Screening of differentially expressed genes and identification of NUF2 as a prognostic marker in breast cancer

Implications of the NDC80 complex on the tumor immune microenvironment and cell growth in pan-cancer

Background: Previous evidence indicates that the NDC80 complex, a conserved spindle microtubule-binding component of the kinetochore, is overexpressed and associated with prognosis in certain cancer types. Herein, we assessed the expression and prognostic value of NDC80 complex components in pan-cancer and interrogated their potential functions in tumor context through multiple databases and software. Results: Our findings showed that the expression of NDC80 complex components was aberrant across almost all cancer types and correlated positively with poor prognosis at the pan-cancer level. Furthermore, the expression levels of NDC80 complex components were positively associated with Th2 cell infiltration in the majority of cancer types. Additionally, higher expression of the NDC80 complex components was associated with increased immune checkpoint gene expression and TP53 mutation in specific cancer types. We also discovered that NDC80 complex components play pivotal roles in cell division, and the cell cycle within the tumor context. Moreover, knockdown of NDC80 significantly suppressed cell growth and inhibited the G1-S phase transition in two breast cancer cell lines. Conclusions: Our study suggests that the NDC80 complex components could serve as reliable biomarkers for cancer detection and prognosis in pan-cancer, in addition to uncovering their role as cancer-promoting genes involved in Th2 cell infiltration, immune checkpoint, cell growth, and TP53 mutation.

FOXM1 promotes neurofibromatosis type 1-associated malignant peripheral nerve sheath tumor progression in a NUF2-dependent manner

Malignant peripheral nerve sheath tumors (MPNSTs) are aggressive soft-tissue sarcomas characterized by poor prognosis and low drug response rates. Traditional chemo/radiotherapies show only mild benefits for patients with MPNSTs, and no targeted therapy is available in the clinic. A better understanding of the molecular background of MPNSTs is critical for the development of effective targeted therapies. Forkhead box M1 (FOXM1) has been implicated in the progression of many human malignancies, though its role in MPNSTs is unclear. In this study, using four Gene Expression Omnibus (GEO) datasets and a tissue microarray, we demonstrated that FOXM1 upregulation was associated with poor prognosis in patients with MPNSTs. FOXM1 overexpression and knockdown regulated the proliferation and colony formation of MPNST cells. Using bioinformatics analysis and luciferase reporter assays, we identified NUF2 as a direct downstream target of FOXM1. Both in vitro and in vivo experiments demonstrated that the induction of MPNST cell proliferation by FOXM1 was dependent on elevated NUF2 expression, as NUF2 knockdown abolished the FOXM1-induced proliferation of MPNST cells. Our study showed that the FOXM1-NUF2 axis mediates human MPNST progression and could be a potential therapeutic target.

A 9-gene prognostic signature for kidney renal clear cell carcinoma overall survival based on co-expression and regression analyses

This research attempted to screen potential signatures associated with KIRC progression and overall survival by weighted gene co-expression network analysis (WGCNA) and Cox regression. The KIRC-associated mRNA expression and clinical data were accessed from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were screened by differential analysis. A co-expression network was constructed by "WGCNA". Based on WGCNA module, GO and KEGG analyses were performed. Protein-protein interaction (PPI) network was constructed. Prognostic signatures were screened by Lasso-Cox regression. Prognostic model was evaluated by Receiver Operating Characteristic (ROC) and Kaplan-Meier (K-M) curves. Multivariate Cox and nomogram were introduced to examine whether risk score could be an independent marker. qRT-PCR was introduced to determine expression of 9 hub genes in KIRC clinical tumor tissues and adjacent tissues, respectively. Genes in the green module were highly associated with clinical status, and green module genes were significantly enriched in mitotic nuclear division, cell cycle, and p53 signaling pathway. Twenty-six candidates were subsequently screened out from the green module. Next, a 9-gene prognostic model (DLGAP5, NUF2, TOP2A, RRM2, HJURP, PLK1, AURKB, KIF18A, CCNB2) was constructed. The predicting ability of the model was optimal. Some cancer-related signaling pathways were differently activated between two risk score groups. Additionally, under-expression of some signature genes (AURKB, CCNB2, PLK1, RRM2, TOP2A) was associated with better survival rate for KIRC patients. Meanwhile, all 9 hub genes were substantially overexpressed in KIRC patients. A KIRC prognostic signature was screened in this study, contributing valuable findings to KIRC biomarker development.

A Comprehensive Landscape of Imaging Feature-Associated RNA Expression Profiles in Human Breast Tissue

The expression abundance of transcripts in nondiseased breast tissue varies among individuals. The association study of genotypes and imaging phenotypes may help us to understand this individual variation. Since existing reports mainly focus on tumors or lesion areas, the heterogeneity of pathological image features and their correlations with RNA expression profiles for nondiseased tissue are not clear. The aim of this study is to discover the association between the nucleus features and the transcriptome-wide RNAs. We analyzed both microscopic histology images and RNA-sequencing data of 456 breast tissues from the Genotype-Tissue Expression (GTEx) project and constructed an automatic computational framework. We classified all samples into four clusters based on their nucleus morphological features and discovered feature-specific gene sets. The biological pathway analysis was performed on each gene set. The proposed framework evaluates the morphological characteristics of the cell nucleus quantitatively and identifies the associated genes. We found image features that capture population variation in breast tissue associated with RNA expressions, suggesting that the variation in expression pattern affects population variation in the morphological traits of breast tissue. This study provides a comprehensive transcriptome-wide view of imaging-feature-specific RNA expression for healthy breast tissue. Such a framework could also be used for understanding the connection between RNA expression and morphology in other tissues and organs. Pathway analysis indicated that the gene sets we identified were involved in specific biological processes, such as immune processes.

NUF2 overexpression contributes to epithelial ovarian cancer progression via ERBB3-mediated PI3K-AKT and MAPK signaling axes

Introduction

NDC80 kinetochore complex component (NUF2) is upregulated and plays an important role in various human cancers. However, the function and mechanism of NUF2 in epithelial ovarian cancer (EOC) remain unclear.

Methods

NUF2 expression was detected in EOC tissues and cell lines. The effects of NUF2 downregulation on cell proliferation, migration and invasion in EOC were analyzed by CCK-8 and Transwell assays. Meanwhile, the effect of NUF2 downregulation on tumor growth in vivo was determined by xenograft tumor models. The mechanisms by which NUF2 regulates EOC progression were detected by RNA sequencing and a series of in vitro assays.

Results

We showed that NUF2 was significantly upregulated in EOC tissues and cell lines, and high NUF2 expression was associated with FIGO stage, pathological grade and poor EOC prognosis. NUF2 downregulation decreased cell proliferation, migration, invasion and tumor growth in nude mice. RNA sequencing studies showed that NUF2 knockdown inhibited several genes enriched in the phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K)-AKT serine/threonine kinase (AKT) and mitogen-activated protein kinase (MAPK) signaling pathways. Erb-B2 receptor tyrosine kinase 3 (ERBB3) was the key factor involved in both of the above pathways. We found that ERBB3 silencing could inhibit EOC progression and repress activation of the PI3K-AKT and MAPK signaling pathways. Furthermore, the exogenous overexpression of ERBB3 partially reversed the inhibitory effects on EOC progression induced by NUF2 downregulation, while LY294002 and PD98059 partially reversed the effects of ERBB3 upregulation.

Conclusion

These results showed that NUF2 promotes EOC progression through ERBB3-induced activation of the PI3K-AKT and MAPK signaling axes. These findings suggest that NUF2 might be a potential therapeutic target for EOC.

Kidney Cancer Biomarker Selection Using Regularized Survival Models

Clear cell renal cell carcinoma (ccRCC) is the most common subtype of RCC showing a significant percentage of mortality. One of the priorities of kidney cancer research is to identify RCC-specific biomarkers for early detection and screening of the disease. With the development of high-throughput technology, it is now possible to measure the expression levels of thousands of genes in parallel and assess the molecular profile of individual tumors. Studying the relationship between gene expression and survival outcome has been widely used to find genes associated with cancer survival, providing new information for clinical decision-making. One of the challenges of using transcriptomics data is their high dimensionality which can lead to instability in the selection of gene signatures. Here we identify potential prognostic biomarkers correlated to the survival outcome of ccRCC patients using two network-based regularizers (EN and TCox) applied to Cox models. Some genes always selected by each method were found (COPS7B, DONSON, GTF2E2, HAUS8, PRH2, and ZNF18) with known roles in cancer formation and progression. Afterward, different lists of genes ranked based on distinct metrics (logFC of DEGs or β coefficients of regression) were analyzed using GSEA to try to find over- or under-represented mechanisms and pathways. Some ontologies were found in common between the gene sets tested, such as nuclear division, microtubule and tubulin binding, and plasma membrane and chromosome regions. Additionally, genes that were more involved in these ontologies and genes selected by the regularizers were used to create a new gene set where we applied the Cox regression model. With this smaller gene set, we were able to significantly split patients into high/low risk groups showing the importance of studying these genes as potential prognostic factors to help clinicians better identify and monitor patients with ccRCC.

NUF2 Expression Promotes Lung Adenocarcinoma Progression and Is Associated With Poor Prognosis

Aberrant expression of the gene encoding the Ndc80 kinetochore complex component (NUF2) reportedly contributes to the progression of several human cancers. However, the functional roles of NUF2 and their underlying mechanisms in lung adenocarcinoma (LUAD) are largely unknown. The current study aimed to investigate the role of NUF2 in LUAD tumorigenesis. Here, TCGA, ONCOMINE, the Human Protein Atlas, UALCAN, and the results of our cohort were used to analyze the expression of NUF2 in LUAD. A Kaplan–Meier analysis and univariate and multivariate Cox regression analyses were performed to estimate the prognostic values of NUF2 expression in the Cancer Genome Atlas cohort. We studied the effects of NUF2 expression on proliferation, migration, invasion, and tumor growth using LUAD cell lines. Gene set enrichment analysis (GSEA) was used to analyze the pathways and biological function enrichment of NUF2 in LUAD. The ssGSEA database was used to analyze the relationship between NUF2 expression and immune cell infiltration in LUAD. Results revealed elevated expression of NUF2 in LUAD specimens. Patients overexpressing NUF2 had poor prognoses relative to those with low NUF2 expression. Knockdown of NUF2 suppressed the proliferation, migration, invasion, epithelial-mesenchymal transition, and colony formation of LUAD cells. Moreover, NUF2 knockdown induced cell cycle arrest at the G0/G1 phase. Gene Ontology and GSEA analyses suggested that NUF2 may be involved in immunity, proliferation, and apoptosis-related pathways. NUF2 overexpression was positively correlated with differential immune cell infiltration. In conclusion, NUF2 expression was associated with the clinical phenotype of LUAD and hence has potential implications in LUAD treatment.

Transcriptome profiling and proteomic validation reveals targets of the androgen receptor signaling in the BT-474 breast cancer cell line

BACKGROUND

Accumulating evidence suggests that the androgen receptor (AR) and its endogenous ligands influence disease progression in breast cancer (BCa). However, AR-mediated changes in BCa differ among the various BCa subtypes according to their hormone receptor profile [i.e., presence/absence of estrogen receptor (ER), progesterone receptor (PR) and human epidermal growth factor receptor 2, (HER2)]. Thus, we explored the androgen-regulated transcriptomic changes in the ER⁺PR⁺HER2⁺ BCa cell line, BT-474, and compared them with PR-mediated changes.

METHODS

We performed RNA sequencing analysis in treated BT-474 cells with dihydrotestosterone (DHT) and progesterone. Validation of the top ten differentially androgen-regulated genes and a number of other genes found in enriched signaling pathways was performed by qRT-PCR in BT-474 and other BCa cell lines. In addition, a parallel reaction monitoring targeted proteomic approach was developed to verify selected transcripts at the protein level.

RESULTS

In total 19,450 transcripts were detected, of which 224 were differentially regulated after DHT treatment. The increased expression of two well-known androgen-regulated genes, KLK2 (p < 0.05) and KLK3 (p < 0.001), confirmed the successful androgen stimulation in BT-474 cells. The transcription factor, ZBTB16, was the most highly upregulated gene, with ~ 1000-fold change (p < 0.001). Pathway enrichment analysis revealed downregulation of the DNA replication processes (p < 0.05) and upregulation of the androgen signaling and fatty acid metabolism pathways (p < 0.05). Changes related to progesterone treatment showed opposite effects in gene expression than DHT treatment. Similar expression profiles were observed among other BCa cell lines expressing high levels of AR (ZR75.1 and MBA-MB-453). The parallel reaction monitoring targeted proteomic analysis further confirmed that altered protein expression (KLK3, ALOX15B) in the supernatant and cell lysate of DHT-treated BT-474 cells, compared to control cells.

DISCUSSION

Our findings suggest that AR modulates the metabolism of BT-474 cells by affecting the expression of a large number of genes and proteins. Based on further pathway analysis, we suggest that androgen receptor acts as a tumor suppressor in the BT-474 cells.

An interactive nomogram based on clinical and molecular signatures to predict prognosis in multiple myeloma patients

Although novel drugs and treatments have been developed and improved, multiple myeloma (MM) is still recurrent and difficult to cure. In the present study, the magenta module containing 400 hub genes was determined from the training dataset of GSE24080 through weighted gene co-expression network analysis (WGCNA). Then, using the least absolute shrinkage and selection operator (Lasso) analysis, a fifteen-gene signature was firstly selected and the predictive performance for overall survival (OS) was favorable, which was identified by Receiver Operating Characteristic (ROC) curves. The risk score model was constructed based on survival-associated fifteen genes from the Lasso model, which classified MM patients into high-risk and low-risk groups. Areas under the curve (AUC) of ROC curve and log-rank test showed that the high-risk group was correlated to the dismal survival outcome of MM patients, which was also identified in testing dataset of GSE9782. The calibration plot, the AUC value of the ROC curve and Concordance-index showed that the interactive nomogram with risk score could favorably predict the probability of multi-year OS of MM patients. Therefore, it may help clinicians make a precise therapeutic decision based on the easy-to-use tool of the nomogram.

Integrative Multi-Omics Analysis of Identified NUF2 as a Candidate Oncogene Correlates With Poor Prognosis and Immune Infiltration in Non-Small Cell Lung Cancer

Background

Lung cancer is one of the most common malignant tumors and the leading causes of cancer-related deaths worldwide. As a component of the nuclear division cycle 80 complex, NUF2 is a part of the conserved protein complex related to the centromere. Although the high expression of NUF2 has been reported in many different types of human cancers, the multi-omics analysis in non-small cell lung cancer (NSCLC) of NUF2 remains to be elucidated.

Methods

In this analysis, NUF2 expression difference analysis in non-small cell lung cancer was evaluated by Oncomine, TIMER, GEO, and TCGA database. And the prognosis analysis of NUF2 based on Kaplan-Meier was performed. R language was used to analyze the differential expression genes, functional annotation and protein-protein interaction (PPI). GSEA analysis of differential expression genes was also carried out. Mechanism analysis about exploring the characteristic of NUF2, multi-omics, and correlation analysis was carried out using UALCAN, cBioportal, GEPIA, TIMER, and TISIDB, respectively.

Results

The expression of NUF2 in NSCLC, both lung adenocarcinoma (LUAD) and squamous lung cancer (LUSC), was significantly higher than that in normal tissues. The analysis of UALCAN database samples proved that NUF2 expression was connected with stage and smoking habits. Meanwhile, the overall survival curve also validated that high expression of NUF2 has a poorer prognosis in NSCLC. GO, KEGG, GSEA, subcellular location from COMPARTMENTS indicated that NUF2 may regulate the cell cycle. Correlation analysis also showed that NUF2 was mainly positively associated with cell cycle and tumor-related genes. NUF2 altered group had a poorer prognosis than unaltered group in NSCLC. Immune infiltration analysis showed that the NUF2 expression mainly have negatively correlation with immune cells and immune subtypes in LUAD and LUSC. Furthermore, quantitative PCR was used to validate the expression difference of NUF2 in LUAD and LUSC.

Conclusion

Our findings elucidated that NUF2 may play an important role in cell cycle, and significantly associated with tumor-related gene in NSCLC; we consider that NUF2 may be a prognostic biomarkers in NSCLC.

Highly heterogeneous-related genes of triple-negative breast cancer: potential diagnostic and prognostic biomarkers

Background

Triple-negative breast cancer (TNBC) is a highly heterogeneous subtype of breast cancer, showing aggressive clinical behaviors and poor outcomes. It urgently needs new therapeutic strategies to improve the prognosis of TNBC. Bioinformatics analyses have been widely used to identify potential biomarkers for facilitating TNBC diagnosis and management.

Methods

We identified potential biomarkers and analyzed their diagnostic and prognostic values using bioinformatics approaches. Including differential expression gene (DEG) analysis, Receiver Operating Characteristic (ROC) curve analysis, functional enrichment analysis, Protein-Protein Interaction (PPI) network construction, survival analysis, multivariate Cox regression analysis, and Non-negative Matrix Factorization (NMF).

Results

A total of 105 DEGs were identified between TNBC and other breast cancer subtypes, which were regarded as heterogeneous-related genes. Subsequently, the KEGG enrichment analysis showed that these genes were significantly enriched in ‘cell cycle’ and ‘oocyte meiosis’ related pathways. Four (FAM83B, KITLG, CFD and RBM24) of 105 genes were identified as prognostic signatures in the disease-free interval (DFI) of TNBC patients, as for progression-free interval (PFI), five genes (FAM83B, EXO1, S100B, TYMS and CFD) were obtained. Time-dependent ROC analysis indicated that the multivariate Cox regression models, which were constructed based on these genes, had great predictive performances. Finally, the survival analysis of TNBC subtypes (mesenchymal stem-like [MSL] and mesenchymal [MES]) suggested that FAM83B significantly affected the prognosis of patients.

Conclusions

The multivariate Cox regression models constructed from four heterogeneous-related genes (FAM83B, KITLG, RBM24 and S100B) showed great prediction performance for TNBC patients’ prognostic. Moreover, FAM83B was an important prognostic feature in several TNBC subtypes (MSL and MES). Our findings provided new biomarkers to facilitate the targeted therapies of TNBC and TNBC subtypes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08318-1.

Poly-SUMO-2/3 chain modification of Nuf2 facilitates CENP-E kinetochore localization and chromosome congression during mitosis

SUMO modification is required for the kinetochore localization of the kinesin-like motor protein CENP-E, which subsequently mediates the alignment of chromosomes to the spindle equator during mitosis. However, the underlying mechanisms by which sumoylation regulates CENP-E kinetochore localization are still unclear. In this study, we first elucidate that the kinetochore protein Nuf2 is not only required for CENP-E kinetochore localization but also preferentially modified by poly-SUMO-2/3 chains. In addition, poly-SUMO-2/3 modification of Nuf2 is significantly upregulated during mitosis, which is temporally correlated to the kinetochore localization of CENP-E during mitosis. We further show that the mitotic defects in CENP-E kinetochore localization and chromosome congression caused by global inhibition of sumoylation can be rescued by expressing a fusion protein between Nuf2 and the SUMO-conjugating enzyme Ubc9 for stimulating Nuf2 SUMO-2/3 modification. Moreover, the expression of another fusion protein between Nuf2 and three SUMO-2 moieties (SUMO-2 trimer), which mimics the trimeric SUMO-2/3 chain modification of Nuf2, can also rescue the mitotic defects due to global inhibition of sumoylation. Conversely, expressing the other forms of Nuf2-SUMO fusion proteins, which imitate Nuf2 modifications by SUMO-2/3 monomer, SUMO-2/3 dimer, and SUMO-1 trimer, respectively, cannot rescue the same mitotic defects. Lastly, compared to Nuf2, the fusion protein simulating the trimeric SUMO-2 chain-modified Nuf2 exhibits a significantly higher binding affinity to CENP-E wild type containing a functional SUMO-interacting motif (SIM) but not the CENP-E SIM mutant. Hence, our results support a model that poly-SUMO-2/3 chain modification of Nuf2 facilitates CENP-E kinetochore localization and chromosome congression during mitosis.Abbreviations: CENP-E, centromere-associated protein E; SUMO, small ubiquitin-related modifier; SIM, SUMO-interacting motif.

Development of a Novel Prognostic Signature Based on Antigen Processing and Presentation in Patients with Breast Cancer

Background: Complex antigen processing and presentation processes are involved in the development and progression of breast cancer (BC). A single biomarker is unlikely to adequately reflect the complex interplay between immune cells and cancer; however, there have been few attempts to find a robust antigen processing and presentation-related signature to predict the survival outcome of BC patients with respect to tumor immunology. Therefore, we aimed to develop an accurate gene signature based on immune-related genes for prognosis prediction of BC. Methods: Information on BC patients was obtained from The Cancer Genome Atlas. Gene set enrichment analysis was used to confirm the gene set related to antigen processing and presentation that contributed to BC. Cox proportional regression, multivariate Cox regression, and stratified analysis were used to identify the prognostic power of the gene signature. Differentially expressed mRNAs between high- and low-risk groups were determined by KEGG analysis. Results: A three-gene signature comprising HSPA5 (heat shock protein family A member 5), PSME2 (proteasome activator subunit 2), and HLA-F (major histocompatibility complex, class I, F) was significantly associated with OS. HSPA5 and PSME2 were protective (hazard ratio (HR) < 1), and HLA-F was risky (HR > 1). Risk score, estrogen receptor (ER), progesterone receptor (PR) and PD-L1 were independent prognostic indicators. KIT and ACACB may have important roles in the mechanism by which the gene signature regulates prognosis of BC. Conclusion: The proposed three-gene signature is a promising biomarker for estimating survival outcomes in BC patients.

Correlation of NUF2 Over-expression with Poorer Patient Survival in Multiple Cancers

Purpose

NUF2 has been implicated in multiple cancers recently, suggesting NUF2 may play a role in the common tumorigenesis process. In this study, we aim to perform comprehensive meta-analysis of NUF2 expression in the cancer types included in the Cancer Genome Atlas (TCGA).

Materials and Methods

RNA-sequencing data in 31 cancer types in the TCGA data and 11 independent datasets were used to examine NUF2 expression. Silencing NUF2 using targeting shRNAs in hepatocellular carcinoma (HCC) cell lines was used to evaluate NUF2’s role in HCC in vitro and in vivo.

Results

NUF2 up-regulation is significantly observed in 23 out of the 31 cancer types in the TCGA datasets and validated in 13 major cancer types using 11 independent datasets. NUF2 overexpression was clinically important as high NUF2 was significantly associated with tumor stages in eight different cancers. High NUF2 was also associated with significantly poorer patient overall survival and disease-free survival in eight and six cancers, respectively. We proceeded to validate NUF2 overexpression and its negative association with overall survival at the protein level in an independent cohort of 40 HCC patients. Compared to the non-targeting controls, NUF2 knockdown cells showed significantly reduced ability to grow, migrate into a scratch wound and invade the 8 μm porous membrane in vitro. Moreover, NUF2 knockdown cells also formed significantly smaller tumors than control cells in mouse xenograft assays in vivo.

Conclusion

NUF2 up-regulation is a common feature of many cancers. The prognostic potential and functional impact of NUF2 up-regulation warrant further studies.

Identification of novel transcription factor-microRNA-mRNA co-regulatory networks in pulmonary large-cell neuroendocrine carcinoma

Background

Large cell neuroendocrine carcinoma (LCNEC) of the lung is a rare neuroendocrine neoplasm. Previous studies have shown that microRNAs (miRNAs) are widely involved in tumor regulation through targeting critical genes. However, it is unclear which miRNAs play vital roles in the pathogenesis of LCNEC, and how they interact with transcription factors (TFs) to regulate cancer-related genes.

Methods

To determine the novel TF-miRNA-target gene feed-forward loop (FFL) model of LCNEC, we integrated multi-omics data from Gene Expression Omnibus (GEO), Transcriptional Regulatory Relationships Unraveled by Sentence-Based Text Mining (TRRUST), Transcriptional Regulatory Element Database (TRED), and The experimentally validated microRNA-target interactions database (miRTarBase database). First, expression profile datasets for mRNAs (GSE1037) and miRNAs (GSE19945) were downloaded from the GEO database. Overlapping differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs) were identified through integrative analysis. The target genes of the FFL were obtained from the miRTarBase database, and the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were performed on the target genes. Then, we screened for key miRNAs in the FFL and performed gene regulatory network analysis based on key miRNAs. Finally, the TF-miRNA-target gene FFLs were constructed by the hypergeometric test.

Results

A total of 343 DEGs and 60 DEMs were identified in LCNEC tissues compared to normal tissues, including 210 down-regulated and 133 up-regulated genes, and 29 down-regulated and 31 up-regulated miRNAs. Finally, the regulatory network of TF-miRNA-target gene was established. The key regulatory network modules included ETS1-miR195-CD36, TAOK1-miR7-1-3P-GRIA1, E2F3-miR195-CD36, and TEAD1-miR30A-CTHRC1.

Conclusions

We constructed the TF-miRNA-target gene regulatory network, which is helpful for understanding the complex LCNEC regulatory mechanisms.

Identification of NUF2 and FAM83D as potential biomarkers in triple-negative breast cancer

Background

Breast cancer is a heterogeneous disease. Compared with other subtypes of breast cancer, triple-negative breast cancer (TNBC) is easy to metastasize and has a short survival time, less choice of treatment options. Here, we aimed to identify the potential biomarkers to TNBC diagnosis and prognosis.

Material/Methods

Three independent data sets (GSE45827, GSE38959, GSE65194) were downloaded from the Gene Expression Omnibus (GEO). The R software packages were used to integrate the gene profiles and identify differentially expressed genes (DEGs). A variety of bioinformatics tools were used to explore the hub genes, including the DAVID database, STRING database and Cytoscape software. Reverse transcription quantitative PCR (RT-qPCR) was used to verify the hub genes in 14 pairs of TNBC paired tissues.

Results

In this study, we screened out 161 DEGs between 222 non-TNBC and 126 TNBC samples, of which 105 genes were up-regulated and 56 were down-regulated. These DEGs were enriched for 27 GO terms and two pathways. GO analysis enriched mainly in “cell division”, “chromosome, centromeric region” and “microtubule motor activity”. KEGG pathway analysis enriched mostly in “Cell cycle” and “Oocyte meiosis”. PPI network was constructed and then 10 top hub genes were screened. According to the analysis results of the Kaplan-Meier survival curve, the expression levels of only NUF2, FAM83D and CENPH were associated with the recurrence-free survival in TNBC samples (P < 0.05). RT-qPCR confirmed that the expression levels of NUF2 and FAM83D in TNBC tissues were indeed up-regulated significantly.

Conclusions

The comprehensive analysis showed that NUF2 and FAM83D could be used as potential biomarkers for diagnosis and prognosis of TNBC.

Identification of potential key genes in gastric cancer using bioinformatics analysis

Gastric cancer (GC) is one of the most common types of cancer worldwide. Patients must be identified at an early stage of tumor progression for treatment to be effective. The aim of the present study was to identify potential biomarkers with diagnostic value in patients with GC. To examine potential therapeutic targets for GC, four Gene Expression Omnibus (GEO) datasets were downloaded and screened for differentially expressed genes (DEGs). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were subsequently performed to study the function and pathway enrichment of the identified DEGs. A protein-protein interaction (PPI) network was constructed. The CytoHubba plugin of Cytoscape was used to calculate the degree of connectivity of proteins in the PPI network, and the two genes with the highest degree of connectivity were selected for further analysis. Additionally, the two DEGs with the largest and smallest log Fold Change values were selected. These six key genes were further examined using Oncomine and the Kaplan-Meier plotter platform. A total of 99 upregulated and 172 downregulated genes common to all four GEO datasets were screened. The DEGs were primarily enriched in the Biological Process terms: ‘extracellular matrix organization’, ‘collagen catabolic process’ and ‘cell adhesion’. These three KEGG pathways were significantly enriched in the categories: ‘ECM-receptor interaction’, ‘protein digestion and absorption’, and ‘focal adhesion’. Based on Oncomine, expression of ATP4A and ATP4B were downregulated in GC, whereas expression of the other genes were all upregulated. The Kaplan-Meier plotter platform confirmed that upregulated expression of the identified key genes was significantly associated with worse overall survival of patients with GC. The results of the present study suggest that FN1, COL1A1, INHBA and CST1 may be potential biomarkers and therapeutic targets for GC. Additional studies are required to explore the potential value of ATP4A and ATP4B in the treatment of GC.