An angiogenesis-related long noncoding RNA signature correlates with prognosis in patients with hepatocellular carcinoma

A Model to Predict Prognosis of Renal Cell Clear Cell Carcinoma Based on 3 Angiogenesis-related Long Non-coding RNAs

Background: Tumor angiogenesis is closely related to the progression of clear cell renal cell carcinoma (ccRCC). Long non-coding RNAs (lncRNAs) regulating angiogenesis could be potential biomarkers for predicting ccRCC prognosis. With this study, we aimed to construct a prognostic model based on lncRNAs and explore its underlying mechanisms. Methods: RNA data and clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Angiogenesis-related genes (ARGs) were extracted from the Molecular Signatures database. Pearson correlation and LASSO and COX regression analyses were performed to identify survival-related AR-lncRNAs (sAR-lncRNAs) and construct a prognostic model. The predictive power of the prognostic model was verified according to Kaplan‒Meier curve, receiver operating characteristic (ROC) curve and nomogram analyses. The correlation between the prognostic model and clinicopathological characteristics was assessed via univariate and multivariate analyses. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was subsequently performed to elucidate the mechanisms of the sAR-lncRNAs. In vitro qPCR, immunohistochemistry, migration and invasion assays were conducted to confirm the angiogenic function of sAR-lncRNAs. Results: Three sAR-lncRNAs were used to construct a prognostic model. The model was moderately accurate in predicting 1- , 3- and 5-year ccRCC prognosis, and the risk score according to this model was closely related to clinicopathological characteristics such as T grade and T stage. A nomogram was constructed to precisely estimate the overall survival of ccRCC patients. KEGG enrichment analysis indicated that the MAPK and Notch pathways were highly enriched in high-risk patients. Additionally, we found that the expression of the lncRNAs AC005324.4 and AC104964.4 in the prognostic model was lower in ccRCC cell lines and cancer tissues than in the HK-2 cell line and paracancerous tissues, while the expression of the lncRNA AC087482.1 showed the opposite trend. In a coculture model, knockdown of lncRNA AC005324.4 and lncRNA AC104964.4 significantly promoted the migration and invasion of human umbilical vein endothelial cells (HUVECs), but siR-AC087482.1 transfection alleviated these effects. Conclusions: We constructed a prognostic model based on 3 sAR-lncRNAs and validated its value in clinicopathological characteristics and prognostic prediction of ccRCC patients, providing a new perspective for ccRCC treatment decision making.

MicroRNAs as the critical regulators of tumor angiogenesis in liver cancer

Liver cancer is one of the most common malignancies in human digestive system. Despite the recent therapeutic methods, there is a high rate of mortality among liver cancer patients. Late diagnosis in the advanced tumor stages can be one of the main reasons for the poor prognosis in these patients. Therefore, investigating the molecular mechanisms of liver cancer can be helpful for the early stage tumor detection and treatment. Vascular expansion in liver tumors can be one of the important reasons for poor prognosis and aggressiveness. Therefore, anti-angiogenic drugs are widely used in liver cancer patients. MicroRNAs (miRNAs) have key roles in the regulation of angiogenesis in liver tumors. Due to the high stability of miRNAs in body fluids, these factors are widely used as the non-invasive diagnostic and prognostic markers in cancer patients. Regarding, the importance of angiogenesis during liver tumor growth and invasion, in the present review, we discussed the role of miRNAs in regulation of angiogenesis in these tumors. It has been reported that miRNAs mainly exert an anti-angiogenic function by regulation of tumor microenvironment, transcription factors, and signaling pathways in liver tumors. This review can be an effective step to suggest the miRNAs for the non-invasive early detection of malignant and invasive liver tumors.

Identifying Treatment Resistance Related Pathways by Analyzing Serum Extracellular Vesicles of Patients With Resistant Versus Regressed Retinoblastoma

Purpose

To identify the genes and pathways responsible for treatment resistance (TR) in retinoblastoma (RB) by analyzing serum small extracellular vesicles (sEVs) of patients with TR active RB (TR-RB) and completely regressed RB (CR-RB).

Methods

Serum-derived sEVs were characterized by transmission electron microscopy and nanoparticle tracking analysis. sEV transcriptome profiles of two TR-RB and one CR-RB with good response (>20 years tumor free) were compared to their age-matched controls (n = 3). Gene expression data were analyzed by the R Bioconductor package. The CD9 protein and mRNA expression of CD9, CD63, and CD81 were studied in five RB tumors and two control retinae by immunohistochemistry and quantitative reverse transcription-polymerase chain reaction.

Results

The isolated serum sEVs were round shaped and within the expected size (30-150 nm), and they had zeta potentials ranging from -10.8 to 15.9 mV. The mean ± SD concentrations of sEVs for two adults and four children were 1.1 × 1012 ± 0.1 and 5.8 × 1011 ± 1.7 particles/mL. Based on log2 fold change of ±2 and P < 0.05 criteria, there were 492 dysregulated genes in TR-RB and 184 in CR-RB. KAT2B, VWA1, CX3CL1, MLYCD, NR2F2, USP46-AS1, miR6724-4, and LINC01257 genes were specifically dysregulated in TR-RB. Negative regulation of apoptotic signaling, cell growth, and proton transport genes were greater than fivefold expressed only in TR-RB. CD9, CD63, and CD81 mRNA levels were high in RB tumors versus control retina, with increased and variable CD9 immunoreactivity in the invasive areas of the tumor.

Conclusions

Serum sEVs could serve as a potential liquid biopsy source for understanding TR mechanisms in RB.

Construction and validation of an angiogenesis-related lncRNA prognostic model in lung adenocarcinoma

Background: There is increasing evidence that long non-coding RNAs (lncRNAs) can be used as potential prognostic factors for cancer. This study aimed to develop a prognostic model for lung adenocarcinoma (LUAD) using angiogenesis-related long non-coding RNAs (lncRNAs) as potential prognostic factors.

Methods: Transcriptome data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) were analyzed to identify aberrantly expressed angiogenesis-related lncRNAs in LUAD. A prognostic signature was constructed using differential expression analysis, overlap analysis, Pearson correlation analysis, and Cox regression analysis. The model’s validity was assessed using K-M and ROC curves, and independent external validation was performed in the GSE30219 dataset. Prognostic lncRNA-microRNA (miRNA)-messenger RNA (mRNA) competing endogenous RNA (ceRNA) networks were identified. Immune cell infiltration and mutational characteristics were also analyzed. The expression of four human angiogenesis-associated lncRNAs was quantified using quantitative real-time PCR (qRT-PCR) gene arrays.

Results: A total of 26 aberrantly expressed angiogenesis-related lncRNAs in LUAD were identified, and a Cox risk model based on LINC00857, RBPMS-AS1, SYNPR-AS1, and LINC00460 was constructed, which may be an independent prognostic predictor for LUAD. The low-risk group had a significant better prognosis and was associated with a higher abundance of resting immune cells and a lower expression of immune checkpoint molecules. Moreover, 105 ceRNA mechanisms were predicted based on the four prognostic lncRNAs. qRT-PCR results showed that LINC00857, SYNPR-AS1, and LINC00460 were significantly highly expressed in tumor tissues, while RBPMS-AS1 was highly expressed in paracancerous tissues.

Conclusion: The four angiogenesis-related lncRNAs identified in this study could serve as a promising prognostic biomarker for LUAD patients.

An Angiogenesis-Related lncRNA Signature Is Associated with Prognosis and Tumor Immune Microenvironment in Breast Cancer

Angiogenesis is crucial in the development and progression of tumors. This study examined the relationship between angiogenesis-related lncRNAs (AR-lncRNAs) and breast cancer (BC) immunity and prognosis. We used univariate Cox regression analysis to obtain AR-lncRNAs closely related to BC prognosis. Cluster analysis of BC patients was performed using non-negative matrix factorization (NMF) analysis according to the expression of AR-lncRNAs that were prognostically relevant. An AR-lncRNA risk model (AR-lncM) was created using LASSO regression analysis to predict the prognosis and survival of BC patients. Subsequently, the effect of LINC01614 on cell migration and invasion was verified by Transwell and Western blot assays, and the CCK-8 assay detected its impact on cell sensitivity to tamoxifen. Finally, we obtained 17 AR-lncRNAs from the TCGA database that were closely associated with the prognosis of BC patients. Based on the expression of these AR-lncRNAs, BC patients were divided into five clusters using NMF analysis. Cluster 1 was found to have a better prognosis, higher expression of immune checkpoints, and higher levels of immune cell infiltration. Furthermore, an AR-LncM model was created using ten prognostic-related AR-lncRNAs. The model’s risk predictive performance was validated using survival analysis, timeROC curves, and univariate and multivariate Cox analysis. The most interesting gene in the model, LINC01614, was found to regulate epithelial-mesenchymal transition (EMT) and tamoxifen sensitivity in BC cells, implying that LINC01614 could be a potential therapeutic target for BC patients.

Identification and validation of a novel angiogenesis-related gene signature for predicting prognosis in gastric adenocarcinoma

Background

Angiogenesis is a major promotor of tumor progression and metastasis in gastric adenocarcinoma (STAD). We aimed to develop a novel lncRNA gene signature by identifying angiogenesis-related genes to better predict prognosis in STAD patients.

Methods

The expression profiles of angiogenesis-related mRNA and lncRNA genes were collected from The Cancer Genome Atlas (TCGA). Then, the "limma" package was used to identify differentially expressed genes (DEGs). The expression profiles of angiogenesis-related genes were clustered by consumusclusterplus. The Pearson correlation coefficient was further used to identify lncRNAs coexpressed with angiogenesis-related clustere genes. We used Lasso Cox regression analysis to construct the angiogenesis-related lncRNAs signature. Furthermore, the diagnostic accuracy of the prognostic risk signature were validated by the TCGA training set, internal test sets and external test set. We used multifactor Cox analysis to determine that the risk score is an independent prognostic factor different from clinical characteristics. Nomogram has been used to quantitatively determine personal risk in a clinical environment. The ssGSEA method or GSE176307 data were used to evaluate the infiltration state of immune cells or predictive ability for the benefit of immunotherapy by angiogenesis-related lncRNAs signature. Finally, the expression and function of these signature genes were explored by RT-PCR and colony formation assays.

Results

Among angiogenesis-related genes clusters, the stable number of clusters was 2. A total of 289 DEGs were identified and 116 lncRNAs were screened to have a significant coexpression relationship with angiogenic DEGs (P value<0.001 and |R| >0.5). A six-gene signature comprising LINC01579, LINC01094, RP11.497E19.1, AC093850.2, RP11.613D13.8, and RP11.384P7.7 was constructed by Lasso Cox regression analysis. The multifactor Cox analysis and Nomogram results showed that our angiogenesis-related lncRNAs signature has good predictive ability for some different clinical factors. For immune, angiogenesis-related lncRNAs signature had the ability to efficiently predict infiltration state of 23 immune cells and immunotherapy. The qPCR analysis showed that the expression levels of the six lncRNA signature genes were all higher in gastric adenocarcinoma tissues than in adjacent tissues. The functional experiment results indicated that downregulation of the expression of these six lncRNA signature genes suppressed the proliferation of ASG and MKN45 cells.

Conclusion

Six angiogenesis-related genes were identified and integrated into a novel risk signature that can effectively assess prognosis and provide potential therapeutic targets for STAD patients.

The Pyroptosis-Related Long Noncoding RNA Signature Predicts Prognosis and Indicates Immunotherapeutic Efficiency in Hepatocellular Carcinoma

Pyroptosis was recently demonstrated to be an inflammatory form of gasdermin-regulated programmed cell death characterized by cellular lysis and the release of several proinflammatory factors and participates in tumorigenesis. However, the effects of pyroptosis-related long noncoding RNAs (lncRNAs) on hepatocellular carcinoma (HCC) have not yet been completely elucidated. Based on the regression coefficients of ZFPM2-AS1, KDM4A-AS1, LUCAT1, NRAV, CRYZL2P-SEC16B, AL031985.3, SNHG4, AL049840.5, AC008549.1, MKLN1-AS, AC099850.3, and LINC01224, HCC patients were classified into a low- or high-risk group. The high-risk score according to pyroptosis-related lncRNA signature was significantly associated with poor overall survival even after adjusting for age and clinical stage. Receiver operating characteristic curves and principal component analysis further supported the accuracy of the model. Our study revealed that a higher pyroptosis-related lncRNA risk score was significantly associated with tumor staging, pathological grade, and tumor-node-metastasis stages. The nomogram incorporating the pyroptosis-related lncRNA risk score and clinicopathological factors demonstrated good accuracy. Furthermore, we observed distinct tumor microenvironment cell infiltration characteristics between high- and low-risk tumors. Notably, based on the risk model, we found that the risk score is closely related to the expression of immune checkpoint genes, immune subtypes of tumors, and the sensitivity of HCC to chemotherapy drugs and immunotherapy. In conclusion, our novel risk score of pyroptosis-related lncRNA can serve as a promising prognostic biomarker for HCC patients and provide help for HCC patients to guide precision drug treatment and immunotherapy.

LncRNAs and the Angiogenic Switch in Cancer: Clinical Significance and Therapeutic Opportunities

Angiogenesis is one of the hallmarks of cancer, and the establishment of new blood vessels is vital to allow for a tumour to grow beyond 1-2 mm in size. The angiogenic switch is the term given to the point where the number or activity of the pro-angiogenic factors exceeds that of the anti-angiogenic factors, resulting in the angiogenic process proceeding, giving rise to new blood vessels accompanied by increased tumour growth, metastasis, and potential drug resistance. Long noncoding ribonucleic acids (lncRNAs) have been found to play a role in the angiogenic switch by regulating gene expression, transcription, translation, and post translation modification. In this regard they play both anti-angiogenic and pro-angiogenic roles. The expression levels of the pro-angiogenic lncRNAs have been found to correlate with patient survival. These lncRNAs are also potential drug targets for the development of therapies that will inhibit or modify tumour angiogenesis. Here we review the roles of lncRNAs in regulating the angiogenic switch. We cover specific examples of both pro and anti-angiogenic lncRNAs and discuss their potential use as both prognostic biomarkers and targets for the development of future therapies.

Angiogenesis-related lncRNAs predict the prognosis signature of stomach adenocarcinoma

Background

Stomach adenocarcinoma (STAD), which accounts for approximately 95% of gastric cancer types, is a malignancy cancer with high morbidity and mortality. Tumor angiogenesis plays important roles in the progression and pathogenesis of STAD, in which long noncoding RNAs (lncRNAs) have been verified to be crucial for angiogenesis. Our study sought to construct a prognostic signature of angiogenesis-related lncRNAs (ARLncs) to accurately predict the survival time of STAD.

Methods

The RNA-sequencing dataset and corresponding clinical data of STAD were acquired from The Cancer Genome Atlas (TCGA). ARLnc sets were obtained from the Ensemble genome database and Molecular Signatures Database (MSigDB, Angiogenesis M14493, INTegrin pathway M160). A ARLnc-related prognostic signature was then constructed via univariate Cox and multivariate Cox regression analysis in the training cohort. Survival analysis and Cox regression were performed to assess the performance of the prognostic signature between low- and high-risk groups, which was validated in the validation cohort. Furthermore, a nomogram that combined the clinical pathological characteristics and risk score conducted to predict the overall survival (OS) of STAD. In addition, ARLnc-mRNA coexpression pairs were constructed with Pearson’s correlation analysis and visualized to infer the functional annotation of the ARLncs by gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. The expression of four ARLncs in STAD and their correlation with the angiogenesis markers, CD34 and CD105, were also validated by RT–qPCR in a clinical cohort.

Results

A prognostic prediction signature including four ARLncs (PVT1, LINC01315, AC245041.1, and AC037198.1) was identified and constructed. The OS of patients in the high-risk group was significantly lower than that of patients in the low-risk group (p < 0.001). The values of the time-dependent area under the curve (AUC) for the ARLnc signature for 1-, 3-, and 5- year OS were 0.683, 0.739, and 0.618 in the training cohort and 0.671, 0.646, and 0.680 in the validation cohort, respectively. Univariate and multivariate Cox regression analyses indicated that the ARLnc signature was an independent prognostic factor for STAD patients (p < 0.001). Furthermore, the nomogram and calibration curve showed accurate prediction of the survival time based on the risk score. In addition, 262 mRNAs were screened for coexpression with four ARLncs, and GO analysis showed that mRNAs were mainly involved in biological processes, including angiogenesis, cell adhesion, wound healing, and extracellular matrix organization. Furthermore, correlation analysis showed that there was a positive correlation between risk score and the expression of the angiogenesis markers, CD34 and CD105, in TCGA datasets and our clinical sample cohort.

Conclusion

Our study constructed a prognostic signature consisting of four ARLnc genes, which was closely related to the survival of STAD patients, showing high efficacy of the prognostic signature. Thus, the present study provided a novel biomarker and promising therapeutic strategy for patients with STAD.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08987-y.

Prognostic value of microvessel density in esophageal squamous cell carcinoma-a systematic review and meta-analysis

OBJECTIVE

Angiogenesis produced by tumor microenvironment is play an important role in development of esophageal squamous cell carcinoma (ESCC). As a quantitative index of angiogenesis, literature has emerged contradictory results about the prognostic role of microvessel density (MVD) in ESCC. The aim of the study was to explore the impact of the correlation between MVD and the prognosis of ESCC based the published evidence.

METHODS

Pubmed and Web of science database were screened for the relationship of MVD with prognostic feature in ESCC up to March, 2021. 11 relevant articles were used for meta-analysis. The following data were extracted from the literature: author, year, country, the patients number of high/low MVD, tumor-node-metastasis (TNM) classification, clinical stage, lymphoid infiltrates, vessel invasion, invasive depth, differential degree and survival rate. The hazard ratio (HR) and odds ratios (OR) with 95% CI were used to assess the associations between MVD and overall survival (OS). Chi-squared test and I² statistics were completed to evaluate the heterogeneity in our study. A random-effects model was used when significant heterogeneity existed (I²>50% and p < 0.05). Egger test was used to calculate the publication bias. Subgroup analysis was stratified by antibody, region, sample capacity to explore the source of heterogeneity.

RESULTS

11 studies with 1055 patients were analyzed. Our results suggested that high MVD is an important factor to advanced TNM classification and clinical stage, and the high MVD is positive correlation with the lymph node invasion and vascular invasion(p < 0.05) in ESCC, but irrelevant to poor differential and invasive depth(p > 0.05). The result also indicated that low MVD is a benefit factor to prolong the survival rate (p < 0.05). And the source of the heterogeneity maybe is that the antibody used to detect the MVD was not consistent, patient number was not large enough and the count method on MVD.

CONCLUSION

Across multiple studies, high MVD is correlated with clinicopathological criteria of poor prognosis and survival in ESCC. MVD could be the quantitative index to reactive angiogenesis and may play a pivotal role in ESCC development and progression. MVD may represent a valuable addition to current pathologic analysis and help to guide prognosis and treatment.

Construction of a Novel Immune-Related lncRNA Pair Signature with Prognostic Significance for Kidney Clear Cell Renal Cell Carcinoma

Background

Renal cell carcinoma (RCC) is one of the most common aggressive malignant tumors in the urinary system, among which the clear cell renal cell carcinoma (ccRCC) is the most common subtype. The immune-related long noncoding ribonucleic acids (irlncRNAs) which are abundant in immune cells and immune microenvironment (IME) have potential significance in evaluating the prognosis and effects of immunotherapy. The signature based on irlncRNA pairs and independent of the exact expression level seems to have a latent predictive significance for the prognosis of patients with malignant tumors but has not been applied in ccRCC yet.

Method

In this article, we retrieved The Cancer Genome Atlas (TCGA) database for the transcriptome profiling data of the ccRCC and performed coexpression analysis between known immune-related genes (ir-genes) and lncRNAs to find differently expressed irlncRNA (DEirlncRNA). Then, we adopted a single-factor test and a modified LASSO regression analysis to screen out ideal DEirlncRNAs and constructed a Cox proportional hazard model. We have sifted 28 DEirlncRNA pairs, 12 of which were included in this model. Next, we compared the area under the curve (AUC), found the cutoff point by using the Akaike information criterion (AIC) value, and distinguished the patients with ccRCC into a high-risk group and a low-risk group using this value. Finally, we tested this model by investigating the relationship between risk score and survival, clinical pathological characteristics, cells in tumor immune microenvironment, chemotherapy, and targeted checkpoint biomarkers.

Results

A novel immune-related lncRNA pair signature consisting of 12 DEirlncRNA pairs was successfully constructed and tightly associated with overall survival, clinical pathological characteristics, cells in tumor immune microenvironment, and reactiveness to immunotherapy and chemotherapy in patients with ccRCC. Besides, the efficacy of this signature was verified in some commonly used clinicopathological subgroups and could serve as an independent prognostic factor in patients with ccRCC.

Conclusions

This signature was proven to have a potential predictive significance for the prognosis of patients with ccRCC and the efficacy of immunotherapy.