POLE2 Serves as a Prognostic Biomarker and Is Associated with Immune Infiltration in Squamous Cell Lung Cancer

Characterization of alternative splicing events and prognostic signatures in gastric cancer

BACKGROUND

Accumulating evidences indicate that the specific alternative splicing (AS) events are linked to the occurrence and prognosis of gastric cancer (GC). Nevertheless, the impact of AS is still unclear and needed to further elucidation.

METHODS

The expression profile of GC and normal samples were downloaded from TCGA. AS events were achieved from SpliceSeq database. Cox regression together with LASSO analysis were employed to identify survival-associated AS events (SASEs) and calculate risk scores. PPI and pathway enrichment analysis were implemented to determine the function and pathways of these genes. Kaplan-Meier (K-M) analysis and Receiver Operating Characteristic Curves were used to evaluate the clinical significance of genes of SASEs. Q-PCR were applied to validate the hub genes on the survival prognosis in 47 GC samples. Drug sensitivity and immune cell infiltration analysis were conducted.

RESULTS

In total, 48 140 AS events in 10 610 genes from 361 GC and 31 normal samples were analyzed. Through univariate Cox regression, 855 SASEs in 763 genes were screened out. Further, these SASEs were analyzed by PPI and 17 hub genes were identified. Meanwhile, using Lasso and multivariate Cox regression analysis, 135 SASEs in 132 genes related to 7 AS forms were further screened and a GC prognostic model was constructed. K-M curves indicates that high-risk group has poorer prognosis. And the nomogram analysis on the basis of the multivariate Cox analysis was disclosed the interrelationships between 7 AS forms and clinical parameters in the model. Five key genes were then screened out by PPI analysis and Differential Expression Gene analysis based on TCGA and Combined-dataset, namely STAT3, RAD51B, SOCS2, POLE2 and TSR1. The expression levels of AS in STAT3, RAD51B, SOCS2, POLE2 and TSR1 were all significantly correlated with survival by qPCR verification. Nineteen drugs were sensitized to high-risk patients and eight immune cells showed significantly different infiltration between the STAD and normal groups.

CONCLUSIONS

In this research, the prognostic model constructed by SASEs can be applied to predict the prognosis of GC patients and the selected key genes are expected to become new biomarkers and therapeutical targets for GC treatment.

Prognostic and chemotherapeutic response prediction by proliferation essential gene signature: Investigating POLE2 in bladder cancer progression and cisplatin resistance

Background: Bladder cancer (BLCA) is the most common genitourinary malignancy. Proliferation essential genes (PEGs) are crucial to the survival of cancer cells. This study aimed to build a PEG signature to predict BLCA prognosis and treatment efficacy. Methods: BLCA PEGs and differentially expressed PEGs were identified using DepMap and TCGA-BLCA datasets, respectively. Based on the prognostic analysis of the differentially expressed PEGs, a PEG model was constructed. Subsequently, we analyzed the relationship between the PEG signature and prognosis of BLCA patients as well as their response to chemotherapy. Finally, we performed random forest analysis to target and functional experiments to validate the most significant PEG which is associated with BLCA progression. CCK-8, invasion, migration, and chemosensitivity assays were performed to assess effects of gene knockdown on BLCA cell proliferation, invasion and migration abilities, and cisplatin chemosensitivity. Results: We screened 10 prognostic PEGs from 201 differentially expressed PEGs and used them to construct a PEG signature model. Patients with high PEG signature score (PEGs-high) exhibited worse OS and lower sensitivity to chemotherapy than those with PEGs-low. We also found significant correlations between the PEG score and previously defined BLCA molecular subtypes. This suggests that the PEG score may effectively predict the molecular subtypes which have distinct clinical outcomes. Random forest analysis revealed that POLE2 (DNA polymerase epsilon subunit 2) was the most significant PEG differentiating BLCA tissue and normal tissue. Bioinformatic analysis and an immunohistochemistry staining assay confirmed that POLE2 was significantly up-regulated in tumor tissues and was associated with poor survival in BLCA patients. Moreover, POLE2 knockdown inhibited the ability of cell clone formation, proliferation, invasion, immigration and IC50 of cisplatin. Conclusion: The PEG signature acts as a potential predictor for prognosis and chemotherapy response in BLCA patients. POLE2 is a key PEG and plays a remarkable role in promoting the malignant progression and cisplatin resistance of BLCA.

The Prognostic Hub Gene POLE2 Promotes BLCA Cell Growth via the PI3K/AKT Signaling Pathway

BACKGROUND

BLCA is a common urothelial malignancy characterized by a high recurrence rate. Despite its prevalence, the molecular mechanisms underlying its development remain unclear.

AIMS

This study aimed to explore new prognostic biomarkers and investigate the underlying mechanism of bladder cancer (BLCA).

OBJECTIVE

The objective of this study is to identify key prognostic biomarkers for BLCA and to elucidate their roles in the disease.

METHODS

We first collected the overlapping DEGs from GSE42089 and TCGA-BLCA samples for the subsequent weighted gene co-expression network analysis (WGCNA) to find a key module. Then, key module genes were analyzed by the MCODE algorithm, prognostic risk model, expression and immunohistochemical staining to identify the prognostic hub gene. Finally, the hub gene was subjected to clinical feature analysis, as well as cellular function assays.

RESULTS

In WGCNA on 1037 overlapping genes, the blue module was the key module. After a series of bioinformatics analyses, POLE2 was identified as a prognostic hub gene in BLCA from potential genes (TROAP, POLE2, ANLN, and E2F8). POLE2 level was increased in BLCA and related to different clinical features of BLCA patients. Cellular assays showed that si-POLE2 inhibited BLCA proliferation, and si-POLE2+ 740Y-P in BLCA cells up-regulated the PI3K and AKT protein levels.

CONCLUSION

In conclusion, POLE2 was identified to be a promising prognostic biomarker as an oncogene in BLCA. It was also found that POLE2 exerts a promoting function by the PI3K/AKT signaling pathway in BLCA.

POLE2 Regulates Apoptosis of Oral Squamous Cell Carcinoma Cells through the PI3K/AKT Signaling Pathway

OBJECTIVE

Oral squamous cell carcinoma (OSCC) is the most common malignant tumor of the head and neck, but its occurrence and progression mechanisms remain unclear. In addition-there is a lack of effective targeting drugs. The second major subunit of DNA polymerase (POLE2) catalyzes the prolongation of new strand replication and modifies exonuclease domain activity. Our previous study found that POLE2 was associated with OSCC progression, but the mechanism remains unclear.

METHODS

The expression of POLE2 in OSCC tissues was detected using immunological assays. Mann-Whitney U analysis was used to investigate the relationship between POLE2 gene expression and tumor classification and prognosis of OSCC. POLE2 expression was inhibited in OSCC cells, and the effects of gene and protein expression were detected using RT-PCR and Western blotting. The POLE2 knockout model was constructed by transfecting a lentiviral vector. Cell proliferation, apoptosis, and migration were detected using various assays including colony formation, MTT, flow cytometry, wound healing assay, Transwell assay, and the Human Apoptosis Antibody Array. The animal model of OSCC was established by subcutaneous injection of transfected HN6 into 4-week-old female nude mice. After 30 days, tumors were removed under anesthesia and tumor weight and dimension were recorded. Tumor cell proliferation was analyzed using Ki67 staining.

RESULTS

POLE2 gene levels were significantly higher in the OSCC tissues than in the normal tissues. In addition, POLE2 gene levels were statistically correlated with tumor classification and prognosis. Silencing POLE2 inhibited the proliferation of oral cancer cells and promoted apoptosis in vitro. Animal experiments also supported a positive correlation between POLE2 and OSCC tumor formation. We further demonstrated that POLE2 could upregulate the expression of apoptosis-related proteins such as caspase-3, CD40, CD40L, DR6, Fas, IGFBP-6, p21, and SMAC. In addition, POLE2 regulated OSCC development by inhibiting the PI3K/AKT signaling pathway.

CONCLUSION

POLE2 is closely related to the progression of OSCC. Thus, POLE2 may be a potential target for OSCC treatment.

MND1 functions as a potential prognostic biomarker associated with cell cycle and immune infiltration in kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is a common and invasive subtype of renal tumors, which has poor prognosis and high mortality. MND1 is a meiosis specific protein that participates in the progress of diverse cancers. Nonetheless, its function in KIRC was unclear. Here, TIMER, TCGA, GEO databases and IHC found MND1 expression is upregulated in KIRC, leading to poor overall survival, and MND1 can serve as an independent prognostic factor. Moreover, enrichment analysis revealed the functional relationship between MND1 and cell cycle, immune infiltration. EdU and transwell assays confirmed that MND1 knockdown surely prohibited the proliferation, migration, and invasion of KIRC cells. Additionally, immune analysis showed that MND1 displayed a strong correlation with various immune cells. Interference with MND1 significantly reduces the expression of chemokines. TCGA and GEO databases indicated that MND1 expression is significantly related to two m6A modification related gene (METTL14, IGF2BP3). Finally, the drug sensitivity analysis revealed 7 potentially sensitive drugs for KIRC patients with high MND1 expression. In conclusion, MND1 can be used as a prognostic biomarker for KIRC and provides clues regarding cell cycle, immune infiltrates and m6A. Sensitive drugs may be an effective treatment strategy for KIRC patients with high expression of MND1.

Induction of senescence upon loss of the Ash2l core subunit of H3K4 methyltransferase complexes

Gene expression is controlled in part by post-translational modifications of core histones. Methylation of lysine 4 of histone H3 (H3K4), associated with open chromatin and gene transcription, is catalyzed by type 2 lysine methyltransferase complexes that require WDR5, RBBP5, ASH2L and DPY30 as core subunits. Ash2l is essential during embryogenesis and for maintaining adult tissues. To expand on the mechanistic understanding of Ash2l, we generated mouse embryo fibroblasts (MEFs) with conditional Ash2l alleles. Upon loss of Ash2l, methylation of H3K4 and gene expression were downregulated, which correlated with inhibition of proliferation and cell cycle progression. Moreover, we observed induction of senescence concomitant with a set of downregulated signature genes but independent of SASP. Many of the signature genes are FoxM1 responsive. Indeed, exogenous FOXM1 was sufficient to delay senescence. Thus, although the loss of Ash2l in MEFs has broad and complex consequences, a distinct set of downregulated genes promotes senescence.

Wilms tumor reveals DNA repair gene hyperexpression is linked to lack of tumor immune infiltration

Background

A T cell-rich tumor microenvironment has been associated with improved clinical outcome and response to immune checkpoint blockade therapies in several adult cancers. Understanding the mechanisms for lack of immune cell infiltration in tumors is critical for expanding immunotherapy efficacy. To gain new insights into the mechanisms of poor tumor immunogenicity, we turned to pediatric cancers, which are generally unresponsive to checkpoint blockade.

Methods

RNA sequencing and clinical data were obtained for Wilms tumor, rhabdoid tumor, osteosarcoma, and neuroblastoma from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database, and adult cancers from The Cancer Genome Atlas (TCGA). Using an 18-gene tumor inflammation signature (TIS) representing activated CD8⁺ T cells, we identified genes inversely correlated with the signature. Based on these results, adult tumors were also analyzed, and immunofluorescence was performed on metastatic melanoma samples to assess the MSH2 relationship to anti-programmed cell death protein-1 (PD-1) efficacy.

Results

Among the four pediatric cancers, we observed the lowest TIS scores in Wilms tumor. TIS scores were lower in Wilms tumors compared with matched normal kidney tissues, arguing for loss of endogenous T cell infiltration. Pathway analysis of genes upregulated in Wilms tumor and anti-correlated with TIS revealed activated pathways involved DNA repair. The majority of adult tumors in TCGA also showed high DNA repair scores associated with low TIS. Melanoma samples from an independent cohort revealed an inverse correlation between MSH2⁺ tumor cells and CD8⁺ T cells. Additionally, melanomas with high MSH2⁺ tumor cell numbers were largely non-responders to anti-PD-1 therapy.

Conclusions

Increased tumor expression of DNA repair genes is associated with a less robust immune response in Wilms tumor and the majority of TCGA tumor types. Surprisingly, the negative relationship between DNA repair score and TIS remained strong across TCGA when correcting for mutation count, indicating a potential role for DNA repair genes outside of preventing the accumulation of mutations. While loss of DNA repair machinery has been associated with carcinogenesis and mutational antigen generation, our results suggest that hyperexpression of DNA repair genes might be prohibitive for antitumor immunity, arguing for pharmacologic targeting of DNA repair as a potential therapeutic strategy.

Using Weighted Gene Co-Expression Network Analysis to Identify Increased MND1 Expression as a Predictor of Poor Breast Cancer Survival

Objective

We used bioinformatics analysis to identify potential biomarker genes and their relationship with breast cancer (BC).

Materials and Methods

We used a weighted gene co-expression network analysis (WGCNA) to create a co-expression network based on the top 25% genes in the GSE24124, GSE33926, and GSE86166 datasets obtained from the Gene Expression Omnibus. We used the DAVID online platform to perform GO and KEGG pathway enrichment analyses and the Cytoscape CytoHubba plug-in to screen the potential genes. Then, we related the genes to prognostic values in BC using the Oncomine, GEPIA, and Kaplan–Meier Plotter databases. Findings were validated by immunohistochemical (IHC) staining in the Human Protein Atlas and the TCGA-BRCA cohort. LinkedOmics identified the interactive expressions of hub genes. We used UALCAN to evaluate the methylation levels of these hub genes. MethSurv and SurvivalMeth were used to assess the multilevel prognostic value. Finally, we assessed hub gene association with immune cell infiltration using TIMER.

Results

The mRNA levels of MKI67, UBE2C, GTSE1, CCNA2, and MND1 were significantly upregulated in BC, whereas ESR1, THSD4, TFF1, AGR2, and FOXA1 were significantly downregulated. The DNA methylation signature analysis showed a better prognosis in the low-risk group. Further subgroup analyses revealed that MND1 might serve as an independent risk factor for unfavorable BC prognosis. Additionally, MND1 expression levels positively correlate with the immune infiltration statuses of CD4+ T cells, CD8+ T cells, B cells, neutrophils, dendritic cells, and macrophages.

Conclusion

Our results indicate that the ten hub genes may be involved in BC’s carcinogenesis, development, or metastasis, and MND1 may be a potential biomarker and therapeutic target for BC.

Identification of a metabolic reprogramming-related signature associated with prognosis and immune microenvironment of head and neck squamous cell carcinoma by in silico analysis

Background

Metabolic reprogramming is one of the essential features of tumorigenesis. Herein, this study aimed to develop a novel metabolism‐related gene signature for head and neck squamous cell carcinoma (HNSCC) patients.

Methods

The transcriptomic and clinical data of HNSCC samples were collected from The Cancer Genome Atlas (TCGA) and GSE65858 datasets. The metabolism‐related gene‐based prognostic signature (MRGPS) was constructed by the Least Absolute Shrinkage and Selection Operator (LASSO) regression model. The time‐dependent receiver operating characteristic (ROC) and Kaplan‐Meier (K‐M) survival curves were plotted for evaluating its predicting performance. At the same time, univariate along with multivariate analysis was carried out to explore its correlation with clinicopathologic factors. Furthermore, GSEA analysis was performed to explore the signaling pathways affected by MRGPS. We also analyzed the associations of MRGPS with the tumor immune microenvironment (TIME), as well as identified potential compounds via Connectivity Map (CMap) and molecular docking.

Results

A total of 12 differentially expressed metabolism‐related genes were identified and selected to construct the MRGPS. Notably, this signature performed well in predicting HNSCC patients’ survival and could serve as an independent prognostic factor in multiple datasets. In addition to the metabolism‐related pathway, this signature could also affect some immune‐related pathways. The results indicated that MRGPS is correlated with immune cells infiltration and anti‐cancer immune response. Furthermore, we identified cephaeline as a potential therapeutic compound for HNSCC.

Conclusion

Taken together, we established an MRGs‐based signature that has the potential to predict the clinical outcome and immune microenvironment, which help to search for potential combination immunotherapy compounds and provide a promising therapeutic strategy for treating HNSCC patients.

Identification of key genes and biological pathways in Chinese lung cancer population using bioinformatics analysis

BACKGROUND

Identification of accurate prognostic biomarkers is still particularly urgent for improving the poor survival of lung cancer patients. In this study, we aimed to identity the potential biomarkers in Chinese lung cancer population via bioinformatics analysis.

METHODS

In this study, the differentially expressed genes (DEGs) in lung cancer were identified using six datasets from Gene Expression Omnibus (GEO) database. Subsequently, enrichment analysis was conducted to evaluate the underlying molecular mechanisms involved in progression of lung cancer. Protein-protein interaction (PPI) and CytoHubba analysis were performed to determine the hub genes. The GEPIA, Human Protein Atlas (HPA), Kaplan-Meier plotter, and TIMER databases were used to explore the hub genes. The receiver operating characteristic (ROC) analysis was performed to evaluate the diagnostic value of hub genes. Reverse transcription quantitative PCR (qRT-PCR) was used to validate the expression levels of hub genes in 10 pairs of lung cancer paired tissues.

RESULTS

A total of 499 overlapping DEGs (160 upregulated and 339 downregulated genes) were identified in the microarray datasets. DEGs were mainly associated with pathways in cancer, focal adhesion, and protein digestion and absorption. There were nine hub genes (CDKN3, MKI67, CEP55, SPAG5, AURKA, TOP2A, UBE2C, CHEK1 and BIRC5) identified by PPI and module analysis. In GEPIA database, the expression levels of these genes in lung cancer tissues were significantly upregulated compared with normal lung tissues. The results of prognostic analysis showed that relatively higher expression of hub genes was associated with poor prognosis of lung cancer. In HPA database, most hub genes were highly expressed in lung cancer tissues. The hub genes have good diagnostic efficiency in lung cancer and normal tissues. The expression of any hub gene was associated with the infiltration of at least two immune cells. qRT-PCR confirmed that the expression level of CDKN3, MKI67, CEP55, SPAG5, AURKA, TOP2A were highly expressed in lung cancer tissues.

CONCLUSIONS

The hub genes and functional pathways identified in this study may contribute to understand the molecular mechanisms of lung cancer. Our findings may provide new therapeutic targets for lung cancer patients.

POLE2 facilitates the malignant phenotypes of glioblastoma through promoting AURKA-mediated stabilization of FOXM1

Glioblastoma (GBM) is a type of brain cancer with high morbidity and mortality worldwide. The clinical significance, biological roles, and underlying molecular mechanisms of DNA poly ε-B subunit (POLE2) in GBM were investigated in the study. Firstly, the Cancer Genome Atlas (TCGA) database found that POLE2 was highly expressed in GBM. Immunohistochemistry (IHC) results further confirmed that POLE2 was abnormally elevated in GBM. In addition, loss-of-function assays revealed that POLE2 knockdown could inhibit the malignant behaviors of GBM, especially reduce cell viability, weaken cell clone formation, enhance the sensitivity of apoptosis, restrain migration and inhibit epithelial-mesenchymal transition (EMT) in vitro. In vivo experiments further clarified the suppressive effects of reduced POLE2 expression on tumors. Mechanically, POLE2 knockdown promoted the ubiquitination as well as reduced the stability of Forkhead transcription factor (FOXM1), which is a known tumor promotor in GBM, through Aurora kinase A (AURKA). Moreover, the knockdown of FOXM1 could weaken the promoting effects of POLE2 on malignant behaviors of GBM. In conclusion, our study revealed crucial roles and a novel mechanism of POLE2 involved in GBM through AURKA-mediated stability of FOXM1 and may provide the theoretical basis of molecular therapy for GBM.

Genomic relevance of FGF14 and associated genes on the prognosis of pancreatic cancer

BACKGROUND

Fibroblast (FGFs) and insulin (IGF) growth factor pathways are among 10 most recurrently altered genomic pathways in pancreatic ductal adenocarcinoma (PDAC). However, the prognostic and therapeutic relevance of FGF and IGF pathways in PDAC is largely unknown.

METHODS

We investigated the relationship between fibroblast and insulin pathway gene expression and clinicopathological features in three independent transcriptomic cohorts of 532 PDAC patients. Furthermore, we have examined the coexpressed genes specific to the prognostic marker identified from these cohorts. Statistical tests including Fisher-exact\Chi-square, Kaplan-Meier, Pearson Correlation and cox regression analyses were performed. Additionally, pathway analysis of gene-specific co-expressed genes was also performed.

RESULTS

The dysregulation of six genes including FGF9, FGF14, FGFR1, FGFR4, IGF2BP2 and IGF2BP3 were significantly associated with different clinical characteristics (including grade, stage, recurrence and nodes) in PDAC cohorts. 11 genes (including FGF9, FGF13, FGF14, FGF17, FGFR1, FGFRL1, FGFBP3, IGFBP3, IGF2BP2, IGF2BP3 and IGFBPL1) showed association with overall survival in different PDAC cohorts. Interestingly, overexpression of FGF14 was found associated with better overall survival (OS) in all three cohorts. Of note, multivariate analysis also revealed FGF14 as an independent prognostic marker for better OS in all three cohorts. Furthermore, FMN2 and PGR were among the top genes that correlated with FGF14 in all 3 cohorts. Of note, overexpression of FMN2 and PGR was found significantly associated with good overall survival in PDAC patients, suggesting FMN2 and PGR can also act as potential markers for the prediction of prognosis in PDAC patients.

CONCLUSION

FGF14 may define a distinct subset of PDAC patients with better prognosis. Moreover, FGF14-based sub-classification of PDAC suggests that FMN2 and PGR can be employed as good prognostic markers in PDAC and this classification may lead to new therapeutic approaches.

Targeting POLE2 Creates a Novel Vulnerability in Renal Cell Carcinoma via Modulating Stanniocalcin 1

Objective

The aim of this study is to investigate the biological functions and the underlying mechanisms of DNA polymerase epsilon subunit 2 (POLE2) in renal cell carcinoma (RCC).

Methods

The datasets of POLE2 expression in The Cancer Genome Atlas Kidney Clear Cell Carcinoma (TCGA-KIRC) and International Cancer Genome Consortium (ICGC) databases was selected and the correlation between POLE2 and various clinicopathological parameters was analyzed. The POLE2 expression in RCC tissues was examined by immunohistochemistry. The POLE2 knockdown cell lines were constructed. In vitro and in vivo experiments were carried out to investigate the function of POLE2 on cellular biology of RCC, including cell viability assay, clone formation assay, flow cytometry, wound-healing assay, Transwell assay, qRT-PCR, Western blot, etc. Besides, microarray, co-immunoprecipitation, rescue experiment, and Western blot were used to investigate the molecular mechanisms underlying the functions of POLE2.

Results

POLE2 was overexpressed in RCC tissues, and high expression of POLE2 was correlated with poor prognosis of RCC. Furthermore, knockdown of POLE2 significantly inhibited cell proliferation, migration, and facilitated apoptosis in vitro. In vivo experiments revealed that POLE2 attenuated RCC tumorigenesis and tumor growth. we also illuminated that stanniocalcin 1 (STC1) was a downstream gene of POLE2, which promoted the occurrence and development of RCC. Besides, knockdown of POLE2 significantly upregulated the expression levels of Bad and p21 while the expression levels of HSP70, IGF-I, IGF-II, survivin, and sTNF-R1 were significantly downregulated. Western blot analysis also showed that knockdown of POLE2 inhibited the expression levels of Cancer-related pathway proteins including p-Akt, CCND1, MAPK9, and PIK3CA.

Conclusion

Knockdown of POLE2 attenuates RCC cells proliferation and migration by regulating STC1, suggesting that POLE2-STC1 may become a potential target for RCC therapy.