Construction of a Glycolysis-related long noncoding RNA signature for predicting survival in endometrial cancer

LIN28B induced PCAT5 promotes endometrial cancer progression and glycolysis via IGF2BP3 deubiquitination

Endometrial cancer (EC) cells exhibit abnormal glucose metabolism, characterized by increased aerobic glycolysis and decreased oxidative phosphorylation. Targeting cellular glucose metabolism in these cells could be an effective therapeutic approach for EC. This study aimed to assess the roles of LIN28B, PCAT5, and IGF2BP3 in the glucose metabolism, proliferation, migration, and invasion of EC cells. LIN28B highly expressed in EC, binds and stabilizes PCAT5. PCAT5, overexpressed in EC, and its 1485-2288nt region can bind to the KH1-2 domain of IGF2BP3 to prevent MKRN2 from binding to the K294 ubiquitination site of IGF2BP3, thus stabilizing IGF2BP3. Finally, IGF2BP3 promotes the aerobic glycolysis, proliferation, migration and invasion of EC cells by stabilizing the key enzymes of glucose metabolism HK2 and PKM2. Taken together, our data reveal that the LIN28B/PCAT5/IGF2BP3 axis is critical for glucose reprogramming and malignant biological behavior in EC cells. Therefore, targeting this axis may contribute to the development of a novel therapeutic strategy for EC metabolism.

Inhibition of DHODH Enhances Replication-Associated Genomic Instability and Promotes Sensitivity in Endometrial Cancer

Endometrial carcinoma (EC) is the most common gynecological malignancy in the United States. De novo pyrimidine synthesis pathways generate nucleotides that are required for DNA synthesis. Approximately 38% of human endometrial tumors present with an overexpression of human dihydroorotate dehydrogenase (DHODH). However, the role of DHODH in cancer cell DNA replication and its impact on modulating a treatment response is currently unknown. Here, we report that endometrial tumors with overexpression of DHODH are associated with a high mutation count and chromosomal instability. Furthermore, tumors with an overexpression of DHODH show significant co-occurrence with mutations in DNA replication polymerases, which result in a histologically high-grade endometrial tumor. An in vitro experiment demonstrated that the inhibition of DHODH in endometrial cancer cell lines significantly induced replication-associated DNA damage and hindered replication fork progression. Furthermore, endometrial cancer cells were sensitive to the DHODH inhibitor either alone or in combination with the Poly (ADP-ribose) polymerase 1 inhibitor. Our findings may have important clinical implications for utilizing DHODH as a potential target to enhance cytotoxicity in high-grade endometrial tumors.

Bioinformatic analysis and verification of a lipid metabolism-related long noncoding RNA prognostic signature for head and neck squamous cell carcinoma

PURPOSE

Both lipid metabolism reprogramming and lncRNAs exert effects on tumor development. We aimed to predict the prognosis of head and neck squamous cell carcinoma (HNSCC) based on lipid metabolism-related (LR)-lncRNAs.

METHODS

LR-lncRNAs were determined from the RNA-ref profiles of HNSCC samples in The Cancer Genome Atlas (TCGA). The prognostic model was established by univariate Cox and Lasso regression analysis. Clinical relevance and predictive accuracy were investigated, and external validation was also performed in the Gene Expression Omnibus (GEO) cohort. Tumor immune infiltration and relevant functional analysis, including the association of autophagy with prognostic signatures, were conducted through single-sample gene set enrichment analysis (ssGSEA). The regulatory network of candidate LR-lncRNAs was investigated via coexpression, ceRNA and cis/trans acting interactions. Potential genes were selected through qRT-PCR analysis, and their effects on tumor biological activities and autophagic activity were explored after gene knockdown.

RESULTS

A total of 222 LR-lncRNAs were identified. Among the 41 genes with prognostic significance, 17 lncRNAs were eligible for the risk model. Patients in the high-risk group had a poorer prognosis than those in the low-risk group, and the risk score was found to be positively associated with tumor microenvironment infiltration via multiple algorithms. Furthermore, improved prognosis was found in patients with high autophagic scores and low risk scores, and autophagy-related genes such as PINK1 and CCL2 showed significantly lower expression in the low-risk group. The expression of immune checkpoint genes such as CD28, CTLA4 and PDCD1 decreased dramatically in the high-risk group. The target genes of candidate lncRNAs were confirmed, such as ENO2 and PPAR-gamma. Furthermore, MIR4435-2HG was the most significantly overexpressed lncRNA in HNSCC cell lines and tumor samples, which could promote proliferation and migration and inhibit apoptosis. Additionally, MIR4435-2HG silencing activated autophagy by increasing LC3B expression.

CONCLUSION

This study constructed an LR-lncRNA prognostic signature for HNSCC and indicated its relationships with tumor immunity and autophagy, which provides a promising future for LR-lncRNA-oriented prognostic tools and therapeutic targets.

Development and validation of a novel DNA damage repair-related long non-coding RNA signature in predicting prognosis, immunity, and drug sensitivity in uterine corpus endometrial carcinoma

Background

DNA damage response (DDR) confer resistance to chemoradiotherapy in cancer cells. However, the role of DDR-related lncRNAs (DRLs) in uterine corpus endometrial carcinoma (UCEC) is poorly understood. In this study, we aimed to identify a DRL-related prognostic signature that could guide the clinical treatment of UCEC.

Methods

We extracted transcriptome and clinical data of patients with UCEC from The Cancer Genome Atlas (TCGA) database and identified DRLs using Spearman correlation analysis. Univariate and multivariate Cox analyses were used to determine candidate prognostic DRLs. The samples were randomly divided into training and test cohorts in a 1:1 ratio. A DRL-related risk signature was constructed from the training cohort data using the least absolute shrinkage and selection operator (LASSO) algorithm, and validated using the test and entire cohorts. Subsequently, a prognostic nomogram was developed using a multivariate Cox regression analysis. The functional annotation, immune microenvironment, tumor mutation burden (TMB), immune checkpoint blockade (ICB) efficacy, and drug sensitivity were also comprehensively analyzed between different risk groups. Finally, the function of AC019069.1 was validated in vitro.

Results

A novel risk signature was developed based on nine DRLs. The risk score efficiently predicted the prognosis of patients with UCEC. Based on the median risk score, two subgroups were identified. The DDR-related pathways were upregulated in the high-risk group. Additionally, high-risk patients have low immune activity, poor response to ICB, and weak sensitivity to chemotherapeutic agents, possibly because of the proficient DDR system. Finally, we demonstrated AC019069.1 could promote cell proliferation, decrease apoptosis and maintain genome stability of UCEC cells.

Conclusions

The developed DRL-related signature can predict the prognosis, immune microenvironment, immunotherapy, and chemoradiotherapy responsiveness of UCEC. Our study also revealed the potential value of DDR-targeted therapy in treating high-risk patients with UCEC.

Development and validation of a two glycolysis-related LncRNAs prognostic signature for glioma and in vitro analyses

BACKGROUND

Mounting evidence suggests that there is a complex regulatory relationship between long non-coding RNAs (lncRNAs) and the glycolytic process during glioma development. This study aimed to investigate the prognostic role of glycolysis-related lncRNAs in glioma and their impact on the tumor microenvironment.

METHODS

This study utilized glioma transcriptome data from public databases to construct, evaluate, and validate a prognostic signature based on differentially expressed (DE)-glycolysis-associated lncRNAs through consensus clustering, DE-lncRNA analysis, Cox regression analysis, and receiver operating characteristic (ROC) curves. The clusterProfiler package was applied to reveal the potential functions of the risk score-related differentially expressed genes (DEGs). ESTIMATE and Gene Set Enrichment Analysis (GSEA) were utilized to evaluate the relationship between prognostic signature and the immune landscape of gliomas. Furthermore, the sensitivity of patients to immune checkpoint inhibitor (ICI) treatment based on the prognostic feature was predicted with the assistance of the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm. Finally, qRT-PCR was used to verify the difference in the expression of the lncRNAs in glioma cells and normal cell.

RESULTS

By consensus clustering based on glycolytic gene expression profiles, glioma patients were divided into two clusters with significantly different overall survival (OS), from which 2 DE-lncRNAs, AL390755.1 and FLJ16779, were obtained. Subsequently, Cox regression analysis demonstrated that all of these lncRNAs were associated with OS in glioma patients and constructed a prognostic signature with a robust prognostic predictive efficacy. Functional enrichment analysis revealed that DEGs associated with risk scores were involved in immune responses, neurons, neurotransmitters, synapses and other terms. Immune landscape analysis suggested an extreme enrichment of immune cells in the high-risk group. Moreover, patients in the low-risk group were likely to benefit more from ICI treatment. qRT-PCR results showed that the expression of AL390755.1 and FLJ16779 was significantly different in glioma and normal cells.

CONCLUSION

We constructed a novel prognostic signature for glioma patients based on glycolysis-related lncRNAs. Besides, this project had provided a theoretical basis for the exploration of new ICI therapeutic targets for glioma patients.

Metabolic reprogramming and interventions in endometrial carcinoma

Cancer cells are usually featured by metabolic adaptations that facilitate their growth, invasion, and metastasis. Thus, reprogramming of intracellular energy metabolism is currently one of the hotspots in the field of cancer research. Whereas aerobic glycolysis (known as the Warburg effect) has long been considered a dominant form of energy metabolism in cancer cells, emerging evidence indicates that other metabolic forms, especially oxidative phosphorylation (OXPHOS), may play a critical role at least in some types of cancer. Of note, women with metabolic syndromes (MetS), including obesity, hyperglycemia, dyslipidemia, and hypertension, have an increased risk of developing endometrial carcinoma (EC), suggesting a close link between metabolism and EC. Interestingly, the metabolic preferences vary among EC cell types, particularly cancer stem cells and chemotherapy-resistant cells. Currently, it is commonly accepted that glycolysis is the main energy provider in EC cells, while OXPHOS is reduced or impaired. Moreover, agents specifically targeting the glycolysis and/or OXPHOS pathways can inhibit tumor cell growth and promote chemosensitization. For example, metformin and weight control not only reduce the incidence of EC but also improve the prognosis of EC patients. In this review, we comprehensively overview the current in-depth understanding of the relationship between metabolism and EC and provide up-to-date insights into the development of novel therapies targeting energy metabolism for auxiliary treatment in combination with chemotherapy for EC, especially those resistant to conventional chemotherapy.

Glucose metabolic reprogramming and its therapeutic potential in obesity-associated endometrial cancer

Endometrial cancer (EC) is a common gynecological cancer that endangers women health. Although substantial progresses of EC management have been achieved in recent years, the incidence of EC still remains high. Obesity has been a common phenomenon worldwide that increases the risk of EC. However, the mechanism associating obesity and EC has not been fully understood. Metabolic reprogramming as a remarkable characteristic of EC is currently emerging. As the primary factor of metabolic syndrome, obesity promotes insulin resistance, hyperinsulinemia and hyperglycaemia. This metabolic disorder remodels systemic status, which increases EC risk and is related with poor prognosis. Glucose metabolism in EC cells is complex and mediated by glycolysis and mitochondria to ensure energy requirement. Factors that affect glucose metabolism may have an impact on EC initiation and progression. In this study, we review the glucose metabolic reprogramming of EC not only systemic metabolism but also inherent tumor cell metabolism. In particular, the role of glucose metabolic regulation in malignant properties of EC will be focused. Understanding of metabolic profile and glucose metabolism-associated regulation mechanism in EC may provide novel perspective for treatment.

LncRNA LINC01833 is a Prognostic Biomarker and Correlates with Immune Infiltrates in Patients with Lung Adenocarcinoma by Integrated Bioinformatics Analysis

Due to the absence of accurate tools for early detection and successful treatment, lung adenocarcinoma (LUAD) is one of the most aggressive tumors with high morbidity and mortality globally. It is absolutely necessary to investigate the process behind its development and search for new biomarkers that could aid in the early detection of LUAD. There is a correlation between the immune microenvironment of the tumor and the prognosis of lung cancer as well as the efficacy of immunotherapy. Long noncoding RNAs (lncRNAs) have been identified as potential prognostic biomarkers linked to immunological activities. In this study, we identified 1 downregulated lncRNA and 76 upregulated lncRNAs in LUAD samples from TCGA datasets. Among the 77 dysregulated lncRNAs, our attention focused on lncRNA LINC01833 (LINC01833). When compared with nontumor specimens, the level of expression of LINC01833 was shown to be significantly elevated in LUAD samples. In addition, the data of the ROC study revealed that LUAD patients with high LINC01833 expression had an AUC value of 0.840 (95% confidence interval: 0.804 to 0.876). There was a correlation between high LINC01833 expression and an advanced clinical stage. Patients who had a high expression of LINC01833 were shown to have a lower overall survival rate (p < 0.001) and a lower disease-specific survival rate (p = 0.004) in comparison to patients who were in the low LINC01833 group, according to the data on survival. In addition, the results of the multivariate analysis revealed that high LINC01833 expression was an independent predictor of poor survival in LUAD. Moreover, the immune analysis revealed that we found that the expression of LINC01833 was positively associated with Th2 cells, aDC, and Tgd, while negatively associated with Mast cells, Tcm, Eosinophils, iDC, DC, Tem, Th17 cells, and pDC. Overall, our data point to the possibility that the unique lncRNA LINC01833 might be employed as a diagnostic and prognostic marker, and as a result, it has a significant impact on clinical practice.

Necroptosis-Related Modification Patterns Depict the Tumor Microenvironment, Redox Stress Landscape, and Prognosis of Ovarian Cancer

Necroptosis is one of programmed cell death discovered recently, which involves in tumorigenesis, cancer metastasis, and immune reaction. We studied the necroptosis-related genes (NRGs) in ovarian cancer (OV) tissues using data from public databases, which separated into two NRGclusters. Patients in cluster A would have severe clinical characteristics, poor prognosis, and worse tumor microenvironment infiltration characteristics. The NRG score was achieved through the Cox analysis, along with a construction of a prognostic model. People with lower risk score would have better prognosis, lower expression of redox related genes, higher immunogenicity, and better effect on immunotherapy. In addition, the NRG score was closely related to cancer stem cell index, copy number variations, tumor mutation load, and chemosensitivity. We built a nomogram to enhance clinical application of the signature. These outcomes can help use know the function of NRGs in OV and provide new ideas for evaluating clinical outcome and developing more effective treatment protocols.

m6A-related long noncoding RNAs predict prognosis and indicate therapeutic response in endometrial carcinoma

BACKGROUND

N6-methyladenosine (m6A) has been identified as the most common, abundant, and conserved internal transcriptional modification. Long noncoding RNAs (lncRNAs) are noncoding RNAs consisting of more than 200 nucleotides, and the expression of various lncRNAs may affect cancer prognosis. The impact of m6A-associated lncRNAs on uterine corpus endometrial carcinoma (UCEC) prognosis is unknown.

METHODS

In this study, UCEC prognosis-related m6A lncRNAs were screened, bioinformatics analysis was performed, and experimental validation was conducted. Endometrial carcinoma (EC) and normal tissue samples were obtained from The Cancer Genome Atlas. The prognosis-related m6A lncRNAs screened by the least absolute shrinkage and selection operator method were used for multivariate Cox proportional risk regression modeling. Principal component analysis and Gene Ontology, immune function difference, and drug sensitivity analyses of the prognostic models were performed. Prognostic analysis was conducted for m6A-associated lncRNAs. The immune infiltration relationship of m6A-associated lncRNAs in EC was identified using the ssGSEA immune infiltration algorithm. A competing endogenouse RNA network was constructed using the LncACTdb database. Finally, quantitative real-time polymerase chain reaction (qRT-PCR) assays were used to validate the differences in m6A-related lncRNA expression in normal and EC cells.

RESULTS

CDKN2B-AS1 and MIR924HG were found to be risk factors for EC. RAB11B-AS1 was a protective factor in EC patients. MIR924HG expression was upregulated in KLE and RL95-2 endometrial cancer cell lines. Prognostic models involved RAB11B-AS1, LINC01812, HM13-IT1, TPM1-AS, SLC16A1-AS1, LINC01936, and CDKN2B-AS1. The high-risk group was more sensitive to five compounds (ABT.263, ABT.888, AP.24534, ATRA, and AZD.0530) than the low-risk group.

CONCLUSION

These findings contribute to understanding of the function of m6A-related lncRNAs in UCEC and provide promising therapeutic strategies for UCEC.

Bioinformatics Analysis and Validation of the Role of Lnc-RAB11B-AS1 in the Development and Prognosis of Hepatocellular Carcinoma

Lnc-RAB11B-AS1 is reported to be dysregulated in several types of cancers and can function as both an oncogene and tumor suppressor gene. To evaluate the potential role of lnc-RAB11B-AS1 in hepatocellular carcinoma (HCC), we investigated and evaluated its expression in HCC based on the data mining of a series of public databases, including TCGA, GEO, ICGC, HPA, DAVID, cBioPortal, GeneMIANA, TIMER, and ENCORI. The data showed downregulation of lnc-RAB11B-AS1 in HCC and was accompanied by the synchronous downregulation of the targeted RAB11B mRNA and its protein. Low expression of lnc-RAB11B-AS1 was associated with shorter overall survival (OS) and disease-free survival (DFS) of HCC patients, PD1/PD-L1 was correlated with low expression of RAB11B. Furthermore, Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis showed a correlation between immune cell change and non-alcoholic fatty liver disease. The above findings revealed that lnc-RAB11B-AS1 was down-regulated in HCC and closely associated with the clinical stage of the HCC patients, suggesting that lnc-RAB11B-AS1 could be a possible predictor for HCC and a potential new therapeutic target for the treatment of HCC.

Identification of cuproptosis-related subtypes, establishment of a prognostic model and tumor immune landscape in endometrial carcinoma

Cuproptosis, the mechanism of copper-dependent cell death, is distinct from all other known forms of regulated cell death and dependents on mitochondrial respiration. Cuproptosis promises to be a novel treatment, especially for tumors resistant to conventional therapies. We investigated the changes in cuproptosis-related genes (CRGs) in endometrial cancer (EC) cohorts from the merged Gene Expression Omnibus and the Cancer Genome Atlas databases, which could be divided into three distinct CRGclusters. Patients in CRGcluster C would have higher survival probability (P = 0.007), and higher levels of tumor microenvironment (TME) cell infiltration than other CRGclusters. CRG score was calculated via the results of univariate, multivariate cox analysis and least absolute shrinkage and selection operator regression analysis. Patients were divided into two risk subgroups according to the median risk score. Low-risk patients exhibited a more favorable prognosis, higher immunogenicity, and greater immunotherapy efficacy. Besides, CRG scores were strongly correlated to copy number variation, immunophenoscore, tumor mutation load, cancer stem cell index, microsatellite instability, and chemosensitivity. The c-index of our model is 0.702, which is higher than other four published model. The results proved that our model can distinguish EC patients with high-risk and low-risk and accurately predict the prognosis of EC patients. It will provide new ideas for clinical prognosis and precise treatments.

Molecular subtypes, clinical significance, and tumor immune landscape of angiogenesis-related genes in ovarian cancer

Angiogenesis is a physiological process, where new blood vessels are formed from pre-existing vessels through the mechanism called sprouting. It plays a significant role in supporting tumor growth and is expected to provide novel therapeutic ideas for treating tumors that are resistant to conventional therapies. We investigated the expression pattern of angiogenesis-related genes (ARGs) in ovarian cancer (OV) from public databases, in which the patients could be classified into two differential ARG clusters. It was observed that patients in ARGcluster B would have a better prognosis but lower immune cell infiltration levels in the tumor microenvironment. Then ARG score was computed based on differentially expressed genes via cox analysis, which exhibited a strong correlation to copy number variation, immunophenoscore, tumor mutation load, and chemosensitivity. In addition, according to the median risk score, patients were separated into two risk subgroups, of which the low-risk group had a better prognosis, increased immunogenicity, and stronger immunotherapy efficacy. Furthermore, we constructed a prognostic nomogram and demonstrated its predictive value. These findings help us better understand the role of ARGs in OV and offer new perspectives for clinical prognosis and personalized treatment.

N1-Methyladenosine-Related lncRNAs Are Potential Biomarkers for Predicting Prognosis and Immune Response in Uterine Corpus Endometrial Carcinoma

Uterine corpus endometrial carcinoma (UCEC) is a malignant disease that, at present, has no well-characterised prognostic biomarker. In this study, two clusters were identified based on 28 N1-methyladenosine- (m1A-) related long noncoding RNAs (lncRNAs), of which cluster 1 was related to immune pathways according to the results of an enrichment analysis. We further observed better prognosis in patients with higher levels of immune cell infiltration, tumor mutation burden, microsatellite instability, and immune checkpoint gene expression. In addition, through Cox regression analysis and least absolute shrinkage and selection operator regression analysis, 10 m1A-related lncRNAs (mRLs) were employed to build a prognosis model. We found that people in higher risk categories had a poorer survival probability than those in lower risk. Low-risk samples were enriched with immune-related pathways, while the high-risk group was similar to the definition of the “immune desert” phenotype, which was associated with decreased immune infiltration, T cell failure, and decreased tumor mutation burden, while also being insensitive to immunotherapy and chemotherapy. This mRL-based model has the ability to accurately predict the prognosis of UCEC patients, and the mRLs could become promising therapeutic targets in enhancing the response of immunotherapy.

Crosstalk of Redox-Related Subtypes, Establishment of a Prognostic Model and Immune Responses in Endometrial Carcinoma

Simple Summary

In order to explore the role of redox as a prognostic indicator in endometrial carcinoma (EC), we detected the expression patterns of 55 redox-related genes (RRGs) in EC cohorts from public databases. Performing consensus cluster algorithm, we determined four molecular subclusters based on RRGs which had significant differences in overall survival (OS) and immune activities of EC patients. Furthermore, we developed a prognostic risk model on the basis of the redox-related subtype by stepwise Cox regression analyses. All EC patients were divided into high-risk and low-risk groups according to the median value of risk score. Our proposed model could accurately assess the clinical outcome and had favorable independent ability in EC cases. Moreover, our signature can serve as a predictor for immune status and chemotherapy sensitivity.

Abstract

Redox plays a central part in the pathogeneses and development of tumors. We comprehensively determined the expression patterns of redox-related genes (RRGs) in endometrial carcinoma (EC) cohorts from public databases and identified four different RRG-related clusters. The prognosis and the characteristics of TME cell infiltration of RRGcluster C patients were worse than those of other RRG clusters. When it comes to the gene cluster, there were great differences in clinicopathology traits and immunocyte infiltration. The RRG score was calculated by Cox analyses, and an RRG-based signature was developed. The risk score performed well in the EC cohort. Samples were separated into two risk subgroups with the standard of the value of the median risk score. Low-risk patients had a better prognosis and higher immunogenicity. In addition, RRG score was closely associated with immunophenoscore, microsatellite instability, tumor mutation burden, tumor stem cell index, copy number variation and chemotherapy sensitivity. The nomogram accurately predicted the prognosis of patients, and our model showed better performance than other published models. In conclusion, we built a prognostic model of RRGs which can help to evaluate clinical outcomes and guide more effective treatment.

METTL16 promotes hepatocellular carcinoma progression through downregulating RAB11B-AS1 in an m6A-dependent manner

BACKGROUND

The molecular mechanisms driving hepatocellular carcinoma (HCC) remain largely unclear. As one of the major epitranscriptomic modifications, N6-methyladenosine (m6A) plays key roles in HCC. The aim of this study was to investigate the expression, roles, and mechanisms of action of the RNA methyltransferase methyltransferase-like protein 16 (METTL16) in HCC.

METHODS

The expression of METTL16 and RAB11B-AS1 was determined by RT-qPCR. The regulation of RAB11B-AS1 by METTL16 was investigated by RNA immunoprecipitation (RIP), methylated RIP (MeRIP), and RNA stability assays. In vitro and in vivo gain- and loss-of-function assays were performed to investigate the roles of METTL16 and RAB11B-AS1.

RESULTS

METTL16 was upregulated in HCC, and its increased expression was correlated with poor prognosis of HCC patients. METTL16 promoted HCC cellular proliferation, migration, and invasion, repressed HCC cellular apoptosis, and promoted HCC tumoral growth in vivo. METTL16 directly bound long noncoding RNA (lncRNA) RAB11B-AS1, induced m6A modification of RAB11B-AS1, and decreased the stability of RAB11B-AS1 transcript, leading to the downregulation of RAB11B-AS1. Conversely to METTL16, RAB11B-AS1 is downregulated in HCC, and its decreased expression was correlated with poor prognosis of patients with HCC. Furthermore, the expression of RAB11B-AS1 was negatively correlated with METTL16 in HCC tissues. RAB11B-AS1 repressed HCC cellular proliferation, migration, and invasion, promoted HCC cellular apoptosis, and inhibited HCC tumoral growth in vivo. Functional rescue assays revealed that overexpression of RAB11B-AS1 reversed the oncogenic roles of METTL16 in HCC.

CONCLUSIONS

This study identified the METTL16/RAB11B-AS1 regulatory axis in HCC, which represented novel targets for HCC prognosis and treatment.

Prognostic-Related Metabolic Score for Survival Prediction in Early-Stage Endometrioid Endometrial Cancer: A Multi-Center and Retrospective Study

Objective

Patients with endometrial cancer (EC) combined with metabolic syndrome (MetS) have a worse prognosis than those without MetS. This study aimed to investigate whether partial metabolic disorder significantly influenced early-stage endometrioid EC (EEC) survival and searched for a more efficient method to evaluate metabolic status.

Methods

This is a nationwide, multicenter cohort study that included 998 patients with primary early-stage EEC from 2001 to 2018. Patients were divided into different metabolic groups based on the diagnostic criteria of the Chinese Medical Association (CDC). The progression-free survival (PFS) time was compared between various metabolic status. Meanwhile, we established an EC Prognostic-Related Metabolic Score (ECPRM Score) to explore the association of the severity of metabolic status and early-stage EEC PFS. A nomogram was established for predicting PFS, which was externally validated in a testing set that includes 296 patients.

Results

A partial metabolic disorder, as well as MetS, was an independent risk factor of poor survival of patients with early-stage EEC [hazard ratio (HR) = 7.6, 95% CI = 1.01–57.5, p < 0.05]. A high ECPRM Score was associated with lower PFS (HR = 2.1, 95% CI = 1.05–4.0, p < 0.001). The nomogram, in which the ECPRM Score contributed most to the prognosis, exhibited excellent discrimination of survival supported by the internal and external validations. In addition, the calibration curve supports its robust predicting ability.

Conclusion

Even though they do not meet the criteria of MetS, partial metabolic disorders were also associated with adverse outcomes in early-stage EEC. The ECPRM Score is beneficial for clinicians to evaluate the severity of metabolic abnormalities and guide patients to ameliorate the poor prognosis of metabolic disorders.

Identification of Immune Subtypes of Esophageal Adenocarcinoma to Predict Prognosis and Immunotherapy Response

A low response rate limits the application of immune checkpoint inhibitors (ICIs) in the treatment of esophageal adenocarcinoma (EAC), which requires the precise characterization of heterogeneous tumor microenvironments. This study aimed to identify the molecular features and tumor microenvironment compositions of EAC to facilitate patient stratification and provide novel strategies to improve clinical outcomes. Here, we performed consensus molecular subtyping with nonnegative matrix factorization (NMF) using EAC data from the Cancer Genome Atlas (TCGA) and identified two distinct subtypes with significant prognostic differences and differences in tumor microenvironments. The findings were further validated in independent EAC cohorts and potential response to ICI therapy was estimated using Tumor Immune Dysfunction and Exclusion (TIDE) and SubMap methods. Our findings suggest that EAC patients of subtype 2 with low levels of cancer-associated fibroblasts, tumor associated macrophages (TAMs), and MDSCs in the tumor microenvironment may benefit from PD-1 blockade therapy, while patients of subtype 1 are more responsive to chemotherapy or combination therapy. These findings might improve our understanding of immunotherapy efficacy and be useful in the development of new strategies to better guide immunotherapy and targeted therapy in the treatment of EAC.

DNA topoisomerase inhibition with the HIF inhibitor acriflavine promotes transcription of lncRNAs in endothelial cells

The transcription factor hypoxia-inducible factor 1 (HIF1) is an important driver of cancer and is therefore an attractive drug target. Acriflavine (ACF) has been suggested to inhibit HIF1, but its mechanism of action is unknown. Here we investigated the interaction of ACF with DNA and long non-coding RNAs (lncRNAs) and its function in human endothelial cells. ACF promoted apoptosis and reduced proliferation, network formation, and angiogenic capacity. It also induced changes in gene expression, as determined by RNA sequencing (RNA-seq), which could not be attributed to specific inhibition of HIF1. A similar response was observed in murine lung endothelial cells. Although ACF increased and decreased a similar number of protein-coding genes, lncRNAs were preferentially upregulated under normoxic and hypoxic conditions. An assay for transposase accessibility with subsequent DNA sequencing (ATAC-seq) demonstrated that ACF induced strong changes in chromatin accessibility at lncRNA promoters. Immunofluorescence showed displacement of DNA:RNA hybrids. Such effects might be due to ACF-mediated topoisomerase inhibition, which was indeed the case, as reflected by DNA unwinding assays. Comparison with other acridine derivatives and topoisomerase inhibitors suggested that the specific function of ACF is an effect of acridinium-class compounds. This study demonstrates that ACF inhibits topoisomerases rather than HIF specifically and that it elicits a unique expression response of lncRNAs.

A Prognostic Signature of Glycolysis-Related Long Noncoding RNAs for Molecular Subtypes in the Tumor Immune Microenvironment of Lung Adenocarcinoma

Purpose

Long noncoding RNAs (lncRNAs) and glycolysis regulate multiple types of cancer. However, the prognostic roles and biological functions of glycolysis-related lncRNAs in lung adenocarcinoma (LUAD) remain unclear. In this study, we investigated the role of glycolysis-related lncRNAs in LUAD.

Patients and Methods

We retrieved glycolysis-related genes from the Molecular Signatures Database and screened for prognostic glycolysis-related lncRNAs from The Cancer Genome Atlas.

Results

We identified three LUAD subtypes (clusters 1–3) by univariate Cox regression analysis and consensus clustering. Patients in cluster 1 had the best overall survival rates. Immune, stromal, and cytolytic-activity scores were the highest in cluster 1. The expression of immune checkpoint molecules (programmed cell death protein 1 and cytotoxic T-lymphocyte-associated protein 4) and other immune-related indicators was the highest in cluster 1, whereas that of epithelial cell biomarkers (Cadherin 1, Cadherin 2, and MET) was the lowest. Therefore, patients in cluster 1 may benefit from immunotherapy. Lasso–Cox regression and multivariate Cox regression analyses were used to select nine lncRNAs to build a robust prognostic model of LUAD. The area under the curve classifier values and a nomogram performed well in predicting survival times for patients with LUAD. The expression levels of nine lncRNAs were validated by quantitative reverse transcriptase-polymerase chain reaction analysis, and most of these lncRNAs were significantly related to immune-related mRNAs. Gene set enrichment analysis revealed that the high-risk group was enriched for cell cycle-related pathways and the low-risk group was enriched for pathways associated with immunity or immune-related diseases.

Conclusion

The LUAD subtypes and prognostic model developed here may help in clinical risk stratification, prognosis management, and treatment decisions for patients with LUAD.

CDKN2B-AS1 Promotes Malignancy as a Novel Prognosis-Related Molecular Marker in the Endometrial Cancer Immune Microenvironment

The prognosis of patients with endometrial cancer (EC) is closely associated with immune cell infiltration. Although abnormal long non-coding RNA (lncRNA) expression is also linked to poor prognosis in patients with EC, the function and action mechanism of immune infiltration-related lncRNAs underlying the occurrence and development of EC remains unclear. In this study, we analyzed lncRNA expression using The Cancer Genome Atlas and clinical data and identified six lncRNAs as prognostic markers for EC, all of which are associated with the infiltration of immune cell subtypes, as illustrated by ImmLnc database and ssGSEA analysis. Real-time quantitative polymerase chain reaction showed that CDKN2B-AS1 was significantly overexpressed in EC, whereas its knockdown inhibited the proliferation and invasion of EC cells and the in vivo growth of transplanted tumors in nude mice. Finally, we constructed a competing endogenous RNA regulatory network and conducted Gene Ontology enrichment analysis to elucidate the potential molecular mechanism underlying CDKN2B-AS1 function. Overall, we identified molecular targets associated with immune infiltration and prognosis and provide new insights into the development of molecular therapies and treatment strategies against EC.

Development of a seven-gene tumor immune microenvironment prognostic signature for high-risk grade III endometrial cancer

Uterine corpus endometrial carcinoma locally infiltrates numerous immune cells and other tumor immune microenvironment components. These cells are involved in malignant tumor growth and proliferation and the process of resistance toward immunotherapies. Here, we aimed to develop a tumor immune microenvironment-related prognostic signature for high-risk grade III endometrial carcinoma based on The Cancer Genome Atlas. The signature was systematically correlated with immune infiltration characteristics of the tumor microenvironment. The seven-gene Riskscore signature was robust and performed well in training, testing, and Gene Expression Omnibus-independent cohorts. A nomogram comprising the gene signature accurately predicted patient prognosis, with our model performing better than other endometrial cancer-related signatures. Analysis of the IMvigor210 immunotherapy cohort revealed that subgroups with a low Riskscore had a better prognosis than subgroups with a high Riskscore. Subgroups with a low Riskscore exhibited immune cell infiltration and inflammatory profiles, whereas subgroups with a high Riskscore experienced progressive disease. The receiver operating characteristic curve indicated that risk score, neoantigen, and tumor mutation burden models together accurately predicted treatment response. Taken together, we developed a tumor microenvironment-based seven-gene prognostic stratification system to predict the prognosis of patients with high-risk endometrial cancer and guide more effective immunotherapy strategies.

Identification of a glycolysis-related lncRNA prognostic signature for clear cell renal cell carcinoma

Background: The present study investigated the independent prognostic value of glycolysis-related long noncoding (lnc)RNAs in clear cell renal cell carcinoma (ccRCC).

Methods: A coexpression analysis of glycolysis-related mRNAs–long noncoding RNAs (lncRNAs) in ccRCC from The Cancer Genome Atlas (TCGA) was carried out. Clinical samples were randomly divided into training and validation sets. Univariate Cox regression and least absolute shrinkage and selection operator (LASSO) regression analyses were performed to establish a glycolysis risk model with prognostic value for ccRCC, which was validated in the training and validation sets and in the whole cohort by Kaplan–Meier, univariate and multivariate Cox regression, and receiver operating characteristic (ROC) curve analyses. Principal component analysis (PCA) and functional annotation by gene set enrichment analysis (GSEA) were performed to evaluate the risk model.

Results: We identified 297 glycolysis-associated lncRNAs in ccRCC; of these, 7 were found to have prognostic value in ccRCC patients by Kaplan–Meier, univariate and multivariate Cox regression, and ROC curve analyses. The results of the GSEA suggested a close association between the 7-lncRNA signature and glycolysis-related biological processes and pathways.

Conclusion: The seven identified glycolysis-related lncRNAs constitute an lncRNA signature with prognostic value for ccRCC and provide potential therapeutic targets for the treatment of ccRCC patients.

An immune-related pseudogene signature to improve prognosis prediction of endometrial carcinoma patients

Background

Pseudogenes show multiple functions in various cancer types, and immunotherapy is a promising cancer treatment. Therefore, this study aims to identify immune-related pseudogene signature in endometrial cancer (EC).

Methods

Gene transcriptome data of EC tissues and corresponding clinical information were downloaded from The Cancer Genome Atlas (TCGA) through UCSC Xena browser. Spearman correlation analysis was performed to identify immune-related pseudogenes (IRPs) between the immune genes and pseudogenes. Univariate Cox regression, LASSO, and multivariate were performed to develop a risk score signature to investigate the different overall survival (OS) between high- and low-risk groups. The prognostic significance of the signature was assessed by the Kaplan–Meier curve, time-dependent receiver operating characteristic (ROC) curve. The abundance of 22 immune cell subtypes of EC patients was evaluated using CIBERSORT.

Results

Nine IRPs were used to build a prognostic signature. Survival analysis revealed that patients in the low-risk group presented longer OS than those in the high-risk group as well as in multiple subgroups. The signature risk score was independent of other clinical covariates and was associated with several clinicopathological variables. The prognostic signature reflected infiltration by multiple types of immune cells and revealed the immunotherapy response of patients with anti-programmed death-1 (PD-1) and anti-programmed cell death 1 ligand 1 (PD-L1) therapy. Function enrichment analysis revealed that the nine IRPs were mainly involved in multiple cancer-related pathways.

Conclusion

We identified an immune-related pseudogene signature that was strongly correlated with the prognosis and immune response to EC. The signature might have important implications for improving the clinical survival of EC patients and provide new strategies for cancer treatment.

Prediction of bladder cancer outcome by identifying and validating a mutation-derived genomic instability-associated long noncoding RNA (lncRNA) signature

Bladder cancer is one of the most common malignant tumors worldwide. Accordingly, its incidence and mortality are high. One of the characteristics of cancer is genomic instability. New studies suggest that long non-coding RNAs (lncRNAs) play an important role in maintaining genomic instability. This study aimed to identify a genomic instability-associated lncRNA signature to predict the outcome of patients with bladder cancer. We downloaded data for bladder cancer patients from The Cancer Genome Atlas database to obtain lncRNA expression profiles as well as somatic mutation profiles. Using the lncRNA computational framework, a genomic instability-related lncRNA signature (GIlncSig) was established and the prognostic value of this signature was assessed and validated. A five-lncRNA signature based on genomic instability (CFAP58-DT, MIR100HG, LINC02446, AC078880.3, and LINC01833) was obtained from 58 differentially expressed lncRNAs. Patients were divided into high-risk and low-risk groups, with the high-risk group having a substantially worse prognosis than the low-risk group. Univariate and multivariate Cox analyses indicated that GIlncSig may be an independent prognostic factor; this finding was subsequently validated. In addition, enrichment analysis indicated that GIlncSig is associated with genomic instability in bladder cancer. GIlncSig has a predictive value for the prognosis of bladder cancer patients and provides guidance for the clinical treatment of these patients.