Cation Lipid-Assisted PEG6-PLGA Polymer Nanoparticles Encapsulated Knocking Down Long ncRNAs Reverse Non-Coding RNA of Xist Through the Support Vector Machine Model to Regulate the Molecular Mechanisms of Gastric Cancer Cell Apoptosis

Retracted article: Functional analysis of ceRNA network of lncRNA TSIX/miR-34a-5p/RBP2 in acute myocardial infarction based on GEO database

Jiezhong Lin, Jianyi Zhou, Guiting Xie, Xiongwei Xie, Yanfang Luo and Jinguang Liu. Functional analysis of ceRNA network of lncRNA TSIX/miR-34a-5p/RBP2 in acute myocardial infarction based on GEO database. 2021 Oct. doi: 10.1080/21655979.2021.2006865.Since publication, significant concerns have been raised about the compliance with ethical policies for human research and the integrity of the data reported in the article.When approached for an explanation, the authors provided some original data but were not able to provide all the necessary supporting information. As verifying the validity of published work is core to the scholarly record's integrity, we are retracting the article. All authors listed in this publication have been informed.We have been informed in our decision-making by our editorial policies and the COPE guidelines.The retracted article will remain online to maintain the scholarly record, but it will be digitally watermarked on each page as 'Retracted.'

Nanomaterials-Based Targeting of Long Non-Coding RNAs in Cancer: A Cutting-Edge Review of Current Trends

This review article spotlights the burgeoning potential of using nanotherapeutic strategies to target long non-coding RNAs (lncRNAs) in cancer cells. This updated discourse underlines the prominent role of lncRNAs in instigating cancer, facilitating its progression, and metastasis, validating lncRNAs' potential for being effective diagnostic biomarkers and therapeutic targets. The manuscript offers an in-depth examination of different strategies presently employed to modulate lncRNA expression and function for therapeutic purposes. Among these strategies, Antisense Oligonucleotides (ASOs), RNA interference (RNAi) technologies, and the innovative clustered regularly interspaced short palindromic repeats (CRISPR)-based gene editing tools garner noteworthy mention. A significant section of the review is dedicated to nanocarriers and their crucial role in drug delivery. These nanocarriers' efficiency in targeting lncRNAs in varied types of cancers is elaborated upon, validating the importance of targeted therapy. The manuscript culminates by reaffirming the promising prospects of targeting lncRNAs to enhance the accuracy of cancer diagnosis and improve treatment efficacy. Consequently, new paths are opened to more research and innovation in employing nanotherapeutic approaches against lncRNAs in cancer cells. Thus, this comprehensive manuscript serves as a valuable resource that underscores the vital role of lncRNAs and the various nano-strategies for targeting them in cancer treatment. Future research should also focus on unraveling the complex regulatory networks involving lncRNAs and identifying fundamental functional interactions to refine therapeutic strategies targeting lncRNAs in cancer.

Transcription Analysis of the THBS2 Gene through Regulation by Potential Noncoding Diagnostic Biomarkers and Oncogenes of Gastric Cancer in the ECM-Receptor Interaction Signaling Pathway: Integrated System Biology and Experimental Investigation

Background

Gastric cancer (GC) is the second most frequent cause of cancer-related death worldwide and the fourth most common malignancy. Despite significant improvements in patient survival over the past few decades, the prognosis for patients with GC remains dismal because of the high recurrence rate. In this comprehensive system biology and experimental investigation, we aimed to find new novel diagnostic biomarkers of GC through a regulatory RNA interaction network.

Methods

Gene expression, coexpression, and survival analyses were performed using microarray and RNAseq datasets (analyzed by RStudio, GEPIA2, and ENCORI). RNA interaction analysis was performed using miRWalk and ENCORI online databases. Gene set enrichment analysis (GSEA) was performed to find related signaling pathways of up- and downregulated genes in the microarray dataset. Gene ontology and pathway enrichment analysis were performed by the enrichr database. Protein interaction analysis was performed by STRING online database. Validation of expression and coexpression analyses was performed using a qRT-PCR experiment.

Results

Based on bioinformatics analyses, THBS2 (FC: 7.14, FDR < 0.0001) has a significantly high expression in GC samples. lncRNAs BAIAP2-AS1, TSIX, and LINC01215 have RNA interaction with THBS2. BAIAP2-AS1 (FC: 1.44, FDR: 0.018), TSIX (FC: 1.34, FDR: 0.038), and LINC01215 (FC: 1.19, FDR: 0.046) have significant upregulation in GC samples. THBS2 has a significant role in the regulation of the ECM-receptor signaling pathway. miR-4677-5p has a significant RNA interaction with THBS2. The expression level of THBS2, BAIAP2-AS1, TSIX, and LINC01215 has a nonsignificant negative correlation with the survival rate of GC patients (HR: 0.28, logrank p: 0.28). qRT-PCR experiment validates mentioned bioinformatics expression analyses. BAIAP2-AS1 (AUC: 0.7136, p value: 0.0096), TSIX (AUC: 0.7456, p value: 0.0029), and LINC01215 (AUC: 0.7872, p value: 0.0005) could be acceptable diagnostic biomarkers of GC.

Conclusion

BAIAP2-AS1, lncRNA LINC01215, lncRNA TSIX, and miR-4677-5p might modulate the ECM-receptor signaling pathway via regulation of THBS2 expression level, as the high-expressed noncoding RNAs in GC. Furthermore, mentioned lncRNAs could be considered potential diagnostic biomarkers of GC.

The Application of Sensitive Nano-Confined Nanoparticle System Using siRNA Targeting Extracellular Signal-Regulated Kinase (ERK)/Mitogen-Activated Protein Kinase (MAPK) Pathway in Gastrointestinal Cancer

In this study we tried to develop a Sensitive Nano-Confined Nanoparticles (S-NCN) system using siRNA against Programmed death-ligand 1 (PDL-1) and Polo Like Kinase 1 (Plk1) to treat gastrointestinal cancer. In this regard, we first synthesized the corresponding materials, prepared the S-NCN system, and verified its functionality. Subsequently, we demonstrated in vitro that S-NCN delivery of siPlk1 could effectively downregulate the expression of Plk1 gene in GC1436 cells and lead to significant apoptosis of tumor cells. Xenografted gastrointestinal cancer model mice were used to evaluate the in vivo efficacy of the nanoparticle. We have demonstrated that the developed S-NCN system can efficiently bind siRNA and deliver it into target tumor cells, solving the main obstacle of siRNA delivery in vivo and effectively silencing target genes with a very potential delivery option.

Immune-Related lncRNA Pairs Clinical Prognosis Model Construction for Hepatocellular Carcinoma

Background

Long non-coding RNA (lncRNA) plays an essential regulatory role in the occurrence and development of hepatocellular carcinoma (HCC). This paper aims to establish an immune-related lncRNA (irlncRNA) pairs model independent of expression level for risk assessment and prognosis prediction of HCC.

Methods

Transcriptome data and corresponding clinical data were downloaded from TCGA. HCC patients were randomly divided into training group and test group. Univariate Cox regression analysis, LASSO regression analysis, and stepwise multiple Cox regression analysis were used to establish a prognostic model. The prediction ability of the model was verified by ROC curves. Next, the patients were divided into low-risk and high-risk groups. We compared the differences between the two groups in survival rate, clinicopathological characteristics, tumor immune cell infiltration status, chemotherapeutic drug sensitivity and immunosuppressive molecules.

Results

A prognosis prediction model was established based on 7 irlncRNA pairs, namely irlncRNA pairs (IRLP). ROC curves of the training group and test group showed that the IRLP model had high sensitivity and specificity for survival prediction. Kaplan–Meier analysis showed that the survival rate of the high-risk group was significantly lower than that of the low-risk group. Immune cell infiltration analysis showed that the high-risk group was significantly correlated with various immune cell infiltration. Finally, there were statistically significant differences in chemosensitivity and molecular marker expression between the two groups.

Conclusion

The prognosis prediction model established by irlncRNA pairs has a certain guiding significance for the prognosis prediction of HCC. It may provide valuable clinical applications in antitumor immunotherapy.