The landscape of long noncoding RNA-involved and tumor-specific fusions across various cancers

Breaking paradigms: Long non-coding RNAs forming gene fusions with potential implications in cancer

Long non-coding RNAs (lncRNAs) are non-coding RNAs longer than 200 nucleotides with dynamic regulatory functions. They interact with a wide range of molecules such as DNA, RNA, and proteins to modulate diverse cellular functions through several mechanisms and, if deregulated, they can lead to cancer development and progression. Recently, it has been described that lncRNAs are susceptible to form gene fusions with mRNAs or other lncRNAs, breaking the paradigm of gene fusions consisting mainly of protein-coding genes. However, their biological significance in the tumor phenotype is still uncertain. Therefore, their recent identification opens a new line of research to study their biological role in tumorigenesis, and their potential as biomarkers with clinical relevance or as therapeutic targets. The present study aimed to review the lncRNA fusions identified so far and to know which of them have been associated with a potential function. We address the current challenges to deepen their study as well as the reasons why they represent a future therapeutic window in cancer.

Prognostic and onco-immunological value of immune-related eRNAs-driven genes in lung adenocarcinoma

BACKGROUND

We aimed to comprehensively analyze the clinical value of immune-related eRNAs-driven genes in lung adenocarcinoma (LUAD) and find the potential biomarkers for prognosis and therapeutic response to improve the survival of this malignant disease.

MATERIALS AND METHODS

Pearson's correlation analysis was performed to identify the immune-related eRNAs-driven genes. Cox regression and least absolute shrinkage and selection operator (LASSO) analyses were used to construct this prognostic risk signature. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were used to investigate the underlying molecular mechanism. The single sample gene set enrichment analysis (ssGSEA) algorithm was conducted to evaluate the immune status based on the signature. The quantitative real-time PCR (qRT-PCR) analysis was performed to evaluate the expression value of the signature genes between LUAD tissues and adjacent lung tissues.

RESULTS

Five immune-related eRNAs-driven genes (SHC1, GDF10, CCL14, FYN, and NOD1) were identified to construct a prognostic risk signature with favorable predictive capacity. The patients with high-risk scores based on the signature were significantly associated with the malignant clinical features compared with those with low-risk scores. Kaplan-Meier analysis demonstrated that the sample in the low-risk group had a prolonged survival compared with those in the high-risk group. This risk signature was validated to have a promising predictive capacity and reliability in diverse clinical situations and independent cohorts. The functional enrichment analysis demonstrated that humoral immune response and intestinal immune network for IgA production pathway might be the underlying molecular mechanism related to the signature. The proportion of the vast majority of immune infiltrating cells in the high-risk group was significantly lower than that in the low-risk group, and the immunotherapy response rate in the low-risk group was significantly higher than that in the high-risk group. Moreover, BI-2536, sepantronium bromide, and ULK1 were the potential drugs for the treatment of patients with higher risk scores. Finally, the experiment in vivo and database analysis indicated that CCL14, FYN, NOD1, and GDF10 are the potential LUAD suppressor and SHC1 is a potential treatment target for LUAD.

CONCLUSION

Above all, we constructed a prognostic risk signature with favorable predictive capacity in LUAD, which was significantly associated with malignant features, immunosuppressive tumor microenvironment, and immunotherapy response and may provide clinical benefit in clinical decisions.

Plasma circulating microRNAs associated with blood-based immune markers: a population-based study

MicroRNAs (miRNAs) are small non-coding RNAs that post-transcriptionally regulate gene expression and different immune-related pathways. There is a great interest in identifying miRNAs involved in immune cell development and function to elucidate the biological mechanisms underlying the immune system, its regulation, and disease. In this study, we aimed to investigate the association of circulating miRNAs with blood cell compositions and blood-based immune markers. Circulating levels of 2083 miRNAs were measured by RNA-sequencing in plasma samples of 1999 participants from the population-based Rotterdam Study collected between 2002 and 2005. Full blood count measurements were performed for absolute granulocyte, platelet, lymphocyte, monocyte, white, and red blood cell counts. Multivariate analyses were performed to test the association of miRNAs with blood cell compositions and immune markers. We evaluated the overlap between predicted target genes of candidate miRNAs associated with immune markers and genes determining the blood immune response markers. First, principal component regression analysis showed that plasma levels of circulating miRNAs were significantly associated with red blood cell, granulocyte, and lymphocyte counts. Second, the cross-sectional analysis identified 210 miRNAs significantly associated (P < 2.82 × 10-5) with neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index. Further genetic look-ups showed that target genes of seven identified miRNAs (miR-1233-3p, miR-149-3p, miR-150-5p, miR-342-3p, miR-34b-3p, miR-4644, and miR-7106-5p) were also previously linked to NLR and PLR markers. Collectively, our study suggests several circulating miRNAs that regulate the innate and adaptive immune systems, providing insight into the pathogenesis of miRNAs in immune-related diseases and paving the way for future clinical applications.

Development of a Novel Pyroptosis-Associated lncRNA Biomarker Signature in Lung Adenocarcinoma

Pyroptosis is a novel type of cell death observed in various diseases. Our study aimed to investigate the relationship between pyroptosis-associated-long non-coding RNAs (lncRNAs), immune infiltration, and expression of immune checkpoints in the setting of lung adenocarcinoma and the prognostic value of pyroptosis-related lncRNAs. RNA-seq transcriptome data and clinical information from The Cancer Genome Atlas (TCGA) were downloaded, and consensus clustering analysis was used to separate the samples into two groups. Least absolute shrinkage and selection operator (LASSO) analyses were conducted to construct a risk signature. The association between pyroptosis-associated lncRNAs, immune infiltration, and expression of immune checkpoints were analysed. The cBioPortal tool was used to discover genomic alterations. Gene set enrichment analysis (GSEA) was utilized to investigate downstream pathways of the two clusters. Drug sensitivity was also examined. A total of 43 DEGs and 3643 differentially expressed lncRNAs were identified between 497 lung adenocarcinoma tissues and 54 normal samples. A signature consisting of 11 pyroptosis-related lncRNAs was established as prognostic for overall survival. Patients in the low-risk group have a significant overall survival advantage over those in the high-risk group in the training group. Immune checkpoints were expressed differently between the two risk groups. Risk scores were validated to develop an independent prognostic model based on multivariate Cox regression analysis. The area under time-dependent receiver operating characteristic curve (AUC of the ROC) at 1-, 3-, and 5-years measured0.778, 0.757, and 0.735, respectively. The high-risk group was more sensitive to chemotherapeutic drugs than the low-risk group. This study demonstrates the association between pyroptosis-associated lncRNAs and prognosis in lung adenocarcinoma and enables a robust predictive signature of 11 lncRNAs to inform overall survival.

Research progress and perspectives of noncoding RNAs in adrenocortical carcinoma: A review

Adrenocortical carcinoma (ACC) is a rare and highly aggressive endocrine malignancy. Although surgery can cure localized disease, but the majority of patients experience recurrence of ACC. The 5-year survival rate of patients with metastatic ACC is <15%, and the prognosis is poor. Therefore, it is urgent to explore the potential diagnostic markers and therapeutic targets for ACC. Recently, it has been proved that non-coding RNA (ncRNAs) is widely involved in pathological and physiological processes, including tumorigenesis and development. Aberrantly expressed ncRNAs have been found to be involved in the pathogenesis of ACC. Here, we summarized the expression patterns and the molecular mechanism of the involvement of microRNAs (miRNAs), long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) in ACC development. To explore the clinical value of ncRNAs as noninvasive biomarkers of ACC, we also displayed the relationship between the expression level of ncRNAs and the diagnosis and prognosis of patients with ACC.

Novel model of pyroptosis-related molecular signatures for prognosis prediction of clear cell renal cell carcinoma patients

Background: Pyroptosis is a programmed death mode of inflammatory cells, which is closely related to tumor progression and tumor immunity. Clear cell renal cell carcinoma (ccRCC) is the major pathological type of renal cell carcinoma (RCC) with poor prognosis. Many theories have tried to clarify the mechanism in the development of ccRCC, but the role of pyroptosis in ccRCC has not been well described. The main purpose of this study is to explore the role of pyroptosis in ccRCC and establish a novel prognosis prediction model of pyroptosis-related molecular signatures for ccRCC. Methods: In the present study, we made a systematical analysis of the association between ccRCC RNA transcriptome sequencing data from The Cancer Genome Atlas (TCGA) database [which included 529 ccRCC patients who were randomized in a training cohort (n=265) and an internal validation cohort (n=264)] and 40 pyroptosis-related genes (PRGs), from which four genes (CASP9, GSDME, IL1B and TIRAP) were selected to construct a molecular prediction model of PRGs for ccRCC. In addition, a cohort of 114 ccRCC patients from Shanghai Eastern Hepatobiliary Surgery Hospital (EHSH) was used as external data to verify the effectiveness of the model by immunohistochemistry. Moreover, the biological functions of the four PRGs were also verified in ccRCC 786-O and 769-P cells by Western blot (WB), CCK-8 cell proliferation, and Transwell invasion assays. Results: The model was able to differentiate high-risk patients from low-risk patients, and this differentiation was consistent with their clinical survival outcomes. In addition, the four PRGs also affected the ability of cell proliferation and invasion in ccRCC. Conclusion: The prediction model of pyroptosis-related molecular markers developed in this study may prove to be a novel understanding for ccRCC.

Circadian rhythm-associated lncRNA RP11-414H17.5 as a key therapeutic target in osteosarcoma affects the tumor immune microenvironment and enhances malignancy

BACKGROUND

It has previously been proven that circadian rhythm disruption is associated with the incidence and deterioration of several tumors, which potentially leads to increased tumor susceptibility and a worse prognosis for tumor-bearing patients. However, their potential role in osteosarcoma has yet to be sufficiently investigated.

METHODS

Transcriptomic and clinical data of 84 osteosarcoma samples and 70 normal bone tissue samples were obtained from the TARGET and GTEx databases, circadian rhythm-related genes were obtained from Genecards, and circadian rhythm-related lncRNAs (CRLs) were obtained by Pearson correlation analysis, differential expression analysis, and protein-protein interaction (PPI) analysis. COX regression and LASSO regression were performed on the CRLs in order to construct a circadian rhythm-related prognostic prediction signature (CRPS). CRPS reliability was verified by Kaplan-Meier (KM), principal component analysis (PCA), nomogram, and receiver operating characteristic (ROC) curve. CRPS effects on the immune microenvironment of osteosarcoma were explored by enrichment analysis and immune infiltration analysis, and the effect of critical gene RP11-414H17.5 on osteosarcoma was experimentally verified.

RESULT

CRPS consisting of three CRLs was constructed and its area under the curve (AUC) values predicted that osteosarcoma prognosis reached 0.892 in the training group and 0.843 in the test group, with a p value of < 0.05 for the KM curve and stable performance across different clinical subgroups. PCA analysis found that CRPS could significantly distinguish between different risk subgroups, and exhibited excellent performance in the prediction of the immune microenvironment. The experiment verified that RP11-414H17.5 can promote metastasis and inhibit apoptosis of osteosarcoma cells.

CONCLUSION

The study revealed that circadian rhythm plays a crucial role in osteosarcoma progression and identified the impact of the key gene RP11-414H17.5 on osteosarcoma, which provides novel insights into osteosarcoma diagnosis and therapy.

The implication of pyroptosis in cancer immunology: Current advances and prospects

Pyroptosis is a regulated cell death pathway involved in numerous human diseases, especially malignant tumors. Recent studies have identified multiple pyroptosis-associated signaling molecules, like caspases, gasdermin family and inflammasomes. In addition, increasing in vitro and in vivo studies have shown the significant linkage between pyroptosis and immune regulation of cancers. Pyroptosis-associated biomarkers regulate the infiltration of tumor immune cells, such as CD4+ and CD8+ T cells, thus strengthening the sensitivity to therapeutic strategies. In this review, we explained the relationship between pyroptosis and cancer immunology and focused on the significance of pyroptosis in immune regulation. We also proposed the future application of pyroptosis-associated biomarkers in basic research and clinical practices to address malignant behaviors. Exploration of the underlying mechanisms and biological functions of pyroptosis is critical for immune response and cancer immunotherapy.

SFyNCS detects oncogenic fusions involving non-coding sequences in cancer

Fusion genes are well-known cancer drivers. However, most known oncogenic fusions are protein-coding, and very few involve non-coding sequences due to lack of suitable detection tools. We develop SFyNCS to detect fusions of both protein-coding genes and non-coding sequences from transcriptomic sequencing data. The main advantage of this study is that we use somatic structural variations detected from genomic data to validate fusions detected from transcriptomic data. This allows us to comprehensively evaluate various fusion detection and filtering strategies and parameters. We show that SFyNCS has superior sensitivity and specificity over existing algorithms through extensive benchmarking in cancer cell lines and patient samples. We then apply SFyNCS to 9565 tumor samples across 33 tumor types in The Cancer Genome Atlas cohort and detect a total of 165,139 fusions. Among them, 72% of the fusions involve non-coding sequences. We find a long non-coding RNA to recurrently fuse with various oncogenes in 3% of prostate cancers. In addition, we discover fusions involving two non-coding RNAs in 32% of dedifferentiated liposarcomas and experimentally validated the oncogenic functions in mouse model.

A novel pyroptosis-associated lncRNA LINC01133 promotes pancreatic adenocarcinoma development via miR-30b-5p/SIRT1 axis

PURPOSE

Pancreatic adenocarcinoma (PAAD) remains a highly aggressive gastrointestinal malignancy with a dismal prognosis. Pyroptosis has a key role in tumor development. Long noncoding RNAs (lncRNAs) are involved in tumorigenesis and pyroptosis regulation. However, the prognostic potential and function of pyroptosis-related lncRNAs (PRLs) in PAAD remain unclear. We aimed to identify PRLs with promising predictive value for PAAD prognosis and investigate the mechanism by which PRLs affect pyroptosis and PAAD development.

METHODS

Key genes that regulate pyroptosis were determined from previous studies, and PRLs were identified from lncRNAs shown to be co-expressed in The Cancer Genome Atlas. Cox analysis and the least absolute shrinkage and selection operator (LASSO) regression model was used to establish a prognostic PRL signature. The clinical significance and functional mechanisms of LINC01133 were explored in vitro and in vivo.

RESULTS

A seven-lncRNA signature was established and the high-risk subgroup exhibited a shorter survival time. With lower immune infiltration abundance, poor immune function, and higher tumor mutational burden (TMB), the high-risk subgroup reflected a more immunosuppressive status with a greater scope for benefiting from immunotherapy. After LINC01133 knockdown, PAAD cells showed lower viability and higher pyroptosis-related gene expression. LINC01133 functioned as a competing endogenous RNA to sequester miR-30b-5p from sponging SIRT1 mRNA to inhibit PAAD pyroptosis.

CONCLUSION

With significant prognostic value, our PRL signature are involved in the biological processes of PAAD cells and associated with the immune environment. LINC01133 suppresses pyroptosis to promote PAAD development and could serve as a potential target for PAAD treatment.

Functional and regulatory impact of chimeric RNAs in human normal and cancer cells

Fusions of two genes can lead to the generation of chimeric RNAs, which may have a distinct functional role from their original molecules. Chimeric RNAs could encode novel functional proteins or serve as novel long noncoding RNAs (lncRNAs). The appearance of chimeric RNAs in a cell could help to generate new functionality and phenotypic diversity that might facilitate this cell to survive against new environmental stress. Several recent studies have demonstrated the functional roles of various chimeric RNAs in cancer progression and are considered as biomarkers for cancer diagnosis and sometimes even drug targets. Further, the growing evidence demonstrated the potential functional association of chimeric RNAs with cancer heterogeneity and drug resistance cancer evolution. Recent studies highlighted that chimeric RNAs also have functional potentiality in normal physiological processes. Several functionally potential chimeric RNAs were discovered in human cancer and normal cells in the last two decades. This could indicate that chimeric RNAs are the hidden layer of the human transcriptome that should be explored from the functional insights to better understand the functional evolution of the genome and disease development that could facilitate clinical practice improvements. This review summarizes the current knowledge of chimeric RNAs and highlights their functional, regulatory, and evolutionary impact on different cancers and normal physiological processes. Further, we will discuss the potential functional roles of a recently discovered novel class of chimeric RNAs named sense-antisense/cross-strand chimeric RNAs generated by the fusion of the bi-directional transcripts of the same gene. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs.

SFyNCS detects oncogenic fusions involving non-coding sequences in cancer

Fusion genes are well-known cancer drivers. However, very few known oncogenic fusions involve non-coding sequences. We develop SFyNCS with superior performance to detect fusions of both protein-coding genes and non-coding sequences from transcriptomic sequencing data. We validate fusions using somatic structural variations detected from the genomes. This allows us to comprehensively evaluate various fusion detection and filtering strategies and parameters. We detect 165,139 fusions in 9,565 tumor samples across 33 tumor types in the Cancer Genome Atlas cohort. Among them, 72% of the fusions involve non-coding sequences and many are recurrent. We discover two long non-coding RNAs recurrently fused with various partner genes in 32% of dedifferentiated liposarcomas and experimentally validated the oncogenic functions in mouse model.

A model based on immune-related lncRNA pairs and its potential prognostic value in immunotherapy for melanoma

A model based on long non-coding RNA (lncRNA) pairs independent of expression quantification was constructed to evaluate prognosis melanoma and response to immunotherapy in melanoma. RNA sequencing data and clinical information were retrieved and downloaded from The Cancer Genome Atlas and the Genotype-Tissue Expression databases. We identified differentially expressed immune-related lncRNAs (DEirlncRNAs), matched them, and used least absolute shrinkage and selection operator and Cox regression to construct predictive models. The optimal cutoff value of the model was determined using a receiver operating characteristic curve and used to categorize melanoma cases into high-risk and low-risk groups. The predictive efficacy of the model with respect to prognosis was compared with that of clinical data and ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data). Then, we analyzed the correlations of risk score with clinical characteristics, immune cell invasion, anti-tumor, and tumor-promoting activities. Differences in survival, degree of immune cell infiltration, and intensity of anti-tumor and tumor-promoting activities were also evaluated in the high- and low-risk groups. A model based on 21 DEirlncRNA pairs was established. Compared with ESTIMATE score and clinical data, this model could better predict outcomes of melanoma patients. Follow-up analysis of the model's effectiveness showed that patients in the high-risk group had poorer prognosis and were less likely to benefit from immunotherapy compared with those in the low-risk group. Moreover, there were differences in tumor-infiltrating immune cells between the high-risk and low-risk groups. By pairing the DEirlncRNA, we constructed a model to evaluate the prognosis of cutaneous melanoma independent of a specific level of lncRNA expression.

The Landscape of Expressed Chimeric Transcripts in the Blood of Severe COVID-19 Infected Patients

The ongoing COVID-19 pandemic caused by SARS-CoV-2 infections has quickly developed into a global public health threat. COVID-19 patients show distinct clinical features, and in some cases, during the severe stage of the condition, the disease severity leads to an acute respiratory disorder. In spite of several pieces of research in this area, the molecular mechanisms behind the development of disease severity are still not clearly understood. Recent studies demonstrated that SARS-CoV-2 alters the host cell splicing and transcriptional response to overcome the host immune response that provides the virus with favorable conditions to replicate efficiently within the host cells. In several disease conditions, aberrant splicing could lead to the development of novel chimeric transcripts that could promote the functional alternations of the cell. As severe SARS-CoV-2 infection was reported to cause abnormal splicing in the infected cells, we could expect the generation and expression of novel chimeric transcripts. However, no study so far has attempted to check whether novel chimeric transcripts are expressed in severe SARS-CoV-2 infections. In this study, we analyzed several publicly available blood transcriptome datasets of severe COVID-19, mild COVID-19, other severe respiratory viral infected patients, and healthy individuals. We identified 424 severe COVID-19 -specific chimeric transcripts, 42 of which were recurrent. Further, we detected 189 chimeric transcripts common to severe COVID-19 and multiple severe respiratory viral infections. Pathway and gene enrichment analysis of the parental genes of these two subsets of chimeric transcripts reveals that these are potentially involved in immune-related processes, interferon signaling, and inflammatory responses, which signify their potential association with immune dysfunction leading to the development of disease severity. Our study provides the first detailed expression landscape of chimeric transcripts in severe COVID-19 and other severe respiratory viral infections.

Recent advances in cancer fusion transcript detection

Extensive investigation of gene fusions in cancer has led to the discovery of novel biomarkers and therapeutic targets. To date, most studies have neglected chromosomal rearrangement-independent fusion transcripts and complex fusion structures such as double or triple-hop fusions, and fusion-circRNAs. In this review, we untangle fusion-related terminology and propose a classification system involving both gene and transcript fusions. We highlight the importance of RNA-level fusions and how long-read sequencing approaches can improve detection and characterization. Moreover, we discuss novel bioinformatic tools to identify fusions in long-read sequencing data and strategies to experimentally validate and functionally characterize fusion transcripts.

Chimeric RNA RRM2-C2orf48 plays an oncogenic role in the development of NNK-induced lung cancer

Chimeric RNAs have been used as biomarkers and therapeutic targets for multiple types of cancers. However, less attention has been paid to their mechanism of action in neoplasia. Here, we reported that high-expressed chimeric RNA RRM2-C2orf48 was found in malignantly transformed BEAS-2B cells induced by 4-(methyl nitrosamine)-1-(3-pyridinyl)-1-butanone (NNK) in 74 lung cancer patients and several lung cancer cell lines. The expression level of RRM2-C2orf48 was significantly correlated with lymph node metastasis, distant metastasis, tumor-lymph node-metastasis (TNM) stage, and smoking. Overexpressing RRM2-C2orf48 promoted cell growth and accelerated the process of NNK-induced lung cancer. RRM2-C2orf48 knockdown inhibited the growth of RRM2-C2orf48-overexpressing BEAS-2B cells. Finally, we identified miR-219a-2-3p as a potential target of RRM2-C2orf48 in lung cancer. In summary, chimeric RNA RRM2-C2orf48 accelerated the process of NNK-induced lung cancer, and miR-219a-2-3p may be involved in this process.

mRNA Capture Sequencing and RT-qPCR for the Detection of Pathognomonic, Novel, and Secondary Fusion Transcripts in FFPE Tissue: A Sarcoma Showcase

We assess the performance of mRNA capture sequencing to identify fusion transcripts in FFPE tissue of different sarcoma types, followed by RT-qPCR confirmation. To validate our workflow, six positive control tumors with a specific chromosomal rearrangement were analyzed using the TruSight RNA Pan-Cancer Panel. Fusion transcript calling by FusionCatcher confirmed these aberrations and enabled the identification of both fusion gene partners and breakpoints. Next, whole-transcriptome TruSeq RNA Exome sequencing was applied to 17 fusion gene-negative alveolar rhabdomyosarcoma (ARMS) or undifferentiated round cell sarcoma (URCS) tumors, for whom fluorescence in situ hybridization (FISH) did not identify the classical pathognomonic rearrangements. For six patients, a pathognomonic fusion transcript was readily detected, i.e., PAX3-FOXO1 in two ARMS patients, and EWSR1-FLI1, EWSR1-ERG, or EWSR1-NFATC2 in four URCS patients. For the 11 remaining patients, 11 newly identified fusion transcripts were confirmed by RT-qPCR, including COPS3-TOM1L2, NCOA1-DTNB, WWTR1-LINC01986, PLAA-MOB3B, AP1B1-CHEK2, and BRD4-LEUTX fusion transcripts in ARMS patients. Additionally, recurrently detected secondary fusion transcripts in patients diagnosed with EWSR1-NFATC2-positive sarcoma were confirmed (COPS4-TBC1D9, PICALM-SYTL2, SMG6-VPS53, and UBE2F-ALS2). In conclusion, this study shows that mRNA capture sequencing enhances the detection rate of pathognomonic fusions and enables the identification of novel and secondary fusion transcripts in sarcomas.

Identification of Prognostic Factors in Cholangiocarcinoma Based on Integrated ceRNA Network Analysis

This study is aimed at screening prognostic biomarkers in cholangiocarcinoma (CHOL) based on competitive endogenous RNA (ceRNA) regulatory network analysis. Microarray data for lncRNAs, mRNA, and miRNAs were downloaded from the GEO and TCGA databases. Differentially expressed RNAs (DERs) were identified in CHOL and normal liver tissue samples. WGCNA was used to identify disease-related gene modules. By integrating the information from the starBase and DIANA-LncBasev2 databases, we constructed a ceRNA network. Survival analysis was performed, and a prognostic gene-based prognostic score (PS) model was generated. The correlation between gene expression and immune cell infiltration or immune-related feature genes was analyzed using TIMER. Finally, real-time quantitative PCR (RT-qPCR) was used to verify the expression of the 10 DERs with independent prognosis. A large cohort of DERs was identified in the CHOL and control samples. The ceRNA network consisted of 6 lncRNAs, 2 miRNAs, 90 mRNAs, and 98 nodes. Ten genes were identified as prognosis-related genes, and a ten-gene signature PS model was constructed, which exhibited a good prognosis predictive ability for risk assessment of CHOL patients (AUC value = 0.975). Four genes, ELF4, AGXT, ABCG2, and LDHD, were associated with immune cell infiltration and closely correlated with immune-related feature genes (CD14, CD163, CD33, etc.) in CHOL. Additionally, the consistency rate of the RT-qPCR results and bioinformatics analysis was 80%, implying a relatively high reliability of the bioinformatic analysis results. Our findings suggest that the ten-signature gene PS model has significant prognostic predictive value for patients with CHOL. These four immune-related DERs are involved in the progression of CHOL and may be useful prognostic biomarkers for CHOLs.

LncRNA ABHD11-AS1 promotes tumor progression in papillary thyroid carcinoma by regulating EPS15L1/EGFR signaling pathway

OBJECTIVES

lncRNA ABHD11 antisense RNA 1 (ABHD11-AS1) acts as an oncogene involved in papillary thyroid carcinoma (PTC) occurrence and progression. ABHD11-AS1 exerts biologic functions by some miRNAs and proteins to regulate multiple targets. Identification of novel mechanism of ABHD11-AS1 could be helpful in therapeutic targeting for PTC treatment.

METHODS

Differentially expressed lncRNAs were selected from TCGA database. qRT-PCR analysis was applied to examine the expression of ABHD11-AS1 in PTC cell lines and tissues. The relationship of ABHD11-AS1 expression and clinicopathological features was analyzed by Kaplan-Meier analysis. Two PTC cell lines (TPC-1 and KTC-1) were transfected with pcDNA 3.1, pcDNA3.1-ABHD11-AS1, si-NC and si-ABHD11-AS1, respectively, to verify the ABHD11-AS1 oncogene-regulating capacity to promote tumor progression. The cell metastasis and proliferation had been evaluated both in vitro and in vivo.

RESULTS

High expression of ABHD11-AS1 was found in PTC tissues (P < 0.01), which was significantly correlated with lymph node metastasis (P < 0.05). ABHD11-AS1 overexpression noticeably promoted cell proliferation, migration, and invasion capabilities, which were obviously decreased upon ABHD11-AS1 knockdown. ABHD11-AS1 positively regulated EGFR/EPS15L1 pathway, as EGFR, EPS15L1, STAT3, and p-STAT3 were activated.

CONCLUSION

ABHD11-AS1 promotes tumor progression in PTC by regulating EPS15L1/EGFR pathway.

A Two-eRNA-Based Signature Can Impact the Immune Status and Predict the Prognosis and Drug Sensitivity of Lung Adenocarcinoma

Enhancer RNAs (eRNAs) are intergenic long noncoding RNAs (lncRNAs) participating in the development of malignant cancers via targeting cancer-associated genes and immune checkpoints. Immune infiltration of the tumor microenvironment was positively associated with overall survival (OS) in lung adenocarcinoma (LUAD). In this study, we aimed to explore the clinical significance of PCBP1-AS1 in LUAD and developed a novel prognostic signature based on two eRNAs. Our team discovered that the expression of PCBP1-AS1 was distinctly downregulated in LUAD specimens compared with nontumor specimens. Lower PCBP1-AS1 expression was related to advanced clinical stages and poor prognosis. KEGG analysis unveiled that the coexpression genes of PCBP1-AS1 were involved in the regulation of several tumor-related pathways. In addition, remarkable associations were observed between the expression of PCBP1-AS1 and the levels of several immune cells. Then, we used PCBP1-AS1 and TBX5-AS1 to develop a prognostic model. Survival assays unveiled that patients with higher risk scores exhibited a shorter OS in contrast to patients with lower risk scores. In addition, multivariable Cox regressive analysis indicated that the risk score was an independent prediction factor in LUAD sufferers. The anticancer drug sensitivity analysis indicated that risk score had a positive relationship with several anticancer drugs. Taken together, our findings indicated PCBP1-AS1 as a function modulator in LUAD development. In addition, we constructed a robust immune-related eRNA signature which might be a clinical prognosis factor for LUAD patients.

NLRP6-Dependent Pyroptosis-Related lncRNAs Predict the Prognosis of Hepatocellular Carcinoma

Pyroptosis, a novel pro-inflammatory type of programmed cell death, is involved in the tumorigenesis of various cancers. Recent findings have implicated long non-coding RNAs (lncRNAs) in the serial steps of cancer development. However, the expression and prognostic signatures of pyroptosis-related lncRNAs in hepatocellular carcinoma (HCC) remain largely unknown. Therefore, a pyroptosis-related lncRNA prognostic model was constructed for HCC. Thirty-four pyroptosis-related genes were obtained from previous reviews, and gene expression data were collected from The Cancer Genome Atlas (TCGA) database. Spearman's correlation test was used to identify potential pyroptosis-related lncRNAs. Cox and LASSO regression analyses were used to construct a prognostic model. Subsequently, receiver operating characteristic (ROC) curves were constructed to assess the model's predictive ability for the overall survival (OS) of HCC patients. CytoHubba was used to screen out the potential hub gene, whose expression was verified using clinical samples from HCC patients. Finally, nine pyroptosis-related differentially expressed lncRNAs in HCC were identified, and a prognostic model with four pyroptosis-related lncRNAs was constructed with an area under the ROC curve (AUC) of approximately 0.734. Single-sample gene set enrichment analysis and TCGA revealed different immune infiltration and immune checkpoints between the two risk groups. Moreover, these lncRNAs are closely related to the pyroptosis-related gene, NLRP6, which may be considered a hub gene. NLRP6 was lower-expressed in HCC samples, and patients with lower expression of NLRP6 had the longer OS. In conclusion, NLRP6-dependent pyroptosis-related lncRNAs play important roles in tumor immunity and may be potential predictors and therapeutic targets for HCC.

LncRNA FOXP4-AS1 Promotes Progression of Ewing Sarcoma and Is Associated With Immune Infiltrates

Ewing sarcoma (ES) is a highly malignant primary bone tumor with poor prognosis. Studies have shown that abnormal expression of lncRNA influences the prognosis of tumor patients. Herein, we established that FOXP4-AS1 was up-regulated in ES and this correlated with poor prognosis. Further analysis illustrated that FOXP4-AS1 down-regulation repression growth, migration, along with invasion of ES. On the contrary, up-regulation of FOXP4-AS1 promoted the growth, migration, as well as invasion of ES. To explore the mechanism of FOXP4-AS1, Spearman correlation analysis was carried out to determine genes that were remarkably linked to FOXP4-AS1 expression. The potential functions and pathways involving FOXP4-AS1 were identified by GO analysis, Hallmark gene set enrichment analysis, GSEA, and GSVA. The subcellular fractionation results illustrated that FOXP4-AS1 was primarily located in the cytoplasm of ES cells. Then a ceRNA network of FOXP4-AS1 was constructed. Analysis of the ceRNA network and GSEA yielded two candidate mRNAs for FOXP4-AS1. Results of the combined survival analysis led us to speculate that FOXP4-AS1 may affect the expression of TMPO by sponging miR-298, thereby regulating the malignant phenotype of ES. Finally, we found that FOXP4-AS1 may modulates the tumor immune microenvironment in an extracellular vesicle-mediated manner. In summary, FOXP4-AS1 correlates with poor prognosis of ES. It promotes the growth, migration, as well as invasion of ES cells and may modulate the tumor immune microenvironment.

Emerging Role of LncRNAs in Ischemic Stroke-Novel Insights into the Regulation of Inflammation

As a crucial kind of pervasive gene, long noncoding RNAs (lncRNAs) are abundant and key players in brain function as well as numerous neurological disorders, especially ischemic stroke. The mechanisms underlying ischemic stroke include angiogenesis, autophagy, apoptosis, cell death, and neuroinflammation. Inflammation plays a vital role in the pathological process of ischemic stroke, and systemic inflammation affects the patient’s prognosis. Although a great deal of research has illustrated that various lncRNAs are closely relevant to regulate neuroinflammation and microglial activation in ischemic stroke, the specific interactional relationships and mechanisms between lncRNAs and neuroinflammation have not been described clearly. This review aimed to summarize the therapeutic effects and action mechanisms of lncRNAs on ischemia by regulating inflammation and microglial activation. In addition, we emphasize that lncRNAs have the potential to modulate inflammation by inhibiting and activating various signaling pathways, such as microRNAs, NF‐κB and ERK.

A prescient evolutionary model for genesis, duplication and differentiation of MIR160 homologs in Brassicaceae

MicroRNA160 is a class of nitrogen-starvation responsive genes which governs establishment of root system architecture by down-regulating AUXIN RESPONSE FACTOR genes (ARF10, ARF16 and ARF17) in plants. The high copy number of MIR160 variants discovered by us from land plants, especially polyploid crop Brassicas, posed questions regarding genesis, duplication, evolution and function. Absence of studies on impact of whole genome and segmental duplication on retention and evolution of MIR160 homologs in descendent plant lineages prompted us to undertake the current study. Herein, we describe ancestry and fate of MIR160 homologs in Brassicaceae in context of polyploidy driven genome re-organization, copy number and differentiation. Paralogy amongst Brassicaceae MIR160a, MIR160b and MIR160c was inferred using phylogenetic analysis of 468 MIR160 homologs from land plants. The evolutionarily distinct MIR160a was found to represent ancestral form and progenitor of MIR160b and MIR160c. Chronology of evolutionary events resulting in origin and diversification of genomic loci containing MIR160 homologs was delineated using derivatives of comparative synteny. A prescient model for causality of segmental duplications in establishment of paralogy in Brassicaceae MIR160, with whole genome duplication accentuating the copy number increase, is being posited in which post-segmental duplication events viz. differential gene fractionation, gene duplications and inversions are shown to drive divergence of chromosome segments. While mutations caused the diversification of MIR160a, MIR160b and MIR160c, duplicated segments containing these diversified genes suffered gene rearrangements via gene loss, duplications and inversions. Yet the topology of phylogenetic and phenetic trees were found congruent suggesting similar evolutionary trajectory. Over 80% of Brassicaceae genomes and subgenomes showed a preferential retention of single copy each of MIR160a, MIR160b and MIR160c suggesting functional relevance. Thus, our study provides a blue-print for reconstructing ancestry and phylogeny of MIRNA gene families at genomics level and analyzing the impact of polyploidy on organismal complexity. Such studies are critical for understanding the molecular basis of agronomic traits and deploying appropriate candidates for crop improvement.