Long non-coding RNA expression profile can predict early recurrence in hepatocellular carcinoma after curative resection

An extensive overview of the role of lncRNAs generated from immune cells in the etiology of cancer

Long non-coding RNAs (lncRNAs) are involved in the control of critical tumor-suppressor and oncogenic pathways in cancer. These types of non-coding RNAs could affect both immune and cancer cells. The thorough analysis of lncRNAs derived from immune cells and the incorporation of new findings significantly advance our understanding of the complex role of lncRNAs in the context of cancer. This work highlights the promise of lncRNAs for translational therapeutic approaches while also establishing a solid foundation for comprehending the complex link between lncRNAs and cancer through a coherent narrative. The main findings of this article are that types of lncRNAs derived from immune cells, such as MM2P and MALAT1, can affect the behaviors of cancer cells, like invasion, angiogenesis, and proliferation. As research in this area grows, the therapeutic potential of targeting these lncRNAs offers promising opportunities for expanding our understanding of cancer biology and developing cutting-edge, precision-based therapies for cancer therapy.

Predicting the prognosis, immune response, and immunotherapy in head and neck squamous cell carcinoma using a novel risk model based on anoikis-related lncRNAs

BACKGROUND

Head and neck squamous cell carcinoma (HNSCC) is an extremely heterogeneous and metastatic disease. Anoikis, which is a specific type of programmed apoptosis, is involved in tumor metastasis, tissue homeostasis, and development. Herein, we constructed an anoikis-related long non-coding RNA (lncRNA) signature to predict the prognosis, immune responses, and therapeutic effects in HNSCC patients.

METHODS

A total of 501 HNSCC samples were acquired from the TCGA database and randomly classified into the training and validation groups (1:1 ratio). Thereafter, the results derived from the training set were analyzed with the LASSO regression analysis, and a novel anoikis-related lncRNA risk model was constructed. Time-dependent ROC curves and Kaplan-Meier analysis were carried out to assess the diagnostic value and survival outcomes. A nomogram was utilized to predict the prognostic accuracy. Furthermore, we studied the tumor microenvironment, tumor mutation burden, enrichment pathways, and the response to chemotherapy and immunotherapy.

RESULTS

Seven anoikis-related lncRNAs (AC015878.1, CYTOR, EMSLR, LINC01503, LINC02084, RAB11B-AS1, Z97200.1) were screened to design a novel risk model, which was recognized as the independent prognostic factor for HNSCC patients. The findings implied that low-risk patients showed significantly longer OS, PFS, and DSS compared to those high-risk patients. The two groups that were classified using the risk model showed significant differences in their immune landscape. The risk model also predicted that low-risk HNSCC patients could attain a better response to immunotherapy, while high-risk patients would be more sensitive to gemcitabine, docetaxel, and cisplatin.

CONCLUSIONS

We constructed a novel risk model that could be employed for effectively predicting patient prognosis with a good independent prognostic value for HNSCC patients. Furthermore, this model could be used for designing new immunotherapeutic and chemotherapeutic strategies, and it helps clinicians establish personalized and detailed strategies for HNSCC patients.

Combining a machine-learning derived 4-lncRNA signature with AFP and TNM stages in predicting early recurrence of hepatocellular carcinoma

BACKGROUND

Near 70% of hepatocellular carcinoma (HCC) recurrence is early recurrence within 2-year post surgery. Long non-coding RNAs (lncRNAs) are intensively involved in HCC progression and serve as biomarkers for HCC prognosis. The aim of this study is to construct a lncRNA-based signature for predicting HCC early recurrence.

METHODS

Data of RNA expression and associated clinical information were accessed from The Cancer Genome Atlas Liver Hepatocellular Carcinoma (TCGA-LIHC) database. Recurrence associated differentially expressed lncRNAs (DELncs) were determined by three DEG methods and two survival analyses methods. DELncs involved in the signature were selected by three machine learning methods and multivariate Cox analysis. Additionally, the signature was validated in a cohort of HCC patients from an external source. In order to gain insight into the biological functions of this signature, gene sets enrichment analyses, immune infiltration analyses, as well as immune and drug therapy prediction analyses were conducted.

RESULTS

A 4-lncRNA signature consisting of AC108463.1, AF131217.1, CMB9-22P13.1, TMCC1-AS1 was constructed. Patients in the high-risk group showed significantly higher early recurrence rate compared to those in the low-risk group. Combination of the signature, AFP and TNM further improved the early HCC recurrence predictive performance. Several molecular pathways and gene sets associated with HCC pathogenesis are enriched in the high-risk group. Antitumor immune cells, such as activated B cell, type 1 T helper cell, natural killer cell and effective memory CD8 T cell are enriched in patients with low-risk HCCs. HCC patients in the low- and high-risk group had differential sensitivities to various antitumor drugs. Finally, predictive performance of this signature was validated in an external cohort of patients with HCC.

CONCLUSION

Combined with TNM and AFP, the 4-lncRNA signature presents excellent predictability of HCC early recurrence.

Revealing Prognostic and Immunotherapy-Sensitive Characteristics of a Novel Cuproptosis-Related LncRNA Model in Hepatocellular Carcinoma Patients by Genomic Analysis

Immunotherapy has shown strong anti-tumor activity in a subset of patients. However, many patients do not benefit from the treatment, and there is no effective method to identify sensitive immunotherapy patients. Cuproptosis as a non-apoptotic programmed cell death caused by excess copper, whether it is related to tumor immunity has attracted our attention. In the study, we constructed the prognostic model of 9 cuproptosis-related LncRNAs (crLncRNAs) and assessed its predictive capability, preliminarily explored the potential mechanism causing treatment sensitivity difference between the high-/low-risk group. Our results revealed that the risk score was more effective than traditional clinical features in predicting the survival of HCC patients (AUC = 0.828). The low-risk group had more infiltration of immune cells (B cells, CD8+ T cells, CD4+ T cells), mainly with anti-tumor immune function (p < 0.05). It showed higher sensitivity to immune checkpoint inhibitors (ICIs) treatment (p < 0.001) which may exert the effect through the AL365361.1/hsa-miR-17-5p/NLRP3 axis. In addition, NLRP3 mutation-sensitive drugs (VNLG/124, sunitinib, linifanib) may have better clinical benefits in the high-risk group. All in all, the crLncRNAs model has excellent specificity and sensitivity, which can be used for classifying the therapy-sensitive population and predicting the prognosis of HCC patients.

A review on the role of long non-coding RNA prostate androgen-regulated transcript 1 (PART1) in the etiology of different disorders

LncRNA prostate androgen-regulated transcript 1 (PART1) is an important lncRNA in the carcinogenesis whose role has been firstly unraveled in prostate cancer. Expression of this lncRNA is activated by androgen in prostate cancer cells. In addition, this lncRNA has a role in the pathogenesis intervertebral disc degeneration, myocardial ischemia-reperfusion injury, osteoarthritis, osteoporosis and Parkinson's disease. Diagnostic role of PART1 has been assessed in some types of cancers. Moreover, dysregulation of PART1 expression is regarded as a prognostic factor in a variety of cancers. The current review provides a concise but comprehensive summary of the role of PART1 in different cancers and non-malignant disorders.

Identification of Hypoxia-Related Prognostic Signature and Competing Endogenous RNA Regulatory Axes in Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a common type of liver cancer and one of the highly lethal diseases worldwide. Hypoxia plays an important role in the development and prognosis of HCC. This study aimed to construct a new hypoxia-related prognosis signature and investigate its potential ceRNA axes in HCC. RNA profiles and hypoxia genes were downloaded, respectively, from the Cancer Genome Atlas hepatocellular carcinoma database and Gene Set Enrichment Analysis website. Cox regression analyses were performed to select the prognostic genes and construct the risk model. The ENCORI database was applied to build the lncRNA-miRNA-mRNA prognosis-related network. The TIMER and CellMiner databases were employed to analyze the association of gene expression in ceRNA with immune infiltration and drug sensitivity, respectively. Finally, the co-expression analysis was carried out to construct the potential lncRNA/miRNA/mRNA regulatory axes. We obtained a prognostic signature including eight hypoxia genes (ENO2, KDELR3, PFKP, SLC2A1, PGF, PPFIA4, SAP30, and TKTL1) and further established a hypoxia-related prognostic ceRNA network including 17 lncRNAs, six miRNAs, and seven mRNAs for hepatocellular carcinoma. Then, the analysis of immune infiltration and drug sensitivity showed that gene expression in the ceRNA network was significantly correlated with the infiltration abundance of multiple immune cells, the expression level of immune checkpoints, and drug sensitivity. Finally, we identified three ceRNA regulatory axes (SNHG1/miR-101-3p/PPFIA4, SNHG1/miR-101-3p/SAP30, and SNHG1/miR-101-3p/TKTL1) associated with the progression of HCC under hypoxia. Here, we constructed a prognosis gene signature and a ceRNA network related to hypoxia for hepatocellular carcinoma. Among the ceRNA network, six highly expressed lncRNAs (AC005540.1, AC012146.1, AC073529.1, AC090772.3, AC138150.2, AL390728.6) and one highly expressed mRNA (PPFIA4) were the potential biomarkers of hepatocellular carcinoma which we firstly reported. The three predicted hypoxia-related regulatory axes may play a vital role in the progression of hepatocellular carcinoma.

Role of a lipid metabolism-related lncRNA signature in risk stratification and immune microenvironment for colon cancer

Background

Energy metabolism disorder, especially lipid metabolism disorder, is an important biological characteristic of colon cancer. This research sought to examine the association between lipid metabolism-related long non-coding RNAs (lncRNAs) and prognoses among colon cancer patients.

Methods

The transcriptome profile and clinical data of patients with colon cancer were retrieved from The Cancer Genome Atlas database. Using consensus clustering, cases were divided into two clusters and Kaplan–Meier analysis was executed to analyze differences in their prognoses. The gene set enrichment analysis (GSEA) was used to discover biological processes and signaling pathways. A lipid metabolism-related lncRNA prognostic model (lipid metabolism-LncRM) was created utilizing the least absolute shrinkage and selection operator (LASSO) regression. The tumor microenvironment was evaluated on the basis of the composition of immune and stromal cells.

Results

The patients in Cluster 2 were found to have a better prognosis and higher expression of programmed cell death 1 (PD-1) and programmed cell death ligand 1 (PD-L1) relative to Cluster 1. The results of GSEA showed the enrichment of energy metabolism pathways in Cluster 2. LASSO regression was used to identify the five LncRNAs that were shown to be most substantially linked to patient prognosis. These were NSMCE1-DT, LINC02084, MYOSLID, LINC02428, and MRPS9-AS1. Receiver operating characteristic (ROC) curves and survival analysis illustrated that the lipid metabolism-LncRM had a significant prognostic value. Further analysis showed that high- and low-risk groups were significantly different in terms of clinical characteristics and immune cells infiltration.

Conclusions

Lipid metabolism-related lncRNAs could predict the prognoses and tumor microenvironment of colon cancer and might be important biomarkers relevant to immunotherapy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01369-8.

Identification and Validation of an Inflammatory Response-Related Polygenic Risk Score as a Prognostic Marker in Hepatocellular Carcinoma

Aims

We hypothesized that the expression patterns of inflammatory response-related genes may be a potential tool for hepatocellular carcinoma (HCC) risk scoring.

Background

Inflammatory response plays a pivotal role in the pathogenesis of HCC.

Objective

To establish and validate a hallmark inflammatory response gene-based polygenic risk score as a prognostic tool in HCC.

Methods

We screened differentially expressed inflammatory response genes and established an inflammatory response-related polygenic risk score (IRPRS) in an HCC-related dataset. Patients with HCC were categorized into high- and low-risk groups according to the median IRPRS, and the overall survival between the two groups was compared. The IRPRS was validated in an independent external dataset. Tumor-infiltrating lymphocytes (TILs) in high- and low-risk groups were compared, and gene set enrichment analysis was performed to characterize high-risk HCC identified using this IRPRS.

Results

Four differentially expressed hallmark inflammatory response genes (CD14, AQP9, SERPINE1, and ITGA5) were identified to construct the IRPRS. Patients in the high-risk group had significantly shorter overall survival than those in the low-risk group in both the training set and the test set. Furthermore, the IRPRS remained an independent prognostic factor compared to the routine clinicopathological characteristics. Many cancer-related hallmark gene sets and TILs were significantly enriched in the high-risk group.

Conclusions

We established and validated a four-hallmark inflammatory response gene-based polygenic risk score, which could successfully divide patients with HCC into high-risk and low-risk groups. These two risk groups of HCC possess significantly distinct prognostic and biological characteristics.

Identification of lncRNA biomarkers in hepatocellular carcinoma by comprehensive analysis of the lncRNA-mediated ceRNA network

Growing evidence implicates that miRNAs can interact with long non-coding RNAs (lncRNAs) to regulate target mRNAs through competitive interactions. However, this mechanism that regulate tumorigenesis and cancer progression remains largely unexplored. Long non-coding RNAs (lncRNAs) act as competing endogenous RNAs (ceRNAs), which play a significant role in regulating gene expression. The purpose of our study was to determine potential lncRNA biomarkers to predict the prognosis of HCC by comprehensive analysis of a ceRNA network. The edgeR package was used to obtain the differentially expressed RNA datasets by analyzing 370 HCC tissues and 50 adjacent non-HCC tissues from The Cancer Genome Atlas (TCGA). Through investigating the differentially expressed between HCC tissues and adjacent non-HCC tissues, a total of 947 lncRNAs, 52 miRNAs, and 1,650 mRNAs were obtained. The novel constructed ceRNA network incorporated 99 HCC-specific lncRNAs, four miRNAs, and 55 mRNAs. Survival analysis identified 22 differentially expressed mRNAs, four miRNAs, and nine lncRNAs which were associated with overall survival (OS) time in HCC (p &lt; 0.05), and further exploration was performed to assess the correlation of these differentially expressed genes with tumor stage. The Interpretation of the potential functions of these differentially expressed genes in HCC was realized by Gene ontology (GO) and KEGG pathway enrichment analyses. Seven lncRNAs were confirmed based on univariate Cox regression analysis, lasso COX regression analysis and multivariate Cox regression analysis to construct a predictive model in HCC patients which were related to the prognosis of OS. In summary, ceRNAs contributed to explore the mechanism of tumorigenesis and development, and a model with seven lncRNAs might be potential biomarker to predict the prognosis of HCC. These findings supported the need to studies on the mechanisms involved in the regulation of HCC by ceRNAs.

A novel 7‑hypoxia‑related long non‑coding RNA signature associated with prognosis and proliferation in melanoma

Hypoxia‑related long non‑coding RNAs (lncRNAs) are important indicators of the poor prognosis of cancers. The present study aimed to explore the potential relationship between melanoma and hypoxia‑related lncRNAs. The transcriptome and clinical data of patients with melanoma were downloaded from The Cancer Genome Atlas database. The prognostic hypoxia‑related lncRNAs were screened out using Pearson's correlation test and univariate Cox analysis. As a result, a hypoxia‑related‑lncRNA signature based on the expression of 7 lncRNAs was constructed, with one unfavourable [MIR205 host gene (MIR205HG)] and six favourable (T cell receptor β variable 11‑2, HLA‑DQB1 antisense RNA 1, AL365361.1, AC004847.1, ubiquitin specific peptidase 30 antisense RNA 1 and AC022706.1) lncRNAs as prognostic factors for melanoma. Patients with melanoma were divided into high‑ and low‑risk groups based on the risk score obtained. Survival analyses were performed to assess the prognostic value of the present risk model. Potential tumour‑associated biological pathways associated with the present signature were explored using gene set enrichment analysis. The CIBERSORT algorithm demonstrated the important role of the hypoxia‑related lncRNAs in regulating tumour‑infiltrating immune cells. Clinical samples collected from our center partly confirmed our findings. Cell Counting Kit‑8 and flow cytometry assays indicated the suppression of proliferation of melanoma cells following inhibition of MIR205HG expression. Indicators of the canonical Wnt/β‑catenin signalling pathway were detected by western blotting. The present study demonstrated that MIR205HG could promote melanoma cell proliferation partly via the canonical Wnt/β‑catenin signalling pathway. These findings indicated a 7‑hypoxia‑related‑lncRNA signature that can serve as a novel predictor of melanoma prognosis.

Long non‑coding RNA PART1: dual role in cancer

Increasing evidence has shown that long non-coding RNAs (lncRNAs), which are non-coding endogenous single-stranded RNAs, play an essential role in various physiological and pathological processes through transcriptional interference, post-transcriptional regulation, and epigenetic modification. Moreover, lncRNAs, as oncogenes or tumor suppressor genes, play an important role in the occurrence and development of human cancers. Prostate androgen-regulated transcript 1 (PART1) was initially identified as a carcinogenic lncRNA in prostate adenomas. The upregulated expression of PART1 plays a tumor-promoting role in liver, prostate, lung cancers, and other tumors. In contrast, the expression of PART1 is downregulated in esophageal squamous cell carcinoma, glioma, and other tumors, which may inhibit the tumor. PART1 plays a dual role in cancer and regulates cell proliferation, apoptosis, invasion, and metastasis through a variety of potential mechanisms. These findings suggest that PART1 is a promising tumor biomarker and therapeutic target. This article reviews the biological functions, related mechanisms, and potential clinical significance of PART1 in a variety of human cancers.

Development and Validation of Ferroptosis- and Immune-Related lncRNAs Signatures for Breast Infiltrating Duct and Lobular Carcinoma

Background

Heterogeneity of breast cancer (BRCA) is significantly correlated with its prognosis. Target therapy for ferroptosis and immunity is a new cancer treatment option discovered in recent years. In the present study, we aimed to identify ferroptosis- and immune-related long non-coding RNAs (lncRNAs) to accurately predict the prognosis and diagnosis of patients with breast infiltrating duct and lobular carcinoma by integrated analyses.

Methods

The corresponding data for the patients with breast infiltrating duct and lobular carcinoma by integrated analyses were obtained from The Cancer Genome Atlas (TCGA). Analyses of univariate and multivariate Cox regressions were used to identify the suitable candidate biomarkers.

Results

We found that seven ferroptosis- and immune-related differentially expressed lncRNAs (FI-DELs) (AC007686.3, AC078883.1, ADAMTS9-AS1, AL035661.1, CBR3-AS1, FTX, and TMEM105) were correlated with the overall survival of patients with breast infiltrating duct and lobular carcinoma. The areas under the receiver operating characteristic (AUCs) value of the prognosis model were all over 0.6 in training, validation, and entire groups. The sensitivity and specificity of the diagnosis model was 87.84% and 97.06%, respectively.

Conclusions

Through a series of bioinformatics analyses, we found that the seven FI-DELs could serve as prognostic and diagnostic biomarkers for patients with breast infiltrating duct and lobular carcinoma. However, whether these seven biomarkers could be really applied to the clinic requires further investigations.

Construction and Comprehensive Analysis of ceRNA Networks and Tumor-Infiltrating Immune Cells in Hepatocellular Carcinoma With Vascular Invasion

Background: Hepatocellular carcinoma (HCC) is a common malignant cancer. Metastasis plays a critical role in tumor progression, and vascular invasion is considered one of the most crucial factors for HCC metastasis. However, comprehensive analysis focusing on competitive endogenous RNA (ceRNA) and immune infiltration in the vascular invasion of HCC is lacking.

Methods: The gene expression profiles of 321 samples, including 210 primary HCC cases and 111 HCC cases with vascular invasion, were downloaded from The Cancer Genome Atlas-Liver Hepatocellular Carcinoma project, and used in identifying significant differentially expressed lncRNAs (DElncRNAs), miRNAs (DEmiRNAs), and mRNAs (DEmRNAs). The RNAs associated with vascular invasion were used in constructing a ceRNA network. A multigene-based risk signature was constructed using the least absolute shrinkage and selection operator algorithm. We detected the fractions of 28 immune cell types in HCC through single-sample gene set enrichment analysis (ssGSEA). Finally, the relationship between the ceRNA network and immune cells was determined through correlation analysis and used in clarifying the potential mechanism involved in vascular invasion.

Results: Overall, 413 DElncRNAs, 27 DEmiRNAs, and 397 DEmRNAs were recognized in HCC. A specific ceRNA network based on the interaction among 3 lncRNA–miRNA pairs and 24 miRNA–mRNA pairs were established. A ceRNA-based prognostic signature was constructed and used in dividing samples into high- and low-risk subgroups. The signature showed significant efficacy; its 3- and 5-year areas under the receiver operating characteristic curves were 0.712 and 0.653, respectively. ceRNA and ssGSEA integration analysis demonstrated that PART1 (p = 0, R = −0.33) and CDK5R2 (p = 0.01, R = −0.15) were negatively correlated to natural killer cells.

Conclusion: This study demonstrated that vascular invasion in HCC might be related to PART1, and its role in regulating CDK5R2 and NK cells. A nomogram was developed to predict the prognosis of patients with HCC and demonstrated the value of the ceRNA network and tumor-infiltrating immune cells value in improving personalized management.

Tumor-derived extracellular vesicles containing long noncoding RNA PART1 exert oncogenic effect in hepatocellular carcinoma by polarizing macrophages into M2

AIM

We explored whether tumor-derived extracellular vesicles (EVs) could deliver long noncoding RNA (lncRNA) PART1 into macrophage to orchestrate macrophage polarization in the progression of hepatocellular carcinoma (HCC).

METHOD

The expression patterns of PART1, microRNA (miR)-372-3p and TLR4 were detected by RT-qPCR in the HCC tissues and HCC cells. PART1 was silenced or overexpressed in HCC cells to assess its effects on the HCC cell process. EVs were isolated from PART1-overexpressed HCC cells, and co-cultured with macrophages, and gain- and loss-of-function assays were implemented in macrophages to evaluate their role in macrophage polarization. Relationship among PART1, miR-372-3p, and TLR4 was evaluated. Effect of EV-PART1 on tumorigenicity in vivo was detected by subcutaneous tumorigenicity test in nude mice.

RESULT

PART1 and TLR4 were upregulated while miR-372-3p was downregulated in HCC tissues and cells. PART1 increased HCC cell proliferation, migration, invasion, and EMT. Mechanistically, PART1 bound to miR-372-3p to downregulate its expression, whereas TLR4 was negatively targeted by miR-372-3p in the macrophages. EVs containing PART1, TLR4 overexpression, or miR-372-3p inhibition induced M2 polarization of macrophages. Also, EVs containing PART1 promoted M2 polarization of macrophages and the occurrence of HCC by affecting miR-372-3p/TLR4 axis.

CONCLUSION

HCC cell-derived EVs might up-regulate TLR4 by inhibiting miR-372-3p via PART1 delivery to promote macrophage M2 polarization in HCC.

Immune checkpoints related-LncRNAs can identify different subtypes of lung cancer and predict immunotherapy and prognosis

BACKGROUND

Non-small cell lung cancer is the most common subtype of lung cancer in the world. However, the survival rate of non-small cell lung cancer patients remains low currently. Immune checkpoint and long non-coding RNAs are emerging as critical roles in prognostic significance and the immunotherapeutic response of non-small cell lung cancer. It is critical to discern LncRNAs related with immune checkpoints in patients with Non-small cell lung cancer.

METHODS

In this study, immune checkpoint-linked LncRNAs were determined and achieved by the co-expression analysis. Immune checkpoint-linked LncRNAs with noteworthy prognostic value (P < 0.05) gained were next utilized to separate into two cluster by non-negative matrix factorization (NMF). Univariate and a least absolute shrinkage and selection operator were applied to construct an immune checkpoint-linked LncRNAs model. Kaplan-Meier analysis, Gene Set Enrichment Analysis, and the nomogram were utilized to investigate the LncRNAs model. Lastly, the capability immunotherapy and chemotherapy prediction value of this risk model were also estimated.

RESULTS

The model consisting of ten immune checkpoint-related LncRNAs was acknowledged to be a self-determining predictor of prognosis. Through regrouping the NSCLC patients by this model, difference between them more efficiently on immunotherapeutic response, tumor microenvironment and chemotherapy response could be discovered. This risk model related to the immune checkpoint-based LncRNAs may have an excellent clinical prediction for prognosis and the immunotherapeutic response in patients with NSCLC.

CONCLUSIONS

We performed an integrative analysis of LncRNAs linked with immune checkpoints and emphasized the significance of NSCLC subtypes classification, immune checkpoints related LncRNAs in estimating the tumor microenvironment score, immune cell infiltration of the tumor, immunotherapy, and chemotherapy response.

Development and Validation of a Novel Hypoxia-Related Long Noncoding RNA Model With Regard to Prognosis and Immune Features in Breast Cancer

Background: Female breast cancer is currently the most frequently diagnosed cancer in the world. This study aimed to develop and validate a novel hypoxia-related long noncoding RNA (HRL) prognostic model for predicting the overall survival (OS) of patients with breast cancer. Methods: The gene expression profiles were downloaded from The Cancer Genome Atlas (TCGA) database. A total of 200 hypoxia-related mRNAs were obtained from the Molecular Signatures Database. The co-expression analysis between differentially expressed hypoxia-related mRNAs and lncRNAs based on Spearman's rank correlation was performed to screen out 166 HRLs. Based on univariate Cox regression and least absolute shrinkage and selection operator Cox regression analysis in the training set, we filtered out 12 optimal prognostic hypoxia-related lncRNAs (PHRLs) to develop a prognostic model. Kaplan-Meier survival analysis, receiver operating characteristic curves, area under the curve, and univariate and multivariate Cox regression analyses were used to test the predictive ability of the risk model in the training, testing, and total sets. Results: A 12-HRL prognostic model was developed to predict the survival outcome of patients with breast cancer. Patients in the high-risk group had significantly shorter median OS, DFS (disease-free survival), and predicted lower chemosensitivity (paclitaxel, docetaxel) compared with those in the low-risk group. Also, the risk score based on the expression of the 12 HRLs acted as an independent prognostic factor. The immune cell infiltration analysis revealed that the immune scores of patients in the high-risk group were lower than those of the patients in the low-risk group. RT-qPCR assays were conducted to verify the expression of the 12 PHRLs in breast cancer tissues and cell lines. Conclusion: Our study uncovered dozens of potential prognostic biomarkers and therapeutic targets related to the hypoxia signaling pathway in breast cancer.

Liquid-Liquid Phase Separation-Related Genes Associated with Tumor Grade and Prognosis in Hepatocellular Carcinoma: A Bioinformatic Study

Aim

The aim of the present study was to identify the association between tumor grade and liquid-liquid phase separation (LLPS)-related genes, and to generate a LLPS-related gene-based risk index (LLPSRI) as a prognostic tool for hepatocellular carcinoma (HCC).

Methods

Weighted gene correlation network analysis was performed to test whether the LLPS-related gene modules were associated with tumor grade of HCC. The candidate modules were subjected to functional enrichment analysis. We generated a LLPSRI using the expression profiles of the hub genes among the candidate modules in order to identify patients at high risk. Then, the biological characteristics of the high-risk patients were revealed using gene set enrichment analysis. Additionally, an independent external data set was used to validate the LLPSRI.

Results

Four gene modules showed a significant positive correlation with tumor grade and involved various cancer-related pathways. Among the hub genes, six were selected to generate the LLPSRI, which was significantly associated with prognosis of HCC patients. The LLPSRI could successfully divide patients with HCC into high- and low-risk groups, and patients in the high-risk group showed shorter overall survival than those in the low-risk group. E2F, MYC, and mTORC1 signaling may be important determinants of survival in the high-risk group. The prognostic value of the LLPSRI was validated with the independent external data set.

Conclusion

We identified LLPS-related gene modules that are associated with HCC tumor grade. The LLPSRI may be useful as a prognostic marker of HCC, and it may reliably stratify patients into groups at low or high risk of worse survival. Our analysis also suggests that certain biological characteristics of HCC may be associated with high risk of worse survival.

Dysregulated lncRNAs are Involved in the Progress of Sepsis by Constructing Regulatory Networks in Whole Blood Cells

Sepsis is a highly heterogeneous syndrome that is caused by an unbalanced host response to an infection. Long noncoding RNAs (lncRNAs) have been reported to exert regulatory roles in a variety of biological processes, and became potential biomarkers and therapeutic targets for diverse diseases. However, current understanding on the roles of lncRNAs in sepsis is extremely limited. Herein, to decipher the underlying functions of lncRNAs, we reexplored the 83 transcriptome datasets from specimens with sepsis, no_sepsis by final diagnosis, and control. The results of differentially expressed genes (DEGs), differentially expressed lncRNA (DElncRNA) analysis, and co-expression analysis of lncRNA–mRNA pairs were obtained. We found that the expression pattern of lncRNAs was significantly activated in sepsis specimens, which was clearly distinguished in sepsis from no_sepsis and control specimens. By performing co-expression analysis, we found DElncRNAs were closely related to T-cell activation and immune response–related terms in sepsis by regulating mRNA expression in the trans manner. The lncRNA–mRNA network and the qRT-PCR test revealed that lncRNAs LINC00861, RP11-284N8.3, and CTB-61M7.2 were significantly correlated with the pathogenesis of sepsis. In addition, weighted gene co-expression analysis (WGCNA) and cis-regulation analysis also revealed sepsis-specific lncRNAs were highly associated with important biological processes correlated with sepsis. In summary, the systematic dysregulation of lncRNAs is tightly involved in the remodeling of gene expression regulatory network in sepsis, and the lncRNA–mRNA expression network may be used to refine biomarker predictions for developing novel therapeutic approaches in sepsis.

Hypoxia-related lncRNAs to build prognostic classifier and reveal the immune characteristics of EGFR wild type and low expression of PD-L1 squamous and adenocarcinoma NSCLC

Background

Recently, the development and application of targeted therapies like tyrosine kinase inhibitors (TKIs) and immune checkpoint inhibitors (ICIs) have achieved remarkable survival benefits in non‐small cell lung cancer (NSCLC) treatment. However, epidermal growth factor receptor (EGFR) wild type and low expression of programmed death‐ligand 1 (PD‐L1) NSCLC remain unmanageable. Few treatments for these patients exist, and more side effects with combination therapies have been observed. We intended to generate a hypoxia‐related lncRNAs (hypolncRNAs) classifier that could successfully identify the high‐risk patients and reveal its underlying molecular immunology characteristics.

Methods

By identifying the bottom 25% PD‐L1 expression level as low expression of PD‐L1 and removing EGFR mutant samples, a total of 222 lung adenocarcinoma (LUAD) and lung squamous carcinoma (LUSC) samples and 93 adjacent non‐tumor samples were finally extracted from The Cancer Genome Atlas (TCGA). A 0 or 1 matrix was constructed by cyclically pairing hypoxia‐related long non‐coding RNAs (hypolncRNAs) and divided into the train set and test set. The univariate Cox regression analysis determined the prognostic hypolncRNAs pairs. Then, the prognostic classifier contained nine hypolncRNAs pairs which were generated by Lasso regression and multivariate Cox analysis. It successfully stratified EGFR wild type and low expression of PD‐L1 squamous and adenocarcinoma NSCLC (double‐negative LUAD and LUSC) patients into the high‐ and low‐risk groups, whose accuracy was proved by the time‐dependent receiver operating characteristic (ROC) curve. Furthermore, diverse acknowledged immunology methods include XCELL, TIMER, QUANTISEQ, MCPcounter, EPIC, CIBERSORT‐ABS, CIBERSORT, and the single‐sample gene set enrichment analysis (ssGSEA) revealed its underlying antitumor immunosuppressive status in the high‐risk patients.

Conclusions

It is noteworthy that hypolncRNAs are associated with the survival of double‐negative LUAD and LUSC patients, for which the possible mechanism is inhibiting the antitumor immune process.

The Role of Tumor-related LncRNA PART1 in cancer

BACKGROUND

As we all know, long non-coding RNA (lncRNA) affects tumor progression, which has caused a great upsurge in recent years. It can also affect the growth, migration, and invasion of tumors. When we refer to the abnormal expression of lncRNA, we will find it associated with malignant tumors. In addition, lncRNA has been proved to be a key targeted gene for the treatment of some diseases. PART1, a member of lncRNA, has been reported as a regulator in the process of tumor occurrence and development. This study aims to reveal the biological functions, specific mechanisms, and clinical significance of PART1 in various tumor cells.

METHODS

Through the careful search of PUBMED, the mechanisms of the effect of PART1 on tumorigenesis and development are summarized.

RESULTS

On the one hand, the up-regulated expression of PART1 plays a tumor-promoting role in tumors, including lung cancer, prostate cancer, bladder cancer and so on. On the other hand, PART1 is down-regulated in gastric cancer, glioma and other tumors to play a tumor inhibitory role. In addition, PART1 regulates tumor growth mainly by targeting microRNA such as miR-635, directly regulating the expression of proteins such as FUS/EZH2, affecting signal pathways such as the Toll-like receptor pathway, or regulating immune cells.

CONCLUSION

PART1 is closely related to tumors by regulating a variety of molecular mechanisms. In addition, PART1 can be used as a clinical marker for the early diagnosis of tumors and plays an important role in tumor-targeted therapy.

Identification and Validation of Immune-Related lncRNA Signature as a Prognostic Model for Skin Cutaneous Melanoma

Purpose

Skin cutaneous melanoma (SKCM) is the most aggressive skin cancer that results in high morbidity and mortality rate worldwide. Immune-related long non-coding RNAs (IRlncRs) play an important role in regulating gene expression in tumors. Therefore, in this study, we aimed to identify IRlncRs signature that could predict prognosis and therapeutic targets for melanoma irrespective of the gene expression levels.

Methods

RNA-sequencing data were obtained from The Cancer Genome Atlas (TCGA). IRlncRs were identified using co-expression analysis and recognized using univariate analysis. The impact of IRlncRs on survival was analyzed using a modified least absolute shrinkage and selection operator (Lasso) regression model. A 1-year survival receiver operating characteristic curve was constructed, and the area under the curve was calculated to identify the optimal cut-off point to distinguish between high and low-risk groups in patients with SKCM. Furthermore, integrative analysis was performed to identify the impact of clinicopathological features, chemotherapeutic treatment, tumor-infiltrating immune cells, and mutant genes on survival.

Results

A total of 28 IRlncRs significantly associated with survival were identified. Seventeen IRlncRs pairs were used to build a survival risk model that could be used to distinguish between low and high-risk groups. The high-risk group was negatively associated with tumor-infiltrating immune cells and had a higher half inhibitory centration for chemotherapeutic agents such as cisplatin and vinblastine. Additionally, the high-risk group had a positive correlation with the expression of specific mutant genes such as BRAF and KIT.

Conclusion

Our findings demonstrate that some IRlncRs have a significant correlation with survival and therapeutic targets for SKCM patients and may provide new insight into the clinical diagnosis and treatment strategies for SKCM patients.

Unraveling Immune-Related lncRNAs in Breast Cancer Molecular Subtypes

Breast cancer (BRCA) is the most leading cause of cancer worldwide. It is a heterogeneous disease with at least five molecular subtypes including luminal A, luminal B, basal-like, HER2-enriched, and normal-like. These five molecular subtypes are usually stratified according to their mRNA profile patterns; however, ncRNAs are increasingly being used for this purpose. Among the ncRNAs class, the long non-coding RNAs (lncRNAs) are molecules with more than 200 nucleotides with versatile regulatory roles; and high tissue-specific expression profiles. The heterogeneity of BRCA can also be reflected regarding tumor microenvironment immune cells composition, which can directly impact a patient's prognosis and therapy response. Using BRCA immunogenomics data from a previous study, we propose here a bioinformatics approach to include lncRNAs complexity in BRCA molecular and immune subtype. RNA-seq data from The Cancer Genome Atlas (TCGA) BRCA cohort was analyzed, and signal-to-noise ratio metrics were applied to create these subtype-specific signatures. Five immune-related signatures were generated with approximately ten specific lncRNAs, which were then functionally analyzed using GSEA enrichment and survival analysis. We highlighted here some lncRNAs in each subtype. LINC01871 is related to immune response activation and favorable overall survival in basal-like samples; EBLN3P is related to immune response suppression and progression in luminal B, MEG3, XXYLT1-AS2, and LINC02613 were related with immune response activation in luminal A, HER2-enriched and normal-like subtypes, respectively. In this way, we emphasize the need to know better the role of lncRNAs as regulators of immune response to provide new perspectives regarding diagnosis, prognosis and therapeutical targets in BRCA molecular subtypes.

Comprehensive analyses of competing endogenous RNA networks reveal potential biomarkers for predicting hepatocellular carcinoma recurrence

Background

Hepatocellular carcinoma (HCC) is one of the most common and deadly malignant tumors, with a high rate of recurrence worldwide. This study aimed to investigate the mechanism underlying the progression of HCC and to identify recurrence-related biomarkers.

Methods

We first analyzed 132 HCC patients with paired tumor and adjacent normal tissue samples from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs). The expression profiles and clinical information of 372 HCC patients from The Cancer Genome Atlas (TCGA) database were next analyzed to further validate the DEGs, construct competing endogenous RNA (ceRNA) networks and discover the prognostic genes associated with recurrence. Finally, several recurrence-related genes were evaluated in two external cohorts, consisting of fifty-two and forty-nine HCC patients, respectively.

Results

With the comprehensive strategies of data mining, two potential interactive ceRNA networks were constructed based on the competitive relationships of the ceRNA hypothesis. The ‘upregulated’ ceRNA network consists of 6 upregulated lncRNAs, 3 downregulated miRNAs and 5 upregulated mRNAs, and the ‘downregulated’ network includes 4 downregulated lncRNAs, 12 upregulated miRNAs and 67 downregulated mRNAs. Survival analysis of the genes in the ceRNA networks demonstrated that 20 mRNAs were significantly associated with recurrence-free survival (RFS). Based on the prognostic mRNAs, a four-gene signature (ADH4, DNASE1L3, HGFAC and MELK) was established with the least absolute shrinkage and selection operator (LASSO) algorithm to predict the RFS of HCC patients, the performance of which was evaluated by receiver operating characteristic curves. The signature was also validated in two external cohort and displayed effective discrimination and prediction for the RFS of HCC patients.

Conclusions

In conclusion, the present study elucidated the underlying mechanisms of tumorigenesis and progression, provided two visualized ceRNA networks and successfully identified several potential biomarkers for HCC recurrence prediction and targeted therapies.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08173-0.

LncRNA PART1 promotes cell proliferation and progression in non-small-cell lung cancer cells via sponging miR-17-5p

It has been demonstrated in previous studies that lncPART1 is dysregulated in non-small cell lung cancer (NSCLC). However, the function of lncPART1 in NSCLC is unclear. Therefore, this experimental design was based on LncPART1 to explore the pathogenesis of NSCLC. Real-time polymerase chain reaction was used to detect the expression of lncPART1 and miR-17-5p in NSCLC. Cell Counting Kit -8, colony formation, and transwell assays were used to examine the effects of lncPART1 and miR-17-5p on NSCLC cell proliferation and migration invasiveness. Target gene prediction, luciferase reporter assays were used to validate downstream target genes for lncPART1 and miR-17-5p. Western blot analysis was used to detect the expression of TGFBETAR2. LncPART1 was highly expressed in NSCLC. LncPART1 significantly promoted cell proliferation of NSCLC cells. miR-17-5p was down-expressed in NSCLC. miR-17-5p overexpression inhibited cell proliferation and migration invasion in NSCLC cells. LncPART1 was able to inhibit miR-17-5p expression and upregulate the expression level of TGFBETAR2. The results of in vivo animal models confirmed that lncPART1 promoted NSCLC progression by miR-17-5p/TGFBETAR2 axis. LncPART1 promoted the progression of NSCLC by miR-17-5p/TGFBETAR2 axis.

LINC00861 inhibits the progression of cervical cancer&nbsp;cells by functioning as a ceRNA for miR‑513b‑5p and&nbsp;regulating the PTEN/AKT/mTOR signaling pathway

Long non‑coding RNAs (lncRNAs) have been discovered to serve important roles in a variety of types of cancer, including cervical cancer. The low expression of lncRNA long intergenic non‑protein coding RNA 861 (LINC00861) is related to poor prognosis in ovarian cancer. However, the effects and underlying mechanisms of LINC00861 in cervical cancer remain largely unknown. The present study aimed to examine the role of LINC00861 in the development and progression of ovarian cancer and its underlying mechanisms. The expression levels of LINC00861 and microRNA (miR)‑513b‑5p were analyzed using reverse transcription‑quantitative PCR analysis. Cell proliferation, migration and invasion were measured by using Cell Counting Kit‑8, colony formation, wound healing and Transwell assays, respectively. A luciferase assay was used to determine whether miR‑513b‑5p targeted LINC00861 and PTEN. The expression of protein was measured by using western blot assay. The results of the present study discovered that LINC00861 expression levels were significantly downregulated in cervical cancer tissues and CaSki and ME‑180 cell lines. Downregulated LINC00861 expression levels were identified to be associated with an advanced‑stage, lymph node metastasis and the poor survival of patients with cervical cancer. Gene Set Enrichment Analysis revealed that the PI3K/AKT/mTOR signaling pathway was significantly enriched in cervical tumors expressing low expression levels of LINC00861 compared with tumors expressing high levels of LINC00861. The overexpression of LINC00861 reduced cervical cancer cell proliferation, migration, invasion and epithelial‑mesenchymal transition (EMT) processes, upregulated PTEN protein expression levels and downregulated phosphorylated (p)‑AKT and p‑mTOR protein expression levels. The regulatory relationship between LINC00861, microRNA (miR)‑513b‑5p and PTEN was validated using a dual luciferase reporter gene assay. PTEN expression levels were significantly downregulated in the miR‑513b‑5p mimic group and significantly upregulated in the miR‑513b‑5p inhibitor group compared with the mimic NC and inhibitor NC in both cell lines. Furthermore, LINC00861 was suggested to serve as a competing endogenous RNA by sponging miR‑513b‑5p and consequently upregulating the expression levels of PTEN in cervical cancer cells. The expression of PTEN, the phosphorylation of Akt and mTOR and and the EMT phenotype were rescued following co‑transfection with LINC00861 and miR‑513b‑5p mimics. In conclusion, the findings of the present study indicated that the LINC00861/miR‑513b‑5p axis may inhibit the progression of cervical cancer cells through the PTEN/AKT/mTOR signaling pathway to suppress the EMT process.

Long Non-Coding RNA PART1 Promotes Proliferation, Migration and Invasion of Hepatocellular Carcinoma Cells via miR-149-5p/MAP2K1 Axis

Background

Hepatocellular carcinoma (HCC) is the most common primary hepatic malignancy worldwide. Long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) have been identified as effective markers for the detection of multiple cancers. This study aimed to illuminate the mechanism of prostate androgen regulated transcript 1 (PART1) in HCC.

Materials and Methods

The levels of PART1, miR-149-5p and mitogen-activated protein kinase 1 (MAP2K1) mRNA were detected by quantitative real-time polymerase chain reaction (qRT-PCR) assay. Cell proliferation was assessed by Cell Counting Kit-8 (CCK-8) assay, and cell migration and invasion were evaluated by transwell assay. Dual-luciferase reporter assay was carried out to examine the relationship among PART1, miR-149-5p and MAP2K1. Western blot assay was conducted to measure the protein expression of MAP2K1.

Results

PART1 and MAP2K1 expression were greatly increased and miR-149-5p level was decreased in HCC tissues. Functional analysis revealed that the si-PART1 inhibited proliferation, migration and invasion of HCC cells. PART1 directly bound to miR-149-5p and miR-149-5p level was down-regulated by PART1. Moreover, restoration experiment demonstrated that the effect of PART1 knockdown on HCC cell progression could be partially rescued by miR-149-5p depletion. MiR-149-5p was predicted to target MAP2K1 and MAP2K1 expression was negatively modulated by miR-149-5p. Also, MAP2K1 rescued the inhibitory effects of miR-149-5p overexpression on proliferation, migration and invasion in HCC cells. Besides, the inhibition of miR-149-5p weakened the impact on MAP2K1 expression mediated by PART1 repression.

Conclusion

PART1 promoted proliferation, migration and invasion of HCC cells by regulating miR-149-5p/MAP2K1 axis.

Construction and Analysis of a Long Non-Coding RNA-Associated Competing Endogenous RNA Network Identified Potential Prognostic Biomarkers in Luminal Breast Cancer

Purpose

To construct a competing endogenous RNA (ceRNA) topology network of RNA-seq data and micro RNA-seq (miRNA-seq) data to identify key prognostic long non-coding RNA (lncRNAs) in luminal breast cancer, and validate the results by human luminal breast cancer samples.

Materials and Methods

The RNA-seq data and miRNA-seq data of luminal A breast cancer in the The Cancer Genome Atlas (TCGA) database were downloaded and compared with those in the miRcode database to obtain lncRNA–miRNA relationship pairs. Final target genes were predicted by all three databases (miRDB, miRTarBase, and TargetScan), thereby obtaining the miRNA-messenger RNA (miRNA-mRNA) relationship pairs and a ceRNA topology network was constructed, then mRNA enrichment analysis, ceRNA topological and stability analysis, univariate and multivariate Cox regression analysis were performed. Overall survival (OS) was evaluated and the key prognostic RNAs were identified. The expression difference between normal and tumor, as well as the correlation of high expression in tumor with pathological parameters (Ki-67, Grade, tumor diameter) were validated by human breast cancer specimens.

Results

A ceRNA topology network was constructed and six lncRNAs were finally identified (The higher expression of PART1, IGF2.AS, WT1.AS, OIP5.AS1, and SLC25A5.AS1 was associated with poor prognosis while AL035706.1 was adverse) and the poor prognostic ones were higher expressed in tumor tissue and correlated with a higher Ki-67 (>10%), tumor grades (II, III) and tumor diameters (>1.5 cm). Using six lncRNAs, we constructed a prognostic model, which performed well for the classification of prognosis in the module.

Conclusion

We identified and verified six biomarkers (OS-predicting) in luminal breast cancer, which significantly enriched the prediction and potential targets of this subtype.

A Novel Scoring System for Risk Assessment of Elderly Patients With Cytogenetically Normal Acute Myeloid Leukemia Based on Expression of Three AQP1 DNA Methylation-Associated Genes

Background: Aquaporin 1 (AQP-1), a transmembrane water channel protein, has been proven to involve in many diseases' progression and prognosis. This research aims to explore the prognostic value of AQP-1 in elderly cytogenetically normal acute myeloid leukemia (CN-AML).

Methods: Complete clinical and expression data of 226 elderly patients (aged > 60) with cytogenetically normal acute myeloid leukemia (CN-AML) were downloaded from the databases of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). We have explored prognostic significance of AQP-1, investigated the underlying mechanism, and developed a novel scoring system for the risk assessment of elderly patients with AML based on AQP1 methylation.

Results: In the first and second independent group, AQP1 shows lower expression in CN-AML than normal people, while high AQP1 expression and AQP1 promoter hypomethylation were related to better overall survival (OS; P < 0.05). To understand the underlying mechanisms, we investigated differentially expressed genes (DEGs), miRNA and lncRNA associated with AQP1 methylation. A three-gene prognostic signature based on AQP1 methylation which was highly correlated with OS was established, and the performance was validated by Permutation Test and Leave-one-out Cross Validation method. Furthermore, an independent cohort was used to verify the prognostic value of this model.

Conclusions: AQP1 methylation could serve as an independent prognostic biomarker in elderly CN-AML, and may provide new insights for the diagnosis and treatment for elderly CN-AML patients.

Long non-coding RNA PART1 promotes intervertebral disc degeneration through regulating the miR‑93/MMP2 pathway in nucleus pulposus cells

The aim of the present study was to investigate the role of the long non‑coding (lnc)RNA PART1 in nucleus pulposus (NP) cells derived from patients with intervertebral disc degeneration (IDD). The level of PART1 in degenerative NP tissues from patients with IDD, bulging and herniated discs was measured by reverse transcription‑quantitative PCR (RT‑qPCR) analysis. NP cells were isolated from patients with IDD and transfected with siPART1, after which time the growth ability of the NP cells was evaluated by Cell Counting Kit‑8 and colony formation assays, and cell apoptosis was measured by flow cytometry. The levels of the cell proliferation marker Ki‑67 and the apoptosis marker cleaved caspase‑3, and the levels of genes related to extracellular matrix (ECM) synthesis and degradation, were also evaluated by western blotting and RT‑qPCR, as appropriate. Bioinformatics methods predicted that miR‑93 was sponged by PART1, and matrix metallopeptidase (MMP)2 was targeted by miR‑93, which was further confirmed by dual‑luciferase reporter assay. The levels of miR‑93 and MMP2 were also measured in NP tissues, and further rescue experiments were performed to confirm the role of the PART1/miR‑93/MMP2 pathway in NP cells. PART1 was found to be upregulated in degenerative NP tissues, and siPART1 caused an increase in cell growth ability and ECM synthesis, whereas it decreased cell apoptosis and ECM degradation in NP cells. miR‑93 was downregulated and MMP2 was upregulated in degenerative NP tissues. Rescue experiments indicated that the effects of miR‑93 inhibitor on NP cells were abolished by siPART1, and the effect of miR‑93 mimic on NP cells was rescued by MMP2 overexpression. Thus, the results of the present study demonstrated that PART1 may regulate NP cell degeneration through the miR‑93/MMP2 pathway. These findings indicate a novel signaling axis in NP cells that may be explored for the treatment of IDD.

Circular RNA Circ100084 functions as sponge of miR‑23a‑5p to regulate IGF2 expression in hepatocellular carcinoma

Hepatocellular carcinoma (HCC) has become a major cause of cancer-related mortality worldwide. Circular RNAs (circRNAs) are non-coding RNAs that serve important roles in multiple cancers. However, the role of circRNAs in HCC remains largely unknown. In the present study, a circRNA microarray dataset of HCC samples, GSE97332, was downloaded from the gene expression omnibus database. Following data preprocessing, differentially expressed circRNAs between HCC tissues and normal tissues were determined using GEO2R. The circRNA-miRNA interactions were predicted by the miRanda database. The miRTarbase database was used to search for target genes of the miRNAs. A circRNA-miRNA-mRNA network was constructed using Cytoscape based on the obtained circRNA, miRNA and mRNA. In this network, the upregulated circRNA hsa_circRNA_100084 was found to be involved in a competing endogenous relationship of hsa_circRNA_100084-hsa-miR-23a-5p- insulin-like growth factor 2 (IGF2). The differential expression of hsa_circRNA_100084, hsa-miR-23a-5p and IGF2 in HCC tissues and liver cancer cells was validated by reverse transcription-quantitative PCR. Additionally, the interactions between hsa-miR-23a-5p with hsa_circRNA_100084 and IGF2 were validated by dual-luciferase reporter assays. Knocking down hsa_circRNA_100084 inhibited the proliferation, migration and invasion of liver cancer cells, while the simultaneous overexpression of IGF2 reversed the effects of hsa_circRNA_100084 knockdown. The results show that hsa_circRNA_100084 could promote the expression of IGF2 by acting as a sponge of hsa-miR-23a-5p in liver cancer cells.

Transcriptome analysis reveals the link between lncRNA-mRNA co-expression network and tumor immune microenvironment and overall survival in head and neck squamous cell carcinoma

Background

As the sixth most common cancer worldwide, head and neck squamous cell carcinoma (HNSCC) develops visceral metastases during the advanced stage of the disease and exhibits a low five-year survival rate. The importance of tumor microenvironment (TME) in tumor initiation and metastasis is widely recognized. In addition, accumulating evidence indicates that long non-coding RNA (lncRNA) is involved in crosstalk between TME and tumor cells. However, the lncRNA-associated regulators modulating the HNSCC microenvironment and progression remain largely unknown.

Methods

The publicly available transcriptome data and matched clinical HNSCC data were collected from The Cancer Genome Atlas (TCGA). Immune scores (ISs) and stromal scores (SSs) of HNSCC TME were calculated using ESTIMATE algorithm. Weighted gene co-expression network analysis (WGCNA) was conducted to determine the co-expressed lncRNAs and protein-coding mRNAs.

Results

Results showed that the high IS HNSCC male patient subgroup exhibited improved survival. Additionally, we identified 169 lncRNAs and 825 protein-coding mRNAs that were differentially expressed in high IS HNSCC samples, with the up-regulated mRNAs displaying enrichment in immune-related biological processes. Notably, we identified a high co-expression lncRNA-mRNA module (i.e., purple module) that showed strong correlation with ISs. This module contained 79 lncRNAs and 442 mRNAs, including 26 lncRNAs and 215 mRNAs showing association between expression and male HNSCC survival. Consistently, 207 of the 215 mRNAs were up-regulated in high IS HNSCC group and were enriched in immune-related signaling pathways. Based on bioinformatics analyses and previous functional assays, certain lncRNAs (e.g., AL365361.1 and PCED1B-AS1) in the purple module likely contributed to the modification of tumor immune microenvironment (TIME) in the high IS HNSCC patients, achieved by regulating transcription of abundant immune-related genes (e.g., CCR7 and TLR8).

Conclusions

In summary, we ascertained a HNSCC male patient subgroup that displayed high ISs and good survival probability. We identified hundreds of genes with specific expression patterns in this HNSCC subgroup as well as a highly co-expressed lncRNA-mRNA module with great potential for the modulation of TIME of HNSCC. Our study provides evidence of a link between the lncRNA-associated gene network, TIME, and HNSCC progression, and highlights potential therapeutic targets for this disease.

Identification three LncRNA prognostic signature of ovarian cancer based on genome-wide copy number variation

PURPOSE

Ovarian cancer is one of the most common malignant tumors of the female reproductive system, which seriously threatens the health of patients. It is of great significance to identify biomarkers to improve the clinical status of ovarian cancer patients.

METHODS

Methylation, RNA- sequencing, Copy number variation (CNV), mutation and clinical characteristics of ovarian cancer and control samples were downloaded from The Cancer Genome Atlas database (TCGA). The "iClusterPlus". R package was used to cluster the molecular subtypes. The copy number variation of the entire lncRNA genome was analyzed using GISTIC. The prognosis-associated lncRNA related to CNV was screened as potential targets for ovarian cancer.

RESULTS

Six molecular subtypes were identified based on multi-omics analysis and DElncRNAs are significantly enriched in specific molecular subtypes. The deletion or amplification of lncRNA copy number affects the occurrence and development of ovarian cancer to some extent. Three prognostic-associated lncRNA including LOC101927151, LINC00861 and LEMD1-AS1 were selected. These lncRNAs can be used as biomarkers to predict survival in patients with ovarian cancer. The accuracy of results were verified using the Gene Expression Omnibus (GEO) dataset.

CONCLUSION

Based on genome-wide copy number variation, prognostic-associated lncRNAs were identified as new biomolecular markers for ovarian cancer.

Updates and advancements in the management of hepatocellular carcinoma patients after hepatectomy

Introduction: The 5-year recurrence rate of hepatocellular carcinoma (HCC) after hepatic resection or local ablation is up to 70%. Adjuvant therapies to prevent HCC recurrence have been reported but are not currently recommended by EASL or AASLD guidelines. This review examined evidence from randomized controlled trials, meta-analyses and systematic reviews on the safety and efficacy of adjuvant therapies and chemotherapies in HCC patients after resection or local ablation.Areas covered: PubMed was searched through 15 June 2019. Available evidence was assessed based on the GRADE system.Expert commentary: Transarterial chemoembolization is the best adjuvant therapy for HCC patients at high risk of recurrence, antiviral therapy with nucleoside analogs is effective for preventing recurrence of HBV-related HCC, and interferon-α is effective for preventing recurrence of HCV-related HCC. Further studies are needed to clarify the efficacy of adjuvant immune checkpoint inhibitors. Adjuvant sorafenib appears to offer negligible clinical benefit and high risk of adverse effects.

Long non-coding RNA miR143HG predicts good prognosis and inhibits tumor multiplication and metastasis by suppressing mitogen-activated protein kinase and Wnt signaling pathways in hepatocellular carcinoma

AIM

The expression of microRNA143HG (miR143HG) was significantly downregulated in hepatocellular carcinoma (HCC) tissues by bioinformatics analysis. This study aimed to determine the role of miR143HG in HCC cell proliferation and metastasis.

METHODS

Fifty patients with HCC were divided into two groups based on median miR143HG expression levels. The correlation between miR143HG expression and prognosis, and the correlations between miR143HG expression and the patients' clinicopathological characteristics were evaluated based on the two groups. Gain-of-function and loss-of-function measurements of miR143HG were carried out to verify the biological function of miR143HG by Cell Counting Kit-8, EdU, Transwell, and western blotting assays and flow cytometric analysis. The underlying mechanism was explored by quantitative real-time polymerase chain reaction of miRNA (miR-155-5p and miR-26b-5p), luciferase reporter assay, western blotting of Wnt signaling pathway-related proteins (β-catenin, adenomatous polyposis coli (APC), glycogen synthase kinase 3β (GSK3β), ZEB1, and E-cadherin), mitogen-activated protein kinase (MAPK) signaling pathway-related proteins (extracellular signal-regulated kinase [ERK]1/2, p-ERK1/2, c-Jun N-terminal kinase (JNK), p-JNK, P38, and p-P38), and immunofluorescence staining of β-catenin.

RESULTS

miR143HG expression was markedly downregulated in HCC tissues and cells. Its expression was associated with the presence or absence of portal vein tumor thrombus, hepatitis B virus infection, relapse and metastasis, and Barcelona Clinic Liver Cancer stage. Additionally, miR143HG expression predicted a good prognosis and acted as an independent prognostic factor in HCC for overall survival. Overexpression of miR143HG suppressed HCC cell proliferation and metastasis, and induced cell cycle arrest and apoptosis. Consistently, the depletion of miR143HG resulted in the opposite phenomenon of the aforementioned results. miR143HG inhibits miR-155 expression; miR-155 directly targets APC, which is a negative regulator of the Wnt/β-catenin pathway, so miR143HG can act on the Wnt pathway. miR143HG was further found to reduce the expression of β-catenin and block the nuclear accumulation of β-catenin, ultimately inhibiting the activation of the Wnt pathway. It inhibits the expression of Wnt downstream target gene ZEB1, and then E-cadherin expression is increased and cell motility is inhibited. Furthermore, miR143HG exerts its antiproliferative function by influencing the MAPK signaling pathway and then inducing G₂ /M arrest in cells.

CONCLUSION

This study showed that miR143HG plays critical roles in the development and progression of HCC by suppressing the MAPK and Wnt signaling pathways.

Bioinformatics profiling utilized a nine immune-related long noncoding RNA signature as a prognostic target for pancreatic cancer

PURPOSE

To identify an immune-related long noncoding RNA (lncRNA) signature with potential prognostic value for patients with pancreatic cancer.

METHODS

Pancreatic cancer samples with available clinical information and whole genomic mRNA expression data obtained from The Cancer Genome Atlas (TCGA) were enrolled in our research. The immune score of each sample was calculated according to the expression level of immune-related genes and used to identify the most promising immune-related lncRNAs. According to the risk score developed from screened immune-related lncRNAs, the high- and low-risk groups were separated on the basis of the median risk score. The prediction reliability was further evaluated in the validation set and combination set. Both gene set enrichment analysis (GSEA) and principal component analysis (PCA) were performed for functional annotation, and the microenvironment cell population record was applied to evaluate the immune composition and purity of the tumor.

RESULTS

A cohort of 176 samples was included in this study. A total of 163 immune-related lncRNAs were collected according to Pearson correlation analyses between immune score and lncRNA expression |R| > 0.5, P < 0.01). Nine immune-related lncRNAs (AL138966.2, AL133520.1, AC142472.1, AC127024.5, AC116913.1, AC083880.1, AC124016.1, AC008443.5, and AC092171.5) with the most significant prognostic values (P < 0.01) were identified. In the training set, it was observed that patients in the low-risk group showed longer overall survival (OS) than those in the high-risk group (P < 0.001); meanwhile, similar results were found in the validation set, combination set and various stratified sets (P < 0.05, P < 0.001, P < 0.05, respectively). Moreover, the signature was identified as an independent prognostic factor and significantly associated with the OS of pancreatic cancer. The area under curve (AUC) of the receiver operating characteristic curve (ROC curve) for the nine lncRNA signature in predicting the 2-year survival rate was 0.703. In addition, the low-risk and high-risk groups displayed different distributed patterns in PCA and different immune statuses in the GSEA. The signature indicated decreased purity of the tumor by implying a lower proportion of cancer cells along with an increasing enrichment of fibroblasts, myeloid dendritic cells, and monocytic lineage cells.

CONCLUSIONS

Our research suggests that the immune-related lncRNA signature possesses latent prognostic value for patients with pancreatic cancer and may provide new information for immunological research and treatment in pancreatic cancer.

Integrated analysis of a competing endogenous RNA network reveals key long noncoding RNAs as potential prognostic biomarkers for hepatocellular carcinoma

Growing evidence has revealed that long noncoding RNAs (lncRNAs) have an important impact on tumorigenesis and tumor progression via a mechanism involving competing endogenous RNAs (ceRNAs). However, their use in predicting the survival of a patient with hepatocellular carcinoma (HCC) remains unclear. The aim of this study was to develop a novel lncRNA expression-based risk score system to accurately predict the survival of patients with HCC. In our study, using expression profiles downloaded from The Cancer Genome Atlas database, the differentially expressed messenger RNAs (mRNAs), lncRNAs, and microRNAs (miRNAs) were explored in patients with HCC and normal liver tissues, and then a ceRNA network constructed. A risk score system was established between lncRNA expression of the ceRNA network and overall survival (OS) or recurrence-free survival (RFS); it was further analyzed for associations with the clinical features of patients with HCC. In HCC, 473 differentially expressed lncRNAs, 63 differentially expressed miRNAs, and 1417 differentially expressed mRNAs were detected. The ceRNA network comprised 41 lncRNA nodes, 12 miRNA nodes, 24 mRNA nodes, and 172 edges. The lncRNA expression-based risk score system for OS was constructed based on six lncRNAs (MYLK-AS1, AL359878.1, PART1, TSPEAR-AS1, C10orf91, and LINC00501), while the risk score system for RFS was based on four lncRNAs (WARS2-IT1, AL359878.1, AL357060.1, and PART1). Univariate and multivariate Cox analyses showed the risk score systems for OS or RFS were significant independent factors adjusted for clinical factors. Receiver operating characteristic curve analysis showed the area under the curve for the risk score system was 0.704 for OS, and 0.71 for RFS. Our result revealed a lncRNA expression-based risk score system for OS or RFS can effectively predict the survival of patients with HCC and aid in good clinical decision-making.

Comprehensive analysis of a ceRNA network reveals potential prognostic cytoplasmic lncRNAs involved in HCC progression

The aberrant expression of long noncoding RNAs (lncRNAs) has drawn increasing attention in the field of hepatocellular carcinoma (HCC) biology. In the present study, we obtained the expression profiles of lncRNAs, microRNAs (miRNAs), and messenger RNAs (mRNAs) in 371 HCC tissues and 50 normal tissues from The Cancer Genome Atlas (TCGA) and identified hepatocarcinogenesis‐specific differentially expressed genes (DEGs, log fold change ≥ 2, FDR < 0.01), including 753 lncRNAs, 97 miRNAs, and 1,535 mRNAs. Because the specific functions of lncRNAs are closely related to their intracellular localizations and because the cytoplasm is the main location for competitive endogenous RNA (ceRNA) action, we analyzed not only the interactions among these DEGs but also the distributions of lncRNAs (cytoplasmic, nuclear or both). Then, an HCC‐associated deregulated ceRNA network consisting of 37 lncRNAs, 10 miRNAs, and 26 mRNAs was constructed after excluding those lncRNAs located only in the nucleus. Survival analysis of this network demonstrated that 15 lncRNAs, 3 miRNAs, and 16 mRNAs were significantly correlated with the overall survival of HCC patients (p < 0.01). Through multivariate Cox regression and lasso analysis, a risk score system based on 13 lncRNAs was constructed, which showed good discrimination and predictive ability for HCC patient survival time. This ceRNA network‐construction approach, based on lncRNA distribution, not only narrowed the scope of target lncRNAs but also provided specific candidate molecular biomarkers for evaluating the prognosis of HCC, which will help expand our understanding of the ceRNA mechanisms involved in the early development of HCC.

Identification of key genes involved in the metastasis of clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common and lethal renal malignant tumor in adults. The aim of the present study was to identify the key genes involved in ccRCC metastasis. Expression profiling data for ccRCC patients with metastasis and without metastasis were obtained from The Cancer Genome Atlas database. The datasets were used to identify differentially expressed genes (DEGs) between the metastasis group and the non-metastasis group using the DESeq2 package. Function enrichment analyses of DEGs were performed. The protein-protein interaction (PPI) network was constructed and analyzed using the Search Tool for the Retrieval of Interacting Genes and Cytoscape for further analysis of the identified hub genes. A total of 472 DEGs were identified, including 247 that were upregulated and 225 that were downregulated in the metastasis group. Gene Ontology enrichment analysis revealed that DEGs were mainly enriched in cell transmembrane movement and mitotic cell cycle process. Kyoto Encyclopedia of Genes Genomes pathway analysis revealed that the DEGs were mainly involved in the ‘cell cycle’ (hsa04110), ‘collecting duct acid secretion’ (hsa04966), ‘complement and coagulation cascades’ (hsa04610) and ‘aldosterone-regulated sodium reabsorption’ (hsa04960) pathways. Using the PPI network, 35 hub genes were identified, and the majority of them were upregulated in ccRCC tissue compared with normal kidney tissue. The expression levels of certain hub genes (CDKN3, TPX2, BUB1B, CDCA8, UBE2C, NDC80, RRM2, NCAPG, NCAPH, PTTG1, FAM64A, ANLN, KIF4A, CEP55, CENPF, KIF20A, ASPM and HJURP) were significantly associated with overall survival and recurrence-free survival in ccRCC. The present study has identified key genes associated with the metastasis of ccRCC.