Long Noncoding RNA CTD-2589M5.4 Inhibits Ovarian Cancer Cell Proliferation, Migration, and Invasion Via Downregulation of the Extracellular Matrix-Receptor Interaction Pathway

Integrated analysis of scRNA-seq and bulk RNA-seq identifies FBXO2 as a candidate biomarker associated with chemoresistance in HGSOC

Background

High-grade serous ovarian carcinoma (HGSOC) is the most prevalent and aggressive histological subtype of epithelial ovarian cancer. Around 80% of individuals will experience a recurrence within five years because of resistance to chemotherapy, despite initially responding well to platinum-based treatment. Biomarkers associated with chemoresistance are desperately needed in clinical practice.

Methods

We jointly analyzed the transcriptomic profiles of single-cell and bulk datasets of HGSOC to identify cell types associated with chemoresistance. Copy number variation (CNV) inference was performed to identify malignant cells. We subsequently analyzed the expression of candidate biomarkers and their relationship with patients' prognosis. The enrichment analysis and potential biological function of candidate biomarkers were explored. Then, we validated the candidate biomarker using in vitro experiments.

Results

We identified 8871 malignant epithelial cells in a single-cell RNA sequencing dataset, of which 861 cells were associated with chemoresistance. Among these malignant epithelial cells, FBXO2 (F-box protein 2) is highly expressed in cells related to chemoresistance. Moreover, FBXO2 expression was found to be higher in epithelial cells from chemoresistance samples compared to those from chemosensitivity samples in a separate single-cell RNA sequencing dataset. Patients exhibiting elevated levels of FBXO2 experienced poorer outcomes in terms of both overall survival (OS) and progression-free survival (PFS). FBXO2 could impact chemoresistance by influencing the PI3K-Akt signaling pathway, focal adhesion, and ECM-receptor interactions and regulating tumorigenesis. The 50% maximum inhibitory concentration (IC50) of cisplatin decreased in A2780 and SKOV3 ovarian carcinoma cell lines with silenced FBXO2 during an in vitro experiment.

Conclusions

We determined that FBXO2 is a potential biomarker linked to chemoresistance in HGSOC by combining single-cell RNA-seq and bulk RNA-seq dataset. Our results suggest that FBXO2 could serve as a valuable prognostic marker and potential target for drug development in HGSOC.

LINC02489 with m6a modification increase paclitaxel sensitivity by inhibiting migration and invasion of ovarian cancer cells

The long non-coding RNA LINC02489 has been shown to be significantly downregulated in advanced ovarian cancer (OC). However, the function of LINC02489 remains unknown. This study aims to explain the role and mechanism of LINC02489 in OC. The expression of LINC02489 was examined by qRT-PCR in primary OC tissues. Additionally, MTT, wound healing, transwell, and flow cytometry assays were used to analyze the function of LINC02489. The mechanism of LINC02489 in OC was investigated by high-throughput RNA-sequencing, qRT-PCR, western blot, and N6-methyladenosine (m6A) meRIP. A total of 1101 and 827 genes are significantly down-regulated and up-regulated in metastatic and chemoresistant OC tissues. The expression of LINC02489 is decreased in metastatic and chemoresistant OC tissues compared with the primary OC tissues (p < 0.05). Overexpression of LINC02489 inhibits proliferation, invasion, and migration of drug-resistant OC cells. In the LINC02489 overexpressed chemoresistant SKOV3 cells, the m6A modified LINC02489 is significantly up-regulated. Furthermore, the expression of PKNOX2 is increased during overexpression of LINC02489, while the expression of PTEN and mTOR plummets. This study demonstrates that LINC02489 can inhibit the invasion and migration of chemoresistant OC cells by increasing its m6A modification and up-regulating PKNOX2 expression. In addition, LINC02489 regulates the invasion ability of OC cells through the PTEN/mTOR signaling pathway, thereby regulating the sensitivity of SKOV3 cells to paclitaxel. This result provides a potential therapeutic target for chemoresistant OC.

Comprehensive analysis to identify pseudogenes/lncRNAs-hsa-miR-200b-3p-COL5A2 network as a prognostic biomarker in gastric cancer

OBJECTIVE

Gastric cancer is one of the most common and deadly types of cancer. The molecular mechanism of gastric cancer progression remains unclear.

MATERIALS AND METHODS

Four hub genes were identified through GEO and TCGA database screening and analysis. Prognostic analysis revealed that COL5A2 was the most likely to affect the prognosis of gastric cancer among the four hub genes. The relationships between COL5A2 and clinical variables and immune cell infiltration were analyzed. Then, COL5A2 was analyzed for single-gene differences and related functional enrichment. Using the starBase database for prediction and analysis, miRNAs and pseudogenes/lncRNAs that might combine with COL5A2 were identified; thus, the ceRNA network was constructed. Finally, the network was verified by Cox analysis and qPCR, and a nomogram was constructed.

RESULTS

First, we found that COL5A2, COL12A1, BGN and THBS2 were highly expressed in gastric cancer. COL5A2 had statistical significance in overall survival (OS), disease-specific survival (DSS), and progression-free interval (PFI) analysis. Immune infiltration analysis suggested that COL5A2 might influence the changes in the tumor immune microenvironment. The StarBase database was used to predict that 3 pseudogenes and 7 lncRNAs might inhibit the hsa-miR-200b-3p-COL5A2 axis in gastric cancer. The pseudogenes/lncRNA-hsa-miR-200b-3p-COL5A2 ceRNA network was identified and verified using Cox regression analysis and PCR. Finally, we constructed a nomogram.

CONCLUSIONS

We elucidated the regulatory role of the pseudogenes/lncRNA-hsa-miR-200b-3p-COL5A2 network in gastric cancer progression and constructed a nomogram. These studies may provide effective treatments and potential prognostic biomarkers for gastric cancer.

A Novel Matrisomal-Related LncRNA Signature Associated With Survival Outcome and Immune Evasion in Patients With Gastric Cancer

Background

Different matrisomal patterns are shared across carcinomas. However, little is known about whether there exists a unique tumor matrisome that modulates GC progression and immune regulation.

Methods

We conducted a genome-wide analysis based on matrisomal-related lncRNAs (MRLs) in 375 patients with GC from the Cancer Genome Atlas (TCGA) database. Patients were split into the training set and validation set at a ratio of 1:1 using the R package cart. Pearson correlation analysis (PCA) was performed to identify lncRNAs that correlated with matrisome based on differential expression genes. Subsequently, we performed univariate Cox regression analyses and lasso Cox analysis on these lncRNAs to construct a risk model. Considering the primary effect of GRASLND on the GC prognosis, we chose it for further validation in an experimental setting.

Results

We identified a 15-MRL signature to predict overall survival and immune cell infiltration of patients with GC. The AUC values to predict 5-year outcome in three sets were 0.89, 0.65, and 0.78, respectively. Further analyses suggested that the high-risk group showed more obvious immune cell infiltration, and demonstrated an immunologically “cold” profile. In vitro, knockdown of GRASLND could inhibit the invasion capability of GC cells, and downregulate the protein expression of crucial matrisomal-related gene MMP9.

Conclusions

The 15-MRL gene signature might serve as a relatively good predictive tool to manage patients with GC.