Aberrant methylation-mediated downregulation of long noncoding RNA C5orf66-AS1 promotes the development of gastric cardia adenocarcinoma

Transcriptome and methylome sequencing reveals altered long non-coding RNA genes expression and their aberrant DNA methylation in equine sarcoids

Recent publications confirmed that long non-coding RNAs (lncRNAs) perform an essential function in gene-specific transcription regulation. Nevertheless, despite its important role, lncRNA has not yet been described in equine sarcoids, the skin neoplasia of horses. Therefore, the aim of this study is to deepen the knowledge about lncRNA expression in the pathogenesis of equine sarcoids and provide new insight into the regulatory function of lncRNA in the bovine papillomavirus-dependent neoplasia of horse dermal tissues. RNA sequencing (RNA-seq) data from 12 equine sarcoid samples and the corresponding controls were reanalyzed in this study. A total of 3396 differentially expressed (DE) lncRNAs and 128 DElncRNA-DE genes (DEGs) pairs were identified. Differentially expressed lncRNAs predicted target genes were enriched in pathways associated with inter alia the extracellular matrix disassembly and cancer pathways. Furthermore, methylation data from the same samples were integrated into the analysis, and 12 DElncRNAs were described as potentially disturbed by aberrant methylation. In conclusion, this study presents novel data about lncRNA's role in the pathogenesis of equine sarcoids.

Abnormally Expressed lncRNAs as Potential Biomarkers for Gastric Cancer Risk: A Diagnostic Meta-Bioinformatics Analysis

Background and Aims

Abnormal expression of lncRNAs is relevant to the occurrence and development of gastric cancer (GC), but the significance remains inconclusive. We performed a diagnostic meta-bioinformatics analysis to elucidate the association between lncRNA expression and GC risk.

Methods

Published datasets were selected from PubMed, Embase, CNKI, and Web of Science, up to 1st December 2021. The pooled sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the curve (AUC) were calculated to evaluate the diagnostic value. RNA sequencing data were downloaded for validation.

Results

54 studies with 4671 patients and 4652 matched controls were included in the meta-analysis. The pooled SEN, SPE, PLR, NLR, DOR, and AUC were 0.71, 0.76, 2.9, 0.39, 8, and 0.79, respectively. Subgroup analyses showed that the DOR and AUC of intergenic lncRNAs, circulating lncRNAs, larger sample size (>200), and high-quality (NOS score ≥ 7) groups were superior to antisense lncRNAs, tissue lncRNAs, smaller sample size (≤200), and low-quality (NOS score < 7) groups, respectively. However, only circulating lncRNAs had significantly higher diagnostic utility than that tissue lncRNAs. Nine differentially expressed lncRNAs in the meta-analysis were verified in TCGA-STAD. PVT1 was the most effective single lncRNA, with AUC of 0.949, SEN of 0.808, and SPE of 0.969, while PVT1 and C5orf66-AS1 were the most effective combination, with AUC of 0.972, SEN of 0.941, and SPE of 0.937.

Conclusion

Abnormally expressed lncRNAs, especially circulating lncRNAs, might be potential diagnostic biomarkers for GC risk. A novel combined model of lncRNAs might achieve better GC diagnosis performance.

Regulatory function of DNA methylation mediated lncRNAs in gastric cancer

As one of the most common malignancies worldwide, gastric cancer contributes to cancer death with a high mortality rate partly responsible for its out-of-control progression as well as limited diagnosis. DNA methylation, one of the epigenetic events, plays an essential role in the carcinogenesis of many cancers, including gastric cancer. Long non-coding RNAs have emerged as the significant factors in the cancer progression functioned as the oncogene genes, the suppressor genes and regulators of signaling pathways over the decade. Intriguingly, increasing reports, recently, have claimed that abnormal DNA methylation regulates the expression of lncRNAs as tumor suppressor genes in gastric cancer and lncRNAs as regulators could exert the critical influence on tumor progression through acting on DNA methylation of other cancer-related genes. In this review, we summarized the DNA methylation-associated lncRNAs in gastric cancer which play a large impact on tumor progression, such as proliferation, invasion, metastasis and so on. Furthermore, the underlying molecular mechanism and signaling pathway might be developed as key points of gastric cancer range from diagnosis to prognosis and treatment in the future.

Identification of novel key regulatory lncRNAs in gastric adenocarcinoma

Background

Stomach adenocarcinoma (STAD) is one of the most common and deadly cancers worldwide. Recent evidence has demonstrated that dysregulation of long noncoding RNAs (lncRNA) is associated with different hallmarks of cancer. lncRNAs also were suggested as novel promising biomarkers for cancer diagnosis and prognosis. Despite these previous investigations, the expression pattern, diagnostic role, and hallmark association of lncRNAs in STAD remain unclear.

Results

In this study, The STAD lncRNA-mRNA network was constructed based on RNAs that differentially expressed among tumor and normal samples and had a strong expression correlation with others. The high degree nodes of the network were associated with overall survival. In addition, we found that the hubs’ regulatory roles have previously been confirmed in different types of cancers by literature. For example, the HCG22 hub inhibited cell proliferation and invasion and induced apoptosis in oral squamous cell carcinoma (OSCC) cells. The levels of PCNA, Vimentin, and Bcl2 were decreased and E-cadherin and Bax expression was elevated in OSCC cells after HCG22 overexpression. Additionally, HCG22 overexpression inhibited the Akt, mTOR, and Wnt/β-catenin pathways.

Then lncRNAs were mapped to their related GO terms and cancer hallmarks. Based on these mappings, we predict the hallmarks that might be associated with each lncRNA. Finally, the literature review confirmed our prediction.

Among the 20 lncRNAs of the STAD network, 11 lncRNAs (LINC02560, SOX21-AS1, C5orf66-AS1, HCG22, PGM5-AS1, NALT1, ENSG00000241224.2, TINCR, MIR205HG, HNF4A-AS1, ENSG00000262756) demonstrated expression correlation with overall survival (OS). Based on expression analysis, survival analysis, hallmark associations, and literature review, LINC02560, SOX21-AS1, C5orf66-AS1, HCG22, PGM5-AS1, NALT1, ENSG00000241224.2, TINCR, MIR205HG, HNF4A-AS1 plays a regulatory role in STAD. For example, our prediction of association between C5orf66-AS1 expression dysregulation and “sustaining proliferative signal” and “Activating invasion and metastasis” has been confirmed in STAD, OSCC and cervical cancer. Finally, we developed a lncRNA signature with SOX21-AS1 and LINC02560, which classified patients into high and low-risk subgroups with significantly different survival outcomes. The mortality rate of the high-risk patients was significantly higher compared to the low-risk patients (28/1% vs 60.13).

Conclusion

These findings help in designing more precise and detailed experimental studies to find STAD biomarkers and therapeutic targets.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08578-6.

Multi-Omics Investigations Revealed Underlying Molecular Mechanisms Associated With Tumor Stiffness and Identified Sunitinib as a Potential Therapy for Reducing Stiffness in Pituitary Adenomas

Purpose: Pituitary adenomas (PAs) are the second most common intracranial neoplasms. Total surgical resection was extremely important for curing PAs, whereas tumor stiffness has gradually become the most critical factor affecting the resection rate in PAs. We aimed to investigate the molecular mechanisms of tumor stiffening and explore novel medications to reduce stiffness for improving surgical remission rates in PA patients.

Methods: RNA sequencing, whole-genome bisulfite sequencing, and whole exome sequencing were applied to identify transcriptomic, epigenomic, and genomic underpinnings among 11 soft and 11 stiff PA samples surgically resected from patients at Peking Union Medical College Hospital (PUMCH). GH3 cell line and xenograft PA model was used to demonstrate therapeutic effect of sunitinib, and atomic force microscopy (AFM) was used to detect the stiffness of tumors.

Results: Tumor microenvironment analyses and immunofluorescence staining indicated endothelial cells (ECs) and cancer-associated fibroblasts (CAFs) were more abundant in stiff PAs. Weighted gene coexpression network analysis identified the most critical stiffness-related gene (SRG) module, which was highly correlated with stiff phenotype, ECs and CAFs. Functional annotations suggested SRGs might regulate PA stiffness by regulating the development, differentiation, and apoptosis of ECs and CAFs and related molecular pathways. Aberrant DNA methylation and m6A RNA modifications were investigated to play crucial roles in regulating PA stiffness. Somatic mutation analysis revealed increased intratumoral heterogeneity and decreased response to immunotherapy in stiff tumors. Connectivity Map analysis of SRGs and pRRophetic algorithm based on drug sensitivity data of cancer cell lines finally determine sunitinib as a promising agent targeting stiff tumors. Sunitinib inhibited PA growth in vitro and in vivo, and also reduced tumor stiffness in xenograft PA models detected by AFM.

Conclusion: This is the first study investigating the underlying mechanisms contributing to the stiffening of PAs, and providing novel insights into medication therapy for stiff PAs.

Site-Specific Hypermethylation of SST 1stExon as a Biomarker for Predicting the Risk of Gastrointestinal Tract Cancers

Background

DNA methylation is an important epigenetic modification in tumorigenesis, and similar epigenetic regulation mechanisms have been found in the gastrointestinal tract (GIT) cancers. Somatostatin (SST) has been confirmed to be expressed throughout the GIT. This study aimed to simultaneously explore the relationships between the SST methylation and the risks of three GIT cancers (esophageal cancer (EC), gastric cancer (GC), and colorectal cancer (CRC)) and to evaluate its diagnostic value.

Methods

Differentially methylated regions (DMRs) of the SST gene, including TSS200, 1stExon, and the gene body, were identified in GIT cancers by The Cancer Genome Atlas (TCGA) database analysis. Further analyses were conducted in tissue samples of EC (n = 50), GC (n = 99), and CRC (n = 80). The SST methylation was detected by bisulfite-sequencing PCR (BSP), and the SST expression was detected by quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR).

Results

In GIT cancers, DMR-related CpG islands were mainly located in the 1stExon. The methylation status of the SST 1stExon in the tumor tissues was significantly higher than that in the adjacent noncancerous tissues, and the methylation rates of the specific CpG sites were correlated with clinical phenotypes. The average methylation rate (AMR) of the SST 1stExon was negatively correlated with the SST gene expression in GC and CRC (both P < 0.001). For the diagnosis of GIT cancers, the combined detection of methylation at CpG sites +18 and +129 showed the highest area under the curve (AUC 0.698), with a sensitivity of 59.3% and a specificity of 72.8%.

Conclusions

The site-specific hypermethylation of the SST 1stExon increases the risk of GIT cancers and might be a potential predictive marker for pan-GIT cancers.

One stomach, two subtypes of carcinoma—the differences between distal and proximal gastric cancer

Gastric cancer (GC) is one of the most common malignant tumors of the digestive tract, posing a significant risk to human health. Over the past 10 years, the pathological characteristics and the prognosis of GC have been determined based on the locations of the tumors that were then classified into two types—proximal and distal GC. This review focuses on the differences in epidemiology, etiology, cell source, pathological characteristics, gene expression, molecular markers, manifestations, treatment, prognosis, and prevention between proximal and distal GC to provide guidance and a basis for clinical diagnosis and treatment.

Long Non-coding RNA LINC01503 Promotes Gastric Cardia Adenocarcinoma Progression via miR-133a-5p/VIM Axis and EMT Process

BACKGROUND

LINC01503 has been reported to act as a candidate oncogenic lncRNA in several types of human cancer. However, the functions and underlying mechanisms of LINC01503 in gastric cardia adenocarcinoma (GCA) remain unclear.

AIMS

To investigate the roles and underlying mechanisms of LINC01503 in GCA progression.

MATERIALS AND METHODS

Gene expressions were detected by quantitative real-time PCR (qRT-PCR). Gain-of-function assays were performed to evaluate the function of LINC01503 in gastric cancer cells. Bioinformatics analysis, luciferase reporter assay, and RIP assay were performed to identify associations among LINC01503, miR-133a-5p, and VIM.

RESULTS

The expression level of LINC01503 was significantly elevated in GCA tissues and cell lines. High expression of LINC01503 was correlated with lymph node metastasis, TNM stage, and poor prognosis of GCA patients. Knockdown of LINC01503 significantly reduced proliferation, migration, and invasion ability in GC cells. LINC01503 might function as a competing endogenous RNA (ceRNA) via sponging miR-133a-5p to upregulate the expression of VIM. Furthermore, overexpression of LINC01503 promoted the progression of epithelial mesenchymal transition (EMT) in vitro.

CONCLUSION

LINC01503 serves as an oncogenic lncRNA to promote GCA progression via affecting LINC01503/miR-133a-5p/VIM axis and EMT process. LINC01503 not only has a critical role in GCA progression but also provide a novel potential biomarker in predicting prognosis for GCA patients.

Long Noncoding RNA DICER1-AS1 Functions in Methylation Regulation on the Multi-Drugresistance of Osteosarcoma Cells via miR-34a-5p and GADD45A

Osteosarcoma (OS) is a common malignant bone tumor that commonly occurs in children and adolescents. Long noncoding RNAs (lncRNAs) are recognized as a novel class of regulators of gene expression associated with tumorigenesis. However, the effect and mechanism of lncRNAs in OS tumorigenesis and drug resistance have not been characterized. The purpose of the study is to screen potential biomarker and therapeutic target against OS. We compared the lncRNA expression profiles between OS cell lines with different drug resistance levels using RNA-seq analysis and found that lncRNA DICER1-AS1 was significantly differentially expressed in multi-drugresistant OS cells SJSA-1 versus multi-drugsensitive OS cells G-292. Bisulfite Sequencing PCR (BSP) assay was performed to analyze the differential methylation status of the promoter region of DICER1-AS1 in four OS cells. Subsequently, in vitro gain- and loss-of-function experiments demonstrated the roles of DICER1-AS1 and miR-34a-5p in the multi-drugresistance of OS cells. The main findings is that DICER1-AS1 directly binds to miR-34a-5p, and their expression has a negative correlation with each other. The hypermethylation of the promoter region of DICER1-AS1 silenced its expression in the drugresistant cells SJSA-1 and MNNG/HOS. Moreover, we found that growth arrest and DNA damage-inducible alpha (GADD45A) participates in the DICER1-AS1/miR-34a-5p-regulated drug resistance of OS cells, probably via the cell cycle/pRb-E2F pathway. Our results revealed DICER1-AS1/miR-34a-5p-regulated drug resistance of OS cells, a new lncRNA-regulated network in OS tumorigenesis, suggested that DICER1-AS1 can be considered as a potential biomarker and therapeutic target against OS cells.

A genome-wide screen for differentially methylated long noncoding RNAs identified that lncAC007255.8 is regulated by promoter DNA methylation in Beas-2B cells malignantly transformed by NNK

Tobacco exposure is well known to induce genetic and epigenetic changes that contribute to the pathogenesis of lung cancer. 4-(Methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK) is a significant tobacco-specific carcinogen, but the oncogenic mechanisms of NNK have not been thoroughly elucidated. In this study we found that DNA methyltransferase 1 (DNMT1) was overexpressed in malignantly transformed human bronchial epithelial Beas-2B cells induced by NNK (2B-NNK cells), by treatment with NNK (400 μg/mL) for 7 days. An Arraystar Human noncoding RNA Promoter Microarray was used to detect the DNA methylation status of the promoter region of long noncoding RNAs (lncRNAs). The result showed that 1010 differentially methylated fragments were present in the lncRNA promoter region. QRT-PCR revealed that the expression of lncRNA AC007255.8 was remarkably downregulated in 2B-NNK cells and lung cancer tissues. Furthermore, Methylation-specific PCR showed that the methylation of the lncRNA AC007255.8 promoter was increased in 2B-NNK cells and lung cancer tissues. The reduced expression of lncRNA AC007255.8 was significantly associated with hypermethylation of lncRNA AC007255.8 promoter region. LncRNA AC007255.8 overexpression could result in decreased cell proliferation and increased cell apoptosis in 2B-NNK cells. In conclusion, NNK induced lncRNA AC007255.8 promoter hypermethylation via upregulation of DNMT1 in Beas-2B cells, leading to downregulation of lncRNA AC007255.8, and ultimately the enhancement of cell proliferation and the inhibition of apoptosis. This research affords novel insights into the epigenetic mechanisms of lung cancer, and will stimulate further research into the involvement of aberrant DNA methylation of non-coding regions of the genome in the pathogenesis of lung cancer.

Identification and Construction of a Long Noncoding RNA Prognostic Risk Model for Stomach Adenocarcinoma Patients

Background

Long noncoding RNA-based prognostic biomarkers have demonstrated great potential in the diagnosis and prognosis of cancer patients. However, systematic assessment of a multiple lncRNA-composed prognostic risk model is lacking in stomach adenocarcinoma (STAD). This study is aimed at constructing a lncRNA-based prognostic risk model for STAD patients.

Methods

RNA sequencing data and clinical information of STAD patients were retrieved from The Cancer Genome Atlas (TCGA) database. Differentially expressed lncRNAs (DElncRNAs) were identified using the R software. Univariate and multivariate Cox regression analyses were performed to construct a prognostic risk model. The survival analysis, C-index, and receiver operating characteristic (ROC) curve were employed to assess the sensitivity and specificity of the model. The results were verified using the GEPIA online tool and our clinical samples. Pearson correlation coefficient analysis, Gene Ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed to indicate the potential biological functions of the selected lncRNA.

Results

A total of 1917 DElncRNAs were identified from 343 cases of STAD tissues and 30 cases of noncancerous tissues. According to univariate and multivariable Cox regression analyses, four DElncRNAs (AC129507.1, LINC02407, AL022316.1, and AP000695.2) were selected to establish a prognostic risk model. There was a significant difference in the overall survival between high-risk patients and low-risk patients based on this risk model. The C-index of the model was 0.652. The area under the curve (AUC) for the ROC curve was 0.769. GEPIA results confirmed the expression and prognostic significance of AP000695.2 in STAD. Our clinical data confirmed that upregulated expression of AP000695.2 was correlated with the T stage, distant metastasis, and TNM stage in STAD. GO and KEGG analyses demonstrated that AP000695.2 was closely related to the tumorigenesis process.

Conclusions

In this study, we constructed a lncRNA-based prognostic risk model for STAD patients. Our study will provide novel insight into the diagnosis and prognosis of STAD patients.

A four-methylated LncRNA signature predicts survival of osteosarcoma patients based on machine learning

Risk stratification using prognostic markers facilitates clinical decision-making in treatment of osteosarcoma (OS). In this study, we performed a comprehensive analysis of DNA methylation and transcriptome data from OS patients to establish an optimal methylated lncRNA signature for determining OS patient prognosis. The original OS datasets were downloaded from the the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database. Univariate, Lasso, and machine learning algorithm-iterative Lasso Cox regression analyses were used to establish a methylated lncRNA signature that significantly correlated with OS patient survival. The validity of this signature was verified by the Kaplan-Meier curves, Receiver Operating Characteristic (ROC) curves. We established a four-methylated lncRNA signature that can predict OS patient survival (verified in independent cohort [GSE39055]). Kaplan-Meier analysis showed that the signature can distinguish between the survival of high- and low-risk patients. ROC analysis corroborated this finding and revealed that the signature had higher prediction accuracy than known biomarkers. Kaplan-Meier analysis of the clinical subgroup showed that the signature's prognostic ability was independent of clinicopathological factors. The four-methylated lncRNA signature is an independent prognostic biomarker of OS.

Development and validation of a nomogram to predict the prognosis of patients with gastric cardia cancer

Our goal was to develop a prognostic nomogram to predict overall survival (OS) and cancer-specific survival (CSS) in patients with gastric cardia cancer (GCC). Patients diagnosed with GCC from 2004 to 2015 were screened from the surveillance, epidemiology, and end results (SEER) database. A nomogram was developed based on the variables associated with OS and CSS using multivariate Cox analysis regression models, which predicted 3- and 5-year OS and CSS. The predictive performance of the nomogram was evaluated using the consistency index (C-index), calibration curve and decision curve analysis (DCA), and the nomogram was calibrated for 3- and 5-year OS and CSS. A total of 7,332 GCC patients were identified and randomized into a training cohort (5,231, 70%) and a validation cohort (2,200, 30%). Multivariate Cox regression analysis showed that marital status, race, SEER stage, grade, T stage, N stage, M stage, tumor size, and surgery were independent risk factors for OS and CSS in GCC patients. Based on the multivariate Cox regression results, we constructed prognostic nomograms of OS and CSS. In the training cohort, the C-index for the OS nomogram was 0.714 (95% CI = 0.705–0.723), and the C-index for the CSS nomogram was 0.759 (95% CI = 0.746–0.772). In the validation cohort, the C-index for the OS nomogram was 0.734 (95% CI = 0.721–0.747), while the C-index for the CSS nomogram was 0.780 (95% CI = 0.759–0.801). Our nomogram has better prediction than the nomogram based on TNM stage. In addition, in the training and external validation cohorts, the calibration curves of the nomogram showed good consistency between the predicted and actual 3- and 5-year OS and CSS rates. The nomogram can effectively predict OS and CSS in GCC patients, which may help clinicians personalize prognostic assessments and clinical decisions.

Evaluation of C5orf66-AS1 as a Potential Biomarker for Predicting Early Gastric Cancer and Its Role in Gastric Carcinogenesis

Background

Long non-coding RNAs (lncRNAs) participate in a series of pathological processes in tumorigenesis. Reports show that C5orf66-AS1, an antisense lncRNA, is expressed in various tumors. However, the role of C5orf66-AS1 in gastric cancer (GC) has not been fully clarified. The study focused on the expression patterns and serum level of C5orf66-AS1 in GC to explore its potential application in GC screening and diagnosis. The effects of C5orf66-AS1 on GC cells were also analyzed.

Methods

Tissue and serum samples were used for RNA isolation. Expression levels of C5orf66-AS1 in GC tissues, serum, and cell lines were detected using quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR). CCK-8, transwell, and wound healing assays were performed to determine the effects of C5orf66-AS1 on GC cell behavior.

Results

C5orf66-AS1 expression was downregulated in GC cells compared to that in adjacent normal tissues. Serum C5orf66-AS1 levels were significantly lower in GC patients than in superficial gastritis (GS) and atrophic gastritis (GA) patients. Low serum expression of C5orf66-AS1 was associated with an increased risk of gastric dysplasia (GD) and GC. Receiver operating characteristic curve results showed that the area under curve (AUC) for GC was 0.688, with a sensitivity and specificity of 77.5% and 53.6%, respectively. For the GD + early gastric cancer (ECG) group, the AUC was 0.789, with a sensitivity and specificity of 85.15% and 62.86%, respectively. Correlation analyses of clinicopathological parameters showed that serum C5orf66-AS1 was predominantly associated with Lauren type, TNM stages, pTNM stages, and vessel tumor emboli. Additionally, in vitro overexpression of C5orf66-AS1 in AGS cells inhibited cell proliferation, migration, and invasion.

Conclusion

Decreased expression levels of serum C5orf66-AS1 can be utilized for diagnosis of GC, especially for early diagnosis. The low level of serum C5orf66-AS1 indicated poor biological behavior of tumors in GC patients. In addition, C5orf66-AS1 can inhibit GC cell proliferation, migration, and invasion.

Genome-Wide Identification and Characterization of DNA Methylation and Long Non-Coding RNA Expression in Gastric Cancer

Abnormal DNA methylation, an epigenetic modification, has increasingly been linked to the pathogenesis of many human cancers. However, there has been little focus on the DNA methylation patterns of genes encoding long noncoding RNAs (lncRNAs) in gastric cancer (GC). This study comprehensively determined DNA methylation and lncRNA expression profiles in GC through genome-wide analysis. Differentially methylated loci and lncRNAs were identified by integrating multi-omics data. In total, 548 differentially methylated CpG sites in lncRNA promoters and 2,399 differentially expressed lncRNAs were screened that were capable of distinguishing GC from normal tissues. Among them, 22 differentially methylation sites in 17 lncRNAs were inversely related to expression levels. Further analysis of DNA methylation status and gene expression level in GC revealed that three CpG sites (cg01550148, cg22497867, and cg20001829) and two lncRNAs (RP11-366F6.2 and RP5-881L22.5) were significantly associated with GC patient overall survival. Molecular function analysis showed that these abnormally methylated lncRNAs were mainly involved in transcriptional activator activity. Our study identified several lncRNAs regulated by aberrant DNA methylation that have clinical utility as novel prognostic biomarkers in GC. These findings help improve the understanding of methylated patterns of lncRNAs and further our knowledge of the role of epigenetics in cancer development.

lncRNA TMEM51-AS1 and RUSC1-AS1 function as ceRNAs for induction of laryngeal squamous cell carcinoma and prediction of prognosis

BACKGROUND

Long non-coding RNAs (lncRNAs) can function as competing endogenous RNAs (ceRNAs) to interact with miRNAs to regulate target genes and promote cancer initiation and progression. The expression of lncRNAs and miRNAs can be epigenetically regulated. The goal of this study was to construct an lncRNA-miRNA-mRNA ceRNA network in laryngeal squamous cell carcinoma (LSCC) and reveal their methylation patterns, which was not investigated previously.

METHODS

Microarray datasets available from the Gene Expression Omnibus database were used to identify differentially expressed lncRNAs (DELs), miRNAs (DEMs), and genes (DEGs) between LSCC and controls, which were then overlapped with differentially methylated regions (DMRs). The ceRNA network was established by screening the interaction relationships between miRNAs and lncRNAs/mRNAs by corresponding databases. TCGA database was used to identify prognostic biomarkers.

RESULTS

Five DELs (downregulated: TMEM51-AS1, SND1-IT1; upregulated: HCP5, RUSC1-AS1, LINC00324) and no DEMs were overlapped with the DMRs, but only a negative relationship occurred in the expression and methylation level of TMEM51-AS1. Five DELs could interact with 11 DEMs to regulate 242 DEGs, which was used to construct the ceRNA network, including TMEM51-AS1-miR-106b-SNX21/ TRAPPC10, LINC00324/RUSC1-AS1-miR-16-SPRY4/MICAL2/ SLC39A14, RUSC1-AS1-miR-10-SCG5 and RUSC1-AS1-miR-7-ZFP1 ceRNAs axes. Univariate Cox regression analysis showed RUSC1-AS1 and SNX21 were associated with overall survival (OS); LINC00324, miR-7 and ZFP1 correlated with recurrence-free survival (RFS); miR-16, miR-10, SCG5, SPRY4, MICAL2 and SLC39A14 were both OS and RFS-related. Furthermore, TRAPPC10 and SLC39A14 were identified as independent OS prognostic factors by multivariate Cox regression analysis.

CONCLUSION

DNA methylation-mediated TMEM51-AS1 and non-methylation-mediated RUSC1-AS1 may function as ceRNAs for induction of LSCC. They and their ceRNA axis genes (particularly TMEM51-AS1-miR-106b-TRAPPC10; RUSC1-AS1-miR-16-SLC39A14) may be potentially important prognostic biomarkers for LSCC.

Risk factors predisposing to cardia gastric adenocarcinoma: Insights and new perspectives

Recent decades have seen an alarming increase in the incidence of cardia gastric adenocarcinoma (CGA) while noncardia gastric adenocarcinoma (NCGA) has decreased. In 2012, 260 000 CGA cases (age‐standardised rate (ASR); 3.3/100 000) and 691 000 NCGA cases (ASR; 8.8/100 000) were reported worldwide. Compared with women, men had greater rates for both the subsites, especially for CGA. Recently, four molecular subtypes of GC have been proposed by the Cancer Genome Atlas (TCGA) and the Asian Cancer Research Group (ACRG); however, these classifications do not take into account predisposing germline variants and their possible interaction with somatic alterations in carcinogenesis. The etiology of adenocarcinoma of the cardia and the gastroesophageal junction (GEJ) is not known. It is thought that CGA is distinct from adenocarcinomas located in the esophagus or distal stomach, both epidemiologically and biologically. Moreover, CGA is often identified in the advanced stage having a poor prognosis. Therefore, understanding the risk and the role of predisposing factors in etiology of CGA can inform clinical practice and counseling for risk reduction. In this paper, we showed that GC family history, lifestyle, demographics, gastroesophageal reflux disease, Helicobacter pylori infection, and multiple genetic and epigenetic risk factors as well as several predisposing conditions may underlie susceptibility to CGA. However, several genome‐wide association studies (GWASs) should be conducted to identify novel high‐penetrance genes and pathways as well as causal germline variants predisposing to CGA. They must include different ethnic groups, especially from high‐incidence countries for CGA, because some risk loci are ancestry‐specific. In parallel, statistical methods can be developed to identify cancer predisposition genes (CPGs) from tumor sequencing data. It is also necessary to find novel long noncoding RNAs related to the risk of CGA. Taken altogether, new cancer risk prediction models, including all genetic and nongenetic factors influencing risk, should be developed to facilitate risk assessment, disease prevention, and early diagnosis and intervention of CGA in the future.

Identification of a six lncRNAs signature as novel diagnostic biomarkers for cervical cancer

Cervical cancer is a tumor with the second highest morbidity and mortality in the world, and it is also the most common cancer and the eighth lethal factor among malignant tumors in Chinese female. This study aimed to identify long noncoding RNAs (lncRNAs) that related to diagnosis and prognosis in cervical cancer to improve early diagnosis and treatment. First, we extracted transcriptome profilings of cervical cancer samples from the cancer genome atlas (TCGA) database, and then extracted the lncRNAs and mRNAs expression profiles. Based on the lncRNAs expression profiles of test set, we screened lncRNAs that related to progression of cervical cancer tumors. We found six lncRNAs associated with tumor progression in cervical cancer patients, in which five lncRNAs have highly similar expression patterns but the other one has the opposite expression pattern. We found that these six lncRNAs might be related to keratinization and immunity by enrichment analysis, and two of them (AC126474 and C5orf66-AS1) were associated with prognosis in patients with cervical cancer. And these results were validated using the validation set. Overall, we identified six lncRNAs that played an important role in the development of cervical cancer, and two of them might be associated with the prognosis of cervical cancer, which provides new insight into the diagnosis and treatment of cervical cancer.

ZCCHC10 suppresses lung cancer progression and cisplatin resistance by attenuating MDM2-mediated p53 ubiquitination and degradation

The activation of p53 tumor suppressor is essential for preventing abnormal cell proliferation and carcinogenesis. ZCCHC10 was previously identified as a potential p53-interacting partner in a yeast two-hybrid screen, but the interaction in cells and its subsequent influence on p53 activity and cancer development have not been investigated. In this paper, we demonstrate that ZCCHC10 expression levels are statistically lower in lung adenocarcinoma tissues than the corresponding adjacent noncancerous tissues, and decreased expression of ZCCHC10 mRNA predicts poorer survival of the patients. Ectopic expression of ZCCHC10 in lung cancer cells harboring wild-type p53 dramatically suppresses cell proliferation, colony formation, migration, invasion and cisplatin resistance in vitro, as well as tumor growth and metastasis in vivo. Conversely, knockdown of ZCCHC10 exerts opposite effects in the normal lung cell Beas-2b. However, ZCCHC10 has no influence on the biological behaviors of p53-null (H358) or p53-mutant (H1437) lung cancer cells. Mechanistically, ZCCHC10 binds and stabilizes p53 by disrupting the interaction between p53 and MDM2. The p53 inhibitor pifithrin-α attenuated the influences of ZCCHC10 overexpression on p53 pathway, cell cycle, apoptosis, and epithelial-mesenchymal transition, whereas the p53 activator Nutlin3 could reverse the effects of ZCCHC10 knockdown. Collectively, our results indicate that ZCCHC10 exerts its tumor-suppressive effects by stabilizing the p53 protein and can be used a potential prognostic marker and therapeutic target in lung adenocarcinoma.

Integrated analysis reveals potential long non-coding RNA biomarkers and their potential biological functions for disease free survival in gastric cancer patients

Background

Increasing evidences supported the association between long non-coding RNA (lncRNA) and disease free survival in gastric cancer (GC) patients. The purpose of the current study was to construct and verify a noninvasive preoperative predictive tool for disease free survival in GC patients.

Methods

There were 265 and 300 GC patients in model dataset and validation dataset respectively. The associations between the lncRNA biomarkers and disease free survival were evaluated by univariate and multivariate Cox regression.

Results

Thirteen lncRNA biomarkers (GAS5-AS1, AL109615.3, KDM7A-DT, AP000866.2, KCNJ2-AS1, LINC00656, LINC01777, AC046185.3, TTTY14, LINC01526, LINC02523, LINC00592, and C5orf66) were identified as prognostic biomarkers with disease free survival. These thirteen lncRNA biomarkers were combined to construct a prognostic signature for disease free survival. The C-indexes of the current predictive signature in model cohort were 0.849 (95% CI 0.803–0.895), 0.859 (95% CI 0.813–0.905) and 0.888 (95% CI 0.842–0.934) for 1-year, 3-year and 5-year disease free survival respectively. Based on thirteen-lncRNA prognostic signature, patients in model cohort could be stratified into high risk group and low risk group with significant different disease free survival rate (hazard ratio [HR] = 7.355, 95% confidence interval [CI] 4.378–12.356). Good reproducibility of thirteen-lncRNA prognostic signature was confirmed in an external validation cohort (GSE62254) with HR 3.919 and 95% CI 2.817–5.453. Further analysis demonstrated that the prognostic significance of thirteen-lncRNA prognostic signature was independent of other clinical characteristics.

Conclusions

In conclusion, a simple noninvasive prognostic signature was established for preoperative prediction of disease free survival in GC patients. This prognostic signature might predict the individual mortality risk of disease free survival without pathological information and facilitate individual treatment decision-making.

Electronic supplementary material

The online version of this article (10.1186/s12935-019-0846-6) contains supplementary material, which is available to authorized users.

The Hippo signaling effector WWTR1 is a metastatic biomarker of gastric cardia adenocarcinoma

Background

Gastric cardia adenocarcinoma (GCA) is an aggressive subtype of gastric cancer with a high metastatic rate. However, the metastatic biomarker of GCA has not been established.

Methods

To search for the biomarker for GCA metastasis, we here examined expression of the Hippo signaling effector WWTR1 (WW domain containing transcription regulator 1, commonly listed as TAZ) in tumor tissue samples from 214 GCA cases using the tissue microarray assay (TMA), and statistically analyzed association of the WWTR1 expression with metastasis-related pathological outcomes and cumulative survival of the GCA patients. Furthermore, shRNA knockdown was used to determine the role of WWTR1 in promoting cell migration in gastric cancer cells.

Results

The results have shown that WWTR1 is overexpressed in 66.4% of the GCA tumor samples. Expression of WWTR1 has a significant inverse correlation with cumulative survival of GCA patients (p < 0.01). WWTR1 positive patients had a mean survival of 56.9 ± 4.4 months, comparing to WWTR1 negative mean survival of 77.3 ± 5.9 months. More importantly, expression of WWTR1 significantly associated with tumor invasion and metastasis (in T stage, p = 0.031; N stage, p < 0.01; and TNM stage, p < 0.001). Furthermore, knockdown of WWTR1 impaired migration of gastric cancer AGS cells.

Conclusions

Our studies have identified WWTR1 as a metastatic biomarker of GCA for poor prognosis, defined a role of WWTR1 in driving metastasis of gastric cancer, and suggested WWTR1 as a potential target for anti-metastatic therapy of GCA.

Analyses on K-ras mutations and fascin expression in patients with cardia cancer

Mutations of K-rat sarcoma (K-ras) in patients with cardia cancer and their effects on the expression of fascin were investigated. A total of 90 cardia cancer patients treated in Jining First People's Hospital from March 2014 to March 2017 were randomly selected. Genomic deoxyribonucleic acid (DNA) was extracted from paraffin-embedded cardia cancer specimens. Pyrosequencing was applied to detect sequences of K-ras gene in all patients and to analyze the mutations of K-ras gene. Then, genotyping of mutations at each mutation site was carried out using quantitative polymerase chain reaction (qPCR). The expression level of fascin in patients was measured via immunohistochemistry and qPCR. The results revealed that among 90 patients with cardia cancer, 21 patients had K-ras mutations (23.3%), including 20 cases of exon 12 mutation and 1 case of exon 13 mutation. Risk factor analyses revealed that alcohol abuse was a high risk factor for mutations (p<0.05). There was no significant difference in the mutation probability between heterozygotes and homozygotes for four mutations at codon 12 (p>0.05). The heterozygote at codon 13 had a higher mutation probability than homozygote (p<0.05). Immunohistochemistry suggested that the number of positive cells in the mutant group was larger than that in the non-mutant group (p<0.05). The results of qPCR showed that the expression level of fascin gene in the mutant group was 2.3 times higher than that in the non-mutant group (p<0.05). In conclusion, the probability of codon 12 mutation in K-ras gene is increased in patients with cardia cancer, and fascin is highly expressed in mutant patients, which is positively correlated with the mutations in K-ras gene.