Flap endonuclease 1 (FEN1) as a novel diagnostic and prognostic biomarker for gastric cancer

Investigation of copper-induced intestinal damage and proteome alterations in Takifugu rubripes: Potential health risks and environmental toxicology detection

Copper is one of the predominant water pollutants. Excessive exposure to copper can cause harm to animal health, affecting the central nervous system and causing blood abnormalities. Cuproptosis is a novel form of cell death that differs from previous programmed cell death methods. However, the impact of copper on the intestines remains unclear. Therefore, we investigated the effects of different concentrations of copper exposure on the intestinal proteome of Takifugu rubripes (T. rubripes). Relevant biomarkers were used to detect cuproptosis. We revealed the crosstalk relationship between cuproptosis and self-rescue at different concentrations, and discussed the feasibility of using potential cuproptosis indicators as anti-infection factors. We observed intestinal damage in the three copper exposure groups, especially in T. rubripes treated with 100 and 500 μg/L copper, with shedding and breakage of intestinal villus and fuzzy and loose structure of intestinal mucosa. The presence of copper stress not only causes cuproptosis but also oxidative damage caused by reactive oxygen species (ROS). The results of quantitative proteomics by TMT showed that compared to the 50 and 100 μg/L copper exposure groups, the expression of glutaminase, pyruvate kinase, and skin mucus lectin in the 500 μg/L group was significantly increased. The positive mediators COX5A and CTNNB1, as well as the negative mediators CD4 and FDXR, were found to be differentially expressed. Using the protein expression trends of cuproptosis indicator factors FDX1 and DLAT to indicate the concentration of copper ions in the environment. In addition, we found a new effect of promoting ferroptosis: providing additional copper ions can activate the phenomenon of ferroptosis. Our results expand our understanding of the potential health risks of copper in T. rubripes. At the same time, it is of great significance for the process of copper poisoning and the development of new environmental toxicology detection reagents.

The endonuclease FEN1 mediates activation of STAT3 and facilitates proliferation and metastasis in breast cancer

BACKGROUND

The metastasis accounts for most deaths from breast cancer (BRCA). Understanding the molecular mechanisms of BRCA metastasis is urgently demanded. Flap Endonuclease 1 (FEN1), a pivotal factor in DNA metabolic pathways, contributes to tumor growth and drug resistance, however, little is known about the role of FEN1 in BRCA metastasis.

METHODS AND RESULTS

In this study, FEN1 expression and its clinical correlation in BRCA were investigated using bioinformatics, showing being upregulated in BRCA samples and significant relationships with tumor stage, node metastasis, and prognosis. Immunohistochemistry (IHC) staining of local BRCA cohort indicated that the ratio of high FEN1 expression in metastatic BRCA tissues rose over that in non-metastatic tissues. The assays of loss-of-function and gain-of-function showed that FEN1 enhanced BRCA cell proliferation, migration, invasion, xenograft growth as well as lung metastasis. It was further found that FEN1 promoted the aggressive behaviors of BRCA cells via Signal Transducer and Activator of Transcription 3 (STAT3) activation. Specifically, the STAT3 inhibitor Stattic thwarted the FEN1-induced enhancement of migration and invasion, while the activator IL-6 rescued the decreased migration and invasion caused by FEN1 knockdown. Additionally, overexpression of FEN1 rescued the inhibitory effect of nuclear factor-κB (NF-κB) inhibitor BAY117082 on phosphorylated STAT3. Simultaneously, the knockdown of FEN1 attenuated the phosphorylation of STAT3 promoted by the NF-κB activator tumor necrosis factor α (TNF-α).

CONCLUSIONS

These results indicate a novel mechanism that NF-κB-driven FEN1 contributes to promoting BRCA growth and metastasis by STAT3 activation.

FEN1 promotes cancer progression of cholangiocarcinoma by regulating the Wnt/β-catenin signaling pathway

PURPOSE

Cholangiocarcinoma (CHOL) comprises a cluster of highly heterogeneous malignant biliary tumors. Flap endonuclease-1 (FEN1) is a member of the Rad2 structure-specific nuclease family. This study aimed to explore the biological functions and mechanisms of FEN1 in CHOL.

METHODS

FEN1 expression was analyzed in tissues of patients with CHOL and FEN1 mutations. We observe the influence of FEN1 on cellular proliferation, migration, and invasion, as well as on DNA damage repair and glycolysis. Western blotting was performed to determine the regulatory mechanism of FEN1 in CHOL progression.

RESULTS

FEN1 was highly expressed in the cancer tissues of CHOL patients. The high mutation rate of FEN1 in CHOL tissues was mainly due to the amplified repeats. FEN1 promotes the proliferation, migration, and invasion of HUCCT1 and QBC939 cells. In addition, FEN1 induced DNA damage repair and aerobic glycolysis in CHOL cells. FEN1 also promoted xenograft tumor growth in vivo. Moreover, we showed that FEN1 mediated the epithelial-mesenchymal transition (EMT) of CHOL. FEN1-mediated EMT was found to be transduced by the Wnt/β-catenin signaling pathway.

CONCLUSION

FEN1 was significantly overexpressed in CHOL tissues, and FEN1 regulates the progression of CHOL through the Wnt/β-catenin signaling pathway.

A one-pot transcriptional assay method that detects the tumor biomarker FEN1 based on its flap cleavage activity

BACKGROUND

Detection of tumor biomarkers in body fluids is a significant advancement in cancer treatment because it allows diagnosis without invasive tissue biopsies. Nucleases have long been regarded as a potential class of biomarkers that can indicate the occurrence and progression of cancers. Among these, flap endonuclease 1 (FEN1) plays an important role in DNA replication and repair, and also overexpressed in abnormally proliferating cells such as cancer cells. FEN1 is thus considered to be a potential biomarker as well as a target for cancer therapy.

RESULTS

We developed a novel method for detecting FEN1 based on its specific endonuclease activity which incises bifurcated nucleic acids (flaps), in combination with in vitro transcription. Developed method uses a simple DNA structure (substrate DNA) carrying a short 5'-flap sequence, and a single-stranded sensor DNA encoding the Broccoli light-up aptamer. When the assay mixture was supplied with a FEN1-containing sample, the flap sequence encoding the sense sequence of T7 promoter was cleaved and released from the substrate DNA. Because the sensor DNA was designed to carry the Broccoli RNA aptamer under the antisense sequence of T7 promoter, hybridization of the excised flap onto the sensor DNA initiated the transcription of the Broccoli RNA aptamer, enabling determination of the FEN1 titer based on the fluorescence of transcribed Broccoli aptamer. By using a combination of FEN1-mediated generation of a short oligonucleotide and subsequent oligonucleotide-dependent in vitro transcription, this method could detect FEN1 in biological samples within 1 h.

SIGNIFICANCE AND NOVELTY

Developed method enables the detection of FEN1 by a simple one-pot reaction. It can detect sub-nanomolar concentrations of FEN1 within an hour, and has the potential to be used for cancer diagnosis, prognosis, and drug screening. It also enables easy identification of compounds that inhibit FEN1 activity and is thus a versatile platform for screening anti-cancer drugs. We anticipate that the basic principles of this assay can be applied to detect other biomolecules, such as nucleic acids.

Construction of dual exponential amplification accompanied by multi-terminal signal output method for convenient detection of tumor biomarker FEN1 activity

As an important 5'-nuclease in DNA replication and damage repair, Flap endonuclease 1 (FEN1) has been considered as a potential tumor biomarker due to its overexpression in different human cancer cells. Here, we developed a convenient fluorescent method based on dual enzymatic repairing exponential amplification accompanied by multi-terminal signal output to realize the rapid and sensitive detection of FEN1. In the presence of FEN1, the double-branched substrate could be cleaved to produce 5' flap single strand DNA (ssDNA) which subsequently was used as a primer to initiate the dual exponential amplification (EXPAR) to generate abundant ssDNAs (X' and Y'), then the ssDNAs can respectively hybridize with the 3' and 5' ends of the signal probe to form partially complementary double strands (dsDNAs). Subsequently, the signal probe on the dsDNAs could be digested under the assistance of Bst. polymerase and T7 exonuclease, as well as releasing the fluorescence signals. The method displayed high sensitivity with the detection limit of 9.7 × 10^-3 U mL^-1 (1.94 × 10^-4 U) and also exhibited good selectivity towards FEN1 under the challenge from complicated samples including extracts of normal and cancer cells. Furthermore, it was successfully applied to screen FEN1 inhibitors, holding great promise in the screening of potential drugs targeting FEN1. This sensitive, selective and convenient method could be used for FEN1 assay without the complicated nanomaterial synthesis/modification, showing great potential in FEN1- related prediction and diagnosis.

Down-regulation of DNA key protein-FEN1 inhibits OSCC growth by affecting immunosuppressive phenotypes via IFN-γ/JAK/STAT-1

Oral squamous cell carcinoma (OSCC) escape from the immune system is mediated through several immunosuppressive phenotypes that are critical to the initiation and progression of tumors. As a hallmark of cancer, DNA damage repair is closely related to changes in the immunophenotypes of tumor cells. Although flap endonuclease-1 (FEN1), a pivotal DNA-related enzyme is involved in DNA base excision repair to maintain the stability of the cell genome, the correlation between FEN1 and tumor immunity has been unexplored. In the current study, by analyzing the clinicopathological characteristics of FEN1, we demonstrated that FEN1 overexpressed and that an inhibitory immune microenvironment was established in OSCC. In addition, we found that downregulating FEN1 inhibited the growth of OSCC tumors. In vitro studies provided evidence that FEN1 knockdown inhibited the biological behaviors of OSCC and caused DNA damage. Performing multiplex immunohistochemistry (mIHC), we directly observed that the acquisition of critical immunosuppressive phenotypes was correlated with the expression of FEN1. More importantly, FEN1 directly or indirectly regulated two typical immunosuppressive phenotype-related proteins human leukocyte antigen (HLA-DR) and programmed death receptor ligand 1 (PD-L1), through the interferon-gamma (IFN-γ)/janus kinase (JAK)/signal transducer and activator transcription 1 (STAT1) pathway. Our study highlights a new perspective on FEN1 action for the first time, providing theoretical evidence that it may be a potential immunotherapy target for OSCC.

Trap remediation of CuBi2O4 nanopolyhedra via surface self-coordination by H2O2: an innovative signaling mode for cathodic photoelectrochemical bioassay

This work conveys a new philosophy of surface self-coordination mediated trap remediation for innovative cathodic photoelectrochemical (PEC) signal transduction. Initially, the surface trap states of CuBi₂O₄ nanopolyhedra resulting from dangling bonds can function as charge carrier recombination centers, which suppress the carrier separation efficiency and result in a low photocurrent output. Particularly, hydrogen peroxide (H₂O₂) spontaneously interacts with the uncoordinated Cu(II) on the surface of CuBi₂O₄, enabling efficient elimination of dangling bonds and remedy of trap states, thereby outputting intensified photocurrent readout. Exemplified by Flap endonuclease 1 (FEN1) as a model target, a tetrahedron DNA (THD)-based strand displacement amplification (SDA) was introduced to manipulate the formation of hemin impregnated G-quadruplex (G-quadruplex/hemin) DNAzyme and the resultant catalytic reduction for H₂O₂. In addition, a highly efficient and ultra-sensitive PEC sensing platform was achieved for FEN1 detection with a wide linear range from 1.0 fM to 100.0 pM and a detection limit of 0.3 fM (S/N = 3). This work not only establishes a new idea of cathodic PEC signal transduction, but also offers an efficient biosensing platform for FEN1.

Biomarkers Associated with Immune Checkpoint, N6-Methyladenosine, and Ferroptosis in Patients with Restenosis

Purpose

This study aimed to identify potential diagnostic markers of restenosis after stent implantation and to determine their association with immune checkpoint, ferroptosis, and N6-methyladenosine (m6A).

Patients and methods

Microarray data were downloaded from the National Center for Biotechnology Information (NCBI: GSE46560 and GSE48060 datasets) to identify differentially expressed genes (DEGs) between in-stent restenosis and no-restenosis samples. We then conducted systematic functional enrichment analyses of the DEGs based on Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG), and further predicted the interactions of different proteins using the Search Tool for the Retrieval of Interacting Genes (STRING). We used the MCC and MCODE algorithms in the cytoHubba plug-in to screen three key genes in the network, and employed receiver operating characteristic (ROC) curves to determine their diagnostic significance using a multiscale curvature classification algorithm. Next, we investigated the relationships between these target genes, immune checkpoint, ferroptosis, and m6A. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) was used to verify the above results.

Results

We identified 62 upregulated genes and 243 downregulated genes. Based on GO, KEGG, and screening results, EEF1D, RPL36, and RPSA are promising genes for predicting restenosis. In addition, the methylation of YTHDF2, the ferroptosis-related gene GLS2, and the immune checkpoint-related gene CTLA4 were observed to be associated with restenosis. The qRT-PCR test confirmed that RPSA and RPL36 are useful diagnostic markers of the restenosis that can provide new insights for future studies on its occurrence and molecular mechanisms.

Conclusion

We found that RPSA and RPL36, as useful diagnostic markers of restenosis, can provide new insights for future studies on its occurrence and molecular mechanisms.

Detection of Cancer Marker Flap Endonuclease 1 Using One-Pot Transcription-Powered Clustered Regularly Interspaced Short Palindromic Repeat/Cas12a Signal Expansion

As a critical functional protein in DNA replication and genome stability, flap endonuclease 1 (FEN1) has been considered a promising biomarker and druggable target for multiple cancers. We report here a transcription-powered clustered regularly interspaced short palindromic repeat (CRISPR)/Cas12a signal expansion platform for rapid and sensitive detection of FEN1. In this method, the probe cleavage by FEN1 generated a free 5' flap single-stranded DNA which could hybridize with the single-stranded T7 promoter-bearing template and trigger the extension. Then, the CRISPR guide RNA (crRNA) transcribed from the extended template activated the collateral DNase activity of Cas12a, releasing the fluorophore from the quenched DNA signal probe to report the FEN1 detection result. The high specificity for FEN1 was validated by comparing with other repair-relevant proteins. The limit of detection (LOD) could be as low as 0.03 mU, which is sensitive enough to detect the FEN1 activity in biological samples. In addition, the inhibition assay of FEN1 was also successfully achieved with this platform, proving its potential in inhibitor screening. In summary, this study provides a novel biosensor for FEN1 activity analysis and provides new insights into the development of CRISPR-based biosensors for non-nucleic acid targets.

Small-Molecule Inhibitors Targeting FEN1 for Cancer Therapy

DNA damage repair plays a key role in maintaining genomic stability and integrity. Flap endonuclease 1 (FEN1) is a core protein in the base excision repair (BER) pathway and participates in Okazaki fragment maturation during DNA replication. Several studies have implicated FEN1 in the regulation of other DNA repair pathways, including homologous recombination repair (HRR) and non-homologous end joining (NHEJ). Abnormal expression or mutation of FEN1 in cells can cause a series of pathological responses, leading to various diseases, including cancers. Moreover, overexpression of FEN1 contributes to drug resistance in several types of cancers. All this supports the hypothesis that FEN1 could be a therapeutic target for cancer treatment. Targeting FEN1 has been verified as an effective strategy in mono or combined treatment of cancer. Small-molecule compounds targeting FEN1 have also been developed and detected in cancer regression. In this review, we summarize the recent development of small-molecule inhibitors targeting FEN1 in recent years, thereby expanding their therapeutic potential and application.

Prediction of Immune Infiltration Diagnostic Gene Biomarkers in Kawasaki Disease

Kawasaki disease (KD) is characterized by disorder of immune response with unknown etiology. Immune cells may be closely related to the onset of KD. The focus of this research was to evaluate the significance of the infiltration of immune cells for this disease and find possible diagnostic biomarkers for KD. The Gene Expression Omnibus database was utilized to retrieve two freely accessible gene expression patterns (GSE68004 and GSE18606 datasets) from human KD and control specimens. 114 KD, as well as 46 control specimens, were searched for obtaining differentially expressed genes (DEGs). Candidate biological markers were determined utilizing the support vector machine recursive feature elimination and the least absolute shrinkage and selection operator regression model analysis. To assess discriminating capacity, the area under the receiver operating characteristic curve (AUC) was computed. The GSE73461 dataset was utilized to observe the biomarkers' expression levels and diagnostic significance in KD (78 KD patients and 55 controls). CIBERSORT was employed to assess the composition profiles of the 22 subtypes of immune cell fraction in KD on the basis of combined cohorts. 37 genes were discovered. The DEGs identified were predominantly involved in arteriosclerotic cardiovascular disease, atherosclerosis, autoimmune disease of the urogenital tract, and bacterial infectious disease. Gene sets related to complement and coagulation cascades, Toll-like receptor signaling pathway, Fc gamma R-mediated phagocytosis, NOD-like receptor signaling pathway, and regulation of actin cytoskeleton underwent differential activation in KD as opposed to the controls. KD diagnostic biomarkers, including the alkaline phosphatase (ALPL), endoplasmic reticulum degradation-enhancing alpha-mannosidase-like protein 2 (EDEM2), and histone cluster 2 (HIST2H2BE), were discovered (AUC = 1.000) and verified utilizing the GSE73461 dataset (AUC = 1.000). Analyses of immune cell infiltration demonstrated that ALPL, EDEM2, and HIST2H2BE were linked to CD4 memory resting T cells, monocytes, M0 macrophages, CD8 T cells, neutrophils, and memory CD4 T cells. ALPL, EDEM2, and HIST2H2BE could be utilized as KD diagnostic indicators, and they can also deliver useful information for future research on the disease's incidence and molecular processes.

A highly sensitive homogeneous electrochemiluminescence biosensor for flap endonuclease 1 based on branched hybridization chain reaction amplification and ultrafiltration separation

A sensitive homogeneous electrochemiluminescence (ECL) biosensor for flap endonuclease 1 (FEN1) detection was developed by combining highly sensitive ECL detection, high efficiency of branched hybridization chain reaction (BHCR) amplification, a convenient homogeneous strategy, and simple ultrafiltration separation. Magnetic beads were first modified with well-designed double flap DNAs containing 5'-flaps. In the presence of FEN1, the 5'-flap can be cleaved, and a large amount of single-stranded DNA can be produced, which can be separated easily from the double-flap DNA-modified beads by a magnet. Then, the cleaved 5'-flap can be used to initiate BHCR amplification to produce a large amount of long-strand dsDNA. Ru(phen)₃²⁺ can insert dsDNA to form Ru-dsDNAs, which can be easily separated from the main solution through ultrafiltration. The ECL signal from the separated Ru-dsDNAs has a good linear relationship with the logarithm of the FEN1 concentration ranging from 6.5 × 10^-2 ∼ 6.5 × 10³ U/L with a detection limit of 2.2 × 10^-2 U/L. The proposed biosensor was used to evaluate FEN1 activity in real samples with satisfactory results.

Machine-Learning Algorithm-Based Prediction of Diagnostic Gene Biomarkers Related to Immune Infiltration in Patients With Chronic Obstructive Pulmonary Disease

Objective

This study aims to identify clinically relevant diagnostic biomarkers in chronic obstructive pulmonary disease (COPD) while exploring how immune cell infiltration contributes towards COPD pathogenesis.

Methods

The GEO database provided two human COPD gene expression datasets (GSE38974 and GSE76925; n=134) along with the relevant controls (n=49) for differentially expressed gene (DEG) analyses. Candidate biomarkers were identified using the support vector machine recursive feature elimination (SVM-RFE) analysis and the LASSO regression model. The discriminatory ability was determined using the area under the receiver operating characteristic curve (AUC) values. These candidate biomarkers were characterized in the GSE106986 dataset (14 COPD patients and 5 controls) in terms of their respective diagnostic values and expression levels. The CIBERSORT program was used to estimate patterns of tissue infiltration of 22 types of immune cells. Furthermore, the in vivo and in vitro model of COPD was established using cigarette smoke extract (CSE) to validated the bioinformatics results.

Results

80 genes were identified via DEG analysis that were primarily involved in cellular amino acid and metabolic processes, regulation of telomerase activity and phagocytosis, antigen processing and MHC class I-mediated peptide antigen presentation, and other biological processes. LASSO and SVM-RFE were used to further characterize the candidate diagnostic markers for COPD, SLC27A3, and STAU1. SLC27A3 and STAU1 were found to be diagnostic markers of COPD in the metadata cohort (AUC=0.734, AUC=0.745). Their relevance in COPD were validated in the GSE106986 dataset (AUC=0.900 AUC=0.971). Subsequent analysis of immune cell infiltration discovered an association between SLC27A3 and STAU1 with resting NK cells, plasma cells, eosinophils, activated mast cells, memory B cells, CD8+, CD4+, and helper follicular T-cells. The expressions of SLC27A3 and STAU1 were upregulated in COPD models both in vivo and in vitro. Immune infiltration activation was observed in COPD models, accompanied by the enhanced expression of SLC27A3 and STAU1. Whereas, the knockdown of SLC27A3 or STAU1 attenuated the effect of CSE on BEAS-2B cells.

Conclusion

STUA1 and SLC27A3 are valuable diagnostic biomarkers of COPD. COPD pathogenesis is heavily influenced by patterns of immune cell infiltration. This study provides a molecular biology insight into COPD occurrence and in exploring new therapeutic means useful in COPD.

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

Background

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

Methods

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

Results

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

Conclusion

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

Integrative analysis of key candidate genes and signaling pathways in ovarian cancer by bioinformatics

Background

Ovarian cancer is one of the most common gynecological tumors, and among gynecological tumors, its incidence and mortality rates are fairly high. However, the pathogenesis of ovarian cancer is not clear. The present study aimed to investigate the differentially expressed genes and signaling pathways associated with ovarian cancer by bioinformatics analysis.

Methods

The data from three mRNA expression profiling microarrays (GSE14407, GSE29450, and GSE54388) were obtained from the Gene Expression Omnibus (GEO) database. Differentially expressed genes between ovarian cancer tissues and normal tissues were identified using R software. The overlapping genes from the three GEO datasets were identified, and profound analysis was performed. The overlapping genes were used for pathway and Gene Ontology (GO) functional enrichment analysis using the Metascape online tool. Protein–protein interactions were analyzed with the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING). Subnetwork models were selected using the plugin molecular complex detection (MCODE) application in Cytoscape. Kaplan–Meier curves were used to analyze the univariate survival outcomes of the hub genes. The Human Protein Atlas (HPA) database and Gene Expression Profiling Interactive Analysis (GEPIA) were used to validate hub genes.

Results

In total, 708 overlapping genes were identified through analyses of the three microarray datasets (GSE14407, GSE29450, and GSE54388). These genes mainly participated in mitotic sister chromatid segregation, regulation of chromosome segregation and regulation of the cell cycle process. High CCNA2 expression was associated with poor overall survival (OS) and tumor stage. The expression of CDK1, CDC20, CCNB1, BUB1B, CCNA2, KIF11, CDCA8, KIF2C, NDC80 and TOP2A was increased in ovarian cancer tissues compared with normal tissues according to the Oncomine database. Higher expression levels of these seven candidate genes in ovarian cancer tissues compared with normal tissues were observed by GEPIA. The protein expression levels of CCNA2, CCNB1, CDC20, CDCA8, CDK1, KIF11 and TOP2A were high in ovarian cancer tissues, which was further confirmed via the HPA database.

Conclusion

Taken together, our study provided evidence concerning the altered expression of genes in ovarian cancer tissues compared with normal tissues. In vivo and in vitro experiments are required to verify the results of the present study.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13048-021-00837-6.

Identification of Flap Endonuclease 1 With Diagnostic and Prognostic Value in Breast Cancer

Objective

This study aims to identify the potential value of flap endonuclease 1 (FEN1) as a diagnostic and prognostic marker for breast cancer (BC).

Methods

ELISA was used to measure serum FEN1 levels and ECLIA for CA153 and CEA levels. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic value. Oncomine and UALCAN databases were used to analyze the differences in FEN1 mRNA and protein expressions. Kaplan-Meier Plotter database was then used to assess the prognostic value.

Results

Bioinformatics analysis showed that the FEN1 mRNA and protein levels were significantly higher in BC tissues than in normal tissues. FEN1 was detected in culture medium of BC cell lines and serum FEN1 concentrations were significantly increased in BC patients than in cancer-free individuals. Besides, FEN1 exhibited higher diagnostic accuracy (AUC values>0.800) than CA153 and CEA for distinguishing BC patients, especially early BC, from the healthy and benign groups, or individually. Additionally, serum FEN1 levels were significantly associated with the stage (P=0.001) and lymph invasion (P=0.016), and serum FEN1 levels were increased with the development of BC. Furthermore, serum FEN1 levels were significantly decreased in post-operative patients than in pre-operative patients (P=0.016). Based on the Kaplan-Meier Plotter database, the survival analysis indicated that FEN1 overexpression was associated with poor prognoses for overall survival (OS), relapse-free survival (RFS), and distant metastasis-free survival (DMFS) in BC patients.

Conclusion

FEN1 might be a novel diagnostic and prognostic marker for BC.

Dual-Mode FEN1 Activity Detection Based on Nt.BstNBI-Induced Tandem Signal Amplification

Flap endonuclease 1 (FEN1) is a structure-specific nuclease that cleaves the 5' single-stranded protrusion (also known as 5' flap) during Okazaki fragment processing. It is overexpressed in various types of human cancer cells and has been considered as an important biomarker for cancer diagnosis. However, conventional methods for FEN1 assay usually suffer from complicated platform and laborious procedures with a limited sensitivity. Here, we developed a dual-signal method for sensitive detection of FEN1 on the basis of duplex-specific nuclease actuated cyclic enzymatic repairing-mediated signal amplification. Once the 5' flap of the double-flap DNA substrate was cleaved by target FEN1, the cleaved 5' flap initiated strand-displacement amplification to produce plenty of G-rich DNA (G) sequences. These G sequences that self-assembled into G-quadruplexes in the presence of hemin revealed horseradish-peroxidase-like catalytic activities as well as fluorescence enhancement of thioflavin T. The UV-vis signal showed a good linear relationship with the logarithm of FEN1 activity ranging from 0.03 to 1.5 U with a detection limit of 0.01 U. The fluorescence signal correlated linearly with the logarithm of FEN1 activity ranging from 0.001 to 1.5 U with a detection limit of 0.75 mU. In addition, FEN1 can be visualized not only by colorimetry but also by fluorescence (under ice-water mixture conditions). This reliable, accurate, and convenient method would be a potential powerful tool in point-of-care testing applications and therapeutic response assessment.

Predicting Diagnostic Gene Biomarkers Associated With Immune Infiltration in Patients With Acute Myocardial Infarction

Objective: The present study was designed to identify potential diagnostic markers for acute myocardial infarction (AMI) and determine the significance of immune cell infiltration in this pathology.

Methods: Two publicly available gene expression profiles (GSE66360 and GSE48060 datasets) from human AMI and control samples were downloaded from the GEO database. Differentially expressed genes (DEGs) were screened between 80 AMI and 71 control samples. The LASSO regression model and support vector machine recursive feature elimination (SVM-RFE) analysis were performed to identify candidate biomarkers. The area under the receiver operating characteristic curve (AUC) value was obtained and used to evaluate discriminatory ability. The expression level and diagnostic value of the biomarkers in AMI were further validated in the GSE60993 dataset (17 AMI patients and 7 controls). The compositional patterns of the 22 types of immune cell fraction in AMI were estimated based on the merged cohorts using CIBERSORT.

Results: A total of 27 genes were identified. The identified DEGs were mainly involved in carbohydrate binding, Kawasaki disease, atherosclerosis, and arteriosclerotic cardiovascular disease. Gene sets related to atherosclerosis signaling, primary immunodeficiency, IL-17, and TNF signaling pathways were differentially activated in AMI compared with the control. IL1R2, IRAK3, and THBD were identified as diagnostic markers of AMI (AUC = 0.877) and validated in the GSE60993 dataset (AUC = 0.941). Immune cell infiltration analysis revealed that IL1R2, IRAK3, and THBD were correlated with M2 macrophages, neutrophils, monocytes, CD4⁺ resting memory T cells, activated natural killer (NK) cells, and gamma delta T cells.

Conclusion: IL1R2, IRAK3, and THBD can be used as diagnostic markers of AMI, and can provide new insights for future studies on the occurrence and the molecular mechanisms of AMI.