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Background: Endometrial carcinoma (EC) is one of the common female malignancies. The effectiveness of immunotherapy in treating EC remains to be testified. Methods: In our present study, we explored the underlying mechanism through tumor microenvironment (TME) and immune-related genes in EC. Based on The Cancer Genome Atlas (TCGA) database to screen immune-related differentially expressed genes (DEGs). Then, survival analysis, functional annotations and interpreted interaction network of these genes were further investigated for the underlying regulation mechanisms. Moreover, we used a conjoint Cox regression analysis to built the immune-related prognostic risk signatures and identify the candidate prognostic biomarkers. Based on the risk model, we further explored the predictive value of risk signatures by exploring the tumor-infiltrating immune cells, prognostic immune checkpoints modulators, and checkpoint inhibitors in TME. Results: As a result, we found 799 up-regulated and 139 down-regulated immune-related and differentially expressed genes of EC. Based on the 225 prognostic DEGs, we built two risk models based on key prognostic immune-related genes, which identified respectively for overall survival and disease-free survival. Gene set enrichment analysis revealed immune-related pathways were mostly enriched in gene sets of the low-risk group, and the nomograms were constructed based on the risk models. By analyzing the immune status in low- and high- group of EC patients , we found higher immune cell infiltration and activation in low risk tumor tissues, which might cause lower tumor purity and contribute to better prognosis of EC. By analyzing the immune checkpoint molecules, we found both the expression and immunophenoscore of immune checkpoints PD-1, CTLA4, PD-L1 and PD-L2 increased significantly in low-risk group. In addition, the low-risk group were found display higher tumor mutational burden. Conclusions: Our study suggested that high-immune TME might prevent the progression of EC, which indicated the possibility of immunotherapy to fight against EC.

Cervical cancer (CC) is the fourth commonest cancer in women worldwide. Increasing evidence proves that microRNA (miRNA)-messenger RNA (mRNA) network is involved in CC. In this study, miRNA and mRNA expression profiles were downloaded from The Cancer Genome Atlas (TCGA) database. Differently expressed miRNAs (DE-miRNAs) and mRNAs (DE-mRNAs) were obtained by "Empirical Analysis of Digital Gene Expression Data in R (EdgeR)" package. Then, functional analyses were conducted. With Cytoscape software, a protein-protein interaction (PPI) network was established to identify hub genes that were used for building an miRNA-hub gene network. Next, a prognostic signature based on hub genes was constructed by Cox regression analysis, and its prognostic value was assessed by a nomogram. Finally, the relationship between immune cell infiltration and the three genes in the prognostic model was investigated by using the CIBERSORT algorithm. We screened out 5096 DE-mRNAs and 114 DE-miRNAs between healthy cervical and CC tissues. Then, 102 target DE-mRNAs of upregulated DE-miRNAs and 150 target DE-mRNAs of downregulated DE-miRNAs were obtained. PPI network demonstrated 20 hub nodes with higher connectivity. DE-mRNAs were mostly enriched in pathways in cancer, cell cycle, and proteoglycans in cancer. The miRNA-hub gene network showed that most hub genes could be potentially modulated by miR-200c-3p, miR-23b-3p, and miR-106b-5p. Quantitative real-time PCR proved that 10 miRNAs were downregulated and 6 mRNAs were upregulated markedly in CC tissues. Furthermore, a prognostic signature was established based on enhancer of zeste homolog 2 (EZH2), Fms-related tyrosine kinase 1 (FLT1), and glyceraldehyde 3-phosphate dehydrogenase (GAPDH). The area under the curve value of the 5-year receiver operating characteristic curve was 0.609. The three genes were also found to be related to the infiltration of six types of immune cells, including dendritic cells, macrophages M0 and M1, mast cells, and monocytes. In conclusion, the development of CC is regulated by the miRNA-mRNA network we proposed in this study.

Background Long noncoding RNAs (lncRNAs) have been identified to participate in tumorigenesis. However, the underlying mechanisms of differentially expressed lncRNAs engaged in diseases remain indistinct and need further exploration. Methods Raw data files downloaded from TCGA and GEO dataset were used to analyze the differentially expressed lncRNAs and LINC00565 was picked out as the potential oncogene. qRT-PCR was used to analyze the LINC00565 level in ovarian tissues and cell lines. Subsequently, the selected ovarian tumor cells were then transfected with LINC00565 siRNA by Lipofectamine 2000 and the cell cycle was detected by flow cytometry. Effect of LINC00565 on tumor growth and cell cycle was verified by tumor formation assay in nude mice. The mechanism of LINC00565 involving in cell cycle regulation was further explored by Western blot. Results In this research, we discovered that LINC00565, a novel lncRNA, was highly expressed in ovarian cancer (OC). LINC00565 expression level was negatively associated with outcomes of OC patients. Further analysis showed that LINC00565 expression was closely correlated to tumor size, FIGO stage, but not related to other clinical features. In vitro experiments indicated that knockdown of LINC00565 significantly inhibited proliferative, invasive and migratory abilities of ovarian cancer cells. Besides, knockdown of LINC00565 can induce cell cycle arrest in G0/G1 phase. In addition, in vivo assay showed that low expression of LINC00565 inhibited the growth of OC. Further study found that LINC00565 knockdown markedly downregulated the protein expressions of CyclinD1, CyclinE1 and CDK4, but upregulated the expression of P16 and P21. Subsequently, we confirmed that LINC00565 promoted the progression of OC via upregulating GAS6, which has been confirmed to promote tumor progression. Conclusion In summary, our study firstly reported that the LINC00565 functioned as an oncogene to promote the progression of OC by interacting with GAS6.

Competing endogenous RNA (ceRNA) network is dysregulated in the initiation and progression of tumors. In the present study, we explored the regulatory mechanism of ceRNA in endometrial carcinoma (EC) and the potential key molecules with potential value in the diagnosis, treatment, and prognosis of EC. The long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) expression profiles (552 EC tissues and 35 nontumor tissues) and microRNAs (miRNAs) expression profiles (546 EC tissues and 33 nontumor tissues) were downloaded from The Cancer Genome Atlas database to identify differentially expressed RNAs (DERNAs) in EC. An integrated bioinformatics analysis was used to construct an EC-specific ceRNA network and select key molecules. As a result, 96 differentially expressed lncRNAs (DElncRNAs), 29 differentially expressed miRNAs (DEmiRNAs), and 77 differentially expressed mRNAs (DEmRNAs) were identified. An EC-specific ceRNA network was built based on nine DElncRNAs significantly associated with overall survival. CCNB1 was found as a key gene in EC through the weighted gene coexpression network analysis and protein-protein interaction network analysis. Our ceRNA network showed C2orf48 and LINC00483 might upregulate CCNB1 via competing with miR-183. In addition, we found a subnetwork which contained survival-associated DERNAs (AC110491.1, LINC00483-miR-192-GRHL1). The results of reverse transcription quantitative polymerase chain reaction supported the relative expressions of C2orf48, LINC00483 were upregulated and that of AC110491.1 was downregulated in EC. We further found C2orf48 was upregulated in serous EC, endometrioid EC, and mixed serous and endometrioid EC. LINC00483 was upregulated in mixed serous and endometrioid EC compared with that in the normal tissues according to UALCAN database. In addition, candidate small molecular drugs were screened out by ConnectivityMap based on the 77 DEmRNAs in the ceRNA network. Eventually, C2orf48, LINC00483, and AC110491.1 were identified as three key lncRNAs in EC.

Background: Chemotherapy resistance remains a barrier in improving the prognosis of epithelial ovarian cancer (EOC), but its mechanism remains to be elucidated. ALKBH5 has been recently proven to be an RNA N6-methyladenosine (m6A) demethyltransferase associated with various cancers, but its role in cancer therapeutic resistance remains unclear. This study aimed to investigate the role of AlkB homolog 5 (ALKBH5) in platinum-resistant EOC.Methods: Functional assays were performed both in vitro and in vivo. RNA sequencing (RNA-seq), m6A-modified RNA immunoprecipitation sequencing (MeRIP-seq), chromatin immunoprecipitation, RNA immunoprecipitation, and luciferase reporter and actinomycin-D assays were performed to investigate RNA/RNA interaction and m6A modification of the ALKBH5-HOXA10 loop.Results: ALKBH5 was upregulated in platinum-resistant EOC and promoted cancer cell cisplatin resistance both in vivo and in vitro. Notably, HOXA10 was found to be the upstream transcription factor of ALKBH5 and formed a loop with ALKBH5., and its overexpression facilitated EOC cell chemoresistance both in vivo and in vitro. HOXA10 overexpression was found to facilitate EOC cell chemoresistance both in vivo and in vitro. Collective results of MeRIP-seq and RNA-seq showed that JAK2 is an m6A-modified gene targeted by ALKBH5. The JAK2/STAT3 signaling pathway was activated by overexpression of the ALKBH5-HOXA10 loop, and this resulted in EOC chemoresistance. Cell sensitivity to cisplatin was rescued by ALKBH5 and HOXA10 knockdown or inhibition of the JAK2/STAT3 signaling pathway in EOC cells overexpressing ALKBH5-HOXA10.Conclusions: The ALKBH5-HOXA10 loop jointly activates the JAK2/STAT3 signaling pathway by mediating JAK2 m6A demethylation, promoting EOC resistance to platinum. Thus, inhibition of the expression of the ALKBH5-HOXA10 loop maybe a potential strategy to overcome platinum resistance in EOC.

Background: Uterine Corpus Endometrial Carcinoma (UCEC) is the most common gynecological cancer. Here, we have investigated the significance of immune-related genes in predicting the prognosis and response of UCEC patients to immunotherapy and chemotherapy.Methods: Based on TCGA database, the single-sample gene-set enrichment analysis (ssGSEA scores) was utilized to obtain enrichment of 29 immune signatures. Univariate, multivariate Cox regression and LASSO regression analyses were performed to generate an immune-related prognostic signature (IRPS). The biological functions of IRPS-associated genes were evaluated using GSEA, TIMER Database analysis, Mutation analysis, IPS analysis, Gene Expression Profiling Interactive Analysis (GEPIA), Genomics of Drug Sensitivity in Cancer (GDSC) and Immune Cell Abundance Identifier (ImmuCellAI). Potential small molecule drugs for UCEC were predicted using the connectivity map (Cmap). The mRNA and protein expression levels of IRPS-associated genes were tested via quantitative real-time PCR (qPCR) and immunohistology.Results: Two immune-related genes (CCL13 and KLRC1) were identified to construct the IRPS. Both genes were related to the prognosis of UCEC patients (PConclusion: IRPS can be utilized to predict the prognosis of UCEC patients and provide valuable information about their therapeutic response to immunotherapy and chemotherapy.

Backgrounds：Platinum-resistance remains a challenge to recurrence and metastasis of epithelial ovarian cancer (EOC) and the mechanisms are unidentified. Tumor microenvironment (TME) and chemokine might play a key role in tumor chemoresistance. This study is designed to reveal the important role of CXCL-2 in causing EOC platinum-resistance. Materials and Methods: Differently expressed chemokines were selected based on the GSE114206 dataset of GEO database. Chemokines levels of platinum-sensitive and platinum-resistant EOC. Cell assays were performed and the cell stem characteristics were investigated for exploring the roles of CXCL-2 in EOC chemoresistance. We further explored the downstream signaling pathway regulated by CXCL-2 by detecting the expression of related molecules and rescue assay with the signaling inhibitor.Results: CXCL-2, CXCL-11 and CXCL-13 were found up-regulated in platinum-resistant EOC based on GSE114206 databases, and CXCL-2 was identified as key chemokine by validation. The cell assays showed overexpressing CXCL-2 and co-culturing with recombinant human CXCL-2 promoted cancer cell chemoresistance. Conversely, knocking down CXCL-2 and co-culturing with neutralizing antibody to CXCL-2 reduced cisplatin-resistance in cisplatin-resistant EOC cells. CXCL-2 levels regulated the stemness of cancer cells and activated ataxia telangiectasia and Rad3-related (ATR)/cell cycle checkpoint kinase1 (CHK1) signaling pathway. The cancer cell chemoresistance can be saved by CXCL-2 receptor inhibitor (SB225002) and CHK1 inhibitor (SAR-020106) in vitro. Conclusion: These results identified a CXCL-2 mediated platinum-resistance mechanism in EOC, and provided a novel target for chemoresistance prevention and treatment strategies.

Background Abnormal gene methylation is crucial for tumor progression. This study explored a cluster of methylation-driven genes involved in cervical squamous cell carcinoma (CESC). Methods The data on RNA expression, methylation and clinical outcomes of CESC patients were downloaded from The Cancer Genome Atlas (TCGA) database. Protein-protein interaction (PPI) network was constructed. Gene Ontology (GO) and KEGG analyses were performed to identify the biological functions of methylation-driven genes, and univariable and multivariate Cox analyses to screen out the key prognostic genes. A risk signature was established and its predictive value was evaluated with Kaplan-Meier and ROC curves. The key genes were further investigated by Cox regression analyses, gene set enrichment analysis (GSEA), and methylation site analysis. Additionally, "rms" package was used for establishing nomogram and calibrate curve. Results We found 144 differentially expressed methylation-driven genes. A risk model was constructed with three key prognostic genes (ITGA5, HHEX and S1PR4). The risk score was an independent risk factor for CESC prognosis. Lowly-expressed and hypermethylated ITGA5, highly-expressed and hypomethylated HHEX and S1PR4 were associated with better CESC prognosis. The methylation sites and biological functions enriched in ITGA5, HHEX and S1PR4 were uncovered. Additionally, the nomogram also validated the performance of risk model. Conclusions Methylation-driven ITGA5, HHEX and S1PR4 are associated with CESC development. The three genes might serve as potential targets in the treatment of CESC.

Background: Many studies have well supported the close relationship between miRNA and endometrial cancer (EC). This bioinformatic study, compared with other similar studies, confirmed a new miRNA-mRNA regulatory network to investigate the miRNA-mRNA regulatory network and the prognostic biomarkers in EC. Methods: We downloaded RNA-seq and miRNA-seq data of endometrial cancer from the TCGA database, and then we used EdegR package to screen differentially expressed miRNAs and mRNAs (DE-miRNAs and DE-mRNAs). The differentially expressed genes (DEGs) were identified and their functions were predicted using the functional and pathway enrichment analysis. Protein–protein interaction (PPI) network was established using STRING database, and the hub genes were verified by Gene Expression Profiling Interactive Analysis (GEPIA). Then, we constructed a regulatory network of EC-associated miRNAs and hub genes by Cytoscape, and determined the expression of unexplored miRNAs in EC tissues and normal adjacent tissues by quantitative Real-Time PCR (qRT-PCR). A prognostic signature model and a predictive nomogram were constructed. Finally, we explored the association between the prognostic model and the immune cell infiltration. Results: 11531 DE-mRNAs and 236 DE-miRNAs, as well as 275 and 118 candidate DEGs for upregulated and downregulated DE-miRNAs were screened out. These DEGs were significantly concentrated in FOXO signaling pathway, cell cycle and Focal adhesion. Among the 20 hub genes identified, 17 exhibited significantly different expression compared with normal tissues. The miRNA-mRNA network included 5 downregulated and 13 upregulated DE-miRNAs . qRT-PCR proved that the expression levels of miRNA-18a-5p, miRNA-18b-5p, miRNA-449c-5p and miRNA-1224-5p and their target genes, NR3C1, CTGF, MYC, and TNS1 were consistent with our predictions. Univariate and multivariate Cox proportional hazards regression analyses of the hub genes revealed that NR3C1, EZH2, and GATA4 showed a significant prognostic value. We identified the three-gene signature as an independent prognostic indicator for EC ( p =0.022，HR=1.321, 95% CI: 1.041-1.675) and these genes were closely related to eight types of immune infiltration cells. Conclusion: Our study revealed the mechanisms of the carcinogenesis and progression of EC.

Aims Cancer Stem Cells (CSCs) refers to heterogeneous tumor cells retaining the abilities of self-renewal and differentiation. This study used mRNAsi, which is an index to describe the similarity between tumor cells and CSCs, to define genes involved in endometrial carcinoma. Materials and methods The mRNA expression profiles of 552 tumor samples and 23 non-tumor samples were calculated for differentially expressed genes. WGCNA was utilized to construct gene co-expression networks and classify screened genes into different modules. Univariate and multivariate Cox regression models were performed to identify and construct the prognostic model. Time-dependent receiver operating characteristic (ROC), Kaplan–Meier curve, multivariate Cox regression analysis, and nomogram were used to assess the prognostic capacity of the six-gene signature. The screened genes were further validated by GEO ( GSE17025 ) and qRT-PCR in EC tissues. Key findings 2573 upregulated and 1890 downregulated genes were identified. A total of 35 genes in the turquoise module were identified as key genes. With multivariate analysis, six genes (DEPDC1, FAM83D, NCAPH, SPC25, TPX2, and TTK) up-regulated in endometrial carcinoma were identified, and their higher expression was associated with a higher stage/age/grade. Moreover, ROC and Kaplan-Meier plots indicated these genes had a high prognostic value for EC. A nomogram was constructed for clinical use. In addition, we explored the pathogenesis involving six genes. The results showed that these genes may become pathogenic as their copy numbers changes and methylation level reduces. Finally, GSEA revealed these genes had a close association with cell cycle, etc. Significance These findings may provide new insights into the treatment of diseases.

Rationale: N6-methyladenosine (m6A) mRNA methylation is the most abundant chemical posttranscriptional modification in mRNA and is involved in the regulation of a number of biological processes. Insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1) has recently been reported as having the capacity to recognize m6A sites in mRNA and plays a role in regulating mRNA metabolization. However, it is unclear which genes IGF2BP1 targets to identify m6A sites and what are their respective functions in endometrial cancer (EC). Methods: Quantitative PCR, western blot and immunohistochemistry were used to measure IGF2BP1 expression in EC cell lines and tissues. Xenograft experiments were performed to examine the in vivo role of IGF2BP1 in EC cell growth. RNA-binding protein immunoprecipitation sequencing, methylated RNA-binding protein immunoprecipitation sequencing and RNA-sequencing were also conducted to identify potential IGF2BP1 targets involved in EC regulation. Co-immunoprecipitation and mass spectrometry were used to identify IGF2BP1-interacting proteins. Results: IGF2BP1 expression increased in EC, and high expression of this protein correlated with poor prognosis. IGF2BP1 overexpression/knockdown can promote (and inhibit) cell proliferation and regulate the tumor cell cycle and cancer progression, both in vivo and in vitro. Mechanistically, IGF2BP1 can recognize m6A sites in the 3' untranslated region (3'UTR) of Paternally Expressed Gene 10 (PEG10) mRNA and recruits polyadenylate-binding protein 1 (PABPC1) to enhance PEG10 mRNA stability, which consequently promotes PEG10 protein expression. Additionally, it would appear that a large number of PEG10 proteins bind p16 and p18 gene promoter sequences, thereby repressing expression and accelerating the cell cycle. Conclusion: This investigation found that IGF2BP1 has a crucial role in the m6A-dependent regulatory mechanism for endometrial cancer. This study provides new insights into our understanding of disease progression and provides another potential route for understanding biological functions.

Background Endometrial cancer is the fourth most common cancer in women. The death rate for endometrial cancer has increased. Glycolysis of cellular respiration is a complex reaction and is the first step in most carbohydrate catabolism, which was proved to participate in tumors. Methods We analyzed the sample data of over 500 patients from TCGA database. The bioinformatic analysis included GSEA, cox and lasso regression analysis to select prognostic genes, as well as construction of a prognostic model and a nomogram for OS evaluation. The immunohistochemistry staining, survival analysis and expression level validation were also performed. Maftools package was for mutation analysis. GSEA identified Glycolysis was the most related pathway to EC. qRT-PCR verified the expression level of hub gene in clinical samples. Results According to the prognostic model using the train set, 9 glycolysis-related genes including B3GALT6, PAM, LCT, GMPPB, GLCE, DCN, CAPN5, GYS2 and FBP2 were identified as prognosis-related genes. Based on nine gene signature, the EC patients could be classified into high and low risk subgroups, and patients with high risk score showed shorter survival time. Time-dependent ROC analysis and Cox regression suggested that the risk score predicted EC prognosis accurately and independently. Analysis of test and train sets yielded consistent results A nomogram which incorporated the 9-mRNA signature and clinical features was also built for prognostic prediction. Immunohistochemistry staining and TCGA validation showed that expression levels of these genes do differ between EC and normal tissue samples. GSEA revealed that the samples of the low-risk group were mainly concentrated on Bile Acid Metabolism. Patients in the low-risk group displayed obvious mutation signatures compared with those in the high-risk group. The expression levels of B3GALT6, DCN, FBP2 and GYS2 are lower in tumor samples and higher in normal tissue samples. The expression of CAPN5 and LCT in clinical sample tissues is just the opposite. Conclusion This study found that the Glycolysis pathway is associated with EC and screened for hub genes on the Glycolysis pathway, which may serve as new target for the treatment of EC.

Cervical cancer remains a primary cause of female death in developing countries, but its prognosis can be greatly improved if patients are diagnosed earlier. In the present study, we screened the common differentially expressed genes (DEGs) of cervical squamous cell carcinoma (CESC) from dataset GSE7803, Gene Expression Omnibus, and The Cancer Genome Atlas databases. An integrated bioinformatics analysis was performed based on these DEGs for their enrichment in functions and pathways, interaction network, prognostic signature, and candidate molecular drugs. As a result, 164 (114 upregulated and 47 downregulated) DEGs of CESC were identified for further investigation. We then conducted the gene ontology term enrichment and Kyoto Encyclopedia of Genes and Genomes Pathway analyses to reveal the underlying functions and pathways of these DEGs. In the protein-protein interaction network, hub module and hub genes were identified. Five genes of significant prognostic value-DSG2, ITM2A, CENPM, RIBC2, and MEIS2-were identified by prognostic signature analysis and used to construct a risk linear model. Further validation and investigation suggested DSG2 might be a key gene in CESC prognosis. We then identified two candidate small molecules (trichostatin A and tanespimycin) against CESC. Further validation and exploration of these hub genes are warranted for future prospect in clinical applications.

Background: Ovarian cancer (OC) is one of the most lethal gynecological cancers worldwide. The pathogenesis of the disease and outcomes prediction of ovarian cancer patients remain largely unclear. This study aimed to explore the key genes and biological pathways in ovarian carcinoma development, as well as construct a prognostic model to predict patients’ overall survival. Results: We identified 164 up-regulated and 80 down-regulated differentially-expressed genes (DEGs) associated with ovarian cancer. GO term enrichment showed DEGs mainly correlated with spindle microtubes. For KEGG pathways, cell cycle was mostly enriched for the DEGs. The PPI network yielded 238 nodes and 1284 edges. Top three modules and 10 hub genes were further filtered and analyzed. Three candidiate drugs targeting for therapy were also selected. Thirteen OS-related genes were selected and an eight-mRNA model was present to stratify patients into high- and low-risk groups with significantly different survival. Conclusions: The identified DEGs and biological pathways may provide new perspective on the pathogenesis and treatments of OC. The identified 8-mRNA signature has significant clinical implication for outcome prediction and tailored therapy guidance for OC patients.

Additional file 1: Table S1. Primer sequence of genes in qRT-PCR.

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) is the fourth commonest female malignancy worldwide. CESC progresses in immune-microenvironment mainly composed of infiltrating immune and stromal cells. Here, we performed an integrated analysis incorporating the expression profiles from the Cancer Genome Atlas (TCGA) database and scores of immune and stromal cells calculated by Estimation of Stromal and Immune cells in Malignant Tumours using Expression data (ESTIMATE) algorithm. A two-gene signature (CD1C and CD6 genes) was established to predict the prognosis of CESC. Based on this signature, patients were divided into the high- and low-risk groups, and this signature showed good prognostic performance according to the results of Kaplan-Meier analysis and receiver operating characteristic (ROC) analysis in train set and two validation sets. A nomogram was built for evaluating the clinical applicability of this signature. In addition, based on Tumor Immune Estimation Resource (TIMER) database, 2 hub genes showed negative correlations with tumor purity and positive correlations with infiltrating levels of immune filtrating cells. What’s more, we propose new treatment strategies for the two prognostic subtypes. Low- risk patients were found presenting with a higher level of immune checkpoint molecules and showing higher immunogenicity in immunophenoscore (IPS) analysis, which indicated a better response for immunotherapy. Meanwhile, estimated by Genomics of Drug Sensitivity in Cancer (GDSC) database, the high-risk patients showed sensitive responses to five chemotherapy drugs. Finally, 10 candidate small-molecule drugs for CESC were defined. In summary, the CD1C-CD6 signature can accurately predict the prognosis of CESC.

Transgenic APPSwe/PS1dE9 (APP/PS1) mice that overproduce amyloid beta (Aβ) are extensively used in the studies of pathogenesis and experimental therapeutics and new drug screening for Alzheimer's disease (AD). However, most of the current literature uses young or adult APP/PS1 mice. In order to provide a broader view of AD-like phenotype of this animal model, in this study, we systematically analyzed behavioral and pathological profiles of 24-month-old male APP/PS1 mice. Aged APP/PS1 mice had reference memory deficits as well as anxiety, hyperactivity, and social interaction impairment. Consistently, there was obvious deposition of amyloid plaques in the dorsal hippocampus with decreased expression of insulin-degrading enzyme, a proteolytic enzyme responsible for degradation of intracellular Aβ. Furthermore, decreases in hippocampal volume, neuronal number and synaptophysin expression, and astrocyte atrophy were also observed in aged APP/PS1 mice. This finding suggests that aged APP/PS1 mice can well replicate cognitive and noncognitive behavioral abnormalities, hippocampal atrophy, and neuronal and astrocyte degeneration in AD patients, to enable more objective and refined preclinical evaluation of therapeutic drugs and strategies for AD treatment.