Expression of Cell Division Cycle Protein 45 in Tissue Microarrays and the CDC45 Gene by Bioinformatics Analysis in Human Hepatocellular Carcinoma and Patient Outcomes

Validation of CDC45 as a novel biomarker for diagnosis and prognosis of gastric cancer

Background

Cell division cycle protein 45 (CDC45) has been demonstrated to play vital roles in the progression of various malignancies. However, the clinical significance of CDC45 in gastric cancer (GC) remains unreported.

Method

In this study, we employed the TCGA database and the TCGA & GTEx dataset to compare the mRNA expression levels of CDC45 between gastric cancer tissues and adjacent or normal tissues (p < 0.05 was considered statistically significant), which was further validated in multiple datasets including GSE13911, GSE29272, GSE118916, GSE66229, as well as RT-qPCR. Furthermore, we harnessed the Human Protein Atlas (HPA) to evaluate the protein expression of CDC45, which was subsequently verified through immunohistochemistry (IHC). To ascertain the diagnostic utility of CDC45, receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC) were calculated in TCGA database, and further validated it in TCGA & GTEx and GSE66229 datasets. The Kaplan-Meier method was used to reveal the prognostic importance of CDC45 in The Cancer Genome Atlas (TCGA) database and authenticated through the GSE66229, GSE84433, and GSE84437 datasets. Through cBioPortal, we identified co-expressed genes of CDC45, and pursued enrichment analysis. Additionally, we availed gene set enrichment analysis (GSEA) to annotate the biological functions of CDC45.

Results

Differential expression analysis revealed that CDC45 was significantly upregulated at both the mRNA and protein levels in GC (all p < 0.05). Remarkably, CDC45 emerged as a promising prognostic indicator and a novel diagnostic biomarker for GC. In a comprehensive the drug susceptibility analysis, we found that patients with high expression of CDC45 had high sensitivity to various chemotherapeutic agents, among which 5-fluorouracil, docetaxel, cisplatin, and elesclomol were most evident. Furthermore, our findings suggested a plausible association between CDC45 and immune cell infiltration. Enrichment analysis revealed that CDC45 and its associated genes may play crucial roles in muscle biofunction, whereas GSEA demonstrated significant enrichment of gene sets pertaining to G protein-coupled receptor ligand binding and G alpha (i) signaling events.

Conclusion

Our study elucidates that upregulation of CDC45 is intricately associated with immune cell infiltration and holds promising potential as a favorable prognostic marker and a novel diagnostic biomarker for GC.

Deciphering the molecular functionality of Cdc45 in replisomal complex

The members of DHH superfamily have been reported with diverse substrate spectrum and play pivotal roles in replication, repair, and RNA metabolism. This family comprises phosphatases, phosphoesterase and bifunctional enzymes having nanoRNase and phosphatase activities. Cell cycle factor Cdc45, a member of this superfamily, is crucial for movement of the replication fork during DNA replication and an important component of the replisome. The specific protein-protein interactions of Cdc45 with other factors along with helicase moderate the faithful DNA replication process. However, the exact biochemical functions of this factor are still unknown and need further investigation. Here, we studied the biochemical roles of Cdc45 and its molecular interactions within the replisomal complex. The alteration in the level of protein, observed when DNA damage is induced in-vivo, suggests its association with DNA replication stress. We analyzed protein Cdc45, providing new insights about the molecular and biochemical functionality of this replisomal factor.

IGF2BP2 promotes glycolysis and hepatocellular carcinoma stemness by stabilizing CDC45 mRNA via m6A modification

A growing number of studies have shown the prognostic importance of Cell division cycle protein 45 (CDC45) in hepatocellular carcinoma (HCC). This study aims to investigate the biological function and mechanism of CDC45 in HCC. The differential expression and prognostic significance of CDC45 in HCC and normal tissues were analyzed by bioinformatics. CDC45 was knocked down and the biological effects of CDC45 in HCC in vitro and in vivo were measured. Subsequently, using RNA m6A colorimetry and Methylated RNA Immunoprecipitation (MeRIP), the levels of m6A modification of total RNA and CDC45 were evaluated in cells. RIP was applied to establish that CDC45 and insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) interact. A test using actinomycin D was performed to gauge the stability of the CDC45 mRNA. Furthermore, the regulatory role of IGF2BP2 on CDC45 expression in HCC progression was explored by overexpressing IGF2BP2. High expression of CDC45 was correlated with poor prognosis in HCC patients. Knocking down CDC45 inhibited HCC cell proliferation, migration, invasion, EMT, stemness, and glycolysis, and promoted apoptosis, which was verified through in vitro experiments. Additionally, IGF2BP2 was highly expressed in HCC cells, and it was found to interact with CDC45. Knocking down IGF2BP2 resulted in reduced stability of CDC45 mRNA. Moreover, overexpression of IGF2BP2 promoted HCC cell proliferation, migration, invasion, EMT, stemness, and glycolysis, while inhibiting apoptosis, which was reversed by knocking down CDC45. In general, IGF2BP2 promoted HCC glycolysis and stemness by stabilizing CDC45 mRNA via m6A modification. [Figure: see text].

Leader gene identification for digestive system cancers based on human subcellular location and cancer-related characteristics in protein–protein interaction networks

Stomach, liver, and colon cancers are the most common digestive system cancers leading to mortality. Cancer leader genes were identified in the current study as the genes that contribute to tumor initiation and could shed light on the molecular mechanisms in tumorigenesis. An integrated procedure was proposed to identify cancer leader genes based on subcellular location information and cancer-related characteristics considering the effects of nodes on their neighbors in human protein–protein interaction networks. A total of 69, 43, and 64 leader genes were identified for stomach, liver, and colon cancers, respectively. Furthermore, literature reviews and experimental data including protein expression levels and independent datasets from other databases all verified their association with corresponding cancer types. These final leader genes were expected to be used as diagnostic biomarkers and targets for new treatment strategies. The procedure for identifying cancer leader genes could be expanded to open up a window into the mechanisms, early diagnosis, and treatment of other cancer types.

Case Report: Balanced Reciprocal Translocation t (17; 22) (p11.2; q11.2) and 10q23.31 Microduplication in an Infertile Male Patient Suffering From Teratozoospermia

Two chromosomal abnormalities are described in an infertile man suffering from teratozoospermia: balanced reciprocal translocation t (17; 22) (p11.2; q11.2) and a microduplication in the region 10q23.31. Twenty genes located on the breakpoints of translocation (e.g., ALKBH5, TOP3A, SPECC1L, and CDC45) are selected due to their high expression in testicular tissues and might be influenced by chromosome translocation. Four genes located on the breakpoints of microduplication including FLJ37201, KIF20B, LINC00865, and PANK1 result in an increased dosage of genes, representing an imbalance in the genome. These genes have been reported to be associated with developmental disorders/retardation and might be risk factors affecting spermatogenesis. Bioinformatics analysis is carried out on these key genes, intending to find the pathogenic process of reproduction in the context of the translocation and microduplication encountered in the male patient. The combination of the two chromosomal abnormalities carries additional risks for gametogenesis and genomic instability and is apparently harmful to male fertility. Overall, our findings could contribute to the knowledge of male infertility caused by genetic factors.

Identification of Pathologic and Prognostic Genes in Prostate Cancer Based on Database Mining

Background: Prostate cancer (PCa) is an epithelial malignant tumor that occurs in the urinary system with high incidence and is the second most common cancer among men in the world. Thus, it is important to screen out potential key biomarkers for the pathogenesis and prognosis of PCa. The present study aimed to identify potential biomarkers to reveal the underlying molecular mechanisms.

Methods: Differentially expressed genes (DEGs) between PCa tissues and matched normal tissues from The Cancer Genome Atlas Prostate Adenocarcinoma (TCGA-PRAD) dataset were screened out by R software. Weighted gene co-expression network analysis was performed primarily to identify statistically significant genes for clinical manifestations. Protein–protein interaction (PPI) network analysis and network screening were performed based on the STRING database in conjunction with Cytoscape software. Hub genes were then screened out by Cytoscape in conjunction with stepwise algorithm and multivariate Cox regression analysis to construct a risk model. Gene expression in different clinical manifestations and survival analysis correlated with the expression of hub genes were performed. Moreover, the protein expression of hub genes was validated by the Human Protein Atlas database.

Results: A total of 1,621 DEGs (870 downregulated genes and 751 upregulated genes) were identified from the TCGA-PRAD dataset. Eight prognostic genes [BUB1, KIF2C, CCNA2, CDC20, CCNB2, PBK, RRM2, and CDC45] and four hub genes (BUB1, KIF2C, CDC20, and PBK) potentially correlated with the pathogenesis of PCa were identified. A prognostic model with good predictive power for survival was constructed and was validated by the dataset in GSE21032. The survival analysis demonstrated that the expression of RRM2 was statistically significant to the prognosis of PCa, indicating that RRM2 may potentially play an important role in the PCa progression.

Conclusion: The present study implied that RRM2 was associated with prognosis and could be used as a potential therapeutic target for PCa clinical treatment.

DNA Damage Repair-Related Genes Signature for Immune Infiltration and Outcome in Cervical Cancer

Background: The mechanism of DNA damage repair plays an important role in many solid tumors represented by cervical cancer.

Purpose: The purpose of this study was to explore the effect of DNA damage repair-related genes on immune function of patients with cervical cancer, and to establish and evaluate a prognosis model based on DNA damage repair-related genes.

Methods: In the study, we analyzed the genes related to DNA damage and repair, and obtained two subtypes (F1 and F2). We selected two groups of samples for different selection, and studied which pathways were enriched expression. For different subtypes, the immune score was explored to explain immune infiltration. We got the key genes through screening, and established the prognosis model through the key genes. These 11 key genes were correlated with the expression of common Clusters of Differentiation (CD) genes in order to explore the effects of these genes on immunity.

Results: Through the Least absolute shrinkage and selection operator (LASSO) method, we screened 11 genes from 232 candidate genes as the key genes for the prognosis score. Through the Kaplan-Meier method, four genes (HAP1, MCM5, RNASEH2A, CETN2) with significant prognostic significance were screened into the final model, forming a Nomogram with C-index of 0.716 (0.649–1.0).

Conclusion: In cervical cancer, DNA damage repair related genes and immune cell infection characteristics have certain association, and DNA damage repair related genes and immune cell infection characteristics can effectively predict the prognosis.

ALDH2 is a prognostic biomarker and related with immune infiltrates in HCC

Hepatocellular carcinoma is a malignant type of carcinoma with complicated pathogenesis. For HCC patients, there is not only a lack of valuable therapeutic targets, but also a lack of prognostic biomarker. The protein encoded by Aldehyde Dehydrogenase 2 Family Member (ALDH2) is a critical member of the aldehyde dehydrogenase family. Many researchers have found that ALDH2 mutations play an important role in the activation of hepatocellular carcinoma carcinogenic pathways. However, the clinicopathological meaning of ALDH2 in HCC and its relation with immune infiltration is still indistinguishable. In this study, we explored the expression of ALDH2 in 41 HCC tissues by immunohistochemistry. The clinicopathological meaning and molecular function of ALDH2 were analyzed and evaluated through comprehensive bioinformatics. ALDH2 expression in HCC was validated in TCGA, GEO and Oncomine databases, and a survival of ALDH2 based on TCGA database was analysed. LinkedOmics was used to classify the co-expressed genes of ALDH2 and its regulatory factors. The relation between ALDH2 and immune infiltration in HCC was further explored by TIMER. IHC results showed decreased levels of ALDH2 in HCC tumor tissues compared with corresponding normal liver tissues. The pathological grade and prognosis of patients with low expression of the ALDH2 gene were worse. Bioinformatics analysis results showed that ALDH2 was considerably down-regulated in cancer tissues compared with corresponding normal liver tissues in 8 GEO series and TCGA profile (all P<0.05). A nomogram was designed using expression of ALDH2 and clinical factors. ALDH2 was correlated with dendritic cells and macrophages in immune infiltration. In conclusion, ALDH2 has significant prognostic value in hepatocellular carcinoma and they may play key roles in regulating tumor progression and the immune cells infiltration. Our results suggest that ALDH2 may be a new type of tumor biomarker, which can be used to judge the prognosis, targeted therapy and immunotherapy of patients with HCC.

Identification of CDK2-Related Immune Forecast Model and ceRNA in Lung Adenocarcinoma, a Pan-Cancer Analysis

Background

Tumor microenvironment (TME) plays important roles in different cancers. Our study aimed to identify molecules with significant prognostic values and construct a relevant Nomogram, immune model, competing endogenous RNA (ceRNA) in lung adenocarcinoma (LUAD).

Methods

“GEO2R,” “limma” R packages were used to identify all differentially expressed mRNAs from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) databases. Genes with P-value <0.01, LogFC>2 or <-2 were included for further analyses. The function analysis of 250 overlapping mRNAs was shown by DAVID and Metascape software. By UALCAN, Oncomine and R packages, we explored the expression levels, survival analyses of CDK2 in 33 cancers. “Survival,” “survminer,” “rms” R packages were used to construct a Nomogram model of age, gender, stage, T, M, N. Univariate and multivariate Cox regression were used to establish prognosis-related immune forecast model in LUAD. CeRNA network was constructed by various online databases. The Genomics of Drug Sensitivity in Cancer (GDSC) database was used to explore correlations between CDK2 expression and IC50 of anti-tumor drugs.

Results

A total of 250 differentially expressed genes (DEGs) were identified to participate in many cancer-related pathways, such as activation of immune response, cell adhesion, migration, P13K-AKT signaling pathway. The target molecule CDK2 had prognostic value for the survival of patients in LUAD (P = 5.8e-15). Through Oncomine, TIMER, UALCAN, PrognoScan databases, the expression level of CDK2 in LUAD was higher than normal tissues. Pan-cancer analysis revealed that the expression, stage and survival of CDK2 in 33 cancers, which were statistically significant. Through TISIDB database, we selected 13 immunodepressants, 21 immunostimulants associated with CDK2 and explored 48 genes related to these 34 immunomodulators in cBioProtal database (P < 0.05). Gene Set Enrichment Analysis (GSEA) and Metascape indicated that 49 mRNAs were involved in PUJANA ATM PCC NETWORK (ES = 0.557, P = 0, FDR = 0), SIGNAL TRANSDUCTION (ES = –0.459, P = 0, FDR = 0), immune system process, cell proliferation. Forest map and Nomogram model showed the prognosis of patients with LUAD (Log-Rank = 1.399e-08, Concordance Index = 0.7). Cox regression showed that four mRNAs (SIT1, SNAI3, ASB2, and CDK2) were used to construct the forecast model to predict the prognosis of patients (P < 0.05). LUAD patients were divided into two different risk groups (low and high) had a statistical significance (P = 6.223e-04). By “survival ROC” R package, the total risk score of this prognostic model was AUC = 0.729 (SIT1 = 0.484, SNAI3 = 0.485, ASB2 = 0.267, CDK2 = 0.579). CytoHubba selected ceRNA mechanism medicated by potential biomarkers, 6 lncRNAs-7miRNAs-CDK2. The expression of CDK2 was associated with IC50 of 89 antitumor drugs, and we showed the top 20 drugs with P < 0.05.

Conclusion

In conclusion, our study identified CDK2 related immune forecast model, Nomogram model, forest map, ceRNA network, IC50 of anti-tumor drugs, to predict the prognosis and guide targeted therapy for LUAD patients.