MEOX1 suppresses the progression of lung cancer cells by inhibiting the cell-cycle checkpoint gene CCNB1

The TEAD4-DYNLL1 axis accelerates cell cycle progression and augments malignant properties of lung adenocarcinoma cells

BACKGROUND

Lung adenocarcinoma (LUAD) is a major contributor to global mortality. Grounded onto bioinformatics insights, this study probes the functions of dynein light chain LC8-type 1 (DYNLL1) in LUAD progression.

METHODS

DYNLL1 levels in LUAD and normal cells were determined using qPCR and western blotting analyses. Lentiviral plasmids-mediated DYNLL1 silencing was induced in LUAD cells, followed by functional assays to investigate DYNLL1's impacts on proliferation, mobility, apoptosis, and cell cycle distribution. KY19382, a Wnt/β-catenin agonist, was employed to analyze the involvement of the Wnt/β-catenin pathway in DYNLL1's effects. Upstream regulator of DYNLL1 was queried using bioinformatics. Mouse LUAD cells LA795 were implanted into BALB/c nude mice to establish animal tumor models.

RESULTS

DYNLL1 exhibited heightened expression in LUAD cells. Its artificial silencing reduced proliferation and dissemination of cancer cells, promoted cell apoptosis, and induced G0/G1 cell cycle arrest. DYNLL1 silencing reduced β-catenin levels in cancer cells, and KY19382 treatment diminished the effects induced by DYNLL1 silencing. TEA domain transcription factor 4 (TEAD4), upregulated in LUAD cells, binds to the DUNLL1 promoter for transcriptional activation. TEAD4 silencing in LUAD cells reduced DYNLL1 transcription and β-catenin levels, thus suppressing proliferation while promoting apoptosis, senescence, and cell cycle arrest. In vivo, TEAD4 silencing weakened tumorigenesis of LA795 cells. Nevertheless, these phenomena were counteracted by the artificial DYNLL1 restoration in LUAD cells.

CONCLUSION

This investigation demonstrates a TEAD4-DYNLL1 axis that accelerates cell cycle progression and augments malignant properties of LUAD cells via the Wnt/β-catenin pathway.

Mechanism of multifunctional adaptor protein SHARPIN regulating myocardial fibrosis and how SNP mutation affect the prognosis of myocardial infarction

Myocardial fibrosis (MF) is characterized by the excessive deposition of extracellular matrix within the heart, often following a cardiovascular insult. SHARPIN, a protein implicated in fibrosis, has emerged as a potential therapeutic target. This study aimed to elucidate the molecular mechanisms of SHARPIN in MF and to investigate the influence of its single nucleotide polymorphism (SNP), rs117299156, on myocardial infarction (MI) patients. A mouse model of Angiotensin II (AngII)-induced MF was established in SHARPIN heterozygous (SHARPIN+/-) and wild-type mice. Adult mouse cardiac fibroblasts (CFs) were isolated and subjected to adenovirus-encapsulated SHARPIN short hairpin RNA (shRNA) infection. Transcriptomic analysis was performed on CFs from SHARPIN+/- and wild-type (WT) mice, complemented by single-cell sequencing data from human cardiac tissues. Additionally, the association between the rs117299156 mutation and cardiovascular events in MI patients was assessed. Our findings indicate that SHARPIN is predominantly expressed in CFs and is upregulated in fibrotic myocardium. Partial knockdown of SHARPIN in murine hearts mitigated AngII-induced cardiac dysfunction and MF. Furthermore, reduced SHARPIN expression in CFs attenuated TGF-β1-induced collagen synthesis, cell proliferation, and myofibroblast transformation. Notably, MI patients carrying the rs117299156_C allele exhibited a reduced incidence of stroke events compared to those without the mutation.

Multi-omics characterization and machine learning of lung adenocarcinoma molecular subtypes to guide precise chemotherapy and immunotherapy

Background

Lung adenocarcinoma (LUAD) is a heterogeneous tumor characterized by diverse genetic and molecular alterations. Developing a multi-omics-based classification system for LUAD is urgently needed to advance biological understanding.

Methods

Data on clinical and pathological characteristics, genetic alterations, DNA methylation patterns, and the expression of mRNA, lncRNA, and microRNA, along with somatic mutations in LUAD patients, were gathered from the TCGA and GEO datasets. A computational workflow was utilized to merge multi-omics data from LUAD patients through 10 clustering techniques, which were paired with 10 machine learning methods to pinpoint detailed molecular subgroups and refine a prognostic risk model. The disparities in somatic mutations, copy number alterations, and immune cell infiltration between high- and low-risk groups were assessed. The effectiveness of immunotherapy in patients was evaluated through the TIDE and SubMap algorithms, supplemented by data from various immunotherapy groups. Furthermore, the Cancer Therapeutics Response Portal (CTRP) and the PRISM Repurposing dataset (PRISM) were employed to investigate new drug treatment approaches for LUAD. In the end, the role of SLC2A1 in tumor dynamics was examined using RT-PCR, immunohistochemistry, CCK-8, wound healing, and transwell tests.

Results

By employing multi-omics clustering, we discovered two unique cancer subtypes (CSs) linked to prognosis, with CS2 demonstrating a better outcome. A strong model made up of 17 genes was created using a random survival forest (RSF) method, which turned out to be an independent predictor of overall survival and showed reliable and impressive performance. The low-risk group not only had a better prognosis but also was more likely to display the "cold tumor" phenotype. On the other hand, individuals in the high-risk group showed a worse outlook and were more likely to respond positively to immunotherapy and six particular chemotherapy medications. Laboratory cell tests demonstrated that SLC2A1 is abundantly present in LUAD tissues and cells, greatly enhancing the proliferation and movement of LUAD cells.

Conclusions

Thorough examination of multi-omics data offers vital understanding and improves the molecular categorization of LUAD. Utilizing a powerful machine learning system, we highlight the immense potential of the riskscore in providing individualized risk evaluations and customized treatment suggestions for LUAD patients.

The role of HGH1 in breast cancer prognosis: a study on immune response and cell cycle

BACKGROUND

Breast cancer (BRCA) remains to be among the main causes of cancer-associated mortality in women globally. HGH1 homolog (HGH1) has been reported to be associated with tumor immunity. However, the function of HGH1 in BRCA remains unclear. Therefore, the present study examined the potential role of HGH1 in BRCA.

METHODS

The Cancer Genome Atlas (TCGA) databases and Gene Expression Omnibus (GEO) were used to obtain RNA-seq data for BRCA. A protein localization of HGH1 was determined by using the Human Protein Atlas (HPA), and immunohistochemistry (IHC) staining revealed an upregulation in the expression of HGH1 in clinical BRCA tissues. Xenograft mice were used to test tumor growth and HGH1 expression in breast cancer cells. The protein interaction information of HGH1 was analyzed using the GeneMANIA website. Based on univariate Cox regression and Kaplan-Meier methods, we evaluated the role of HGH1 in BRCA prognosis. HGH1-related differentially expressed genes were analyzed using GO, KEGG, and GSEA. We also examined the relationship between HGH1 expression, immune checkpoints, and immune infiltration. CCK-8, EdU, and colony formation assays were used to measure cell proliferation, and western blot analysis was used to evaluate HGH1's role in BRCA.

RESULTS

IHC results showed that the expression of HGH1 was significantly upregulated in BRCA tissues compared to normal tissues. High levels of HGH1 expression was associated with worse clinical features and a worse prognosis. HGH1 expression was an independent predictor of BRCA outcomes in both univariate and multivariate analyses. Functionally, western blot analysis showed that HGH1 is implicated in cell cycle. As well, knocking down HGH1 significantly reduced BRCA cells' proliferative abilities. Crucially, HGH1 expression levels were positively correlated with Th2 cell infiltration and negatively correlated with Tcm cell infiltration.

CONCLUSION

Biomarkers such as HGH1 can reliably predict prognosis in BRCA patients.

Regulatory Role of Meox1 in Muscle Growth of Sebastes schlegelii

Meox1 is a critical transcription factor that plays a pivotal role in embryogenesis and muscle development. It has been established as a marker gene for growth-specific muscle stem cells in zebrafish. In this study, we identified the SsMeox1 gene in a large teleost fish, Sebastes schlegelii. Through in situ hybridization and histological analysis, we discovered that SsMeox1 can be employed as a specific marker of growth-specific muscle stem cells, which originate from the somite stage and are primarily situated in the external cell layer (ECL) and myosepta, with a minor population distributed among muscle fibers. The knockdown of SsMeox1 resulted in a significant increase in Ccnb1 expression, subsequently promoting cell cycle progression and potentially accelerating the depletion of the stem cell pool, which ultimately led to significant growth retardation. These findings suggest that SsMeox1 arrests the cell cycle of growth-specific muscle stem cells in the G2 phase by suppressing Ccnb1 expression, which is essential for maintaining the stability of the growth-specific muscle stem cell pool. Our study provides significant insights into the molecular mechanisms underlying the indeterminate growth of large teleosts.

Naringenin nanoparticles targeting cyclin B1 suppress the progression of rheumatoid arthritis-associated lung cancer by inhibiting fibroblast-to-myofibroblast transition

There is growing evidence of an elevated risk of lung cancer in patients with rheumatoid arthritis. The poor prognosis of rheumatoid arthritis-associated lung cancer and the lack of therapeutic options pose an even greater challenge to the clinical management of patients. This study aimed to identify potential molecular targets associated with the progression of rheumatoid arthritis-associated lung cancer and examine the efficacy of naringenin nanoparticles targeting cyclin B1. Mendelian randomizatio analysis revealed that rheumatoid arthritis has a positive correlation with the risk of lung cancer. Cyclin B1 was significantly upregulated in patients with rheumatoid arthritis-associated lung cancer and was significantly overexpressed in synovial tissue fibroblasts. Furthermore, the overexpression of cyclin B1 in rheumatoid arthritis fibroblast-like synoviocytes, which promotes their proliferation and fibroblast-to-myofibroblast transition, can significantly contribute to the growth and infiltration of lung cancer cells. Importantly, our prepared naringenin nanoparticles targeting cyclin B1 effectively attenuated proliferation and fibroblast-to-myofibroblast transition by blocking cells at the G2/M phase. In vivo experiments, naringenin nanoparticles targeting cyclin B1 significantly alleviated the development of collagen-induced arthritis and lung orthotopic tumors. Collectively, our results reveal that naringenin nanoparticles targeting cyclin B1 can suppress the progression of rheumatoid arthritis-associated lung cancer by inhibiting fibroblast-to-myofibroblast transition. These findings provide new insights into the treatment of rheumatoid arthritis-associated lung cancer therapy.

Unraveling the molecular mechanisms of lymph node metastasis in ovarian cancer: focus on MEOX1

BACKGROUND

Lymph node metastasis (LNM) is a major factor contributing to the high mortality rate of ovarian cancer, making the treatment of this disease challenging. However, the molecular mechanism underlying LNM in ovarian cancer is still not well understood, posing a significant obstacle to overcome.

RESULTS

Through data mining from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, we have identified MEOX1 as a specific gene associated with LNM in ovarian cancer. The expression of MEOX1 was found to be relatively high in serous ovarian adenocarcinoma, and its higher expression were associated with increased tumor grade and poorer clinical prognosis for ovarian cancer patients. Bioinformatics analysis revealed that MEOX1 exhibited the highest mRNA levels among all cancer types in ovarian cancer tissues and cell lines. Furthermore, gene set enrichment analysis (GSEA) and pathway analysis demonstrated that MEOX1 was involved in various LNM-related biological activities, such as lymphangiogenesis, lymphatic vessel formation during metastasis, epithelial-mesenchymal transition (EMT), G2/M checkpoint, degradation of extracellular matrix, and collagen formation. Additionally, the expression of MEOX1 was positively correlated with the expression of numerous prolymphangiogenic factors in ovarian cancer. To validate our findings, we conducted experiments using clinical tissue specimens and cell lines, which confirmed that MEOX1 was highly expressed in high-grade serous ovarian cancer (HGSOC) tissues and various ovarian cancer cell lines (A2780, SKOV3, HO8910, and OVCAR5) compared to normal ovarian tissues and normal ovarian epithelial cell line IOSE-80, respectively. Notably, we observed a higher protein level of MEOX1 in tumor tissues of LNM-positive HGSOC compared to LNM-negative HGSOC. Moreover, our fundamental experiments demonstrated that suppression of MEOX1 led to inhibitory effects on ovarian cancer cell proliferation and EMT, while overexpression of MEOX1 enhanced the proliferation and EMT capacities of ovarian cancer cells.

CONCLUSIONS

The results of our study indicate that MEOX1 plays a role in the lymph node metastasis of ovarian cancer by regulating multiple biological activities, including the proliferation and EMT of ovarian cancer, lymphangiogenesis, and ECM remodeling. Our findings suggest that MEOX1 could serve as a potential biomarker for the diagnosis and treatment of ovarian cancer with LNM.

Long non-coding RNA NRAV in the 12q24.31 risk locus drives gastric cancer development through glucose metabolism reprogramming

Long non-coding RNAs (lncRNAs) serve as vital candidates to mediate cancer risk. Here, we aimed to identify the risk single-nucleotide polymorphisms (SNPs)-induced lncRNAs and to investigate their roles in gastric cancer (GC) development. Through integrating the differential expression analysis of lncRNAs in GC tissues and expression quantitative trait loci analysis in normal stomach tissues and GC tissues, as well as genetic association analysis based on GC genome-wide association studies and an independent validation study, we identified four lncRNA-related SNPs consistently associated with GC risk, including SNHG7 [odds ratio (OR) = 1.16, 95% confidence interval (CI): 1.09-1.23], NRAV (OR = 1.11, 95% CI: 1.05-1.17), LINC01082 (OR = 1.16, 95% CI: 1.08-1.22) and FENDRR (OR = 1.16, 95% CI: 1.07-1.25). We further found that a functional SNP rs6489786 at 12q24.31 increases binding of MEOX1 or MEOX2 at a distal enhancer and results in up-regulation of NRAV. The functional assays revealed that NRAV accelerates GC cell proliferation while inhibits GC cell apoptosis. Mechanistically, NRAV decreases the expression of key subunit genes through the electron transport chain, thereby driving the glucose metabolism reprogramming from aerobic respiration to glycolysis. These findings suggest that regulating lncRNA expression is a crucial mechanism for risk-associated variants in promoting GC development.

New perspectives on the potential of tetrandrine in the treatment of non-small cell lung cancer: bioinformatics, Mendelian randomization study and experimental investigation

BACKGROUND

Although there are numerous treatment methods for NSCLC, long-term survival remains a challenge for patients. The objective of this study is to investigate the role and causal relationship between the target of tetrandrine and non-small cell lung cancer (NSCLC) through transcriptome and single-cell sequencing data, summary-data-based Mendelian Randomization (SMR) and basic experiments. The aim is to provide a new perspective for the treatment of NSCLC.

METHODS

We obtained the drug target gene of tetrandrine through the drug database, and then used the GSE19188 data set to obtain the NSCLC pathogenic gene, established a drug-disease gene interaction network, screened out the hub drug-disease gene, and performed bioinformatics and tumor cell immune infiltration analysis. Single-cell sequencing data (GSE148071) to determine gene location, SMR to clarify causality and drug experiment verification.

RESULTS

10 drug-disease genes were obtained from 213 drug targets and 529 disease genes. DO/GO/KEGG analysis showed that the above genes were all related to the progression and invasion of NSCLC. Four drug-disease genes were identified from a drug-disease PPI network. These four genes were highly expressed in tumors and positively correlated with plasma cells, T cells, and macrophages. Subsequent single-cell sequencing data confirmed that these four genes were distributed in epithelial cells, and SMR analysis revealed the causal relationship between CCNA2 and CCNB1 and the development of NSCLC. The final molecular docking and drug experiments showed that CCNA2 and CCNB1 are key targets for tetrandrine in the treatment of NSCLC.

The Tumor Stemness Indice mRNAsi can Act as Molecular Typing Tool for Lung Adenocarcinoma

Due to the high heterogeneity, lung adenocarcinoma (LUAD) cannot be distinguished into precise molecular subtypes, thereby resulting in poor therapeutic effect and low 5-year survival rate clinically. Although the tumor stemness score (mRNAsi) has been shown to accurately characterize the similarity index of cancer stem cells (CSCs), whether mRNAsi can serve as an effective molecular typing tool for LUAD isn't reported to date. In this study, we first demonstrate that mRNAsi is significantly correlated with the prognosis and disease degree of LUAD patients, i.e., the higher the mRNAsi, the worse the prognosis and the higher the disease degree. Second, we identify 449 mRNAsi-related genes based on both weighted gene co-expression network analysis (WGCNA) and univariate regression analysis. Third, our results display that 449 mRNAsi-related genes can accurately distinguish the LUAD patients into two molecular subtypes: ms-H subtype (with high mRNAsi) and ms-L subtype (with low mRNAsi), particularly the ms-H subtype has a worse prognosis. Remarkably, significant differences in clinical characteristics, immune microenvironment, and somatic mutation exist between the two molecular subtypes, which might lead to the poorer prognosis of the ms-H subtype patients than that of the ms-L subtype ones. Finally, we establish a prognostic model containing 8 mRNAsi-related genes, which can effectively predict the survival rate of LUAD patients. Taken together, our work provides the first molecular subtype related to mRNAsi in LUAD, and reveals that these two molecular subtypes, the prognostic model and marker genes may have important clinical value for effectively monitoring and treating LUAD patients.

Squalene epoxidase promotes breast cancer progression by regulating CCNB1 protein stability

BACKGROUND

Breast cancer (BC) is a prevalent malignancy affecting women, characterized by a substantial occurrence rate. Squalene epoxidase (SQLE) is a crucial regulator of ferroptosis and has been associated with promoting cell growth and invasion in different types of human cancers. This study aimed to investigate the functional significance of SQLE in BC and elucidate the underlying molecular mechanisms involved.

METHODS

SQLE expression levels in BC tissues were evaluated using quantitative real-time polymerase chain reaction, western blotting, and immunohistochemistry. Cell viability, invasion, migration, and cell cycle distribution were assessed using a combination of assays, including the Cell Counting Kit-8, EdU, colony formation, Transwell, and wound healing assays and flow cytometry analysis. Measurement of intracellular reactive oxygen species (ROS), malondialdehyde assay, and glutathione assay were utilized to investigate ferroptosis. Furthermore, co-immunoprecipitation and immunofluorescence assays were conducted to explore the correlation between SQLE and CCNB1. The in vivo tumor growth was evaluated by conducting a xenograft tumorigenicity assay to investigate the impact of SQLE.

RESULTS

SQLE expression was significantly increased in BC, and higher SQLE expression levels were significantly associated with an unfavorable prognosis. In vitro functional assays revealed that the overexpression of SQLE markedly enhanced the proliferation, migration, and invasion capacities of BC cells. Furthermore, SQLE overexpression facilitated tumor growth in nude mice. Mechanistically, SQLE alleviated the ubiquitination modification of CCNB1, leading to enhanced stability of the CCNB1 protein and decreased intracellular ROS levels. Ultimately, this inhibited ferroptosis and facilitated the progression of BC. Our findings have provided insights into a crucial pathway by which elevated SQLE expression confers protection to BC cells against ferroptosis, thus promoting cancer progression. SQLE may serve as a novel oncological marker and a potential therapeutic target for BC progression.

CONCLUSIONS

In conclusion, this study provides evidence that SQLE plays a regulatory role in BC progression by modulating CCNB1 and ferroptosis. These findings offer valuable insights into the role of SQLE in the pathogenesis of BC and demonstrate its potential as a therapeutic target for treating BC.

Phosphorylation of Bcl-2 by JNK confers gemcitabine resistance in lung cancer cells by reducing autophagy-mediated cell death

The most common cancer-related death in the world is non-small cell lung cancer (NSCLC). Gemcitabine (GEM) is a common and effective first-line chemotherapeutic drug for the treatment of NSCLC. However, the long-term use of chemotherapeutic drugs in patients usually induces cancer cell drug resistance, leading to poor survival, and prognosis. In this study, to observe and explore the key targets and potential mechanisms of NSCLC resistance to GEM, we first cultured lung cancer CL1-0 cells in a GEM-containing medium to induce CL1-0 cells to develop GEM resistance. Next, we compared protein expression between the parental and GEM-R CL1-0 cell groups. We observed significantly lower expression of autophagy-related proteins in GEM-R CL1-0 cells than in parental CL1-0 cells, indicating that autophagy is associated with GEM resistance in CL1-0 cells. Furthermore, a series of autophagy experiments revealed that GEM-R CL1-0 cells had significantly reduced GEM-induced c-Jun N-terminal kinase phosphorylation, which further affected the phosphorylation of Bcl-2, thereby reducing the dissociation of Bcl-2 and Beclin-1 and ultimately reducing the generation of GEM-induced autophagy-dependent cell death. Our findings suggest that altering the expression of autophagy is a promising therapeutic option for drug-resistant lung cancer.

EPN3 plays oncogenic role in non-small cell lung cancer by activating the JAK1/2-STAT3 pathway

The effect of Epsin 3 (EPN3) on non-small cell lung cancer (NSCLC) has not yet been clearly elucidated. This study identified the exact function of EPN3 on NSCLC progression. EPN3 expression in NSCLC patients were analyzed based on the Cancer Genome Atlas database. Kaplan-Meier analysis was implemented to research the effect of EPN3 on patients' survival. EPN3 expression in clinical tissues of 62 NSCLC cases was monitored by real-time quantitative reverse transcription polymerase chain reaction, immunohistochemistry and Western blot. A549 and H1299 cells were transfected with EPN3 shRNA and treated by RO8191 (20 μM). Proliferation was researched by cell counting kit-8 and 5-ethnyl-2 deoxyuridine assays. Apoptosis was monitored by flow cytometry. Migration and invasion was assessed by Transwell experiment. EPN3 effect on A549 cell in vivo growth was researched using nude mice. RO8191 (200 μg) was intratumoral injected into mice. Immunohistochemistry and Western blot was implemented to monitor protein expression in cells and xenograft tumor tissues. EPN3 was abnormally up-regulated in NSCLC patients and cells, indicating a lower overall survival. Loss of EPN3 weakened proliferation, migration and invasion, induced apoptosis, and repressed epithelial-mesenchymal transition in NSCLC cells. Loss of EPN3 inactivated the JAK1/2-STAT3 pathway in NSCLC cells. RO8191 treatment reversed the inhibition of EPN3 knockdown on the malignant phenotype of NSCLC cells. RO8191 intratumoral injection reversed the suppression of EPN3 silencing on NSCLC cell in vivo growth. EPN3 acted as an oncogene in NSCLC via activating the JAK1/2-STAT3 pathway. EPN3 may be a promising target for NSCLC treatment.

The role of MEOX1 in non-neoplastic and neoplastic diseases

Targeted gene therapy has shown durable efficacy in non-neoplastic and neoplastic patients. Therefore, finding a suitable target has become a key area of research. Mesenchyme homeobox 1 (MEOX1) is a transcriptional factor that plays a significant role in regulation of somite development. Evidence indicates that abnormalities in MEOX1 expression and function are associated with a variety of pathologies, including non-neoplastic and neoplastic diseases. MEOX1 expression is upregulated during progression of most diseases and plays a critical role in maintenance of the cellular phenotypes such as cell differentiation, cell cycle arrest and senescence, migration, and proliferation. Therefore, MEOX1 may become an important molecular target and therapeutic target. This review will discuss the current state of knowledge on the role of MEOX1 in different diseases.

Identification of Potential Key Genes and Prognostic Biomarkers of Lung Cancer Based on Bioinformatics

Objective

To analyze and identify the core genes related to the expression and prognosis of lung cancer including lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) by bioinformatics technology, with the aim of providing a reference for clinical treatment.

Methods

Five sets of gene chips, GSE7670, GSE151102, GSE33532, GSE43458, and GSE19804, were obtained from the Gene Expression Omnibus (GEO) database. After using GEO2R to analyze the differentially expressed genes (DEGs) between lung cancer and normal tissues online, the common DEGs of the five sets of chips were obtained using a Venn online tool and imported into the Database for Annotation, Visualization, and Integrated Discovery (DAVID) database for Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. The protein-protein interaction (PPI) network was constructed by STRING online software for further study, and the core genes were determined by Cytoscape software and KEGG pathway enrichment analysis. The clustering heat map was drawn by Excel software to verify its accuracy. In addition, we used the University of Alabama at Birmingham Cancer (UALCAN) website to analyze the expression of core genes in P53 mutation status, confirmed the expression of crucial core genes in lung cancer tissues with Gene Expression Profiling Interactive Analysis (GEPIA) and GEPIA2 online software, and evaluated their prognostic value in lung cancer patients with the Kaplan-Meier online plotter tool.

Results

CHEK1, CCNB1, CCNB2, and CDK1 were selected. The expression levels of these four genes in lung cancer tissues were significantly higher than those in normal tissues. Their increased expression was negatively correlated with lung cancer patients (including LUAD and LUSC) prognosis and survival rate.

Conclusion

CHEK1, CCNB1, CCNB2, and CDK1 are the critical core genes of lung cancer and are highly expressed in lung cancer. They are negatively correlated with the prognosis of lung cancer patients (including LUAD and LUSC) and closely related to the formation and prediction of lung cancer. They are valuable predictors and may be predictive biomarkers of lung cancer.

CircPVT1 promotes the tumorigenesis and metastasis of osteosarcoma via mediation of miR-26b-5p/CCNB1 axis

INTRODUCTION

Osteosarcoma (OS) is the most aggressive malignancy among the bone tumors in the world. Circular RNAs (circRNAs) have been reported to be participated in multiple cancers, including OS. Meanwhile, circPVT1 has been proved to be upregulated in OS. However, the mechanism by which circPVT1 mediates the tumorigenesis of OS remains to be further explored.

MATERIALS AND METHODS

Protein and gene expressions in OS cells were measured by western blot and RT-qPCR, respectively. Cell growth was assessed by flow cytometry and colony formation, respectively. In addition, cell migration was assessed by wound healing, and invasion was evaluated by Transwell assay. Meanwhile, the correlation among circPVT1, miR-26b-5p and CCNB1 was explored by RNA pull-down and dual luciferase assay. Finally, in vivo model was established to explore the role of circPVT1 in OS in vivo.

RESULTS

CircPVT1 and CCNB1 were significantly upregulated in OS cells, while miR-26b-5p was downregulated. Knockdown of circPVT1 notably inhibited proliferation and induced apoptosis of OS cells. CircPVT1 shRNA significantly suppressed the OS cell invasion and migration. Meanwhile, circPVT1 sponged miR-26b-5p and CCNB1 was found to be the direct target of miR-26b-5p. Furthermore, silencing of circPVT1 inhibited the growth and metastasis of OS in vivo.

CONCLUSION

Silencing of circPVT1 notably suppressed the tumorigenesis and metastasis of OS via miR-26b-5p/CCNB1 axis. Therefore, circPVT1 might be used as a target for OS treatment.

Immune Landscape and Classification in Lung Adenocarcinoma Based on a Novel Cell Cycle Checkpoints Related Signature for Predicting Prognosis and Therapeutic Response

Lung adenocarcinoma (LUAD) is one of the most common malignancies with the highest mortality globally, and it has a poor prognosis. Cell cycle checkpoints play a central role in the entire system of monitoring cell cycle processes, by regulating the signalling pathway of the cell cycle. Cell cycle checkpoints related genes (CCCRGs) have potential utility in predicting survival, and response to immunotherapies and chemotherapies. To examine this, based on CCCRGs, we identified two lung adenocarcinoma subtypes, called cluster1 and cluster2, by consensus clustering. Enrichment analysis revealed significant discrepancies between the two subtypes in gene sets associated with cell cycle activation and tumor progression. In addition, based on Least Absolute Shrinkage and Selection Operator (LASSO) Cox regression, we have developed and validated a cell cycle checkpoints-related risk signature to predict prognosis, tumour immune microenvironment: (TIME), immunotherapy and chemotherapy responses for lung adenocarcinoma patients. Results from calibration plot, decision curve analysis (DCA), and time-dependent receiver operating characteristic curve (ROC) revealed that combining age, gender, pathological stages, and risk score in lung adenocarcinoma patients allowed for a more accurate and predictive nomogram. The area under curve for lung adenocarcinoma patients with 1-, 3-, 5-, and 10-year overall survival was: 0.74, 0.73, 0.75, and 0.81, respectively. Taken together, our proposed 4-CCCRG signature can serve as a clinically useful indicator to help predict patients outcomes, and could provide important guidance for immunotherapies and chemotherapies decision for lung adenocarcinoma patients.

Statistics and network-based approaches to identify molecular mechanisms that drive the progression of breast cancer

Breast cancer (BC) is one of the most malignant tumors and the leading cause of cancer-related death in women worldwide. So, an in-depth investigation on the molecular mechanisms of BC progression is required for diagnosis, prognosis and therapies. In this study, we identified 127 common differentially expressed genes (cDEGs) between BC and control samples by analyzing five gene expression profiles with NCBI accession numbers GSE139038, GSE62931, GSE45827, GSE42568 and GSE54002, based-on two statistical methods LIMMA and SAM. Then we constructed protein-protein interaction (PPI) network of cDEGs through the STRING database and selected top-ranked 7 cDEGs (BUB1, ASPM, TTK, CCNA2, CENPF, RFC4, and CCNB1) as a set of key genes (KGs) by cytoHubba plugin in Cytoscape. Several BC-causing crucial biological processes, molecular functions, cellular components, and pathways were significantly enriched by the estimated cDEGs including at-least one KGs. The multivariate survival analysis showed that the proposed KGs have a strong prognosis power of BC. Moreover, we detected some transcriptional and post-transcriptional regulators of KGs by their regulatory network analysis. Finally, we suggested KGs-guided three repurposable candidate-drugs (Trametinib, selumetinib, and RDEA119) for BC treatment by using the GSCALite online web tool and validated them through molecular docking analysis, and found their strong binding affinities. Therefore, the findings of this study might be useful resources for BC diagnosis, prognosis and therapies.