Startseite Identification of key enzalutamide-resistance-related genes in castration-resistant prostate cancer and verification of RAD51 functions
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Identification of key enzalutamide-resistance-related genes in castration-resistant prostate cancer and verification of RAD51 functions

  • Wen Xu , Li Liu , Zhongqi Cui , Mingyang Li , Jinliang Ni , Nan Huang , Yue Zhang , Jie Luo , Limei Sun und Fenyong Sun EMAIL logo
Veröffentlicht/Copyright: 26. Mai 2023
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Open Medicine
Aus der Zeitschrift Open Medicine Band 18 Heft 1

Abstract

Patients with castration-resistant prostate cancer (CRPC) often develop drug resistance after treatment with enzalutamide. The goal of our study was to identify the key genes related to enzalutamide resistance in CRPC and to provide new gene targets for future research on improving the efficacy of enzalutamide. Differential expression genes (DEGs) associated with enzalutamide were obtained from the GSE151083 and GSE150807 datasets. We used R software, the DAVID database, protein–protein interaction networks, the Cytoscape program, and Gene Set Cancer Analysis for data analysis. The effect of RAD51 knockdown on prostate cancer (PCa) cell lines was demonstrated using Cell Counting Kit-8, clone formation, and transwell migration experiments. Six hub genes with prognostic values were screened (RAD51, BLM, DTL, RFC2, APOE, and EXO1), which were significantly associated with immune cell infiltration in PCa. High RAD51, BLM, EXO1, and RFC2 expression was associated with androgen receptor signaling pathway activation. Except for APOE, high expression of hub genes showed a significant negative correlation with the IC50 of Navitoclax and NPK76-II-72-1. RAD51 knockdown inhibited the proliferation and migration of PC3 and DU145 cell lines and promoted apoptosis. Additionally, 22Rv1 cell proliferation was more significantly inhibited with RAD51 knockdown than without RAD51 knockdown under enzalutamide treatment. Overall, six key genes associated with enzalutamide resistance were screened (RAD51, BLM, DTL, RFC2, APOE, and EXO1), which are potential therapeutic targets for enzalutamide-resistant PCa in the future.

Keywords: castration-resistant prostate cancer; prostate cancer; enzalutamide; RAD51

1 Introduction

According to Global Cancer Statistics 2020, prostate cancer (PCa) is a common cancer type that causes death worldwide in men. Approximately 1.4 million people are diagnosed with PCa worldwide, resulting in 375,000 deaths annually, which is an upward trend compared to 2018 [1,2]. The androgen receptor (AR) signaling pathway is involved in the entire process of PCa progression, including transformation and metastasis [3]. Therefore, androgen-deprivation therapy (ADT) constitutes the first-line therapy for PCa [4]. However, there are limitations to ADT therapy, and almost all patients treated with this method inevitably end up with castration-resistant prostate cancer (CRPC) [5,6].

Enzalutamide is an FDA-approved targeted drug for treating CRPC [7]. Enzalutamide is a small molecule oral agent that functions as an AR signaling inhibitor by negatively affecting AR nuclear translocation, thereby inhibiting the transcription of related drivers located downstream of the AR cascade. This results in the induction of apoptosis and suppression of CRPC cell proliferation [8,9]. Many studies demonstrate the positive effects of enzalutamide in CRPC patients, such as significantly prolonging survival after chemotherapy [10]. However, insensitivity to enzalutamide is found in almost half of the patients [11]. In addition, although some patients do better on initial treatment with enzalutamide, acquired resistance occurring after 11.2 months is common [12]. Given that the underlying mechanisms of enzalutamide resistance remain largely unclear, there is an urgent need to explore the causes of resistance to improve further therapeutic efficacy in CRPC.

Enzalutamide resistance in CRPC is a complex process that is usually associated with abnormal expression of certain genes, which play an important role in the development of enzalutamide resistance [13]. Researchers have actively explored genes associated with enzalutamide resistance. For example, AR-V7 is the most common variant detected in circulating tumor cells of patients with CRPC, which is significantly increased after enzalutamide treatment, and the splicing factors hnRNPA1 and Malat1 have been identified to mediate enzalutamide resistance by promoting the production and expression of AR-V7 [14]. Furthermore, galectin-3, a member of the animal lectin family, significantly inhibited the therapeutic effect of enzalutamide by increasing the expression of KLK3 and TMPRSS2 [15]. Although we have identified several genes associated with enzalutamide resistance, many unknown genes are likely to remain unidentified. Therefore, exploring aberrant genes associated with enzalutamide resistance will help discover biomarkers of resistance susceptibility and develop advanced therapeutic targets to provide more treatment options for patients with CRPC.

With the generation and application of high-throughput sequencing technologies, many important genes and signaling pathways involved in the cancer process have been massively mined and stored in public databases. Researchers can access and download the needed genomic data from international public knowledge databases such as Gene Expression Omnibus (GEO) and TCGA for free [16]. In the present study, we obtained data on enzalutamide-resistant and -sensitive cell lines from the GEO database and identified key genes involved in enzalutamide resistance through bioinformatics analysis. These results may provide new directions and new therapeutic targets for advancing research on CRPC resistance to enzalutamide.

2 Materials and methods

2.1 Date acquisition

Considering that the acquisition of drug resistance in enzalutamide-sensitive PCa cells is a slow process, we used cells cultured long term in enzalutamide (≥6 months) as a screening criterion to select the data we needed. We downloaded the high-throughput sequencing data of two different PCa cell lines treated with enzalutamide from the GEO database (GSE151083 and GSE150807 datasets; https://www.ncbi.nlm.nih.gov/geo/). GSE150807 contains data on enzalutamide-sensitive and -resistant LNCaP cell lines, while GSE151083 contains data on enzalutamide-sensitive and -resistant C42B cell lines. We also downloaded data related to prostate adenocarcinoma from TCGA database, which included 501 PCa and 52 normal samples. In addition, GSE32269, containing 22 primary PCa (hormone-dependent) and 29 metastatic CRPC tissues, was used for follow-up validation.

2.2 Analysis of differential expression genes (DEGs) associated with enzalutamide resistance

The “limma package” was used to analyze the DEGs in the GSE150807 and GSE151083 datasets. All DEGs between the enzalutamide-resistant and enzalutamide-sensitive cells were identified and visualized. To screen DEGs, |log2FoldChange| > 1 and adjusted P-value <0.05 were used as thresholds. The results were visualized in volcano and heat map plots, with the heat map showing only the top 20 highest and lowest expressed genes. Screened DEGs from the GSE151083 and GSE150807 datasets were intersected in a Venn diagram using Venny 2.1 (https://bioinfogp.cnb.csic.es/tools/venny/index.html), and overlapping DEGs common to both datasets were considered significantly associated with enzalutamide resistance.

2.3 Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses

To explore the potential biological functions of the DEGs associated with enzalutamide resistance, GO and KEGG analyses of the DEGs were investigated through the DAVID online website. The downloaded results were further analyzed using an online web tool (https://www.bioinformatics.com.cn). P-values <0.05 were considered statistically significant.

2.4 Construction of protein–protein interaction (PPI) network and identification of candidate hub genes

The PPI network for DEGs associated with enzalutamide resistance was built using STRING (STRING version 11.5). Interactions with a score >0.7 were considered statistically significant. The PPI network was visualized using Cytoscape software (v3.9.1), and the hub genes were determined using the plugin cytohubba in Cytoscape. The top 20 genes in the network, ranked using the maximal clique centrality (MCC) method, were treated as candidate hub genes.

2.5 Survival analysis and expression validation to identify hub genes

Gene Expression Profiling Interactive Analysis (GEPIA; http://gepia.cancer-pku.cn/), a versatile online analysis site based on TCGA and Genotype-Tissue Expression (GTEx) databases, was used to validate the correlation between the disease-free survival (DFS) and expression levels of the 20 candidate hub genes. Fragments per kilobase of exon per million mapped fragment (FPKM) data associated with PCa from TCGA database were downloaded, and we analyzed the expression differences of the 20 candidate hub genes between 501 PCa tissues and 52 normal tissues using the Wilcoxon test method. Finally, we visualized the results using the beeswarm package in R software. Through the above analysis, the candidate hub genes with clinical prognostic value were identified as hub genes. P-values < 0.05 were considered statistically significant.

2.6 Clinical parameter analysis of hub genes

The N- and T-stage-related information of the samples were extracted from the data related to PCa downloaded from TCGA, and the correlation between the expression levels of the hub genes and the N- and T-stage was investigated using the Wilcoxon test and Kruskal–Wallis test. P-values < 0.05 were considered statistically significant.

2.7 Analysis of the relationship between hub genes and enzalutamide

With enzalutamide being an AR signaling inhibitor, we evaluated the potential relationship between hub gene expression and the AR signaling pathway via Gene Set Cancer Analysis (GSCA; http://bioinfo.life.hust.edu.cn/GSCA/#/), a versatile platform for data analysis. Moreover, we analyzed the expression differences of the six hub genes between primary PCa and metastatic CRPC (mCRPC) tissue samples using Wilcoxon test based on the GSE32269 dataset. P-value < 0.05 was considered statistically significant.

2.8 Exploration of the potential relationship between hub genes and immune cell infiltration

The immune infiltration and mRNA expression module in GSCA was used to estimate the association between the expression levels of the hub genes and the infiltration levels of macrophages, monocytes, and natural killer (NK) cells. FDR < 0.05 was considered statistically significant.

2.9 Drug sensitivity evaluation

We determined the correlation between the expression of hub genes and drug IC50 via Pearson correlation analysis based on the Genomics of Drug Sensitivity in Cancer (GDSC) database through the drug sensitivity module in GSCA. This is done to identify potential molecular compounds for targeted therapies. FDR < 0.05 was considered statistically significant.

2.10 Cell line and culture

PCa cell lines PC3, DU145, and 22Rv1 were purchased from the American Type Culture Collection (ATCC). They were cultured in RPMI-1640 medium (Gibco, USA) containing 10% Fetal Bovine Serum (Ausbian, Cat. No. WS500T) and 1% penicillin/streptomycin (Gibco, USA) and maintained at 37°C in a 5% CO2 environment.

2.11 Transient transfection of cells

For transient transfection, 5 × 104 cells/mL of PC3, DU145, and 22Rv1 cells were added to 6-well plates the day before transfection and cultured overnight. The next day, at about 30–40% confluence, the cells were transfected with Lipofectamine 2000 (Invitrogen, Carlsbad, CA, USA) and small interfering RNA (siRNA) and then further incubated for 48 h. The siRNAs targeting RAD51 are shown in Table 1.

Table 1

Sequences of the two siRNAs

siRNA siRNA sequence information
siRNA#1 5′-AAGCTATGTTCGCCATTAATT-3′
siRNA#2 5′-CGCCCTTTACAGAACAGACTA-3′

2.12 RNA extraction and quantitative reverse transcription-polymerase chain reaction (qRT-PCR)

The collected PC3, DU145, and 22Rv1 cell pellets were treated with TRIzol reagent (Invitrogen, Thermo Scientific, Shanghai, China) for total RNA extraction. The general process was as follows: cells were treated with TRIzol reagent for 10 min, centrifuged at 12,000 rpm for 15 min at 4°C, and then the upper aqueous phase was extracted and mixed with isopropyl alcohol for 10 min, and centrifuged for another 10 min under the same conditions. The supernatant was removed, the residual liquid was washed with absolute ethanol, and then centrifuged at 7,500 rpm for 5 min to remove the supernatant to obtain the RNA precipitate. Finally, the RNA precipitate was dissolved in RNase-free water, and RNA was quantified using Nano drop 300 (ALLSHENG). Total RNA was subsequently reverse transcribed to obtain cDNA using a reverse transcription kit (TaKaRa Bio, Shiga, Japan). Finally, the relative expression of RAD51 was detected via qRT-PCR in a TK-6000 PCR system using a SYBR Green kit (TaKaRa Bio, Shiga, Japan). GAPDH expression was used for normalization of gene expression. Primers for qRT-PCR are listed in Table 2.

Table 2

qRT-PCR primer pairs

Name Primer sequence information
RAD51-F 5′-CAACCCATTTCACGGTTAGAGC-3′
RAD51-R 5′-TTCTTTGGCGCATAGGCAACA-3′
GAPDH-F 5′-GGAGCGAGATCCCTCCAAAAT-3′
GAPDH-R 5′-GGCTGTTGTCATACTTCTCATGG-3′

2.13 Western blotting detection

PC3, DU145, and 22Rv1 cells were lysed with RIPA buffer containing protease and phosphatase inhibitors to isolate proteins. Following separation via a 10% sodium dodecyl-sulfate polyacrylamide gel electrophoresis, the protein samples (30 µg) were transferred to nitrocellulose membranes. The membranes were blocked with 5% non-fat powdered milk and incubated with rabbit antibody against RAD51 (Proteintech, Cat#: 14961-1-AP) and mouse antibody against Actin (Abmart, Cat#: M20011) for 1 h at 37°C, followed by washing of the membranes. The fluorescently conjugated secondary antibodies (Licor, USA) were incubated with the membrane for 1 h at room temperature. Protein signals were detected by a two-color infrared laser imaging system (Odyssey CLx). Actin protein expression was used as an internal control.

2.14 Cell counting kit (CCK)-8 and colony formation assays

PC3 and DU145 cells were treated with siRNA for 48 h, and the cell proliferation ability was determined using the CCK-8 kit (Share-bio, SB-CCK8). The colony formation ability of PCa cells was determined by colony formation assay [17].

2.15 Apoptosis assay

Transiently transfected PC3 and DU145 cells were collected in 1.5 mL EP tubes, and 50 μL of diluted fluorescein isothiocyanate (FITC) was added to each tube. After 20 min, 250 μL of propidium iodide was added for 5 min according to the instructions of the FITC Annexin V apoptosis Detection Kit (BD Biosciences, San Diego, CA). Finally, the samples were analyzed using the BD LSRFortessa analyzer (BD Biosciences).

2.16 Cell migration assay

The transwell migration assay was set up in 24-well plates containing 500 μL of medium containing 10% FBS. The transwell units were placed in the wells, and 400 μL of serum-free medium containing 5 × 104 transiently transfected PC3 and DU145 cells was added to the corresponding upper chamber. The cells were incubated in a 5% CO2 incubator at 37°C for 24 h. Uninvaded cells on the membrane surface were gently removed using a wet swab, and the remaining cells were fixed with 4% paraformaldehyde for 15 min at room temperature before staining with 0.1% crystalline violet. Once the transwell units were dry, we examined them using an inverted microscope (Nikon). The invading cells were quantified using ImageJ software.

2.17 Drug treatments

RPMI-1640 medium containing 10% FBS and 1% penicillin/streptomycin was used to prepare 0, 5, 10, 20, 40, and 80 μM working concentrations of enzalutamide (Beyotime, Cat#: SC0074-10mM). The 22Rv1 cells siRNA-treated for 48 h were seeded at 1 × 104 cells/well in 96-well plates. After 24 h, the medium in the wells was removed and 200 μL of enzalutamide medium was added to the wells according to the principle of five replicate wells for each concentration. Cell viability was determined by CCK-8 kit after 48 h treatment.

2.18 Statistical analysis

Statistical analysis of the data was performed using R software. Comparisons of two independent samples were analyzed using Wilcoxon test, and comparisons of multiple independent samples were analyzed using the Kruskal–Wallis test or ANOVA. P-value <0.05 was considered statistically significant. The relationships between gene expression and signaling pathway activity, drug sensitivity, and immune infiltration were automatically generated by an online website, and FDR < 0.05 was considered statistically significant.

Figure 1 The design flow chart of this study. DEGs, differentially expressed genes; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; PPI, protein–protein interaction; DFS, disease-free survival.
Figure 1

The design flow chart of this study. DEGs, differentially expressed genes; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; PPI, protein–protein interaction; DFS, disease-free survival.

3 Results

3.1 Identification of DEGs associated with enzalutamide resistance

Two GEO datasets were used to identify DEGs associated with enzalutamide resistance. After analysis, 4,366 and 2,825 differential genes were identified in GSE150807 and GSE151083, respectively (Figure 1). Volcano and heat maps were used to visualize these DEGs (Figure 2a–d), with the heat map showing only the top 20 highest and lowest expressed genes with the largest differential expression multiplicity. The Venn diagram shows 1,208 overlapping DEGs associated with enzalutamide resistance found in both datasets (Figure 2e).

Figure 2 DEGs in enzalutamide-resistant and enzalutamide-sensitive PCa cell lines. (a and b) The heat map shows the top 20 DEGs in the GSE151083 and GSE150807 datasets with enzalutamide-resistant and enzalutamide-sensitive cell lines. (c and d) Volcano plot showing all DEGs in the GSE151083 and GSE150807 datasets with enzalutamide- resistant and enzalutamide-sensitive cell lines. (e) Venn diagram showing the overlapping DEGs in GSE151083 and GSE150807. DEGs, differentially expressed genes; PCa, prostate cancer.
Figure 2

DEGs in enzalutamide-resistant and enzalutamide-sensitive PCa cell lines. (a and b) The heat map shows the top 20 DEGs in the GSE151083 and GSE150807 datasets with enzalutamide-resistant and enzalutamide-sensitive cell lines. (c and d) Volcano plot showing all DEGs in the GSE151083 and GSE150807 datasets with enzalutamide- resistant and enzalutamide-sensitive cell lines. (e) Venn diagram showing the overlapping DEGs in GSE151083 and GSE150807. DEGs, differentially expressed genes; PCa, prostate cancer.

3.2 GO and KEGG pathway analyses

To further explore the potential functions of DEGs, we performed GO and KEGG analysis. As shown in Figure 3, biological process analysis showed that DEGs were mainly enriched in signal transduction, positive regulation of gene expression, and drug response. Cellular component analysis showed that the nucleus, cytosol, cytoplasm, and plasma membrane were the most common classifications. For the molecular function, protein binding was significantly enriched. In addition, KEGG pathway analysis showed that these genes were involved in metabolic pathways and cancer-related pathways.

Figure 3 GO and KEGG analysis of DEGs. (a–d) Bubble plots showing the results of functional annotation analysis of 1,208 overlapping DEGs. (a) Biological process. (b) Cell component. (c) Molecular function. (d) KEGG pathways. GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; DEGs, differentially expressed genes.
Figure 3

GO and KEGG analysis of DEGs. (a–d) Bubble plots showing the results of functional annotation analysis of 1,208 overlapping DEGs. (a) Biological process. (b) Cell component. (c) Molecular function. (d) KEGG pathways. GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes; DEGs, differentially expressed genes.

3.3 Construction of PPI network and identification of candidate hub genes

We uploaded 1,208 overlapping DEGs to the STRING database and the analyzed data were downloaded. The PPI network was then imported into Cytoscope and the top 20 genes with the highest degree of connectivity were derived by the MCC algorithm using the plugin cytohubba (Figure 4). These 20 genes – RAD51, PCNA, POLE, EXO1, MSH2, BLM, LIG1, RFC2, MCM6, BRCA1, GEN1, MCM7, CDK2, DTL, POLD4, RPS27A, PKM, LDHA, APP, and Apolipoprotein E (APOE) – were identified as candidate hub genes.

Figure 4 The PPI network shows the top 20 genes with the highest degree of connectivity calculated by the MCC algorithm in cytohubba from 1,208 overlapping genes. PPI, protein–protein interaction network; MCC, maximal clique centrality.
Figure 4

The PPI network shows the top 20 genes with the highest degree of connectivity calculated by the MCC algorithm in cytohubba from 1,208 overlapping genes. PPI, protein–protein interaction network; MCC, maximal clique centrality.

3.4 Identification of hub genes through expression and survival analyses of candidate genes

To screen for hub genes with clinical application, we explored the differences in expression of candidate hub genes in PCa and normal tissues, including DFS. We identified six genes, including RAD51, BLM, APOE, DTL, RFC2, and EXO1, with high expression associated with poorer DFS (Figure 5). These six genes with prognostic value were defined as hub genes.

Figure 5 Validation of the expression and DFS of top 6 genes. (a) RAD51. (b) BLM. (c) APOE. (d) DTL. (e) RFC2. (f) EXO1. The significance of differences between the two groups was determined using the Wilcoxon test. DFS, disease-free survival.
Figure 5

Validation of the expression and DFS of top 6 genes. (a) RAD51. (b) BLM. (c) APOE. (d) DTL. (e) RFC2. (f) EXO1. The significance of differences between the two groups was determined using the Wilcoxon test. DFS, disease-free survival.

3.5 Clinical parameter analysis of hub genes

In order to explore whether the hub genes had clinical value, we focused on the relationship between their expression level and N- and T-stages. Our results showed that the expression levels of these six hub genes increased with the increase in N- and T-stages of PCa (P < 0.05; Figure 6).

Figure 6 Validation of the correlation between the expression levels of hub genes and N-stage and T-stage. (a) RAD51. (b) BLM. (c) APOE. (d) DTL. (e) RFC2. (f) EXO1. The significance of differences between the two groups was determined using the Wilcoxon test, and Kruskal–Wallis test was used to compare multiple groups.
Figure 6

Validation of the correlation between the expression levels of hub genes and N-stage and T-stage. (a) RAD51. (b) BLM. (c) APOE. (d) DTL. (e) RFC2. (f) EXO1. The significance of differences between the two groups was determined using the Wilcoxon test, and Kruskal–Wallis test was used to compare multiple groups.

3.6 Validation of the relationship between hub genes and enzalutamide

Since enzalutamide exerts its inhibitory effect on CRPC mainly through inhibition of AR signaling, we investigated the potential role of hub gene expression levels on the AR signaling pathway’s activity. RAD51, BLM, EXO1, and RFC2 (Figure 7a) activated the AR signaling pathway (FDR < 0.05), and their expression level correlated with AR pathway activity, while DTL and APOE had no significant effect on AR pathway activity (Figure 7b–g). Differential expression analysis on the dataset GSE32269 containing primary PCa and mCRPC tissue samples showed that the expression levels of RAD51, BLM, DTL, and APOE were significantly upregulated in mCRPC compared to those in primary PCa tissues (FDR < 0.05), while the expression of EXO1 and RFC2 were not significantly different (Figure 7h–m).

Figure 7 Validation of the relationship between the expression levels of hub genes and the AR signaling pathway. (a) The potential role of hub genes on signaling pathways in PCa is summarized in the figure. The red module indicates that expression of the gene has an activating effect on the signaling pathway, while the blue module indicates an inhibitory effect. (b–g) Relationship between higher and lower expression groups of hub genes and AR signaling pathway activity score. (b) RAD51. (c) BLM. (d) APOE. (e) DTL. (f) RFC2. (g) EXO1. (h–m) Validation of hub genes expression differences in localized Pca (22) and mCRPC (29) based on the GSE32269 dataset. (h) RAD51. (i) BLM. (j) APOE. (k) DTL. (l) RFC2. (m) EXO1. The significance of differences between the two groups was determined using the Wilcoxon test. AR signaling pathway, androgen receptor signaling pathway; PCa, prostate cancer; mCRPC, metastatic CRPC.
Figure 7

Validation of the relationship between the expression levels of hub genes and the AR signaling pathway. (a) The potential role of hub genes on signaling pathways in PCa is summarized in the figure. The red module indicates that expression of the gene has an activating effect on the signaling pathway, while the blue module indicates an inhibitory effect. (b–g) Relationship between higher and lower expression groups of hub genes and AR signaling pathway activity score. (b) RAD51. (c) BLM. (d) APOE. (e) DTL. (f) RFC2. (g) EXO1. (h–m) Validation of hub genes expression differences in localized Pca (22) and mCRPC (29) based on the GSE32269 dataset. (h) RAD51. (i) BLM. (j) APOE. (k) DTL. (l) RFC2. (m) EXO1. The significance of differences between the two groups was determined using the Wilcoxon test. AR signaling pathway, androgen receptor signaling pathway; PCa, prostate cancer; mCRPC, metastatic CRPC.

3.7 Validation of the relationship between hub genes and immune infiltration

We performed a literature review to investigate if these hub genes mediate CRPC resistance to enzalutamide by affecting the infiltration level of immune cells and found that NK cells, monocytes, and macrophages are associated with enzalutamide resistance [18,19]. In view of this, we analyzed the relationship between the expression of hub genes in PCa and the infiltration levels of NK cells, monocytes, and macrophages. As shown in Figure 8, the expression of RAD51, BLM, DTL, and EXO1 showed a significant positive correlation with the infiltration levels of monocytes and macrophages, while the expression of RFC2 and APOE only showed a significant positive correlation with the infiltration level of macrophages but not monocytes. In addition, the infiltration level of NK cells showed a significant negative correlation with the expression of BLM, DTL, and EXO1, but not with that of RAD51, and a positive correlation with RFC2 and APOE expression.

Figure 8 Spearman correlation of hub genes expression in PCa with macrophage, monocyte, and NK cell infiltration. (a) RAD51. (b) BLM. (c) APOE. (d) DTL. (e) RFC2. (f) EXO1. NK, natural killer.
Figure 8

Spearman correlation of hub genes expression in PCa with macrophage, monocyte, and NK cell infiltration. (a) RAD51. (b) BLM. (c) APOE. (d) DTL. (e) RFC2. (f) EXO1. NK, natural killer.

3.8 Relationship between hub gene expression and drug sensitivity

Based on the data provided by the GDSC database, we analyzed the relationship between the expression levels of hub genes and tumor drug sensitivity (IC50) through the GSCA online data analysis website. A gene’s expression being positively correlated with drug sensitivity indicates drug resistance, and vice versa. The high expression of hub genes, except that of APOE, showed a significant negative correlation with the IC50 of Navitoclax and NPK76−II−72−1, while APOE expression showed a significant correlation with the IC50 of SB590885, Dabrafenib, and PLX4720 (Figure 9).

Figure 9 Correlation between GDSC drug (top 30) sensitivity and hub genes expression. The negative correlation indicates that high expression of the gene is sensitive to the drug, and vice versa. GDSC, Genomics of Drug Sensitivity in Cancer.
Figure 9

Correlation between GDSC drug (top 30) sensitivity and hub genes expression. The negative correlation indicates that high expression of the gene is sensitive to the drug, and vice versa. GDSC, Genomics of Drug Sensitivity in Cancer.

3.9 Knockdown of RAD51 inhibits the proliferation and migration of PCa cells and promotes apoptosis

To explore the role of RAD51 in PCa, we knocked down RAD51 in PC3, DU145, and 22Rv1 cell lines (Figures 10a and 11a). The CCK-8 and clone formation assays demonstrated that the knockdown of RAD51 inhibited the proliferative capacity of both PCa cell lines (Figure 10b and c). Moreover, transwell assays showed that knockdown of RAD51 inhibited the migratory ability of DU145 cells but had no effect on PC3 cells (Figure 10d). Apoptosis assays demonstrated that knockdown of RAD51 promoted apoptosis in two PCa cell lines (Figure 10e). In addition, knockdown of RAD51 inhibited the proliferation of 22Rv1 cells more significantly than no knockdown of RAD51 under enzalutamide treatment (Figure 11b).

Figure 10 Effect of RAD51 on the proliferation, migration, and apoptosis of PCa cell lines. (a) PC3 and DU145 cells were transfected with siRAD51 to verify the knockdown efficiency of RAD51 at the mRNA and protein expression levels (one-way analysis of variance). (b) CCK-8 detects the proliferation ability of PC3 and DU145 cells after RAD51 knockdown (one-way analysis of variance). (c) Clone formation assay detects the proliferation ability of PC3 and DU145 cells after RAD51 knockdown (one-way analysis of variance). (d) Transwell migration assay detects the proliferation ability of DU145 cell after RAD51 knockdown (100×) (one-way analysis of variance). (e) Flow cytometry assays detect the apoptosis of PC3 and DU145 cells after RAD51 knockdown (one-way analysis of variance). The significance of differences between multiple groups was determined by ANOVA. *P-value < 0.05, **P-value < 0.01, ***P-value < 0.001, ****P-value < 0.0001. PCa, prostate cancer.
Figure 10

Effect of RAD51 on the proliferation, migration, and apoptosis of PCa cell lines. (a) PC3 and DU145 cells were transfected with siRAD51 to verify the knockdown efficiency of RAD51 at the mRNA and protein expression levels (one-way analysis of variance). (b) CCK-8 detects the proliferation ability of PC3 and DU145 cells after RAD51 knockdown (one-way analysis of variance). (c) Clone formation assay detects the proliferation ability of PC3 and DU145 cells after RAD51 knockdown (one-way analysis of variance). (d) Transwell migration assay detects the proliferation ability of DU145 cell after RAD51 knockdown (100×) (one-way analysis of variance). (e) Flow cytometry assays detect the apoptosis of PC3 and DU145 cells after RAD51 knockdown (one-way analysis of variance). The significance of differences between multiple groups was determined by ANOVA. *P-value < 0.05, **P-value < 0.01, ***P-value < 0.001, ****P-value < 0.0001. PCa, prostate cancer.

Figure 11 Effect of RAD51 on the proliferation, migration, and apoptosis of PCa cell lines. (a) 22Rv1 cells were transfected with siRAD51 to verify the knockdown efficiency of RAD51 at the mRNA and protein expression levels (one-way analysis of variance). (b) Effect of RAD51 knockdown on the viability of 22Rv1 cells treated with different concentrations of enzalutamide for 48 h as detected using a CCK-8 assay. *P-value < 0.05, **P-value < 0.01, ***P-value < 0.001, ****P-value < 0.0001.
Figure 11

Effect of RAD51 on the proliferation, migration, and apoptosis of PCa cell lines. (a) 22Rv1 cells were transfected with siRAD51 to verify the knockdown efficiency of RAD51 at the mRNA and protein expression levels (one-way analysis of variance). (b) Effect of RAD51 knockdown on the viability of 22Rv1 cells treated with different concentrations of enzalutamide for 48 h as detected using a CCK-8 assay. *P-value < 0.05, **P-value < 0.01, ***P-value < 0.001, ****P-value < 0.0001.

4 Discussion

An increasing number of studies have shown that abnormal expression of certain genes promotes CRPC resistance to enzalutamide [20,21,22]. In the present study, we analyzed six hub genes, RAD51, BLM, DTL, RFC2, APOE, and EXO1, which were significantly correlated with enzalutamide resistance, through bioinformatics analysis from multiple perspectives. The expression of RAD51, BLM, RFC2, and EXO1 was highly correlated with AR pathway activity, more so in the high-expression group than the low-expression group. Meanwhile, differential analysis of the GSE32269 dataset showed that the expression of RAD51, BLM, DTL, and APOE was higher in CRPC tissues than in primary PCa tissues. Curiously, the expression of RFC2 and EXO1 in CRPC tissues was not significantly different from that in primary PCa tissues. It is plausible that there was no increase in gene expression, but there may be other mechanisms by which these proteins increase in expression [23]. The AR signaling pathway, a key driver in the uncontrolled growth of malignant PCa cells, is reactivated in CRPC and contributes to CRPC progression [3]. Enzalutamide resistance is associated with the AR signaling pathway [24,25]. Therefore, inhibiting this pathway is a logical strategy for treating CRPC [26]. RAD51 and BLM were shown to be highly expressed in CRPC tissues in our study, and the expression levels were positively correlated with the promotion of AR signaling pathway activity. These results suggest that RAD51 and BLM likely mediate CRPC resistance to enzalutamide by promoting the AR signaling pathway. In addition, we verified that RAD51 knockdown can inhibit the proliferation and migratory ability of PCa cell lines and promote apoptosis. Not only that, the proliferation of 22Rv1 cells was more significantly inhibited under the treatment with enzalutamide when RAD51 was knocked down than when it was not, which further verified that RAD51 could promote enzalutamide resistance. This result is similar to the findings of Kohrt et al. [23], who identified 11 genes (TFAP2C, CAD, SPDEF, EIF6, GABRG2, CDC37, PSMD12, COL5A2, AR, MAP3K11, and ACAT1) whose loss resulted in decreased cell survival in response to enzalutamide. Further experimental validation revealed that three of these genes (ACAT1, MAP3K11, and PSMD12) could serve as proponents of enzalutamide resistance in vitro [23]. There is no doubt that these genes may serve as new therapeutic targets for enzalutamide-resistant PCa in the future.

Different cell types and extracellular components of the tumor microenvironment (TME) not only play a pivotal role in tumor progression, but also significantly influence therapeutic efficacy and mediate drug resistance [27]. Immune infiltration in the TME is associated with enzalutamide resistance [28,29]; we found from our literature review that enzalutamide-resistant CRPC cells were better able to recruit NK cells than ordinary PCa cells, and NK cells inhibited enzalutamide resistance in CRPC by targeting AR splice variant 7 (ARv7) [18]. Furthermore, enzalutamide induced neuroendocrine like (NE-like) PCa cells to enhance monocyte recruitment to the tumor region and promoted monocytes toward tumor-associated macrophages (TAMs). Further studies revealed that enzalutamide-treated C4-2 cells expressed higher levels of NSE and CHGA when co-cultured with NE-like PCa-activated THP-1 cells and sorted into monocytes. In addition, the survival rate of enzalutamide-treated C4-2 cells co-cultured with TAMs was higher than that of enzalutamide-treated cells alone [19]. In summary, NK cells can inhibit enzalutamide resistance in CRPC, while monocytes and macrophages have a facilitative effect on the survival of enzalutamide-resistant CRPC cells. Our results demonstrate that the expression levels of EXO1, BLM, and DTL significantly correlated with the infiltration levels of monocytes, macrophages, and NK cells. The expression levels of RAD51, EXO1, BLM, and DTL showed a significant positive correlation with the infiltration levels of monocytes and macrophages. The expression levels of EXO1, BLM, and DTL showed a significant negative correlation with the infiltration levels of NK cells, and finally, the expression levels of RFC2 and APOE were only significantly and positively correlated with the infiltration levels of macrophages. Collectively, our results suggest that the six hub genes may mediate enzalutamide resistance through the different immune cell infiltration pathways.

In our analysis of the relationship between the expression of hub genes and drug sensitivity based on GDSC, high expression of RAD51, BLM, DTL, RFC2, and EXO1 was significantly associated with higher sensitivity to NPK76-II-72-1 and Navitoclax. Studies have demonstrated that CRPC patient-derived conditionally reprogrammed cells (CRCs) are sensitive to Navitoclax [30]. Navitoclax is an inhibitor of BCL-2 protein families, which are often overexpressed in cancer and associated with drug resistance [31]. BCL-2 family members, BCL-XL and MCL1, are involved in enzalutamide resistance through activation of PI3K/AKT signaling, leading to apoptosis evasion [32]. In addition, BCL-2 was found to be overexpressed in enzalutamide-sensitive cell lines, leading to the emergence of enzalutamide resistance. BCL-2 inhibitors suppressed the development of enzalutamide resistance in xenografts [33]. Through inhibition of the BCL-2 family of proteins, Navitoclax can induce apoptosis. Therefore, RAD51, BLM, DTL, RFC2, and EXO1 may be potential targets of Navitoclax. The combination of enzalutamide and Navitoclax may be a promising treatment regimen to counter enzalutamide resistance.

In this study, we identified a total of 1,208 DEGs, including the six key genes mentioned above, associated with enzalutamide resistance by analyzing the datasets GSE151083 and GSE150807. GO enrichment analysis showed that DEGs were mainly enriched in processes such as signal transduction, positive regulation of gene expression, and drug response. KEGG pathway analysis showed that DEGs were involved in the cancer metabolic pathways and pathways in cancer. In recent years, studies have reported that glucose and lipid metabolism are related to enzalutamide resistance [34,35,36].

RAD51 codes for an enzyme involved in double-stranded DNA break repair [37] is highly expressed in various types of tumors and is associated with poor clinical prognosis [38,39,40]. It can promote the occurrence and development of different tumor types [41,42]. Although RAD51 has been shown to be overexpressed in aggressive PCa [43], its functional role in PCa has not been investigated. Our study demonstrated that RAD51 knockdown in PCa cell lines PC3 and DU145 significantly reduced cell proliferation efficiency, promoted apoptosis, and inhibited migration. In addition, it has been well documented that RAD51 overexpression is associated with tumor resistance to chemotherapy [44,45,46,47]. These results suggest that RAD51 may be a key gene mediating enzalutamide resistance. Bloom syndrome protein (BLM) is an important enzyme in DNA metabolism [48,49]. Its expression in PCa tissues and PC3 cells is significantly higher than that in non-PCa tissues and benign prostatic hyperplasia cells. Knockdown of BLM inhibits PCa cell proliferation and promotes apoptosis, and overexpression can reverse tumor growth inhibition [50,51]. Studies have reported that EZH2 knockdown has an inhibitory effect on the growth of PCa cells, but overexpression of BLM can reverse this effect, and the expression of BLM is positively correlated with that of EZH2 [52]. In addition, it has been shown that EZH2 expression can inhibit CCN3 expression, and CCN3 expression inhibits AR signaling, thereby inhibiting the growth of enzalutamide-resistant PCa cells [53]. This evidence suggests that BLM may play an important role in promoting enzalutamide resistance through the EZH2-CCN3 axis. DTL, also known as CDT2, is mainly involved in the regulation of DNA replication and cell cycle [54,55]. It has been well documented that DTL promotes the development of certain cancers [56,57,58]. DTL was shown to be associated with AKT/mTOR activation, while inhibition of the mTOR pathway inhibited the proliferation of enzalutamide-resistant PCa cells, leading to AR or AR-V degradation [59,60]. Therefore, DTL may promote enzalutamide resistance through the AKT/mTOR pathway. EXO1, a damage-repair related gene, is associated with the clinical progression, metastasis, and survival prognosis of PCa [61,62]. Moreover, the high expression of EXO1 is related to the resistance of gastric and ovarian cancers to cisplatin [63,64]. APOE is a protein related to lipid metabolism that is abundantly secreted by hepatocytes and macrophages [65,66]. One study found that enzalutamide-treated C4-2B cells co-cultured with TAMs increased cell survival [19]. In addition, APOE has been reported to be highly expressed in a variety of tumor types and to promote cancer progression [67,68,69,70]. Replication factor C is a protein complex consisting of five subunits (RFC1-5) that mediates DNA replication and repair [71]. Forkhead box O1 has been reported to promote temozolomide resistance in gliomas through modulation of RFC2 [72]. Meanwhile, Forkhead box M1 (FoxM1) mediates temozolomide resistance in glioma cells by regulating the expression of RFC5 [73]. Recently, it has been increasingly reported that the high expression of RFC2 is associated with the proliferation, migration, and invasion of colorectal cancer and hepatocellular carcinoma. Although all six of the above mentioned hub genes were shown to be associated with cancer progression and we analyzed their relationship with enzalutamide resistance from a bioinformatics perspective, a limitation of the present study is that we did not demonstrate the role of these hub genes in enzalutamide resistance from an enzalutamide resistance cell model. Therefore, their specific role in enzalutamide resistance remains unclear, and future experiments are needed to demonstrate their functions.

5 Conclusion

We identified six key genes associated with enzalutamide resistance, RAD51, BLM, DTL, RFC2, APOE, and EXO1, and their role in enzalutamide resistance was validated via bioinformatic approaches in terms of signaling pathways and immune infiltration. In addition, we verified that RAD51 knockdown can inhibit the proliferation and migratory ability of PCa cell lines and promote apoptosis. Furthermore, the proliferation of 22Rv1 cells was more significantly inhibited with knockdown of RAD51 than without knockdown of RAD51 under enzalutamide treatment. RAD51 is a promotor of enzalutamide resistance. These genes and their protein products may serve as new therapeutic targets for enzalutamide-resistant PCa in the future.

# Authors contributed equally.

  1. Funding information: This study was supported by the National Natural Science Foundation of China (82103178), Shanghai Sailing Program (20YF1438000 and 22YF1433800) and Shanghai Tenth People’s Hospital Climbing Talents Program (2021SYPDRC023).

  2. Author contributions: Conception and design: Wen Xu and Li Liu; administrative support: Fenyong Sun; provision of study materials: Jinliang Ni, Yue Zhang, and Mingyang Li; collection and assembly of data: Wen Xu, Zhongqi Cui, Nan Huang, Jie Luo, and Limei Sun; data analysis and interpretation: Wen Xu, Li Liu, and Zhongqi Cui; manuscript writing and final approval of manuscript: All authors. All authors reviewed and approved the manuscript for publication.

  3. Conflict of interest: The authors declare that they have no conflicts of interest.

  4. Data availability statement: This study used the following publicly available databases: TCGA (https://portal.gdc.cancer.gov/), GEO (https://www.ncbi.nlm.nih.gov/geo/), GEPIA (http://gepia.cancer-pku.cn/), and GSCA (http://bioinfo.life.hust.edu.cn/GSCA/#/).

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Received: 2022-11-28
Revised: 2023-03-16
Accepted: 2023-04-17
Published Online: 2023-05-26

© 2023 the author(s), published by De Gruyter

This work is licensed under the Creative Commons Attribution 4.0 International License.

Artikel in diesem Heft

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  216. Long-term administration of probiotics prevents gastrointestinal mucosal barrier dysfunction in septic mice partly by upregulating the 5-HT degradation pathway
  217. miR-192 inhibits the activation of hepatic stellate cells by targeting Rictor
  218. Diagnostic and prognostic value of MR-pro ADM, procalcitonin, and copeptin in sepsis
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  247. Rapid Communication
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  249. Erratum
  250. Erratum to “Inhibition of miR-21 improves pulmonary vascular responses in bronchopulmonary dysplasia by targeting the DDAH1/ADMA/NO pathway”
  251. Erratum to: “Fer exacerbates renal fibrosis and can be targeted by miR-29c-3p”
  252. Retraction
  253. Retraction of “Study to compare the effect of casirivimab and imdevimab, remdesivir, and favipiravir on progression and multi-organ function of hospitalized COVID-19 patients”
  254. Retraction of “circ_0062491 alleviates periodontitis via the miR-142-5p/IGF1 axis”
  255. Retraction of “miR-223-3p alleviates TGF-β-induced epithelial-mesenchymal transition and extracellular matrix deposition by targeting SP3 in endometrial epithelial cells”
  256. Retraction of “SLCO4A1-AS1 mediates pancreatic cancer development via miR-4673/KIF21B axis”
  257. Retraction of “circRNA_0001679/miR-338-3p/DUSP16 axis aggravates acute lung injury”
  258. Retraction of “lncRNA ACTA2-AS1 inhibits malignant phenotypes of gastric cancer cells”
  259. Special issue Linking Pathobiological Mechanisms to Clinical Application for cardiovascular diseases
  260. Effect of cardiac rehabilitation therapy on depressed patients with cardiac insufficiency after cardiac surgery
  261. Special issue The evolving saga of RNAs from bench to bedside - Part I
  262. FBLIM1 mRNA is a novel prognostic biomarker and is associated with immune infiltrates in glioma
  263. Special Issue Computational Intelligence Methodologies Meets Recurrent Cancers - Part III
  264. Development of a machine learning-based signature utilizing inflammatory response genes for predicting prognosis and immune microenvironment in ovarian cancer
https://doi.org/10.1515/med-2023-0715
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castration-resistant prostate cancer; prostate cancer; enzalutamide; RAD51
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Artikel in diesem Heft

  1. Research Articles
  2. Exosomes derived from mesenchymal stem cells overexpressing miR-210 inhibits neuronal inflammation and contribute to neurite outgrowth through modulating microglia polarization
  3. Current situation of acute ST-segment elevation myocardial infarction in a county hospital chest pain center during an epidemic of novel coronavirus pneumonia
  4. circ-IARS depletion inhibits the progression of non-small-cell lung cancer by circ-IARS/miR-1252-5p/HDGF ceRNA pathway
  5. circRNA ITGA7 restrains growth and enhances radiosensitivity by up-regulating SMAD4 in colorectal carcinoma
  6. WDR79 promotes aerobic glycolysis of pancreatic ductal adenocarcinoma (PDAC) by the suppression of SIRT4
  7. Up-regulation of collagen type V alpha 2 (COL5A2) promotes malignant phenotypes in gastric cancer cell via inducing epithelial–mesenchymal transition (EMT)
  8. Inhibition of TERC inhibits neural apoptosis and inflammation in spinal cord injury through Akt activation and p-38 inhibition via the miR-34a-5p/XBP-1 axis
  9. 3D-printed polyether-ether-ketone/n-TiO2 composite enhances the cytocompatibility and osteogenic differentiation of MC3T3-E1 cells by downregulating miR-154-5p
  10. Propofol-mediated circ_0000735 downregulation restrains tumor growth by decreasing integrin-β1 expression in non-small cell lung cancer
  11. PVT1/miR-16/CCND1 axis regulates gastric cancer progression
  12. Silencing of circ_002136 sensitizes gastric cancer to paclitaxel by targeting the miR-16-5p/HMGA1 axis
  13. Short-term outcomes after simultaneous gastrectomy plus cholecystectomy in gastric cancer: A pooling up analysis
  14. SCARA5 inhibits oral squamous cell carcinoma via inactivating the STAT3 and PI3K/AKT signaling pathways
  15. Molecular mechanism by which the Notch signaling pathway regulates autophagy in a rat model of pulmonary fibrosis in pigeon breeder’s lung
  16. lncRNA TPT1-AS1 promotes cell migration and invasion in esophageal squamous-cell carcinomas by regulating the miR-26a/HMGA1 axis
  17. SIRT1/APE1 promotes the viability of gastric cancer cells by inhibiting p53 to suppress ferroptosis
  18. Glycoprotein non-metastatic melanoma B interacts with epidermal growth factor receptor to regulate neural stem cell survival and differentiation
  19. Treatments for brain metastases from EGFR/ALK-negative/unselected NSCLC: A network meta-analysis
  20. Association of osteoporosis and skeletal muscle loss with serum type I collagen carboxyl-terminal peptide β glypeptide: A cross-sectional study in elder Chinese population
  21. circ_0000376 knockdown suppresses non-small cell lung cancer cell tumor properties by the miR-545-3p/PDPK1 pathway
  22. Delivery in a vertical birth chair supported by freedom of movement during labor: A randomized control trial
  23. UBE2J1 knockdown promotes cell apoptosis in endometrial cancer via regulating PI3K/AKT and MDM2/p53 signaling
  24. Metabolic resuscitation therapy in critically ill patients with sepsis and septic shock: A pilot prospective randomized controlled trial
  25. Lycopene ameliorates locomotor activity and urinary frequency induced by pelvic venous congestion in rats
  26. UHRF1-induced connexin26 methylation is involved in hearing damage triggered by intermittent hypoxia in neonatal rats
  27. LINC00511 promotes melanoma progression by targeting miR-610/NUCB2
  28. Ultra-high-performance liquid chromatography-tandem mass spectrometry analysis of serum metabolomic characteristics in people with different vitamin D levels
  29. Role of Jumonji domain-containing protein D3 and its inhibitor GSK-J4 in Hashimoto’s thyroiditis
  30. circ_0014736 induces GPR4 to regulate the biological behaviors of human placental trophoblast cells through miR-942-5p in preeclampsia
  31. Monitoring of sirolimus in the whole blood samples from pediatric patients with lymphatic anomalies
  32. Effects of osteogenic growth peptide C-terminal pentapeptide and its analogue on bone remodeling in an osteoporosis rat model
  33. A novel autophagy-related long non-coding RNAs signature predicting progression-free interval and I-131 therapy benefits in papillary thyroid carcinoma
  34. WGCNA-based identification of potential targets and pathways in response to treatment in locally advanced breast cancer patients
  35. Radiomics model using preoperative computed tomography angiography images to differentiate new from old emboli of acute lower limb arterial embolism
  36. Dysregulated lncRNAs are involved in the progress of myocardial infarction by constructing regulatory networks
  37. Single-arm trial to evaluate the efficacy and safety of baclofen in treatment of intractable hiccup caused by malignant tumor chemotherapy
  38. Genetic polymorphisms of MRPS30-DT and NINJ2 may influence lung cancer risk
  39. Efficacy of immune checkpoint inhibitors in patients with KRAS-mutant advanced non-small cell lung cancer: A retrospective analysis
  40. Pyroptosis-based risk score predicts prognosis and drug sensitivity in lung adenocarcinoma
  41. Upregulation of lncRNA LANCL1-AS1 inhibits the progression of non-small-cell lung cancer via the miR-3680-3p/GMFG axis
  42. CircRANBP17 modulated KDM1A to regulate neuroblastoma progression by sponging miR-27b-3p
  43. Exosomal miR-93-5p regulated the progression of osteoarthritis by targeting ADAMTS9
  44. Downregulation of RBM17 enhances cisplatin sensitivity and inhibits cell invasion in human hypopharyngeal cancer cells
  45. HDAC5-mediated PRAME regulates the proliferation, migration, invasion, and EMT of laryngeal squamous cell carcinoma via the PI3K/AKT/mTOR signaling pathway
  46. The association between sleep duration, quality, and nonalcoholic fatty liver disease: A cross-sectional study
  47. Myostatin silencing inhibits podocyte apoptosis in membranous nephropathy through Smad3/PKA/NOX4 signaling pathway
  48. A novel long noncoding RNA AC125257.1 facilitates colorectal cancer progression by targeting miR-133a-3p/CASC5 axis
  49. Impact of omicron wave and associated control measures in Shanghai on health management and psychosocial well-being of patients with chronic conditions
  50. Clinicopathological characteristics and prognosis of young patients aged ≤45 years old with non-small cell lung cancer
  51. TMT-based comprehensive proteomic profiling identifies serum prognostic signatures of acute myeloid leukemia
  52. The dose limits of teeth protection for patients with nasopharyngeal carcinoma undergoing radiotherapy based on the early oral health-related quality of life
  53. miR-30b-5p targeting GRIN2A inhibits hippocampal damage in epilepsy
  54. Long non-coding RNA AL137789.1 promoted malignant biological behaviors and immune escape of pancreatic carcinoma cells
  55. IRF6 and FGF1 polymorphisms in non-syndromic cleft lip with or without cleft palate in the Polish population
  56. Comprehensive analysis of the role of SFXN family in breast cancer
  57. Efficacy of bronchoscopic intratumoral injection of endostar and cisplatin in lung squamous cell carcinoma patients underwent conventional chemoradiotherapy
  58. Silencing of long noncoding RNA MIAT inhibits the viability and proliferation of breast cancer cells by promoting miR-378a-5p expression
  59. AG1024, an IGF-1 receptor inhibitor, ameliorates renal injury in rats with diabetic nephropathy via the SOCS/JAK2/STAT pathway
  60. Downregulation of KIAA1199 alleviated the activation, proliferation, and migration of hepatic stellate cells by the inhibition of epithelial–mesenchymal transition
  61. Exendin-4 regulates the MAPK and WNT signaling pathways to alleviate the osteogenic inhibition of periodontal ligament stem cells in a high glucose environment
  62. Inhibition of glycolysis represses the growth and alleviates the endoplasmic reticulum stress of breast cancer cells by regulating TMTC3
  63. The function of lncRNA EMX2OS/miR-653-5p and its regulatory mechanism in lung adenocarcinoma
  64. Tectorigenin alleviates the apoptosis and inflammation in spinal cord injury cell model through inhibiting insulin-like growth factor-binding protein 6
  65. Ultrasound examination supporting CT or MRI in the evaluation of cervical lymphadenopathy in patients with irradiation-treated head and neck cancer
  66. F-box and WD repeat domain containing 7 inhibits the activation of hepatic stellate cells by degrading delta-like ligand 1 to block Notch signaling pathway
  67. Knockdown of circ_0005615 enhances the radiosensitivity of colorectal cancer by regulating the miR-665/NOTCH1 axis
  68. Long noncoding RNA Mhrt alleviates angiotensin II-induced cardiac hypertrophy phenotypes by mediating the miR-765/Wnt family member 7B pathway
  69. Effect of miR-499-5p/SOX6 axis on atrial fibrosis in rats with atrial fibrillation
  70. Cholesterol induces inflammation and reduces glucose utilization
  71. circ_0004904 regulates the trophoblast cell in preeclampsia via miR-19b-3p/ARRDC3 axis
  72. NECAB3 promotes the migration and invasion of liver cancer cells through HIF-1α/RIT1 signaling pathway
  73. The poor performance of cardiovascular risk scores in identifying patients with idiopathic inflammatory myopathies at high cardiovascular risk
  74. miR-2053 inhibits the growth of ovarian cancer cells by downregulating SOX4
  75. Nucleophosmin 1 associating with engulfment and cell motility protein 1 regulates hepatocellular carcinoma cell chemotaxis and metastasis
  76. α-Hederin regulates macrophage polarization to relieve sepsis-induced lung and liver injuries in mice
  77. Changes of microbiota level in urinary tract infections: A meta-analysis
  78. Identification of key enzalutamide-resistance-related genes in castration-resistant prostate cancer and verification of RAD51 functions
  79. Falls during oxaliplatin-based chemotherapy for gastrointestinal malignancies – (lessons learned from) a prospective study
  80. Outcomes of low-risk birth care during the Covid-19 pandemic: A cohort study from a tertiary care center in Lithuania
  81. Vitamin D protects intestines from liver cirrhosis-induced inflammation and oxidative stress by inhibiting the TLR4/MyD88/NF-κB signaling pathway
  82. Integrated transcriptome analysis identifies APPL1/RPS6KB2/GALK1 as immune-related metastasis factors in breast cancer
  83. Genomic analysis of immunogenic cell death-related subtypes for predicting prognosis and immunotherapy outcomes in glioblastoma multiforme
  84. Circular RNA Circ_0038467 promotes the maturation of miRNA-203 to increase lipopolysaccharide-induced apoptosis of chondrocytes
  85. An economic evaluation of fine-needle cytology as the primary diagnostic tool in the diagnosis of lymphadenopathy
  86. Midazolam impedes lung carcinoma cell proliferation and migration via EGFR/MEK/ERK signaling pathway
  87. Network pharmacology combined with molecular docking and experimental validation to reveal the pharmacological mechanism of naringin against renal fibrosis
  88. PTPN12 down-regulated by miR-146b-3p gene affects the malignant progression of laryngeal squamous cell carcinoma
  89. miR-141-3p accelerates ovarian cancer progression and promotes M2-like macrophage polarization by targeting the Keap1-Nrf2 pathway
  90. lncRNA OIP5-AS1 attenuates the osteoarthritis progression in IL-1β-stimulated chondrocytes
  91. Overexpression of LINC00607 inhibits cell growth and aggressiveness by regulating the miR-1289/EFNA5 axis in non-small-cell lung cancer
  92. Subjective well-being in informal caregivers during the COVID-19 pandemic
  93. Nrf2 protects against myocardial ischemia-reperfusion injury in diabetic rats by inhibiting Drp1-mediated mitochondrial fission
  94. Unfolded protein response inhibits KAT2B/MLKL-mediated necroptosis of hepatocytes by promoting BMI1 level to ubiquitinate KAT2B
  95. Bladder cancer screening: The new selection and prediction model
  96. circNFATC3 facilitated the progression of oral squamous cell carcinoma via the miR-520h/LDHA axis
  97. Prone position effect in intensive care patients with SARS-COV-2 pneumonia
  98. Clinical observation on the efficacy of Tongdu Tuina manipulation in the treatment of primary enuresis in children
  99. Dihydroartemisinin ameliorates cerebral I/R injury in rats via regulating VWF and autophagy-mediated SIRT1/FOXO1 pathway
  100. Knockdown of circ_0113656 assuages oxidized low-density lipoprotein-induced vascular smooth muscle cell injury through the miR-188-3p/IGF2 pathway
  101. Low Ang-(1–7) and high des-Arg9 bradykinin serum levels are correlated with cardiovascular risk factors in patients with COVID-19
  102. Effect of maternal age and body mass index on induction of labor with oral misoprostol for premature rupture of membrane at term: A retrospective cross-sectional study
  103. Potential protective effects of Huanglian Jiedu Decoction against COVID-19-associated acute kidney injury: A network-based pharmacological and molecular docking study
  104. Clinical significance of serum MBD3 detection in girls with central precocious puberty
  105. Clinical features of varicella-zoster virus caused neurological diseases detected by metagenomic next-generation sequencing
  106. Collagen treatment of complex anorectal fistula: 3 years follow-up
  107. LncRNA CASC15 inhibition relieves renal fibrosis in diabetic nephropathy through down-regulating SP-A by sponging to miR-424
  108. Efficacy analysis of empirical bismuth quadruple therapy, high-dose dual therapy, and resistance gene-based triple therapy as a first-line Helicobacter pylori eradication regimen – An open-label, randomized trial
  109. SMOC2 plays a role in heart failure via regulating TGF-β1/Smad3 pathway-mediated autophagy
  110. A prospective cohort study of the impact of chronic disease on fall injuries in middle-aged and older adults
  111. circRNA THBS1 silencing inhibits the malignant biological behavior of cervical cancer cells via the regulation of miR-543/HMGB2 axis
  112. hsa_circ_0000285 sponging miR-582-3p promotes neuroblastoma progression by regulating the Wnt/β-catenin signaling pathway
  113. Long non-coding RNA GNAS-AS1 knockdown inhibits proliferation and epithelial–mesenchymal transition of lung adenocarcinoma cells via the microRNA-433-3p/Rab3A axis
  114. lncRNA UCA1 regulates miR-132/Lrrfip1 axis to promote vascular smooth muscle cell proliferation
  115. Twenty-four-color full spectrum flow cytometry panel for minimal residual disease detection in acute myeloid leukemia
  116. Hsa-miR-223-3p participates in the process of anthracycline-induced cardiomyocyte damage by regulating NFIA gene
  117. Anti-inflammatory effect of ApoE23 on Salmonella typhimurium-induced sepsis in mice
  118. Analysis of somatic mutations and key driving factors of cervical cancer progression
  119. Hsa_circ_0028007 regulates the progression of nasopharyngeal carcinoma through the miR-1179/SQLE axis
  120. Variations in sexual function after laparoendoscopic single-site hysterectomy in women with benign gynecologic diseases
  121. Effects of pharmacological delay with roxadustat on multi-territory perforator flap survival in rats
  122. Analysis of heroin effects on calcium channels in rat cardiomyocytes based on transcriptomics and metabolomics
  123. Risk factors of recurrent bacterial vaginosis among women of reproductive age: A cross-sectional study
  124. Alkbh5 plays indispensable roles in maintaining self-renewal of hematopoietic stem cells
  125. Study to compare the effect of casirivimab and imdevimab, remdesivir, and favipiravir on progression and multi-organ function of hospitalized COVID-19 patients
  126. Correlation between microvessel maturity and ISUP grades assessed using contrast-enhanced transrectal ultrasonography in prostate cancer
  127. The protective effect of caffeic acid phenethyl ester in the nephrotoxicity induced by α-cypermethrin
  128. Norepinephrine alleviates cyclosporin A-induced nephrotoxicity by enhancing the expression of SFRP1
  129. Effect of RUNX1/FOXP3 axis on apoptosis of T and B lymphocytes and immunosuppression in sepsis
  130. The function of Foxp1 represses β-adrenergic receptor transcription in the occurrence and development of bladder cancer through STAT3 activity
  131. Risk model and validation of carbapenem-resistant Klebsiella pneumoniae infection in patients with cerebrovascular disease in the ICU
  132. Calycosin protects against chronic prostatitis in rats via inhibition of the p38MAPK/NF-κB pathway
  133. Pan-cancer analysis of the PDE4DIP gene with potential prognostic and immunotherapeutic values in multiple cancers including acute myeloid leukemia
  134. The safety and immunogenicity to inactivated COVID-19 vaccine in patients with hyperlipemia
  135. Circ-UBR4 regulates the proliferation, migration, inflammation, and apoptosis in ox-LDL-induced vascular smooth muscle cells via miR-515-5p/IGF2 axis
  136. Clinical characteristics of current COVID-19 rehabilitation outpatients in China
  137. Luteolin alleviates ulcerative colitis in rats via regulating immune response, oxidative stress, and metabolic profiling
  138. miR-199a-5p inhibits aortic valve calcification by targeting ATF6 and GRP78 in valve interstitial cells
  139. The application of iliac fascia space block combined with esketamine intravenous general anesthesia in PFNA surgery of the elderly: A prospective, single-center, controlled trial
  140. Elevated blood acetoacetate levels reduce major adverse cardiac and cerebrovascular events risk in acute myocardial infarction
  141. The effects of progesterone on the healing of obstetric anal sphincter damage in female rats
  142. Identification of cuproptosis-related genes for predicting the development of prostate cancer
  143. Lumican silencing ameliorates β-glycerophosphate-mediated vascular smooth muscle cell calcification by attenuating the inhibition of APOB on KIF2C activity
  144. Targeting PTBP1 blocks glutamine metabolism to improve the cisplatin sensitivity of hepatocarcinoma cells through modulating the mRNA stability of glutaminase
  145. A single center prospective study: Influences of different hip flexion angles on the measurement of lumbar spine bone mineral density by dual energy X-ray absorptiometry
  146. Clinical analysis of AN69ST membrane continuous venous hemofiltration in the treatment of severe sepsis
  147. Antibiotics therapy combined with probiotics administered intravaginally for the treatment of bacterial vaginosis: A systematic review and meta-analysis
  148. Construction of a ceRNA network to reveal a vascular invasion associated prognostic model in hepatocellular carcinoma
  149. A pan-cancer analysis of STAT3 expression and genetic alterations in human tumors
  150. A prognostic signature based on seven T-cell-related cell clustering genes in bladder urothelial carcinoma
  151. Pepsin concentration in oral lavage fluid of rabbit reflux model constructed by dilating the lower esophageal sphincter
  152. The antihypertensive felodipine shows synergistic activity with immune checkpoint blockade and inhibits tumor growth via NFAT1 in LUSC
  153. Tanshinone IIA attenuates valvular interstitial cells’ calcification induced by oxidized low density lipoprotein via reducing endoplasmic reticulum stress
  154. AS-IV enhances the antitumor effects of propofol in NSCLC cells by inhibiting autophagy
  155. Establishment of two oxaliplatin-resistant gallbladder cancer cell lines and comprehensive analysis of dysregulated genes
  156. Trial protocol: Feasibility of neuromodulation with connectivity-guided intermittent theta-burst stimulation for improving cognition in multiple sclerosis
  157. LncRNA LINC00592 mediates the promoter methylation of WIF1 to promote the development of bladder cancer
  158. Factors associated with gastrointestinal dysmotility in critically ill patients
  159. Mechanisms by which spinal cord stimulation intervenes in atrial fibrillation: The involvement of the endothelin-1 and nerve growth factor/p75NTR pathways
  160. Analysis of two-gene signatures and related drugs in small-cell lung cancer by bioinformatics
  161. Silencing USP19 alleviates cigarette smoke extract-induced mitochondrial dysfunction in BEAS-2B cells by targeting FUNDC1
  162. Menstrual irregularities associated with COVID-19 vaccines among women in Saudi Arabia: A survey during 2022
  163. Ferroptosis involves in Schwann cell death in diabetic peripheral neuropathy
  164. The effect of AQP4 on tau protein aggregation in neurodegeneration and persistent neuroinflammation after cerebral microinfarcts
  165. Activation of UBEC2 by transcription factor MYBL2 affects DNA damage and promotes gastric cancer progression and cisplatin resistance
  166. Analysis of clinical characteristics in proximal and distal reflux monitoring among patients with gastroesophageal reflux disease
  167. Exosomal circ-0020887 and circ-0009590 as novel biomarkers for the diagnosis and prediction of short-term adverse cardiovascular outcomes in STEMI patients
  168. Upregulated microRNA-429 confers endometrial stromal cell dysfunction by targeting HIF1AN and regulating the HIF1A/VEGF pathway
  169. Bibliometrics and knowledge map analysis of ultrasound-guided regional anesthesia
  170. Knockdown of NUPR1 inhibits angiogenesis in lung cancer through IRE1/XBP1 and PERK/eIF2α/ATF4 signaling pathways
  171. D-dimer trends predict COVID-19 patient’s prognosis: A retrospective chart review study
  172. WTAP affects intracranial aneurysm progression by regulating m6A methylation modification
  173. Using of endoscopic polypectomy in patients with diagnosed malignant colorectal polyp – The cross-sectional clinical study
  174. Anti-S100A4 antibody administration alleviates bronchial epithelial–mesenchymal transition in asthmatic mice
  175. Prognostic evaluation of system immune-inflammatory index and prognostic nutritional index in double expressor diffuse large B-cell lymphoma
  176. Prevalence and antibiogram of bacteria causing urinary tract infection among patients with chronic kidney disease
  177. Reactive oxygen species within the vaginal space: An additional promoter of cervical intraepithelial neoplasia and uterine cervical cancer development?
  178. Identification of disulfidptosis-related genes and immune infiltration in lower-grade glioma
  179. A new technique for uterine-preserving pelvic organ prolapse surgery: Laparoscopic rectus abdominis hysteropexy for uterine prolapse by comparing with traditional techniques
  180. Self-isolation of an Italian long-term care facility during COVID-19 pandemic: A comparison study on care-related infectious episodes
  181. A comparative study on the overlapping effects of clinically applicable therapeutic interventions in patients with central nervous system damage
  182. Low intensity extracorporeal shockwave therapy for chronic pelvic pain syndrome: Long-term follow-up
  183. The diagnostic accuracy of touch imprint cytology for sentinel lymph node metastases of breast cancer: An up-to-date meta-analysis of 4,073 patients
  184. Mortality associated with Sjögren’s syndrome in the United States in the 1999–2020 period: A multiple cause-of-death study
  185. CircMMP11 as a prognostic biomarker mediates miR-361-3p/HMGB1 axis to accelerate malignant progression of hepatocellular carcinoma
  186. Analysis of the clinical characteristics and prognosis of adult de novo acute myeloid leukemia (none APL) with PTPN11 mutations
  187. KMT2A maintains stemness of gastric cancer cells through regulating Wnt/β-catenin signaling-activated transcriptional factor KLF11
  188. Evaluation of placental oxygenation by near-infrared spectroscopy in relation to ultrasound maturation grade in physiological term pregnancies
  189. The role of ultrasonographic findings for PIK3CA-mutated, hormone receptor-positive, human epidermal growth factor receptor-2-negative breast cancer
  190. Construction of immunogenic cell death-related molecular subtypes and prognostic signature in colorectal cancer
  191. Long-term prognostic value of high-sensitivity cardiac troponin-I in patients with idiopathic dilated cardiomyopathy
  192. Establishing a novel Fanconi anemia signaling pathway-associated prognostic model and tumor clustering for pediatric acute myeloid leukemia patients
  193. Integrative bioinformatics analysis reveals STAT2 as a novel biomarker of inflammation-related cardiac dysfunction in atrial fibrillation
  194. Adipose-derived stem cells repair radiation-induced chronic lung injury via inhibiting TGF-β1/Smad 3 signaling pathway
  195. Real-world practice of idiopathic pulmonary fibrosis: Results from a 2000–2016 cohort
  196. lncRNA LENGA sponges miR-378 to promote myocardial fibrosis in atrial fibrillation
  197. Diagnostic value of urinary Tamm-Horsfall protein and 24 h urine osmolality for recurrent calcium oxalate stones of the upper urinary tract: Cross-sectional study
  198. The value of color Doppler ultrasonography combined with serum tumor markers in differential diagnosis of gastric stromal tumor and gastric cancer
  199. The spike protein of SARS-CoV-2 induces inflammation and EMT of lung epithelial cells and fibroblasts through the upregulation of GADD45A
  200. Mycophenolate mofetil versus cyclophosphamide plus in patients with connective tissue disease-associated interstitial lung disease: Efficacy and safety analysis
  201. MiR-1278 targets CALD1 and suppresses the progression of gastric cancer via the MAPK pathway
  202. Metabolomic analysis of serum short-chain fatty acid concentrations in a mouse of MPTP-induced Parkinson’s disease after dietary supplementation with branched-chain amino acids
  203. Cimifugin inhibits adipogenesis and TNF-α-induced insulin resistance in 3T3-L1 cells
  204. Predictors of gastrointestinal complaints in patients on metformin therapy
  205. Prescribing patterns in patients with chronic obstructive pulmonary disease and atrial fibrillation
  206. A retrospective analysis of the effect of latent tuberculosis infection on clinical pregnancy outcomes of in vitro fertilization–fresh embryo transferred in infertile women
  207. Appropriateness and clinical outcomes of short sustained low-efficiency dialysis: A national experience
  208. miR-29 regulates metabolism by inhibiting JNK-1 expression in non-obese patients with type 2 diabetes mellitus and NAFLD
  209. Clinical features and management of lymphoepithelial cyst
  210. Serum VEGF, high-sensitivity CRP, and cystatin-C assist in the diagnosis of type 2 diabetic retinopathy complicated with hyperuricemia
  211. ENPP1 ameliorates vascular calcification via inhibiting the osteogenic transformation of VSMCs and generating PPi
  212. Significance of monitoring the levels of thyroid hormone antibodies and glucose and lipid metabolism antibodies in patients suffer from type 2 diabetes
  213. The causal relationship between immune cells and different kidney diseases: A Mendelian randomization study
  214. Interleukin 33, soluble suppression of tumorigenicity 2, interleukin 27, and galectin 3 as predictors for outcome in patients admitted to intensive care units
  215. Identification of diagnostic immune-related gene biomarkers for predicting heart failure after acute myocardial infarction
  216. Long-term administration of probiotics prevents gastrointestinal mucosal barrier dysfunction in septic mice partly by upregulating the 5-HT degradation pathway
  217. miR-192 inhibits the activation of hepatic stellate cells by targeting Rictor
  218. Diagnostic and prognostic value of MR-pro ADM, procalcitonin, and copeptin in sepsis
  219. Review Articles
  220. Prenatal diagnosis of fetal defects and its implications on the delivery mode
  221. Electromagnetic fields exposure on fetal and childhood abnormalities: Systematic review and meta-analysis
  222. Characteristics of antibiotic resistance mechanisms and genes of Klebsiella pneumoniae
  223. Saddle pulmonary embolism in the setting of COVID-19 infection: A systematic review of case reports and case series
  224. Vitamin C and epigenetics: A short physiological overview
  225. Ebselen: A promising therapy protecting cardiomyocytes from excess iron in iron-overloaded thalassemia patients
  226. Aspirin versus LMWH for VTE prophylaxis after orthopedic surgery
  227. Mechanism of rhubarb in the treatment of hyperlipidemia: A recent review
  228. Surgical management and outcomes of traumatic global brachial plexus injury: A concise review and our center approach
  229. The progress of autoimmune hepatitis research and future challenges
  230. METTL16 in human diseases: What should we do next?
  231. New insights into the prevention of ureteral stents encrustation
  232. VISTA as a prospective immune checkpoint in gynecological malignant tumors: A review of the literature
  233. Case Reports
  234. Mycobacterium xenopi infection of the kidney and lymph nodes: A case report
  235. Genetic mutation of SLC6A20 (c.1072T > C) in a family with nephrolithiasis: A case report
  236. Chronic hepatitis B complicated with secondary hemochromatosis was cured clinically: A case report
  237. Liver abscess complicated with multiple organ invasive infection caused by hematogenous disseminated hypervirulent Klebsiella pneumoniae: A case report
  238. Urokinase-based lock solutions for catheter salvage: A case of an upcoming kidney transplant recipient
  239. Two case reports of maturity-onset diabetes of the young type 3 caused by the hepatocyte nuclear factor 1α gene mutation
  240. Immune checkpoint inhibitor-related pancreatitis: What is known and what is not
  241. Does total hip arthroplasty result in intercostal nerve injury? A case report and literature review
  242. Clinicopathological characteristics and diagnosis of hepatic sinusoidal obstruction syndrome caused by Tusanqi – Case report and literature review
  243. Synchronous triple primary gastrointestinal malignant tumors treated with laparoscopic surgery: A case report
  244. CT-guided percutaneous microwave ablation combined with bone cement injection for the treatment of transverse metastases: A case report
  245. Malignant hyperthermia: Report on a successful rescue of a case with the highest temperature of 44.2°C
  246. Anesthetic management of fetal pulmonary valvuloplasty: A case report
  247. Rapid Communication
  248. Impact of COVID-19 lockdown on glycemic levels during pregnancy: A retrospective analysis
  249. Erratum
  250. Erratum to “Inhibition of miR-21 improves pulmonary vascular responses in bronchopulmonary dysplasia by targeting the DDAH1/ADMA/NO pathway”
  251. Erratum to: “Fer exacerbates renal fibrosis and can be targeted by miR-29c-3p”
  252. Retraction
  253. Retraction of “Study to compare the effect of casirivimab and imdevimab, remdesivir, and favipiravir on progression and multi-organ function of hospitalized COVID-19 patients”
  254. Retraction of “circ_0062491 alleviates periodontitis via the miR-142-5p/IGF1 axis”
  255. Retraction of “miR-223-3p alleviates TGF-β-induced epithelial-mesenchymal transition and extracellular matrix deposition by targeting SP3 in endometrial epithelial cells”
  256. Retraction of “SLCO4A1-AS1 mediates pancreatic cancer development via miR-4673/KIF21B axis”
  257. Retraction of “circRNA_0001679/miR-338-3p/DUSP16 axis aggravates acute lung injury”
  258. Retraction of “lncRNA ACTA2-AS1 inhibits malignant phenotypes of gastric cancer cells”
  259. Special issue Linking Pathobiological Mechanisms to Clinical Application for cardiovascular diseases
  260. Effect of cardiac rehabilitation therapy on depressed patients with cardiac insufficiency after cardiac surgery
  261. Special issue The evolving saga of RNAs from bench to bedside - Part I
  262. FBLIM1 mRNA is a novel prognostic biomarker and is associated with immune infiltrates in glioma
  263. Special Issue Computational Intelligence Methodologies Meets Recurrent Cancers - Part III
  264. Development of a machine learning-based signature utilizing inflammatory response genes for predicting prognosis and immune microenvironment in ovarian cancer
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Heruntergeladen am 11.9.2025 von https://www.degruyterbrill.com/document/doi/10.1515/med-2023-0715/html
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