Systematic screening of protein-coding gene expression identified HMMR as a potential independent indicator of unfavorable survival in patients with papillary muscle-invasive bladder cancer

CDC6 may serve as an indicator of lung adenocarcinoma prognosis and progression based on TCGA and GEO data mining and experimental analyses

Lung adenocarcinoma (LUAD) is one of the most lethal types of cancer worldwide, and accurately predicting patient prognosis is an important challenge. Gene prediction models, which are known for their simplicity and efficiency, have the potential to be used for prognostic predictions. However, the availability of models with true clinical value is limited. The present study integrated tissue sequencing and the clinical information of patients with LUAD from The Cancer Genome Atlas and Gene Expression Omnibus databases using bioinformatics. This comprehensive approach enabled the identification of 252 differentially expressed genes. Subsequently, univariate and multivariate Cox analyses were performed using these genes, and 14 and 3 genes [including cell division cycle 6 (CDC6), hyaluronan mediated motility receptor and STIL centriolar assembly protein] were selected for the construction of two prognostic models. Notably, the 3‑gene prognostic model exhibited a comparable predictive ability to that of the 14‑gene model. Functionally, pathway enrichment analysis revealed that CDC6 played a role in regulating the cell cycle and promoting tumor staging. To further investigate the relevance of CDC6, in vitro experiments involving the downregulation of CDC6 expression were conducted, which resulted in significant inhibition of tumor cell migration, invasion and proliferation. Moreover, in vivo experiments demonstrated that downregulating CDC6 expression significantly reduced the burden and metastasis of in situ lung tumors in mice. These findings suggested that CDC6 may be a critical gene involved in the development and prognosis of LUAD. In summary, the present study successfully constructed a simple yet accurate prognostic prediction model consisting of 3 genes. Additionally, the functional importance of CDC6 as a key gene in the model was identified. These findings lay a crucial foundation for further exploration of prognostic prediction models and a deeper understanding of the functional mechanisms of CDC6. Notably, these results have potential clinical implications for improving personalized treatment and prognosis evaluation for patients with LUAD.

Tumor-promoting roles of HMMR in lung adenocarcinoma

Searching for differential genes in lung adenocarcinoma (LUAD) is vital for research. Hyaluronan mediated motility receptor (HMMR) promotes malignant progression of cancer patients. However, the molecular regulators of HMMR-mediated LUAD onset are unknown. This work aimed to study the relevance of HMMR to proliferation, migration and invasion of LUAD cells. Let-7c-5p and HMMR levels in LUAD cells and HLF-a cells were assessed, and their correlation was also detected. Their interaction was determined by dual-luciferase experiments and qRT-PCR. Cell proliferation, migration and invasion potentials in vitro were validated through cell counting kit-8 (CCK-8), colony formation, scratch healing, and transwell assays. The expression of HMMR was examined by qRT-PCR and western blot and the expression of let-7c-5p was assayed by qRT-PCR. It was found that HMMR level was increased in LUAD and negatively correlated with let-7c-5p level. Let-7c-5p directly targeted HMMR to repress LUAD cell proliferation, migration and invasion. The above data illustrated that the let-7c-5p/HMMR axis may provide certain therapeutic value for LUAD patients.

Characteristics of circadian rhythm-related genes and establishment of a prognostic scoring system for lung adenocarcinoma with experimental verification: a bioinformatics analysis

BACKGROUND

Non-small cell lung cancer (NSCLC) is one of the most common malignant tumors worldwide. Lung adenocarcinoma (LUAD), the main subtype of NSCLC, has a poor prognosis. In recent years, circadian rhythm (CR)-related genes (CRRGs) have demonstrated associations with tumor occurrence and development, but the relationship between CRRGs and LUAD is not clear. Because of the correlation between CRRGs and tumors, we have reason to believe that CRRGs will become an important prognostic indicator for LUAD and guide the treatment of LUAD prognosis.

METHODS

Based on data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we explored the biological function and immune cell infiltration of LUAD in different CR clusters and quantified CR genes using principal component analysis (PCA). Then, we built a CR scoring system (CRscore) to explore the relationship between CRRGs and LUAD prognosis.

RESULTS

Patients were divided into three clusters (A, B, and C). Biological characteristics, such as survival, immune cell infiltration, and gene enrichment, were significantly different among the three clusters (P<0.001). We then established the usefulness of the CR score, which could probably predict the prognosis of LUAD. Specifically, patients with a high CR score had a better prognosis and were more sensitive to chemotherapy than those with a low CR score.

CONCLUSIONS

It is possible to use CRRGs to assess the prognosis of patients with LUAD. Quantification of CR using the CRscore tool in patients with LUAD maybe help to guide personalized cancer immunotherapy strategies in the future. Thus, the CRscore may be a prognostic tool for LUAD.

The role of RHAMM in cancer: Exposing novel therapeutic vulnerabilities

Receptor for hyaluronic acid-mediated motility (RHAMM) is a cell surface receptor for hyaluronic acid that is critical for cell migration and a cell cycle protein involved in microtubule assembly and stability. These functions of RHAMM are required for cellular stress responses and cell cycle progression but are also exploited by tumor cells for malignant progression and metastasis. RHAMM is often overexpressed in tumors and is an independent adverse prognostic factor for a number of cancers such as breast and prostate. Interestingly, pharmacological or genetic inhibition of RHAMM in vitro and in vivo ablates tumor invasiveness and metastatic spread, implicating RHAMM as a potential therapeutic target to restrict tumor growth and improve patient survival. However, RHAMM’s pro-tumor activity is dependent on its subcellular distribution, which complicates the design of RHAMM-directed therapies. An alternative approach is to identify downstream signaling pathways that mediate RHAMM-promoted tumor aggressiveness. Herein, we discuss the pro-tumoral roles of RHAMM and elucidate the corresponding regulators and signaling pathways mediating RHAMM downstream events, with a specific focus on strategies to target the RHAMM signaling network in cancer cells.

The comprehensive and systematic identification of BLCA-specific SF-regulated, survival-related AS events

Bladder urothelial carcinoma (BLCA) is a complex disease with high morbidity and mortality. Changes in alternative splicing (AS) and splicing factor (SF) can affect gene expression, thus playing an essential role in tumorigenesis. This study downloaded 412 patients' clinical information and 433 samples of transcriptome profiling data from TCGA. And we collected 48 AS signatures from SpliceSeq. LASSO and Cox analyses were used for identifying survival-related AS events in BLCA. Finally, 1,645 OS-related AS events in 1,129 genes were validated by Kaplan-Meier (KM) survival analysis, ROC analysis, risk curve analysis, and independent prognostic analysis. Finally, our survey provides an AS-SF regulation network consisting of five SFs and 46 AS events. In the end, we profiled genes that AS occurred in pan-cancer and five SFs' expression in tumor and normal samples in BLCA. We selected CLIP-seq data for validation the interaction regulated by RBP. Our study paves the way for potential therapeutic targets of BLCA.

Autophagy characteristics and establishment of autophagy prognostic models in lung adenocarcinoma and lung squamous cell carcinoma

Background

Non-small cell lung cancer (NSCLC), which makes up the majority of lung cancers, remains one of the deadliest malignancies in the world. It has a poor prognosis due to its late detection and lack of response to chemoradiaiton. Therefore, it is urgent to find a new prognostic marker.

Methods

We evaluated biological function and immune cell infiltration in lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) patients from TCGA and GEO databases between different clusters based on autophagy related hub genes. Autophagy scores were used to assess the degree of autophagy in each individual by using component analysis.

Results

Three different clusters were obtained. Gene set variation analysis, single-sample gene set enrichment analysis and survive analysis showed differences among these three clusters. We demonstrated that the autophagy score of each patient could predict tumor stage and prognosis. Patients with a high autophagy score had a better prognosis, higher immune infiltration, and were more sensitive to immunotherapy and conventional chemotherapy.

Conclusion

It was uncovered that autophagy played an irreplaceable role in NSCLC. Quantified autophagy scores for each NSCLC patient would help guide effective treatment strategies.

The Prognostic Value and Immune Landscapes of a m6A/m5C/m1A-Related LncRNAs Signature in Head and Neck Squamous Cell Carcinoma

Background: N6-methyladenosine (m6A), 5-methylcytosine (m5C) and N1-methyladenosine (m1A) are the main RNA methylation modifications involved in the progression of cancer. However, it is still unclear whether m6A/m5C/m1A-related long non-coding RNAs (lncRNAs) affect the prognosis of head and neck squamous cell carcinoma (HNSCC). Methods: We summarized 52 m6A/m5C/m1A-related genes, downloaded 44 normal samples and 501 HNSCC tumor samples with RNA-seq data and clinical information from The Cancer Genome Atlas (TCGA) database, and then searched for m6A/m5C/m1A-related genes co-expressed lncRNAs. We adopt the least absolute shrinkage and selection operator (LASSO) Cox regression to obtain m6A/m5C/m1A-related lncRNAs to construct a prognostic signature of HNSCC. Results: This prognostic signature is based on six m6A/m5C/m1A-related lncRNAs (AL035587.1, AC009121.3, AF131215.5, FMR1-IT1, AC106820.5, PTOV1-AS2). It was found that the high-risk subgroup has worse overall survival (OS) than the low-risk subgroup. Moreover, the results showed that most immune checkpoint genes were significantly different between the two risk groups (p < 0.05). Immunity microenvironment analysis showed that the contents of NK cell resting, macrophages M2, and neutrophils in samples of low-risk group were significantly lower than those of high-risk group (p < 0.05), while the contents of B cells navie, plasma cells, and T cells regulatory (Tregs) were on the contrary (p < 0.05). In addition, patients with high tumor mutational burden (TMB) had the worse overall survival than those with low tumor mutational burden. Conclusion: Our study elucidated how m6A/m5C/m1A-related lncRNAs are related to the prognosis, immune microenvironment, and TMB of HNSCC. In the future, these m6A/m5C/m1A-related lncRNAs may become a new choice for immunotherapy of HNSCC.

HMMR is a downstream target of FOXM1 in enhancing proliferation and partial epithelial-to-mesenchymal transition of bladder cancer cells

Our previous that HMMR upregulation independently predicts poor survival in patients with papillary muscle-invasive bladder cancer (MIBC). In this study, we explored its downstream regulations and the potential transcriptional factors activating its expression. MIBC derived T24 cells, and non-MIBC (NMIBC) derived RT4 cells were used for in vitro and in vivo studies. HMMR expression enhanced cell proliferation, the expression of mesenchymal markers, and cell invasion. It induced the nuclear entry of β-catenin, increased its active form in the nuclear part, and elevated the relative TOP/FOP activity. The promoter region of HMMR has a canonical FKH motif. FOXM1 bound to this site and activated HMMR transcription. HMMR knockdown significantly weakened FOXM1 overexpression induced bladder cancer growth, invasion, partial epithelial-to-mesenchymal transition (pEMT), as well as the activation of the Wnt/β-catenin signaling pathway. In conclusion, the findings in this study expanded our understanding of the mechanisms underlying HMMR dysregulation and the functional role of the FOXM1-HMMR axis in bladder cancer.

Identification of hub genes associated with prognosis, diagnosis, immune infiltration and therapeutic drug in liver cancer by integrated analysis

Background

Liver cancer is one of the most common cancers and causes of cancer death worldwide. The objective was to elucidate novel hub genes which were benefit for diagnosis, prognosis, and targeted therapy in liver cancer via integrated analysis.

Methods

GSE84402, GSE101685, and GSE112791 were filtered from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified by using the GEO2R. The GO and KEGG pathway of DEGs were analyzed in the DAVID. PPI and TF network of the DEGs were constructed by using the STRING, TRANSFAC, and Harmonizome. The relationship between hub genes and prognoses in liver cancer was analyzed in UALCAN based on The Cancer Genome Atlas (TCGA). The diagnostic value of hub genes was evaluated by ROC. The relationship between hub genes and tumor-infiltrate lymphocytes was analyzed in TIMER. The protein levels of hub genes were verified in HPA. The interaction between the hub genes and the drug were identified in DGIdb.

Results

In total, 108 upregulated and 60 downregulated DEGs were enriched in 148 GO terms and 20 KEGG pathways. The mRNA levels and protein levels of CDK1, HMMR, PTTG1, and TTK were higher in liver cancer tissues compared to normal tissues, which showed excellent diagnostic and prognostic value. CDK1, HMMR, PTTG1, and TTK were positively correlated with tumor-infiltrate lymphocytes, which might involve tumor immune response. The CDK1, HMMR, and TTK had close interaction with anticancer agents.

Conclusions

The CDK1, HMMR, PTTG1, and TTK were hub genes in liver cancer; hence, they might be potential biomarkers for diagnosis, prognosis, and targeted therapy of liver cancer.

A Comprehensive Bioinformatics Analysis of Notch Pathways in Bladder Cancer

Simple Summary

The Notch pathway is important in embryology and numerous tumor diseases. However, its role in bladder cancer (BCa) has not been deeply investigated thus far. Gene expression data are available for BCa, and bioinformatics analysis can provide insights into a possible role of the Notch pathway in BCa development and prognosis. Using this information can help in better understanding the origin of BCa, finding novel biomarkers for prediction of disease progression, and potentially opening new avenues to improved treatment. Our analysis identified the Notch receptors NOTCH2/3 and their ligand DLL4 as potential drivers of BCa by direct interaction with basic cell functions and indirect by modulating the immune response.

Abstract

Background: A hallmark of Notch signaling is its variable role in tumor biology, ranging from tumor-suppressive to oncogenic effects. Until now, the mechanisms and functions of Notch pathways in bladder cancer (BCa) are still unclear. Methods: We used publicly available data from the GTEx and TCGA-BLCA databases to explore the role of the canonical Notch pathways in BCa on the basis of the RNA expression levels of Notch receptors, ligands, and downstream genes. For statistical analyses of cancer and non-cancerous samples, we used R software packages and public databases/webservers. Results: We found differential expression between control and BCa samples for all Notch receptors (NOTCH1, 2, 3, 4), the delta-like Notch ligands (DLL1, 3, 4), and the typical downstream gene hairy and enhancer of split 1 (HES1). NOTCH2/3 and DLL4 can significantly differentiate non-cancerous samples from cancers and were broadly altered in subgroups. High expression levels of NOTCH2/3 receptors correlated with worse overall survival (OS) and shorter disease-free survival (DFS). However, at long-term (>8 years) follow-up, NOTCH2 expression was associated with a better OS and DFS. Furthermore, the cases with the high levels of DLL4 were associated with worse OS but improved DFS. Pathway network analysis revealed that NOTCH2/3 in particular correlated with cell cycle, epithelial–mesenchymal transition (EMT), numbers of lymphocyte subtypes, and modulation of the immune system. Conclusions: NOTCH2/3 and DLL4 are potential drivers of Notch signaling in BCa, indicating that Notch and associated pathways play an essential role in the progression and prognosis of BCa through directly modulating immune cells or through interaction with cell cycle and EMT.

Identification of novel hub genes associated with gastric cancer using integrated bioinformatics analysis

Background

Gastric cancer (GC) is one of the most common solid malignant tumors worldwide with a high-recurrence-rate. Identifying the molecular signatures and specific biomarkers of GC might provide novel clues for GC prognosis and targeted therapy.

Methods

Gene expression profiles were obtained from the ArrayExpress and Gene Expression Omnibus database. Differentially expressed genes (DEGs) were picked out by R software. The hub genes were screened by cytohubba plugin. Their prognostic values were assessed by Kaplan–Meier survival analyses and the gene expression profiling interactive analysis (GEPIA). Finally, qRT-PCR in GC tissue samples was established to validate these DEGs.

Results

Total of 295 DEGs were identified between GC and their corresponding normal adjacent tissue samples in E-MTAB-1440, GSE79973, GSE19826, GSE13911, GSE27342, GSE33335 and GSE56807 datasets, including 117 up-regulated and 178 down-regulated genes. Among them, 7 vital upregulated genes (HMMR, SPP1, FN1, CCNB1, CXCL8, MAD2L1 and CCNA2) were selected. Most of them had a significantly worse prognosis except SPP1. Using qRT-PCR, we validated that their transcriptions in our GC tumor tissue were upregulated except SPP1 and FN1, which correlated with tumor relapse and predicts poorer prognosis in GC patients.

Conclusions

We have identified 5 upregulated DEGs (HMMR, CCNB1, CXCL8, MAD2L1, and CCNA2) in GC patients with poor prognosis using integrated bioinformatical methods, which could be potential biomarkers and therapeutic targets for GC treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08358-7.

Development of prognostic signature based on immune-related genes in muscle-invasive bladder cancer: bioinformatics analysis of TCGA database

Background: Muscle-invasive bladder cancer (MIBC) with high tumor stages accounts for most bladder cancer patient mortality. Platinum-based chemotherapy provides insufficient survival benefits; however, immunotherapy is a promising option for MIBC.

Results: There were 31 differentially expressed IRGs that significantly correlated with the clinical outcomes of MIBC patients. A prognostic signature based on 12 IRGs (MMP9, RBP7, ADIPOQ, AHNAK, OAS1, RAC3, SLIT2, EDNRA, IL34, PDGFD, PPY, IL17RD) performed moderately in prognostic predictions with area under the curve (AUC) equal to 0.76. The high-risk patient group presented worse survival outcomes (hazard ratio 1.197, 95% confidence interval 1.103–1.299, p < 0.001). Furthermore, immune cell infiltration analysis showed increased tumor infiltration of macrophages in the high-risk group.

Conclusion: This novel prognostic signature can effectively divide MIBC patients into different risk groups, allowing for intensive treatment of high-risk individuals who have worse predicted survival outcomes.

Methods: Bioinformatics analyses were conducted using the Cancer Genome Atlas (TCGA) database. Differentially expressed genes and survival-associated immune-related genes (IRGs) were analyzed through a computational algorithm and Cox regression. The potential mechanisms of IRG expression were explored with transcription factors, and a prognosis classification based on IRG expression was developed to stratify patients into distinct risk groups.

Identification of four novel prognosis biomarkers and potential therapeutic drugs for human colorectal cancer by bioinformatics analysis

Colorectal cancer (CRC) is one of the most deadly cancers in the world with few reliable biomarkers that have been selected into clinical guidelines for prognosis of CRC patients. In this study, mRNA microarray datasets GSE113513, GSE21510, GSE44076, and GSE32323 were obtained from the Gene Expression Omnibus (GEO) and analyzed with bioinformatics to identify hub genes in CRC development. Differentially expressed genes (DEGs) were analyzed using the GEO2R tool. Gene ontology (GO) and KEGG analyses were performed through the DAVID database. STRING database and Cytoscape software were used to construct a protein-protein interaction (PPI) network and identify key modules and hub genes. Survival analyses of the DEGs were performed on GEPIA database. The Connectivity Map database was used to screen potential drugs. A total of 865 DEGs were identified, including 374 upregulated and 491 downregulated genes. These DEGs were mainly associated with metabolic pathways, pathways in cancer, cell cycle and so on. The PPI network was identified with 863 nodes and 5817 edges. Survival analysis revealed that HMMR, PAICS, ETFDH, and SCG2 were significantly associated with overall survival of CRC patients. And blebbistatin and sulconazole were identified as candidate drugs. In conclusion, our study found four hub genes involved in CRC, which may provide novel potential biomarkers for CRC prognosis, and two potential candidate drugs for CRC.

Prognostic implication of glycolysis related gene signature in non-small cell lung cancer

Abnormal glycolysis is one of the hallmarks of cancer and plays an important role in its development. This study was devoted to identify glycolysis related genes as prognostic biomarkers for non-small cell lung cancer (NSCLC). The mRNA expression profile and clinical follow-up data were obtained using The Cancer Genome Atlas (TCGA) database. The validation set was obtained by bootstrap method of random repeated sampling. A total of 200 glycolysis-related genes were obtained from Gene Set Enrichment Analysis (GSEA) and 46 genes were significantly associated with overall survival (OS). Five genes (PKP2, LDHA, HMMR, COL5A1 and B3GNT3) were eventually identified to calculate risk score of NSCLC patients.

The univariate and multivariate Cox regression analysis indicated that the risk score was an independent prognostic factor (training set: HR=2.126, 95% CI [1.605, 2.815], p<0.001; validation set: HR=2.298, 95%CI [1.450, 3.640], p<0.001). Patients assigned to the high-risk group were associated with poor OS compared with patients in the low-risk group (training set: P=7.946e-06; validation set: P=6.368e-07). Receiver operating characteristic (ROC) curve and stratification analysis also demonstrated the potential prognostic performance. In conclusion, we constructed a novel glycolysis related risk signature which might contribute to predicting the prognosis of NSCLC.

Comprehensive analysis of the relationship between competitive endogenous RNA (ceRNA) networks and tumor infiltrating-cells in hepatocellular carcinoma

Background

The innovation of immune checkpoint blockade (ICB) represents a promising shift in the treatment of advanced hepatocellular carcinoma (HCC). However, response to ICB has varied largely due to the high tumor heterogeneity and complex tumor microenvironment (TME). The competitive endogenous RNA (ceRNA) network also plays an important role in tumor occurrence and progression, but its relation with tumor-infiltrating immune cells (TICs) remains largely unexplored in HCC. The overriding objective of our study was thus to construct a prognosis-related risk model and to further evaluate the relationship between ceRNA networks and TICs.

Methods

Differentially expressed gene (DEG) analysis was performed to identify the differentially expressed RNAs. Lasso and multivariable Cox regression analyses were used to construct risk models, which were assessed by the area under the receiver operating characteristic curve (AUC of ROC) and Kaplan-Meier (K-M) curves. Then, a single-sample gene set enrichment analysis (ssGSEA) algorithm was adopted to dissect the TICs in HCC samples. Nomograms were constructed and calibration curves were used to verify the discrimination and accuracy of the nomograms. Finally, integration analysis was performed to validate the correlation of ceRNA and TICs.

Results

In the study, 7 differentially expressed RNAs [5 messenger RNA s (mRNAs) and 2 micro RNAs (miRNAs)] were incorporated to construct a ceRNA risk model. The AUC of the 1-, 3-, and 5-year overall survival (OS) were 0.784, 0.685, and 0.691 respectively. Likewise, 7 types TICs were in the TICs signature model and the AUC of the 1-, 3-, and 5-year OS were 0.706, 0.731, and 0.721 respectively. The integration analysis showed that 7 pairs of mRNA-TICs and 1 pair of miRNA-TICs had a close relation (all correlation coefficients >0.2, P<0.001).

Conclusions

Through constructing two risk models based on ceRNA network and TICs, we identified the hub RNAs and key TICs in the progression and prognosis of HCC, and further explored the relationship between ceRNA and TME. Importantly, targeting these hub RNAs may facilitate the remodeling of the TME and be a potential therapeutic alternative to enhancing the response to ICB, thus improving the prognosis of HCC patients.

A glycolysis-related gene pairs signature predicts prognosis in patients with hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is one of the most universal malignant liver tumors worldwide. However, there were no systematic studies to establish glycolysis‑related gene pairs (GRGPs) signatures for the patients with HCC. Therefore, the study aimed to establish novel GRGPs signatures to better predict the prognosis of HCC.

Methods

Based on the data from Gene Expression Omnibus, The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium databases, glycolysis-related mRNAs were used to construct GRGPs. Cox regression was applied to establish a seventeen GRGPs signature in TCGA dataset, which was verified in two validation (European and American, and Asian) datasets.

Results

Seventeen prognostic GRGPs (HMMR_PFKFB1, CHST1_GYS2, MERTK_GYS2, GPC1_GYS2, LDHA_GOT2, IDUA_GNPDA1, IDUA_ME2, IDUA_G6PD, IDUA_GPC1, MPI_GPC1, SDC2_LDHA, PRPS1_PLOD2, GALK1_IER3, MET_PLOD2, GUSB_IGFBP3, IL13RA1_IGFBP3 and CYB5A_IGFBP3) were identified to be significantly progressive factors for the patients with HCC in the TCGA dataset, which constituted a GRGPs signature. The patients with HCC were classified into low-risk group and high-risk group based on the GRGPs signature. The GRGPs signature was a significantly independent prognostic indicator for the patients with HCC in TCGA (log-rank P = 2.898e−14). Consistent with the TCGA dataset, the patients in low-risk group had a longer OS in two validation datasets (European and American: P = 1.143e−02, and Asian: P = 6.342e−08). Additionally, the GRGPs signature was also validated as a significantly independent prognostic indicator in two validation datasets.

Conclusion

The seventeen GRGPs and their signature might be molecular biomarkers and therapeutic targets for the patients with HCC.

A Novel Prognostic Index Based on the Analysis of Glycolysis-Related Genes in Head and Neck Squamous Cell Carcinomas

Aims

The preferential dependence on glycolysis as a pathway of energy metabolism is a hallmark of cancer cells. However, the prognostic significance of glycolysis-related genes in head and neck squamous cell carcinoma (HNSCC) remains obscure. The purpose of this study was to identify glycolysis-related genes of prognostic value in HNSCC.

Results

Transcriptional and clinical data of 544 HNSCC samples were obtained from The Cancer Genome Atlas (TCGA) dataset. By gene set enrichment analysis (GSEA) and by employing a univariate and subsequently a stepwise multivariate Cox proportional regression model, eight glycolysis-related genes of prognostic significance in HNSCC (KIF2A, JMJD8, HMMR, STC2, HK1, EXT2, GPR8, and STC1) were identified. The patients were clustered into two groups (high and low risk) based on the expression of these genes. High-risk patients had significantly a shorter overall survival than low-risk patients. Furthermore, a new prognostic indicator based on selected glycolysis-related genes was developed by multivariate Cox analysis that proved to be a better predictor of patient outcome compared to other clinical factors.

Conclusion

Our findings provide new insights into the role of glycolysis in HNSCC. The identified genes predict the patient prognosis and might substantially contribute to the development of individualized treatments.

CDK4/RB/E2Fs axis as potential therapeutic target of endometrial cancer

The increasing incidence rate and decreasing patients' five-year survival rate for endometrial cancer (EC) in recent decades highlight the necessity for further investigation of the molecular characteristics involved in cancer initiation and progression. In this study, we found that the pathways associated with mitotic cell cycle were enriched in primary EC samples versus normal endometrial samples through analyzing RNA-seq data of The Cancer Genome Atlas (TCGA). The messenger RNA (mRNA) expression of three activator E2Fs (E2F1, E2F2, and E2F3) and their target genes increased significantly in EC samples. Additionally, the high transcriptional activity of activator E2Fs was associated with poor survival, advanced clinical stage, high histologic grade, and aggressive histological type. We further demonstrated that E2Fs hyperactivation correlated with DNA hypomethylation and high cyclin-dependent kinase 4 (CDK4) expression. Moreover, abemaciclib, a selective CDK4 inhibitor, significantly inhibited the proliferation rates of human EC cell lines in vitro. And, abemaciclib also obviously inhibited EC cell growth in nude mice model. Collectively, our data suggest that the misregulation of CDK4/RB/E2Fs axis is associated with EC oncogenesis, and abemaciclib is a potential targeted drug for EC.