Aberrant FAM64A mRNA expression is an independent predictor of poor survival in pancreatic cancer

FAM64A regulates the malignant phenotype and tumor microenvironment of non-small cell lung cancer by activating the JAK/STAT3/PDL1 axis

Non-small cell lung cancer (NSCLC) is a life-threatening disease that still lacks effective targeted treatment. Family with sequence similarity 64, member A (FAM64A) is dysregulated in different malignancies and participates in the cancer progression. To address the role of FAM64A in NSCLC. The FAM64A expression was detected by reverse transcription quantitative polymerase chain reaction and western blotting. Short-hairpin RNAs (shRNAs) against FAM64A were transfected into A549 and H460 cells. The role of FAM64A in vitro was evaluated by cell counting kit-8, transwell, enzyme-linked immunosorbent assay, immunofluorescence and western blotting. In vivo role of FAM64A was addressed in xenografted mice using immunohistochemistry and western blotting. FAM64A was upregulated in NSCLC that predicted a dismal prognosis for NSCLC patients. Knockdown of FAM64A diminished cell viability, invaded cell numbers, the Vimentin expression and the concentrations of TGF-β and IL-10, but fostered the E-cadherin expression and the concentrations of IL-2 and IFN-γ in NSCLC cells. Mechanistically, silencing of FAM64A declined the expression of JAK/STAT3/PD-L1 pathway, which was restored with the application of RO8191, an activator of JAK/STAT3 pathway. The inhibitory role of FAM64A knockdown in NSCLC cell proliferation, invasion, EMT and immune escape was inverted by the management of RO8191. In vivo, knockdown of FAM64A reduced tumor size and weight, the level of Vimentin and PD-L1, and the expression of JAK/STAT3/PD-L1 pathway, but enhanced the IFN-γ level. Upregulation of FAM64A promoted proliferation, invasion, EMT and immune escape through activating JAK/STAT3/PD-L1 axis.

The immune-related gene CD5 is a prognostic biomarker associated with the tumor microenvironment of breast cancer

The occurrence and progression of breast cancer (BCa) are complex processes involving multiple factors and multiple steps. The tumor microenvironment (TME) plays an important role in this process, but the functions of immune components and stromal components in the TME require further elucidation. In this study, we obtained the RNA-seq data of 1086 patients from The Cancer Genome Atlas (TCGA) database. We calculated the proportions of tumor-infiltrating immune cells (TICs) and immune and stromal components using the CIBERSORT and ESTIMATE methods, and we screened differentially expressed genes (DEGs). Univariate Cox regression analysis of overall survival was performed on the DEGs, and a protein-protein interaction network of their protein products was generated. Finally, the hub gene CD5 was obtained. High CD5 expression was found to be associated with longer survival than low expression. Gene set enrichment analysis showed that DEGs upregulated in the high-CD5 expression group were mainly enriched in tumor- and immune-related pathways, while those upregulated in the low-expression group were enriched in protein export and lipid synthesis. TIC analysis showed that CD5 expression was positively correlated with the infiltration of CD8+ T cells, activated memory CD4+ T cells, gamma delta T cells, and M1 macrophages and negatively correlated with the infiltration of M2 macrophages. CD5 can increase anticancer immune cell infiltration and reduce M2 macrophage infiltration. These results suggest that CD5 is likely a potential prognostic biomarker and therapeutic target, providing novel insights into the treatment and prognostic assessment of BCa.

Clinical diagnostic value of PIMREG on liver cancer cell phenotype and tumorigenic ability in nude mice

OBJECTIVES

In vitro experiments were manipulated to investigate the effect of the PIMREG (PICALM-interacting mitotic regulator gene) expression level on the malignant phenotype of liver cancer cells and their tumorigenesis ability in nude mice, and bioinformatics were used to analyze the clinical diagnostic and prognostic value in liver cancer.

METHODS

After liver cancer-related data were obtained from the TCGA database and GTEx database, the differences in PIMREG expression in liver cancer and normal liver tissue were compared using bioinformatics, and their correlation with the clinical pathological characteristics of liver cancer and the prognosis value were analyzed. A knockdown and overexpression model of PIMREG was constructed using Huh7 cells. The effect of the PIMREG expression level on the malignant phenotype of Huh7 cells was tested through CCK-8 and Transwell experiments. At the same time, animal knockdown and overexpression models were constructed to study the effect of the PIMREG expression level on the tumorigenesis ability in nude mice.

RESULTS

Bioinformatics analysis showed that PIMREG mRNA was significantly overexpressed in liver cancer tissue (P<0.001). There were differences in T-staging (P<0.001), pathological staging (P=0.002), vascular infiltration (P<0.001), histological grading (P<0.001), and AFP levels (P<0.001) between the high- and low-expression groups. A high expression of PIMREG is associated with a poor prognosis, manifested as a significant decrease in the overall survival, disease-specific survival, and progression-free survival rates of patients (P values of 0.006, 0.014, and 0.002, respectively). In the PIMREG overexpression model, the proliferation rate and invasion ability of Huh7 cells were significantly increased, and the tumorigenesis ability of nude mice was significantly enhanced. In the knockdown model, the opposite results were observed.

CONCLUSIONS

The PIMREG gene is highly expressed in hepatocellular carcinoma, and increasing its expression level can significantly promote the malignant phenotype of liver cancer cells and their tumorigenesis ability in nude mice. Knocking down its expression level has the opposite effect. The expression level of PIMREG is related to the pathological stages of liver cancer patients, and its elevated expression is a risk factor for poor prognosis. PIMREG may become a new target for the clinical diagnosis, treatment, and prognosis evaluation of liver cancer.

FAM64A aggravates proliferation, invasion, lipid droplet formation, and chemoresistance in gastric cancer: A biomarker for aggressiveness and a gene therapy target

FAM64A is a mitogen-induced regulator of the metaphase and anaphase transition. Here, we found that FAM64A messenger RNA (mRNA) and protein expression levels were higher in gastric cancer tissue than in normal mucosa (p < .05). FAM64A methylation was negatively correlated with FAM64A mRNA expression (p < .05). The differentially expressed genes of FAM64A were mainly involved in digestion, potassium transporting or exchanging ATPase, contractile fibers, endopeptidase, and pancreatic secretion (p < .05). The FAM64A-related genes were principally categorized into ubiquitin-mediated proteolysis, cell cycle, chromosome segregation and mitosis, microtubule binding and organization, metabolism of amino acids, cytokine receptors, lipid droplet, central nervous system, and collagen trimer (p < .05). FAM64A protein expression was lower in normal gastric mucosa than intestinal metaplasia, adenoma, and primary cancer (p < .05), negatively correlated with older age, T stage, lymphatic and venous invasion, tumor, node, metastasis stage, and dedifferentiation (p < .05), and associated with a favorable overall survival of gastric cancer patients. FAM64A overexpression promoted proliferation, antiapoptosis, migration, invasion, and epithelial-mesenchymal transition via the EGFR/Akt/mTOR/NF-κB, while the opposite effect was observed for FAM64A knockdown. FAM64A also induced chemoresistance directly or indirectly through lipid droplet formation via ING5. These results suggested that upregulation of FAM64A expression might induce aggressive phenotypes, leading to gastric carcinogenesis and its subsequent progression. Thus, FAM64A could be regarded as a prognosis biomarker and a target for gene therapy.

Cell Cycle-Related FAM64A Could be Activated by TGF-β Signaling to Promote Glioma Progression

Gliomas are aggressive brain tumors characterized by uncontrolled cell proliferation. FAM64A, a cell cycle-related gene, has been found to promote cell proliferation in various tumors, including gliomas. However, the regulatory mechanism and clinical significance of FAM64A in gliomas remain unclear. In this study, we investigated FAM64A expression in gliomas with different grades and constructed FAM64A silenced cell lines to study its functions. Our results demonstrated that FAM64A was highly expressed in glioblastoma (P < 0.001) and associated with a poor prognosis (P < 0.001). Expression profiles at the single-cell resolution indicated FAM64A could play a role in a cell-cycle-dependent way to promote glioma cell proliferation. We further observed that FAM64A silencing in glioma cells resulted in disrupted proliferation and migration ability, and increased cell accumulation in the G2/M phase (P = 0.034). Additionally, TGF-β signaling upregulates FAM64A expression, and SMAD4 and FAM64A co-localize in high-grade glioma tissues. We found FAM64A knockdown inhibited TGF-β-induced epithelial-mesenchymal transition in glioma. Our findings suggest that FAM64A could serve as a diagnostic and therapeutic target in gliomas.

Whole Transcriptome Sequencing Reveals Cancer-Related, Prognostically Significant Transcripts and Tumor-Infiltrating Immunocytes in Mantle Cell Lymphoma

Mantle cell lymphoma (MCL) is an aggressive B-cell non-Hodgkin lymphoma (NHL) subtype characterized by overexpression of CCND1 and SOX11 genes. It is generally associated with clinically poor outcomes despite recent improvements in therapeutic approaches. The genes associated with the development and prognosis of MCL are still largely unknown. Through whole transcriptome sequencing (WTS), we identified mRNAs, lncRNAs, and alternative transcripts differentially expressed in MCL cases compared with reactive tonsil B-cell subsets. CCND1, VCAM1, and VWF mRNAs, as well as MIR100HG and ROR1-AS1 lncRNAs, were among the top 10 most significantly overexpressed, oncogenesis-related transcripts. Survival analyses with each of the top upregulated transcripts showed that MCL cases with high expression of VWF mRNA and low expression of FTX lncRNA were associated with poor overall survival. Similarly, high expression of MSTRG.153013.3, an overexpressed alternative transcript, was associated with shortened MCL survival. Known tumor suppressor candidates (e.g., PI3KIP1, UBXN) were significantly downregulated in MCL cases. Top differentially expressed protein-coding genes were enriched in signaling pathways related to invasion and metastasis. Survival analyses based on the abundance of tumor-infiltrating immunocytes estimated with CIBERSORTx showed that high ratios of CD8⁺ T-cells or resting NK cells and low ratios of eosinophils are associated with poor overall survival in diagnostic MCL cases. Integrative analysis of tumor-infiltrating CD8⁺ T-cell abundance and overexpressed oncogene candidates showed that MCL cases with high ratio CD8⁺ T-cells and low expression of FTX or PCA3 can potentially predict high-risk MCL patients. WTS results were cross-validated with qRT-PCR of selected transcripts as well as linear correlation analyses. In conclusion, expression levels of oncogenesis-associated transcripts and/or the ratios of microenvironmental immunocytes in MCL tumors may be used to improve prognostication, thereby leading to better patient management and outcomes.

Excessive activation of HOXB13/PIMREG axis promotes hepatocellular carcinoma progression and drug resistance

The transcription factor HOXB13 is bound up with the occurrence, progression and drug fast of many kinds of cancer. Nevertheless, the specific molecular mechanism of HOXB13 in hepatocellular carcinoma (HCC) is still unknown. This provides an obstacle to the exploration of HCC treatments targeting HOXB13. This study found that HOXB13 was up-regulated in HCC tissues. HOXB13 enhanced the multiplication and metastasis of HCC cells. It enhanced HCC cell drug and anoikis resistance. The analysis of HCC RNA seq data indicated that the expression of HOXB13 and PIMREG were positively correlated. Luciferase report assay showed that HOXB13 could activate PIMREG promoter transcription. The results of RT-qPCR and western blot showed that HOXB13 regulated the transcription of PIMREG. Western blot proved that high expression of PIMREG participated in DNA damage repair and cell cycle regulation by up-regulating RAD51, BRCA1, CDC25A, CDC25B and CDC25C and down-regulating HIPK2. This led to a significant increase in DNA repair capacity, accelerated cell cycle progression, and insensitive to DNA damage. Down-regulation of PIMREG in Hep3B cells overexpressing HOXB13 attenuated the phenotype induced by HOXB13. Therefore, HOXB13 functioned through PIMREG instead of directly regulating the transcription of RAD51, BRCA1, CDC25A, CDC25B and CDC25C. The same results were obtained in vivo. It was concluded that HOXB13 affected the expression of cell cycle and DNA repair related factors by up-regulating the transcription of PIMREG, thereby promoting the progression of HCC and enhancing the resistance of HCC to chemotherapeutics.

Predictive value of PIMREG in the prognosis and response to immune checkpoint blockade of glioma patients

Glioma is the most common primary brain tumor in the human brain. The present study was designed to explore the expression of PIMREG in glioma and its relevance to the clinicopathological features and prognosis of glioma patients. The correlations of PIMREG with the infiltrating levels of immune cells and its relevance to the response to immunotherapy were also investigated. PIMREG expression in glioma was analyzed based on the GEO, TCGA, and HPA databases. Kaplan–Meier survival analysis was used to examine the predictive value of PIMREG for the prognosis of patients with glioma. The correlation between the infiltrating levels of immune cells in glioma and PIMREG was analyzed using the CIBERSORT algorithm and TIMRE database. The correlation between PIMREG and immune checkpoints and its correlation with the patients’ responses to immunotherapy were analyzed using R software and the GEPIA dataset. Cell experiments were conducted to verify the action of PIMREG in glioma cell migration and invasion. We found that PIMREG expression was upregulated in gliomas and positively associated with WHO grade. High PIMREG expression was correlated with poor prognosis of LGG, prognosis of all WHO grade gliomas, and prognosis of recurrent gliomas. PIMREG was related to the infiltration of several immune cell types, such as M1 and M2 macrophages, monocytes and CD8+ T cells. Moreover, PIMREG was correlated with immune checkpoints in glioma and correlated with patients’ responses to immunotherapy. KEGG pathway enrichment and GO functional analysis illustrated that PIMREG was related to multiple tumor- and immune-related pathways. In conclusion, PIMREG overexpression in gliomas is associated with poor prognosis of patients with glioma and is related to immune cell infiltrates and the responses to immunotherapy.

Multi-omics data integration for subtype identification of Chinese lower-grade gliomas: a joint similarity network fusion approach

Lower-grade gliomas (LGG), characterized by heterogeneity and invasiveness, originate from the central nervous system. Although studies focusing on molecular subtyping and molecular characteristics have provided novel insights into improving the diagnosis and therapy of LGG, there is an urgent need to identify new molecular subtypes and biomarkers that are promising to improve patient survival outcomes. Here, we proposed a joint similarity network fusion (Joint-SNF) method to integrate different omics data types to construct a fused network using the Joint and Individual Variation Explained (JIVE) technique under the SNF framework. Focusing on the joint network structure, a spectral clustering method was employed to obtain subtypes of patients. Simulation studies show that the proposed Joint-SNF method outperforms the original SNF approach under various simulation scenarios. We further applied the method to a Chinese LGG data set including mRNA expression, DNA methylation and microRNA (miRNA). Three molecular subtypes were identified and showed statistically significant differences in patient survival outcomes. The five-year mortality rates of the three subtypes are 80.8%, 32.1%, and 34.4%, respectively. After adjusting for clinically relevant covariates, the death risk of patients in Cluster 1 was 5.06 times higher than patients in other clusters. The fused network attained by the proposed Joint-SNF method enhances strong similarities, thus greatly improves subtyping performance compared to the original SNF method. The findings in the real application may provide important clues for improving patient survival outcomes and for precision treatment for Chinese LGG patients. An R package to implement the method can be accessed in Github at https://github.com/Sameerer/Joint-SNF.

FAM64A promotes HNSCC tumorigenesis by mediating transcriptional autoregulation of FOXM1

Head and neck squamous cell carcinoma (HNSCC) still lacks effective targeted treatment. Therefore, exploring novel and robust molecular targets is critical for improving the clinical outcome of HNSCC. Here, we reported that the expression levels of family with sequence similarity 64, member A (FAM64A) were significantly higher in HNSCC tissues and cell lines. In addition, FAM64A overexpression was found to be strongly associated with an unfavorable prognosis of HNSCC. Both in vitro and in vivo evidence showed that FAM64A depletion suppressed the malignant activities of HNSCC cells, and vice versa. Moreover, we found that the FAM64A level was progressively increased from normal to dysplastic to cancerous tissues in a carcinogenic 4-nitroquinoline-1-oxide mouse model. Mechanistically, a physical interaction was found between FAM64A and forkhead box protein M1 (FOXM1) in HNSCC cells. FAM64A promoted HNSCC tumorigenesis not only by enhancing the transcriptional activity of FOXM1, but also, more importantly, by modulating FOXM1 expression via the autoregulation loop. Furthermore, a positive correlation between FAM64A and FOXM1 was found in multiple independent cohorts. Taken together, our findings reveal a previously unknown mechanism behind the activation of FOXM1 in HNSCC, and FAM64A might be a promising molecular therapeutic target for treating HNSCC.

Application of Proteomics in Pancreatic Ductal Adenocarcinoma Biomarker Investigations: A Review

Pancreatic ductal adenocarcinoma (PDAC), a highly aggressive malignancy with a poor prognosis is usually detected at the advanced stage of the disease. The only US Food and Drug Administration-approved biomarker that is available for PDAC, CA 19-9, is most useful in monitoring treatment response among PDAC patients rather than for early detection. Moreover, when CA 19-9 is solely used for diagnostic purposes, it has only a recorded sensitivity of 79% and specificity of 82% in symptomatic individuals. Therefore, there is an urgent need to identify reliable biomarkers for diagnosis (specifically for the early diagnosis), ascertain prognosis as well as to monitor treatment response and tumour recurrence of PDAC. In recent years, proteomic technologies are growing exponentially at an accelerated rate for a wide range of applications in cancer research. In this review, we discussed the current status of biomarker research for PDAC using various proteomic technologies. This review will explore the potential perspective for understanding and identifying the unique alterations in protein expressions that could prove beneficial in discovering new robust biomarkers to detect PDAC at an early stage, ascertain prognosis of patients with the disease in addition to monitoring treatment response and tumour recurrence of patients.

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.

Pan-Cancer Analysis of PIMREG as a Biomarker for the Prognostic and Immunological Role

Phosphatidylinositol binding clathrin assembly protein interacting mitotic regulator (PIMREG) localizes to the nucleus and can significantly elevate the nuclear localization of clathrin assembly lymphomedullary leukocythemia gene. Although there is some evidence to support an important action for PIMREG in the occurrence and development of certain cancers, currently no pan-cancer analysis of PIMREG is available. Therefore, we intended to estimate the prognostic predictive value of PIMREG and to explore its potential immune function in 33 cancer types. By using a series of bioinformatics approaches, we extracted and analyzed datasets from Oncomine, The Cancer Genome Atlas, Cancer Cell Lineage Encyclopedia (CCLE) and the Human Protein Atlas (HPA), to explore the underlying carcinogenesis of PIMREG, including relevance of PIMREG to prognosis, microsatellite instability (MSI), tumor mutation burden (TMB), tumor microenvironment (TME) and infiltration of immune cells in various types of cancer. Our findings indicate that PIMREG is highly expressed in at least 24 types of cancer, and is negatively correlated with prognosis in major cancer types. In addition, PIMREG expression was correlated with TMB in 24 cancers and with MSI in 10 cancers. We revealed that PIMREG is co-expressed with genes encoding major histocompatibility complex, immune activation, immune suppression, chemokine and chemokine receptors. We also found that the different roles of PIMREG in the infiltration of different immune cell types in different tumors. PIMREG can potentially influence the etiology or pathogenesis of cancer by acting on immune-related pathways, chemokine signaling pathway, regulation of autophagy, RIG-I like receptor signaling pathway, antigen processing and presentation, FC epsilon RI pathway, complement and coagulation cascades, T cell receptor pathway, NK cell mediated cytotoxicity and other immune-related pathways. Our study suggests that PIMREG can be applied as a prognostic marker in a variety of malignancies because of its role in tumorigenesis and immune infiltration.

Identification of the Effects of Chondroitin Sulfate on Inhibiting CDKs in Colorectal Cancer Based on Bioinformatic Analysis and Experimental Validation

With a high occurrence rate and high mortality, the treatment of colorectal cancer (CRC) is increasingly attracting the attention of scholars. Hub genes that determine the phenotypes of CRC become essential for targeted therapy. In the present study, the importance of cyclin-dependent kinases (CDKs) on the occurrence of CRC was identified by data mining of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The results showed that the gene expression levels of CDK1, CDK4, and CDK6 were obviously changed in different stages of CRC. Among the CDKs, CDK4 was suggested as an independent risk factor for CRC based on Cox analysis. Furthermore, chondroitin sulfate (CS), a kind of dietary supplement to treat osteoarthritis, was predicted to treat CRC based on its chemical structure and GEO datasets. Cell assay experiments with the human CRC cell line HCT-116 also verified this prediction. CS inhibited the gene and protein expression levels of CDKs and increased the ratios of apoptotic or dead HCT-116 cells by regulating mitogen-activated protein (MAP) kinase pathways. Our data highlight the essential roles of CDKs in CRC carcinogenesis and the effects of CS on treating CRC, both of which will contribute to the future CRC treatment.

Tumor-promoting function of PIMREG in glioma by activating the β-catenin pathway

Glioma is the most common primary brain tumor in adults with an adverse prognosis and obscure pathogenesis. PICALM interacting mitotic regulator protein (PIMREG) functions as an oncogene in multiple types of cancer, but its function in glioma remains unknown. The Gene Expression Profiling Interactive Analysis 2 (GEPIA2, http://gepia2.cancer-pku.cn/#index) showed that PIMREG expression in the glioma tissues was higher than that in normal brain tissues. Herein, cell counting kit-8 assay and flow cytometry analysis exhibited that overexpression of PIMREG significantly promoted the proliferation of glioma cells and the transition from G1 phase of the cell cycle to S phase. Wound-healing and transwell assays showed that overexpression of PIMREG markedly enhanced the migration and invasion of glioma cells. Western blot analysis revealed that overexpression of PIMREG increased the expression of cyclin D1, cyclin E, Vimentin, matrix metalloproteinase (MMP)-2, and MMP-9, but reduced the expression of E-cadherin. In addition, overexpression of PIMREG activated the β-catenin signaling pathway, as evidenced by the increased total and nuclear expression of β-catenin and the up-regulated expression of its downstream target c-myc. Furthermore, immunofluorescence staining further indicated the increased nuclear translocation of β-catenin in PIMREG-overexpressing cells. However, knockdown of PIMREG exerted opposite effects on glioma cells. Blockade of the β-catenin signaling by ICG-001 markedly impeded the promoting effects of PIMREG on glioma cell proliferation and invasion. In conclusion, PIMREG acts as a tumor promoter in glioma at least partly via activating the β-catenin signaling pathway. This study provides new insights into the molecular mechanism for glioma pathogenesis and treatment.

High expression of PIMREG predicts poor survival outcomes and is correlated with immune infiltrates in lung adenocarcinoma

Background

PIMREG is upregulated in multiple cancer types. However, the potential role of PIMREG in lung adenocarcinoma (LUAD) remains unclear. The present study aimed to explore its clinical significance in LUAD.

Methods

Using the Cancer Genome Atlas (TCGA) databases, we obtained 513 samples of LUAD and 59 normal samples from the Cancer Genome Atlas (TCGA) databases to analyze the relationship between PIMREG and LUAD. We used t and Chi-square tests to evaluate the level of expression of PIMREG and its clinical implication in LUAD. The prognostic value of PIMREG in LUAD was identified through the Kaplan–Meier method, Cox regression analysis, and nomogram. Gene set enrichment analysis (GSEA) and single-sample gene set enrichment analysis (ssGSEA) were performed to screen biological pathways and analyze the correlation of the immune infiltrating level with the expression of PIMREG in LUAD.

Results

PIMREG was highly expressed in patients with LUAD. Specifically, the level of PIMREG gradually increased from pathological stage I to IV. Further, we validated the higher expression of PIMREG expressed in LUAD cell lines. Moreover, PIMREG had a high diagnostic value, with an -AUC of 0.955. Kaplan–Meier survival and Cox regression analyses revealed that the high expression of PIMREG was independently associated with poor clinical outcomes. In our prognostic nomogram, the expression of PIMREG implied a significant prognostic value. Gene set enrichment analysis (GSEA) identified that the high expression PIMREG phenotype was involved in the mitotic cell cycle, mRNA splicing, DNA repair, Rho GTPase signaling, TP53 transcriptional regulation, and translation pathways. Next, we also explored the correlation of PIMREG and tumor-immune interactions and found a negative correlation between PIMREG and the immune infiltrating level of T cells, macrophages, B cells, dendritic cells (DCs) , and CD8⁺ T cells in LUAD.

Conclusions

High levels of PIMREG correlated with poor prognosis and immune infiltrates in LUAD.

FAM64A is an androgen receptor-regulated feedback tumor promoter in prostate cancer

Endocrine therapy for prostate cancer (PCa) mainly inhibits androgen receptor (AR) signaling, due to increased androgen synthesis and AR changes, PCa evolved into castration-resistant prostate cancer (CRPC). The function of Family With Sequence Similarity 64 Member A (FAM64A) and its association with prostate cancer has not been reported. In our research, we first reported that FAM64A is up-regulated and positively associated with poor prognosis of patients with prostate cancer (PCa) by TCGA database and immunohistochemistry staining. Moreover, knockdown of FAM64A significantly suppressed the proliferation, migration, invasion, and cell cycle of PCa cells in vitro. Mechanistically, FAM64A expression was increased by dihydrotestosterone (DHT) through direct binding of AR to FAM64A promoter, and notably promoted the proliferation, migration, invasion, and cell cycle of androgen-dependent cell line of PCa. In addition, abnormal expression of FAM64A affects the immune and interferon signaling pathway of PCa cells. In conclusion, FAM64A was up-regulated by AR through directly binding to its specific promoter region to promote the development of PCa, and was associated with the immune mechanism and interferon signaling pathway, which provided a better understanding and a new potential for treating PCa.

Molecular mechanisms underlying curcumin-mediated microRNA regulation in carcinogenesis; Focused on gastrointestinal cancers

Curcumin is a bioactive ingredient found in the Rhizomes of Curcuma longa. Curcumin is well known for its chemopreventive and anti-cancer properties. Recent findings have demonstrated several pharmacological and biological impacts of curcumin, related to the control and the management of gastrointestinal cancers. Mechanistically, curcumin exerts its biological impacts via antioxidant and anti-inflammatory effects through the interaction with various transcription factors and signaling molecules. Moreover, epigenetic modulators such as microRNAs (miRNAs) have been revealed as novel targets of curcumin. Curcumin was discovered to regulate the expression of numerous pathogenic miRNAs in gastric, colorectal, esophageal and liver cancers. The present systematic review was performed to identify miRNAs that are modulated by curcumin in gastrointestinal cancers.

Low REST Expression Indicates a Biomarker of Poor Prognosis in Patients with Renal Cell Carcinoma

It was initially found that neural-restrictive silencer factor/repressor 1-silencing transcription factor (REST) is a transcriptional repressor of neuronal genes in nonneuronal cells. However, it is reported to be abundantly expressed in various types of aggressive cancer cells. In this study, we evaluated the expression patterns of REST in renal cell carcinoma and found that its expression is lower in tumor tissues compared to normal tissues. The chi-square test showed that the low REST expression was closely related to patients' clinicopathologic parameters, including the pathologic stage and survival status. ROC curve showed that REST had excellent clinical diagnostic prospect. In addition, patients with low REST expression had poor over survival (OS) and relapse-free survival (RFS). Univariate and multivariate Cox regression analysis confirmed that the low REST expression was an independent predictor of poor prognosis in renal cell carcinoma. Gene set enrichment analysis identified P53 pathway, reactive oxygen species pathway, glycolysis, DNA repair, cholesterol homeostasis, and MYC targets V2 enriched with low REST expression phenotype. These results suggested that REST may be a novel biomarker for the diagnosis and prognosis of renal cell carcinoma in clinical applications.

Identification of Immune-Related Therapeutically Relevant Biomarkers in Breast Cancer and Breast Cancer Stem Cells by Transcriptome-Wide Analysis: A Clinical Prospective Study

Cancer stem cells (CSCs) represent a subset of tumor cells that are responsible for recurrence and metastasis of tumors. These cells are resistant to radiotherapy and chemotherapy. Immunotherapeutic strategies that target CSCs specifically have provided initial results; however, the mechanism of action of these strategies is unclear. The data were requested from The Cancer Genome Atlas and Genotype-Tissue Expression, followed with the survival analysis and weighted gene co-expression network analysis to detect survival and stemness related genes. Patients were divided into three groups based on their immune status by applying single sample GSEA (ssGSEA) with proven dependability by ESTIMATE analysis. The filtered key genes were analyzed using oncomine, GEPIA, HPA, qRT-PCR, and functional analysis. Patients in a group with a higher stemness and a lower immune infiltration showed a worse overall survival probability, stemness and immune infiltration characteristics of breast cancer progressed in a non-linear fashion. Thirteen key genes related to stemness and immunity were identified and the functional analysis indicated their crucial roles in cell proliferation and immune escape strategies. The qRT-PCR results showed that the expression of PIMREG and MTFR2 differed in different stages of patients. Our study revealed a promising potential for CSC-target immunotherapy in the early stage of cancer and a probable value for PIMREG and MTFR2 as biomarkers and targets for immunotherapy.

Multi-omics analysis identifies potential mechanisms of AURKB in mediating poor outcome of lung adenocarcinoma

Aurora kinases B (AURKB), which plays a critical role in chromosomal segmentation and mitosis, greatly promotes cell cycle progression and aggressive proliferation of cancers. So far, its role and underlying mechanisms in mediating poor outcome of lung adenocarcinoma (LUAD) remained largely unclear. Analyses on multiple omics data of lung adenocarcinoma cohort in The Cancer Genome Atlas (TCGA) were performed based on AURKB expression, and demonstrated its association with clinical characteristics and the potential of using AURKB as a biomarker in predicting patients' survival. This study found aberrant alterations of genomics and epigenetics, including up-regulation and down-regulation of oncogenic genes and tumor suppressors, pathways involved in the cell cycle, DNA repair, spliceosome, and proteasome, hypermethylation enrichments around transcriptional start sites, which are all related to AURKB expression. We further discovered the possible role of tumor suppressors DLC1 and HLF in AURKB-mediated adverse outcome of LUAD. To conclude, this study proved AURKB as a potential prognostic factor and therapeutic target for lung adenocarcinoma treatment and provide a future research direction.

Identifying breast cancer subtypes associated modules and biomarkers by integrated bioinformatics analysis

Breast cancer is the most common form of cancer afflicting women worldwide. Patients with breast cancer of different molecular classifications need varied treatments. Since it is known that the development of breast cancer involves multiple genes and functions, identification of functional gene modules (clusters of the functionally related genes) is indispensable as opposed to isolated genes, in order to investigate their relationship derived from the gene co-expression analysis. In total, 6315 differentially expressed genes (DEGs) were recognized and subjected to the co-expression analysis. Seven modules were screened out. The blue and turquoise modules have been selected from the module trait association analysis since the genes in these two modules are significantly correlated with the breast cancer subtypes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment show that the blue module genes engaged in cell cycle, DNA replication, p53 signaling pathway, and pathway in cancer. According to the connectivity analysis and survival analysis, 8 out of 96 hub genes were filtered and have shown the highest expression in basal-like breast cancer. Furthermore, the hub genes were validated by the external datasets and quantitative real-time PCR (qRT-PCR). In summary, hub genes of Cyclin E1 (CCNE1), Centromere Protein N (CENPN), Checkpoint kinase 1 (CHEK1), Polo-like kinase 1 (PLK1), DNA replication and sister chromatid cohesion 1 (DSCC1), Family with sequence similarity 64, member A (FAM64A), Ubiquitin Conjugating Enzyme E2 C (UBE2C) and Ubiquitin Conjugating Enzyme E2 T (UBE2T) may serve as the prognostic markers for different subtypes of breast cancer.

A new survival model based on ion channel genes for prognostic prediction in hepatocellular carcinoma

Accumulating studies revealed the vital role of ion channels in cancers, but the prognosis role of ion channels in hepatocellular carcinoma (HCC) remains limited. Here, we developed and validated an ion channel signature for prognostic prediction of HCC patients. In total, 35 differential expressed ion channel genes (DEChannelGs) were identified in HCC and a novel ion channel risk model was established for HCC prognosis prediction using the TCGA cohort, which was validated using the ICGC cohort. Moreover, this risk model was an independent prognostic factor and was associated with the immune microenvironment in HCC. Finally, the mRNA and protein levels of ANO10 and CLCN2 were prominently up-regulated and were related to the poor prognosis of HCC patients. Taken together, these results indicated a novel ion channel risk model as a prognostic biomarker for HCC patients and provided further insight into its immunoregulatory mechanism in HCC progression.

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.

Study on the Selection of the Targets of Esophageal Carcinoma and Interventions of Ginsenosides Based on Network Pharmacology and Bioinformatics

Background

Esophageal carcinoma (ESCA) is not only a threat to people's health but also the sixth most common cause of cancer-related mortality worldwide.

Methods

In this study, the key targets of ESCA are screened through GeneCards and DisGeNET databases combined with the Gene Expression Omnibus (GEO) database (GSE1420 and GSE20347). Then, data associated with ESCA samples are downloaded from The Cancer Genome Atlas (TCGA) database for integrated analysis. Moreover, the effect of epithelial cell adhesion molecule (EpCAM) expression on the survival of patients with ESCA is evaluated by Kaplan–Meier and Cox analyses. The virtual screening is carried out using a Suflex-Dock molecular docking module. The chemical components, which have been well bound to EpCAM, are screened out based on a total score >5 as a threshold. Ginsenosides and EpCAM are analyzed by LigPlot + v.2.2 software to identify the binding sites.

Results

Four ESCA targets are obtained from GeneCards, DisGeNET, and GEO databases. In this study, it is found that high EpCAM expression is associated with histologic grade, stage, patient age, N classification, T classification, and radiation therapy. The Kaplan–Meier curves for overall survival also show that the higher expression of EpCAM is associated with worse outcomes in patients with ESCA. Univariate and multivariate Cox analyses indicate that EpCAM mRNA expression might be a useful biomarker for ESCA(P < 0.05). Molecular docking technology suggests that ginsenoside Rg3 and ginsenoside Rh2 can easily establish good docking modes and have a high affinity with EpCAM. The 6′-hydroxyl and 6″-hydroxyl on the 3-glycosyl of ginsenoside Rg3 are prone to form hydrogen bonds (Lys151 and Lys221) with the active sites of EpCAM ligand binding domain. The hydroxyl groups on the 12 sites of the ginsenoside Rh2 glycoside framework are found to have hydrogen bonding with Leu240. The formation of hydrogen bonds plays an important role in binding of ginsenoside Rg3 and ginsenoside Rh2 to EpCAM, as well as the stability of EpCAM conformation.

Conclusion

EpCAM may be determined as a potential biomarker for early diagnosis and prognosis of ESCA. Ginsenoside Rg3 and ginsenoside Rh2 have potential antiesophageal cancer activities. This experiment provides a reference for the study of the chemical compositions of ginsenosides in the treatment of esophageal 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.

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.

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.

PIMREG, a Marker of Proliferation, Facilitates Aggressive Development of Cholangiocarcinoma Cells Partly Through Regulating Cell Cycle-Related Markers

BACKGROUND

Phosphatidylinositol binding clathrin assembly protein interacting mitotic regulator (PIMREG) is a protein associated with cell proliferation. Its aberrant expression was reported to be correlated with the development in multiple tumors. However, its role in cholangiocarcinoma (CAA) has not yet been evaluated in detail.

METHODS

Data were acquired from the public TCGA database for evaluating the expression pattern of PIMREG and assessing its clinical relevance as well as its correlation with overall survival. RBE and HUH28 cell lines were selected to perform loss- and gain-of-function of PIMREG assays respectively. Quantitative real-time PCR (RT-qPCR) and western blot analyses were used to measure the mRNA and protein levels of PIMREG. Cell Counting Kit-8, colony formation tests, and Transwell assays served to measure the effect of PIMREG on the proliferative, invasive and migratory capacities of CAA cells, appropriately. Gene set enrichment analysis (GSEA) was conducted to identify PIMREG associated gene set, which was further confirmed by western blot.

RESULTS

PIMREG was found to be highly expressed in CAA tissues and cell lines according to the public dataset and RT-qPCR analysis, and negatively related to the prognosis of patients with CAA. Moreover, knockdown of PIMREG suppressed and overexpression of PIMREG promoted the proliferation, invasion and migration of CAA cells. Furthermore, GSEA revealed that high PIMREG expression was positively associated with cell cycle signaling. And the next western blot analysis demonstrated that silencing PIMREG resulted in a reduction on the levels of p-CDK1, CCNE1, and CCNB1, whereas PIMREG overexpression led to an opposite result.

CONCLUSION

The results suggested that PIMREG facilitates the growth, invasion and migration of CAA cells partly by regulating the cell cycle relative biomarkers, revealing that PIMREG may be a crucial molecule in the progression of CAA.

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.

TYMS presents a novel biomarker for diagnosis and prognosis in patients with pancreatic cancer

Pancreatic cancer is one of the most malignant tumors worldwide. DNA replication plays a critical role in the occurrence and development of pancreatic cancer. TYMS encodes thymidylate synthase, which is important for DNA synthesis. The TYMS gene has been assessed in some tumors. However, the specific role of TYMS in pancreatic cancer has not been identified. This study was designed to clarify the diagnostic and prognostic significance of TYMS in pancreatic cancer.The Cancer Genome Atlas (TCGA) database was used to compare TYMS expression in pancreatic cancer, and ROC curve analysis was used to investigate its diagnostic value. The correlation between clinical characteristics and TYMS expression was analyzed, and the prognostic value of TYMS expression in the patients with pancreatic cancer was assessed by Kaplan-Meier curves and Cox analysis.TYMS was upregulated in pancreatic cancer and associated with poor overall survival (OS) and recurrence-free survival (RFS). Univariate and multivariate survival analysis demonstrated that TYMS is an independent risk factor for OS and RFS in patients with pancreatic cancer.The upregulation of TYMS in pancreatic cancer leads to unfavorable OS and RFS in patients, and represents a diagnostic and prognostic biomarker for patients with pancreatic 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.