts poor prognosis in liver cancer and serves as a molecular marker to determine disease prognosis.

GPSM2 Serves as an Independent Prognostic Biomarker for Liver Cancer Survival

BACKGROUND AND OBJECTIVE

Liver cancer is a malignancy with a poor prognosis. G protein signaling modulator 2 is mainly related to cell division and cell cycle regulation. In this review, the relationship between G protein signaling modulator 2 and clinical characteristics of patients with liver cancer has been explored, especially with respect to its prognostic value.

METHODS

G protein signaling modulator 2 messenger RNA expression and clinicopathological characteristics of patients with liver cancer were obtained from The Cancer Genome Atlas. The expression level of G protein signaling modulator 2 RNA-Seq was validated by using Gene Expression Omnibus. Chi-square test was performed to evaluate the relationship between G protein signaling modulator 2 expression and clinical characteristics. The threshold value of G protein signaling modulator 2 in the diagnosis of liver cancer was evaluated by a receiver-operating characteristic curve. Cox regression analysis and Kaplan-Meier curves were performed to evaluate the relationship between G protein signaling modulator 2 and liver cancer prognosis, which included overall and residual-free survival, and explored the prognostic value of G protein signaling modulator 2. Liver cancer survival analyses were validated by using the data of G protein signaling modulator 2 RNA-Seq from the International Cancer Genome Consortium.

RESULTS

The expression level of G protein signaling modulator 2 messenger RNA was remarkably higher in liver cancer than that in healthy tissues (P < 2.2 × e-16), which was also validated by data from the GSE14520 database. In addition, high G protein signaling modulator 2 expression significantly correlated with histological grade (P = .020), vital status (P < .001), clinical (P = .001), and T stage (P = .001). The receiver-operating characteristic curves showed G protein signaling modulator 2 to be an advantageous diagnostic molecule for liver cancer (area under curve = 0.893). Furthermore, the results of Cox analysis and Kaplan-Meier curves suggested that the upregulation of G protein signaling modulator 2 expression is linked to poor prognosis and G protein signaling modulator 2 messenger RNA could be an independent predictor for liver cancer, which was validated by data from the International Cancer Genome Consortium database.

CONCLUSIONS

G protein signaling modulator 2 messenger RNA was overexpressed in liver cancer, and G protein signaling modulator 2 is an independent prognostic factor. G protein signaling modulator 2 is expected to be a treatment target for cancer.

Low EIF2B5 expression predicts poor prognosis in ovarian cancer

Ovarian cancer has the highest mortality among gynecological cancers. Although ovarian cancer usually responds well to chemotherapy, most patients still have a poor prognosis. EIF2B5 is a crucial molecule in posttranscriptional modifications involved in tumor progression, and here we investigated the prognostic role of EIF2B5 in ovarian cancer. We examined the differential expression of EIF2B5 mRNA in ovarian cancer by exploring The Cancer Genome Atlas (TCGA) database. The chi square test was used to identify a clinical correlation. Survival analysis and Cox regression model were performed to determine the association between EIF2B5 expression and overall survival (OS) in ovarian cancer patients. As a result, Low EIF2B5 expression was found in ovarian cancer tissues and correlated with survival status. Survival analysis showed that ovarian cancer patients with low EIF2B5 expression had a short OS. Moreover, Cox regression analysis indicated that low EIF2B5 expression was an independent risk factor for a poor prognosis in ovarian cancer. Additionally, according to gene set enrichment analysis, mesenchymal transition, angiogenesis, coagulation, and bile acid metabolism were differentially enriched in ovarian cancer with high EIF2B5 expression. In conclusion, Low EIF2B5 expression is an independent risk factor for a poor prognosis in ovarian cancer patients.

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.

High MAST2 mRNA expression and its role in diagnosis and prognosis of liver cancer

Liver cancer is a high morbidity and low survival disease all over the world. Chromosomal instability is hallmark of liver cancer. Microtubule-associated serine and threonine kinase 2 (MAST2), as a microtubule associated protein, may involve in tumorous chromosomal instability and plays important roles in cell proliferation and survival. The role of MAST2 in liver cancer has not been well elucidated, which is the aim of our study. In this study, The Cancer Genome Atlas database was used to study the MAST2 mRNA expression in liver cancer, and Chi-squared tests were performed to test the correlation between clinical features and MAST2 expression. ROC curve was performed to examined the diagnostic capacity. The prognostic value of MAST2 in liver cancer was assessed through Kaplan-Meier curves as well as Cox analysis. Our results showed MAST2 was upregulated in liver cancer, and the area under the curve (AUC) was 0.925 and indicated powerful diagnostic capability. High MAST2 expression was associated with advanced clinical status such as histological type (p = 0.0059), histologic grade (p = 0.0142), stage (p = 0.0008), T classification (p = 0.0028), N classification (p = 0.0107), survival status (p = 0.0062), and poor prognosis of patients. Importantly, MAST2 was an independent risk factor for patients' prognosis after adjusting for other risk factors including stage, T classification, and residual tumor. In total, MAST2 is a potential diagnostic and prognostic biomarker of liver cancer.

High peroxidasin-like expression is a potential and independent prognostic biomarker in breast cancer

Breast cancer is a frequent female malignant tumor with high mortality and poor prognosis. Peroxidasin like (PXDNL) has many biological functions, including characteristic activity of hormone biosynthesis, host defense, and cell motility. In addition, PXDNL is closely connected with the progression of breast cancer. In this study, we found that PXDNL may be an independent prognostic biomarker of breast cancer.We tested the mRNA expression of PXDNL in breast cancer by detecting The Cancer Genome Atlas (TCGA) database. The chi-squared test was used to evaluate clinical correlation. The receiver operating characteristic (ROC) curves were drawn to evaluate diagnosis potential in breast cancer. Subsequently, survival analyses were performed to identify the relevance between the expression of PXDNL and the overall survival/relapse-free survival of patients with breast cancer. Univariate/multivariate Cox regression model was executed to detect risk factors affecting the prognosis of patients with breast cancer.PXDNL is highly expressed in breast cancer tissues and is related to survival status of patients. The ROC curve showed that PXDNL had beneficial diagnostic ability in breast cancer. Survival analysis indicated that patients with breast cancer with high PXDNL expression generally had decreased overall survival/relapse-free survival. Univariate/multivariate Cox model analyses further suggested an association between PXDNL expression and prognosis of patients with breast cancer.High PXDNL expression is a potential and independent prognostic biomarker in breast cancer.

A new prognostic factor of breast cancer: High carboxyl ester lipase expression related to poor survival

OBJECTIVE

The enzyme carboxyl ester lipase (CEL), known as bile salt-dependent lipase (BSDL) or bile salt-stimulated lipase (BSSL), is mainly expressed in pancreatic acinar cells and lactating mammary glands. To investigate the link between CEL expression of breast cancer (BC) tissues and the survival of BC patients by analyzing The Cancer Genome Atlas Breast Carcinoma (TCGA-BRCA) level 3 data.

METHODS

The clinical information and RNA-sequencing (RNA-Seq) expression data were downloaded from TCGA. Patients were divided into a high CEL expression group and a low CEL expression group using the optimal cutoff value (5.611) identified from the ROC curve. Chi-square test and Fisher exact test were used to find the correlation between the expression of CEL and clinicopathologic features. To assess the diagnostic capability, the receiver operating characteristic (ROC) curve of CEL was drawn. The survival differences between high and low CEL expression groups were compared by Cox regression analysis. Log-rank test was applied to the calculation of p values and the comparison of the Kaplan-Meier curves. Furthermore, Gene Expression Omnibus (GEO) datasets were used for external data validation.

RESULTS

Analysis of 1104 cases of tumor data showed that CEL was over-expressed in breast cancer. There were relationships between high CEL expression and clinicopathologic features. The high CEL expression group had a lower survival. By analyzing the area under the ROC curve (AUC) of CEL, it was found to have a limited diagnostic capability. CEL expression may be an independent prognostic factor for breast cancer survival through the multivariate analysis. The validation in GEO datasets also showed that CEL expression was higher in breast tumor tissues than in normal breast tissues. High CEL expression was associated with the poor overall survival of breast cancer.

CONCLUSIONS

High CEL expression may be an independent prognostic factor for the poor survival of breast cancer.

Investigation of the Clinical Significance and Prognostic Value of the lncRNA ACVR2B-As1 in Liver Cancer

A refined liver cancer staging system and effective prognostic prediction can help clinicians make optimized treatment decisions, which is essential in our fight against cancer and for improving the unsatisfying survival rate of liver cancer globally. The prognosis of liver cancer is not only related to tumor status, it is also affected by the patients' liver functions and the chosen treatment. Currently, several staging systems are being tested. Herein, we analyzed RNA-seq data from the TCGA database and identified a newly annotated lncRNA, ACVR2B-AS1, whose expression is upregulated in liver cancer. Higher ACVR2B-AS1 expression is an independent adverse prognostic factor for overall survival (OS) and relapse-free survival (RFS) in liver cancer patients. Our work suggests that the lncRNA ACVR2B-AS1 could be a candidate biomarker for liver cancer prognosis. Furthermore, ACVR2B-AS1 might serve as a potential therapeutic target, which is a possibility that is worthy of further study.

Expression of La Ribonucleoprotein Domain Family Member 4B (LARP4B) in Liver Cancer and Their Clinical and Prognostic Significance

BACKGROUND AND OBJECTIVE

Liver cancer is a common malignant tumor with few poor diagnostic and prognostic markers, which greatly shortens the potential life span of patients. The RNA-binding protein la ribonucleoprotein 4B (LARP4B) has a la motif (lam) that is important in the process of cancer. We aimed to explore the role of LARP4B in the diagnosis and prognosis of liver cancer.

METHODS

The Cancer Genome Atlas (TCGA) database was searched to detect LARP4B gene expression in liver cancer. The clinical relevance and diagnostic ability of LARP4B were evaluated by a chi-squared test and a receiver operating characteristic (ROC) curve, respectively. Survival and risk factors of patients with liver cancer were assessed by survival analysis and univariate/multivariate Cox regression model. Additionally, we carried out gene set enrichment analysis (GSEA) to identify LARP4B-related signaling pathways in liver cancer.

RESULTS

LARP4B mRNA was highly expressed in liver cancer tissues and was correlated with survival status. The chi-squared test showed that LARP4B had clinical relevance, while ROC curves showed that LARP4B had good diagnostic ability. Survival analysis showed that liver cancer patients with high LARP4B expression had shorter overall/relapse-free survival. The univariate/multivariate Cox regression model indicated that high LARP4B expression may be an independent risk factor for the prognosis of liver cancer patients. Finally, we found that genes involved in the G2M checkpoint, E2F targets, and mitotic spindle were differentially enriched in the high LARP4B-expression phenotype.

CONCLUSIONS

LARP4B is a potential independent biomarker for diagnosis and prognosis in liver cancer patients.

OGDHL Expression as a Prognostic Biomarker for Liver Cancer Patients

BACKGROUND AND OBJECTIVE

Liver cancer is a highly malignant tumor, and patients typically have poor prognoses. Metabolic reprogramming is a hallmark of cancer, and downregulation of oxoglutarate dehydrogenase-like (OGDHL) contributes to the onset and progression of several cancers. We examined the role of altered OGDHL expression in liver cancer and determined its value as a diagnostic and prognostic indicator for patients.

MATERIAL AND METHODS

R (version 3.5.1) and several R extensions were used for data mining of The Cancer Genome Atlas (TCGA) dataset (including RNAseq and clinical information) and statistical analysis. Receiver operating characteristic analysis was used to determine the diagnostic value of OGDHL. The chi-squared test was used to identify the clinical correlates of OGDHL downregulation. Survival analysis (with the log-rank test) and univariate and multivariate Cox analysis were used to evaluate the effect of OGDHL expression on overall survival (OS) and relapse-free survival. TCGA was used for analysis of gene set enrichment.

RESULTS

OGDHL had lower expression in cancerous liver tissues than noncancerous adjacent tissues, and low expression correlated with more advanced patient age, histologic grade, stage, T classification, and poor survival. Patients with lower OGDHL expression had shorter OS and relapse-free survival. Multivariate Cox regression indicated that low OGDHL expression was an independent risk factor for poor prognosis. Gene set enrichment analysis indicated enrichment of the mitotic spindle, G2M checkpoint, and E2F targets in the OGDHL low expression phenotype.

CONCLUSION

OGDHL has potential as a diagnostic and prognostic biomarker for liver cancer.

Low CYP24A1 mRNA expression and its role in prognosis of breast cancer

Breast cancer is the most common malignant cancer in women. CYP24A1 expression regulates cellular response to vitamin D, which has antitumor effects against breast cancer. This study aimed to identify the correlation between CYP24A1 mRNA expression and prognosis of breast cancer. This study enrolled 1102 patients, including 1090 females and 12 males, from TCGA-BRCA cohort. The Cancer Genome Atlas database was used to study CYP24A1 mRNA expression in breast cancer, and Chi-squared tests were performed to test the correlation between clinical features and CYP24A1 expression. The prognostic value of CYP24A1 in breast cancer was assessed using Kaplan-Meier curves and Cox analysis. Low CYP24A1 expression was associated with age, molecular subtype, ER, PR, HER2, menopause status, N classification, vital status, overall survial and relapse-free survival. CYP24A1 presented a moderate diagnostic ability in breast cancer. Furthermore, low CYP24A1 expression was correlated with poor prognosis. CYP24A1 was an independent risk factor for breast cancer. CYP24A1 plays an important role in prognosis of breast cancer. CYP24A1 has the potential to be a biomarker, especially in predicting prognosis.

PGM5: a novel diagnostic and prognostic biomarker for liver cancer

BACKGROUND

Liver cancer is a common malignancy and a significant public health problem worldwide, but diagnosis and prognostic evaluation remain challenging for clinicians. Metabolic reprogramming is a hallmark of cancer, and we therefore examined the diagnostic and prognostic value of a metabolic enzyme, phosphoglucomutase-like protein 5 (PGM5), in liver cancer.

METHODS

All data were from The Cancer Genome Atlas database. R and related statistical packages were used for data analysis. Hepatic PGM5 expression was determined in different groups, and the chi-squared test and Fisher's exact test were used to determine the significance of differences. The pROC package was used to determine receiver operating characteristic (ROC) curves, the survival package was used to for survival analysis and development of a Cox multivariable model, and the ggplot2 package was used for data visualization.

RESULTS

PGM5 expression was significantly lower in cancerous than adjacent normal liver tissues, and had modest diagnostic value based on ROC analysis and calculations of area under the curve (AUC). Hepatic PGM5 expression had positive associations with male sex and survival, but negative associations with advanced histologic type, advanced histologic grade, advanced stage, and advanced T classification. Patents with low PGM5 levels had poorer overall survival and relapse-free survival. PGM5 was independently associated with patient prognosis.

CONCLUSION

PGM5 has potential use as a diagnostic and prognostic biomarker for liver cancer.

ITGA3 serves as a diagnostic and prognostic biomarker for pancreatic cancer

Background and objective: ITGA3 is a cell surface adhesion protein that interacts with extracellular matrix proteins which function in cancer metastasis. We examined the relationship of pancreatic ITGA3 expression with the clinical and pathological characteristics of patients with pancreatic cancer. Methods: Data mining was used to analyze pancreatic cancer data from The Cancer Genome Atlas database. A Chi squared test was used to evaluate correlations of ITGA3 expression with clinical and pathological parameters. Receiver operating characteristic (ROC) analysis was used to evaluate the diagnostic performance of ITGA3 expression. Survival analysis and Cox regression analysis were used to examine the prognostic value of ITGA3 expression. Gene Set Enrichment Analysis (GSEA) was used to identify signaling pathways related to ITGA3 expression. Results: Pancreatic expression of ITGA3 was greater in patients with pancreatic cancer than those without cancer, and was also associated with histological type, histological grade, stage, T classification, vital status, and relapse. ROC analysis indicated that ITGA3 had significant diagnostic value, in that high expression correlated with poor overall survival and relapse-free survival, especially in patients with early-stage cancer. Cox analysis indicated that high ITGA3 expression was an independent prognostic factor for pancreatic cancer. GSEA analysis identified 9 signaling pathways that were enriched in the presence of high ITGA3 expression. Conclusion: Expression of ITGA3 can be used as a diagnostic and prognostic biomarker in pancreatic cancer.

TROAP Promotes Breast Cancer Proliferation and Metastasis

Trophinin-associated protein (TROAP) is a cytoplasmic protein required for microtubular cytoskeleton regulation and spindle assembly, and its expression plays a critical role in the initiation and progression of various types of cancer. However, little is known about the role of TROAP in breast cancer (BC). TROAP mRNA expression levels and clinical data from Gene Expression Omnibus (GEO) datasets (GSE42568, 104 BC patients; GSE1456, 159 BC patients; and GSE21653, 266 BC patients) were analyzed by the R2: Genomics Analysis and Visualization Platform to estimate overall survival (OS). We also analyzed the genes correlated with TROAP by gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to predict potential relationships between TROAP and other genes in BC. Our study verified that both TROAP mRNA and protein expression levels were upregulated in human BC samples and cell lines. In vitro experiments demonstrated that TROAP knockdown significantly inhibited cell proliferation, the G1 to S phase transition, and the migration and invasion abilities of BC cells. The present study suggests that TROAP plays an important role in promoting the proliferation, invasion, and metastasis of BC.

ATP binding cassette subfamily B member 9 (ABCB9) is a prognostic indicator of overall survival in ovarian cancer

Ovarian cancer (OC) is one of the most common gynecological malignancies and owns the highest mortality rate among all gynecological malignant tumors. ATP binding cassette subfamily B member 9 (ABCB9) is an antigen processing-like (TAPL) transporter that has been found to be involved in the development and progression of various malignant tumors in accumulating reports. However, the potential role of ABCB9 in OC has never been reported.In this study, ABCB9 expression was evaluated in normal ovarian tissues and ovarian cancer tissues using The Cancer Genome Atlas (TCGA) database. And the associations between ABCB9 expression and clinical parameters of patients of OC were evaluated by Chi-square tests. Kaplan-Meier analysis and Cox regression analysis were performed to evaluate the prognostic significance of ABCB9. GSEA was performed to explore related signaling pathway.ABCB9 expression levels were significantly decreased in OC compared with normal ovarian tissues (P < .001). Low ABCB9 expression was associated with survival status (P = .0148) in OC. Kaplan-Meier analysis showed that low ABCB9 expression was associated with poor overall survival in OC (P = .0032). Multivariable Cox regression analysis indicated that low ABCB9 expression was an independent prognostic factor (HR 0.64; P = .01) in OC patients. Besides, epithelial mesenchymal transition, UV response, and TGF-β signaling were enriched in low ABCB9 expression phenotype, respectively, examined by gene set enrichment analysis.These results suggest that ABCB9 is an independent prognostic indicator in OC with certain clinical significance.

Trophinin-associated protein expression is an independent prognostic biomarker in lung adenocarcinoma

Background

Lung cancer is the leading cause of cancer-related deaths worldwide, with lung adenocarcinoma (LAC) representing the most common subtype. Trophinin-associated protein (TROAP) is a cytoplasmic protein first identified to mediate the process of embryo transplantation, which has been recently found to be involved in microtubule regulation. However, limited information about the role of TROAP in LAC is available.

Methods

We evaluated the relationship of TROAP expression in LAC tissues with clinical pathologic parameters and the survival time in LAC patients based on a statistical analysis of The Cancer Genome Atlas (TCGA) lung cancer data (N=528). Differences in survival between high and low expression groups (median expression cutoff) from the Cox univariate/multivariate regression analysis were then compared.

Results

According to the Chi-square tests, we found high TROAP expression correlated with younger age (≤60) (P=0.047), male sex (P<0.005), an earlier T-stage (P=0.011), N-stage (P=0.017), M-stage (P=0.022), TNM (P=0.007), and a longer smoking history (>30 pack-year) (P<0.001). A Kaplan-Meier analysis demonstrated that high TROAP expression may correspond with poor overall survival of LAC patients in T3 stage (P=0.0013), N0 stage (P=0.014), and M0 stage (P=0.0023). Multivariate analysis confirmed that TROAP expression was related to overall survival in LAC patients independently [hazard ratio (HR): 1.784, 95% confidence interval (CI): 1.072-2.968, P=0.026].

Conclusions

Our results suggested that TROAP is an independent prognostic biomarker of poor survival in LAC.