LINC01436 Inhibited miR-585-3p Expression and Upregulated MAPK1 Expression to Promote Gastric Cancer Progression

The Effect of Race/Ethnicity and MED12 Mutation on the Expression of Long Non-Coding RNAs in Uterine Leiomyoma and Myometrium

The objective of this study was to elucidate the expression of long non-coding RNA (lncRNA) in leiomyomas (Lyo) and paired myometrium (Myo) and explore the impact of race and MED12 mutation. Fold change analysis (Lyo/paired Myo) indicated the expression of 63 lncRNAs was significantly altered in the mutated group but not in the non-mutated Lyo. Additionally, 65 lncRNAs exhibited an over 1.5-fold change in the Black but not the White group. Fifteen differentially expressed lncRNAs identified with next-generation sequencing underwent qRT-PCR confirmation. Compared with Myo, the expression of TPTEP1, PART1, RPS10P7, MSC-AS1, SNHG12, CA3-AS1, LINC00337, LINC00536, LINC01436, LINC01449, LINC02433, and LINC02624 was significantly higher, while the expression of ZEB2-AS1, LINC00957, and LINC01186 was significantly lower. Comparison of normal Myo with diseased Myo showed significant differences in the expression of several lncRNAs. Analysis based on race and Lyo MED12 mutation status indicated a significantly higher expression of RPS10P7, SNHG12, LINC01449, LINC02433, and LINC02624 in Lyo from Black patients. The expression of TPTEP1, PART1, RPS10P7, MSC-AS1, LINC00337, LINC00536, LINC01436, LINC01449, LINC02433, and LINC02624 was higher, while LINC01186 was significantly lower in the MED12-mutated group. These results indicate that Lyo are characterized by aberrant lncRNA expression, which is further impacted by race and Lyo MED12 mutation status.

Epigenetic signatures in gastric cancer: current knowledge and future perspectives

INTRODUCTION

Gastric cancer (GC) is the fifth most common malignancy in the world and accounts for 7.7% of all cancer-related deaths. Early diagnosis of GC is critical in terms of prognosis, and aberrations at the molecular level, especially epigenetic alterations, manifest much earlier than histological findings. In recent years, there has been a great deal of research on the epigenomic profile of GC, and epigenetic alterations seem to play a more important role than genetic factors. With the introduction of epigenetic drugs into clinical use in the last decade, the importance of the epigenetic background of GC has increased considerably.

AREAS COVERED

In this review, we summarize the role of methylation changes, histone modifications, and non-coding RNAs in the pathogenesis of GC and how these signatures can be used as diagnostic and therapeutic targets in clinical management.

EXPERT OPINION

Epigenetic alterations take place before most genetic aberrations observed in GC and may have an initiating role in the pathogenesis of GC. They can be used as biomarkers in risk calculation, early diagnosis, and evaluation of prognosis of GC, as well as treatment targets.

Investigating the Active Substance and Mechanism of San-Jiu-Wei-Tai Granules via UPLC-QE-Orbitrap-MS and Network Pharmacology

San-Jiu-Wei-Tai granules (SJWTG) are a significant Chinese patent medicine for the treatment of chronic gastritis (CG), having outstanding advantages in long-term treatment; however, the chemical composition and potential mechanism have not been investigated until now. In this study, a rapid separation and identification method based on UPLC-QE-Orbitrap-MS was established, and 95 chemical components from SJWTGs were identified, including 6 chemical components of an unknown source that are not derived from the 8 herbs included in SJWTGs. The identified chemical components were subsequently analysed by network pharmacology, suggesting that the core targets for the treatment of CG with SJWTGs were EGFR, SRC, AKT1, HSP90AA1, MAPK1, and MAPK3 and thus indicating that SJWTGs could reduce the inflammatory response of gastric epithelial cells and prevent persistent chronic inflammation that induces cancerization by regulating the MAPK signalling pathway and the C-type lectin receptor signalling pathway as well as their upstream and downstream pathways in the treatment of CG. The key bioactive components in SJWTGs were identified as 2,6-bis(4-ethylphenyl)perhydro-1,3,5,7-tetraoxanaphth-4-ylethane-1,2-diol, a chemical component of an unknown source, murrangatin, meranzin hydrate, paeoniflorin, and albiflorin. The results of molecular docking showed the strong binding interaction between the key bioactive components and the core targets, demonstrating that the key bioactive components deserve to be further studied and considered as Q-markers. By acting on multiple targets, SJWTG is less susceptible to drug resistance during the long-term treatment of CG, indicating the advantage of Chinese patent medicines. Furthermore, the preventive effect of SJWTGs on gastric cancer also demonstrates the superiority of preventive treatment of disease with traditional Chinese medicine.

The functions of long noncoding RNAs on regulation of F-box proteins in tumorigenesis and progression

Accumulated evidence has revealed that F-box protein, a subunit of SCF E3 ubiquitin ligase complexes, participates in carcinogenesis and tumor progression via targeting its substrates for ubiquitination and degradation. F-box proteins could be regulated by cellular signaling pathways and noncoding RNAs in tumorigenesis. Long noncoding RNA (lncRNA), one type of noncoding RNAs, has been identified to modulate the expression of F-box proteins and contribute to oncogenesis. In this review, we summarize the role and mechanisms of multiple lncRNAs in regulating F-box proteins in tumorigenesis, including lncRNAs SLC7A11-AS1, MT1JP, TUG1, FER1L4, TTN-AS1, CASC2, MALAT1, TINCR, PCGEM1, linc01436, linc00494, GATA6-AS1, and ODIR1. Moreover, we discuss that targeting these lncRNAs could be helpful for treating cancer via modulating F-box protein expression. We hope our review can stimulate the research on exploration of molecular insight into how F-box proteins are governed in carcinogenesis. Therefore, modulation of lncRNAs is a potential therapeutic strategy for cancer therapy via regulation of F-box proteins.

Network pharmacology and experimental verification based research into the effect and mechanism of Aucklandiae Radix-Amomi Fructus against gastric cancer

To investigate the mechanism of the Aucklandiae Radix–Amomi Fructus (AR–AF) herb pair in treating gastric cancer (GC) by using network pharmacology and experimental verification. Using the traditional Chinese medicine system pharmacology database and analysis platform (TCMSP), the major active components and their corresponding targets were estimated and screened out. Using Cytoscape 3.7.2 software, a visual network was established using the active components of AR–AF and the targets of GC. Based on STRING online database, the protein interaction network of vital targets was built and analyzed. With the Database for Annotation, Visualization, and Integrated Discovery (DAVID) server, the gene ontology (GO) biological processes and the Kyoto Encyclopedia of Genes and Genomes (KEGG) signaling pathways of the target enrichment were performed. AutoDock Vina was used to perform molecular docking and calculate the binding affinity. The mRNA and protein expression levels of the hub targets were analyzed by the Oncomine, GEPIA, HPA databases and TIMER online tool, and the predicted targets were verified by qRT–PCR in vitro. Eremanthin, cynaropicrin, and aceteugenol were identified as vital active compounds, and AKT1, MAPK3, IL6, MAPK1, as well as EGFR were considered as the major targets. These targets exerted therapeutic effects on GC by regulating the cAMP signaling pathway, and PI3K-Akt signaling pathway. Molecular docking revealed that these active compounds and targets showed good binding interactions. The validation in different databases showed that most of the results were consistent with this paper. The experimental results confirmed that eremanthin could inhibit the proliferation of AGS by reducing the mRNA expression of hub targets. As predicted by network pharmacology and validated by the experimental results, AR–AF exerts antitumor effects through multiple components, targets, and pathways, thereby providing novel ideas and clues for the development of preparations and the treatment of GC.

MAPK1 Is Regulated by LOC102188416/miR-143-3p Axis in Dairy Goat Mammary Epithelial Cells

MicroRNA-143-3p (miR-143-3p) is one of the miRNAs involved in the growth of goat mammary epithelial cells (GMECs). In this study, Illumina/Solexa sequencing was performed to establish the lncRNA database in Laoshan dairy goats. Using the lncRNA database, long noncoding RNAs (lncRNAs) regulated by miR-143-3p were screened. In total, 4899 lncRNAs were identified, with 173 lncRNAs being differentially expressed in all three replicates. The target genes of the differentially expressed lncRNAs were annotated in GO terms and KEGG pathways. Among the differentially expressed lncRNAs, lncRNA LOC102188416 was predicted to sponge miR-143-3p and share MAPK1 as a common target gene with miR-143-3p, which was validated by dual luciferase reporter assay system and qRT-PCR. The miR-143-3p mimic significantly lowered the relative luciferase activity of psiCHECK2-LOC102188416 wildtype vector but not mutated vector, suggesting that lncRNA LOC102188416 might be a sponge of miR-143-3p, which was verified by the promotion role of lncRNA LOC102188416 siRNA (siR-LOC102188416) in the expression of miR-143-3p. It was shown that the expression of MAPK1 was downregulated by either miR-143-3p mimic or siR-LOC102188416, indicating that miR-143-3p and lncRNA LOC102188416 had a coregulatory effect on MAPK1 expression. The co-transfection of miR-143-3p inhibitor with siR-LOC102188416 reversed the decrease of MAPK1 expression regulated by siR-LOC102188416 alone, strengthening the existence of lncRNA LOC102188416/miR-143-3p/MAPK1 axis in GMECs of Laoshan dairy goats.

Identification of Potential Predictor of Biochemical Recurrence in Prostate Cancer

Background

Prostate cancer is a common malignancy in men. Radical prostatectomy is one of the primary treatment modalities for patients with prostate cancer. However, early identification of biochemical recurrence is a major challenge for post-radical prostatectomy surveillance. There is a lack of reliable predictors of biochemical recurrence. The purpose of this study was to explore potential biochemical recurrence indicators for prostate cancer.

Materials and Methods

We analyzed transcriptomic data of cases with biochemical recurrence in The Cancer Genome Atlas (TCGA). Then, we performed integrative bioinformatics analyses to establish a biochemical recurrence predictor model of prostate cancer.

Results

There were 146 differentially expressed genes (DEGs) between prostate cancer and normal prostate, including 12 upregulated and 134 downregulated genes. Comprehensive pathway enrichment analyses revealed that these DEGs were associated with multiple cellular metabolic pathways. Subsequently, according to the random assignment principle, 208 patients were assigned to the training cohort and 205 patients to the validation cohort. Univariate Cox regression analysis showed that 7 genes were significantly associated with the biochemical recurrence of prostate cancer. A model consisting of 5 genes was constructed using LASSO regression and multivariate Cox regression to predict biochemical recurrence of prostate cancer. Expression of PAH and AOC1 decreased with an increasing incidence of prostate cancer, whereas expression of DDC, LINC01436 and ORM1 increased with increasing incidence of prostate cancer. Kaplan–Meier curves and receiver operator characteristic (ROC) curves indicated that the 5-gene model had reliable utility in identifying the risk of biochemical recurrence of prostate cancer.

Conclusion

This study provides a model for predicting prostate cancer recurrence after surgery, which may be an optional indicator for postoperative follow-up.

Circular RNA circ_0002360 regulates the Taxol resistance and malignant behaviors of Taxol-resistant non-small cell lung cancer cells by microRNA-585-3p-dependent modulation of G protein regulated inducer of neurite outgrowth 1

Drug resistance has become the major obstacle for the treatment of non-small cell lung cancer (NSCLC). Circular RNAs (circRNAs) are tightly linked to the development of drug resistance of NSCLC. Herein, we tested the function of circ_0002360 in the Taxol resistance of NSCLC. Circ_0002360, microRNA (miR)-585-3p and G protein regulated inducer of neurite outgrowth 1 (GPRIN1) were quantified by quantitative real-time PCR (qRT-PCR). To identify the circular structure of circ_0002360, RNase R digestion was applied. To detect cell proliferation, colony formation and 5-ethynyl-2’-deoxyuridine (EdU) assays were used. For assessment of cell apoptosis, flow cytometry was adopted. For motility and invasion analyses, transwell assay was employed. Our data showed that circ_0002360 was mainly located in the cytoplasm and was highly expressed in the Taxol-resistant NSCLC. Silencing of circ_0002360 inhibited cell Taxol resistance, proliferation, motility, and invasiveness and induced apoptosis in vitro. MiR-585-3p was underexpressed in Taxol-resistant NSCLC and was targeted by circ_0002360. MiR-585-3p knockdown alleviated the influence of circ_0002360 silence on Taxol-resistant cells. GPRIN1 was directly targeted by miR-585-3p. The influence of miR-585-3p on cell Taxol resistance and functional behaviors was reversed by GPRIN1 overexpression. Moreover, circ_0002360 modulated GPRIN1 through miR-585-3p. Additionally, silencing of circ_0002360 weakened the growth of xenografts in vivo. Our study demonstrated that silencing of circ_0002360 enhanced the Taxol sensitivity and suppressed the malignant behaviors of Taxol-resistant NSCLC cells by miR-585-3p/GPRIN1 axis, providing novel targets for improving the anti-tumor efficacy of Taxol in NSCLC.

DesA Prognostic Risk Model of LncRNAs in Patients With Acute Myeloid Leukaemia Based on TCGA Data

Purpose: This study aimed to combine the clinical data of acute myeloid leukaemia (AML) from The Cancer Genome Atlas (TCGA) database to obtain prognosis-related biomarkers, construct a prognostic risk model using long non-coding RNAs (lncRNAs) in AML and help patients with AML make clinical treatment decisions.

Methods: We analysed the transcriptional group information of 151 patients with AML obtained from TCGA and extracted the expressions of lncRNAs. According to the mutation frequency, the patients were divided into the high mutation group (genomic unstable group, top 25% of mutation frequency) and low mutation group (genomic stable group, 25% after mutation frequency). The ‘limma’ R package was used to analyse the difference in lncRNA expressions between the two groups, and the “survival,” “caret,” and “glmnet” R packages were used to screen lncRNAs that are related to clinical prognosis. Subsequently, a prognosis-related risk model was constructed and verified through different methods.

Results: According to the lncRNA expression data in TCGA, we found that seven lncRNAs (i.e. AL645608.6, LINC01436, AL645608.2, AC073534.2, LINC02593, AL512413.1, and AL645608.4) were highly correlated with the clinical prognosis of patients with AML, so we constructed a prognostic risk model of lncRNAs based on LINC01436, AC073534.2, and LINC02593. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses of differentially expressed lncRNA-related target genes were performed, receiver operating characteristic (ROC) curves were created, the applicability of the model in children was assessed using the TARGET database and the model was externally verified using the GEO database. Furthermore, different expression patterns of lncRNAs were validated in various AML cell lines derived from Homo sapiens.

Conclusions: We have established a lncRNA prognostic model that can predict the survival of patients with AML. The Kaplan-Meier analysis showed that this model distinguished survival differences between patients with high- and low-risk status. The ROC analysis confirmed this finding and showed that the model had high prediction accuracy. The Kaplan-Meier analysis of the clinical subgroups showed that this model can predict prognosis independent of clinicopathological factors. Therefore, the proposed prognostic lncRNA risk model can be used as an independent biomarker of AML.

Interaction of ncRNA and Epigenetic Modifications in Gastric Cancer: Focus on Histone Modification

Gastric cancer has developed as a very common gastrointestinal tumors, with recent effective advancements in the diagnosis and treatment of early gastric cancer. However, the prognosis for gastric cancer remains poor. As a result, there is in sore need of better understanding the mechanisms of gastric cancer development and progression to improve existing diagnostic and treatment options. In recent years, epigenetics has been recognized as an important contributor on tumor progression. Epigenetic changes in cancer include chromatin remodeling, DNA methylation and histone modifications. An increasing number of studies demonstrated that noncoding RNAs (ncRNAs) are associated with epigenetic changes in gastric cancer. Herein, we describe the molecular interactions of histone modifications and ncRNAs in epigenetics. We focus on ncRNA-mediated histone modifications of gene expression associated with tumorigenesis and progression in gastric cancer. This molecular mechanism will contribute to our deeper understanding of gastric carcinogenesis and progression, thus providing innovations in gastric cancer diagnosis and treatment strategies.

MiR-585-3p suppresses tumor proliferation and migration by directly targeting CAPN9 in high grade serous ovarian cancer

Background

Aberrant expression of microRNAs (miRNAs) contributes to the development of high grade serous ovarian cancer (HGSOC). However, the molecular mechanism by which miRNA-585-3p mediates high-grade serous ovarian carcinogenesis is unclear. This study aims to investigate the specific mechanism of action of miR-585-3p in HGSOC.

Methods

Expression of miR-585-3p in HGSOC tissues and cell lines was detected by qRT-PCR. Cell viability and migration were detected using MTT and transwell system. The expression of target genes and target proteins of miR-585-3p was detected by dual luciferase reporter assay and western blot.

Results

The expression of miR-585-3p was significantly lower in HGSOC tissues and cells than in normal ovarian tissues and cell lines. In HGSOC tissues, CAPN9 expression was inversely correlated with miR-585-3p expression. MiR-585-3p inhibited the proliferation and migration of HGSOC cells. MiR-585-3p bound to the 3'-untranslated region (UTR) of CAPN9 and inhibits CAPN9 expression. Overexpression of CAPN9 reduced the inhibitory effect of miR-585-3p in HGSOC cells.

Conclusions

miR-585-3p is significantly down-regulated in HGSOC tissues and cell lines. MiR-585-3p inhibits the proliferation and migration of HGSOC cells by targeting CAPN9.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13048-021-00841-w.

Study of the active ingredients and mechanism of Sparganii rhizoma in gastric cancer based on HPLC-Q-TOF-MS/MS and network pharmacology

Sparganii rhizoma (SL) has potential therapeutic effects on gastric cancer (GC), but its main active ingredients and possible anticancer mechanism are still unclear. In this study, we used HPLC-Q-TOF–MS/MS to comprehensively analyse the chemical components of the aqueous extract of SL. On this basis, a network pharmacology method incorporating target prediction, gene function annotation, and molecular docking was performed to analyse the identified compounds, thereby determining the main active ingredients and hub genes of SL in the treatment of GC. Finally, the mRNA and protein expression levels of the hub genes of GC patients were further analysed by the Oncomine, GEPIA, and HPA databases. A total of 41 compounds were identified from the aqueous extract of SL. Through network analysis, we identified seven main active ingredients and ten hub genes: acacetin, sanleng acid, ferulic acid, methyl 3,6-dihydroxy-2-[(2-hydroxyphenyl) ethynyl]benzoate, caffeic acid, adenine nucleoside, azelaic acid and PIK3R1, PIK3CA, SRC, MAPK1, AKT1, HSP90AA1, HRAS, STAT3, FYN, and RHOA. The results indicated that SL might play a role in GC treatment by controlling the PI3K-Akt and other signalling pathways to regulate biological processes such as proliferation, apoptosis, migration, and angiogenesis in tumour cells. In conclusion, this study used HPLC-Q-TOF–MS/MS combined with a network pharmacology approach to provide an essential reference for identifying the chemical components of SL and its mechanism of action in the treatment of GC.