Upregulation of KIF20A promotes tumor proliferation and invasion in renal clear cell carcinoma and is associated with adverse clinical outcome

3D spheroid culturing of Astyanax mexicanus liver-derived cell lines recapitulates distinct transcriptomic and metabolic states of in vivo tissue environment

In vitro assays are crucial tools for gaining detailed insights into various biological processes, including metabolism. Cave morphs of the river-dwelling fish species, Astyanax mexicanus, have adapted their metabolism allowing them to thrive in the biodiversity-deprived and nutrient-limited environment of caves. Liver-derived cells from the cave and river morphs of A. mexicanus have proven to be excellent in vitro resources to better understand the unique metabolism of these fish. However, the current 2D cultures have not fully captured the complex metabolic profile of the Astyanax liver. It is known that 3D culturing can modulate the transcriptomic state of cells when compared to its 2D monolayer culture. Therefore, to broaden the possibilities of the in vitro system by modeling a wider gamut of metabolic pathways, we cultured the liver-derived Astyanax cells of both surface and cavefish into 3D spheroids. We successfully established 3D cultures at various cell seeding densities for several weeks and characterized the resultant transcriptomic and metabolic variations. We found that the 3D cultured Astyanax cells exhibit an altered transcriptomic profile and consequently represent a wider range of metabolic pathways, including cell cycle changes and antioxidant activities, associated with liver functioning as compared to its monolayer culture. Enzymatic assay measuring antioxidants in 2D culture and 3D spheroids also revealed enhanced antioxidative capacity of 3D cultured spheroids, in line with the differential gene expression data. Additionally, the spheroids also exhibited surface and cave-specific metabolic signatures, making it a suitable system for evolutionary studies associated with cave adaptation. Notably, cavefish derived spheroids enriched for genes responding to xenobiotic stimulus, while the ones from surface enriched for immune response, both of which resonated with known physiologically adaptations associated with each morph. Taken together, the liver-derived spheroids prove to be a promising in vitro model for widening our understanding of metabolism in A. mexicanus and of vertebrates in general.

Bioinformatics Approach to Identify the Pathogenetic Link of Gut Microbiota-Derived Short-Chain Fatty Acids and Ischemic Stroke

Stroke is a life-threatening condition that impairs the arteries and causes neurological impairment. The incidence of stroke is increasing year by year with the arrival of the aging population. Thus, there is an urgent need for early stroke diagnosis. Short-chain fatty acids (SCFAs) can modulate the central nervous system and directly and indirectly impact behavioral and cognitive functions. This study aimed to investigate the connection between SCFA metabolism and stroke development via bioinformatic analysis. Initially, the Gene Set Enrichment Analysis (GSEA) and immune cell infiltration analysis were performed based on RNA data from stroke patients to comprehend the mechanisms governing stroke pathogenesis. The functional analysis, including Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Protein-Protein Interaction (PPI), was performed based on the Differentially Expressed Gene (DEG) selected by the limma package. 1220 SCFA metabolism-related genes screened from Genecards databases were intersected with 242 genes in main modules determined by Weighted Gene Co-Expression Network Analysis (WGCNA), and the final 10 SCFA key genes were obtained. GO analysis revealed that these genes were involved in immune response processes. Through lasso regression analyses, we established a stroke early diagnosis model and selected 6 genes with diagnostic value. The genes were validated by the area under curve (AUC) values and had a relatively good diagnostic performance. Finally, 4 potential therapeutic drugs targeting these genes were predicted using the Drug Signatures Database (DSigDB) via Enrichr. In conclusion, this paper analyzes the involvement of SCFAs in the complex gut-brain axis mechanism, which contributes to developing new targets for treating central nervous system diseases and provides new ideas for early ischemic stroke diagnosis.

Bioinformatics analysis highlights CCNB1 as a potential prognostic biomarker and an anti-kidney renal papillary cell carcinoma drug target

Kidney renal papillary cell carcinoma (KIRP) is a common urinary tumor that causes lymph node invasion. Once metastatic, the prognosis is poor and there is a lack of effective early diagnostic markers for this tumor. The expression of CCNB1 in KIRP tumor tissues was significantly higher than that in normal tissues in The Cancer Genome Atlas database with or without the genotype-tissue expression database, and a consistent result was obtained in 32 paired tissues. In addition, CCNB1 expression increased remarkably with the progression of the T and M stages. Moreover, using the online HPA database, we verified that the immunohistochemical scores of CCNB1 in KIRP were higher than those in the normal kidney tissues. The higher expression group of CCNB1 showed a worse prognosis in KIRP. Moreover, the receiver operating characteristic curve, univariate and multivariate analyses, and construction of the column diagram further illustrated that CCNB1 was an independent prognostic factor for KIRP. Meanwhile, CCNB1 could better predict the 1- and 3-year survival rates of KIRP. Six genes were significantly and positively co-expressed with CCNB1. We also found that the CCNB1 high-expression group was enriched in the ECM_RECEPTOR_INTERACTION and FOCAL_ADHESION pathways. Finally, drug sensitivity analysis combined with molecular docking identified 5 targeting drugs with the strongest binding activity to CCNB1. CCNB1 is a potential and reliable biomarker for KIRP diagnosis and can be used to predict the survival of patients with KIRP. The 5 selected drugs targeting CCNB1 may provide new hopes for patients with KIRP metastasis.

KIF20A Promotes CRC Progression and the Warburg Effect through the C-Myc/HIF-1α Axis

BACKGROUND

Colorectal cancer (CRC) is a prevalent form of cancer globally, characterized by a high mortality rate. Therefore, discovering effective therapeutic approaches for CRC treatment is critical.

METHODS

The levels of KIF20A in CRC clinical samples were determined using Western Blot and immunofluorescence assay. SW480 cells were transfected with siRNA targeting KIF20A, while HT-29 cells were transfected with a KIF20A overexpression vector. Cell viability and apoptosis of CRC cells were assessed using CCK-8 and TUNEL analysis. Migration ability was investigated using Transwell. The levels of pyruvate, lactate and ATP were determined through corresponding assay kits. Western Blot was applied to confirm the level of proteins associated with glycolysis, c- Myc, HIF-1α, PKM2 and LDHA. Subsequently, functional rescue experiments were conducted to investigate further the regulatory relationship between KIF20A, c-Myc, and HIF-1α in colorectal cancer (CRC), employing the c-Myc inhibitor 10058-F4 and c-Myc overexpression plasmids.

RESULTS

KIF20A was up-regulated in vivo and in vitro in CRC. KIF20A knockdown inhibited cell viability and migration while promoting cell apoptosis in SW480 cells. Conversely, overexpression of KIF20A yielded contrasting effects in HT-29 cells. Moreover, inhibition of KIF20A restrained the pyruvate, lactate production and ATP level, whereas overexpression of KIF20A enhanced the Warburg effect. Western Blot indicated that knockdown KIF20A attenuated the levels of c-Myc, HIF-1α, PKM2 and LDHA. In addition, rescue experiments further verified that KIF20A enhanced the Warburg effect by the KIF20A/c-Myc/HIF-1α axis in CRC.

CONCLUSION

KIF20A, being a crucial regulator in the progression of CRC, has the potential to be a promising therapeutic target for the treatment of CRC.

Multidimensional analysis to elucidate the possible mechanism of bone metastasis in breast cancer

BACKGROUND

Breast cancer (BC) patients tend to suffer from distant metastasis, especially bone metastasis.

METHODS

All the analysis based on open-accessed data was performed in R software, dependent on multiple algorithms and packages. The RNA levels of specific genes were detected using quantitative Real-time PCR as a method of detecting the RNA levels. To assess the ability of BC cells to proliferate, we utilized the CCK8 test, colony formation, and the 5-Ethynyl-20-deoxyuridine assay. BC cells were evaluated for invasion and migration by using Transwell assays and wound healing assays.

RESULTS

In our study, we identified the molecules involved in BC bone metastasis based on the data from multiple BC cohorts. Then, we comprehensively investigated the effect pattern and underlying biological role of these molecules. We found that in the identified molecules, the EMP1, ACKR3, ITGA10, MMP13, COL11A1, and THY1 were significantly correlated with patient prognosis and mainly expressed in CAFs. Therefore, we explored the CAFs in the BC microenvironment. Results showed that CAFs could activate multiple carcinogenic pathways and most of these pathways play an important role in cancer metastasis. Meanwhile, we noticed the interaction between CAFs and malignant, endothelial, and M2 macrophage cells. Moreover, we found that CAFs could induce the remodeling of the BC microenvironment and promote the malignant behavior of BC cells. Then, we identified MMP13 for further analysis. It was found that MMP13 can enhance the malignant phenotype of BC cells. Meanwhile, biological enrichment and immune infiltration analysis were conducted to present the effect pattern of MMP13 in BC.

CONCLUSIONS

Our result can improve the understanding of researchers on the underlying mechanisms of BC bone metastasis.

Hsa_circ_0003596 enhances the development of cell renal clear cell carcinoma through the miR-502-5p/IGF1/PI3K/AKT axis

Accumulating research findings have shown that circular RNAs (circRNAs) play an indispensable role in tumorigenesis and tumor progression. The current study aimed to explore the role and modulatory mechanism of hsa_circ_0003596 in clear cell renal cell carcinoma (ccRCC). Quantitative real-time polymerase chain reaction was adopted to detect the expression of hsa_circ_0003596 in ccRCC tissue and cell lines. 5-Ethynyl-2'-deoxyuridine, cell counting kit 8 and the colony formation assay were utilized to assess the proliferation potential of the ccRCC cells. Transwell along with wound healing assays were adopted to quantify infiltration coupled with the migration potential of the cells. The current research study found that the circRNA hsa_circ_0003596 was overexpressed in ccRCC tissue and cell lines. Further, result showed that hsa_circ_0003596 was associated with distant metastasis of renal cancer. Notably, the knockdown of hsa_circ_0003596 can lower the proliferation, infiltration and migration potential of ccRCC cells. The results of in vivo experiments found that the reduction of hsa_circ_0003596 significantly hampered the growth of tumors in mice. In addition, it was evident that hsa_circ_0003596 acts as a "molecular sponge" for miR-502-5p to upregulate the expression of the microRNA-502-5p (miR-502-5p) target insulin-like growth factor 1 (IGF1R). Furthermore, it was found that the phosphatidylinositol 3-kinase (PI3K)/AKT signaling was the downstream cascade of hsa_circ_0003596/miR-502-5p/IGF1R cascade, which is partly responsible for the cancer-promoting effect. Overall, the results of the present study showed that hsa_circ_0003596 facilitated the proliferation, infiltration and migration of ccRCC through the miR-502-5p/IGF1R/PI3K/AKT axis. Therefore, it was evident that hsa_circ_0003596 can serve as a possible biomarker and therapeutic target against ccRCC.

Stemness genes and miR-1247-3p expression associate with clinicopathological parameters and prognosis in lung adenocarcinoma

Lung cancer makes up one-fourth of all cancer-related mortality with the highest mortality rate among all cancers. Despite recent scientific advancements in cancer therapeutics, the 5-year survival rate of lung adenocarcinoma (LUAD) cancer patients remains below 15 percent. It has been suggested that the high mortality rate of LUAD is linked to the acquisition of progenitor-like cells with stem-like characteristics that assist the whole tumor in regulating immune cell infiltration. To examine this hypothesis further, this study mined several databases to explore the presence of stemness-related genes and miRNAs in LUAD cancers. We examine their association with immune and accessory cell infiltration rates and patient survival. We found 3 stem cell-related genes, ORC1L, KIF20A, and DLGAP5, present in LUAD that also correlate with changes in immune infiltration rates and reduced patient survival rates. Additionally, the modulation in myeloid-derived suppressor cell (MDSC) infiltration and miRNA hsa-mir-1247-3p mediated targeting of tumor suppressor SLC24A4 and oncogenes RAB3B and HJURP appears to primarily regulate LUAD patient survival. Given these findings, hsa-mir-1247-3p and/or its associated gene targets may offer a promising avenue to enhance patient survivability.

Integrated bioinformatics analysis and experimental validation reveals hub genes of rheumatoid arthritis

Rheumatoid arthritis (RA) is an autoimmune disease characterized by systemic inflammation, especially synovitis, leading to joint damage. It is important to explore potential biomarkers and therapeutic targets to improve the clinical treatment of RA. However, the potential underlying mechanisms of action of available treatments for RA have not yet been fully elucidated. The present study investigated the potential biomarkers of RA and identified specific targets for therapeutic intervention. A comprehensive analysis was performed using mRNA files downloaded from the Gene Expression Omnibus. Differences in gene expression were analyzed and compared between the normal and RA groups. In addition, Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses were performed on differentially expressed genes (DEGs). A protein-protein interaction network, Molecular Complex Detection and cytoHubba network were evaluated to identify hub genes. Finally, using an experimental RA rat model induced by Freund's complete adjuvant (FCA), the expression of potential biomarkers or target genes in RA were verified through reverse transcription-quantitative PCR. The results of the mRNA dataset processing revealed 195 DEGs in patients with RA when compared with the healthy controls. Moreover, 10 hub genes were identified in patients with RA and four candidate mRNAs were identified, as follows: Discs large homolog-associated protein 5 (DLGAP5), kinesin family member 20A (KIF20A), maternal embryonic leucine zipper kinase (MELK) and nuclear division cycle 80 (NDC80). Finally, the bioinformatics analysis results were validated by quantifying the expression of the DLGAP5, KIF20A, MELK and NDC80 genes in the FCA-induced experimental RA rat model. The findings of the present study suggested that the treatment of RA may be successful through the inhibition of DLGAP5, KIF20A, MELK and NDC80 expression. Therefore, the targeting of these genes may result in more effective treatments for patients with RA.

Grade scoring system reveals distinct molecular subtypes and identifies KIF20A as a novel biomarker for predicting temozolomide treatment efficiency in gliomas

BACKGROUND

The importance of molecular diagnostics is increasingly emphasized in the 2021 WHO guidelines for gliomas. There is considerable variability in molecular features and prognosis among glioma patients with the same pathological WHO grade.

METHODS

mRNA data and clinical information of human glioma patients were obtained from TCGA and CGGA databases, while expression profiles and TMZ resistance phenotypes of human glioma stem cells were acquired from the GEO database. Differentially expressed genes were identified across distinct WHO grades. Unsupervised clustering was performed on glioma patients based on DEG expression profiles. The Boruta algorithm was employed to identify feature genes for distinct molecular subtypes, and PCA was used to reduce the dimensionality of the feature gene expression data. Grade scores for each sample were calculated and correlated with patients' clinical molecular pathological features and immune microenvironment. Gene set enrichment analysis identified grade score-related functional pathways. Weighted gene co-expression network analysis identified grade score-associated biomarkers. The impact of the hub gene on malignant glioma behavior was validated through in vitro experiments, including CCK-8, EdU, colony formation, Transwell, wound healing, and immunofluorescence assays.

RESULTS

A total of 672 and 687 samples were screened from TCGA and CGGA databases, respectively, along with 6 control, 24 low-grade, and 40 glioblastoma samples from our hospital. Two robust gene clusters were identified based on the expression profiles of 4,476 DEGs among grades 2, 3, and 4 tissues, revealing distinct prognoses. The grade scores exhibited significant heterogeneity across different WHO grade samples, representing diverse immune microenvironments. Grade scores served as independent risk factors for predicting patient prognosis, with higher sensitivity than traditional biomarkers. KIF20A, identified as a grade score-related biomarker, was independently associated with glioma prognosis. Exclusively expressed in tumor cells, KIF20A knockdown significantly inhibited tumor growth, invasion, and EMT biological behavior in glioma cells. Furthermore, KIF20A could serve as a biological marker for predicting patient response to TMZ treatment.

CONCLUSION

The grade scoring system enhances our understanding of the glioma tumor microenvironment. KIF20A, a novel biomarker for predicting TMZ treatment efficiency, influences malignant tumor behavior by affecting the EMT biological behavior of glioma cells.

Pan-cancer analysis of kinesin family members with potential implications in prognosis and immunological role in human cancer

Background

Kinesin is a molecular motor for transporting "goods" within cells and plays a key role in many types of tumors. The multi-angle study of kinesin at the pan-cancer level is conducive to understanding its role in tumorigenesis and development and clinical treatment potential.

Methods

We evaluated the expression of KIF genes, performed differential analysis by using the R package limma, and explored the pan-cancer prognosis of KIF genes by univariate Cox regression analysis. To evaluate the pan-cancer role of KIF genes as a whole, we defined the KIFscore with the help of gene set variation analysis (GSVA) and explored the KIFscores across normal tissues, tumor cell lines, and 33 tumor types in TCGA. Next, we used spearman correlation analysis to extensively study the correlation between the KIFscore and tumor prognosis and be-tween the KIFscore and clinical indicators. We also identified the relationship between the KIFscore and genomic variation and immune molecular signatures by multiplatform analysis. Finally, we identified the key genes in clear cell renal cell carcinoma (ccRCC) through machine learning algorithms and verified the candidate genes by CCK8, wound healing assay, Transwell assay, and flow cytometry.

Results

In most cancers, KIFscores are high and they act as a risk factor for cancer. The KIFscore was significantly associated with copy number variation (CNV), tumor mutation burden (TMB), immune subtypes, DNA repair deficiency, and tumor stemness indexes. Moreover, in almost all cancer species, the KIFscore was positively correlated with T cell CD4+ TH2, the common lymphoid pro-genitor, and the T cell follicular helper. In addition, it was negatively correlated with CXCL16, CCL14, TNFSF13, and TNFRSF14 and positively correlated with ULBP1, MICB, and CD276. Machine learning helped us to identify four hub-genes in ccRCC. The suitable gene, KIF14, is highly expressed in ccRCC and promotes tumor cell proliferation, migration, and invasion.

Conclusion

Our study shows that the KIF genes play an important pan-cancer role and may become a potential new target for a variety of tumor treatments in the future. Furthermore, KIF14, a key molecule in the KIF genes, can provide a new idea for the ccRCC treatment.

3D spheroid culturing of Astyanax mexicanus liver-derived cell lines recapitulates distinct transcriptomic and metabolic states of in vivo tissue environment

In vitro assays are crucial tools for gaining detailed insights into various biological processes, including metabolism. Cave morphs of the river-dwelling fish species, Astyanax mexicanus, have adapted their metabolism allowing them to thrive in the biodiversity-deprived and nutrient-limited environment of caves. Liver-derived cells from the cave and river morphs of Astyanax mexicanus have proven to be excellent in vitro resources to better understand the unique metabolism of these fish. However, the current 2D cultures have not fully captured the complex metabolic profile of the Astyanax liver. It is known that 3D culturing can modulate the transcriptomic state of cells when compared to its 2D monolayer culture. Therefore, in order to broaden the possibilities of the in vitro system by modeling a wider gamut of metabolic pathways, we cultured the liver-derived Astyanax cells of both surface and cavefish into 3D spheroids. We successfully established 3D cultures at various cell seeding densities for several weeks and characterized the resultant transcriptomic and metabolic variations. We found that the 3D cultured Astyanax cells represent a wider range of metabolic pathways, including cell cycle changes and antioxidant activities, associated with liver functioning as compared to its monolayer culture. Additionally, the spheroids also exhibited surface and cave-specific metabolic signatures, making it a suitable system for evolutionary studies associated with cave adaptation. Taken together, the liver-derived spheroids prove to be a promising in vitro model for widening our understanding of metabolism in Astyanax mexicanus and of vertebrates in general.

A novel oxidative-stress related lncRNA signature predicts the prognosis of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is a primary malignant tumour of tubular epithelial origin and is most common in the urinary tract. Growing evidence suggests that oxidative stress (OS), generates high levels of reactive oxygen species (ROS) and free radicals, and plays a critical role in cancer in humans. However, the predictive value of OS-related long non-coding RNAs (lncRNAs) in ccRCC remains unclear. We constructed a predictive signature of survival based on OS-related lncRNAs that were obtained from The Cancer Genome Atlas (TCGA-KIRC), to predict the prognosis of patients with ccRCC. The signature comprised seven lncRNAs: SPART-AS1, AL162586.1, LINC00944, LINC01550, HOXB-AS4, LINC02027, and DOCK9-DT. OS-related signature of lncRNAs had diagnostic efficiency higher than that of clinicopathological variables, with an area of 0.794 under the receiver operating characteristic curve. Additionally, the nomogram based on risk scores and clinicopathological variables (age, gender, grade, stage, M-stage, and N-stage) showed strong predictive performance. Patients with high-risk were found to be more sensitive to the therapeutic drugs ABT.888, AICAR, MS.275, sunitinib, AZD.2281, and GDC.0449. Our constructed the predictive signature can independently predict the prognosis of patients with ccRCC; however, the underlying mechanism needs further investigation.

Molecular subtype identification and signature construction based on Golgi apparatus-related genes for better prediction prognosis and immunotherapy response in hepatocellular carcinoma

Introduction

The Golgi apparatus (GA) is the center of protein and lipid synthesis and modification in normal cells and is involved in regulating various cellular process as a signaling hub, the dysfunction of which can lead to the development of various pathological conditions, including tumors. Mutations in Golgi apparatus-related genes (GARGs) are prevalent in most tumors, and their mutations can make them pro-tumor metastatic. The aim of this study was to analyze the predictive role of GARGs in the prognosis and immunotherapeutic outcome of hepatocellular carcinoma.

Methods

We used TCGA, GEO and ICGC databases to classify hepatocellular carcinoma samples into two molecular subtypes based on the expression of GARGs. Signature construction was then performed using GARGs, and signature genes were selected for expression validation and tumor phenotype experiments to determine the role of GARGs in the prognosis of hepatocellular carcinoma.

Results

Using the TCGA, GEO and ICGC databases, two major subtypes of molecular heterogeneity among hepatocellular carcinoma tumors were identified based on the expression of GARGs, C1 as a high-risk subtype (low survival) and C2 as a low-risk subtype (high survival). The high-risk subtype had lower StromalScore, ImmuneScore, ESTIMATEScore and higher TumorPurity, indicating poorer treatment outcome for ICI. Meanwhile, we constructed a new risk assessment profile for hepatocellular carcinoma based on GARGs, and we found that the high-risk group had a worse prognosis, a higher risk of immune escape, and a higher TP53 mutation rate. Meanwhile, TME analysis showed higher tumor purity TumorPurity and lower ESTIMATEScore, ImmuneScore and StromalScore in the high-risk group. We also found that the high-risk group responded more strongly to a variety of anticancer drugs, which is useful for guiding clinical drug use. Meanwhile, the expression of BSG was experimentally found to be associated with poor prognosis of HCC. After interfering with the expression of BSG in HCC cells SMMC-7721, the proliferation and migration ability of HCC cells were significantly restricted.

Discussion

The signature we constructed using GARGs can well predict the prognosis and immunotherapy effect of hepatocellular carcinoma, providing new ideas and strategies for the treatment of hepatocellular carcinoma.

Expression, regulating mechanism and therapeutic target of KIF20A in multiple cancer

Kinesin family member 20A (KIF20A) is a member of the kinesin family. It transports chromosomes during mitosis, plays a key role in cell division. Recently, studies proved that KIF20A was highly expressed in cancer. High expression of KIF20A was correlated with poor overall survival (OS). In this review, we summarized all the cancer that highly expressed KIF20A, described the role of KIF20A in cancer. We also organized phase I and phase II clinical trials of KIF20A peptides vaccine. All results indicated that KIF20A was a promising therapeutic target for multiple cancer.

High expression of KIF20A in bladder cancer as a potential prognostic target for poor survival of renal cell carcinoma

Urinary system tumors are malignant tumors, including renal cancer and bladder cancer. however, molecular target of them remains unclear. GSE14762 and GSE53757 were downloaded from GEO database to screen differentially expressed genes (DEGs). Weighted gene co-expression network analysis was performed. Gene Ontology (GO) and Kyoto encyclopedia of genes and genomes were used for enrichment analysis. Gene ontology and Kyoto encyclopedia of genes and genomes analyses were performed on whole genome, as formulated by gene set enrichment analysis. Survival analysis was also performed. Comparative toxicogenomics database was used to identify diseases most associated with hub genes. A total of 1517 DEGs were identified. DEGs were mainly enriched in cancer pathway, HIF-1 signaling pathway, organic acid metabolism, glyoxylate and dicarboxylate metabolism, and protein homodimerization activity. Ten hub genes (TPX2, ASPM, NUSAP1, RAD51AP1, CCNA2, TTK, PBK, MELK, DTL, kinesin family member 20A [KIF20A]) were obtained, which were up-regulated in tumor tissue. The expression of KIF20A was related with the overall survival of renal and bladder cancer. KIF20A was up-regulated in the tumor tissue, and might worsen the overall survival of bladder and kidney cancer. KIF20A could be a novel biomarker of bladder and kidney cancer.

Classification molecular subtypes of hepatocellular carcinoma based on PRMT-related genes

Background: Recent studies highlighted the functional role of protein arginine methyltransferases (PRMTs) catalyzing the methylation of protein arginine in malignant progression of various tumors. Stratification the subtypes of hepatocellular carcinoma (HCC) is fundamental for exploring effective treatment strategies. Here, we aim to conduct a comprehensive analysis of PRMTs with bioinformatic tools to identify novel biomarkers for HCC subtypes classification and prognosis prediction, which may be potential ideal targets for therapeutic intervention. Methods: The expression profiling of PRMTs in HCC tissues was evaluated based on the data of TCGA-LIHC cohort, and further validated in HCC TMA cohort and HCC cell lines. HCC was systematically classified based on PRMT family related genes. Subsequently, the differentially expressed genes (DEGs) between molecular subtypes were identified, and prognostic risk model were constructed using least absolute shrinkage and selection operator (LASSO) and Cox regression analysis to evaluate the prognosis, gene mutation, clinical features, immunophenotype, immunotherapeutic effect and antineoplastic drug sensitivity of HCC. Results: PRMTs expression was markedly altered both in HCC tissues and HCC cell lines. Three molecular subtypes with distinct immunophenotype were generated. 11 PRMT-related genes were enrolled to establish prognostic model, which presented with high accuracy in predicting the prognosis of two risk groups in the training, validation, and immunotherapy cohort, respectively. Additionally, the two risk groups showed significant difference in immunotherapeutic efficacy. Further, the sensitivity of 72 anticancer drugs was identified using prognostic risk model. Conclusion: In summary, our findings stratified HCC into three subtypes based on the PRMT-related genes. The prognostic model established in this work provide novel insights into the exploration of related therapeutic approaches in treating HCC.

Integrated Analysis of the Role of Enolase 2 in Clear Cell Renal Cell Carcinoma

Enolase 2 (ENO2) has increasingly been documented in multiple cancers in recent years. However, the role of ENO2 in clear cell renal carcinoma (ccRCC) has not been fully explored. In the present study, open-access data were downloaded from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and the Human Protein Atlas (HPA) databases. All statistical analyses were performed in R and GraphPad Prism 8 softwares. Results showed that ENO2 was overexpressed in ccRCC tissues and cell lines and correlated with worse clinical features and prognosis. In vitro experiments indicated that the inhibition of ENO2 could hamper the malignant behaviors of ccRCC cells. Gene Set Enrichment Analysis showed that epithelial-mesenchymal transition, KRAS signaling, inflammatory response, angiogenesis, hypoxia, and WNT/β-catenin pathways were upregulated in the ENO2 high-expression group; whereas adipogenesis, DNA repair, and androgen response pathways were downregulated. Immune infiltration analysis indicated that patients with high ENO2 levels might have higher M2 macrophages and lower γβ T cells in the tumor microenvironment, which may account to some extent for the worse prognosis of ENO2. Moreover, it was found that patients with low and high ENO2 expression might be more sensitive to PD-1 therapy and CTLA-4 therapy, respectively. In addition, patients with high ENO2 expression showed lower sensitivity to common chemotherapy drugs for ccRCC, including axitinib, cisplatin, gemcitabine, pazopanib, sunitinib, and temsirolimus. Overall, these results suggest that ENO2 is a potential prognosis biomarker of ccRCC and could affect the malignant biological behavior of cancer cells, highlighting its value as a potential therapeutic target.

Identification of the hub genes related to adipose tissue metabolism of bovine

Due to the demand for high-quality animal protein, there has been consistent interest in how to obtain more high-quality beef. As well-known, the adipose content of beef has a close connection with the taste and quality of beef, and cattle with different energy or protein diet have corresponding effects on the lipid metabolism of beef. Thus, we performed weighted gene co-expression network analysis (WGCNA) with subcutaneous adipose genes from Norwegian red heifers fed different diets to identify hub genes regulating bovine lipid metabolism. For this purpose, the RNA sequencing data of subcutaneous adipose tissue of 12-month-old Norwegian red heifers (n = 48) with different energy or protein levels were selected from the GEO database, and 7,630 genes with the largest variation were selected for WGCNA analysis. Then, three modules were selected as hub genes candidate modules according to the correlation between modules and phenotypes, including pink, magenta and grey60 modules. GO and KEGG enrichment analysis showed that genes were related to metabolism, and participated in Rap, MAPK, AMPK, VEGF signaling pathways, and so forth. Combined gene interaction network analysis using Cytoscape software, eight hub genes of lipid metabolism were identified, including TIA1, LOC516108, SNAPC4, CPSF2, ZNF574, CLASRP, MED15 and U2AF2. Further, the expression levels of hub genes in the cattle tissue were also measured to verify the results, and we found hub genes in higher expression in muscle and adipose tissue in adult cattle. In summary, we predicted the key genes of lipid metabolism in the subcutaneous adipose tissue that were affected by the intake of various energy diets to find the hub genes that coordinate lipid metabolism, which provide a theoretical basis for regulating beef quality.

Screening of Differentially Expressed Iron Death-Related Genes and the Construction of Prognosis Model in Patients with Renal Clear Cell Carcinoma

Objective

In this study, we used the TCGA database and ICGC database to establish a prognostic model of iron death associated with renal cell carcinoma, which can provide predictive value for the identification of iron death-related genes and clinical treatment of renal clear cell carcinoma.

Methods

The gene expression profiles and clinical data of renal clear cell carcinoma and normal tissues were obtained in the TCGA database and ICGC database, and the differential genes related to iron death were screened out. The differential genes were screened out by single and multifactor Cox risk regression model. R software, "edge" package (version 4.0), was used to identify the DELs of 551 transcriptional gene samples and 522 clinical samples. The risk prediction model with genes was established to analyze the correlation between the genes in the established model and clinical characteristics, Through the final screening of iron death related genes, it can be used to predict the prognosis of renal clear cell carcinoma and provide advice for clinical targeted therapy.

Results

Seven iron death differential genes (CLS2, FANCD2, PHKG2, ACSL3, ATP5MC3, CISD1, PEBP1) associated with renal clear cell carcinoma were finally screened and were refer to previous relevant studies. These genes are closely related to iron death and have great value for the prognosis of renal clear cell carcinoma.

Conclusion

Seven iron death genes can accurately predict the survival of patients with renal clear cell carcinoma.

Targeted metabolomics analysis of bile acids and cell biology studies reveal the critical role of glycodeoxycholic acid in buffalo follicular atresia

The follicular fluid of mammals has a high abundance of bile acids and these have proven to be closely related to the follicular atresia. However, the origin and content of bile acids in follicular fluid and its mechanisms on follicular atresia remain largely unknown. In this work, we analyzed the origin of bile acids in buffalo follicles by using cell biology studies, and quantified the subspecies of bile acids in follicular fluid from healthy follicles (HF) and atretic follicles (AF) by targeted metabolomics. The function of differential bile acids on follicular granulosa cells was also studied. The results showed that the bile acids transporters were abundantly expressed in ovarian tissues, but the rate-limiting enzymes were not, which was consistent with the inability of cultured follicular cells to convert cholesterol into bile acids. Targeted metabolomics analysis revealed thirteen differential subspecies of bile acids between HF and AF. The free bile acids were significant down-regulated and their conjugated forms were significantly up-regulated in AF as compared to HF. Finally, cell biological validation found a specific differentially conjugated bile acid, glycodeoxycholic acid (GDCA), which could promote follicular granulosa cell apoptosis and reduce steroid hormone secretion. In summary, our studies suggest that bile acids in buffalo follicles are transported from the blood rather than being synthesized within the follicles. The conjugated bile acids such as GDCA, accumulate in buffalo follicles, and may accelerate atresia by promoting apoptosis of granulosa cells and inhibiting steroid hormone production. These results will provide new clues for studying the physiological role and mechanism of bile acids involved in buffalo follicular atresia.

Identification and Validation of Genomic Subtypes and a Prognostic Model Based on Antigen-Presenting Cells and Tumor Microenvironment Infiltration Characteristics in Hepatocellular Carcinoma

Currently, the prognosis of hepatocellular carcinoma (HCC) is poor, and there is a lack of effective targeted therapy. As key mediators of the immune response, the prognostic value of antigen-presenting cells (APCs) in HCC still remains unclear. In this study, we aimed to identify APC-related genomic subtypes and develop a novel prognostic model in HCC. Our results indicated that overall survival (OS) and the level of immune infiltration significantly differed between different APC clusters. By analyzing the gene expression profile between APC clusters, APC-related genomic subtypes were identified. There was a significant difference in OS and tumor microenvironment infiltration in HCC patients with different genomic subtypes. With the aid of genomic subtypes, significantly differentially expressed genes were screened to generate a novel prognostic model. The risk score of the model had a significant positive correlation with APCs and was associated with immune checkpoint expressions. Through the clinical cohort collected from the First Affiliated Hospital of Wenzhou Medical University, the prognostic value of the risk score was further validated. Moreover, after the risk score and clinical characteristics were combined, a nomogram was constructed to evaluate the prognosis for HCC patients. In conclusion, we mainly identified the APC-related genomic subtypes and generated a novel prognostic model to improve the prognostic prediction and targeted therapy for HCC patients.

Integrated Analysis of Transcriptome Data Revealed AURKA and KIF20A as Critical Genes in Medulloblastoma Progression

Medulloblastoma is the neuroepithelial tumor with the highest degree of malignancy in the central nervous system, accounting for about 8% to 10% of children’s brain tumors. It has a high degree of malignancy and is easily transmitted through cerebrospinal fluid, with a relatively poor prognosis. Although medulloblastoma has been widely studied and treated, its molecular mechanism remains unclear. To determine which gene plays a crucial role in medulloblastoma development and progression, we analyzed three microarray datasets from Gene Expression Omnibus. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were used to detect and evaluate differentially expressed genes. Protein interaction network was established, and the hub genes were determined in cytoHubba through various assessment methods, while the target genes were screened out using survival analysis. Ultimately, human medulloblastoma samples were utilized to confirm target gene expression. In conclusion, This study found that aurora kinase A (AURKA) and kinesin family member 20A (KIF20A) may be involved in the initiation and development of medulloblastoma, have a close association with prognosis, and may become a potential therapeutic target and prognostic marker of MED.

LncRNA ARAP1-AS1 Promotes Bladder Cancer Development by Regulating the miR-3918/KIF20A Axis

This study is to clarify the effect of the long non-coding RNA ArfGAP with RhoGAP domain, ankyrin repeat and PH domain 1-antisense RNA 1 (ARAP1-AS1)/microRNA (miR)-3918/kinesin family member 20A (KIF20A) on bladder cancer cell function. ARAP1-AS1, miR-3918, and KIF20A expression levels in bladder cancer cells were determined using quantitative reverse transcription-polymerase chain reaction. The effects of ARAP1-AS1, miR-3918, and KIF20A on bladder cell activity, proliferation, apoptosis, and in vivo growth were examined using the cell counting kit-8, colony formation, caspase-3 activity, and xenograft tumor growth assays, respectively, in nude mice. The binding relationships among ARAP1-AS1, miR-3918, and KIF20A were analyzed using luciferase and RNA immunoprecipitation assays. ARAP1-AS1 and KIF20A were overexpressed in bladder cancer, while miR-3918 was underexpressed. The downregulation of ARAP1-AS1 or KIF20A expression significantly inhibited the viability and proliferation of cancer cells and promoted apoptosis, whereas low expression of miR-3918 or high expression of ARAP1-AS1/KIF20A showed the opposite effect. miR-3918 was sponged by ARAP1-AS1, and targeted KIF20A. In addition, miR-3918 expression was inversely correlated with ARAP1-AS1 and KIF20a expression levels in bladder cancer tissues. In addition, the rescue experiment showed that interference with miR-3918 could reverse the effect of low ARAP1-AS1 or KIF20A expression on bladder cancer cell malignancy. ARAP1-AS1 facilitates the malignant behavior of bladder cancer cells via the regulation of KIF20A expression by sponging miR-3918.

The kinesin KIF20A promotes progression to castration-resistant prostate cancer through autocrine activation of the androgen receptor

Prostate cancer that recurs following androgen-deprivation therapy is termed castration-resistant, which is incurable and is marked by reactivation of androgen receptor (AR) signaling. KIF20A, a kinesin with unique structural features, is overexpressed in human castration-resistant prostate cancer (CRPC) compared to androgen-dependent PC and benign tissue. KIF20A has well-described roles in mitotic processes, but it has a less characterized function in vesicle fission and trafficking within Golgi-driven secretory pathways. Stable expression of KIF20A in androgen-dependent PC cells promoted progression to CRPC through the activation of AR signaling in vitro and in vivo. KIF20A expression resulted in the secretion of autocrine factors in the conditioned media that activated AR and caused castration-resistant proliferation of naïve androgen-dependent cells. Pharmacologic disruption of vesicle biogenesis blocked KIF20A-driven castration-resistant proliferation of androgen-dependent PC. KIF20A depletion or treatment with the KIF20A-specific inhibitor, paprotrain, reduced CRPC. These data are the first to establish KIF20A as a driver of CRPC progression through AR activation and as a promising therapeutic target against CRPC.

Identification of KIF23 as a Prognostic Biomarker Associated With Progression of Clear Cell Renal Cell Carcinoma

About 3% of adult cancers are caused by renal cell carcinoma (RCC) and its pathogenesis remains elusive. Among RCC, clear cell renal cell carcinoma (ccRCC) is the predominant histological subtype. Resistance to conventional treatments leaves few treatment options for advanced ccRCC. Although the transcriptome profile of primary ccRCC has been comprehensively summarized, the transcriptome profile of metastatic ccRCC is still lacking. In this study we identified a list of metastasis-related genes and constructing a metastasis-associated prognostic gene signature. By analyzing data from GSE85258 and GSE105288 datasets, 74 genes were identified as metastasis-related genes. To construct prognostic features, we downloaded the expression data of ccRCC from the Cancer Genome Atlas (TCGA). Metastasis-associated genes were initially selected through the LASSO Cox regression analysis and 12 metastasis-related were included to construct prognostic model. Transcriptome profile, patient prognosis, and immune cell infiltration characteristics differed between low- and high-risk groups after grouping according to median risk score. Through explored the functions of differentially expressed genes (DEGs) between the two groups. Kinesin family member 23 (KIF23) was identified as a prognostic marker in ccRCC patients. Furthermore, inhibition of KIF23 expression reduced the proliferation, migration and invasion of ccRCC cells. We further demonstrated that KIF23 promote nuclear translocation of β-catenin in ccRCC cells, which provides novel insight into the functions and molecular machinery of KIF23 in ccRCC.

Identification of potentially functional circular RNAs hsa_circ_0070934 and hsa_circ_0004315 as prognostic factors of hepatocellular carcinoma by integrated bioinformatics analysis

Hepatocellular carcinoma (HCC) is one of the most prevalent cancers worldwide, which has a high mortality rate and poor treatment outcomes with yet unknown molecular basis. It seems that gene expression plays a pivotal role in the pathogenesis of the disease. Circular RNAs (circRNAs) can interact with microRNAs (miRNAs) to regulate gene expression in various malignancies by acting as competitive endogenous RNAs (ceRNAs). However, the potential pathogenesis roles of the ceRNA network among circRNA/miRNA/mRNA in HCC are unclear. In this study, first, the HCC circRNA expression data were obtained from three Gene Expression Omnibus microarray datasets (GSE164803, GSE94508, GSE97332), and the differentially expressed circRNAs (DECs) were identified using R limma package. Also, the liver hepatocellular carcinoma (LIHC) miRNA and mRNA sequence data were retrieved from TCGA and differentially expressed miRNAs (DEMIs) and mRNAs (DEGs) were determined using the R DESeq2 package. Second, CSCD website was used to uncover the binding sites of miRNAs on DECs. The DECs' potential target miRNAs were revealed by conducting an intersection between predicted miRNAs from CSCD and downregulated DEMIs. Third, candidate genes were uncovered by intersecting targeted genes predicted by miRWalk and targetscan online tools with upregulated DEGs. The ceRNA network was then built using the Cytoscape software. The functional enrichment and the overall survival time of these potential targeted genes were analyzed, and a PPI network was constructed in the STRING database. Network visualization was performed by Cytoscape, and ten hub genes were detected using the CytoHubba plugin tool. Four DECs (hsa_circ_0000520, hsa_circ_0008616, hsa_circ_0070934, hsa_circ_0004315) were obtained and six miRNAs (hsa-miR-542-5p, hsa-miR-326, hsa-miR-511-5p, hsa-miR-195-5p, hsa-miR-214-3p, and hsa-miR-424-5p) which are regulated by the above DECs were identified. Then 543 overlapped genes regulated by six miRNAs mentioned above were predicted. Functional enrichment analysis showed that these genes are mostly associated with regulatory pathways in cancer. Ten hub genes (TTK, AURKB, KIF20A, KIF23, CEP55, CDC6, DTL, NCAPG, CENPF, PLK4) have been screened from the PPI network of the 204 survival-related genes. KIF20A, NCAPG, TTK, PLK4, and CDC6 were selected for the highest significance p-values. At the end, a circRNA-miRNA-mRNA regulatory axis was established for five final selected hub genes. This study implies the potential pathogenesis of the obtained network and proposes that the two DECs (has_circ_0070934 and has_circ_0004315) may be important prognostic markers for HCC.

Integrative Pan-Cancer Analysis of KIF15 Reveals Its Diagnosis and Prognosis Value in Nasopharyngeal Carcinoma

Background

KIF15 plays a vital role in many biological processes and has been reported to influence the occurrence and development of certain human cancers. However, there are few systematic evaluations on the role of KIF15 in human cancers, and the role of KIF15 in the diagnosis and prognosis of nasopharyngeal carcinoma (NPC) also remains unexplored. Therefore, this study aimed to conduct a pan-cancer analysis of KIF15 and evaluate its diagnostic and prognostic potential in NPC.

Methods

The expression pattern, prognostic value, molecular function, tumor mutation burden, microsatellite instability, and immune cell infiltration of KIF15 were examined based on public databases. Next, the diagnostic value of KIF15 in NPC was analyzed using the Gene Expression Omnibus (GEO) database and immunohistochemistry (IHC). Kaplan–Meier curves, Cox regression analyses, and nomograms were used to evaluate the effects of KIF15 expression on NPC prognosis. Finally, the effect of KIF15 on NPC was explored by in vitro experiments.

Results

The expression of KIF15 was significantly upregulated in 20 out of 33 cancer types compared to adjacent normal tissue. Kyoto Encyclopedia of Genes and Genomes enrichment (KEGG) analysis showed that KIF15 could participate in several cancer-related pathways. The increased expression level of KIF15 was correlated with worse clinical outcomes in many types of human cancers. Additionally, KIF15 expression was related to cancer infiltration of immune cells, tumor mutation burden, and microsatellite instability. In the analysis of NPC, KIF15 was significantly upregulated based on the GEO database and immunohistochemistry. A high expression of KIF15 was negatively associated with the prognosis of patients with NPC. A nomogram model integrating clinical characteristics and KIF15 expression was established, and it showed good predictive ability with an area under the curve value of 0.73. KIF15 knockdown significantly inhibited NPC cell proliferation and migration.

Conclusions

Our findings revealed the important and functional role of KIF15 as an oncogene in pan-cancer. Moreover, high expression of KIF15 was found in NPC tissues, and was correlated with poor prognosis in NPC. KIF15 may serve as a potential therapeutic target in NPC treatment.

Centromere protein E as a novel biomarker and potential therapeutic target for retinoblastoma

Retinoblastoma is the most common intraocular malignancy during childhood. Currently, there is no effective treatment for metastatic retinoblastoma. We investigated potential biomarkers of retinoblastoma by utilizing three datasets from a public database. Functional enrichment analysis, including gene ontology, Kyoto encyclopedia of genes and genomes, gene set enrichment analysis and variation analysis, suggested that differentially expressed genes in retinoblastoma were enriched in accelerated cell cycle events. Protein-protein interaction analysis constructed a network consisting of six hub genes, including benzimidazoles 1 (BUB1), cyclin dependent kinase 1 (CDK1), centromere protein E (CENPE), kinesin family member 20A (KIF20A), PDZ binding kinase (PBK), and targeting protein for xklp2 (TPX2). Drug sensitivity analysis showed that nelarabine was positively correlated with five hub genes. All six genes were expressed differently in six immune subtypes and were positively correlated with stemness indices in most human cancer types. Since CENPE is the least known hub gene in retinoblastoma, we further analyzed the potential non-coding RNAs and transcription factors that regulate CENPE and built interaction networks of competing endogenous RNA and transcription factors. Immune cell infiltration, especially by plasma and B cells, was enhanced in samples with high CENPE expression. Pan-cancer analysis illustrated that CENPE was highly expressed in a wide range of human tumors. In vitro validation revealed that CENPE was significantly upregulated at both the mRNA and protein levels in retinoblastoma cells. In conclusion, CENPE, along with other hub genes, could serve as a potential biomarker and intervention target for retinoblastoma.

miR-7 regulates the apoptosis of chicken primary myoblasts through the KLF4 gene

1. MicroRNAs (miRNAs) play a vital role in the proliferation, differentiation, and apoptosis of myoblasts. However, the effect of miR-7 on the apoptosis of chicken primary myoblasts (CPMs) and its mechanism is still unclear.2. In this study, the expression of apoptosis marker genes (RAF1, Caspase3, Caspase9, Cytc, Fas) in CPMs was significantly increased after transfection of miR-7 mimic. The expression of the apoptosis marker genes in CPMs was significantly reduced after transfection with miR-7 inhibitor. Flow cytometry showed that the late apoptosis rate of the mimic group was significantly higher than the negative control (NC). The viable cells of the mimic group were significantly lower than the NC. In contrast, inhibition of miR-7 had the opposite effect.3. The dual-luciferase assay showed that the KLF4 was a target gene of miR-7. The rescue experiment showed that the KLF4 gene could attenuate the effect of miR-7 on the expression of apoptosis marker genes in CPMs.4. Determination of the function the KLF4 gene showed that the expression of the apoptosis marker genes in CPMs decreased significantly compared with the NC after its overexpression. Inhibition of KLF4 gene had the opposite effect. Flow cytometry showed that overexpression of the KLF4 gene inhibited early apoptosis of myoblasts (P ≤ 0.01), while interference with the KLF4 gene could promote early apoptosis of myoblasts (P ≤ 0.001).5. The results demonstrated, for the first time, that miR-7 promotes apoptosis in chicken primary myoblasts by regulating the expression of the KLF4 gene.

Identification of a Four Hypoxia-Associated Long Non-Coding RNA Signature and Establishment of a Nomogram Predicting Prognosis of Clear Cell Renal Cell Carcinoma

To identify novel hypoxia-associated long non-coding RNAs (lncRNAs) as potential biomarkers, we developed a risk stratification signature and constructed a prognosis prediction nomogram of clear cell renal cell carcinoma (ccRCC). Hypoxia-related lncRNAs were identified through Pearson correlation analysis between the expression profiles of hypoxia-related differentially expressed genes and lncRNAs from The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC) dataset. Then, a signature of four key lncRNAs (COMETT, EMX2OS, AC026462.3, and HAGLR) was developed. The four lncRNAs were downregulated in high-grade, advanced stage, and high-risk ccRCC. The signature had an independent and long-standing prognosis prediction ability up to a 10-year follow-up. Notably, the risk score was significantly positively correlated with the infiltration abundances of six immune cells from the Tumor IMmune Estimation Resource (TIMER). The gene set enrichment analysis (GSEA) also suggested that the signature was involved in metabolism and tumorigenesis, which were closely related to the hypoxic tumor microenvironment. Ultimately, a nomogram of signature, age, stage, and grade, was built to predict the individual long-term survival possibility. Finally, the expressions of four lncRNAs were validated by quantitative real-time PCR (qRT-PCR). Our study identified a four-lncRNA signature and established a prognostic nomogram that reliably predicts survival in ccRCC. The findings may be beneficial to therapeutic customization and medical decision-making.

Five-gene signature associating with Gleason score serve as novel biomarkers for identifying early recurring events and contributing to early diagnosis for Prostate Adenocarcinoma

Background: Compared to non-recurrent type, recurrent prostate adenocarcinoma (PCa) is highly fatal, and significantly shortens the survival time of affected patients. Early and accurate laboratory diagnosis is particularly important in identifying patients at high risk of recurrence, necessary for additional systemic intervention. We aimed to develop efficient and accurate diagnostic and prognostic biomarkers for new PCa following radical therapy. Methods: We identified differentially expressed genes (DEGs) and clinicopathological data of PCa patients from Gene Expression Omnibus (GEO) datasets and The Cancer Genome Atlas (TCGA) repositories. We then uncovered the most relevant clinical traits and genes modules associated with PCa prognosis using the Weighted gene correlation network analysis (WGCNA). Univariate Cox regression analysis and multivariate Cox proportional hazards (Cox-PH) models were performed to identify candidate gene signatures related to Disease-Free Interval (DFI). Data for internal and external cohorts were utilized to test and validate the accuracy and clinical utility of the prognostic models. Results: We constructed and validated an accurate and reliable model for predicting the prognosis of PCa using 5 Gleason score-associated gene signatures (ZNF695, CENPA, TROAP, BIRC5 and KIF20A). The ROC and Kaplan-Meier analysis revealed the model was highly accurate in diagnosing and predicting the recurrence and metastases of PCa. The accuracy of the model was validated using the calibration curves based on internal TCGA cohort and external GEO cohort. Using the model, patients could be prognostically stratified in to various groups including TNM classification and Gleason score. Multivariate analysis revealed the model could independently predict the prognosis of PCa patients and its utility was superior to that of clinicopathological characteristics. In addition, we fund the expression of the 5 gene signatures strongly and positively correlated with tumor purity but negatively correlated with infiltration CD8+ T cells to the tumor microenvironment. Conclusions: A 5 gene signatures can accurately be used in the diagnosis and prediction of PCa prognosis. Thus this can guide the treatment and management prostate adenocarcinoma.