Transcriptional E2F1/2/5/8 as potential targets and transcriptional E2F3/6/7 as new biomarkers for the prognosis of human lung carcinoma

Oncogenic FLT3 internal tandem duplication activates E2F1 to regulate purine metabolism in acute myeloid leukaemia

Oncogene FLT3 internal tandem duplication (FLT3-ITD) mutation accounts for 30 % of acute myeloid leukaemia (AML) cases and induces transformation. Previously, we found that E2F transcription factor 1 (E2F1) was involved in AML cell differentiation. Here, we reported that E2F1 expression was aberrantly upregulated in AML patients, especially in AML patients carrying FLT3-ITD. E2F1 knockdown inhibited cell proliferation and increased cell sensitivity to chemotherapy in cultured FLT3-ITD-positive AML cells. E2F1-depleted FLT3-ITD⁺ AML cells lost their malignancy as shown by the reduced leukaemia burden and prolonged survival in NOD-Prkdc^scidIl2rg^em1/Smoc mice receiving xenografts. Additionally, FLT3-ITD-driven transformation of human CD34⁺ hematopoietic stem and progenitor cells was counteracted by E2F1 knockdown. Mechanistically, FLT3-ITD enhanced the expression and nuclear accumulation of E2F1 in AML cells. Further study using chromatin immunoprecipitation-sequencing and metabolomics analyses revealed that ectopic FLT3-ITD promoted the recruitment of E2F1 on genes encoding key enzymatic regulators of purine metabolism and thus supported AML cell proliferation. Together, this study demonstrates that E2F1-activated purine metabolism is a critical downstream process of FLT3-ITD in AML and a potential target for FLT3-ITD⁺ AML patients.

Regulators CDCA8 as potential targets and biomarkers for the prognosis of human skin cutaneous melanoma

Cutaneous melanoma (CM) is considered as the most malignant skin tumor with high distant metastasis and poor prognosis. Cell division cycle-associated protein (CDCA) family has a role in regulating cell proliferation and modulating immune cell and tumor cell proliferation in the tumor microenvironment to regulate tumor oncogenesis, development and affect patient outcomes. However, the differential expression pattern and prognostic value of CDCA factors (CDCAs) have not been clarified. In this study, the role of CDCAs in CM was analyzed by using bioinformatics and found that the transcriptional expressions of CDCA1/2/3/5/6/8 were upregulating in CM samples than in normal compares. CM patients with downregulated of CDCA1/3/4/5/6/8 and high transcriptional levels of CDCA7 suggest a significantly better prognosis. Furthermore, the significant correlations among the expression of CDCAs and the infiltration of immune cells. In terms of the protein level, we found CDCA8 was upregulated in CM patients. In conclusion, CDCA8 is a powerful prognostic biomarker for CM and can be a novel target for immunotherapy.

Glucosamine-phosphate N-acetyltransferase 1 and its DNA methylation can be biomarkers for the diagnosis and prognosis of lung cancer

Objective

Lung cancer ranking high in the cancer‐related list has long perplexed patients, in which glucosamine‐phosphate N‐acetyltransferase 1 (GNPNAT1) is found to be highly expressed. Besides, DNA methylation is perceived as a biomarker to assess the prognosis of patients with various cancers. However, the correlation between GNPNAT1 and DNA methylation and the role of GNPNAT1 in lung cancer remain vague.

Methods

Principal component analysis (PCA), heatmap, volcano map, Venn diagram, gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to screen out the candidate genes. The viability, migration, and invasion of lung cancer cells were detected by CCK‐8 and Transwell assays. An xenograft tumor mouse model was established. The relative expressions of GNPNAT1, E‐cadherin, vimentin, Matrix metalloproteinase‐2 (MMP‐2), tissue inhibitor of metalloproteinase‐2 (TIMP‐2), E2F1, and cyclin D1 in cells or xenograft tumor tissues were quantified by Western blot, RT‐qPCR, or immunohistochemistry assay.

Results

GNPNAT1 was screened as the research object. GNPNAT1 methylation was downregulated, while GNPNAT1 expression was upregulated in lung cancer tissues. The methylation and mRNA levels of GNPNAT1 were correlated with the patient prognosis. GNPNAT1 increased cell viability, migration and invasion, and promoted the xenograft tumor volume and weight, whereas shGNPNAT1 acted oppositely. Moreover, expressions of Vimentin, MMP‐2, E2F1, and cyclin D1 were increased, but E‐cadherin and TIMP‐2 expressions were decreased by overexpressed GNPNAT1, whilst GNPNAT1 knockdown ran conversely.

Conclusion

GNPNAT1 and methylated GNPNAT1 coverage are biomarkers for the diagnosis and prognosis of lung cancer.

Combined analysis of expression, prognosis and immune infiltration of GINS family genes in human sarcoma

Objective: This study was undertaken to explore the expression and prognostic value of GINS family in human sarcoma, as well as the association between the expression levels of the GINS family and sarcoma immune infiltration.

Results: We discovered that the mRNA expression levels of GINS1, GINS2, GINS3, and GINS4 were all higher in the majority of tumor tissues than in normal samples, of course, including sarcoma. Through the CCLE, all the four members expression were observed in high levels in sarcoma cell lines. In Gene Expression Profiling Analysis (GEPIA) and Kaplan-Meier Plotter, our results indicated that the poor overall survival (OS), disease-free survival (DFS) and relapse free survival (RFS) were tightly associated with the increased expression of GINS genes. In TIMER database, we found that highly expressed GINS was significantly correlated with the low infiltration level of CD4+ T cell and macrophage.

Conclusions: The four GINS family members were all the prognostic biomarkers for the prognosis of human sarcoma and can reduce the level of immune cell infiltration in the sarcoma microenvironment.

Methods: In terms of the expression levels of mRNA for GINS family members, a particular contrast in various cancers, especially human sarcoma, was conducted through ONCOMINE and GEPIA and CCLE databases. Kaplan-Meier Plotter was used to identify the prognostic value of GINS family in sarcoma. The relationship between the expression level of GINS and the infiltration of immune cells was analyzed in TIMER database.

Identifying General Tumor and Specific Lung Cancer Biomarkers by Transcriptomic Analysis

The bioinformatic pipeline previously developed in our research laboratory is used to identify potential general and specific deregulated tumor genes and transcription factors related to the establishment and progression of tumoral diseases, now comparing lung cancer with other two types of cancer. Twenty microarray datasets were selected and analyzed separately to identify hub differentiated expressed genes and compared to identify all the deregulated genes and transcription factors in common between the three types of cancer and those unique to lung cancer. The winning DEGs analysis allowed to identify an important number of TFs deregulated in the majority of microarray datasets, which can become key biomarkers of general tumors and specific to lung cancer. A coexpression network was constructed for every dataset with all deregulated genes associated with lung cancer, according to DAVID’s tool enrichment analysis, and transcription factors capable of regulating them, according to oPOSSUM´s tool. Several genes and transcription factors are coexpressed in the networks, suggesting that they could be related to the establishment or progression of the tumoral pathology in any tissue and specifically in the lung. The comparison of the coexpression networks of lung cancer and other types of cancer allowed the identification of common connectivity patterns with deregulated genes and transcription factors correlated to important tumoral processes and signaling pathways that have not been studied yet to experimentally validate their role in lung cancer. The Kaplan–Meier estimator determined the association of thirteen deregulated top winning transcription factors with the survival of lung cancer patients. The coregulatory analysis identified two top winning transcription factors networks related to the regulatory control of gene expression in lung and breast cancer. Our transcriptomic analysis suggests that cancer has an important coregulatory network of transcription factors related to the acquisition of the hallmarks of cancer. Moreover, lung cancer has a group of genes and transcription factors unique to pulmonary tissue that are coexpressed during tumorigenesis and must be studied experimentally to fully understand their role in the pathogenesis within its very complex transcriptomic scenario. Therefore, the downstream bioinformatic analysis developed was able to identify a coregulatory metafirm of cancer in general and specific to lung cancer taking into account the great heterogeneity of the tumoral process at cellular and population levels.

Comprehensive Analysis of the E2F Transcription Factor Family in Human Lung Adenocarcinoma

Background

E2F transcription factors (E2Fs), code a family of pivotal transcription factors, have been identified as key regulators in tumor tumorigenesis. However, the function of E2F family in human lung adenocarcinoma (LUAD) have not been fully elucidated.

Methods

Herein, The Cancer Genome Atlas (TCGA) databases, Kaplan-Meier plotter, cBioPortal and TIMER were used to analyze differential expression, prognostic value, genetic alteration and immune cell infiltration of E2Fs in LUAD patients.

Results

The expression levels of E2Fs (E2F1-8) were all significantly upregulated in LUAD tissues compared with normal lung tissues. All eight E2Fs had low rates of gene mutation in LUAD patients from cBioPortal databases. Survival analysis revealed that E2F2 (P=0.038; HR 1.36; 95% CI 1.02–1.81), E2F7 (P<0.001; HR 1.78; 95% CI 1.33–2.39) and E2F8 (P=0.03; HR 1.37; 95% CI 1.02–1.82) were significantly associated with poor prognosis. Multivariate cox regression analysis found that only E2F7 (P<0.001; HR 2.72; 95% CI 1.75–4.25) was an independent prognostic predictor in LUAD after adjusting common clinical parameters. The receiver operating characteristic (ROC) analysis also found that E2F7 had high diagnostic value for LUAD (AUC=0.901). Further analysis found that E2F7 was significantly associated with LUAD immune cell infiltration of B cell, T cell, neutrophil, and myeloid dendritic cell. E2F7 also have positive correlations with immune checkpoint genes including SIGLEC15, CD274, HAVCR2, PDCD1LG2, CTLA4, TIGIT, LAG3 and PDCD1 in LUAD.

Conclusion

Our findings showed various association of E2F7 in LUAD diagnostic and prognostic aspects, which suggested its potential in becoming a novel biomarker.

E2F2 promotes lung adenocarcinoma progression through B-Myb- and FOXM1-facilitated core transcription regulatory circuitry

Lung adenocarcinoma (LUAD) causes severe cancer death worldwide. E2F2 is a canonical transcription factor implicated in transcription regulation, cell cycle and tumorigenesis. The role of E2F2 as well as its transcription regulatory network in LUAD remains obscure. In this study, we constructed a weighted gene co-expression network and identified several key modules and networks overrepresented in LUAD, including the E2F2-centered transcription regulatory network. Function analysis revealed that E2F2 overexpression accelerated cell growth, cell cycle progression and cell motility in LUAD cells whereas E2F2 knockdown inhibited these malignant phenotypes. Mechanistic investigations uncovered various E2F2-regulated downstream genes and oncogenic signaling pathways. Notably, three core transcription factors of E2F2, B-Myb and FOXM1 from the LUAD transcription regulatory network exhibited positive expression correlation, associated with each other, mutually transactivated each other, and regulated similar downstream gene cascades, hence constituting a consolidated core transcription regulatory circuitry. Moreover, E2F2 could promote and was essentially required for LUAD growth in orthotopic mouse models. Prognosis modeling revealed that a two-gene signature of E2F2 and PLK1 from the transcription regulatory circuitry remarkably stratified patients into low- and high-risk groups. Collectively, our results clarified the critical roles of E2F2 and the exquisite core transcription regulatory circuitry of E2F2/B-Myb/FOXM1 in LUAD progression.

E2F2 enhances the chemoresistance of pancreatic cancer to gemcitabine by regulating the cell cycle and upregulating the expression of RRM2

Both pro-oncogenic and anti-oncogenic effects of E2F2 have been revealed in different malignancies. However, the precise role of E2F2 in pancreatic cancer, in particular in relation to therapeutic intervention with gemcitabine, remains unclear. In this study, the effect of E2F2 on the proliferation and cell cycle modulation of pancreatic cancer cells, and whether E2F2 plays a role in the treatment of pancreatic cancer cells by gemcitabine, were investigated. The expression of E2F2 in pancreatic cancer was assessed by various methods including bioinformatics prediction, Western blotting, and real-time PCR. The effect of E2F2 on the proliferation and cell cycling of pancreatic cancer cells was analyzed by tissue culture and flow cytometry. In addition, the effect of E2F2 on the intervention of pancreatic cancer by gemcitabine was investigated using both in vitro and in vivo approaches. The expression of E2F2 was found to be significantly increased in pancreatic cancer tissues and cell lines. The pathogenic capacity of E2F2 lied in the fact that this transcription factor promoted the transformation of pancreatic cancer cell cycle from G1-phase to S-phase, thus enhancing the proliferation of pancreatic cancer cells. Furthermore, the expression of E2F2 was increased in pancreatic cancer cells in the presence of gemcitabine, and the augmented expression of E2F2 upregulated the gemcitabine resistance-related gene RRM2 and its downstream signaling molecule deoxycytidine kinase (DCK). The resistance of pancreatic cancer cells to gemcitabine was confirmed using both in vitro and in vivo models. In this study, E2F2 has been demonstrated for the first time to play a pro-oncogenic role in pancreatic cancer by promoting the transition of the cell cycle from G1-phase to S-phase and, therefore, enhancing the proliferation of pancreatic cancer cells. E2F2 has also been demonstrated to enhance the chemotherapy resistance of pancreatic cancer cells to gemcitabine by upregulating the expression of RRM2 and DCK that is downstream of RRM2.

LINC00265 Promotes Metastasis and Progression of Hepatocellular Carcinoma by Interacting with E2F1 at The Promoter of CDK2

Objective

This study aimed to explore biological function of long intergenic non-protein coding RNA 265 (LINC00265) in hepatocellular carcinoma (HCC) cells, and evaluate its potential function as a biomarker.

Materials and Methods

In this experimental study, GEPIA database and Kaplan-Meier Plotter database were employed to analyze LINC00265 expression in HCC tissue samples and its predicting value for prognosis. LINC00265 expression in HCC tissues and cells was detected by quantitative real-time polymerase chain reaction (qRT-PCR). After overexpressing and knocking-down of LINC00265 in HCC cells, cell counting kit-8 (CCK-8) and 5-Ethynyl-2'- deoxyuridine (EdU) assays were adopted to detect proliferation of HCC cells. Transwell assay was used to detect migration and invasion of HCC cells. Interaction of LINC00265 with E2F transcription factor 1 (E2F1) was verified by the catRAPID online analysis tool, RNA pull-down experiment and RNA binding protein immunoprecipitation (RIP) assay. Binding of E2F1 to the promoter region of cyclin-dependent kinases 2 (CDK2) was detected by dual-luciferase reporter assay and chromatin immunoprecipitation. Regulatory effects of LINC00265 and E2F1 on CDK2 expression were probed by Western blot.

Results

LINC00265 expression was increased in HCC tissues and cells. LINC00265 overexpression promoted proliferation, migration and invasion of HCC cells, and knocking-down LINC00265 worked oppositely. LINC00265 could bind to E2F1 and it could enhance combination of E2F1 and CDK2 promoter regions, thus promoting CDK2 transcription. LINC00265 overexpression promoted expression of CDK2 in HCC cells.

Conclusion

Our data suggested that LINC00265 can promote malignant behaviors of HCC cells by recruiting E2F1 to the promoter region of CDK2.

Targeting SNORA38B attenuates tumorigenesis and sensitizes immune checkpoint blockade in non-small cell lung cancer by remodeling the tumor microenvironment via regulation of GAB2/AKT/mTOR signaling pathway

BACKGROUND

Non-coding RNAs (ncRNAs), including small nucleolar RNAs (snoRNAs), are widely involved in the physiological and pathological processes of human beings. While up to date, although considerable progress has been achieved in ncRNA-related pathogenesis of non-small cell lung cancer (NSCLC), the underlying mechanisms and biological significance of snoRNAs in NSCLC still need to be further clarified.

METHODS

Quantitative real-time polymerase chain reaction or RNAscope was performed to verify the expression of Small Nucleolar RNA, H/ACA Box 38B (SNORA38B) in NSCLC cell lines or clinical samples. BALB/c nude mice xenograft model or C57BL/6J mice syngeneic tumor model were estimated to detect the effects of SNORA38B in tumor growth or tumor immune microenvironment in vivo. Cytometry by time of flight, enzyme-linked immunosorbent assay and flow cytometry assay were conducted to clarify the effects and mechanisms of SNORA38B-mediated tumor immunosuppressive microenvironment. The binding activity between SNORA38B and E2F transcription factor 1(E2F1) was detected by RNA immunoprecipitation and RNA pull-down assays. Then, bioinformatics analysis and chromatin immunoprecipitation were utilized to demonstrate the regulation of GRB2-associated-binding protein 2 (GAB2) by E2F1. Moreover, the combinatorial treatment of SNORA38B locked nucleic acid (LNA) and immune checkpoint blockade (ICB) was used to treat murine Lewis lung carcinoma-derived tumor burden C57BL/6J mice to clarify the effectiveness of targeting SNORA38B in NSCLC immunotherapy.

RESULTS

SNORA38B was found highly expressed in NSCLC tissues and cell lines, and associated with worse prognosis. Further results showed that SNORA38B functioned as an oncogene via facilitating cell proliferation, migration, invasion, and inhibiting cell apoptosis in vitro and promoting tumorigenesis of NSCLC cells in vivo. SNORA38B could also recruit the CD4+FOXP3+ regulatory T cells by triggering tumor cells to secrete interleukin 10, which in turn reduced the infiltration of CD3+CD8+ T cells in NSCLC tumor microenvironment (TME), favoring tumor progression and poorer immune efficacy. Mechanistically, SNORA38B mainly distributed in the nucleus, and promoted NSCLC progression by regulating GAB2 transcription to activate protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway through directly binding with E2F1. Moreover, we found that SNORA38B LNAs were able to ameliorate CD3+CD8+ T cell infiltration in TME, which sensitized NSCLC to the treatment of ICB.

CONCLUSIONS

In conclusion, our data demonstrated that SNORA38B functioned as an oncogene in NSCLC both in vitro and in vivo at least in part by regulating the GAB2/AKT/mTOR pathway via directly binding to E2F1. SNORA38B could also sensitize NSCLC to immunotherapy, which may be a critical therapeutic target for NSCLC.

Differential Expression of E2F Transcription Factors and Their Functional and Prognostic Roles in Human Prostate Cancer

Given the tumor heterogeneity, most of the current prognostic indicators cannot accurately evaluate the prognosis of patients with prostate cancer, and thus, the best opportunity to intervene in the progression of this disease is missed. E2F transcription factors (E2Fs) have been reported to be involved in the growth of various cancers. Accumulating studies indicate that prostate cancer (PCa) carcinogenesis is attributed to aberrant E2F expression or E2F alteration. However, the expression patterns and prognostic value of the eight E2Fs in prostate cancer have yet to be explored. In this study, The Cancer Genome Atlas (TCGA), Kaplan–Meier Plotter, Metascape, the Kyoto Encyclopedia of Genes and Genomes (KEGG), CIBERSORT, and cBioPortal and bioinformatic analysis were used to investigate E2Fs in patients with PCa. Our results showed that the expression of E2F1–3, E2F5, and E2F6 was higher in prostate cancer tissues than in benign tissues. Furthermore, elevated E2F1–3 and E2F5 expression levels were associated with a higher Gleason score (GS), advanced tumor stage, and metastasis. Survival analysis suggested that high transcription levels of E2F1–3, E2F5, E2F6, and E2F8 were associated with a higher risk of biochemical recurrence. In addition, we developed a prognostic model combining E2F1, E2F6, Gleason score, and the clinical stage that may accurately predict a biochemical recurrence-free survival. Functional enrichment analysis revealed that the E2F family members and their neighboring genes were mainly enriched in cell cycle-related pathways. Somatic mutations in different subgroups were also investigated, and immune components were predicted. Further experiments are warranted to clarify the biological associations between Pca-related E2F family genes, which may influence prognosis via the cell cycle pathway.

OSgc: A Web Portal to Assess the Performance of Prognostic Biomarkers in Gastric Cancer

Evaluating the prognostic value of genes of interest in different populations of gastric cancer (GC) is difficult and time-consuming for basic and translational researchers even though many datasets are available in public dataset depositories. In the current study, we developed a robust web-based portal called OSgc (Online consensus Survival analysis of gastric cancer) that enables easy and swift verification of known and novel biomarker candidates in GC. OSgc is composed of gene expression profiling data and clinical follow-up information of 1,824 clinical GC cases, which are collected from 7 public independent datasets derived from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). By OSgc, users input the official gene symbol and will promptly retrieve the Kaplan-Meier survival plot with hazard ratio (HR) and log rank p value on the output webpage, by which users could assess the prognostic value of interesting genes for GC patients. Five survival end points containing overall survival, progression-free survival, progression-free interval, relapse-free survival, and disease-free survival could be measured in OSgc. OSgc can greatly help cancer biologists and clinicians to explore the effect of gene expression on patient survival. OSgc is freely available without restrictions at http://bioinfo.henu.edu.cn/GC/GCList.jsp.

E2F1-induced lncRNA, EMSLR regulates lncRNA LncPRESS1

E2F1 induces hundreds of protein-coding genes influencing diverse signaling pathways but much less is known about its non-coding RNA targets. For identifying E2F1-dependent oncogenic long non-coding RNAs (lncRNAs), we carried out genome-wide transcriptome analysis and discovered an lncRNA, EMSLR, which is induced both in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC). EMSLR depletion blocks the cells in G1 phase and inhibits the clonogenic ability indicating that it is essential for the tumor-related phenotypes. We discovered that EMSLR represses the promoter activity of another lncRNA, LncPRESS1, which is located 6.9 kb upstream of EMSLR and they display an inverse expression pattern in lung cancer cell lines. Depletion of C-MYC results in downregulation of EMSLR and simultaneous upregulation of EMSLR target LncPRESS1, exemplifying how C-MYC and E2F1 signal transduction pathways control the network of lncRNA genes to modulate cell proliferation and differentiation.

E2F1/2/4 mRNA is associated with immune infiltration and are potential biomarkers for the prognosis of human gastric carcinoma

Background

E2Fs are genes that regulate DNA synthesis and the cell cycle by encoding a family of transcription factors. Increasing experimental evidence has revealed that E2Fs play key roles in tumor progression in various types of cancer.

Methods

We investigated the survival, expression and transcriptional data of E2F1/2/4 in gastric cancer (GC) patients using the immunohistochemistry assay, Kaplan-Meier Plotter, cBioPortal, String, and GEPIA databases. The plasma of GC patients was analyzed using the real-time reverse transcription polymerase chain reaction (RT-PCR) assay. The correlation between E2F1/2/4 expression and clinical features was analyzed using the quartile method. As well, the correlation between E2F1/2/4 and GC immune infiltration was also investigated using the TIMER database. Database of Immune Cell Expression (DICE) was also used to analyze correlations between SOX4 and immune responses.

Results

RT-PCR and tissue immunohistochemistry confirmed that E2F1/2/4 was highly expressed in serum and GC tissue samples of GC patients, the expression of which was not affected by patient age and gender. Also, the survival analysis revealed that low levels of E2F1/2/4 expression were significantly associated with a longer overall survival (OS) in GC patients. E2F1/2/4 was correlated with patient prognosis and immune cell infiltration, including B cells, CD8⁺ T cells, CD4⁺ T cells, macrophages, neutrophils, and DCs in GC. Our findings indicated that E2F1/2/4 could be used as a prognostic biomarker and indicator of immune infiltration in GC.

Conclusions

This study revealed that E2F1/2/4 could be a promising indicator for tumor-associated immune infiltration and prognosis in GC patients.

Identification of the Expression and Clinical Significance of E2F Family in Clear Cell Renal Cell Carcinoma

Background

Multiple studies have identified that E2F transcriptions act as important regulators for the tumorigenesis and progression of several human cancers. However, little is known about the function of E2Fs in clear cell renal cell carcinoma (ccRCC).

Methods

We firstly investigated the expression levels, genetic alteration, and biological function of E2Fs in patients with ccRCC and the connections between the immune cell infiltration and the overall survivals of ccRCC patients with the E2Fs expression levels based on UALCAN, The Cancer Genome Atlas database, Gene Expression Profiling Interactive Analysis, TIMER, STRING, GSCALite and cBioPortal databases.

Results

Results revealed that the expression levels of E2F1/2/3/4/6/7/8 were markedly upregulated in patients with ccRCC, while the expression of E2F5 displayed an opposite trend. We also experimentally validated the overexpression of E2F3/4/7 in human ccRCC tissues and ccRCC cell lines. Furthermore, the high E2F1/2/3/4/7/8 expression levels were clearly associated with worse pathological characteristics of ccRCC, including high pathological stage, poor molecular subtypes and high tumor grade. Meanwhile, high expression levels of E2F1/2/4/7/8 were evidently associated with worse overall survivals (OSs) and progression-free survivals (PFSs) of patients harboring ccRCC. Univariate and multivariate analyses illustrated that the expressions of E2F4/5/7 were independent factors associated with the OSs and PFSs of patients with ccRCC. Meanwhile, the mutations in E2Fs were also significantly related to poor OSs and PFSs of patients with ccRCC. Mechanically, the E2Fs genes synergistically promoted the progression of ccRCC by accelerating the cell cycle and inhibiting DNA damage response and apoptosis after performing the protein structure, functional enrichment, and PPI network analyses. In addition, E2Fs genes were also significantly associated with tumor immune cells infiltration and the drug sensitivity in ccRCC.

Conclusion

As a result, E2F4/7 were highly expressed in ccRCC and significantly associated with worse pathological characteristics of ccRCC, including high pathological stage, poor molecular subtypes and high tumor grade, tumor immune cell infiltration, and drug sensitivity, consequently translating into poor OSs and PFSs of patients with ccRCC. Our results indicated that E2F4/7 could be potential biomarkers and therapeutic targets of ccRCC patients.

DOK5 as a Prognostic Biomarker of Gastric Cancer Immunoinvasion: A Bioinformatics Analysis

Background

Docking protein 5 (DOK5) is a member of the docking protein group of membrane proteins and is an adapter protein involved in signal transduction. Nevertheless, the role of DOK5 expression in the prognosis of gastric cancer (GC) remains unclear.

Methods

In this study, clinical prognostic parameters and survival data related to DOK5, in patients with GC, were analyzed using bioinformatics analysis comprising Oncomine and TIMER, UALCAN database, Kaplan-Meier plotter, GEPIA, GSEA, DAVID, and cBioPortal websites.

Results

In our study, GC contained various DOK5 expressions, which forecasted poor survival outcomes. Moreover, our research showed that high DOK5 could predict high-level infiltration of several GC immune cells, as evidenced by M1, TAM, M2, B cell, and T cell failure. Hence, DOK5 might become a new gastric cancer biomarker and therapeutic target. In the following analysis, in order to explore the prognostic value of DOK5 in GC, more clinical trials are needed to validate our results.

Conclusions

Through multiple database verifications, DOK5 was found to be part of the pathogenic genes for GC. Thus, it can change the formation and progression of tumors by acting on human immunity.

Bioinformatics Analysis of Hub Genes and Potential Therapeutic Agents Associated with Gastric Cancer

Purpose

The current treatment methods available for advanced gastric cancer are not very promising. Hence, it is important to explore novel biomarkers and potential therapeutic agents to treat gastric cancer (GC). This study aimed to identify hub genes associated with GC prognosis and explore potential drugs for its treatment.

Materials and Methods

Three gene expression data of GC and normal tissues were downloaded from the Gene Expression Omnibus (GEO) and processed to identify the differentially expressed genes (DEGs). We conducted a comprehensive analysis of DEGs, including functional enrichment analysis, construction of protein-protein interaction (PPI) network, identification of hub genes, survival analysis and expression verification of hub genes. Finally, we constructed the network of miRNA-mRNA, and predicted the drugs that might be effective for GC treatment.

Results

A total of 340 DEGs, including 94 up-regulated and 246 down-regulated genes, were identified. Among the up-regulated DEGs, the enrichment terms were primarily related to tumorigenesis and tumor progression, extracellular matrix organization, and collagen catabolic process. Additionally, 10 hub genes (FN1, COL3A1, COL1A2, BGN, THBS2, COL5A2, THBS1, COL5A1, SPARC, and COL4A1) were identified, out of which 7 genes were significantly associated with poor overall survival (OS) in GC. The expression levels of these 7 hub genes were verified using real-time PCR, immunohistochemistry, and the GEPIA2 (Gene Expression Profiling Interactive Analysis) server. A regulatory network of miRNA-mRNA was also constructed, and the top 4 interactive miRNAs (hsa-miR-29b-3p, hsa-miR-140-3p, hsa-miR-29a-3p, and hsa-miR-29c-3p) that targeted the most hub genes were identified. Finally, fourteen small molecules were predicted to be effective in treating GC.

Conclusion

The identification of the hub genes, miRNA-mRNA network, and potential candidate drugs associated with GC provides new insights into the molecular mechanisms and treatment of GC.

Prognostic Value of E2F Transcription Factor Expression in Pancreatic Adenocarcinoma

Background

Pancreatic adenocarcinoma (PAAD) is one of the deadliest types of cancer. In the early stages, patients often have atypical symptoms, making diagnosis difficult. The prognosis of diagnosed patients is very poor and treating PAAD is challenging. Therefore, determining reliable risk factors related to PAAD development is critical for improving patient prognosis. E2F family transcription factors (TFs) are essential regulators of DNA synthesis and cell cycle progression in eukaryotic cells, and they have been identified as prognostic biomarkers associated with multiple cancer types. However, further research is necessary to establish the prognostic relevance of these TFs in PAAD patients.

Material/Methods

We assessed PAAD patient transcriptional and outcome data using the TIMER, ONCOMINE, STRING, GEPIA, cBioPortal, Kaplan-Meier Plotter, GSCALite, and starBase databases.

Results

PAAD tumor tissues exhibited increased expression of E2F1/3/5/7/8 relative to that in normal tissues, while the expression of E2F2/3/6/8 was associated with a more advanced tumor stage. Survival analyses indicated that PAAD patients expressing higher levels of E2F1/2/3/7/8 exhibited shorter overall survival (OS) and disease-free survival (DFS) than patients expressing lower levels of these TFs. In addition, E2F4 and E2F6 overexpression was associated with poorer DFS and OS, respectively. We also found that the expression of E2Fs was significantly correlated with immune infiltrates, including CD8+ T cells, CD4+ T cells, B cells, dendritic cells, neutrophils, and macrophages.

Conclusions

Our study may provide new insights into the optimal choice of immunotherapy and promising novel targets for therapeutic intervention in PAAD patients.

Prognostic value of SEC61G in lung adenocarcinoma: a comprehensive study based on bioinformatics and in vitro validation

BACKGROUND

Studies have shown that the Sec61 gamma subunit (SEC61G) is overexpressed in several tumors and could serve as a potential prognostic marker. However, the correlation between SEC61G and lung adenocarcinoma (LUAD) remains unclear. In the current study, we aimed to demonstrate the prognostic value and potential biological function of the SEC61G gene in LUAD.

METHODS

Public datasets were used for SEC61G expression analyses. The prognostic value of SEC61G in LUAD was investigated using the Kaplan-Meier survival and Cox analyses. The correlation between the methylation level of SEC61G and its mRNA expression was evaluated via cBioPortal. Additionally, MethSurv was used to determine the prognostic value of the SEC61G methylation levels in LUAD. Functional enrichment analysis was conducted to explore the potential mechanism of SEC61G. Also, single sample GSEA (ssGSEA) and TIMER online tool were applied to identify the correlation between SEC61G and immune filtration. Furthermore, cell functional experiments were conducted to verify the biological behavior of SEC61G in lung adenocarcinoma cells (LAC).

RESULTS

SEC61G was upregulated in pan-cancers, including LUAD. High SEC61G expression was significantly correlated with worse prognosis in LUAD patients. Multivariate analysis demonstrated that high SEC61G expression was an independent prognostic factor in the TCGA cohort. (HR = 1.760 95% CI: 1.297-2.388, p < 0.001). The methylation level of SEC61G negatively correlated with the SEC61G expression (R = - 0.290, p < 0.001), and patients with low SEC61G methylation had worse overall survival. (p = 0.0014). Proliferation-associated terms such as cell cycle and cell division were significantly enriched in GO and KEGG analysis. Vitro experiments demonstrated that knockdown of SEC61G resulted in decreased cell proliferation, invasion and facilitated apoptosis in LAC. GSEA analysis found that SEC61G expression was associated with the E2F targets. Moreover, SEC61G expression was negatively correlated with the immune cell infiltration including CD4+ T cell, CD8+ T cell, B cell, macrophage, neutrophil, and dendritic cell.

CONCLUSION

Our study indicated that overexpression of SEC61G was significantly associated with poor prognosis of LUAD patients and the malignant phenotypes of LUAD cells, suggesting that it could be a novel prognostic biomarker and potential therapeutic target of LUAD.

Procollagen-lysine, 2-oxoglutarate 5-dioxygenase 1 increases cellular proliferation and colony formation capacity in lung cancer via activation of E2F transcription factor 1

Procollagen-lysine, 2-oxoglutarate 5-dioxygenase 1 (PLOD1) is an enzyme that catalyzes the hydroxylation of lysyl residues in collagen-like peptides, and is responsible for the stability of intermolecular crosslinks. High PLOD1 mRNA levels have been determined to be prognostically significant in numerous human malignancies. The objective of the present study was to elucidate the pathological mechanism of PLOD1 in lung cancer. The expression status and prognostic value of PLOD1 in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSA) were investigated using Gene Expression Profiling Interactive Analysis (GEPIA). Cell Counting Kit 8 and colony formation assays were performed to assess the impact of PLOD1 depletion and overexpression on the proliferation and colony formation abilities of the A549 lung cancer cell line. Luciferase reporter assays were used to clarify whether E2F transcription factor 1 (E2F1) was a downstream target of PLOD1 in lung cancer. Finally, the correlations between PLOD1 expression and a typical central downstream effector molecule of E2F1 signaling were determined using cBioportal. The GEPIA datasets revealed that PLOD1 mRNA levels were upregulated in LUAD and LUSC samples. Furthermore, the overexpression of PLOD1 promoted cancer cell proliferation and colony formation in vitro, while PLOD1-knockout produced the opposite effect. Notably, PLOD1 markedly induced the transcriptional activity of E2F1. Additionally, the expression of PLOD1 was significantly correlated with that of H2A histone family member X. In conclusion, the findings of the present study indicate that PLOD1 promoted lung cancer through E2F1 activation, and proposed a rationale for targeting the PLOD1/E2F1 axis to treat lung cancer.

Systematic study on expression and prognosis of E2Fs in human colorectal cancer

BACKGROUND

E2Fs are important components of transcription factors and play key roles in occurrence or advancement of various cancers, but the expression and exact roles of each E2F in colorectal cancer (CRC) are rarely known.

METHODS

To address this issue, we investigated the roles and prognostic values of E2Fs expressions in CRC patients by searching ONCOMINE, cBioPortal, GEPIA, Matascape and UALCAN.

RESULTS

E2F1, 3-8 were upregulated at the mRNA level and E2F2 was less expressed in CRC tissues than in normal tissues. The eight E2Fs were correlated with tumor stages of CRC. Survival analysis using GEPIA revealed that high expressions of E2F3, 4 were related with short overall survival in all CRC patients. The mutation rate of E2Fs (60%) was high and genetic alteration in E2Fs was linked with longer overall survival in CRC patients. Functional analysis implied that E2Fs and their 50 nearby genes were concentrated in tumor-related pathways.

CONCLUSIONS

E2Fs may be candidate biomarkers for CRC diagnosis and E2F3, 4 are potential prognosis biomarkers of CRC. Nevertheless, our findings must be validated in the future to popularize the clinical application of E2Fs in CRC.

UGT1A Gene Family Members Serve as Potential Targets and Prognostic Biomarkers for Pancreatic Cancer

Background

Pancreatic cancer (PC) is one of the most common cancers worldwide, with high mortality. The UGT1A gene family plays important roles in pharmacology and toxicology, contributing to interindividual differences in drug disposition. However, mRNA expression and prognostic value of the UGT1A gene family in PC have not been identified.

Methods

Oncomine, GEPIA2, DAVID 6.8, Metascape, Kaplan-Meier plotter, cBioPortal, GeneMANIA, TRRUST v2, TIMER, and R software were used in our study.

Results

The transcriptional levels of UGT1A1/3/6/8/9/10 in PC tissues were significantly higher than those in normal tissues. These results were further validated using five pairs of PC tumor tissues and adjacent nontumor tissues. A significant correlation was found between the expression of UGT1A1/6/10 and the pathological stage of PC. PC patients with lower transcriptional levels of UGT1A1/4/5/6/10 were associated with a better prognosis. The differentially expressed UGT1A gene family functions were primarily related to the glucuronidation pathway, cytokine-cytokine receptor interactions, and the ILK signaling pathway. Our data suggest that HNF1A, AHR, and CDX2 are key transcription factors for the UGT1A gene family. Furthermore, the expression levels of UGT1A1/3/8/9/10 were positively correlated with the activities of tumor-infiltrating immune cells, especially B cells. The expression levels of UGT1A6/9 were negatively correlated with macrophage infiltration levels.

Conclusions

These results suggest that the UGT1A gene family could serve as a potential prognostic biomarker and target for PC. However, future studies are required to validate our findings and promote the clinical utility of the UGT1A gene family in PC.

Screening and Identification of Key Biomarkers of Gastric Cancer: Three Genes Jointly Predict Gastric Cancer

Background

Gastric cancer (GC) is one of the most common cancers all over the world, causing high mortality. Gastric cancer screening is one of the effective strategies used to reduce mortality. We expect that good biomarkers can be discovered to diagnose and treat gastric cancer as early as possible.

Methods

We download four gene expression profiling datasets of gastric cancer (GSE118916, GSE54129, GSE103236, GSE112369), which were obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between gastric cancer and adjacent normal tissues were detected to explore biomarkers that may play an important role in gastric cancer. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of overlap genes were conducted by the Metascape online database; the protein-protein interaction (PPI) network was constructed by the STRING online database, and we screened the hub genes of the PPI network using the Cytoscape software. The survival curve analysis was conducted by km-plotter and the stage plots of hub genes were created by the GEPIA online database. PCR, WB, and immunohistochemistry were used to verify the expression of hub genes. A neural network model was established to quantify the predictors of gastric cancer.

Results

The relative expression level of cadherin-3 (CDH3), lymphoid enhancer-binding factor 1 (LEF1), and matrix metallopeptidase 7 (MMP7) were significantly higher in gastric samples, compared with the normal groups (p<0.05). Receiver operator characteristic (ROC) curves were constructed to determine the effect of the three genes’ expression on gastric cancer, and the AUC was used to determine the degree of confidence: CDH3 (AUC = 0.800, P<0.05, 95% CI =0.857-0.895), LEF1 (AUC=0.620, P<0.05, 95%CI=0.632-0.714), and MMP7 (AUC=0.914, P<0.05, 95%CI=0.714-0.947). The high-risk warning indicator of gastric cancer contained 8<CDH3<15 and 10<expression of LEF1<16.

Conclusions

CDH3, LEF1, and MMP7 can be used as candidate biomarkers to construct a neural network model from hub genes, which may be helpful for the early diagnosis of gastric cancer.

Emerging Role of E2F Family in Cancer Stem Cells

The E2F family of transcription factors (E2Fs) consist of eight genes in mammals. These genes encode ten proteins that are usually classified as transcriptional activators or transcriptional repressors. E2Fs are important for many cellular processes, from their canonical role in cell cycle regulation to other roles in angiogenesis, the DNA damage response and apoptosis. A growing body of evidence demonstrates that cancer stem cells (CSCs) are key players in tumor development, metastasis, drug resistance and recurrence. This review focuses on the role of E2Fs in CSCs and notes that many signals can regulate the activities of E2Fs, which in turn can transcriptionally regulate many different targets to contribute to various biological characteristics of CSCs, such as proliferation, self-renewal, metastasis, and drug resistance. Therefore, E2Fs may be promising biomarkers and therapeutic targets associated with CSCs pathologies. Finally, exploring therapeutic strategies for E2Fs may result in disruption of CSCs, which may prevent tumor growth, metastasis, and drug resistance.

Circ-E2F3 promotes cervical cancer progression by inhibiting microRNA-296-5p and increasing STAT3 nuclear translocation

Circular RNA E2F transcription factor 3 (circ-E2F3) has been demonstrated to be differentially expressed in some diseases and cancers. However, the role of circ-E2F3 in cervical cancer (CC) progression remains unclear. Therefore, we aimed to elucidate the mechanism of circ-E2F3 regulation of CC progression. Circ-E2F3 expression was determined in CC samples, and its correlation with the clinicopathological characteristics of CC patients and cell biological processes was examined. The interaction among circ-E2F3, microRNA-296-5p (miR-296-5p), and signal transducer and activator of transcription 3 (STAT3) was analyzed by dual luciferase reporter gene and fluorescence in situ hybridization assays. Circ-E2F3-depleted CaSki cells were implanted into nude mice to verify the function of circ-E2F3 in vivo. Circ-E2F3 was upregulated in both CC tissues and cell lines, and this correlated with the clinicopathological features and poor prognosis of CC patients. Moreover, circ-E2F3 promoted the proliferation, invasion, and migration of CC cells and tumor growth in vivo. It was also observed that circ-E2F3 promoted the nuclear translocation of STAT3 through inhibition of miR-296-5p, thus affecting the expression of cyclin D1. Taken together, the key findings of our study demonstrate that circ-E2F3 induces inhibition of miR-296-5p, which triggers activation and nuclear translocation of STAT3 that then upregulates cyclin D1 expression.

High mRNA Expression of CENPL and Its Significance in Prognosis of Hepatocellular Carcinoma Patients

Centromere proteins (CENPs) are the main constituent proteins of kinetochore, which are essential for cell division. In recent years, several studies have revealed that several CENPs were aberrantly expressed in hepatocellular carcinoma (HCC). However, numerous centromere proteins have not been studied in HCC. In this study, we used databases of Oncomine, Gene Expression Profiling Interactive Analysis (GEPIA), the Kaplan-Meier Plotter, cBioPortal, the Human Protein Atlas (HPA), and TIMER (Tumor Immune Estimation Resource) and immunohistochemical staining of clinical specimens to investigate the expression of 15 major centromere proteins in HCC to evaluate their potential prognostic value. We found that the mRNA levels of 4 out of 15 centromere proteins (CENPL, CENPQ, CENPR, and CENPU) were significantly higher in HCC than in normal tissues, and their mRNA levels were associated with the tumor stages (p values < 0.01). Patients with higher mRNA levels of CENPL had poorer overall survival, progression-free survival, relapse-free survival, and disease-specific survival (p values < 0.05). Furthermore, the higher levels of CENPL mRNA were associated with worse overall survival in males without hepatitis virus infection (p values < 0.05). The protein expression level of CENPL in human HCC tissue was higher than that in normal liver tissue. In addition, the expression of CENPL was positively correlated with the levels of the tumor-infiltrating lymphocytes. The results suggest that the high mRNA expression of CENPL may be a potential predictor of prognosis in HCC patients.

Overexpression of BCCIP predicts an unfavorable prognosis and promotes the proliferation and migration of lung adenocarcinoma

Background

Lung cancer accounts for the highest rate of cancer‐related diagnosis and mortality. Lung adenocarcinoma (LUAD) is the most common histopathological type. BCCIP was originally identified as a BRCA2 and CDKN1A interacting protein. In different cancers, BCCIP plays different roles. The role of BCCIP in LUAD is still unknown.

Methods

The expression and prognostic value of BCCIP was analyzed using public databases, including LCE, GEPIA, TCGA, and clinical specimens. Bioinformatic analysis and vitro experiments were conducted to explore the biological functions of BCCIP in LUAD. By using the GEPIA and TIMER databases, we investigated the correlations between LUAD expression and immune infiltration in LUAD.

Results

Compared with normal tissue, LUAD tissue had a higher expression level of BCCIP and high expression level of BCCIP was detrimental to LUAD patient survival. The suppression of BCCIP inhibited LUAD cell proliferation, migration and resulted in G1/S phase arrest in vitro. Bioinformatic analysis demonstrated that BCCIP could be associated with cell cycle, DNA repair and E2F transcription factor family. There were significant correlations between BCCIP expression and immune infiltrates, including B cell, CD4+ T cell, macrophage, neutrophil and dendritic cells. Furthermore, BCCIP expression showed strong correlations with diverse immune marker sets in LUAD, such as B cell, macrophage and DC.

Conclusions

Overexpression of BCCIP predicts an unfavorable prognosis and promotes the proliferation and migration of lung adenocarcinoma cells. BCCIP is correlated with immune infiltration in LUAD. Suppression of BCCIP may be a potential approach in the prevention and treatment of LUAD.

NMU Is a Poor Prognostic Biomarker in Patients with Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is the most prevalent histologic type of lung cancer, associated with a high incidence rate and substantial mortality rate worldwide. Accumulating evidence shows that the aberrant expression of neuromedin U (NMU) contributes to the initiation and progression of cancer. Herein, we explored whether NMU could be adopted as a new diagnostic and therapeutic marker in LUAD. The UALCAN and GEPIA web resources were employed to assess data on the NMU expression in LUAD. The STRING web resource was used to develop the PPI (protein-protein interaction) network of NMU, whereas Cytoscape was applied for module analysis. The Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses of NMU and the interacting proteins were examined using the WebGestalt tool. Survival analysis was performed with the Kaplan-Meier plotter tool. Results revealed that the NMU expression in LUAD was significantly higher than in the nonmalignant tissues. Moreover, higher NMU levels were dramatically related to shorter overall survival, first progression survival, and postprogression survival. The specific gene mutations G45V, R143T, and F152L of NMU occurred in LUAD samples and were associated with a worse prognosis in patients. KEGG and western blot analyses demonstrated an association of NMU with the cell cycle and the cAMP signaling cascade. Bioinformatic analysis and the in vitro experiments implicated NMU as a promising prognostic signature and treatment target for LUAD.

The E2F transcription factor 2: What do we know?

E2F transcription factor 2 (E2F2) is a member of the E2F family of transcription factors. The classical view is that some E2Fs act as "activators" and others "inhibitors" of cell cycle gene expression. However, the so-called "activator" E2F2 is particularly enigmatic, with seemingly contradictory roles in the cell cycle, proliferation, apoptosis, inflammation, and cell migration and invasion. How can we rationalize the apparently opposing functions of E2F2 in different situations? This is difficult because different methods of studying E2F2 have yielded conflicting results, so extrapolating mechanisms from an observed endpoint is challenging. This review will attempt to summarize and clarify these issues. This review focuses on genetic studies that have helped elucidate the biological functions of E2F2 and that have enhanced our understanding of how E2F2 is integrated into pathways controlling the cell cycle, proliferation, apoptosis, inflammation, and cell migration and invasion. This review will also discuss the function of E2F2 in cancer and other diseases. This review provides a strong basis for further research on the biological function and clinical potential of E2F2.

Cancer Essential Genes Stratified Lung Adenocarcinoma Patients with Distinct Survival Outcomes and Identified a Subgroup from the Terminal Respiratory Unit Type with Different Proliferative Signatures in Multiple Cohorts

Background: Heterogeneous features of lung adenocarcinoma (LUAD) are used to stratify patients into terminal respiratory unit (TRU), proximal-proliferative (PP), and proximal-inflammatory (PI) subtypes. A more-accurate subtype classification would be helpful for future personalized medicine. However, these stratifications are based on genes with variant expression levels without considering their tumor-promoting roles. We attempted to identify cancer essential genes for LUAD stratification and their clinical and biological differences. Methods: Essential genes in LUAD were identified using genome-scale CRIPSR screening of RNA sequencing data from Project Achilles and The Cancer Genome Atlas (TCGA). Patients were stratified using consensus clustering. Survival outcomes, genomic alterations, signaling activities, and immune profiles within clusters were investigated using other independent cohorts. Findings: Thirty-six genes were identified as essential to LUAD, and there were used for stratification. Essential gene-classified clusters exhibited distinct survival rates and proliferation signatures across six cohorts. The cluster with the worst prognosis exhibited TP53 mutations, high E2F target activities, and high tumor mutation burdens, and harbored tumors vulnerable to topoisomerase I and poly(ADP ribose) polymerase inhibitors. TRU-type patients could be divided into clinically and molecularly different subgroups based on these essential genes. Conclusions: Our study showed that essential genes to LUAD not only defined patients with different survival rates, but also refined preexisting subtypes.

Long non-coding RNA ZEB1-AS1 promotes proliferation and metastasis of hepatocellular carcinoma cells by targeting miR-299-3p/E2F1 axis

There is emerging evidence that dysregulation of long non-coding RNAs (lncRNAs) is associated with hepatocellular carcinoma (HCC). Zinc finger E-box binding homeobox 1 antisense 1 (ZEB1-AS1) functions as an oncogenic regulator in various malignancies. Nonetheless, the potential role of ZEB1-AS1 in HCC remains poorly elucidated. Herein, qRT-PCR was employed for examining ZEB1-AS1, miR-299-3p and E2F1 mRNA expressions in HCC cells and tissues. MTT assay was performed to evaluate cell proliferation. Transwell assay was utilized for evaluating cancer cell migration and invasion. Western blot was employed for measuring E2F1 protein expression. What's more, dual-luciferase reporter assay was utilized for verifying the targeting relationships between ZEB1-AS1 and miR-299-3p, as well as E2F1 and miR-299-3p. It was demonstrated that, in HCC tissues and cells, ZEB1-AS1 expression was markedly increased, and meanwhile, its high expression level is related to the unfavorable clinicopathologic indicators. ZEB1-AS1 overexpression facilitated HCC cell proliferation, migration and invasion, while its knockdown led to the opposite effects. In terms of mechanism, we discovered that ZEB1-AS1 could decoy miR-299-3p and up-regulate E2F1 expression. This work reveals the functions and mechanism of ZEB1-AS1 in HCC tumorigenesis and progression, which provides novel biomarkers and therapeutic targets for HCC.

Two predicted models based on ceRNAs and immune cells in lung adenocarcinoma

Background

It is well accepted that both competitive endogenous RNAs (ceRNAs) and immune microenvironment exert crucial roles in the tumor prognosis. The present study aimed to find prognostic ceRNAs and immune cells in lung adenocarcinoma (LUAD).

Materials and Methods

More specifically, we explored the associations of crucial ceRNAs with the immune microenvironment. The Cancer Genome Atlas (TCGA) database was employed to obtain expression profiles of ceRNAs and clinical data. CIBERSORT was utilized to quantify the proportion of 22 immune cells in LUAD.

Results

We constructed two cox regression models based on crucial ceRNAs and immune cells to predict prognosis in LUAD. Subsequently, seven ceRNAs and seven immune cells were involved in prognostic models. We validated both predicted models via an independent cohort GSE72094. Interestingly, both predicted models proved that the longer patients were smoking, the higher risk scores would be obtained. We further investigated the relationships between seven genes and immune/stromal scores via the ESTIMATE algorithm. The results indicated that CDC14A and H1F0 expression were significantly related to stromal scores/immune scores in LUAD. Moreover, based on the result of the ceRNA model, single-sample gene set enrichment analysis (ssGSEA) suggested that differences in immune status were evident between high- and low-risk groups.

Potential role of glucosamine-phosphate N-acetyltransferase 1 in the development of lung adenocarcinoma

Glucosamine-phosphate N-acetyltransferase 1 (GNPNAT1) is a key enzyme associated with glucose metabolism and uridine diphosphate-N-acetylglucosamine biosynthesis. Abnormal GNPNAT1 expression might be associated with carcinogenesis. We analyzed multiple lung adenocarcinoma (LUAD) gene expression databases and verified GNPNAT1 higher expression in LUAD tumor tissues than in normal tissues. Moreover, we analyzed the survival relationship between LUAD patients’ clinical status and GNPNAT1 expression, and found higher GNPNAT1 expression in LUAD patients with unfavorable prognosis. We built GNPNAT1 gene co-expression networks and further annotated the co-expressed genes’ Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and various associated regulatory factors. These co-expression genes’ functional networks mainly participate in chromosome segregation, RNA metabolic process, and RNA transport. We analyzed GNPNAT1 genetic alterations and co-occurrence networks, and the functional networks of these genes showed that GNPNAT1 participates in multiple steps of cell cycle transition and in the development of some cancers. We assessed the correlation between GNPNAT1 expression and cancer immune infiltrates and showed that GNPNAT1 expression is correlated with several immune cells, chemokines, and immunomodulators in LUAD. We found that GNPNAT1 correlates with LUAD development and prognosis, laying a foundation for further research, especially in immunotherapy.

Uncovering the Pharmacological Mechanism of 2-Dodecyl-6-Methoxycyclohexa-2,5 -Diene-1,4-Dione Against Lung Cancer Based on Network Pharmacology and Experimental Evaluation

Background: 2-Dodecyl-6-Methoxycyclohexa-2, 5-Diene-1,4-Dione (DMDD) was purified from the roots of Averrhoa carambola L. Previous research demonstrated that DMDD is a small molecular compound with significant therapeutic potential for tumors. However, the potential targets and pharmacological mechanism of DMDD to treat lung cancer has not been reported.

Methods: We employed network pharmacology and experimental evaluation to reveal the pharmacological mechanism of DMDD against lung cancer. Potential therapeutic targets of DMDD were screened by PharmMapper. Differentially expressed genes (DEGs) in The Cancer Genome Atlas (TCGA) lung cancer data sets were extracted and analyzed by GEPIA2. The mechanism of DMDD against lung cancer was determined by PPI, gene ontology (GO) and KEGG pathway enrichment analysis. Survival analysis and molecular docking were employed to obtain the key targets of DMDD. Human lung cancer cell lines H1975 and PC9 were used to detect effects of DMDD treatment in vitro. The expression of key targets after DMDD treated was validated by Western Blot.

Results: A total of 60 Homo sapiens potential therapeutic targets of DMDD and 3,545 DEGs in TCGA lung cancer datasets were identified. Gene ontology and pathway analysis revealed characteristic of the potential targets of DMDD and DEGs in lung cancer respectively. Cell cycle and pathways in cancer were overlapping with DMDD potential targets and lung cancer DEGs. Eight overlapping genes were found between DMDD potential therapeutic targets and lung cancer related DEGs. Survival analysis showed that high expression of DMDD potential targets CCNE1 and E2F1 was significantly related to poor patient survival in lung cancer. Molecular docking found that DMDD exhibited significant binding affinities within the active site of CCNE1 and E2F1. Further tests showed that DMDD inhibited the proliferation, migration and clone formation in lung cancer cell lines (H1975 and PC9) in a dose and time dependent manner. Mechanistically, DMDD treatment decreased the expression of CDK2, CCNE1, E2F1 proteins and induced cell cycle arrest at the G1/S phase in H1975 and PC9 cells.

Conclusion: These results delineated that DMDD holds therapeutic potential that blocks tumorigenesis by cell cycle regulation in lung cancer, and may provide potential therapies for lung cancer.

CDCA3 Is a Novel Prognostic Biomarker Associated with Immune Infiltration in Hepatocellular Carcinoma

Cell division cycle-associated protein-3 (CDCA3) contributes to the regulation of the cell cycle. CDCA3 plays an important role in the carcinogenesis of various cancers; however, the association between CDCA3 expression, prognosis of patients, and immune infiltration in the tumor microenvironment is still unknown. Here, we demonstrated that CDCA3 was differentially expressed between the tumor tissues and corresponding normal tissues using in silico analysis in the ONCOMINE and Tumor Immune Estimation Resource (TIMER) databases. We analyzed the relationship between the expression of CDCA3 and prognosis of patients with hepatocellular carcinoma (HCC) using the Kaplan-Meier plotter database and Gene Expression Profiling Interactive Analysis (GEPIA). Furthermore, we determined the prognostic value of CDCA3 expression using univariate and multivariate analyses. We observed that CDCA3 expression closely correlated with immune infiltration and gene markers of infiltrating immune cells in the TIMER database. CDCA3 was highly expressed in the tumor tissues than in the adjacent normal tissues in various cancers, including HCC. Increased expression of CDCA3 was accompanied by poorer overall survival (OS), relapse-free survival (RFS), progression-free survival (PFS), and disease-specific survival (DSS). The correlation between CDCA3 expression and OS and disease-free survival (DFS) was also studied using GEPIA. CDCA3 expression was associated with the levels of immune cell infiltration and was positively correlated with tumor purity. Moreover, CDCA3 expression was associated with gene markers such as PD-1, CTLA4, LAG3, and TIM-3 from exhausted T cells, CD3D, CD3E, and CD2 from T cells, and TGFB1 and CCR8 located on the surface of Tregs. Thus, we demonstrated that CDCA3 may be a potential target and biomarker for the management and diagnosis of HCC.

Bioinformatics Analysis of Potential Therapeutic Targets and Prognostic Biomarkers amid CXC Chemokines in Ovarian Carcinoma Microenvironment

Background

Ovarian cancer (OC) is one of the leading lethal gynecologic cancers of women around the world. More than 70% of patients are diagnosed with stage III or IV with poor outcome. This is partly because of lacking early effective screening techniques and potential biomarkers of OC. CXC chemokines in tumor microenvironment (TME) and their interaction with relative receptors can excite the downstream signaling pathways to influence tumor progression. However, the role of CXC chemokines in OC has not been identified.

Methods

ONCOMINE, GEPIA, Kaplan–Meier plotter, cBioPortal, TIMER, Metascape, and LinkedOmics were applied in our study.

Results

The transcriptional levels of CXCL1/8/9/10/11/12/13/14/16/17 were significantly elevated while CXCL3 was obviously reduced in OC vs normal ovarian tissue. CXCL8/9/11/13 were correlated with clinic pathological stage. Patients with low expression of CXCL8/9/11/13 were associated with better prognosis. We also found that CXCL3 and CXC12 could be used as potential prognostic markers of OC through Kaplan–Meier plotter. Patients with high expression of CXCL3/12 had a significantly better prognosis. Their functions focus on locomotion, signaling, response to stimulus, undergoing the process of multiorganism, immune system, biological regulation, etc. The differentiated CXC chemokines mainly participate in cytokine-cytokine receptor interaction, chemokine signaling pathway, IL-17 signaling pathway, and toll-like receptor signaling pathway. Our results showed that CXC chemokines were highly correlated with infiltration of immune cells. The kinase targets of differentially expressed CXC chemokines are mainly in ATM, LYN, LCK, PLK1, FYN, CDK2, and ATR.

Conclusions

Our results may provide a new insight for selecting precision biomarkers of targeted therapy of OC.

Transcriptional E2F1/2/3/6 as potential prognostic biomarkers in cutaneous melanoma

Although the abnormal expression of members of the E2F family has been reported to participate in carcinogenesis in many human types of cancer, the bioinformatics role of the E2F family in melanoma is unknown. This research was designed to detect the expression, methylation, prognostic value and potential effects of the E2F family in melanoma. We investigated E2F family mRNA expression from the Oncomine and GEPIA databases and their methylation status in the MethHC database. Meanwhile, we detected the relative E2F family expression levels by qPCR and immunohistochemistry. Kaplan-Meier Plotter was used to draw survival analysis charts, and gene functional enrichment analyses were applied through cBioPortal database analysis. E2F1/2/3/4/5/6 mRNA and proteins were clearly upregulated in cutaneous melanoma patients, and high expression levels of E2F1/2/3/6 were statistically related to high methylation levels. Increased mRNA expression of E2F1/2/3/6 was related to lower overall survival rates (OS) and disease-free survival (DFS) in cutaneous melanoma cases. Meanwhile, E2F1/2/3/6 carried out these effects through regulating multiple signaling pathways, including the MAPK, PI3K-Akt and p53 signaling pathways. Taking together, our findings suggest that E2F1/2/3/6 could act as potential targets for precision therapy in cutaneous melanoma patients.

Prognostic relevance of SMC family gene expression in human sarcoma

Objective: To explore the prognostic value of the expression of genes encoding structural maintenance of chromosomes (SMCs) in human sarcoma.

Results: We found that the levels of SMC1A, SMC2, SMC3, SMC4, SMC5 and SMC6 mRNA were all higher in most tumors compared to normal tissues, and especially in sarcoma. According to the Cancer Cell Line Encyclopedia (CCLE), SMC1A, SMC2, SMC3, SMC4, SMC5 and SMC6 are also highly expressed in sarcoma cell lines. Results of Gene Expression Profiling Interactive Analysis (GEPIA) indicated that high expression of SMC1A was significantly related to poor overall survival (OS) (p<0.05) and disease-free survival (DFS) in sarcoma (p<0.05). Additionally, strong expression of SMC2 was significantly related to poor OS in sarcoma (p<0.05). In contrast, SMC3, SMC4, SMC5, and SMC6 expression had no significant impact on OS or DFS in sarcoma.

Conclusions: Expression of SMC family members is significantly different in sarcoma relative to normal tissues, and SMC1A and SMC2 may be useful as prognostic biomarkers.

Methods: We performed a detailed comparison of cancer and normal tissues regarding the expression levels of mRNA for SMC family members in various cancers including sarcoma through ONCOMINE and GEPIA (Gene Expression Profile Interactive Analysis) databases.

Predictive value of protease-activated receptor-2 (PAR2 ) in cervical cancer metastasis

Metastasis is the primary cause of an unfavourable prognosis in patients with malignant cancer. Over the last decade, the role of proteinases in the tumour microenvironment has attracted increasing attention. As a sensor of proteinases, proteinase-activated receptor 2 (PAR₂ ) plays crucial roles in the metastatic progression of cervical cancer. In the present study, the expression of PAR₂ in multiple types of cancer was analysed by Gene Expression Profiling Interactive Analysis (GEPIA). Kaplan-Meier plotter was used to calculate the correlation between survival and the levels of PAR₂ , Grb-associated binding protein 2(Gab2) and miR-125b. Immunohistochemistry (IHC) was performed to examine PAR₂ expression in a tissue microarray (TMA) of CESCs. Empower Stats was used to assess the predictive value of PAR₂ in the metastatic potential of CESC. We found that PAR₂ up-regulation was observed in multiple types of cancer. Moreover, PAR₂ expression was positively correlated with the clinicopathologic characteristics of CESC. miR-125b and its target Gab2, which are strongly associated with PAR₂ -induced cell migration, are well-characterized as predictors of the prognostic value of CESC. Most importantly, the Cancer Genome Atlas (TCGA) data set analysis showed that the area under the curve (AUC) of the PAR₂ model was significantly greater than that of the traditional model (0.833 vs 0.790, P < .05), demonstrating the predictive value of PAR₂ in CESC metastasis. Our results suggest that PAR₂ may serve as a prognostic factor for metastasis in CESC patients.

Identification of novel prognostic biomarkers in renal cell carcinoma

Objective: To identify novel prognostic biomarkers in renal cell carcinoma (RCC).

Results: 12 coding genes and one miRNA were finally identified as prognostic biomarkers. All of them were related to a poor prognosis. Lower expression levels of the coding genes were observed in higher clinical stages. Prognostic signatures including 7 biomarkers were identified. Patients in the high-risk group had worse survival than those in the low-risk group. The areas under the curves in different years indicated that it was a valuable signature in prognosis. It was found that elevated WDR72 inhibited the survival and invasion of 786-O and 769P cells in vitro.

Conclusions: Thirteen prognostic biomarkers of RCC were identified. Among them, 7 biomarkers comprised a signature to evaluate the RCC prognosis. WDR72 was a cancer suppressor and a potential therapeutic target in RCC.

Methods: Differentially expressed genes/miRNAs (DEGs/DEMs) and prognosis-related genes/miRNAs were acquired from public database. Prognostic biomarkers were identified by overlapping the significant DEGs/DEMs and prognosis-related genes/miRNAs. The associations between these biomarkers and the clinical stages were analyzed. All of these prognostic biomarkers were further investigated with multi-variable Cox regression. Finally, the inhibitory effect of WDR72 on the growth and invasion of RCC cells was studied.

Bioinformatics Identification of the Expression and Clinical Significance of E2F Family in Endometrial Cancer

Background

Besides being one of the most prevalent cancers among women, incidence and mortality rates of endometrial cancer (EC) are still increasing. The E2F family of transcriptional factors is involved in cell differentiation, apoptosis, and inhibition of DNA damage response, thus affecting growth and invasion of tumor cells.

Methods

We used multiple bioinformatics tools to explore the role of E2F family in endometrial cancer.

Results

The expression of E2F1/2/3/7/8 was significantly upregulated in endometrial cancer tissues, converse to E2F4, which was downregulated. Methylation downregulates all E2Fs except for E2F2. Accordingly, E2F1/2/3/5/7/8 are potential diagnostic biomarkers for EC. In particular, EC patients displaying upregulated E2F1, and E2F3 expression had a worse overall survival and relapse-free survival. E2F8, E2F7, and E2F1 were the top three, most-frequently altered genes in endometrial cancer. E2F family activates apoptosis pathways, regulates cell cycle, and impairs DNA damage response pathways. Drug-sensitivity analysis demonstrated that the level of E2F2/3/8 negatively correlated with drug resistance. Meanwhile, immune infiltrations analysis revealed that E2F family is associated with recruitment of several immune cells. Enrichment analysis on its part revealed that the E2F family is mainly associated with cell cycle, sequence-specific DNA binding, nuclear transcription factor complex, PI3K-Akt signaling, and p53 signaling pathway. We also identified multiple E2Fs-associated miRNA and kinase targets in endometrial cancer.

Conclusion

Our study revealed the unique expression signature and clinical significance of E2F family in EC, demonstrating the potential clinical utility of these transcription factors (TF) in endometrial cancer.

Expression profiles and prognostic significance of AFTPH in different tumors

Aftiphilin (AFTPH) plays an important role in regulating intracellular trafficking, exocytosis, and the pro‐inflammatory response. However, the potential prognostic role of AFTPH in cancers remains unclear. Here, we examined the expression profiles and prognostic significance of AFTPH in breast invasive carcinoma (BRCA), diffuse large B‐cell lymphoma (DLBC), lung squamous cell carcinoma (LUSC), and pancreatic adenocarcinoma (PADD) using the GEPIA and UALCAN databases. AFTPH expression was observed to be higher in cancer tissues than in normal tissues, but expression did not differ significantly between tumor stages for the four cancer types. AFTPH expression in cancer cell lines was investigated using the CCLE database; AFTPH was found to be highly expressed in four cancer cell lines. The relationship between AFTPH expression and patient prognosis was analyzed using GEPIA, LinkedOmics, and Kaplan–Meier plotter databases. Low expression of AFTPH was associated with improved prognosis for BRCA, DLBC, LUSC, and PAAD. Genetic alterations of AFTPH in cancers were explored using the cBioPortal website, revealing that gene copy number gains and amplification are common in BRCA, DLBC, LUSC, and PAAD. Related genes and markers associated with AFTPH were discovered using the LinkedOmics database. Furthermore, transfection of cells with AFTPH siRNA demonstrated that AFTPH exerts positive effects on cell proliferation in BRCA, LUSC, and PAAD cells. In conclusion, AFTPH may be a potential therapeutic target and prognostic biomarker for BRCA, DLBC, LUSC, and/or PAAD.

Expression Patterns and Prognostic Values of ORMDL1 in Different Cancers

The mammalian orosomucoid-like gene family (ORMDL), containing ORMDL1, ORMDL2, and ORMDL3, is the important regulator of sphingolipid metabolism, which is relevant to cell growth, proliferation, migration, and invasion. Since the role of ORMDL1 in cancers remained unclear, the main purpose of our study was to explore the expression patterns and prognostic values of ORMDL1 in different tumors, especially in cholangiocarcinoma (CHOL), lymphoid neoplasm diffuse large B cell lymphoma (DLBCL), acute myeloid leukemia (LAML), and thymoma (THYM). Bioinformatics tools including GEPIA, CCLE, LinkedOmics, cBioPortal, and TIMER databases were used. As a result, the expression levels of ORMDL1 in tumor tissues and normal tissues varied in different cancers, especially significantly upregulated in CHOL, DLBCL, LAML, and THYM. Moreover, ORMDL1 mRNA was also highly expressed in cell lines of DLBCL and LAML. Further studies showed that ORMDL1 overexpression was associated with poor prognosis in DLBCL, but not significant in CHOL, LAML, and THYM. Consistently, there were genetic alterations of ORMDL1 in DLBCL, and patients with genetic alterations indicated worse survival. Coexpressed genes and related biological events with ORMDL1 in DLBCL were found via LinkedOmics, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. The relationship between ORMDL1 and cancer immune cells was investigated, and ORMDL1 expression was positively correlated with infiltrating levels of B cells. In conclusion, ORMDL1 is suggested to be a tumorigenic factor and considered as the potential therapeutic target and prognostic biomarker in DLBCL.

Characterization of the expression and prognostic value of 14-3-3 isoforms in breast cancer

The tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation proteins (14-3-3) participate in the tumorigenesis and progression of numerous malignances, but their precise prognostic values in breast cancer (BrCa) remain unknown. Here, we investigated the expression profiles and prognostic roles of 14-3-3 isoforms by employing multiple online databases. The transcriptional levels of most 14-3-3 isoforms in BrCa tissues were significantly higher than those in normal tissues. High mRNA expression of 14-3-3 beta/sigma/theta/zeta was significantly associated with poor overall survival (OS) in BrCa patients, while high mRNA expression of 14-3-3 epsilon was notably related to favorable OS. High mRNA expression of 14-3-3 beta/gamma/sigma/theta/zeta was significantly associated with poor relapse-free survival (RFS) in BrCa patients. A high mutation rate of 14-3-3 was determined to be associated with poor clinical outcomes. In addition, 14-3-3 expression was correlated with the infiltration of specific immune cells types. Analysis of the breast-specific protein-protein interaction (PPI) network suggested that 14-3-3 proteins were involved in several potential oncogenic mechanisms in BrCa. Finally, we performed experimentally validated their oncogenic roles in BrCa. Overall, our findings systematically elucidate the expression and distinct prognostic value of 14-3-3 isoforms in BrCa, which may provide potential therapeutic targets and prognostic biomarkers for BrCa.

E2F1/2/7/8 as independent indicators of survival in patients with cervical squamous cell carcinoma

Background

Cervical cancer is the second leading cause of death in women 20–39 years old. Because coverage for cervical cancer screening is low, and the vaccination rate of human papillomavirus (HPV) is poor in some countries, potential markers to detect the disease at early stages are needed. E2F transcription factors (E2Fs) are a family of transcription factors that function in cell proliferation, differentiation, apoptosis, and tumorigenesis. As abnormal activation and regulation of E2Fs are related to tumor development and poor prognosis, we performed bioinformatic analyses and in vitro assays to evaluate the role of E2Fs in cervical cancer.

Methods

Transcriptional expression of E2Fs was initially evaluated in silico using ONCOMINE and Gene Expression Profiling Interactive Analysis (GEPIA), followed by evaluation of E2F1/2/7/8 protein levels using immunohistochemistry in 88 patient tissues. E2F2 and E2F7 mRNA levels were measured by RT-qPCR. LinkedOmics and Metascape were used to predict functions of E2Fs, and in vitro experiments were performed to assess the tumorigenic role of E2F2 and E2F7.

Results

In silico analysis showed that E2F1/2/7/8 were significantly overexpressed in cervical cancer, findings which were confirmed at the protein level using immunohistochemistry. Further, upregulation of E2F1/2/7/8 was associated with different clinicopathological prognostic factors, including positivity for lymph vessel invasion and deep invasion of cervical stroma. Increased expression of E2F1/2/7/8 was also related to shorter overall survival (OS) and disease-free survival (DFS) in patients with cervical cancer. Using multivariate analysis, we confirmed E2F1/2/7/8 as independent prognostic factors for shorter OS of patients with cervical cancer. Finally, in vitro experiments showed that E2F2 and E2F7 are involved in cell proliferation and migration and cell cycle regulation in both HPV-positive and HPV-negative cervical cancer cells.

Conclusions

E2F1/2/7/8 may be prognostic biomarkers for survival of patients with cervical cancer. E2F2 and E2F7 are involved in cell proliferation, migration, and cell cycle in both HPV-positive and HPV-negative cervical cancer cells.

Identification of a Novel Tumor Microenvironment-Associated Eight-Gene Signature for Prognosis Prediction in Lung Adenocarcinoma

Background

Lung cancer has become the most common cancer type and caused the most cancer deaths. Lung adenocarcinoma (LUAD) is one of the major types of lung cancer. Accumulating evidence suggests the tumor microenvironment is correlated with the tumor progress and the patient's outcome. This study aimed to establish a gene signature based on tumor microenvironment that can predict patients' outcomes for LUAD.

Methods

Dataset TCGA-LUAD, downloaded from the TCGA portal, were taken as training cohort, and dataset GSE72094, obtained from the GEO database, was set as validation cohort. In the training cohort, ESTIMATE algorithm was applied to find intersection differentially expressed genes (DEGs) among tumor microenvironment. Kaplan-Meier analysis and univariate Cox regression model were performed on intersection DEGs to preliminarily screen prognostic genes. Besides, the LASSO Cox regression model was implemented to build a multi-gene signature, which was then validated in the validation cohorts through Kaplan-Meier, Cox, and receiver operating characteristic curve (ROC) analyses. In addition, the correlation between tumor mutational burden (TMB) and risk score was evaluated by Spearman test. GSEA and immune infiltrating analyses were conducted for understanding function annotation and the role of the signature in the tumor microenvironment.

Results

An eight-gene signature was built, and it was examined by Kaplan-Meier analysis, revealing that a significant overall survival difference was seen. The eight-gene signature was further proven to be independent of other clinico-pathologic parameters via the Cox regression analyses. Moreover, the ROC analysis demonstrated that this signature owned a better predictive power of LUAD prognosis. The eight-gene signature was correlated with TMB. Furthermore, GSEA and immune infiltrating analyses showed that the exact pathways related to the characteristics of eight-genes signature, and identified the vital roles of Mast cells resting and B cells naive in the prognosis of the eight-gene signature.

Conclusion

Identifying the eight-gene signature (INSL4, SCN7A, STAP1, P2RX1, IKZF3, MS4A1, KLRB1, and ACSM5) could accurately identify patients' prognosis and had close interactions with Mast cells resting and B cells naive, which may provide insight into personalized prognosis prediction and new therapies for LUAD patients.

Identification and validation of the prognostic value of immune-related genes in non-small cell lung cancer

Immune-related genes play a significant role in predicting the overall survival and monitoring the status of the cancer immune microenvironment. The aim of this research study was to identify differentially expressed immune-related genes (DEIRGs) and establish a Cox prediction model for the evaluation of prognosis in patients with non-small cell lung cancer (NSCLC). Transcription expression data, immune gene data, and tumor transcription factor data from The Cancer Genome Atlas (TCGA), the Immunology Database and Analysis Portal, and the Cistrome Cancer database were analyzed to detect differentially expressed genes (DEGs), DEIRGs, and differentially expressed transcription factors (DETFs). Multivariate Cox regression analysis was used to obtain potential DEIRGs as independent prognostic factors. Oncomine, The Human Protein Atlas (HPA), TIMER databases were performed to validate the mRNA and protein expression level of DEIRGs. TIMER database was performed to explore the immunocytes infiltration of DEIRGs. In total, 7448 DEGs, 536 DEIRGs, 87 DETFs were identified from 1,037 NSCLC tissues and 108 normal tissues in TCGA database. Fifteen-DEIRG signatures (THBS1, S100P, S100A16, DLL4, CD70, DKK1, IL33, NRTN, PDGFB, STC2, VGF, GCGR, HTR3A, LGR4, SHC3) could be perceived as independent prognostic factors for predicting the overall survival of patients with NSCLC (P = 4.89e--09). Immune cell correlation analysis showed that neutrophils and b cells were positively and negatively correlated with the riskscore of the prediction model, respectively. Our study identified a Cox prediction model based on DEIRGs to predict the overall survival of patients with NSCLC. The immunocyte infiltration analysis provided a novel horizon for monitoring the status of the NSCLC immune microenvironment.

SMAD-6, -7 and -9 are potential molecular biomarkers for the prognosis in human lung cancer

SMADs, a family of proteins that function as signal transducers and transcriptional regulators to regulate various signaling pathways, including the transforming growth factor-β signaling pathway, are similar to the mothers against decapentaplegic family of genes and the sma gene family in Caenorhabditis elegans. SMADs generate context-dependent modulation by interacting with various sequence-specific transcription factors, such as E2F4/5, c-Fos, GATA3, YY1 and SRF, which have been found to serve a key role in lung carcinoma oncogenesis and progression. However, the prognostic values of the eight SMADs in lung cancer have not been fully understood. In the present study, the expression levels and survival data of SMADs in patients with lung carcinoma from the Oncomine, Gene Expression Profiling Interactive Analysis, Kaplan-Meier plotter and cBioPortal databases were downloaded and analyzed. It was found that the mRNA expression levels of SMAD-6, -7 and -9 were decreased in lung adenocarcinoma and squamous cell carcinoma compared with that in adjacent normal tissues, while there was no significant difference in SMADs 1-5. Survival analysis revealed that not only were low transcriptional levels of SMAD-6, -7 and -9 associated with low overall survival but they also had prognostic role for progression-free survival and post-progression survival (P<0.05) in patients with lung carcinoma. In conclusion, the present study demonstrated that SMAD-6, -7 and -9 are potential biomarkers for the prognosis of patients with lung carcinoma.

Inhibition of pyruvate dehydrogenase kinase‑1 by dicoumarol enhances the sensitivity of hepatocellular carcinoma cells to oxaliplatin via metabolic reprogramming

The Warburg effect is a unique metabolic feature of the majority of tumor cells and is closely related to chemotherapeutic resistance. Pyruvate dehydrogenase kinase 1 (PDK1) is considered a 'switch' that controls the fate of pyruvate in glucose metabolism. However, to date, to the best of our knowledge, there are only a few studies to available which had studied the reduction of chemotherapeutic resistance via the metabolic reprogramming of tumor cells with PDK1 as a target. In the present study, it was found dicoumarol (DIC) reduced the phosphorylation of pyruvate dehydrogenase (PDH) by inhibiting the activity of PDK1, which converted the metabolism of human hepatocellular carcinoma (HCC) cells to oxidative phosphorylation, leading to an increase in mitochondrial reactive oxygen species ROS (mtROS) and a decrease in mitochondrial membrane potential (MMP), thereby increasing the apoptosis induced by oxaliplatin (OXA). Furthermore, the present study elucidated that the targeting of PDK1 may be a potential strategy for targeting metabolism in the chemotherapy of HCC. In addition, DIC as an 'old drug' exhibits novel efficacy, bringing new hope for antitumor therapy.