Integrated analysis of long non-coding RNA competing interactions reveals the potential role in progression of human gastric cancer

LncRNA RPLP0P2 Promotes Colorectal Cancer Proliferation and Invasion via the miR-129-5p/Zinc Finger and BTB Domain-Containing 20 Axis

We previously reported that long non-coding RNA (lncRNA) RPLP0P2 is involved in the progression of colorectal cancer (CRC); however, its molecular mechanisms in CRC remain unclear. In this study, we observed that RPLP0P2 was upregulated in CRC tissues and cell lines. Cell viability was measured using the MTT and colony formation assays. Migration and invasion capabilities were monitored by wound healing, transwell, and immunofluorescence assays. The results showed that RPLP0P2 downregulation inhibited cell viability, migration, and invasion capabilities of CRC cells, accompanied by decreased PCNA, N-cadherin, and Vimentin, and increased E-cadherin expression. Using the DIANA online database, miR-129-5p was identified as a downstream target of RPLP0P2. In fact, RPLP0P2 colocalized with miR-129-5p, acting as a miR-129-5p sponge. MiR-129-5p-inhibition almost abrogated the anti-tumor effects induced by RPLP0P2 inhibition in CRC cells. Zinc finger and BTB domain-containing 20 (ZBTB20) was identified as a potential downstream target of miR-129-5p in CRC cells. ZBTB20 overexpression prevented miR-129-5p mimic-mediated anti-tumor effects in CRC cells. A tumor xenograft assay was performed to monitor the role of RPLP0P2 in tumor growth. Of note, in tumor-bearing mice, RPLP0P2-silencing inhibited tumor growth, followed by increased miR-129-5p and decreased ZBTB20 expression. Our results suggest that lncRNA RPLP0P2 functions as an oncogene that promotes CRC cell proliferation and invasion via regulating the miR-129-5p/ZBTB20 axis, thus, it may serve as a candidate target for CRC interventional therapies.

LncRNAs associated with lymph node metastasis in thyroid cancer based on TCGA database

OBJECTIVE

Long non-coding RNA (lncRNA), especially RNA associated with lymph node metastasis, plays an important role in the development of cancer. Identifying metastasis related lncRNAs and exploring their clinical significance can guide the treatment and prognosis of thyroid cancer patients.

METHODS

RNA expression and clinical data of thyroid cancer was derived from The Cancer Genome Atlas (TCGA) database, while the survival data was obtained from the ULCAN database. R language and SPSS software were used to analyze the correlation between lncRNA and lymph node metastasis of thyroid cancer and the lncRNAs associated with lymph node metastasis were screened.

RESULT

10 lncRNAs showed significant differential expression in thyroid cancer with and without lymph node metastasis. Four lncRNAs (LRRC52-AS1, AP002358.1, AC004847.1, and AC254633.1) were overexpressed in metastatic thyroid cancer, while six lncRNAs (SLC26A4-AS1, LINC01886, LINC01789, AF131216.3, AC062015.1, and AL031710.1) were underexpressed. The expression levels of these lncRNAs were associated with the clinical staging of tumors. Cox regression analysis further showed that elevated expression levels of AP002358.1 and LRRC52-AS1 were associated with poor prognosis in patients with thyroid cancer. In addition, analysis of the UALCAN database indicated that these two lncRNAs were significantly overexpressed in thyroid cancer compared to other cancers, and the expression levels of AF131216.3 and AL031710.1 were associated with progression-free survival in thyroid cancer patients.

CONCLUSION

These lncRNAs may play crucial roles in the development and progression of thyroid cancer and could serve as potential markers for predicting tumor metastasis, clinical stage, and patient prognosis.

Integrated analysis of transcriptome and epigenome reveals ENSR00000272060 as a potential biomarker in gastric cancer

Background: Enhancer RNAs (eRNAs) are involved in gene expression regulation. Although functional roles of eRNAs in the pathophysiology of neoplasms have been reported, their involvement in gastric cancer (GC) is less known. Materials & methods: A network-based integrative approach was utilized for analyzing transcriptome and epigenome alterations in GC, and an eRNA was selected for experimental validation. Survival analysis and clinicopathological associations were also performed. Results: A hub eRNA, ENSR00000272060, showed significantly increased expression in tumor versus nontumor tissues, as well as an association with clinicopathological features. A seven-gene prognostic model was also constructed. Conclusion: The constructed network provides a comprehensive understanding of the underlying processes implicated in the progression of GC, along with a starting point from which to derive potential diagnostic/prognostic biomarkers.

The TINCR ubiquitin-like microprotein is a tumor suppressor in squamous cell carcinoma

The TINCR (Terminal differentiation-Induced Non-Coding RNA) gene is selectively expressed in epithelium tissues and is involved in the control of human epidermal differentiation and wound healing. Despite its initial report as a long non-coding RNA, the TINCR locus codes for a highly conserved ubiquitin-like microprotein associated with keratinocyte differentiation. Here we report the identification of TINCR as a tumor suppressor in squamous cell carcinoma (SCC). TINCR is upregulated by UV-induced DNA damage in a TP53-dependent manner in human keratinocytes. Decreased TINCR protein expression is prevalently found in skin and head and neck squamous cell tumors and TINCR expression suppresses the growth of SCC cells in vitro and in vivo. Consistently, Tincr knockout mice show accelerated tumor development following UVB skin carcinogenesis and increased penetrance of invasive SCCs. Finally, genetic analyses identify loss-of-function mutations and deletions encompassing the TINCR gene in SCC clinical samples supporting a tumor suppressor role in human cancer. Altogether, these results demonstrate a role for TINCR as protein coding tumor suppressor gene recurrently lost in squamous cell carcinomas.

The role of LncRNA MCM3AP-AS1 in human cancer

Long noncoding RNAs (lncRNA) play pivotal roles in every level of gene and genome regulation. MCM3AP-AS1 is a lncRNA that has an oncogenic role in several kinds of cancers. Aberrant expression of MCM3AP-AS1 has been reported to be involved in the progression of diverse malignancies, including colorectal, cervical, prostate, lymphoma, lung, ovary, liver, bone, and breast cancers. It is generally believed that MCM3AP-AS1 expression is associated with cancer cell growth, proliferation, angiogenesis, and metastasis. MCM3AP-AS1 by targeting various signaling pathways and microRNAs (miRNAs) presents an important role in cancer pathogenesis. MCM3AP-AS1 as a competitive endogenous RNA has the ability to sponge miRNA, inhibit their expressions, and bind to different target mRNAs related to cancer development. Therefore, MCM3AP-AS1 by targeting several signaling pathways, including the FOX family, Wnt, EGF, and VEGF can be a potent target for cancer prediction and diagnosis. In this review, we will summarize the role of MCM3AP-AS1 in various human cancers.

The expression of long non-coding RNA LINC01389, LINC00365, RP11-138J23.1, and RP11-354K4.2 in gastric cancer and their impacts on EMT

BACKGROUND

Epithelial cancers acquire the epithelial to mesenchymal transition (EMT), which leads tumor cells to invade and metastasize to adjacent and distant tissues. The mechanisms involved in EMT phenotype are controlled by numerous markers as well as signalling pathways. Recently, long non-coding RNAs (lncRNAs) were introduced that play the regulatory role in EMT via crosstalk with EMT-related transcription factors and signalling pathways. The present study aimed to investigate the expression of four lncRNAs in human GC and elucidate their probable role in EMT procedure and the pathogenesis of gastric cancer (GC).

METHODS

The expression profile of lncRNAs (LINC01389, LINC00365, RP11-138J23.1, and RP11-354K4.2) and mRNAs (TWIST1, MMP13, MAML1, CD44s, and SALL4) between eighty-three GC and adjacent non-cancerous tissues were assessed by quantitative real-time PCR.

RESULTS

The significant downregulation of LINC00365 (66.3%) and RP11-354K4.2 (62.7%) were observed in GC samples; while the upregulation of LINC01389, RP11-138J23.1, TWIST1, MMP13, MAML1, CD44s, and SALL4 were found in 67.5%, 45.8%, 56.6%, 44.6%, 59%, 55.4%, and 62.7% tumors samples at the mRNA level, respectively. Dysregulation of these lncRNAs and EMT-related markers was significantly related to each other in a variety of clinicopathological features of patients (P < 0.05), indicating positive correlations between LINC01389, LINC00365, RP11-138J23.1, and RP11-354K4.2 with EMT status in GC.

CONCLUSION

These EMT-regulating lncRNAs may play a key role in transforming gastric epithelial to mesenchymal phenotype and can be novel therapeutic targets for GC. Our results highlight the importance of discovering new lncRNAs involved in gastric carcinogenesis. Detailed molecular mechanisms of these noncoding-coding markers in GC are urgently required.

Cuproptosis-Related lncRNA Gene Signature Establishes a Prognostic Model of Gastric Adenocarcinoma and Evaluate the Effect of Antineoplastic Drugs

BACKGROUND

One of the most frequent malignancies of the digestive system is stomach adenocarcinoma (STAD). Recent research has demonstrated how cuproptosis (copper-dependent cell death) differs from other cell death mechanisms that were previously understood. Cuproptosis regulation in tumor cells could be a brand-new treatment strategy. Our goal was to create a cuproptosis-related lncRNA signature. Additionally, in order to evaluate the possible immunotherapeutic advantages and drug sensitivity, we attempted to study the association between these lncRNAs and the tumor immune microenvironment of STAD tumors.

METHODS

The TCGA database was accessed to download the RNA sequencing data, genetic mutations, and clinical profiles for TCGA STAD. To locate lncRNAs related to cuproptosis and build risk-prognosis models, three techniques were used: co-expression network analysis, Cox-regression techniques, and LASSO techniques. Additionally, an integrated methodology was used to validate the models' predictive capabilities. Then, using GO and KEGG analysis, we discovered the variations in biological functions between each group. The link between the risk score and various medications for STAD treatment was estimated using the tumor mutational load (TMB) and tumor immune dysfunction and rejection (TIDE) scores.

RESULT

We gathered 22 genes linked to cuproptosis based on the prior literature. Six lncRNAs related to cuproptosis were used to create a prognostic marker (AC016394.2, AC023511.1, AC147067.2, AL590705.3, HAGLR, and LINC01094). After that, the patients were split into high-risk and low-risk groups. A statistically significant difference in overall survival between the two groups was visible in the survival curves. The risk score was demonstrated to be an independent factor affecting the prognosis by both univariate and multivariate Cox regression analysis. Different risk scores were substantially related to the various immunological states of STAD patients, as further evidenced by immune cell infiltration and ssGSEA analysis. The two groups had differing burdens of tumor mutations. In addition, immunotherapy was more effective for STAD patients in the high-risk group than in the low-risk group, and risk scores for STAD were substantially connected with medication sensitivity.

CONCLUSIONS

We discovered a marker for six cuproptosis-associated lncRNAs linked to STAD as prognostic predictors, which may be useful biomarkers for risk stratification, evaluation of possible immunotherapy, and assessment of treatment sensitivity for STAD.

Clinicopathological and prognostic value of lncRNAs expression in gastric cancer: A field synopsis of observational studies and databases validation

BACKGROUND

The purpose of this study was to evaluate existing evidence in the field of long non-coding RNAs (lncRNAs) and prognosis of gastric cancer.

METHODS

A comprehensive literature search was performed through the electronic database. The combined hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) of overall survival (OS), disease-free survival (DFS), or progression free survival (PFS) were calculated to assess the strength of the association. Kaplan-Meier (KM) plotter was used to verify lncRNA HOX transcript antisense RNA (HOTAIR) expression and OS.

RESULTS

Overall, a significant correlation between high lncRNAs expression and poor OS was explored in patients with gastric cancer (HR = 1.78, P < .001). Subgroup analysis based on statistical methods indicated the high expression of lncRNAs in log-rank (HR = 1.87, P < .001) and multivariate analysis (HR = 1.71, P < .001) were all significantly correlated with the poor OS. Clinicopathological parameters analysis showed the lncRNA expression were significantly associated prognosis, including TNM stage, tumor size, pathological differentiation, lymph nodes metastasis, distance metastasis, invasion depth and Lauren's classification. It was consistent with the verification results of bioinformatics database for lncRNA HOTAIR (P < .001).

CONCLUSION

Our study confirmed the expression of lncRNAs and clinicopathological features may serve as effective indicators of prognosis in patients with gastric cancer.

Long noncoding RNA (lncRNA) HOTAIR: Pathogenic roles and therapeutic opportunities in gastric cancer

Gastric cancer is one of the first malignant cancers in the world and a large number of people die every year due to this disease. Many genetic and epigenetic risk factors have been identified that play a major role in gastric cancer. HOTAIR is an effective epigenetic agent known as long noncoding RNA (lncRNA). HOTAIR has been described to have biological functions in biochemical and cellular processes through interactions with many factors, leading to genomic stability, proliferation, survival, invasion, migration, metastasis, and drug resistance. In the present article, we reviewed the prognostic value of the molecular mechanisms underlying the HOTAIR regulation and its function in the development of Gastric Cancer, whereas elucidation of HOTAIR–protein and HOTAIR–DNA interactions can be helpful in the identification of cancer processes, leading to the development of potential therapeutic strategies.

Discovery and Validation of Clinically Relevant Long Non-Coding RNAs in Colorectal Cancer

Simple Summary

Recent efforts in biomedical research have focused on the identification of molecular biomarkers to improve the diagnosis, prognosis and eventually treatment of the most common human diseases worldwide, including cancer. In this context, a large number of studies point to a pivotal role of long non-coding RNAs (lncRNAs) in the pathophysiology of carcinogenesis, suggesting diagnostic or therapeutic potential. However, for most of them, supporting evidence is scarce and often based on a single large-scale analysis. Here, focusing on colorectal cancer (CRC), we present an overview of the main approaches for discovering and validating lncRNA candidate molecules, and provide a curated list of the most promising lncRNAs associated with this malignancy.

Abstract

Colorectal cancer (CRC) is the third most prevalent cancer worldwide, with nearly two million newly diagnosed cases each year. The survival of patients with CRC greatly depends on the cancer stage at the time of diagnosis, with worse prognosis for more advanced cases. Consequently, considerable effort has been directed towards improving population screening programs for early diagnosis and identifying prognostic markers that can better inform treatment strategies. In recent years, long non-coding RNAs (lncRNAs) have been recognized as promising molecules, with diagnostic and prognostic potential in many cancers, including CRC. Although large-scale genome and transcriptome sequencing surveys have identified many lncRNAs that are altered in CRC, most of their roles in disease onset and progression remain poorly understood. Here, we critically review the variety of detection methods and types of supporting evidence for the involvement of lncRNAs in CRC. In addition, we provide a reference catalog that features the most clinically relevant lncRNAs in CRC. These lncRNAs were selected based on recent studies sorted by stringent criteria for both supporting experimental evidence and reproducibility.

Small integral membrane protein 10 like 1 downregulation enhances differentiation of adipose progenitor cells

Small integral membrane protein 10 like 1 (SMIM10L1) was identified by RNA sequencing as the most significantly downregulated gene in Phosphatase and Tensin Homologue (PTEN) knockdown adipose progenitor cells (APCs). PTEN is a tumor suppressor that antagonizes the growth promoting Phosphoinositide 3-kinase (PI3K)/AKT/mechanistic Target of Rapamycin (mTOR) cascade. Diseases caused by germline pathogenic variants in PTEN are summarized as PTEN Hamartoma Tumor Syndrome (PHTS). This overgrowth syndrome is associated with lipoma formation, especially in pediatric patients. The mechanisms underlying this adipose tissue dysfunction remain elusive. We observed that SMIM10L1 downregulation in APCs led to an enhanced adipocyte differentiation in two- and three-dimensional cell culture and increased expression of adipogenesis markers. Furthermore, SMIM10L1 knockdown cells showed a decreased expression of PTEN, pointing to a mutual crosstalk between PTEN and SMIM10L1. In line with these observations, SMIM10L1 knockdown cells showed increased activation of PI3K/AKT/mTOR signaling and concomitantly increased expression of the adipogenic transcription factor SREBP1. We computationally predicted an α-helical structure and membrane association of SMIM10L1. These results support a specific role for SMIM10L1 in regulating adipogenesis, potentially by increasing PI3K/AKT/mTOR signaling, which might be conducive to lipoma formation in pediatric patients with PHTS.

miRNA and lncRNA Expression Networks Modulate Cell Cycle and DNA Repair Inhibition in Senescent Prostate Cells

Cellular senescence is a state of permanent growth arrest that arises once cells reach the limit of their proliferative capacity. It creates an inflammatory microenvironment favouring the initiation and progression of various age-related diseases, including prostate cancer. Non-coding RNAs (ncRNAs) have emerged as important regulators of cellular gene expression. Nonetheless, very little is known about the interplay of microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) and how deregulation of ncRNA networks promotes cellular senescence. To investigate this, human prostate epithelial cells were cultured through different passages until senescent, and their RNA was extracted and sequenced using RNA sequencing (RNAseq) and microRNA sequencing (miRNA-seq) miRNAseq. Differential expression (DE) gene analysis was performed to compare senescent and proliferating cells with Limma, miRNA-target interactions with multiMiR, lncRNA-target interactions using TCGA data and network evaluation with miRmapper. We found that miR-335-3p, miR-543 and the lncRNAs H19 and SMIM10L2A all play central roles in the regulation of cell cycle and DNA repair processes. Expression of most genes belonging to these pathways were down-regulated by senescence. Using the concept of network centrality, we determined the top 10 miRNAs and lncRNAs, with miR-335-3p and H19 identified as the biggest hubs for miRNAs and lncRNA respectively. These ncRNAs regulate key genes belonging to pathways involved in cell senescence and prostate cancer demonstrating their central role in these processes and opening the possibility for their use as biomarkers or therapeutic targets to mitigate against prostate ageing and carcinogenesis.

Gene signature to predict prognostic survival of hepatocellular carcinoma

Hepatocellular carcinoma (HCC) has a high incidence and poor prognosis and is the second most fatal cancer, and certain HCC patients also show high heterogeneity. This study developed a prognostic model for predicting clinical outcomes of HCC. RNA and microRNA (miRNA) sequencing data of HCC were obtained from the cancer genome atlas. RNA dysregulation between HCC tumors and adjacent normal liver tissues was examined by DESeq algorithms. Survival analysis was conducted to determine the basic prognostic indicators. We identified competing endogenous RNA (ceRNA) containing 15,364 pairs of mRNA–long noncoding RNA (lncRNA). An imbalanced ceRNA network comprising 8 miRNAs, 434 mRNAs, and 81 lncRNAs was developed using hypergeometric test. Functional analysis showed that these RNAs were closely associated with biosynthesis. Notably, 53 mRNAs showed a significant prognostic correlation. The least absolute shrinkage and selection operator’s feature selection detected four characteristic genes (SAPCD2, DKC1, CHRNA5, and UROD), based on which a four-gene independent prognostic signature for HCC was constructed using Cox regression analysis. The four-gene signature could stratify samples in the training, test, and external validation sets (p <0.01). Five-year survival area under ROC curve (AUC) in the training and validation sets was greater than 0.74. The current prognostic gene model exhibited a high stability and accuracy in predicting the overall survival (OS) of HCC patients.

Comprehensive analysis of the LncRNAs, MiRNAs, and MRNAs acting within the competing endogenous RNA network of LGG

Messenger RNA (mRNA) and long noncoding RNA (lncRNA) targets interact via competitive microRNA (miRNA) binding. However, the roles of cancer-specific lncRNAs in the competing endogenous RNA (ceRNA) networks of low-grade glioma (LGG) remain unclear. This study obtained RNA sequencing data for normal solid tissue and LGG primary tumour tissue from The Cancer Genome Atlas database. We used a computational method to analyse the relationships among the mRNAs, lncRNAs, and miRNAs in these samples. Gene ontology (GO) function and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was used to predict the biological processes (BPs) and pathways associated with these genes. Kaplan-Meier survival analysis was used to evaluate the association between the expression levels of specific mRNAs, lncRNAs, and miRNAs and overall survival. Finally, we created a ceRNA network describing the relationships among these mRNAs, lncRNAs, and miRNAs using Cytoscape 3.5.1. A total of 2555 differentially expressed (DE) mRNAs, 218 DElncRNAs, and 192 DEmiRNAs were identified using R. In addition, GO and KEGG pathway analysis of the mRNAs and lncRNAs in the ceRNA network identified 10 BPs, 10 cell components, 10 molecular functions, and 48 KEGG pathways as selectively enriched. A total of 55 lncRNAs, 50 miRNAs, and 10 mRNAs from this network were shown to be closely associated with overall survival in LGG. Finally, 59 miRNAs, 235 mRNAs, and 17 lncRNAs were used to develop a ceRNA network comprising 313 nodes and 1046 edges. This study helps expand our understanding of ceRNA networks and serves to clarify the underlying pathogenesis mechanism of LGG.

Potential of Internet of Medical Things (IoMT) applications in building a smart healthcare system: A systematic review

Sudden spurting of Corona virus disease (COVID-19) has put the whole healthcare system on high alert. Internet of Medical Things (IoMT) has eased the situation to a great extent, also COVID-19 has motivated scientists to make new ‘Smart’ healthcare system focusing towards early diagnosis, prevention of spread, education and treatment and facilitate living in the new normal. This review aims to identify the role of IoMT applications in improving healthcare system and to analyze the status of research demonstrating effectiveness of IoMT benefits to the patient and healthcare system along with a brief insight into technologies supplementing IoMT and challenges faced in developing a smart healthcare system.

An internet-based search in PUBMED, Google Scholar and IEEE Library for english language publications using relevant terms resulted in 987 articles. After screening title, abstract, and content related to IoMT in healthcare and excluding duplicate articles, 135 articles published in journal with impact factor ≥1 were eligible for inclusion. Also relevant articles from the references of the selected articles were considered.

The habituation of IoMT and related technology has resolved several difficulties using remote monitoring, telemedicine, robotics, sensors etc. However mass adoption seems challenging due to factors like privacy and security of data, management of large amount of data, scalability and upgradation etc. Although ample knowledge has been compiled and exchanged, this structured systematic review will help the healthcare practitioners, policymakers/decision makers, scientists and researchers to gauge the applicability of IoMT in healthcare more efficiently.

Identification of Novel CircRNA-miRNA-mRNA Regulatory Network and Its Prognostic Prediction in Breast Cancer

Aim

This study aimed to investigate the expression profiles of circRNAs and candidate circRNA-miRNA-mRNA network in BC.

Methods

Differentially expressed circRNAs, miRNAs, and mRNAs (DEcircRNAs, DEmiRNAs, and DEmRNAs) between BC and normal breast tissue samples were screened by analyzing raw data of the RNA sequencing profile. The expression levels of hub genes in 48 pairs of cancerous and tumor-free breast tissues surgically resected from BC patients were determined by RT-qPCR analysis.

Results

A total of 145 DEcircRNAs, 140 DEmiRNAs, and 2451 DEmRNAs between BC and normal breast tissue samples were screened out. There were 5 pairs of upcircRNA-downmiRNA-upmRNA network and 20 pairs of downcircRNA-upmiRNA-downmRNA network. EIF4EBP1, DUSP1, EGR2, EZH1, and CBX7 were found to be correlated with overall survival of the patients with BC. The expression level of EIF4EBP1 was increased and the expression levels of DUSP1, EGR2, EZH1, and CBX7 were decreased in cancerous breast tissues compared to tumor-free breast tissues (p < 0.0001). The RT-qPCR results from 48 BC patients were consistent with the bioinformatics results.

Conclusion

This study provides a novel perspective to study circRNA-miRNA-mRNA network in BC and assists in the identification of new potential biomarkers to be used for diagnostic and prognostic purposes.

Moderate Prognostic Value of lncRNA FOXD2-AS1 in Gastric Cancer with Helicobacter pylori Infection

PURPOSE

Gastric cancer (GC) is one of the most frequent tumors worldwide and identification of a sensitive and specific prognostic biomarker is of great importance. Long non-coding RNAs (lncRNAs) play crucial roles in tumorigenesis of various malignancies. In the present study, we investigated lncRNA FOXD2-AS1 expression in gastric tumors and assessed its potential as a prognostic biomarker.

METHODS

A total of 95 tumor and corresponding adjacent non-tumor tissue specimens were collected from patients with GC from Imam Reza hospital, Tabriz, Iran. Total RNA was isolated and FOXD2-AS1 expression was measured using quantitative reverse transcriptase (qRT)-PCR.

RESULTS

FOXD2-AS1 was significantly upregulated in tumor samples as compared to non-tumor tissues (P < 0.0001). In addition, higher expression of FOXD2-AS1 was significantly associated with lymph node metastasis and Helicobacter pylori infection. The receiver operating characteristic (ROC) curve analysis revealed that FOXD2-AS1 might be served as a potential prognostic biomarker for GC.

CONCLUSION

FOXD2-AS1 is upregulated in gastric tumors and can be used as a valuable biomarker in the prognosis of patients with GC.

Bioinformatic and integrated analysis identifies an lncRNA-miRNA-mRNA interaction mechanism in gastric adenocarcinoma

BACKGROUND

lncRNAs-miRNAs-mRNAs networks play an important role in Gastric adenocarcinoma (GA). Identification of these networks provide new insight into the role of these RNAs in gastric cancer.

OBJECTIVES

Biological information databases were screened to characterize and examine the regulatory networks and to further investigate the potential prognostic relationship this regulation has in GA.

METHODS

By mining The Cancer Genome Atlas (TCGA) database, we gathered information on GA-related lncRNAs, miRNAs, and mRNAs. We identified differentially expressed (DE) lncRNAs, miRNAs, and mRNAs using R software. The lncRNA-miRNA-mRNA interaction network was constructed and subsequent survival examination was performed. Representative genes were selected out using The Biological Networks Gene Ontology plug-in tool on Cytoscape. Additional analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) terms were used to screen representative genes for functional enrichment. Reverse transcription quantitative polymerase chain reaction (RT-qPCR) were used to identify the expression of five candidate differential expressed RNAs.

RESULTS

Information of samples from 375 cases of gastric cancer and 32 healthy cases (normal tissues) were downloaded from the TCGA database. A total of 1632 DE-mRNAs, 1008 DE-lncRNAs and 104 DE-miRNAs were identified and screened. Among them, 65 DE-lncRNAs, 10 DE-miRNAs, and 10 DE-mRNAs form lncRNAs-miRNAs-mRNAs regulatory network. Additionally, 10 lncRNAs and 2 mRNAs were associated with the prognosis of GA. Multivariable COX analysis revealed that AC018781.1 and VCAN-AS1 were independent risk factors for GA. GO functional enrichment analysis found DE-mRNA was significantly enriched TERM (P < 0.05). The KEGG signal regulatory network analysis found 11 significantly enrichment networks, the most prevailing was for the AGE-RAGE signaling pathway associated with Diabetic complications. Results of RT-qPCR was consistent with the in silico results.

CONCLUSIONS

The results of the present study represent a view of GA from a analysis of lncRNA, miRNA and mRNA. The network of lncRNA-miRNA-mRNA interactions revealed here may potentially further experimental studies and may help biomarker development for GA.

Identification of hub driving genes and regulators of lung adenocarcinoma based on the gene Co-expression network

Lung adenocarcinoma (LUAD) remains the leading cause of cancer-related deaths worldwide. Increasing evidence suggests that circular RNAs (circRNAs) and long non-coding RNAs (lncRNAs) can regulate target gene expression and participate in tumor genesis and progression. However, hub driving genes and regulators playing a potential role in LUAD progression have not been fully elucidated yet. Based on data from The Cancer Genome Atlas database, 2837 differentially expressed genes, 741 DE-regulators were screened by comparing cancer tissues with paracancerous tissues. Then, 651 hub driving genes were selected by the topological relation of the protein-protein interaction network. Also, the target genes of DE-regulators were identified. Moreover, a key gene set containing 65 genes was obtained from the hub driving genes and target genes intersection. Subsequently, 183 hub regulators were selected based on the analysis of node degree in the ceRNA network. Next, a comprehensive analysis of the subgroups and Wnt, mTOR, and MAPK signaling pathways was conducted to understand enrichment of the subgroups. Survival analysis and a receiver operating characteristic curve analysis were further used to screen for the key genes and regulators. Furthermore, we verified key molecules based on external database, LRRK2, PECAM1, EPAS1, LDB2, and HOXA11-AS showed good results. LRRK2 was further identified as promising biomarker associated with CNV alteration and various immune cells' infiltration levels in LUAD. Overall, the present study provided a novel perspective and insight into hub driving genes and regulators in LUAD, suggesting that the identified signature could serve as an independent prognostic biomarker.

Downregulation of lncRNA RPLP0P2 inhibits cell proliferation, invasion and migration, and promotes apoptosis in colorectal cancer

Recent studies have revealed that long noncoding RNAs (lncRNAs) are closely associated with colorectal cancer (CRC); however, the role of the lncRNA RPLP0P2 in CRC remains largely unknown. In the present study, RNA expression profiles of CRC were collected from The Cancer Genome Atlas database and the prognosis of CRC with respect to RPLP0P2 was assessed. Subsequently, RPLP0P2 expression was knocked down in the human CRC cell line RKO using a short hairpin RNA (shRNA) lentivirus, and the biological behaviors of the cells, such as proliferation, migration, cell cycle progression and apoptosis, were examined. The results demonstrated that the expression levels of RPLP0P2 were higher in CRC tissue compared with those in normal tissue, and RPLP0P2 was associated with prognosis. RPLP0P2 knockdown significantly decreased cell colony formation, migration and invasion, and arrested CRC cells in the S phase to G₂/M phase transition. Furthermore, apoptosis was significantly increased in CRC cells infected with the RPLP0P2 shRNA lentivirus compared with in the control group. In conclusion, RPLP0P2 may promote proliferation, invasion and migration, and inhibit apoptosis of CRC cells, suggesting that RPLP0P2 may function as an oncogene in CRC.

Identification of a metabolic-related gene signature predicting the overall survival for patients with stomach adenocarcinoma

Background

The reprogramming of energy metabolism and consistently altered metabolic genes are new features of cancer, and their prognostic roles remain to be further studied in stomach adenocarcinoma (STAD).

Methods

Messenger RNA (mRNA) expression profiles and clinicopathological data were downloaded from The Cancer Genome Atlas (TCGA) and the GSE84437 databases from the Gene Expression Omnibus (GEO) database. A univariate Cox regression analysis and the least absolute shrinkage and selection operator (LASSO) Cox regression model established a novel metabolic signature based on TCGA. The area under the receiver operating characteristic (ROC) curve (AUROC) and a nomogram were calculated to assess the predictive accuracy.

Results

A novel metabolic-related signature (including acylphosphatase 1, RNA polymerase I subunit A, retinol dehydrogenase 12, 5-oxoprolinase, ATP-hydrolyzing, malic enzyme 1, nicotinamide N-methyltransferase, gamma-glutamyl transferase 5, deoxycytidine kinase, galactosidase alpha, DNA polymerase delta 3, glutathione S-transferase alpha 2, N-acyl sphingosine amidohydrolase 1, and N-acyl sphingosine amidohydrolase 1) was identified. In both TCGA and GSE84437, patients in the high-risk group showed significantly poorersurvival than the patients in the low-risk group. A good predictive value was shown by the AUROC and nomogram. Furthermore, gene set enrichment analyses (GSEAs) revealed several significantly enriched pathways, which may help in explaining the underlying mechanisms.

Conclusions

A novel robust metabolic-related signature for STAD prognosis prediction was conducted. The signature may reflect the dysregulated metabolic microenvironment and can provided potential biomarkers for metabolic therapy in STAD.

Integrated analysis of competing endogenous RNA in esophageal carcinoma

Background

The Competing endogenous RNA (CeRNA) network plays important roles in the development and progression of multiple human cancers. Increasing attention has been paid to CeRNA in esophageal carcinoma (ESCA).

Methods

We explored The Cancer Genome Atlas (TCGA) database and then analyzed the RNAs of 142 samples to obtain long non-coding RNAs (lncRNAs), micro RNAs (miRNAs), and messenger RNAs (mRNAs) with different expression trends alongside the progress of ESCA. A series test of cluster (STC) analysis was carried out to identify a set of unique model expression tendencies. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were used to validate the function of key genes that were obtained from the STC analysis.

Results

Through our analysis, 272 lncRNAs, 87 miRNAs, and 692 mRNAs showed upward expression or downward expression trends, and these molecules were tightly involved in cell cycle, pathways in cancer, metabolic processes, and protein phosphorylation, among others. Ultimately, we constructed a CeRNA network containing a total of 71 lncRNAs, 56 miRNAs, and 125 mRNAs. The overall survival (OS) was analyzed using univariate Cox regression analysis to clarify the relationship between these key molecules from the CeRNA network and the prognosis of ESCA patients. Through survival analysis, we finally screened out two lncRNAs (DLEU2, RP11-890B15.3), three miRNAs (miR-26b-3p, miR-92a-3p, miR-324-5p), and one mRNA (SIK2) as crucial prognostic factors for ESCA.

Conclusions

The novel CeRNA network that we constructed will provide new novel prognostic biomarkers and therapeutic targets for patients with ESCA.

Long Non-Coding RNA FOXD2-AS1 Serves as a Potential Prognostic Biomarker for Patients With Cancer: A Meta-Analysis and Database Testing

BACKGROUND

The aim of this study is to summarize the current findings concerning the FOXD2-AS1 expression and cancer prognosis.

METHODS

The correlation intensity between FOXD2-AS1 expression and cancer prognosis was estimated using pooled hazard ratio (HRs) with 95% confidence intervals (CIs). GEPIA was used to assess disease-free survival (DFS), progression-free survival (PFS) and overall survival (OS) of cancer patients and differential FOXD2-AS1 expression in cancer and adjacent tissues.

RESULTS

A total of 11 studies including 2,177 patients with OS and 477 patients with DFS/PFS data were analyzed in evidence synthesis. Overall, the pooled analysis indicated that FOXD2-AS1 expression was significantly associated with OS (HR=1.51, 95%Cl: 1.26-1.81, P<0.001) and DFS (HR=1.66, 95%CI: 1.34-2.04, P<0.001). Subgroup analysis showed that high expression of FOXD2-AS1 was significant correlated with poor OS in the median (HR=1.51, 95%CI: 1.30-1.75, P<0.001) and normal group (HR=1.50, 95%CI: 1.09-2.05, 0.01) based on cut-off value, and high FOXD2-AS1 expression was significant linked with poor DFS in patients with digestive tract cancer (DTC) (HR=1.66, 95%CI: 1.34-2.04, P<0.001). Similarly, a significant correlation between increased FOXD2-AS1 expression and poor PFS with other cancers (HR=3.84, 95%CI 1.26-11.70, P=0.02) was found. In database testing, a highly significant correlation was observed between high expression of FOXD2-AS1 and poor OS (HR=1.9, P<0.001), but not DFS (HR=1.0, P=0.900).

CONCLUSIONS

Our findings indicated that FOXD2-AS1 may serve as a potential independent prognostic factor in cancer, especially in the Chinese population.

Comprehensive RNA expression profile of therapeutic adipose‑derived mesenchymal stem cells co‑cultured with degenerative nucleus pulposus cells

Stem cell-based therapy is a promising alternative to conventional approaches to treating intervertebral disc degeneration (IDD). However, comprehensive understanding of stem cell-based therapy at the gene level is still lacking. In the present study, we identified the expression profiles of messenger RNAs (mRNAs) and long non-coding RNAs (lncRNAs) expressed within a co-culture system of adipose-derived mesenchymal stem cells (ASCs) and degenerative nucleus pulposus cells (NPCs) and explored the signaling pathways involved and their regulatory networks. Microarray analysis was used to compare ASCs co-cultured with degenerative NPCs to ASCs cultured alone, and the underlying regulatory pattern, including the signaling pathways and competing endogenous RNA (ceRNA) network, was analyzed with robust bioinformatics methods. The results showed that 360 lncRNAs and 1757 mRNAs were differentially expressed by ASCs, and the microarray results were confirmed by quantitative PCR. Moreover, 589 Gene Ontology terms were upregulated, whereas 661 terms were downregulated. A total of 299 signaling pathways were significantly altered. A Path-net and a Signal-net were built to show interactions among differentially expressed genes. An mRNA-lncRNA co-expression network was constructed to reveal the interplay among differentially expressed mRNAs and lncRNAs, whereas a ceRNA network was built to investigate their connections with microRNAs involved in IDD. To the best of our knowledge, this original and comprehensive exploration reveals differentially expressed lncRNAs and mRNAs of ASCs stimulated by degenerative NPCs, underscoring the regulation pattern within the co-culture system at the gene level. These data may further understanding of NPC-directed differentiation of ASCs and facilitate the application of ASCs in future treatments for IDD.

Comprehensive landscape of epigenetic-dysregulated lncRNAs reveals a profound role of enhancers in carcinogenesis in BC subtypes

Aberrant expression of long non-coding RNAs (lncRNA) is associated with altered DNA methylation and histone modifications during carcinogenesis. However, identifying epigenetically dysregulated lncRNAs and characterizing their functional mechanisms in different cancer subtypes are still major challenges for cancer studies. In this study, we systematically analyzed the epigenetic alterations of lncRNAs at important regulatory elements in three breast cancer subtypes. We identified 87, 691, and 1,197 epigenetically dysregulated lncRNAs in luminal, basal, and claudin-low subtypes of breast cancer, respectively. The landscape of epigenetically dysregulated lncRNAs at enhancer elements revealed that epigenetic changes of the majority of lncRNAs occurred in a subtype-specific manner and contributed to subtype-specific biological functions. We identified six acetylation of lysine 27 on histone H3 (H3K27ac)-dysregulated lncRNAs and three DNA methylation-dysregulated lncRNAs (CTC-303L1.2, RP11-738B7.1, and SLC26A4-AS1) as prognostic biomarkers of basal subtype. These lncRNAs were involved in immune response-related biological functions. Treatment of the basal breast cancer cell line MDA-MB-468 with CREBBP/EP300 bromodomain inhibitors downregulated H3K27 acetylation levels and caused a decrease in the expression of five H3K27ac-dysregulated lncRNAs (LINC00393, KB-1836B5.1, RP1-140K8.5, AC005162.1, and AC020916.2) and inhibition of the growth of breast cancer cells. One epigenetically dysregulated lncRNA (LINC01983) and four lncRNA regulators (UCA1, RP11-221J22.2, RP11-221J22.1, and RP1-212P9.3) were identified as prognostic biomarkers of the luminal molecular subtype of breast cancer by controlling the tumor necrosis factor (TNF) signaling pathway, T helper (Th)17 cell differentiation, and T cell migration. Finally, our results highlighted a profound role of enhancer-related H3K27ac-dysregulated lncRNAs, DNA methylation-dysregulated lncRNAs, and lncRNA regulators in breast cancer subtype carcinogenesis and their potential prognostic value.

A Competing Endogenous RNA Network and an 8-lncRNA Prognostic Signature Identify MYO16-AS1 as an Oncogenic lncRNA in Bladder Cancer

Recently, growing evidence has shed light on the competitive endogenous RNAs (ceRNAs) activity of long noncoding RNAs (lncRNAs) in carcinogenesis and tumor progression. To better elucidate the regulatory mechanisms of lncRNA in muscle-invasive bladder cancer (MIBC), we identified aberrantly expressed mRNAs, lncRNAs, and miRNAs in tumor tissues by using RNA sequence profiles from The Cancer Genome Atlas. The MIBC-specific ceRNA network, including 58 lncRNAs, 22 miRNAs, and 52 mRNAs, was constructed and visualized in Cytoscape. Further, using the univariate and multivariate Cox regression model, we screened 8 lncRNAs (AC078778.1, LINC00525, AC008676.1, AP000553.1, SACS-AS1, AC009065.1, AC127496.3, and MYO16-AS1) to construct an lncRNA signature for predicting the overall survival of MIBC patients. Kaplan-Meier analysis and a receiver operating characteristic curve were applied to evaluate the performance of the signature. Real-time quantitative PCR analysis was carried out to test expression levels of the 8 lncRNAs in MIBC patient tissues. Transwell assays demonstrated that overexpressing MYO16-AS1 can enhance UMUC2 migration and invasion. Our study offers a novel lncRNA-correlated ceRNA model to better understand the molecular mechanisms involved in MIBC. In addition, we developed an independent 8-lncRNAs biomarker for prognostic prediction and identified MYO16-AS1 as an oncogenic lncRNA in bladder cancer.

Long Noncoding RNA TINCR-Mediated Regulation of Acetyl-CoA Metabolism Promotes Nasopharyngeal Carcinoma Progression and Chemoresistance

Frontier evidence suggests that dysregulation of long noncoding RNAs (lncRNA) is ubiquitous in all human tumors, indicating that lncRNAs might have essential roles in tumorigenesis. Therefore, an in-depth study of the roles of lncRNA in nasopharyngeal carcinoma (NPC) carcinogenesis might be helpful to provide novel therapeutic targets. Here we report that lncRNA TINCR was significantly upregulated in NPC and was associated positively with poor survival. Silencing TINCR inhibited NPC progression and cisplatin resistance. Mechanistically, TINCR bound ACLY and protected it from ubiquitin degradation to maintain total cellular acetyl-CoA levels. Accumulation of cellular acetyl-CoA promoted de novo lipid biosynthesis and histone H3K27 acetylation, which ultimately regulated the peptidyl arginine deiminase 1 (PADI1)-MAPK-MMP2/9 pathway. In addition, insulin-like growth factor 2 mRNA-binding protein 3 interacted with TINCR and slowed its decay, which partially accounted for TINCR upregulation in NPC. These findings demonstrate that TINCR acts as a crucial driver of NPC progression and chemoresistance and highlights the newly identified TINCR-ACLY-PADI1-MAPK-MMP2/9 axis as a potential therapeutic target in NPC. SIGNIFICANCE: TINCR-mediated regulation of a PADI1-MAPK-MMP2/9 signaling pathway plays a critical role in NPC progression and chemoresistance, marking TINCR as a viable therapeutic target in this disease.

Long non coding RNA SLC26A4-AS1 exerts antiangiogenic effects in human glioma by upregulating NPTX1 via NFKB1 transcriptional factor

Malignant gliomas are a heterogeneous group of brain tumors with a poor prognosis, which is largely due to its aggressive invasiveness and angiogenesis. In recent years, it has been found that multiple long noncoding RNAs (lncRNAs) participate in a wide range of biological functions including angiogenesis through the regulation of gene expression in cancers. In this study, we investigate and report the novel role of lncRNA SLC26A4-AS1 in gliomas, with a novel mechanism involving transcription factors NFKB1 and NPTX1. We determined that SLC26A4-AS1 was downregulated in human glioma tissues and cells. Furthermore, overexpression of SLC26A4-AS1 or NPTX1 restrained the aggressiveness of glioma cells and their pro-angiogenic ability. SLC26A4-AS1 was also found to upregulate NPTX1 by recruiting NFKB1 into the NPTX1 promoter. Moreover, silencing of either NPTX1 or NFKB1 restored the aggressive and pro-angiogenic properties of glioma cells in the presence of SLC26A4-AS1. Taken together, we demonstrate that SLC26A4-AS1 promotes NPTX1 transcriptional activity by recruiting NFKB1 and thus exerting antiangiogenic effects on glioma cells. This study provides an experimental basis for the intervention of SLC26A4-AS1 in the treatment of gliomas.

AI Techniques for COVID-19

Artificial Intelligence (AI) intent is to facilitate human limits. It is getting a standpoint on human administrations, filled by the growing availability of restorative clinical data and quick progression of insightful strategies. Motivated by the need to highlight the need for employing AI in battling the COVID-19 Crisis, this survey summarizes the current state of AI applications in clinical administrations while battling COVID-19. Furthermore, we highlight the application of Big Data while understanding this virus. We also overview various intelligence techniques and methods that can be applied to various types of medical information-based pandemic. We classify the existing AI techniques in clinical data analysis, including neural systems, classical SVM, and edge significant learning. Also, an emphasis has been made on regions that utilize AI-oriented cloud computing in combating various similar viruses to COVID-19. This survey study is an attempt to benefit medical practitioners and medical researchers in overpowering their faced difficulties while handling COVID-19 big data. The investigated techniques put forth advances in medical data analysis with an exactness of up to 90%. We further end up with a detailed discussion about how AI implementation can be a huge advantage in combating various similar viruses.

Long noncoding RNA FOXD2-AS1 aggravates hepatocellular carcinoma tumorigenesis by regulating the miR-206/MAP3K1 axis

LncRNAs play crucial roles in the development of various cancers including hepatocellular carcinoma (HCC). Nevertheless, the function of the long noncoding RNA (lncRNA) FOXD2‐AS1 in HCC is still poorly understood. In this study, we focused on the role of FOXD2‐AS1 in HCC. We found that FOXD2‐AS1 was significantly upregulated in HCC cells in comparison to normal human liver cells, LO2. In this study, we also demonstrated that miR‐206 expression was greatly reduced in HCC cells. Furthermore, the inhibition of FOXD2‐AS1 repressed HCC cell proliferation, enhanced cell apoptosis, and restrained cell invasion and migration. The knockdown of FOXD2‐AS1 elevated miR‐206 expression, and we validated an interaction between these RNAs. Additionally, miR‐206 mimics inhibited HCC development while miR‐206 mimics had the opposite effect. MAP kinase 1 (MAP3K1) was predicted to be a target of miR‐206. We discovered that FOXD2‐AS1 modulated MAP3K1 expression by sponging miR‐206 in MHCC‐97L and HepG2 cells. Finally, our in vivo experiments validated that the knockdown of FOXD2‐AS1 inhibited HCC progression by modulating the miR‐206/MAP3K1 axis. In conclusion, this work implies FOXD2‐AS1 accelerates HCC progression through sponging miR‐206 and regulating MAP3K1 expression.

Gastric cancer risk-scoring system based on analysis of a competing endogenous RNA network

Background

Long noncoding RNAs (lncRNAs) can play vital roles in tumor initiation, progression, invasion, and metastasis. However, the functional role of the lncRNA-based competing endogenous RNA (ceRNA) networks in gastric cancer (GC) is still unclear. We aimed to identify novel lncRNAs and their association with GC prognosis.

Methods

The lncRNA, miRNA, and mRNA expression profiles of GC patients data were obtained from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) were identified using the edge-R package. Then, the relationship among lncRNAs-miRNAs-mRNAs was integrated into a constructed ceRNA network with Cytoscape software. Using Cox regression analysis, a risk score system based on DEGs associated with patient prognosis in GC was established. Finally, a nomogram was founded to predict the prognosis of GC patients.

Results

A total of 971 differentially expressed lncRNAs (DElncRNAs), 144 differentially expressed miRNAs (DEmiRNAs) and 2,789 differentially expressed mRNAs (DEmRNAs) were identified and found to be associated with GC risk. Using the bioinformatics method, a ceRNA network involving 62 DElncRNAs, 21 DEmiRNAs and 59 DEmRNAs was constructed. Based on the results of the Cox regression analysis, a risk-scoring system involving 3 lncRNAs (i.e., ADAMTS9-AS1, C15orf54, and AL391152.1) was set up for the survival analysis of GC patients. The area under the receiver operating characteristic (ROC) curve for the risk-scoring system was 0.674, with a C-index of 0.64 [95% confidence interval (CI): 0.59–0.69, P=2.806485e−08]. Univariate and multivariate Cox regression analyses demonstrated that the risk-scoring system was an independent prognostic factor for GC. The risk-scoring system is positively associated with advanced tumor grade. The expression of these 3 lncRNAs were validated in GEPIA database. A nomogram based on these 3 lncRNAs was created to predict the prognosis of GC patients.

Conclusions

Our study established a novel lncRNA-expression-based ceRNA network and an ADAMTS9-AS1-C15orf54-AL391152.1-based risk-scoring system, which can be used to predict the prognosis of GC patients.

Identifying Significant Metabolic Pathways Using Multi-Block Partial Least-Squares Analysis

In metabolomics, identification of metabolic pathways altered by disease, genetics, or environmental perturbations is crucial to uncover the underlying biological mechanisms. A number of pathway analysis methods are currently available, which are generally based on equal-probability, topological-centrality, or model-separability methods. In brief, prior identification of significant metabolites is needed for the first two types of methods, while each pathway is modeled separately in the model-separability-based methods. In these methods, interactions between metabolic pathways are not taken into consideration. The current study aims to develop a novel metabolic pathway identification method based on multi-block partial least squares (MB-PLS) analysis by including all pathways into a global model to facilitate biological interpretation. The detected metabolites are first assigned to pathway blocks based on their roles in metabolism as defined by the KEGG pathway database. The metabolite intensity or concentration data matrix is then reconstructed as data blocks according to the metabolite subsets. Then, a MB-PLS model is built on these data blocks. A new metric, named the pathway importance in projection (PIP), is proposed for evaluation of the significance of each metabolic pathway for group separation. A simulated dataset was generated by imposing artificial perturbation on four pre-defined pathways of the healthy control group of a colorectal cancer study. Performance of the proposed method was evaluated and compared with seven other commonly used methods using both an actual metabolomics dataset and the simulated dataset. For the real metabolomics dataset, most of the significant pathways identified by the proposed method were found to be consistent with the published literature. For the simulated dataset, the significant pathways identified by the proposed method are highly consistent with the pre-defined pathways. The experimental results demonstrate that the proposed method is effective for identification of significant metabolic pathways, which may facilitate biological interpretation of metabolomics data.

Inhibiting SLC26A4 reverses cardiac hypertrophy in H9C2 cells and in rats

Background

It has been confirmed that mutations in solute carrier family 26 member 4 (SLC26A4) contribute to pendred syndrome. However, the role of SLC26A4 in cardiac hypertrophy and the signaling pathways remain unclear.

Methods

Cardiomyocytes were treated by 200 µM phenylephrine (PE) to induce cardiac hypertrophy. Also, the expression of SLC26A4, GSK3, cardiac hypertrophy markers including atrial natriuretic peptide (ANP) and brain natriuretic peptide (BNP) was detected through real-time quantitative polymerase chain reaction (RT-qPCR). Flow cytometry assay was used to test the apoptosis of PE-induced cardiomyocytes transfected by small interfere RNA (siRNA)-SLC26A4. Furthermore, we detected the expression of autophagy-related markers including light chain 3 (LC3) and P62. Finally, we established a rat model of abdominal aortic constriction (AAC)-induced cardiac hypertrophy in vivo.

Results

RT-qPCR results showed that the mRNA expression of SLC26A4 was significantly up-regulated in PE-induced cardiac hypertrophy. After inhibiting SLC26A4, the release of ANP and BNP was significantly decreased and GSK3β was elevated in vivo and in vitro. Furthermore, inhibiting SLC26A4 promoted apoptosis of cardiac hypertrophy cells. In addition, LC3 was down-regulated and P62 was enhanced after transfection of siRNA-SLC26A4.

Conclusion

Our findings revealed that SLC26A4 increases cardiac hypertrophy, and inhibiting SLC26A4 could decrease the release of ANP/BNP and promote the expression of GSK-3β in vitro and in vivo. Moreover, SLC26A4 silencing inhibits autophagy of cardiomyocytes and induces apoptosis of cardiomyocytes. Therefore, SLC26A4 possesses potential value to be a therapeutic target of cardiac hypertrophy, and our study provides new insights into the mechanisms of cardiac hypertrophy.

Large-scale analyses identify a cluster of novel long noncoding RNAs as potential competitive endogenous RNAs in progression of hepatocellular carcinoma

The abnormal expression of noncoding RNAs has attracted increasing interest in the field of hepatocellular carcinoma progression. However, the underlying molecular mechanisms mediated by noncoding RNAs in these processes are unclear. Here, we obtained the expression profiles of long noncoding RNAs, microRNAs, and mRNAs from the Gene Expression Omnibus database and identified hepatocarcinogenesis-specific differentially expressed transcripts. Next, we identified significant Gene Ontology and pathway terms that the differentially expressed transcripts involved in. Using functional analysis and target prediction, we constructed a hepatocellular carcinoma-associated deregulated competitive endogenous RNA network to reveal the potential mechanisms underlying tumor progression. By analyzing The Cancer Genome Atlas dataset, six key long noncoding RNAs showed significant association with overall survival as well as strong correlation with some microRNAs and mRNAs in the competitive endogenous RNA network. We further validated the above results and determined their diagnostic and prognostic value in clinical samples. Importantly, by large-scale analyses, we identified a cluster of long noncoding RNAs, GBAP1, MCM3AP-AS1, SLC16A1-AS1, C3P1, DIO3OS, and HNF4A-AS1 as candidate biomarkers for the diagnosis and prognosis of hepatocellular carcinoma, which will improve our understanding of competitive endogenous RNA-mediated regulatory mechanisms underlying hepatocellular carcinoma development and will provide novel therapeutic targets in the future.

Long Noncoding RNA UCA1 Regulates PRL-3 Expression by Sponging MicroRNA-495 to Promote the Progression of Gastric Cancer

Gastric cancer (GC) is among the most frequently occurring malignancies worldwide. In recent years, long noncoding RNAs (lncRNAs) have been widely studied because of their ability to regulate the cellular processes involved with tumorigenesis. The present study aims to investigate the underlying molecular mechanism by which lncRNA urothelial carcinoma-associated 1 (UCA1) influences the progression of GC. Differentially expressed lncRNA UCA1 was initially identified by microarray-based analysis, after which a high expression of UCA1 was determined in GC tissues and cells. It is important to note that UCA1 could upregulate the expression of phosphatase of regenerating liver-3 (PRL-3) by sponging miR-495. The expression of UCA1 and miR-495 was altered in human GC cells to evaluate cell activity in vitro, as well as peritoneal metastasis and tumor formation ability in vivo. Results suggested that increased expression of UCA1 promoted cell proliferation, migration, and invasion, accompanied by suppressed cell apoptosis, as well as enhanced peritoneal metastasis and tumorigenesis of GC cells. Meanwhile, the upregulated expression of miR-495 could reverse the promotive effects exerted by UCA1. Taken conjointly, UCA1, as a competing endogenous RNA (ceRNA) of miR-495, could accelerate the development of GC by upregulating PRL-3, highlighting a potentially promising basis for the targeted intervention treatment of GC.

Differentially expressed long noncoding RNAs and regulatory mechanism of LINC02407 in human gastric adenocarcinoma

BACKGROUND

Long noncoding RNAs (lncRNAs) have been identified to play important roles in the development and progression of various tumors, including gastric cancer (GC). However, the molecular role of lncRNAs in GC progression remains unclear.

AIM

To investigate the differential expression of lncRNAs in human GC and elucidate the function and regulatory mechanism of LINC02407.

METHODS

The Cancer Genome Atlas database was used to investigate the involvement of lncRNAs in GC. Quantitative real-time polymerase chain reaction was used to estimate the relative expression level of LINC02407 in GC tissues and cells. Functional experiments including CCK8 assay, apoptosis assay, wound healing assay, and transwell assay were used to investigate the effect of LINC02407 on GC cells. Some microRNAs were predicted and verified via bioinformatics analysis and the luciferase reporter system. Predictive analysis and Western blot assay were used to analyze the expression of related proteins.

RESULTS

Many differentially expressed lncRNAs were identified in GC, and some of them including LINC02407 can affect the survival. LINC02407 was upregulated in tumor tissues compared with adjacent tissues. HGC-27 cells showed the highest LINC02407 expression and HaCaT cells exhibited the lowest expression. Different experiment groups were constructed using LINC02407 overexpressing plasmids and related siRNAs. The results of functional experiments showed that LINC02407 can promote the proliferation, migration, and invasion of GC cells but inhibit apoptosis. Luciferase reporter assay showed that hsa-miR-6845-5p and hsa-miR-4455 was downstream regulated by LINC02407. Western blot analysis showed that adhesion G protein-coupled receptor D1 (ADGRD1) was regulated by the LINC02407-miR-6845-5p/miR-4455-ADGRD1 pathways.

CONCLUSION

LINC02407 plays a role in GC through the LINC02407-miR-6845-5p/miR-4455-ADGRD1 pathways, and thus, it may be an important oncogene and has potential value in GC diagnosis and treatment.

Construction of a Competitive Endogenous RNA Network and Identification of Potential Regulatory Axis in Gastric Cancer

Background: Increasing studies has found that long non-coding RNAs (lncRNAs) play critical roles in carcinogenesis, but the underlying mechanisms remain unclear. The aim of this study is to construct a competitive endogenous RNA (ceRNA) network and to identify potential regulatory axis in gastric cancer (GC).

Methods: Differentially expressed (DE) mRNAs, miRNAs, and lncRNAs were obtained by analyzing the RNA expression profiles of stomach adenocarcinoma (STAD) retrieved from The Cancer Genome Atlas (TCGA) database. The lncRNA-miRNA-mRNA regulatory networks of GC were constructed by comprehensive bioinformatics methods including functional annotation, RNA-RNA interactomes prediction, correlation analysis, and survival analysis. The interactions and correlations among ceRNAs were validated by experiments on cancer tissues and cell lines.

Results: A total of 41 lncRNAs, 9 miRNAs, and 10 mRNAs were identified and selected to establish the ceRNA regulatory network of GC. Several ceRNA regulatory axes, which consist of 18 lncRNAs, 4 miRNAs, and 6 mRNAs, were obtained from the network. A potential ADAMTS9-AS2/miR-372/CADM2 axis which perfectly conformed to the ceRNA theory was further analyzed. qRT-PCR showed that ADAMTS9-AS2 knockdown remarkably increased miR-372 expression but reduced CADM2 expression, whereas ADAMTS9-AS2 overexpression had the opposite effects. Dual luciferase reporter assay indicated that miR-372 could bound to the ADAMTS9-AS2 and the 3′UTR of CADM2.

Conclusion: The constructed novel ceRNA network and the potential regulatory axes might provide a novel approach of the exploring the potential mechanisms of development in GC. The ADAMTS9-AS2/miR-372/CADM2 could act as a promising target for GC treatment.

UCA1 long non-coding RNA: An update on its roles in malignant behavior of cancers

The lncRNA urothelial carcinoma-associated 1 (UCA1) is a 1.4 kb long transcript which has been firstly recognized in human bladder cancer cell line. Subsequent studies revealed its over-expression in a wide array of human cancer cell lines and patients' samples. In addition to conferring malignant phenotype to cells, it enhances resistance to conventional anti-cancer drugs. Moreover, transcript levels of this lncRNA have been regarded as diagnostic markers in several cancer types including gastric, bladder and liver cancers. The underlying mechanism of its participation in carcinogenesis has been identified in some cancer types. Sponging tumor suppressor miRNAs, interacting with cancer-promoting signaling pathways and enhancing cell cycle progression are among these mechanisms. Although few studies have shown anti-carcinogenic properties for this lncRNA, the bulk of evidence supports its oncogenic roles. In the current study, we have reviewed the current literature on the role of UCA1 in the carcinogenic process based on the results of in vitro studies, investigations in animal models and assessment of UCA1 expression in clinical samples.

Cancer-related long noncoding RNAs show aberrant expression profiles and competing endogenous RNA potential in esophageal adenocarcinoma

Long non-coding RNAs (lncRNAs) govern gene expression by competitively binding to microRNA response elements (MREs). Although they were initially considered as transcriptional noise, lncRNAs have attracted increased attention in oncology. Dysregulation of lncRNAs occurs in various types of human tumor, including esophageal adenocarcinoma (EAC). However, the functions of these cancer-associated lncRNAs and of their related competitive endogenous RNA (ceRNA) network in EAC remains unknown. To determine the relevant potential mechanisms, the present study analyzed the transcriptome sequencing data and clinical information of 79 patients with EAC, including 79 tumor samples and 11 normal samples, which were obtained from The Cancer Genome Atlas esophageal cancer project. The edgeR v3.25.0 software was used for differential gene expression analysis. The results exhibited 561 cancer-associated lncRNAs with a >2.0-fold change and a false discovery rate-adjusted P<0.01. Among these lncRNAs, 26 were significantly associated with patient overall survival. According to data from bioinformatics databases and differentially expressed RNAs, an lncRNA-regulated ceRNA network for EAC was constructed. The results demonstrated that the aberrantly expressed lncRNA-associated ceRNA network included 37 EAC cancer-associated lncRNAs, five miRNAs and 13 mRNAs. In conclusion, the present study identified novel lncRNAs as candidate prognostic biomarkers and revealed a potential regulatory network of gene expression in EAC.

Genome-wide analysis of long noncoding RNAs, microRNAs, and mRNAs forming a competing endogenous RNA network in repeated implantation failure

Repeated implantation failure (RIF) was mainly due to poor endometrium receptivity. Long noncoding RNAs (lncRNAs) could regulate endometrium receptivity and act in competing endogenous RNA (ceRNA) theory. However, the regulatory mechanism of the lncRNA-miRNA-mRNA network in repeated implantation failure (RIF) is unclear. We obtained RIF-related expression profiles of lncRNAs, mRNAs, and miRNAs using mid-secretory endometrial tissue samples from 5 women with RIF and 5 controls by RNA-sequencing. Co-expression analysis revealed that three functional modules were enriched in immune response/inflammation process; two functional modules were enriched in metabolic/ biosynthetic process, and one functional module were enriched in cell cycle pathway. By adding the miRNA data, ceRNA regulatory relationship of each module was reconstructed. The ceRNA network of the whole differentially expressed RNAs revealed 10 hub lncRNAs. Among them, TRG-AS1, SIMM25, and NEAT1 were involved in the module1, module2, and module3, respectively; LNC00511 and SLC26A4-AS1 in the module4; H19 in the module5. The real-time polymerase chain reaction (RT-PCR) results of 15 randomly selected RNAs were consistent with our sequencing data. These can be used as novel potential biomarkers for RIF. Furthermore, they might be involved in endometrium receptivity by acting as ceRNA.

lncRNA FOXD2-AS1 confers cisplatin resistance of non-small-cell lung cancer via regulation of miR185-5p-SIX1 axis

Background: Chemoresistance is a major obstacle for chemotherapy failure in non-small-cell lung cancer (NSCLC). lncRNAs are a class of pivotal regulators in various cancers, and the lncRNA FOXD2-AS1 is implicated in the progression of NSCLC. However, it is still unclear whether it regulates chemosensitivity. Methods: Expression levels of FOXD2-AS1, miR185-5p, and SIX1 mRNA were identified by reverse-transcription qPCR. CCK8 assay was performed to assess cell proliferation and chemosensitivity of cisplatin-resistant A549/DDP and H1299/DDP cells. Colony-forming assay was utilized to detect colony numbers. Cell migration and invasion ability were measured by transwell assay. The protein levels of LRP, Pgp, MRP1, and SIX1 were examined by Western blot assay. The correlation between FOXD2-AS1 and miR185-5p or miR185-5p and SIX1 were validated by bioinformatic, dual-luciferase, and RNA immunoprecipitation assays. Tumor xenografts were constructed to confirm the function and mechanism of FOXD2-AS1 in chemosensitivity of DDP-resistant NSCLC. Results: FOXD2-AS1 and SIX1 were upregulated and miR185-5p downregulated in DDP-resistant NSCLC. Absence of FOXD2-AS1 enhanced drug sensitivity of A549/DDP and H1299/DDP cells, reflected by the reduced colony formation, cell proliferation, migration, invasion, and drug resistance-associated protein expression. FOXD2-AS1 acted as a molecular sponge for miR185-5p and relieved the binding of miR185-5p and its target gene SIX1, leading to the derepression of SIX1 in A549/DDP and H1299/DDP cells. Rescue experiments validated the functional interaction among FOXD2-AS1, miR185-5p, and SIX1. Moreover, FOXD2-AS1 interference receded the growth of DDP-resistant NSCLC tumors in vivo. Conclusion: FOXD2-AS1/miR185-5p/SIX1 regulates the progression and chemosensitivity of DDP-resistant NSCLC, suggesting a potential therapeutic target for cisplatin-resistant NSCLC patients.

Potential diagnostic and prognostic value of plasma long noncoding RNA LINC00086 and miR-214 expression in gastric cancer

BACKGROUND

Plasma carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), and cancer antigen 72-4 (CA72-4) are common markers which are useful in the diagnosis and prognosis of GC. However, their sensitivity and specificity in GC remain unsatisfactory. Identification of cancer diagnosed-biomarkers would be of great value.

OBJECTIVE

Evaluate the diagnostic and prognostic value of LINC00086 and miR-214 in GC.

METHODS

In this study, we determined the expression of LINC00086 and miR-214 in GC by qRT-PCR. Additionally, we investigated the relationship between various clinicopathological features of GC patients and LINC00086 or miR-214 expression, and evaluated the diagnostic and prognostic value of LINC00086 and miR-214 in GC.

RESULTS

In this study, we found that plasma LINC00086 expression was significantly lower, whereas plasma miR-214 expression was significantly higher in GC patients than in normal individuals. LINC00086 and miR-214 exhibited high sensitivity and specificity in diagnosing GC. Additionally, GC patients with low LINC00086 or high miR-214 expression were likely to have larger tumors, lymphatic metastasis, larger TNM stage, and higher CEA and CA19-9 levels. Moreover, GC patients with low LINC00086 or high miR-214 expression showed lower survival rates. Lymphatic metastasis, LINC00086, and miR-214 are independent factors affecting patient diagnosis.

CONCLUSIONS

LINC00086 and miR-214 are potentially diagnostic and prognostic markers for GC.

Role of epigenetics in transformation of inflammation into colorectal cancer

Molecular mechanisms associated with inflammation-promoted tumorigenesis have become an important topic in cancer research. Various abnormal epigenetic changes, including DNA methylation, histone modification, chromatin remodeling, and noncoding RNA regulation, occur during the transformation of chronic inflammation into colorectal cancer (CRC). These changes not only accelerate transformation but also lead to cancer progression and metastasis by activating carcinogenic signaling pathways. The NF-κB and STAT3 signaling pathways play a particularly important role in the transformation of inflammation into CRC, and both are critical to cellular signal transduction and constantly activated in cancer by various abnormal changes including epigenetics. The NF-κB and STAT3 signals contribute to the microenvironment for tumorigenesis through secretion of a large number of pro-inflammatory cytokines and their crosstalk in the nucleus makes it even more difficult to treat CRC. Compared with gene mutation that is irreversible, epigenetic inheritance is reversible or can be altered by the intervention. Therefore, understanding the role of epigenetic inheritance in the inflammation-cancer transformation may elucidate the pathogenesis of CRC and promote the development of innovative drugs targeting transformation to prevent and treat this malignancy. This review summarizes the literature on the roles of epigenetic mechanisms in the occurrence and development of inflammation-induced CRC. Exploring the role of epigenetics in the transformation of inflammation into CRC may help stimulate futures studies on the role of molecular therapy in CRC.

Prognostic value of long non-coding RNA FOXD2-AS1 expression in patients with solid tumors

BACKGROUND

Although increasing evidence has revealed that FOXD2-AS1 overexpression exists in various solid tumors, the value of FOXD2-AS1 as a prognostic marker in such cancers remains uncertain. Accordingly, the present research aimed to assess the association of FOXD2-AS1 with cancer prognosis and predict the biological function of FOXD2-AS1.

METHODS

We systematically retrieved PubMed, PMC, Web of Science, EMBASE and Wiley Online Library databases for eligible articles published up to December 2018. Pooled hazard ratios (HRs) and odds ratios (ORs) with 95% confidence intervals (95%CIs) were calculated to evaluate the correlation of FOXD2-AS1 expression with overall survival (OS), disease free survival (DFS) and clinicopathological characteristics. We also used five Gene Expression Omnibus (GEO) datasets from breast cancer patients to explore the relationship between FOXD2-AS1 expression and prognosis. Finally, we validated FOXD2-AS1 expression in various carcinomas and predicted its biological function based on the public databases.

RESULTS

A total of 13 studies with 2502 tumor patients were included. The pooled HRs demonstrated that FOXD2-AS1 overexpression was significantly associated with unfavorable OS (HR = 1.39, 95%CI: 1.23-1.57, p < 0.001) and DFS (HR = 2.24, 95%CI: 1.55-3.23, p < 0.001) in tumor patients. The pooled ORs indicated that FOXD2-AS1 upregulation was related to large tumor size (OR = 1.53, 95%CI: 1.26-1.85, p < 0.001), deep invasion depth (OR = 1.99, 95%CI: 1.53-2.58, p < 0.001), distant metastasis (OR = 2.03, 95%CI: 1.69-2.43, p < 0.001) and advanced TNM stage (OR = 1.35, 95%CI: 1.06-1.72, p = 0.0150), but not to lymph node metastasis nor differentiation. Moreover, a similar pooled result for the OS of breast cancer patients was obtained (HR = 1.55, 95%CI: 1.14-2.11, p = 0.0052) by analyzing GEO data. Finally, elevated FOXD2-AS1 expression in various solid tumor tissues was verified based on The Cancer Genome Atlas (TCGA) data. Further functional prediction demonstrated that FOXD2-AS1 may participate in some cancer-related pathways.

CONCLUSION

Elevated FOXD2-AS1 expression was associated with poor survival in patients with solid tumors and may serve as a potential prognostic biomarker for a variety of cancers.

Integrated analysis of competing endogenous RNA network revealing potential prognostic biomarkers of hepatocellular carcinoma

Objective: The goal of our study is to identify a competing endogenous RNA (ceRNA) network using dysregulated RNAs between HCC tumors and the adjacent normal liver tissues from The Cancer Genome Atlas (TCGA) datasets, and to investigate underlying prognostic indicators in hepatocellular carcinoma (HCC) patients.

Methods: All of the RNA- and miRNA-sequencing datasets of HCC were obtained from TCGA, and dysregulated RNAs between HCC tumors and the adjacent normal liver tissues were investigated by DESeq and edgeR algorithm. Survival analysis was used to confirm underlying prognostic indicators.

Results: In the present study, we constructed a ceRNA network based on 16 differentially expressed genes (DEGs), 7 differentially expressed microRNAs and 34 differentially expressed long non-coding RNAs (DELs). Among these dysregulated RNAs, three DELs (AP002478.1, HTR2A-AS1, and ERVMER61-1) and six DEGs (enhancer of zeste homolog 2 [EZH2], kinesin family member 23 [KIF23], chromobox 2 [CBX2], centrosomal protein 55 [CEP55], cell division cycle 25A [CDC25A], and claspin [CLSPN]) were used for construct a prognostic signature for HCC overall survival (OS), and performed well in HCC OS (adjusted P<0.0001, adjusted hazard ratio = 2.761, 95% confidence interval = 1.838-4.147). Comprehensive survival analysis demonstrated that this prognostic signature may be act as an independent prognostic indicator of HCC OS. Functional assessment of these dysregulated DEGs in the ceRNA network and gene set enrichment of this prognostic signature suggest that both were enriched in the biological processes and pathways of the cell cycle, cell division and cell proliferation.

Conclusions: Our current study constructed a ceRNA network for HCC, and developed a prognostic signature that may act as an independent indicator for HCC OS.

Identification and development of long non-coding RNA-associated regulatory network in colorectal cancer

Colorectal cancer (CRC) is one of the leading causes of cancer‐associated death globally. Long non‐coding RNAs (lncRNAs) have been identified as micro RNA (miRNA) sponges in a competing endogenous RNA (ceRNA) network and are involved in the regulation of mRNA expression. This study aims to construct a lncRNA‐associated ceRNA network and investigate the prognostic biomarkers in CRC. A total of 38 differentially expressed (DE) lncRNAs, 23 DEmiRNAs and 27 DEmRNAs were identified by analysing the expression profiles of CRC obtained from The Cancer Genome Atlas (TCGA). These RNAs were chosen to develop a ceRNA regulatory network of CRC, which comprised 125 edges. Survival analysis showed that four lncRNAs, six miRNAs and five mRNAs were significantly associated with overall survival. A potential regulatory axis of ADAMTS9‐AS2/miR‐32/PHLPP2 was identified from the network. Experimental validation was performed using clinical samples by quantitative real‐time PCR (qRT‐PCR), which showed that expression of the genes in the axis was associated with clinicopathological features and the correlation among them perfectly conformed to the ‘ceRNA theory’. Overexpression of ADAMTS9‐AS2 in colon cancer cell lines significantly inhibited the miR‐32 expression and promoted PHLPP2 expression, while ADAMTS9‐AS2 knockdown had the opposite effects. The constructed novel ceRNA network may provide a comprehensive understanding of the mechanisms of CRC carcinogenesis. The ADAMTS9‐AS2/miR‐32/PHLPP2 regulatory axis may serve as a potential therapeutic target for CRC.

Analysis of Expression Pattern of snoRNAs in Different Cancer Types with Machine Learning Algorithms

Small nucleolar RNAs (snoRNAs) are a new type of functional small RNAs involved in the chemical modifications of rRNAs, tRNAs, and small nuclear RNAs. It is reported that they play important roles in tumorigenesis via various regulatory modes. snoRNAs can both participate in the regulation of methylation and pseudouridylation and regulate the expression pattern of their host genes. This research investigated the expression pattern of snoRNAs in eight major cancer types in TCGA via several machine learning algorithms. The expression levels of snoRNAs were first analyzed by a powerful feature selection method, Monte Carlo feature selection (MCFS). A feature list and some informative features were accessed. Then, the incremental feature selection (IFS) was applied to the feature list to extract optimal features/snoRNAs, which can make the support vector machine (SVM) yield best performance. The discriminative snoRNAs included HBII-52-14, HBII-336, SNORD123, HBII-85-29, HBII-420, U3, HBI-43, SNORD116, SNORA73B, SCARNA4, HBII-85-20, etc., on which the SVM can provide a Matthew’s correlation coefficient (MCC) of 0.881 for predicting these eight cancer types. On the other hand, the informative features were fed into the Johnson reducer and repeated incremental pruning to produce error reduction (RIPPER) algorithms to generate classification rules, which can clearly show different snoRNAs expression patterns in different cancer types. The analysis results indicated that extracted discriminative snoRNAs can be important for identifying cancer samples in different types and the expression pattern of snoRNAs in different cancer types can be partly uncovered by quantitative recognition rules.