Long non-coding RNA TTTY15 silencing inhibits gastric cancer progression by sponging microRNA-98-5p to down-regulate cyclin D2 expression

MicroRNA-98 as a novel diagnostic marker and therapeutic target in cancer patients

The progress of cancer treatment methods in the last decade has significantly reduced mortality rate among these patients. Nevertheless, cancer is still recognized as one of the main causes of human deaths. One of the main reasons for the high death rate in cancer patients is the late diagnosis in the advanced tumor stages. Therefore, it is necessary to investigate the molecular biology of tumor progressions in order to introduce early diagnostic markers. MicroRNAs (miRNAs) have an important role in regulating cellular processes associated with tumor progression. Due to the high stability of miRNAs in body fluids, they are widely used as non-invasive markers in the early tumor diagnosis. Since, deregulation of miR-98 has been reported in a wide range of cancers, we investigated the molecular mechanisms of miR-98 during tumor progression. It has been reported that miR-98 mainly inhibits the tumor growth by the modulation of transcription factors and signaling pathways. Therefore, miR-98 can be introduced as a tumor marker and therapeutic target among cancer patients.

Application of angiogenesis-related genes associated with immune infiltration in the molecular typing and diagnosis of acute myocardial infarction

BACKGROUND

Angiogenesis has been discovered to be a critical factor in developing tumors and ischemic diseases. However, the role of angiogenesis-related genes (ARGs) in acute myocardial infarction (AMI) remains unclear.

METHODS

The GSE66360 dataset was used as the training cohort, and the GSE48060 dataset was used as the external validation cohort. The random forest (RF) algorithm was used to identify the signature genes. Consensus clustering analysis was used to identify robust molecular clusters associated with angiogenesis. The ssGSEA was used to analyze the correlation between ARGs and immune cell infiltration. In addition, we constructed miRNA-gene, transcription factor network, and targeted drug network of signature genes. RT-qPCR was used to verify the expression levels of signature genes.

RESULTS

Seven signature ARGs were identified based on the RF algorithm. Receiver operating characteristic curves confirmed the classification accuracy of the risk predictive model based on signature ARGs (area under the curve [AUC] = 0.9596 in the training cohort and AUC = 0.7773 in the external validation cohort). Subsequently, the ARG clusters were identified by consensus clustering. Cluster B had a more generalized high expression of ARGs and was significantly associated with immune infiltration. The miRNA and transcription factor network provided new ideas for finding potential upstream targets and biomarkers. Finally, the results of RT-qPCR were consistent with the bioinformatics analysis, further validating our results.

CONCLUSIONS

Angiogenesis is closely related to AMI, and characterizing the angiogenic features of patients with AMI can help to risk-stratify patients and provide personalized treatment.

Investigation of Molecular Mechanisms of S-1, Docetaxel and Cisplatin in Gastric Cancer with a History of Helicobacter Pylori Infection

Gastric cancer rates and fatality rates have not decreased. Gastric cancer treatment has historically included surgery (both endoscopic and open), chemotherapy, targeted therapy, and immunotherapy. One of the aggravating carriers of this cancer is Helicobacter pylori infection. Various drug combinations are used to treat gastric cancer. However, examining the molecular function of these drugs, depending on whether or not there is a history of Helicobacter pylori infection, can be a better help in the treatment of these patients. This study was designed as bioinformatics. Various datasets such as patients with gastric cancer, with and without a history of H. pylori, and chemotherapy drugs cisplatin, docetaxel, and S-1 were selected. Using Venn diagrams, the similarities between gene expression profiles were assessed and isolated. Then, selected the signal pathways, ontology of candidate genes and proteins. Then, in clinical databases, we confirmed the candidate genes and proteins. The association between gastric cancer patients with and without a history of H. pylori with chemotherapy drugs was investigated. The pathways of cellular aging, apoptosis, MAPK, and TGFβ were clearly seen. After a closer look at the ontology of genes and the relationship between proteins, we nominated important biomolecules. Accordingly, NCOR1, KIT, MITF, ESF1, ARNT2, TCF7L2, and KRR1 proteins showed an important role in these connections. Finally, NCOR1, KIT, KRR1, and ESF1 proteins showed a more prominent role in the molecular mechanisms of S-1, Docetaxel, and Cisplatin in gastric cancer associated with or without H. pylori.

More than the SRY: The Non-Coding Landscape of the Y Chromosome and Its Importance in Human Disease

Historically, the Y chromosome has presented challenges to classical methodology and philosophy of understanding the differences between males and females. A genetic unsolved puzzle, the Y chromosome was the last chromosome to be fully sequenced. With the advent of the Human Genome Project came a realization that the human genome is more than just genes encoding proteins, and an entire universe of RNA was discovered. This dark matter of biology and the black box surrounding the Y chromosome have collided over the last few years, as increasing numbers of non-coding RNAs have been identified across the length of the Y chromosome, many of which have played significant roles in disease. In this review, we will uncover what is known about the connections between the Y chromosome and the non-coding RNA universe that originates from it, particularly as it relates to long non-coding RNAs, microRNAs and circular RNAs.

Identification of m6A/m5C-related lncRNA signature for prediction of prognosis and immunotherapy efficacy in esophageal squamous cell carcinoma

N6-methyladenosine (m6A) and 5-methylcytosine (m5C) RNA modifications have garnered significant attention in the field of epigenetic research due to their close association with human cancers. This study we focus on elucidating the expression patterns of m6A/m5C-related long non-coding RNAs (lncRNAs) in esophageal squamous cell carcinoma (ESCC) and assessing their prognostic significance and therapeutic potential. Transcriptomic profiles of ESCC were derived from public resources. m6A/m5C-related lncRNAs were obtained from TCGA using Spearman's correlations analysis. The m6A/m5C-lncRNAs prognostic signature was selected to construct a RiskScore model for survival prediction, and their correlation with the immune microenvironment and immunotherapy response was analyzed. A total of 606 m6A/m5C-lncRNAs were screened, and ESCC cases in the TCGA cohort were stratified into three clusters, which showed significantly distinct in various clinical features and immune landscapes. A RiskScore model comprising ten m6A/m5C-lncRNAs prognostic signature were constructed and displayed good independent prediction ability in validation datasets. Patients in the low-RiskScore group had a better prognosis, a higher abundance of immune cells (CD4 + T cell, CD4 + naive T cell, class-switched memory B cell, and Treg), and enhanced expression of most immune checkpoint genes. Importantly, patients with low-RiskScore were more cline benefit from immune checkpoint inhibitor treatment (P < 0.05). Our findings underscore the potential of RiskScore system comprising ten m6A/m5C-related lncRNAs as effective biomarkers for predicting survival outcomes, characterizing the immune landscape, and assessing response to immunotherapy in ESCC.

Mechanism of miR-98-5p in gastric cancer cell proliferation, migration, and invasion through the USP44/CTCFL axis

Objectives

Gastric cancer (GC) is the leading digestive malignancy with high incidence and mortality rate. microRNAs (miRs) play an important role in GC progresssion. This study aimed to investigate the effect of miR-98-5p on proliferation, migration, and invasion of GC cells.

Methods

The expression levels of miR-98-5p, ubiquitin specific peptidase 44 (USP44), and CCCTCbinding factor-like (CTCFL) in GC tissues and cells were identified using reversetranscription quantitative polymerase chain reaction and Western blot assay. The relationship between miR-98-5p expression/USP44 and the clinicopathological features in GC patients was analyzed. GC cell proliferation, invasion, and migration were evaluated by cell counting kit-8 and clone formation assays and Transwell assays. The bindings of miR-98-5p to USP44 and USP44 to CTCFL were examined using dualluciferase assay and co-immunoprecipitation. GC cells were treated with MG132 and the ubiquitination level of CTCFL was examined using ubiquitination assay. Rescue experiments were performed to verify the roles of USP44 and CTCFL in GC cells.

Results

miR-98-5p was downregulated in GC. miR-98-5p overexpression inhibited the proliferation, migration, and invasion of GC cells. miR-98-5p inhibited USP44 expression. USP44 bound to CTCFL and limited ubiquitination degradation of CTCFL. Overexpression of USP44 and CTCFL attenuated the inhibitory effects of miR-98-5p overexpression on GC cell progression.

Conclusion

miR-98-5p overexpression limited USP44-mediated CTCFL deubiquitination, and suppressed CTCFL expression, mitigating GC cell proliferation, migration, and invasion.

LncRNA expression signature identified using genome-wide transcriptomic profiling to predict lymph node metastasis in patients with stage T1 and T2 gastric cancer

BACKGROUND

Lymph node (LN) status is vital to evaluate the curative potential of relatively early gastric cancer (GC; T1-T2) treatment (endoscopic or surgery). Currently, there is a lack of robust and convenient methods to identify LN metastasis before therapeutic decision-making.

METHODS

Genome-wide expression profiles of long noncoding RNA (lncRNA) in primary T1 gastric cancer data from The Cancer Genome Atlas (TCGA) was used to identify lncRNA expression signature capable of detecting LN metastasis of GC and establish a 10-lncRNA risk-prediction model based on deep learning. The performance of the lncRNA panel in diagnosing LN metastasis was evaluated both in silico and clinical validation methods. In silico validation was conducted using TCGA and Asian Cancer Research Group (ACRG) datasets. Clinical validation was performed on T1 and T2 patients, and the panel's efficacy was compared with that of traditional tumor markers and computed tomography (CT) scans.

RESULTS

Profiling of genome-wide RNA expression identified a panel of lncRNA to predict LN metastasis in T1 stage gastric cancer (AUC = 0.961). A 10-lncRNA risk-prediction model was then constructed, which was validated successfully in T1 and T2 datasets (TCGA, AUC = 0.852; ACRG, AUC = 0.834). Thereafter, the clinical performance of the lncRNA panel was validated in clinical cohorts (T1, AUC = 0.812; T2, AUC = 0.805; T1 + T2, AUC = 0.764). Notably, the panel demonstrated significantly better performance compared with CT and traditional tumor markers.

CONCLUSIONS

The novel 10-lncRNA could diagnose LN metastasis robustly in relatively early gastric cancer (T1-T2), with promising clinical potential.

Cell Cycle-Related lncRNAs as Innovative Targets to Advance Cancer Management

Long non-coding RNAs (lncRNAs) are non-coding RNAs (ncRNAs) longer than 200nt. They have complex biological functions and take part in multiple fundamental biological processes, such as cell proliferation, differentiation, survival and apoptosis. Recent studies suggest that lncRNAs modulate critical regulatory proteins involved in cancer cell cycle, such as cyclin, cell cycle protein-dependent kinases (CDK) and cell cycle protein-dependent kinase inhibitors (CKI) through different mechanisms. To clarify the role of lncRNAs in the regulation of cell cycle will provide new ideas for design of antitumor therapies which intervene with the cell cycle progression. In this paper, we review the recent studies about the controlling of lncRNAs on cell cycle related proteins such as cyclin, CDK and CKI in different cancers. We further outline the different mechanisms involved in this regulation and describe the emerging role of cell cycle-related lncRNAs in cancer diagnosis and therapy.