CDPath: Cooperative Driver Pathways Discovery Using Integer Linear Programming and Markov Clustering

Multi-omics pan-cancer study of SPTBN2 and its value as a potential therapeutic target in pancreatic cancer

SPTBN2 is a protein-coding gene that is closely related to the development of malignant tumors. However, its prognostic value and biological function in pan-cancer, especially pancreatic cancer (PAAD), have not been reported. In the present study, a novel exploration of the value and potential mechanism of SPTBN2 in PAAD was conducted using multi-omics in the background of pan-cancer. Via various database analysis, up-regulated expression of SPTBN2 was detected in most of the tumor tissues examined. Overexpression of SPTBN2 in PAAD and kidney renal clear cell cancer patients potentially affected overall survival, disease-specific survival, and progression-free interval. In PAAD, SPTBN2 can be used as an independent factor affecting prognosis. Mutations and amplification of SPTBN2 were detected, with abnormal methylation of SPTBN2 affecting its expression and the survival outcome of PAAD patients. Immunoassay results demonstrate that SPTBN2 was a potential biomarker for predicting therapeutic response in PAAD, and may influence the immunotherapy efficacy of PAAD by regulating levels of CD8 + T cells and neutrophil infiltration. Results from an enrichment analysis indicated that SPTBN2 may regulate the development of PAAD via immune pathways. Thus, SPTBN2 is a potential prognostic biomarker and immunotherapy target based on its crucial role in the development of PAAD.

Decreased SPTBN2 expression regulated by the ceRNA network is associated with poor prognosis and immune infiltration in low‑grade glioma

The majority of low-grade gliomas (LGGs) in adults invariably progress to glioblastoma over time. Spectrin β non-erythrocytic 2 (SPTBN2) is detected in numerous tumors and is involved in tumor occurrence and metastasis. However, the specific roles and detailed mechanisms of SPTBN2 in LGG are largely unknown. The present study performed pan-cancer analysis for the expression and prognosis of SPTBN2 in LGG using The Cancer Genome Atlas and The Genotype-Tissue Expression. Western blotting was used to detect the amount of SPTBN2 between glioma tissues and normal brain tissues. Subsequently, based on expression, prognosis, correlation and immune infiltration, non-coding RNAs (ncRNAs) were identified that regulated SPTBN2 expression. Finally, tumor immune infiltrates associated with SPTBN2 and prognosis were performed. Lower expression of SPTBN2 was correlated with an unfavorable outcome in LGG. A significant correlation between the low SPTBN2 mRNA expression and poor clinicopathological features was observed, including wild-type isocitrate dehydrogenase status (P<0.001), 1p/19q non-codeletion (P<0.001) and elders (P=0.019). The western blotting results revealed that, compared with normal brain tissues, the amount of SPTBN2 was significantly lower in LGG tissues (P=0.0266). Higher expression of five microRNAs (miRs/miRNAs), including hsa-miR-15a-5p, hsa-miR-15b-5p, hsa-miR-16-5p, hsa-miR-34c-5p and hsa-miR-424-5p, correlated with poor prognosis by targeting SPTBN2 in LGG. Subsequently, four long ncRNAs (lncRNAs) [ARMCX5-GPRASP2, BASP1-antisense RNA 1 (AS1), EPB41L4A-AS1 and LINC00641] were observed in the regulation of SPTBN2 via five miRNAs. Moreover, the expression of SPTBN2 was significantly correlated with tumor immune infiltration, immune checkpoint expression and biomarkers of immune cells. In conclusion, SPTBN2 was lowly expressed and correlated with an unfavorable prognosis in LGG. A total of six miRNAs and four lncRNAs were identified as being able to modulate SPTBN2 in a lncRNA-miRNA-mRNA network of LGG. Furthermore, the current findings also indicated that SPTBN2 possessed anti-tumor roles by regulating tumor immune infiltration and immune checkpoint expression.

SPTBN2 regulates endometroid ovarian cancer cell proliferation, invasion and migration via ITGB4‑mediated focal adhesion and ECM receptor signalling pathway

Ovarian cancer is as a major contributor to gynaecologic death globally. The present study aimed to investigate the regulatory role of spectrin β non-erythrocytic 2 gene (SPTBN2) in endometroid ovarian cancer and its mechanism of action. According to the Gene Expression Profiling Interactive Analysis (GEPIA) database, SPTBN2 expression is elevated in ovarian cancer tissues and higher SPTBN2 expression indicated a worse prognosis. The present study assessed SPTBN2 mRNA and protein expression levels by reverse transcription-quantitative PCR and western blotting, respectively. Cell viability, proliferation, migration and invasion were assessed with Cell Counting Kit-8, 5-ethynyl-2'-deoxyuridine incorporation, wound healing and Transwell assays, respectively. SPTBN2 expression was notably enhanced in ovarian cancer cell lines, especially in A2780 cells compared with HOSEPiC cells (P<0.001). Following transfection with small interfering (si)RNA targeting SPTBN2, the viability, proliferation, migration and invasion of A2780 cells were decreased compared with those of A2780 cells transfected with siRNA-NC (P<0.001). Gene Set Enrichment Analysis database revealed that SPTBN2 was primarily enriched in 'focal adhesion' and 'extracellular matrix (ECM)-receptor interaction', whereas SPTBN2 was significantly associated with integrin β4 (ITGB4) in the GEPIA database. In addition, rescue experiments were performed to determine the mechanism of SPTBN2 in endometroid ovarian cancer. ITGB4 overexpression reversed the inhibitory effects of the SPTBN2 knockdown on viability, proliferation, migration and invasion of A2780 cells (P<0.05). The impacts of SPTBN2 on the expression of focal adhesion and downstream ECM receptor signalling-related proteins, including Src and p-FAK/FAK, were significantly reversed by ITGB4 overexpression (P<0.01). Collectively, SPTBN2 may regulate endometroid ovarian cancer cell proliferation, invasion and migration through the ITGB4-mediated focal adhesion and ECM receptor signalling pathway.

Investigating the evolution process of lung adenocarcinoma via random walk and dynamic network analysis

Lung adenocarcinoma (LUAD) is a typical disease regarded as having multi-stage progression. However, many existing methods often ignore the critical differences among these stages, thereby limiting their effectiveness for discovering key biological molecules and biological functions as signals at each stage. In this study, we propose a method to discover the evolution between biological molecules and biological functions by investigating the multi-stage biological molecules of LUAD. The method is based on the random walk algorithm and the Monte Carlo method to generate clusters as the modules, which were used as subgraphs of the differentiated biological molecules network in each stage. The connection between modules of adjacent stages is based on the measurement of the Jaccard coefficient. The online gene set enrichment analysis tool (DAVID) was used to obtain biological functions corresponding to the individual important modules. The core evolution network was constructed by combining the aforementioned two networks. Since the networks here are all dynamic, we also propose a strategy to visualize the dynamic information together in one network. Eventually, 12 core modules and 11 core biological functions were found through such evolutionary analyses. Among the core biological functions that we obtained, six functions are related to the disease, the biological function of neutrophil chemotaxis is not directly associated with LUAD but can serve as a predictor, two functions may serve as a predictive signal, and two functions need to be verified through more biological evidence. Compared with two alternative design methods, the method proposed in this study performed more efficiently.

CERS6-AS1 contributes to the malignant phenotypes of colorectal cancer cells by interacting with miR-15b-5p to regulate SPTBN2

Accumulating evidence indicates that long noncoding RNAs (lncRNAs) act as tumor promoters or suppressors in various types of cancer. Previous investigations suggest that ceramide synthase 6 (CERS6) antisense RNA 1 (CERS6-AS1) acts as an oncogene in breast cancer; however, its role in colorectal cancer is unknown. This study aimed to explore the molecular mechanism of CERS6-AS1 in colorectal cancer. Gene expression in colorectal cancer was examined using reverse transcription-quantitative polymerase chain reaction and western blot analyses. The viability and proliferation of colorectal cancer cells were measured by Cell Counting Kit-8 assays and colony formation assays. The migratory and invasive capacities of the colorectal cancer cells were assessed by Transwell assay. Cell stemness was examined by sphere-formation assay. Mechanistically, RNA pull-down assays, RNA immunoprecipitation assays, and luciferase reporter assays were performed to explore the relationship among CERS6-AS1, miR-15b-5p and spectrin beta, non-erythrocytic 2 (SPTBN2). Moreover, a xenograft tumor model was established to investigate the role of CERS6-AS1 in vivo. We found that CERS6-AS1 and SPTBN2 were highly expressed in colorectal cancer tissues and cells. CERS6-AS1 depletion inhibited cell viability, proliferation, migration, and invasion; the epithelial-mesenchymal transition process and stemness. It suppressed xenograft tumor growth in colorectal cancer. Moreover, SPTBN2 levels were positively regulated by CERS6-AS1 and negatively regulated by miR-15b-5p in colorectal cancer cells. Rescue assays revealed that SPTBN2 reversed the inhibitory effect of CERS6-AS1 deficiency on the malignant behaviors of colorectal cancer cells. Overall, the lncRNA CERS6-AS1 facilitates malignant phenotypes of colorectal cancer cells by targeting miR-15b-5p to upregulate SPTBN2.

An Algorithm to Mine Therapeutic Motifs for Cancer from Networks of Genetic Interactions

Study of pairwise genetic interactions, such as mutually exclusive mutations, has led to understanding of underlying mechanisms in cancer. Investigation of various combinatorial motifs within networks of such interactions can lead to deeper insights into its mutational landscape and inform therapy development. One such motif called the Between-Pathway Model (BPM) represents redundant or compensatory pathways that can be therapeutically exploited. Finding such BPM motifs is challenging since most formulations require solving variants of the NP-complete maximum weight bipartite subgraph problem. In this paper we design an algorithm based on Integer Linear Programming (ILP) to solve this problem. In our experiments, our approach outperforms the best previous method to mine BPM motifs. Further, our ILP-based approach allows us to easily model additional application-specific constraints. We illustrate this advantage through a new application of BPM motifs that can potentially aid in finding combination therapies to combat cancer.

SPTBN2, a New Biomarker of Lung Adenocarcinoma

Objectives

The roles played by β-III-spectrin, also known as spectrin beta, non-erythrocytic 2 (SPTBN2), in the occurrence and development of lung adenocarcinoma (LUAD) have not been previously examined. Our study aimed to reveal the relationship between the SPTBN2 expression and LUAD.

Materials and Methods

Twenty pairs of LUAD tissues and adjacent tissues were collected from patients diagnosed and treated at the Thoracic Surgery Department of The First Affiliated Hospital of Zhengzhou University from July 2019 to September 2020. RNA sequencing (RNA-seq) analysis determined that the expression of SPTBN2 was higher in LUAD samples than in adjacent normal tissues. The expression levels of SPTBN2 were examined in various databases, including the Cancer Cell Line Encyclopedia (CCLE), Gene Expression Omnibus (GEO), and Human Protein Atlas (HPA). The Search Tool for the Retrieval of Interacting Genes (STRING) online website was used to examine protein–protein interactions involving SPTBN2, and the results were visualized by Cytoscape software. The Molecular Complex Detection (MCODE) plug-in for Cytoscape software was used to identify functional modules of the obtained protein–protein interaction (PPI) network. Gene enrichment analysis was performed, and survival analysis was conducted using the Kaplan–Meier plotter. The online prediction website TargetScan was used to predict SPTBN2-targeted miRNA sequences by searching for SPTBN2 sequences. Finally, we verified the expression of SPTBN2 in the obtained tissue samples using real-time fluorescence quantitative polymerase chain reaction (RT-qPCR). The human lung cancer cell lines A549 and H1299 were selected for the transfection of small interfering RNA (siRNA) targeting SPTBN2 (si-SPTBN2), and the knockdown efficiency was evaluated by RT-qPCR. The cellular proliferation, migration, and invasion capacities of A549 and H1299 cells were determined using the cell counting kit-8 (CCK-8) proliferation assay; the wound-healing assay and the Transwell migration assay; and the Matrigel invasion assay, respectively.

Results

The expression of SPTBN2 in non–small cell lung cancer (NSCLC) ranked 13th among cancer cell lines based on the CCLE database. At the mRNA and protein levels, the expression levels of SPTBN2 were higher in LUAD tissues than in normal lung tissues. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that proteins related to SPTBN2 were enriched in apoptotic and phagosomal pathways. Kaplan–Meier survival analysis revealed that SPTBN2 expression was significantly related to the prognosis of patients with LUAD. The TargetScan database verified that miR-16 was a negative regulator of SPTBN2 mRNA expression. The results of the CCK-8 cell proliferation assay revealed that SPTBN2 knockdown significantly inhibited the cell proliferation abilities of A549 and H1299 cells. The wound-healing assay indicated that SPTBN2 knockdown resulted in reduced migration after 48 h compared with the control group. The Transwell migration and invasion test revealed that the migration and invasion abilities were greatly decreased by SPTBN2 knockdown compared with control conditions.

Conclusion

We uncovered a novel gene, SPTBN2, that was significantly upregulated in LUAD tissues relative to normal tissue expression. SPTBN2 is highly expressed in LUAD, positively correlated with poor prognosis, and can promote the proliferation, migration, and invasion of LUAD cells.