Characterization of long non-coding RNAs and MEF2C-AS1 identified as a novel biomarker in diffuse gastric cancer

The necroptosis-related signature and tumor microenvironment immune characteristics associated with clinical prognosis and drug sensitivity analysis in stomach adenocarcinoma

PURPOSE

Necroptosis plays an important role in the tumorigenesis, development, metastasis, and drug resistance of malignant tumors. This study explored the new model for assessing stomach adenocarcinoma (STAD) prognosis and immunotherapy by combining long noncoding RNAs associated with necroptosis.

METHODS

Patient clinical data and STAD gene expression profiles were curated from The Cancer Genome Atlas (TCGA). Immune-related genes were sourced from a specialized molecular database. Perl software and R software were used for data processing and analysis. Necroptosis-related lncRNAs in STAD were pinpointed via R's correlation algorithms. These lncRNAs, in conjunction with clinical data, informed the construction of a prognostic lncRNA-associated risk score model using univariate and multivariate Cox regression analyses. The model's prognostic capacity was evaluated by Kaplan-Meier survival curves and validated as an independent prognostic variable. Further, a nomogram incorporating this model with clinical parameters was developed, offering refined individual survival predictions. Subsequent analyses of immune infiltration and chemosensitivity within necroptosis-related lncRNA clusters utilized an arsenal of bioinformatic tools, culminating in RT-PCR validation of lncRNA expression.

RESULTS

Through rigorous Cox regression, 21 lncRNAs were implicated in the risk score model. Stratification by median risk scores delineated patients into high- and low-risk cohorts, with the latter demonstrating superior prognostic outcomes. The risk model was corroborated as an independent prognostic indicator for STAD. The integrative nomogram displayed high concordance between predicted and observed survival rates, as evidenced by calibration curves. Differential immune infiltration in risk-defined groups was illuminated by the single sample GSEA (ssGSEA), indicating pronounced immune presence in higher-risk patients. Tumor microenvironment (TME) analysis showed that cluster-C3 had the highest score in the analysis of the three TMEs. Through the differential analysis of immune checkpoints, it was found that almost all immune checkpoint-related genes were expressed differently in various tumor clusters. Among them, CD44 expression was the highest. By comparing all drug sensitivities, we screened out 29 drugs with differences in drug sensitivity across different clusters. Risk score gene expression identification results showed that these lncRNAs were abnormally expressed in gastric cancer cell lines.

CONCLUSIONS

This investigation provides a robust methodological advance in prognosticating and personalizing immunotherapy for STAD, leveraging quantitatively derived tumor cluster risk scores. It posits the use of necroptosis-related lncRNAs as pivotal molecular beacons for guiding therapeutic strategies and enhancing clinical outcomes in STAD.

Comprehensive Analysis of Disulfidptosis-Related LncRNAs in Molecular Classification, Immune Microenvironment Characterization and Prognosis of Gastric Cancer

BACKGROUND

Disulfidptosis is a novel form of programmed cell death that unveils promising avenues for the exploration of tumor treatment modalities. Gastric cancer (GC) is a malignant tumor characterized by high incidence and mortality rate. However, there has been no systematic study of disulfidptosis-related long noncoding RNAs (DRLs) signature in GC patients.

METHODS

The lncRNA expression profiles containing 412 GC samples were acquired from the Cancer Genome Atlas (TCGA) database. Differential expression analysis was performed alongside Pearson correlation analysis to identify DRLs. Prognostically significant DRLs were further screened using univariate COX regression analysis. Subsequently, LASSO regression and multifactorial COX regression analyses were employed to establish a risk signature composed of DRLs that exhibit independent prognostic significance. The predictive value of this risk signature was further validated in a test cohort. The ESTIMATE, CIBERSORT and ssGSEA methodologies were utilized to investigate the tumor immune microenvironment of GC populations with different DRLs profiles. Finally, the correlation between DRLs and various GC drug responses was explored.

RESULTS

We established a prognostic signature comprising 12 disulfidptosis-related lncRNAs (AC110491.1, AL355574.1, RHPN1-AS1, AOAH-IT1, AP001065.3, MEF2C-AS1, AC016394.2, LINC00705, LINC01952, PART1, TNFRSF10A-AS1, LINC01537). The Kaplan-Meier survival analysis revealed that patients in the high-risk group exhibited a poor prognosis. Both univariate and multivariate COX regression models demonstrated that the DRLs signature was an independent prognostic indicator in GC patients. Furthermore, the signature exhibited accurate predictions of survival at 1-, 3- and 5- years with the area under the curve (AUC) values of 0.708, 0.689 and 0.854, respectively. In addition, we also observed significant associations between the DRLs signature and various clinical variables, distinct immune landscape and drug sensitivity profiles in GC patients. The low-risk group patients may be more likely to benefit from immunotherapy and chemotherapy.

CONCLUSIONS

Our study investigated the role and potential clinical implications of DRLs in GC. The risk model constructed by DRLs demonstrated high accuracy in predicting the survival outcomes of GC and improving the treatment efficacy for GC patients.

Long non‑coding RNAs, lipid metabolism and cancer (Review)

Cancer has emerged as the most common cause of death in China. The change in lipid metabolism has been confirmed to have a role in several tumor types, such as esophageal, gastric, colorectal and liver cancer. Cancer cells use lipid metabolism for energy and then rapidly proliferate, invade and migrate. The main pathway by which cancer cell lipid metabolism influences cancer progression is increased fatty acid synthesis. Long non-coding (lnc)RNAs are important ncRNAs that were indicated to have significant roles in the development of human tumors. They are considered potential tumor biomarkers. Increased lipid synthesis or uptake due to deregulation of lncRNAs contributes to rapid tumor growth. In the present review, current studies on the relationship between lncRNAs, lipid metabolism and the occurrence and development of tumors were collated and summarized, and their mechanism of action was discussed. The review is expected to provide a theoretical basis for tumor treatment and prognosis evaluation based on the effective regulation of lncRNAs and lipid metabolism.

MEF2C and miR-194-5p: New Players in Triple Negative Breast Cancer Tumorigenesis

Among breast cancer (BC) subtypes, the most aggressive is triple negative BC (TNBC), which is prone to metastasis. We previously found that microRNA (miR)-194-5p is downregulated at the early stages of TNBC brain metastasis development. Additionally, the transcription factor myocyte enhancer factor 2 (MEF2)C, a bioinformatically predicted miR-194-5p target, was increasingly expressed throughout TNBC brain metastasis formation and disease severity. However, the contributions of these two players to malignant cells' features remain undetermined. This study aimed at disclosing the role of miR-194-5p and MEF2C in TNBC tumorigenesis. The transfection of 4T1 cells with a silencer for MEF2C or with a pre-miRNA for miR-194-5p was employed to study TNBC cells' phenotypic alterations regarding epithelial and mesenchymal markers, as well as migratory capability alterations. MEF2C-silenced cells presented a decline in both vimentin and cytokeratin expression, whereas the overexpression of miR-194-5p promoted an increase in cytokeratin and a reduction in vimentin, reflecting the acquisition of an epithelial phenotype. Both treatments reduced TNBC cells' migration. These results suggest that MEF2C may determine TNBC cells' invasive properties by partially determining the occurrence of epithelial-mesenchymal transition, while the overexpression of miR-194-5p promotes a decline in TNBC cells' aggressive behavior and reinforces this miRNA's role as a tumor suppressor in TNBC.

An exosome-related long non-coding RNAs risk model could predict survival outcomes in patients with breast cancer

Breast cancer (BC) is one of the most frequent malignancies among women worldwide. Accumulating evidence indicates that long non-coding RNA (lncRNA) may affect BC progression. Exosomes, a class of small membrane vesicles, have been reported to promote tumor progression through transporting proteins, mRNAs, lncRNAs and some other small molecules. However, the interaction between exosome-related lncRNAs and the microenvironment of malignancies is unclear. Hence, we proceeded to investigate the relationship between exosome-related lncRNAs and BC microenvironment. 121 exosome-associated genes were extracted from ExoBCD database. Then, the Pearson analysis was used to screened out the exosome-related lncRNAs. After that, 15 exosome-related differentially expressed lncRNAs were identified by the correlation with BC prognosis. According to the sum of the expression of these 15 lncRNAs, extracted from The Cancer Genome Atlas, and the regression coefficients, an exosome-related lncRNAs signature was developed by using Cox regression analysis. With the median risk score of the training set, the patients in training and validation sets were separated to low-risk group and high-risk group. Subsequently, the lncRNA-mRNA co-expression network was constructed. The distinct enrichment pathways were compared among the different risk groups by using the R package clusterProfiler. The ESTIMATE method and ssGESA database were adopted to study the ESTIMATE Score and immune cell infiltration. Eventually, the expression of immune checkpoint associated genes, microsatellite instable and the immunophenoscore were further analyzed between different risk groups. Different risk groups exhibited different prognosis, with lower survival rate in the high-risk group. The differentially expressed genes between the different risk groups were enriched in biological processes pathways as well as immune responses. BC patients in high-risk group were identified with lower scores of ESTIMATE scores. Subsequently, we noticed that the infiltrating levels of aDCs, B cells, CD8+ T cells, iDCs, DCs, Neutrophils, macrophages, NK cells, pDCs, Tfh, T helper cells, TIL and Tregs were obvious elevated with the decreased risk score in training and validation cohorts. And some immune signatures were significantly activated with the decreased risk score in both cohorts. Eventually, the exosome-associated lncRNAs risk model was demonstrated to accurately predict immunotherapy response in patients with BC. The results of our study suggest that exosome-related lncRNAs risk model has close relationship with prognosis and immune cells infiltration in BC patients. These findings could make a great contribution to improving BC immunotherapy.

Hypermethylation of tumor suppressor lncRNA MEF2C-AS1 frequently happened in patients at all stages of colorectal carcinogenesis

Background

The novel long noncoding RNA MEF2C-AS1 has been identified to play suppressor roles during tumorigenesis. DNA methylation has a regulatory effect on gene expression in cancer initiation and progression. However, the methylation status of MEF2C-AS1 and its role in colorectal cancer (CRC) development remain unclear.

Methods

The expression and methylation levels of MEF2C-AS1 were systematically analyzed among 31 cancers with available qualified data in GEPIA and UCSC Xena databases. Then, the MEF2C-AS1 methylation status was firstly examined among 12 CRCs by Illumina Infinium MethylationEPIC BeadChip in in-house step 1 and further quantified among 48 CRCs by the MassARRAY method in in-house step 2. Subsequently, its methylation and expression levels were quantified among 81 non-advanced adenomas (NAAs), 81 advanced adenomas (AAs), and 286 CRCs using the MassARRAY method, and among 34 NAAs, 45 AAs, and 75 CRCs by qRT-PCR, in in-house step 3, respectively. The effect of MEF2C-AS1 methylation on CRC survival was analyzed by the Kaplan–Meier method. Additionally, in vitro cell proliferation, migration and invasion assays, and bioinformatics analysis were performed to explore the role of MEF2C-AS1 in colorectal carcinogenesis.

Results

Lower expression and higher methylation of MEF2C-AS1 were found in CRC by online databases. In the comparisons of lesion tissues with adjacent normal tissues, MEF2C-AS1 hypermethylation of each individual site and mean level was found among CRC patients in in-house step 1 and step 2, more meaningfully, among NAA patients, AA patients, and CRC patients at all stages during colorectal carcinogenesis in in-house step 3 (all p < 0.05). Further comparisons demonstrated significant differences between CRC and NAA (p = 0.025), AA and NAA (p = 0.020). Moreover, MEF2C-AS1 hypermethylation was associated with poorer disease-specific survival of CRC patients (p = 0.044). In addition, hypermethylation and lower expression of MEF2C-AS1 were verified in RKO cells, and the MEF2C-AS1 overexpression significantly suppressed RKO cell proliferation, migration, and invasion.

Conclusions

The findings reveal that MEF2C-AS1 hypermethylation might be an early driven event during colorectal carcinogenesis. It might serve as a promising prognostic biomarker for CRC survival. Our study also indicates the potential tumor-suppressing role of MEF2C-AS1 in CRC.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01328-1.

Comprehensive analysis of lncRNA expression profiles in postmenopausal osteoporosis

To explore the key lncRNAs affecting postmenopausal osteoporosis (PMOP) progression, the transcriptome sequencing of peripheral blood mononuclear cells from fifteen early postmenopausal women, according to bone mineral density, were divided into groups of osteoporosis, osteopenia and normality, in each of which the expression profiles of lncRNAs was investigated. From the results we observed nine candidates of lncRNAs, which were to be compared with miRBase, and found that MIR22HG as one candidate of lncRNA was most likely to be directly used as miRNA precursor. Based on the KEGG annotation and lncRNA-miRNA-mRNA-KEGG network, we analyzed the potential role of candidate lncRNAs. The results showed that the expression profiles of lncRNAs could help identify the novel ones involved in the progression of PMOP, and that MIR22HG could serve as a miRNA precursor to regulate FoxO signaling pathway in bone metabolism. Our findings can be of great help in predicting and diagnosing early PMOP.

Machine Learning-Devised Immune-Related lncRNA Signature Panel Predicts the Prognosis and Immune Landscape in Breast Cancer Novel IRLP Signature in BRCA

Long noncoding RNAs (lncRNAs) actively participate in breast cancer (BRCA) tumorigenesis via epigenetic mechanisms. Our study identified immune-related lncRNA (irlncRNA) pairs and compiled them into a set of noncoding gene signatures able to stratify subtypes of BRCA associated with variable degrees of survival and immune cell infiltration. A 40 immune-related lncRNA pair (IRLP) signature including 43 irlncRNAs was built, with high sensitivity and specificity for the prediction of survival in different molecular subtypes of BRCA. Results demonstrated that the low-risk group showed a significantly longer survival rate, and this novel IRLP signature was highly associated with survival status, T stage, metastatic disease, and overall stage in BRCA. Immune infiltrating analyses found that the low-risk group has a lower expression level of macrophage M2 and a higher expression level of immunosuppressed biomarkers than the high-risk group. DEirlncRNAs were further proven to be significantly related to the MAPK signaling, Jak-STAT signaling, and ErbB signaling pathways in BRCA. In conclusion, the 40 IRLP signature showed a promising clinical prediction value in the prognosis of different molecular subtypes and immunotherapy response in BRCA, and the underlying mechanism for these IRLPs warrants further investigations.

Regulatory Roles of Noncoding RNAs in the Progression of Gastrointestinal Cancers and Health Disparities

Annually, more than a million individuals are diagnosed with gastrointestinal (GI) cancers worldwide. With the advancements in radio- and chemotherapy and surgery, the survival rates for GI cancer patients have improved in recent years. However, the prognosis for advanced-stage GI cancers remains poor. Site-specific GI cancers share a few common risk factors; however, they are largely distinct in their etiologies and descriptive epidemiologic profiles. A large number of mutations or copy number changes associated with carcinogenesis are commonly found in noncoding DNA regions, which transcribe several noncoding RNAs (ncRNAs) that are implicated to regulate cancer initiation, metastasis, and drug resistance. In this review, we summarize the regulatory functions of ncRNAs in GI cancer development, progression, chemoresistance, and health disparities. We also highlight the potential roles of ncRNAs as therapeutic targets and biomarkers, mainly focusing on their ethnicity-/race-specific prognostic value, and discuss the prospects of genome-wide association studies (GWAS) to investigate the contribution of ncRNAs in GI tumorigenesis.

Bioinformatics analysis of potential Key lncRNA-miRNA-mRNA molecules as prognostic markers and important ceRNA axes in gastric cancer

Gastric cancer (GC), the fifth most common malignancy worldwide, has an extremely poor prognosis at the advanced stage or the early stage if inadequately treated. Long noncoding RNAs (lncRNAs), microRNAs (miRNAs) and mRNAs all function as competing endogenous RNAs (ceRNAs) that target and regulate each other. Changes in their expression and their regulatory bioprocesses play important roles in GC. However, the roles of key RNAs and their regulatory networks remain unclear. In this study, RNA profiles were extracted from The Cancer Genome Atlas database, and R language was used to discover the differentially expressed (DE) lncRNAs, miRNAs and mRNAs in GC. Then, the DERNAs were paired by miRcode, miRDB, TargetScan and DIANA, and the ceRNA network was further constructed and visualized using Cytoscape. Moreover, a functional enrichment analysis was performed using Metascape. Afterward, the "survival" package was employed to identify candidate prognostic targets (DERNA-os) in the ceRNA network. Ultimately, the ceRNA network was analyzed to identify crucial lncRNA/miRNA/mRNA axes. Based on 374 gastric adenocarcinoma and gastric adenoma samples, 283 DEceRNAs (69 lncRNAs, 10 miRNAs, and 204 mRNAs) were identified. The 204 mRNAs were significantly enriched in some interesting functional clusters, such as the trans-synaptic signaling cluster and the protein digestion and absorption cluster. The ceRNA network consisted of 43 ceRNAs (13 lncRNAs, 2 miRNAs, and 28 mRNAs) that were related to prognosis. Among them, 2 lncRNAs (LNC00469 and AC010145.1) and 1 mRNA (PRRT4) were potential new biomarkers. In addition, according to the lncRNA/miRNA/mRNA regulatory relationships among the 43 ceRNAs, we identified four axes that might play important roles in the progression of GC and investigated the potential mechanism of the most promising axis (POU6F2-AS2/hsa-mir-137/OPCML) in promoting the proliferation and invasiveness of GC.

LncRNA FENDRR Inhibits Gastric Cancer Cell Proliferation and Invasion via the miR-421/SIRT3/Notch-1 Axis

Objective

This study aimed to investigate the regulatory effect of lncRNA fetal-lethal non-coding developmental regulatory RNA (FENDRR) on gastric cancer (GC) progression.

Methods

The expression levels of FENDRR in GC tissues and paracancerous tissues, as well as in gastric normal epithelial cell line and GC cell lines were detected. The Ad-FENDRR or si-FENDRR was transfected into AGS and SGC-7901 cells, and cell proliferation, invasion and apoptosis were determined. Online bioinformatics database predicted and screened miR-421 as a potential target of FENDRR, and SIRT3 was predicted as a target gene of miR-421. The pcDNA-SIRT3 or si-SIRT3 was transfected into AGS cells, and cell proliferation, invasion, apoptosis and Notch-1 protein expression were determined. Ad-FENDRR was transfected into AGS and SGC-7901 cells alone or together with miR-421 mimic to explore the effect of miR-421 on cells. The AGS cells transfected with Ad-FENDRR were injected into the armpits of nude mice to establish subcutaneous xenograft tumor model, and tumor growth was observed.

Results

FENDRR expression was downregulated in GC tissues and cell lines. Overexpression of FENDRR or SIRT3 inhibited tumor proliferation and invasion, and promoted apoptosis. The overexpression of Notch-1 reversed the inhibitory effect of SIRT3 on AGS cell. MiR-421 mimic reversed the inhibitory effect of FENDRR on the growth of AGS and SGC-7901 cells. Nude mice injected with FENDRR overexpressing AGS cells had smaller tumor volume and weight and weaker tumor cell proliferation ability.

Conclusion

FENDRR inhibits Notch-1 pathway to inhibit GC cell proliferation and invasion by upregulating SIRT3 expression via targeting miR-421.

Development of a novel five-lncRNA prognostic signature for predicting overall survival in elderly patients with breast cancer

Background

Breast cancer (BC) is an age‐related disease. Long noncoding RNAs (lncRNAs) have been proven to be crucial contributors in tumorigenesis. This study aims to develop a novel lncRNA‐based signature to predict elderly BC patients’ prognosis.

Methods

The RNA expression profiles and corresponding clinical information of 182 elderly BC patients were retrieved from The Cancer Genome Atlas (TCGA). Differentially expressed lncRNAs (DElncRNAs) between BC and adjacent normal samples were used to construct the signature in the training set through univariate Cox regression analysis, LASSO regression analysis, and multivariate Cox regression analysis. Kaplan–Meier analysis and time‐dependent receiver operating characteristic (ROC) analysis were used to evaluate the predictive performance. Besides, we developed the nomogram. Gene set enrichment analysis (GSEA) was performed to reveal the underlying molecular mechanisms.

Results

We constructed the five‐lncRNA signature (including LEF1‐AS1, MEF2C‐AS1, ST8SIA6‐AS1, LINC01224, and LINC02408) in the training set, which successfully divided the patients into low‐ and high‐risk groups with significantly different prognosis (p = 0.000049), and the AUC at 3 and 5 years of the signature was 0.779 and 0.788, respectively. The predictive performance of this signature was validated in the test and entire set. The 5‐lncRNA signature was an independent prognostic factor of OS (p = 0.007) and the nomogram constructed by independent prognostic factors was an accurate predictor of predicting overall survival probability. Besides, several pathways associated with tumorigenesis have been identified by GSEA.

Conclusions

The 5‐lncRNA signature and nomogram are reliable in predicting elderly BC patients’ prognosis and provide clues for clinical decision‐making.

A Novel Autophagy-Related Long Non-Coding RNA Signature to Predict Prognosis and Therapeutic Response in Esophageal Squamous Cell Carcinoma

Background

Considering the significance of autophagy and long non-coding RNAs (lncRNAs) in the biology of esophageal squamous cell carcinoma (ESCC), the present study aimed to identify a new autophagy-related lncRNA signature to forecast the clinical outcomes of ESCC patients and to guide individualized treatment.

Methods

The expression profiles were obtained from Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA) database. We extracted autophagy-related genes from the Human Autophagy Database and identified autophagy-related lncRNAs through Spearman correlation analysis. Univariate, least absolute shrinkage and selection operator and multivariate Cox regression analyses were performed on GSE53625 to construct an autophagy-related lncRNAs prognostic signature. The model was subjected to bootstrap internal validation, and the expression levels of lncRNAs were verified by TCGA database. The potential molecular mechanism of the model was explored by gene set enrichment analysis (GSEA). Spearman correlation coefficient examined the correlation between risk score and ferroptosis-associated genes as well as the response to immunotherapy and chemotherapy.

Results

We identified and validated an autophagy-related lncRNAs prognostic signature in 179 patients with ESCC. The prognosis of patients in the low-risk group was significantly better than that in the high-risk group (p-value <0.001). The reliability of the model was verified by Brier score and ROC. GSEA results showed significant enrichment of cancer- and autophagy-related signaling pathways in the high-risk group and metabolism-related pathways in the low-risk group. Correlation analysis indicated that the model can effectively forecast the effect of immunotherapy and chemotherapy. About 35.41% (74/209) ferroptosis-related genes were significantly correlated with risk scores.

Conclusion

In brief, we constructed a novel autophagy-related lncRNAs signature (LINC02024, LINC01711, LINC01419, LCAL1, FENDRR, ADAMTS9-AS1, AC025244.1, AC015908.6 and AC011997.1), which could improve the prediction of clinical outcomes and guide individualized treatment of ESCC patients.

Histological and mutational profile of diffuse gastric cancer: current knowledge and future challenges

Gastric cancer (GC) pathogenesis is complex and heterogeneous, reflecting morphological, molecular and genetic diversity. Diffuse gastric cancer (DGC) and intestinal gastric cancer (IGC) are the major histological types. GC may be sporadic or hereditary; sporadic GC is related to environmental and genetic low-risk factors and hereditary GC is caused by inherited high-risk mutations, so far identified only for the diffuse histotype. DGC phenotypic heterogeneity challenges the current understanding of molecular mechanisms underlying carcinogenesis. The definition of a DGC-specific mutational profile remains controversial, possibly reflecting the heterogeneity of DGC-related histological subtypes [signet-ring cell carcinoma (SRCC) and poorly cohesive carcinoma not otherwise specified (PCC-NOS)]. Indeed, DGC and DGC-related subtypes may present specific mutational profiles underlying the particularly aggressive behaviour and dismal prognosis of DGC vs IGC and PCC-NOS vs SRCC. In this systematic review, we revised the histological presentations, molecular classifications and approved therapies for gastric cancer, with a focus on DGC. We then analysed results from the most relevant studies, reporting mutational analysis data specifying mutational frequencies, and their relationship with DGC and IGC histological types, and with specific DGC subtypes (SRCC and PCC-NOS). We aimed at identifying histology-associated mutational profiles with an emphasis in DGC and its subtypes (DGC vs IGC; sporadic vs hereditary DGC; and SRCC vs PCC-NOS). We further used these mutational profiles to identify the most commonly affected molecular pathways and biological functions, and explored the clinical trials directed specifically to patients with DGC. This systematic analysis is expected to expose a DGC-specific molecular profile and shed light into potential targets for therapeutic intervention, which are currently missing.

Elucidating the Role of Serum tRF-31-U5YKFN8DYDZDD as a Novel Diagnostic Biomarker in Gastric Cancer (GC)

Background

Gastric cancer (GC) is one of the malignant tumors with the highest morbidity and mortality in the world. Early diagnosis combined with surgical treatment can significantly improve the prognosis of patients. Therefore, it is urgent to seek higher sensitivity and specificity biomarkers in GC. tRNA-derived small RNAs are a new non-coding small RNA that widely exists in tumor cells and body fluids. In this study, we explore the expression and biological significance of tRNA-derived small RNAs in GC.

Materials and Methods

First of all, we screened the differentially expressed tRNA-derived small RNAs in tumor tissues by high-throughput sequencing. Agarose gel electrophoresis (AGE), Sanger sequencing, and Nuclear and Cytoplasmic RNA Separation Assay were used to screen tRF-31-U5YKFN8DYDZDD as a potential tumor biomarker for the diagnosis of GC. Then, we detected the different expressions of tRF-31-U5YKFN8DYDZDD in 24 pairs of GC and paracancerous tissues, the serum of 111 GC patients at first diagnosis, 89 normal subjects, 48 superficial gastritis patients, and 28 postoperative GC patients by quantitative real-time PCR (qRT-PCR). Finally, we used the receiver operating characteristic (ROC) curve to analyze its diagnostic efficacy.

Results

The expression of tRF-31-U5YKFN8DYDZDD has good stability and easy detection. tRF-31-U5YKFN8DYDZDD was highly expressed in tumor tissue, serum, and cell lines of GC, and the expression was significantly related to TNM stage, depth of tumor invasion, lymph node metastasis, and vascular invasion. The expression of serum tRF-31-U5YKFN8DYDZDD in the GC patients decreased after the operation (P = 0.0003). Combined with ROC curve analysis, tRF-31-U5YKFN8DYDZDD has better detection efficiency than conventional markers.

Conclusions

The expressions of tRF-31-U5YKFN8DYDZDD in the tumor and paracancerous tissues, the serum of GC patients and healthy people, and the serum of GC patients before and after operation were different. tRF-31-U5YKFN8DYDZDD is not only a diagnostic biomarker of GC but also a predictor of poor prognosis.

Regulatory Non-coding RNAs for Death Associated Protein Kinase Family

The death associated protein kinases (DAPKs) are a family of calcium dependent serine/threonine kinases initially identified in the regulation of apoptosis. Previous studies showed that DAPK family members, including DAPK1, DAPK2 and DAPK3 play a crucial regulatory role in malignant tumor development, in terms of cell apoptosis, proliferation, invasion and metastasis. Accumulating evidence has demonstrated that non-coding RNAs, including microRNA (miRNA), long non-coding RNA (lncRNA) and circRNA, are involved in the regulation of gene expression and tumorigenesis. Recent studies indicated that non-coding RNAs participate in the regulation of DAPKs. In this review, we summarized the current knowledge of non-coding RNAs, as well as the potential miRNAs, lncRNAs and circRNAs, that are involved in the regulation of DAPKs.

A Novel Identified Long Non-coding RNA, lncRNA MEF2C-AS1, Inhibits Cervical Cancer via Regulation of miR-592/RSPO1

Purpose: Our purpose was to investigate the effect of lncRNA MEF2C antisense RNA 1 (MEF2C-AS1) on cervical cancer and further explore its underlying molecular mechanisms. Methods: The proliferation, migration and invasion of CC cells were determined by counting Kit-8 (CCK-8), colony formation assay, and transwell assays, respectively. qRT-PCR and western blot were conducted to quantitatively detect the expression of lncRNA MEF2C-AS1, miR-592 and R-spondin1 (RSPO1). Kaplan-Meier survival curve from the Cancer Genome Atlas (TCGA) database and the Gene Expression Profiling Interactive Analysis (GEPIA) website was used to describe the overall survival. Bioinformatics analysis was performed to search the downstream target of lncRNA MEF2C-AS1 and miR-592. Luciferase reporter assay was conducted to detect the interaction between lncRNA MEF2C-AS1 and miR-592 or miR-592 and RSPO1. Results: The data from GEPIA website showed that lncRNA MEF2C-AS1 expression was down-regulated in CC tissues and also associated with survival rate of CC patients. Moreover, the results of qRT-PCR also showed lncRNA MEF2C-AS1 was lowly expressed in CC cells. Subsequently, we confirmed that overexpression of lncRNA MEF2C-AS1 inhibited the proliferation, migration and invasion of CC cells. Further research illustrated that lncRNA MEF2C-AS1 was the target of miR-592, and RSPO1 was the downstream target gene of miR-592. Importantly, functional research findings indicated that lncRNA MEF2C-AS1 inhibited CC via suppressing miR-592 by targeting RSPO1. Conclusion: In our study, we demonstrated the functional role of the lncRNA MEF2C-AS1-miR-592-RSPO1 axis in the progression of CC, which provides a latent target for CC treatment.

FENDRR: A pivotal, cancer-related, long non-coding RNA

Long non-coding RNAs (lncRNAs) have more than 200 nucleotides and do not encode proteins. Based on numerous studies, lncRNAs have emerged as new and crucial regulators of biological function and have been implicated in the pathogenesis of a variety of diseases, especially cancers. Specific lncRNAs have been identified as novel molecular biomarkers for cancer diagnosis, prognosis, and treatment efficacy. Fetal-lethal non-coding developmental regulatory RNA (FENDRR, also known as FOXF1-AS1) is a novel lncRNA that is located at chr3q13.31 and has four exons and 3099 nucleotides, and its genomic site is located at chr3q13.31. FENDRR is abnormally expressed in a variety of cancers and is significantly associated with different clinical characteristics. In addition, FENDRR has shown potential as a biomarker for cancer diagnosis, prognosis, and treatment. In this review, we summarize the current understanding of FENDRR and its mechanistic role in cancer progression. We also discuss recent insights into the clinical significance of FENDRR for cancer diagnosis, prognosis, and treatment.

FENDRR Sponges miR-424-5p to Inhibit Cell Proliferation, Migration and Invasion in Colorectal Cancer

Objective:

LncRNAs are non-coding RNAs exerting vital roles in the occurrence and development of various cancer types. This study tended to describe the expression pattern of FENDRR in colorectal cancer (CRC), and further investigate the role of FENDRR in CRC cell biological behaviors.

Methods:

Gene expression profile of colon cancer was accessed from the TCGA database, and then processed for differential analysis for identification of differentially expressed lncRNAs and miRNAs. Some in vitro experiments like qRT-PCR, MTT, colony formation assay, wound healing assay and Transwell assay were performed to assess the effect of FENDRR on cell biological behaviors. Dual-luciferase reporter assay was conducted to further validate the targeting relationship between FENDRR and miR-424-5p, and rescue experiments were carried out for determining the mechanism of FENDRR/miR-424-5p underlying the proliferation, migration and invasion of CRC cells.

Results:

Bioinformatics analysis suggested that FENDRR was significantly down-regulated in CRC tissue, and low FENDRR was intimately correlated to poor prognosis. FENDRR overexpression could greatly inhibit cell proliferation, migration and invasion. Besides, there was a negative correlation between FENDRR and miR-424-5p. Dual-luciferase reporter assay indicated that miR-424-5p was a direct target of FENDRR. Rescue experiments discovered that FENDRR exerted its role in cell proliferation, migration and invasion in CRC via targeting miR-424-5p.

Conclusion:

FENDRR is poorly expressed in CRC tissue and cells, and low FENDRR is responsible for the inhibition of cell proliferation, migration and invasion of CRC by means of targeting miR-424-5p.

RNA sequencing: new technologies and applications in cancer research

Over the past few decades, RNA sequencing has significantly progressed, becoming a paramount approach for transcriptome profiling. The revolution from bulk RNA sequencing to single-molecular, single-cell and spatial transcriptome approaches has enabled increasingly accurate, individual cell resolution incorporated with spatial information. Cancer, a major malignant and heterogeneous lethal disease, remains an enormous challenge in medical research and clinical treatment. As a vital tool, RNA sequencing has been utilized in many aspects of cancer research and therapy, including biomarker discovery and characterization of cancer heterogeneity and evolution, drug resistance, cancer immune microenvironment and immunotherapy, cancer neoantigens and so on. In this review, the latest studies on RNA sequencing technology and their applications in cancer are summarized, and future challenges and opportunities for RNA sequencing technology in cancer applications are discussed.

Long non-coding RNAs towards precision medicine in gastric cancer: early diagnosis, treatment, and drug resistance

Gastric cancer is a deadly disease and remains the third leading cause of cancer-related death worldwide. The 5-year overall survival rate of patients with early-stage localized gastric cancer is more than 60%, whereas that of patients with distant metastasis is less than 5%. Surgical resection is the best option for early-stage gastric cancer, while chemotherapy is mainly used in the middle and advanced stages of this disease, despite the frequently reported treatment failure due to chemotherapy resistance. Therefore, there is an unmet medical need for identifying new biomarkers for the early diagnosis and proper management of patients, to achieve the best response to treatment. Long non-coding RNAs (lncRNAs) in body fluids have attracted widespread attention as biomarkers for early screening, diagnosis, treatment, prognosis, and responses to drugs due to the high specificity and sensitivity. In the present review, we focus on the clinical potential of lncRNAs as biomarkers in liquid biopsies in the diagnosis and prognosis of gastric cancer. We also comprehensively discuss the roles of lncRNAs and their molecular mechanisms in gastric cancer chemoresistance as well as their potential as therapeutic targets for gastric cancer precision medicine.

Polysome-associated lncRNAs during cardiomyogenesis of hESCs

Long non-coding RNAs (lncRNAs) have been found to be involved in many biological processes, including the regulation of cell differentiation, but a complete characterization of lncRNA is still lacking. Additionally, there is evidence that lncRNAs interact with ribosomes, raising questions about their functions in cells. Here, we used a developmentally staged protocol to induce cardiogenic commitment of hESCs and then investigated the differential association of lncRNAs with polysomes. Our results identified lncRNAs in both the ribosome-free and polysome-bound fractions during cardiogenesis and showed a very well-defined temporal lncRNA association with polysomes. Clustering of lncRNAs was performed according to the gene expression patterns during the five timepoints analyzed. In addition, differential lncRNA recruitment to polysomes was observed when comparing the differentially expressed lncRNAs in the ribosome-free and polysome-bound fractions or when calculating the polysome-bound vs ribosome-free ratio. The association of lncRNAs with polysomes could represent an additional cytoplasmic role of lncRNAs, e.g., in translational regulation of mRNA expression.

Long non-coding RNA signature in gastric cancer

Gastric cancer as a common human malignancy has been associated with aberrant expressions of several coding and non-coding genes. Long non-coding RNAs (lncRNAs) as regulators of gene expressions at different genomic, transcriptomic and post-transcriptomic levels are among putative biomarkers and therapeutic targets in gastric cancer. In the present study, we have searched available literature and listed lncRNAs that are involved in the pathogenesis of gastric cancer. In addition, we discuss associations between expressions of these lncRNAs and tumoral features or risk factors for gastric cancer. Based on the established role of lncRNAs in regulation of genomic stability, cell cycle, apoptosis, angiogenesis and other aspects of cell physiology, the potential of these transcripts as therapeutic targets in gastric cancer should be evaluated in future studies.

LncRNA FENDRR attenuates colon cancer progression by repression of SOX4 protein

Background and purpose: Homo sapiens FOXF1 adjacent noncoding developmental regulatory RNA (FENDRR) is a novel long noncoding RNA (lncRNA) exerting important effects on transcriptional and post-transcriptional regulation. The purpose of this study was to investigate the potential role of FENDRR in colon cancer. Methods: Multiple cellular and molecular biology experiments were performed in the present study, such as CCK-8, Western blot, immunohistochemistry, confocal immunofluorescent and animal studies. Results: We determined that attenuation of FENDRR was a frequent event in colon cancer tissues and colon cancer cell lines, in contrast to their normal counterparts. Low levels of FENDRR were associated with the clinical stages and poor prognosis. Moreover, ectopic expression of FENDRR repressed colon cancer cell viability, invasion and epithelial-mesenchymal transition. Furthermore, through a series of in vitro and in vivo assays, we reported the discovery of FENDRR modulating the expression of SOX4 protein, and hence in the progression of colon cancer. Conclusion: Based on these data, we demonstrated that FENDRR may function as a tumor-suppressor gene by repressing SOX4 and as a potential therapeutic target for colon cancer.