Overexpression of ANLN in lung adenocarcinoma is associated with metastasis

Identification of a combined hypoxia and lactate metabolism prognostic signature in lung adenocarcinoma : Author

BACKGROUND

In the tumor microenvironment (TME), a bidirectional relationship exists between hypoxia and lactate metabolism, with each component exerting a reciprocal influence on the other, forming an inextricable link. The aim of the present investigation was to develop a prognostic model by amalgamating genes associated with hypoxia and lactate metabolism. This model is intended to serve as a tool for predicting patient outcomes, including survival rates, the status of the immune microenvironment, and responsiveness to therapy in patients with lung adenocarcinoma (LUAD).

METHODS

Transcriptomic sequencing data and patient clinical information specific to LUAD were obtained from comprehensive repositories of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). A compendium of genes implicated in hypoxia and lactate metabolism was assembled from an array of accessible datasets. Univariate and multivariate Cox regression analyses were employed. Additional investigative procedures, including tumor mutational load (TMB), microsatellite instability (MSI), functional enrichment assessments and the ESTIMATE, CIBERSORT, and TIDE algorithms, were used to evaluate drug sensitivity and predict the efficacy of immune-based therapies.

RESULTS

A novel prognostic signature comprising five lactate and hypoxia-related genes (LHRGs), PKFP, SLC2A1, BCAN, CDKN3, and ANLN, was established. This model demonstrated that LUAD patients with elevated LHRG-related risk scores exhibited significantly reduced survival rates. Both univariate and multivariate Cox analyses confirmed that the risk score was a robust prognostic indicator of overall survival. Immunophenotyping revealed increased infiltration of memory CD4 + T cells, dendritic cells and NK cells in patients classified within the high-risk category compared to their low-risk counterparts. Higher probability of mutations in lung adenocarcinoma driver genes in high-risk groups, and the MSI was associated with the risk-score. Functional enrichment analyses indicated a predominance of cell cycle-related pathways in the high-risk group, whereas metabolic pathways were more prevalent in the low-risk group. Moreover, drug sensitivity analyses revealed increased sensitivity to a variety of drugs in the high-risk group, especially inhibitors of the PI3K-AKT, EGFR, and ELK pathways.

CONCLUSIONS

This prognostic model integrates lactate metabolism and hypoxia parameters, offering predictive insights regarding survival, immune cell infiltration and functionality, as well as therapeutic responsiveness in LUAD patients. This model may facilitate personalized treatment strategies, tailoring interventions to the unique molecular profile of each patient's disease.

Integrated bulk and single-cell RNA sequencing identifies an aneuploidy-based gene signature to predict sensitivity of lung adenocarcinoma to traditional chemotherapy drugs and patients' prognosis

Background

Patients with lung adenocarcinoma (LUAD) often develop a poor prognosis. Currently, researches on prognostic and immunotherapeutic capacity of aneuploidy-related genes in LUAD are limited.

Methods

Genes related to aneuploidy were screened based on bulk RNA sequencing data from public databases using Spearman method. Next, univariate Cox and Lasso regression analyses were performed to establish an aneuploidy-related riskscore (ARS) model. Results derived from bioinformatics analysis were further validated using cellular experiments. In addition, typical LUAD cells were identified by subtype clustering, followed by SCENIC and intercellular communication analyses. Finally, ESTIMATE, ssGSEA and CIBERSORT algorithms were employed to analyze the potential relationship between ARS and tumor immune environment.

Results

A five-gene ARS signature was developed. These genes were abnormally high-expressed in LUAD cell lines, and in particular the high expression of CKS1B promoted the proliferative, migratory and invasive phenotypes of LUAD cell lines. Low ARS group had longer overall survival time, higher degrees of inflammatory infiltration, and could benefit more from receiving immunotherapy. Patients in low ASR group responded more actively to traditional chemotherapy drugs (Erlotinib and Roscovitine). The scRNA-seq analysis annotated 17 cell subpopulations into seven cell clusters. Core transcription factors (TFs) such as CREB3L1 and CEBPD were enriched in high ARS cell group, while TFs such as BCLAF1 and UQCRB were enriched in low ARS cell group. CellChat analysis revealed that high ARS cell groups communicated with immune cells via SPP1 (ITGA4-ITGB1) and MK (MDK-NCl) signaling pathways.

Conclusion

In this research, integrative analysis based on the ARS model provided a potential direction for improving the diagnosis and treatment of LUAD.

Development of an invasion score based on metastasis-related pathway activity profiles for identifying invasive molecular subtypes of lung adenocarcinoma

The invasive capacity of lung adenocarcinoma (LUAD) is an important factor influencing patients' metastatic status and survival outcomes. However, there is still a lack of suitable biomarkers to evaluate tumor invasiveness. LUAD molecular subtypes were identified by unsupervised consistent clustering of LUAD. The differences in prognosis, tumor microenvironment (TME), and mutation were assessed among different subtypes. After that, the invasion-related gene score (IRGS) was constructed by genetic differential analysis, WGCNA analysis, and LASSO analysis, then we evaluated the relationship between IRGS and invasive characteristics, TME, and prognosis. The predictive ability of the IRGS was verified by in vitro experiments. Next, the "oncoPredict" R package and CMap were used to assess the potential value of IRGS in drug therapy. The results showed that LUAD was clustered into two molecular subtypes. And the C1 subtype exhibited a worse prognosis, higher stemness enrichment activity, less immune infiltration, and higher mutation frequency. Subsequently, IRGS developed based on molecular subtypes demonstrated a strong association with malignant characteristics such as invasive features, higher stemness scores, less immune infiltration, and worse survival. In vitro experiments showed that the higher IRGS LUAD cell had a stronger invasive capacity than the lower IRGS LUAD cell. Predictive analysis based on the "oncoPredict" R package showed that the high IRGS group was more sensitive to docetaxel, erlotinib, paclitaxel, and gefitinib. Among them, in vitro experiments verified the greater killing effect of paclitaxel on high IRGS cell lines. In addition, CMap showed that purvalanol-a, angiogenesis-inhibitor, and masitinib have potential therapeutic effects in the high IRGS group. In summary we identified and analyzed the molecular subtypes associated with the invasiveness of LUAD and developed IRGS that can efficiently predict the prognosis and invasive ability of the tumor. IRGS may be able to facilitate the precision treatment of LUAD to some extent.

Dysregulated ANLN reveals immune cell landscape and promotes carcinogenesis by regulating the PI3K/Akt/mTOR pathway in clear cell renal cell carcinoma

Background

Abnormal anillin (ANLN) expression has been observed in multiple tumours and is closely associated with patient prognosis and clinical features. In this study, we systematically elucidated the clinical significance and biological roles of ANLN in patients with clear cell renal cell carcinoma (ccRCC).

Methods

We obtained transcriptome and clinical data of patients with ccRCC from public databases. Multi-omics data and clinical samples were combined to analyse the correlation between ANLN expression and the clinical characteristics of patients with renal cancer. Additionally, the immune cell landscape of ANLN expression was evaluated using different immune algorithms in the tumour microenvironment. The tumour-promoting potential of ANLN was confirmed using in vitro assays, including CCK8 and Transwell assays.

Results

Bioinformatics analysis showed that ANLN is over-expressed in patients with ccRCC, as validated by clinical samples. Publicly available clinical data suggest that high ANLN expression may indicate poor outcomes in patients with ccRCC. Moreover, biological function analysis revealed a marked enrichment of the cell cycle and PI3K-Akt pathways. The distribution of immune cells, particularly M2 macrophages, differed in patients with ccRCC. Furthermore, ANLN silencing inhibited the proliferation, migration, and invasion of renal cancer cells in vitro. After ANLN expression was knocked down in 786-O cells, the protein levels of important PI3K signalling pathway components, including PI3K, Akt, and mTOR, drastically decreased.

Conclusions

These findings suggest that ANLN is dysregulated in renal cancer tissues and promotes tumour progression by activating the PI3K/Akt/mTOR signalling pathway.

Alternative Splicing Landscape of Head and Neck Squamous Cell Carcinoma

Head and neck malignancies are a significant global health concern, with head and neck squamous cell carcinoma (HNSCC) being the sixth most common cancer worldwide accounting for > 90% of cases. In recent years, there has been growing recognition of the potential role of alternative splicing (AS) in the etiology of cancer. Increasing evidence suggests that AS is associated with various aspects of cancer progression, including tumor occurrence, invasion, metastasis, and drug resistance. Additionally, AS is involved in shaping the tumor microenvironment, which plays a crucial role in tumor development and response to therapy. AS can influence the expression of factors involved in angiogenesis, immune response, and extracellular matrix remodeling, all of which contribute to the formation of a supportive microenvironment for tumor growth. Exploring the mechanism of AS events in HNSCC could provide insights into the development and progression of this cancer, as well as its interaction with the tumor microenvironment. Understanding how AS contributes to the molecular changes in HNSCC cells and influences the tumor microenvironment could lead to the identification of new therapeutic targets. Targeted chemotherapy and immunotherapy strategies tailored to the specific AS patterns in HNSCC could potentially improve treatment outcomes and reduce side effects. This review explores the concept, types, processes, and technological advancements of AS, focusing on its role in the initiation, progression, treatment, and prognosis of HNSCC.

ELOVL6 is associated with immunosuppression in lung adenocarcinoma through bioinformatics analysis

The aim of this paper was to reveal the correlation between the expression of ELOVL fatty acid elongase 6 (ELOVL6) gene in lung adenocarcinoma (LUAD) and its clinical significance, immune cell infiltration level and prognosis. Expression profile data of ELOVL6 mRNA were collected from the cancer genome atlas database to analyze the differences in ELOVL6 mRNA expression in LUAD tissues and normal lung tissues, and to analyze the correlation between ELOVL6 and information on clinicopathological features. Based on TIMER database, TISDIB database and GEPIA2 database, the correlation between ELOVL6 expression and tumor immune cell infiltration in LUAD was analyzed. Gene ontology and Kyoto encyclopedia of genes and genomes enrichment analyses of ELOVL6-related co-expressed genes were performed to identify the involved signaling pathways and to construct their co-expressed gene protein interaction networks. Drugs affected by ELOVL6 expression were screened based on the Cell Miner database. These findings suggest that ELOVL6 plays an important role in the course of LUAD, and the expression level of this gene has a close relationship with clinicopathological characteristics and survival prognosis, and has the potential to become a prognostic marker and therapeutic target for LUAD.

The mitotic spindle-related seven-gene predicts the prognosis and immune microenvironment of lung adenocarcinoma

PURPOSE

Abnormalities in the mitotic spindle have been linked to a variety of cancers. Data on their role in the onset, progression, and treatment of lung adenocarcinoma (LUAD) need to be explored.

METHODS

The data were retrieved from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and Molecular Signatures Database (MSigDB), for the training cohort, external validation cohort, and the hallmark mitotic spindle gene set, respectively. Mitotic spindle genes linked to LUAD prognosis were identified and intersected with differentially expressed up-regulated genes in the training cohort. Nomogram prediction models were built based on least absolute shrinkage and selection operator (LASSO) regression, univariate cox, and multivariate cox analyses. The seven-gene immunological score was examined, as well as the correlation of immune checkpoints. The DLGAP5 and KIF15 expression in BEAS-2B, A549, H1299, H1975, and PC-9 cell lines was validated with western blot (WB).

RESULTS

A total of 965 differentially expressed up-regulated genes in the training cohort intersected with 51 mitotic spindle genes associated with LUAD prognosis. Finally, the seven-gene risk score was determined and integrated with clinical characteristics to construct the nomogram model. Immune cell correlation analysis revealed a negative correlation between seven-gene expression with B cell, endothelial cell (excluding LMNB1), and T cell CD8 + (p < 0.05). However, the seven-gene expression was positively correlated with multiple immune checkpoints (p < 0.05). The expression of DLGAP5 and KIF15 were significantly higher in A549, H1299, H1975, and PC-9 cell lines than that in BEAS-2B cell line.

CONCLUSION

High expression of the seven genes is positively correlated with poor prognosis of LUAD, and these genes are promising as prospective immunotherapy targets.

Metastasis-related long non-coding RNAs AL359220.1, SH3BP5-AS1 and ZF-AS1 are significant for prognostic assessment of lung adenocarcinoma

BACKGROUND

Metastasis of lung adenocarcinoma (LUAD) severely worsens prognosis. Genetic alteration in the tumor microenvironment (TME) is closely associated with metastasis and other malignant biological properties of LUAD. In this study, we establish a metastasis-related risk model to accurately predict LUAD prognosis.

METHODS

RNA-sequencing profiles and clinical data of LUAD patients including 503 tumor tissues and 54 adjacent normal tissues were collected in TCGA database. Additionally, the paired specimens from 156 LUAD patients were obtained in a single center. The metastatic relevance and clinical significance of metastasis-related long non-coding RNA (MRLNRs) was validated by series of in vitro experiments including western blotting, qPCR and transwell assays.

RESULTS

Six MRLNRs were significantly correlated to prognoses of LUAD patients, of which AL359220.1, SH3BP5-AS1 and ZF-AS1 were further used to establish a metastasis-related risk scoring model (MRRS) due to the close associations with overall survival of LUAD patients. According to the MRRS, patients with higher scores in the high-risk group obtained poorer prognoses and survival outcomes. ZFAS1 expressed highly in tumor tissues and showed the inverse results compared to SH3BP5-AS1 and AL359220.1. In addition, the high expression of ZFAS1 was prominently correlated to the more advanced T-stage and distant metastasis. The reduction of ZFAS1 induced by siRNAs dramatically diminished the migration and invasion abilities of LUAD cells.

CONCLUSIONS

In the present research, we elucidate the metastatic relevance and clinical significance of AL359220.1, SH3BP5-AS1 and ZF-AS1 in LUAD. Moreover, MRRS provide a promising assessing model for clinical decision making and prognosis of LUAD.

Comprehensive multiomics and in silico approach uncovers prognostic, immunological, and therapeutic roles of ANLN in lung adenocarcinoma

The anillin actin-binding protein (ANLN) is immensely overexpressed in cancers, including lung cancer (LC). Phytocompounds have gained interest due to their broader potential and reduced unwanted effects. Screening numerous compounds presents a challenge, but in silico molecular docking is pragmatic. The present study aims to identify the role of ANLN in lung adenocarcinoma (LUAD), along with identification and interaction analysis of anticancer and ANLN inhibitory phytocompounds followed by molecular dynamics (MD) simulation. Using a systematic approach, we found that ANLN is significantly overexpressed in LUAD and mutated with a frequency of 3.73%. It is linked with advanced stages, clinicopathological parameters, worsening of relapse-free survival (RFS), and overall survival (OS), pinpointing its oncogenic and prognostic potential. High-throughput screening and molecular docking of phytocompounds revealed that kaempferol (flavonoid aglycone) interacts strongly with the active site of ANLN protein via hydrogen bonds, Vander Waals interactions, and acts as a potent inhibitor. Furthermore, we discovered that ANLN expression was found to be significantly higher (p) in LC cells compared to normal cells. This is a propitious and first study to demonstrate ANLN and kaempferol interactions, which might eventually lead to removal of rout from cell cycle regulation posed by ANLN overexpression and allow it to resume normal processes of proliferation. Overall, this approach suggested a plausible biomarker role of ANLN and the combination of molecular docking subsequently led to the identification of contemporary phytocompounds, bearing symbolic anticancer effects. The findings would be advantageous for pharmaceutics but require validation using in vitro and in vivo methods. HIGHLIGHTS: • ANLN is significantly overexpressed in LUAD. • ANLN is implicated in the infiltration of TAMs and altering plasticity of TME. • Kaempferol (potential ANLN inhibitor) shows important interactions with ANLN which could remove the alterations in cell cycle regulation, imposed by ANLN overexpression eventually leading to normal process of cell proliferation.

Proteomics analysis of prefrontal cortex of Alzheimer's disease patients revealed dysregulated proteins in the disease and novel proteins associated with amyloid-β pathology

BACKGROUND

Alzheimer's disease (AD) is a progressive, chronic, and neurodegenerative disease, and the most common cause of dementia worldwide. Currently, the mechanisms underlying the disease are far from being elucidated. Thus, the study of proteins involved in its pathogenesis would allow getting further insights into the disease and identifying new markers for AD diagnosis.

METHODS

We aimed here to analyze protein dysregulation in AD brain by quantitative proteomics to identify novel proteins associated with the disease. 10-plex TMT (tandem mass tags)-based quantitative proteomics experiments were performed using frozen tissue samples from the left prefrontal cortex of AD patients and healthy individuals and vascular dementia (VD) and frontotemporal dementia (FTD) patients as controls (CT). LC-MS/MS analyses were performed using a Q Exactive mass spectrometer.

RESULTS

In total, 3281 proteins were identified and quantified using MaxQuant. Among them, after statistical analysis with Perseus (p value < 0.05), 16 and 155 proteins were defined as upregulated and downregulated, respectively, in AD compared to CT (Healthy, FTD and VD) with an expression ratio ≥ 1.5 (upregulated) or ≤ 0.67 (downregulated). After bioinformatics analysis, ten dysregulated proteins were selected as more prone to be associated with AD, and their dysregulation in the disease was verified by qPCR, WB, immunohistochemistry (IHC), immunofluorescence (IF), pull-down, and/or ELISA, using tissue and plasma samples of AD patients, patients with other dementias, and healthy individuals.

CONCLUSIONS

We identified and validated novel AD-associated proteins in brain tissue that should be of further interest for the study of the disease. Remarkably, PMP2 and SCRN3 were found to bind to amyloid-β (Aβ) fibers in vitro, and PMP2 to associate with Aβ plaques by IF, whereas HECTD1 and SLC12A5 were identified as new potential blood-based biomarkers of the disease.

Identification and validation of novel prognostic biomarkers and therapeutic targets for non-small cell lung cancer

Background: Despite the significant survival benefits of anti-PD-1/PD-L1 immunotherapy, non-small cell lung cancer (NSCLC) remains one of the most common tumors and major causes of cancer-related deaths worldwide. Thus, there is an urgent need to identify new therapeutic targets for this refractory disease.

Methods: In this study, microarray datasets GSE27262, GSE75037, GSE102287, and GSE21933 were integrated by Venn diagram. We performed functional clustering and pathway enrichment analyses using R. Through the STRING database and Cytoscape, we conducted protein-protein interaction (PPI) network analysis and identified the key genes, which were verified by the GEPIA2 and UALCAN portal. Validation of actin-binding protein anillin (ANLN) was performed by quantitative real-time polymerase chain reaction and Western blotting. Additionally, Kaplan-Meier methods were used to compute the survival analyses.

Results: In total, 126 differentially expressed genes were identified, which were enriched in mitotic nuclear division, mitotic cell cycle G2/M transition, vasculogenesis, spindle, and peroxisome proliferator-activated receptor signaling pathway. 12 central node genes were identified in the PPI network complex. The survival analysis revealed that high transcriptional levels were associated with inferior survival in NSCLC patients. The clinical implication of ANLN was further explored; its protein expression showed a gradually increasing trend from grade I to III.

Conclusion: These Key genes may be involved in the carcinogenesis and progression of NSCLC, which may serve as useful targets for NSCLC diagnosis and treatment.

Native Size-Exclusion Chromatography-Based Mass Spectrometry Reveals New Components of the Early Heat Shock Protein 90 Inhibition Response Among Limited Global Changes

The molecular chaperone heat shock protein 90 (HSP90) works in concert with co-chaperones to stabilize its client proteins, which include multiple drivers of oncogenesis and malignant progression. Pharmacologic inhibitors of HSP90 have been observed to exert a wide range of effects on the proteome, including depletion of client proteins, induction of heat shock proteins, dissociation of co-chaperones from HSP90, disruption of client protein signaling networks, and recruitment of the protein ubiquitylation and degradation machinery-suggesting widespread remodeling of cellular protein complexes. However, proteomics studies to date have focused on inhibitor-induced changes in total protein levels, often overlooking protein complex alterations. Here, we use size-exclusion chromatography in combination with mass spectrometry (SEC-MS) to characterize the early changes in native protein complexes following treatment with the HSP90 inhibitor tanespimycin (17-AAG) for 8 h in the HT29 colon adenocarcinoma cell line. After confirming the signature cellular response to HSP90 inhibition (e.g., induction of heat shock proteins, decreased total levels of client proteins), we were surprised to find only modest perturbations to the global distribution of protein elution profiles in inhibitor-treated HT29 cells at this relatively early time-point. Similarly, co-chaperones that co-eluted with HSP90 displayed no clear difference between control and treated conditions. However, two distinct analysis strategies identified multiple inhibitor-induced changes, including known and unknown components of the HSP90-dependent proteome. We validate two of these-the actin-binding protein Anillin and the mitochondrial isocitrate dehydrogenase 3 complex-as novel HSP90 inhibitor-modulated proteins. We present this dataset as a resource for the HSP90, proteostasis, and cancer communities (https://www.bioinformatics.babraham.ac.uk/shiny/HSP90/SEC-MS/), laying the groundwork for future mechanistic and therapeutic studies related to HSP90 pharmacology. Data are available via ProteomeXchange with identifier PXD033459.

Clinical implication and immunological landscape analyses of ANLN in pan-cancer: A new target for cancer research

BACKGROUND

Anillin is a F-actin binding protein (ANLN) mainly involved in the process of cytokinesis and known to be dysregulated in diverse cancers. However, the role of ANLN in pan-cancer prognosis and tumor immunity remains unclear.

METHODS

Gene expression profiles of 31 solid tumors were downloaded from The Cancer Genome Atlas (TCGA) database. ANLN mRNA and protein expression were quantified using quantitative real-time PCR (qRT-PCR) and immunohistochemistry (IHC). Protein expression of ANLN was further confirmed in Human Protein Atlas (HPA) database. Cox regression and Kaplan-Meier analysis were utilized to assess the prognostic value of ANLN in pan-cancer. The correlation between ANLN and different immune gene markers and infiltration cells was analyzed via ESTIMATE and CIBERSORT. A BLCA immunotherapy cohort: IMvigor (210) was used to confirm the role of ANLN in immune response.

RESULTS

ANLN upregulation was detected in 21 types of cancers and was associated with poor overall survival (OS), disease-free interval (DFI), and progression-free interval (PFI) in most cancers except in THYM (Thymoma). Additionally, correlation analysis revealed a significantly positive association between ANLN expression and tumor mutation burden (TMB), microsatellite instability (MSI), immune cells infiltration. and immune checkpoint genes in various cancers. The BLCA immunotherapy cohort confirmed that patients with higher ANLN level had better immune responses and longer OS.

CONCLUSION

ANLN may serve as a prognostic biomarker for pan-cancer. ANLN upregulation is associated with higher TMB, MSI, and immune cell infiltration in multiple types of tumors, shedding new light for cancer treatment.

Identification of natural killer cell associated subtyping and gene signature to predict prognosis and drug sensitivity of lung adenocarcinoma

Introduction: This research explored the immune characteristics of natural killer (NK) cells in lung adenocarcinoma (LUAD) and their predictive role on patient survival and immunotherapy response. Material and methods: Molecular subtyping of LUAD samples was performed by evaluating NK cell-associated pathways and genes in The Cancer Genome Atlas (TCGA) dataset using consistent clustering. 12 programmed cell death (PCD) patterns were acquired from previous study. Riskscore prognostic models were constructed using Least absolute shrinkage and selection operator (Lasso) and Cox regression. The model stability was validated in Gene Expression Omnibus database (GEO). Results: We classified LUAD into three different molecular subgroups based on NK cell-related genes, with the worst prognosis in C1 patients and the optimal in C3. Homologous Recombination Defects, purity and ploidy, TMB, LOH, Aneuploidy Score, were the most high-expressed in C1 and the least expressed in C3. ImmuneScore was the highest in C3 type, suggesting greater immune infiltration in C3 subtype. C1 subtypes had higher TIDE scores, indicating that C1 subtypes may benefit less from immunotherapy. Generally, C3 subtype presented highest PCD patterns scores. With four genes, ANLN, FAM83A, RHOV and PARP15, we constructed a LUAD risk prediction model with significant differences in immune cell composition, cell cycle related pathways between the two risk groups. Samples in C1 and high group were more sensitive to chemotherapy drug. The score of PCD were differences in high- and low-groups. Finally, we combined Riskscore and clinical features to improve the performance of the prediction model, and the calibration curve and decision curve verified that the great robustness of the model. Conclusion: We identified three stable molecular subtypes of LUAD and constructed a prognostic model based on NK cell-related genes, maybe have a greater potential for application in predicting immunotherapy response and patient prognosis.

In silico analysis revealed the potential circRNA-miRNA-mRNA regulative network of non-small cell lung cancer (NSCLC)

BACKGROUND

The primary source of death in the world is non-small cell lung cancer (NSCLC). However, NSCLCs pathophysiology is still not completely understood. The current work sought to study the differential expression of mRNAs involved in NSCLC and their interactions with miRNAs and circRNAs.

METHODS

We utilized three microarray datasets (GSE21933, GSE27262, and GSE33532) from the GEO NCBI database to identify the differentially expressed genes (DEGs) in NSCLC. We employed DAVID Functional annotation tool to investigate the underlying GO biological process, molecular functions, and KEGG pathways involved in NSCLC. We performed the Protein-protein interaction (PPI) network, MCODE, and CytoHubba analysis from Cytoscape software to identify the significant DEGs in NSCLC. We utilized miRnet to anticipate and build interaction between miRNAs and mRNAs in NSCLC and ENCORI to predict the miRNA-circRNA relationships and build the ceRNA regulatory network. Finally, we executed the gene expression and Kaplan-Meier survival analysis to validate the significant DEGs in the ceRNA network utilizing TCGA NSCLC and GEPIA data.

RESULTS

We revealed a total of 156 overlapped DEGs (47 upregulated and 109 downregulated genes) in NSCLC. The PPI network, MCODE, and CytoHubba analysis revealed 12 hub genes (cdkn3, rrm2, ccnb1, aurka, nuf2, tyms, kif11, hmmr, ccnb2, nek2, anln, and birc5) that are associated with NSCLC. We identified that these 12 genes encode 12 mRNAs that are strongly linked with 8 miRNAs, and further, we revealed that 1 circRNA was associated with this 5 miRNA. We constructed the ceRNAs network that contained 1circRNA-5miRNAs-7mRNAs. The expression of these seven significant genes in LUAD & LUSC (NSCLC) was considerably higher in the TCGA database than in normal tissues. Kaplan-Meier survival plot reveals that increased expression of these hub genes was related to a poor survival rate in LUAD.

CONCLUSION

Overall, we developed a circRNA-miRNA-mRNA regulation network to study the probable mechanism of NSCLC.

A network-based dynamic criterion for identifying prediction and early diagnosis biomarkers of complex diseases

Lung adenocarcinoma (LUAD) seriously threatens human health and generally results from dysfunction of relevant module molecules, which dynamically change with time and conditions, rather than that of an individual molecule. In this study, a novel network construction algorithm for identifying early warning network signals (IEWNS) is proposed for improving the performance of LUAD early diagnosis. To this end, we theoretically derived a dynamic criterion, namely, the relationship of variation (RV), to construct dynamic networks. RV infers correlation [Formula: see text] statistics to measure dynamic changes in molecular relationships during the process of disease development. Based on the dynamic networks constructed by IEWNS, network warning signals used to represent the occurrence of LUAD deterioration can be defined without human intervention. IEWNS was employed to perform a comprehensive analysis of gene expression profiles of LUAD from The Cancer Genome Atlas (TCGA) database and the Gene Expression Omnibus (GEO) database. The experimental results suggest that the potential biomarkers selected by IEWNS can facilitate a better understanding of pathogenetic mechanisms and help to achieve effective early diagnosis of LUAD. In conclusion, IEWNS provides novel insight into the initiation and progression of LUAD and helps to define prospective biomarkers for assessing disease deterioration.

Comprehensive bioinformatics analysis reveals the prognostic value, predictive value, and immunological roles of ANLN in human cancers

Anillin (ANLN) is a unique scaffolding, actin-binding protein, which is essential for the integrity and ingression of the cleavage furrow. It is mainly involved in the cytokinesis process, while its role in various tumors has not been fully addressed and remains largely elusive. To provide a thorough perspective of ANLN’s roles among diverse malignancies, we conducted a comprehensive, pan-cancer analysis about ANLN, including but not limited to gene expression levels, prognostic value, biological functions, interacting proteins, immune-related analysis, and predictive value. As a result, when compared to normal tissues, ANLN expression is elevated in most cancers, and its expression also differs in different immune subtypes and molecular subtypes in diverse cancers. In addition, in 17 types of cancer, ANLN expression is increased in early tumor stages, and higher ANLN expression predicts worse survival outcomes in more than ten cancers. Furthermore, ANLN shows close correlations with the infiltration levels of most immune cells, and enrichment analysis using ANLN co-expressed genes reveals that ANLN plays essential roles in cell cycle, mitosis, cellular senescence, and p53 signaling pathways. In the final, ANLN exhibits high accuracy in predicting many cancers, and subsequent multivariate analysis suggests ANLN could be an independent prognostic factor in specific cancer types. Taken together, ANLN is proved to be a novel and promising biomarker for its excellent predictive utility, promising prognostic value, and potential immunological roles in pan-cancer. Targeting ANLN might be an attractive approach to tumor treatment.

Ultrasound microbubble-mediated delivery of ANLN silencing-repressed EZH2 expression alleviates cervical cancer progression

Ultrasound-targeted microbubble destruction (UTMD) is a new gene therapy method that uses ultrasound and microbubbles carrying target genes to achieve gene transfection. However, whether UTMD-mediated ANLN silencing transfection helps to restrain the growth of cervical cancer (CC) is obscure. ANLN level in tumor tissues, adjacent tissues, and cells was tested using the database, qRT-PCR, and western blot. The optimal concentration of SF6 was determined by MTT assay. Mechanical index (MI) was selected by flow cytometry. After transfection with liposome or UTMD-mediated liposome, cell function experiments, qRT-PCR, and western blot were employed to assess CC cell biological behaviors and EZH2 level. Epithelial-mesenchymal transition (EMT)-related marker and apoptosis-related marker expressions were examined utilizing qRT-PCR and western blot. 10% SF6 and MI of 0.28 were selected for subsequent tests. ANLN was highly expressed in CC and cells. The transfection efficiency of the UTMD-siANLN group was higher than that of the L-siANLN group. Moreover, the repression of UTMD-siANLN on CC cell malignant phenotypes was stronger than L-siANLN. UTMD-siANLN attenuated EZH2 expression in CC cells. The modulatory role of UTMD-siANLN on EMT- and apoptosis-related markers was reversed by EZH2 overexpression. UTMD can improve the efficiency of siANLN transfection into CC cells to induce suppression of CC cell malignant phenotypes, which may become a new target of gene therapy for CC.

Establishing an 8-gene immune prognostic model based on TP53 status for lung adenocarcinoma

Background

Lung adenocarcinoma (LUAD) results in a majority of cancer burden worldwide. TP53 is the most commonly mutated in LUAD. This study aimed to reveal the relation between TP53 and tumor microenvironment (TME) for improving LUAD treatment.

Methods

Differentially expressed genes (DEGs) related to immunity were analyzed between TP53‐WT and TP53‐MUT groups. Least absolute shrinkage and selection operator (LASSO) Cox regression was applied to screen prognostic DEGs. Two independent datasets were included to evaluate the robustness of the prognostic model.

Results

An 8‐gene prognostic model containing ANLN, CCNB1, DLGAP5, FAM83A, GJB2, NAPSA, SFTPB, and SLC2A1 was established based on DEGs. LUAD samples were classified into high‐ and low‐risk groups with differential overall survival in the two datasets. M0 macrophages, M1 macrophages, and activated memory CD4 T cells were more enriched in high‐risk group. Immune checkpoints of PDCD1, LAG3, and CD274 were also high‐expressed in high‐risk group.

Conclusion

The study improved the understanding of the role of TP53 in the TME modulation. The 8‐gene model had robust performance to predict LUAD prognosis in clinical practice. In addition, the eight prognostic genes may also serve as potential targets for designing therapeutic drugs for LUAD patients.

A Four-Gene Prognostic Signature Based on the TEAD4 Differential Expression Predicts Overall Survival and Immune Microenvironment Estimation in Lung Adenocarcinoma

Background: TEA domain transcription factor 4 (TEAD4) is a member of the transcriptional enhancer factor (TEF) family of transcription factors, which is studied to be linked to the tumorigenesis and progression of various forms of cancers, including lung adenocarcinoma (LUAD). However, the specific function of this gene in the progression of LUAD remains to be explored.

Method: A total of 19 genes related to the Hippo pathway were analyzed to identify the significant genes involved in LUAD progression. The TCGA-LUAD data (n = 585) from public databases were mined, and the differentially expressed genes (DEGs) in patients with the differential level of TEAD4 were identified. The univariate Cox regression, zero LASSO regression coefficients, and multivariate Cox regression were performed to identify the independent prognostic signatures. The immune microenvironment estimation in the two subgroups, including immune cell infiltration, HLA family genes, and immune checkpoint genes, was assessed. The Gene Set Enrichment Analysis (GSEA) and GO were conducted to analyze the functional enrichment of DEGs between the two risk groups. The potential drugs for the high-risk subtypes were forecasted via the mode of action (moa) module of the connectivity map (CMap) database.

Results:TEAD4 was found to be significantly correlated with poor prognosis in LUAD-patients. A total of 102 DEGs in TEAD4-high vs. TEAD4-low groups were identified. Among these DEGs, four genes (CPS1, ANLN, RHOV, and KRT6A) were identified as the independent prognostic signature to conduct the Cox risk model. The immune microenvironment estimation indicated a strong relationship between the high TEAD4 expression and immunotherapeutic resistance. The GSEA and GO showed that pathways, including cell cycle regulation, were enriched in the high-risk group, while immune response-related and metabolism biological processes were enriched in the low-risk group. Several small molecular perturbagens targeting CFTR or PLA2G1B, by the mode of action (moa) modules of the glucocorticoid receptor agonist, cyclooxygenase inhibitor, and NFkB pathway inhibitor, were predicted to be suited for the high-risk subtypes based on the high TEAD4 expression.

Conclusion: The current study revealed TEAD4 is an immune regulation–related predictor of prognosis and a novel therapeutic target for LUAD.

Homeobox A1 Facilitates Immune Escape and Alleviates Oxidative Stress in Lung Adenocarcinoma

Objective

Recent studies have demonstrated that homeobox A1 (HOXA1) is upregulated in lung cancer due to RNA modifications (N6-methyladenosine), but the specific function of HOXA1 in lung adenocarcinoma (LUAD) remains indistinct. Herein, we investigated the role of HOXA1 in LUAD biology.

Methods

This study presented pancancer analysis of associations of HOXA1 with prognosis, TMB, and immune checkpoints. The expression of HOXA1 was detected in LUAD and normal tissues with immunohistochemistry and western blot. Through least absolute shrinkage and selection operator (LASSO) analysis, HOXA1-derived gene model was conducted in LUAD. Correlations of HOXA1 with immune cell infiltrations, immune checkpoints, HLAs, and chemotherapeutic sensitivity were evaluated. Colony formation, proliferation, and migration of LUAD cells with si-HOXA1 transfection were investigated, and the effects of HOXA1 on T cell exhaustion were assessed in vitro.

Results

HOXA1 expression was a risk factor of overall survival, disease-specific survival, and progression-free interval of LUAD. HOXA1 exhibited prominent associations with immune cell infiltration, immune checkpoints, and HLAs. HOXA1-derived gene signature reliably and independently predicted LUAD outcomes. Also, high-risk cases presented increased sensitivity to cisplatin, paclitaxel, docetaxel, vinorelbine, and etoposide. HOXA1 knockdown exhibited an inhibitory effect on proliferation and migration abilities of LUAD cells. Silencing HOXA1 weakened the expression of antioxidative stress markers Nrf2/HO-1 and T cell exhaustion marker CD155 in LUAD cells. Moreover, LUAD cells with HOXA1 knockdown enhanced the CD8+ T cell response.

Conclusion

Our data support the oncogenic function and prognostic significance of HOXA1 that facilitates immune escape and alleviates oxidative stress of LUAD.

ANLN and UBE2T are prognostic biomarkers associated with immune regulation in breast cancer: a bioinformatics analysis

OBJECTIVES

To screen and verify differential genes affecting the prognosis of breast cancer.

METHODS

Breast cancer gene expression datasets were downloaded from the GEO database, and original data were analyzed in R. The TIMER database was used to analyze the relationship between ANLN and UBE2T and immune cell infiltration.

RESULTS

Ten hub-key genes were identified, and survival analysis showed that UBE2T and ANLN were upregulated in breast cancer and their upregulation was associated with a poor prognosis. ANLN and UBE2T upregulation was associated with the prevalence of Th1 and Th2 cells, shifting the Th1/Th2 balance to Th2 in Basal and Luminal-B breast cancers, which indicates a poor prognosis (P < 0.05).

CONCLUSION

ANLN and UBE2T are potential biomarkers for predicting the prognosis of breast cancer.

Integrated Bioinformatics Analysis Identifies a New Stemness Index-Related Survival Model for Prognostic Prediction in Lung Adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) is one of the most lethal malignancies and is currently lacking in effective biomarkers to assist in diagnosis and therapy. The aim of this study is to investigate hub genes and develop a risk signature for predicting prognosis of LUAD patients.

METHODS

RNA-sequencing data and relevant clinical data were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was performed to identify hub genes associated with mRNA expression-based stemness indices (mRNAsi) in TCGA. We utilized LASSO Cox regression to assemble our predictive model. To validate our predictive model, me applied it to an external cohort.

RESULTS

mRNAsi index was significantly associated with the tissue type of LUAD, and high mRNAsi scores may have a protective influence on survival outcomes seen in LUAD patients. WGCNA indicated that the turquoise module was significantly correlated with the mRNAsi. We identified a 9-gene signature (CENPW, MCM2, STIL, RACGAP1, ASPM, KIF14, ANLN, CDCA8, and PLK1) from the turquoise module that could effectively identify a high-risk subset of these patients. Using the Kaplan-Meier survival curve, as well as the time-dependent receiver operating characteristic (tdROC) analysis, we determined that this gene signature had a strong predictive ability (AUC = 0.716). By combining the 9-gene signature with clinicopathological features, we were able to design a predictive nomogram. Finally, we additionally validated the 9-gene signature using two external cohorts from GEO and the model proved to be of high value.

CONCLUSION

Our study shows that the 9-gene mRNAsi-related signature can predict the prognosis of LUAD patient and contribute to decisions in the treatment and prevention of LUAD patients.

Screening key prognostic factors and constructing survival prognostic risk prediction model based on ceRNA network in early lung adenocarcinoma

Background

We aim to discover some prognostic factors, provide a basis for discovering molecular markers, and provide a basis for molecular features of early lung adenocarcinoma (LUAD) to predict patient prognosis.

Methods

Sequence data of LUAD were downloaded from The Cancer Genome Atlas (TCGA) database to screen out differentially expressed lncRNAs, miRNAs, and mRNAs (DERs). DERs were identified using R software’s limma package. The competitive endogenous RNA (ceRNA) network was constructed based on these RNAs. Univariate and multivariate Cox regression analysis on the RNAs in the ceRNA screened out independent prognostic-related RNAs to construct a prognostic risk score (PS) model. Combined with clinical data, we can calculate the survival rate of patients with early LUAD.

Results

There were 2,701 differentially expressed mRNAs (DEmRNAs), 47 differentially expressed lncRNAs (DElncRNAs), and 161 differentially expressed miRNAs (DEmiRNAs) identified in early LUAD. Based on these RNAs, 32 lncRNAs, 87 miRNAs, and 174 mRNAs participated in the ceRNA network. Twelve independently prognostic-related RNAs form an optimized combination. We developed a PS model based on these RNAs. Age, tumor recurrence and PS model status were independent survival prognostic clinical factors. Nomogram was established to predict the 3-year and 5-year survival rates.

Conclusions

We successfully constructed a ceRNA regulatory network based on the DERs in early LUAD. It can help us clarify the molecular mechanism of early LUAD. Simultaneously, the prognostic-related RNAs in early LUAD were also screened out. This network could provide new bases for diagnoses and prognoses of patients with LUAD.

Genomics and Prognosis Analysis of N6-Methyladenosine Regulators in Lung Adenocarcinoma

Objective: N⁶-methyladenosine (m⁶A) modification is involved in modulating various biological processes in human cancers. But the implication of m⁶A modification in lung adenocarcinoma (LUAD) is still unclear. Hence, this study conducted a comprehensive analysis of the expression and clinical implication of m⁶A regulators in LUAD.

Methods: Consensus clustering analysis of 502 LUAD samples in the TCGA dataset was presented based on the expression profiles of 20 m⁶A regulators using ConsensusClusterPlus package. Overall survival (OS), activation of signaling pathways and tumor immunity (immune/stromal score, tumor purity, expression of HLA and immune checkpoints, and immune cell infiltration) were compared between m⁶A modification patterns. The m⁶A-related genes between patterns were identified and prognostic m⁶A-related genes were imported into LASSO-cox regression analysis. The m⁶A risk score was developed and its prognostic implication was evaluated and externally verified in the GSE30219 and GSE72094 dataset. Furthermore, a nomogram that contained independent prognostic indicators was established, followed by external verification.

Results: Two m⁶A modification patterns were clustered across LUAD based on the expression similarity of the m⁶A regulators via consensus clustering analysis, with distinct OS, activation of signaling pathways and tumor immunity. Totally, 213 m⁶A-related genes that were identified by comparing two patterns were significantly related to LUAD prognosis. By LASSO method, we constructed the m⁶A risk score that was a reliable and independent prognostic factor for LUAD. Patients with low m⁶A risk score displayed a prominent survival advantage. After incorporating independent clinical features, we developed the prognostic nomogram that exhibited high predictive accuracy and the best clinical net benefit for OS.

Conclusion: Collectively, our study may provide a clinically useful tool for precise prognostic management and optimization of immunotherapeutic strategies for LUAD patients.

Development and Validation of a Prognostic N6-Methyladenosine-Related Immune Gene Signature for Lung Adenocarcinoma

Purpose

The prognostic value of an N6-methyladenosine (m6A) methylation-related immune gene signature for lung adenocarcinoma (LUAD) was investigated.

Patients and Methods

Gene expression and clinical phenotype data of LUAD patients were downloaded from The Cancer Genome Atlas database. A list of immune-related genes was retrieved from the InnateDB database. Correlation analysis, survival analysis, and univariate and multivariate Cox regression analyses were performed. After allocating patients into a high-risk or a low-risk group, the corresponding survival rates, immune microenvironment, expression of immune checkpoint genes, and modulation of Kyoto Encyclopedia of Genes and Genomes pathways were examined. Finally, the expression levels of prognostic biomarkers were assessed in the GSE126044 dataset.

Results

Seven m6A-related immune prognostic genes were identified. High expression of PSMD10P1, DIDO1, ABCA5, and CIITA was associated with high survival rates, while that of PRC1, ZWILCH, and ANLN was associated with low survival rates. The high- and low-risk groups showed significant differences in terms of the abundance of six tumor-infiltrating immune cell types and expression of 12 immune checkpoint genes. The risk group acted as an independent prognostic factor (hazard ratio = 0.398, 95% confidence interval = 0.217–0.729, P = 0.003). Finally, the developed nomogram could predict most efficiently the 1-, 2-, and 3-year survival probability of LUAD patients with a C-index of 0.833.

Conclusion

A seven-gene risk signature, associated with the immune microenvironment in LUAD, showed independent prognostic value.

Ferroptosis Characterization in Lung Adenocarcinomas Reveals Prognostic Signature With Immunotherapeutic Implication

The iron-dependent cell death named ferroptosis has been implicated in the progression and therapeutic response of several tumors. However, potential role of ferroptosis in lung adenocarcinomas (LUAD) remained less well understood. In TCGA-LUAD cohort, unsupervised clustering was first conducted based on ferroptosis regulators extracted from FerrDb database. Comprehensive correlation analysis and comparisons were performed among ferroptosis subtypes. The ferroptosis-related prognostic (FRP) signature was identified based on filtered features and repeated LASSO and was validated in five independent cohorts. The clinical relevance between the risk score and therapeutic response was further explored by multiple algorithms. qPCR was implemented to verify gene expression. A total of 1,168 LUAD patients and 161 ferroptosis regulators were included in this study. Three ferroptosis subtypes were identified and patients in subtype B had the best prognosis among the three subtypes. Significant differences in immune microenvironment and biological function enrichment were illustrated in distinct subtypes. The Boruta algorithm was conducted on 308 common differentially expressed genes for dimensionality reduction. A total of 56 genes served as input for model construction and a six-gene signature with the highest frequencies of 881 was chosen as FRP. The prognostic significance of FRP was validated in five independent cohorts. High FRP risk score was also linked to increased tumor mutation burden, PD-L1 protein expression and number of neoantigens. Of the FRP genes, 83.3% was abnormally expressed in LUAD cell lines. In conclusion, ferroptosis plays a non-negligible role in LUAD. Exploration of the ferroptosis pattern will enhance the prognostic stratification of individual patients and move toward the purpose of personalized treatment.

Tumor stemness and immune infiltration synergistically predict response of radiotherapy or immunotherapy and relapse in lung adenocarcinoma

Cancer stem cells (CSCs) have been shown to accelerate tumor recurrence, radiotherapy, and chemotherapy resistance. Immunotherapy is a powerful anticancer treatment that can significantly prolong the overall survival of patients with lung adenocarcinoma (LUAD). However, little is known about the function of genes related to tumor stemness and immune infiltration in LUAD. After integrating the tumor stemness index based on mRNA expression (mRNAsi), immune score, mRNA expression, and clinical information from the TCGA database, we screened 380 tumor stemness and immune (TSI)-related genes and constructed a five TSI-specific-gene (CPS1, CCR2, NT5E, ANLN, and ABCC2) signature (TSISig) using a machine learning method. Survival analysis indicated that TSISig could stably predict the prognosis of patients with LUAD. Comparison of mRNAsi and immune score between high- and low-TSISig groups suggested that TSISig characterized tumor stemness and immune infiltration. In addition, enrichment of immune subpopulations showed that the low-TSISig group held more immune subpopulations. GSEA revealed that TSISig had a strong association with the cell cycle and human immune response. Further analysis revealed that TSISig not only had a good predictive ability for prognosis but could also serve as an excellent predictor of tumor recurrence and response to radiotherapy and immunotherapy in LUAD patients. TSISig might regulate the development of LUAD by coordinating tumor stemness and immune infiltration. Finally, a connectivity map (CMap) analysis demonstrated that the HDAC inhibitor could target TSISig.

ANLN Regulated by miR-30a-5p Mediates Malignant Progression of Lung Adenocarcinoma

BACKGROUND

ANLN and miR-30a-5p may be involved in the progression of lung adenocarcinoma (LUAD). However, their underlying mechanism in LUAD has not been completely comprehended.

METHODS

Differential expression analysis, binding site prediction, and survival analysis were conducted by bioinformatics approaches. ANLN mRNA and miR-30a-5p expression were detected by qRT-PCR. ANLN protein expression was detected by western blot. Cell behaviors in LUAD were examined by functional experiments.

RESULTS

ANLN was activated in LUAD cells in terms of mRNA and protein. High ANLN level was positively correlated with poor prognosis. Enforced ANLN stimulated protumorigenesis LUAD cell behaviors. miR-30a-5p could target ANLN mRNA, as revealed and verified through assays. Remarkably low miR-30a-5p expression was observed in LUAD cells, and it could repress ANLN expression. The accelerated cell behaviors by overexpression of ANLN were counteracted by upregulating miR-30a-5p.

CONCLUSION

Overall, miR-30a-5p remarkably restrained the malignant progression of LUAD cells by constraining ANLN expression. Thus, ANLN and miR-30a-5p could be novel therapeutic targets of LUAD.

Comprehensive Bioinformatics Analysis to Identify the Gene HMMR Associated With Lung Adenocarcinoma Prognosis and Its Mechanism of Action in Multiple Cancers

Background

Lung cancer is the third most frequently diagnosed cancer in the world, with lung adenocarcinoma (LUAD) as the most common pathological type. But studies on the predictive effect of a single gene on LUAD are limited. We aimed to discover new predictive markers for LUAD.

Methods

Differentially high-expressed genes at each stage were obtained from the TCGA and GTEx databases. The functions of these genes were investigated through GO enrichment and KEGG pathway analyses. Then, the key genes were selected by applying whole gene overall survival time. The expression of the key gene was studied in LUAD, and survival analysis was performed using Kaplan-Meier mapper, followed by univariate and multifactorial COX analysis. Finally, the gene expression and its prognostic significance in the pan-cancer were examined.

Results

A total of 10,106 DEGs were obtained from the two datasets. The top 266 differentially upregulated genes intersected with the top 1,497 overall survival-related genes, and 87 key genes were identified. High-expressed HMMR was associated with a poor prognosis of LUAD. Univariate and multifactorial Cox analysis showed that HMMR was an independent prognostic factor for LUAD patients. A high HMMR expression was strongly associated with the overall survival (OS) and disease-specific survival (DSS) in 11 cancer types and with poorer OS, DSS, and PFI in 10 cancer types.

Conclusion

HMMR may be an independent prognostic indicator and an important biomarker in diagnosing and predicting the survival of LUAD patients. Also, HMMR may be a key predictor of a variety of cancers.

Implications of prognosis-associated genes in pancreatic tumor metastasis: lessons from global studies in bioinformatics

Pancreatic cancer (PC) is a highly lethal malignancy with a 5-year survival rate of 10%. The occurrence of metastasis, among other hallmarks, is the main contributor to its poor prognosis. Consequently, the elucidation of metastatic genes involved in the aggressive nature of the disease and its poor prognosis will result in the development of new treatment modalities for improved management of PC. There is a deep interest in understanding underlying disease pathology, identifying key prognostic genes, and genes associated with metastasis. Computational approaches, which have become increasingly relevant over the last decade, are commonly used to explore such interests. This review aims to address global studies that have employed global approaches to identify prognostic and metastatic genes, while highlighting their methods and limitations. A panel of 48 prognostic genes were identified across these studies, but only five, including ANLN, ARNTL2, PLAU, TOP2A, and VCAN, were validated in multiple studies and associated with metastasis. Their association with metastasis has been further explored here, and the implications of these genes in the metastatic cascade have been interpreted.

Characteristic of molecular subtypes in lung adenocarcinoma based on m6A RNA methylation modification and immune microenvironment

BACKGROUND

Lung adenocarcinoma (LUAD) is a major subtype of lung cancer and closely associated with poor prognosis. N6-methyladenosine (m6A), one of the most predominant modifications in mRNAs, is found to participate in tumorigenesis. However, the potential function of m6A RNA methylation in the tumor immune microenvironment is still murky.

METHODS

The gene expression profile cohort and its corresponding clinical data of LUAD patients were downloaded from TCGA database and GEO database. Based on the expression of 21 m6A regulators, we identified two distinct subgroups by consensus clustering. The single-sample gene-set enrichment analysis (ssGSEA) algorithm was conducted to quantify the relative abundance of the fraction of 28 immune cell types. The prognostic model was constructed by Lasso Cox regression. Survival analysis and receiver operating characteristic (ROC) curves were used to evaluate the prognostic model.

RESULT

Consensus classification separated the patients into two clusters (clusters 1 and 2). Those patients in cluster 1 showed a better prognosis and were related to higher immune scores and more immune cell infiltration. Subsequently, 457 differentially expressed genes (DEGs) between the two clusters were identified, and then a seven-gene prognostic model was constricted. The survival analysis showed poor prognosis in patients with high-risk score. The ROC curve confirmed the predictive accuracy of this prognostic risk signature. Besides, further analysis indicated that there were significant differences between the high-risk and low-risk groups in stages, status, clustering subtypes, and immunoscore. Low-risk group was related to higher immune score, more immune cell infiltration, and lower clinical stages. Moreover, multivariate analysis revealed that this prognostic model might be a powerful prognostic predictor for LUAD. Ultimately, the efficacy of this prognostic model was successfully validated in several external cohorts (GSE30219, GSE50081 and GSE72094).

CONCLUSION

Our study provides a robust signature for predicting patients' prognosis, which might be helpful for therapeutic strategies discovery of LUAD.

Dauricine inhibits human pancreatic carcinoma cell proliferation through regulating miRNAs

Pancreatic cancer is one of the most malignant digestive tract tumors with the worst prognosis. Dauricine (Dau) can inhibit the proliferation of the pancreatic cancer cell line, and has the potential to be used as an adjuvant drug against pancreatic cancer; however, the working mechanism of Dau has not been elucidated. To unravel the effects and mechanisms of Dau on proteins and metabolic pathways, we evaluated the mRNA and microRNA expression in BxPC3 cells treated with Dau. The differences in the gene expression were compared using principal component analysis using mRNA and miRNA data to detect and analyze the sample discrimination. 187 miRNA and 907 mRNA that were significantly differentially expressed were identified using Python programming. On comparing genes and miRNAs in the DISEASES database, 79 known miRNA and 47 mRNA were found to be affected by Dau. The up-regulated and down-regulated genes were annotated with GO biological processes to determine the functional effect. Interactions between mRNA and mRNA were analyzed using the STRING database and the miRBase database was queried to obtain experimentally verified interactions between miRNA and mRNA as edges of miRNA and mRNA in the network. Finally, 413 sites and 2125 sides of the network were obtained, including 1 up-regulated and 18 down-regulated miRNAs. The expression of 19 miRNAs was identified by qPCR. The analysis of the protein-protein interaction network, using the Molecular Complex Detection (MCODE) plug-in of cytoscape, helped in identifying 12 important sub-networks. Most subnets are indirectly or directly related to specific miRNAs. This study provides evidence for the anticancer effect of Dau as a potential anticancer compound.

Alternatively spliced ANLN isoforms synergistically contribute to the progression of head and neck squamous cell carcinoma

Head and neck squamous cell carcinoma (HNSCC) is a common cancer with high mortality. Anilin actin-binding protein (ANLN) has been reported to be associated with carcinogenesis in multiple tumors. However, the expression pattern and functional effects of ANLN in HNSCC remain to be unclear. Clinical data and online databases were used to analyze the expression of ANLN and its relationship with HNSCC patient survival. Expression of two major splice variants of ANLN was assessed in HNSCC tissues and cell lines. The functional effects and related mechanisms of ANLN isoforms were investigated in HNSCC in vitro and in vivo. Our study showed that patients with high expression of ANLN had a poor prognosis. The two primary isoforms of ANLN transcripts ANLN-201 and ANLN-210 were highly expressed in HNSCC tissues and cell lines. Knockout of ANLN restrained cell proliferation, migration, and invasion of SCC-9 cells. Mechanically, ANLN-201 could interact with c-Myc to keep its protein stability, thereby playing a oncogenic role in HNSCC. ANLN-210 could be transferred to macrophages via exosomes by binding to RNA-binding protein hnRNPC. Exosomal ANLN-210 promoted macrophage polarization via PTEN/PI3K/Akt signaling pathway, thus stimulating tumor growth of HNSCC. ANLN was an independent prognostic factor in patients with HNSCC. Alternatively spliced ANLN isoforms collaboratively promote HNSCC tumorigenesis in vitro and in vivo, which might provide the in-depth role and mechanism of ANLN in HNSCC development.

Knockdown of circ‑PVT1 inhibits the progression of lung adenocarcinoma and enhances the sensitivity to cisplatin via the miR‑429/FOXK1 signaling axis

Lung cancer is one of the most prevalent cancers in China, and its incidence and morbidity remain high due to various independent factors. Lung adenocarcinoma (ADC) is the most common type of non‑small cell lung carcinoma. Circular RNA plasmacytoma variant translocation 1 (circ‑PVT1) plays an oncogenic role in various types of cancer, but the specific role of circ‑PVT1 in lung ADC has not yet been reported. In the present study, circ‑PVT1 was knocked down in A549 cells and the cell viability, proliferation, migration and invasion were measured via MTT, colony formation, wound healing and Transwell assays, respectively. Then, the cell viability of A549 cells with circ‑PVT1‑knockdown or ‑overexpression was detected after exposure to cisplatin (DDP). After confirming the associations among circ‑PVT1, microRNA (miR)‑429 and forkhead box k1 (FOXK1) using various tools and assays, the cellular functions of A549 cells treated with combined short hairpin (sh)RNA‑circ‑PVT1 and miR‑429 inhibitor/pcDNA3.1‑FOXK1 were tested again. The expression of circ‑PVT1 was found to be increased in lung ADC cells, and shRNA‑circ‑PVT1 led to decreased cell viability, proliferation, migration and invasion. The expression of circ‑PVT1 was higher in A549/DDP cells than that in A549 cells, and the activity of caspase‑3 was also activated by DDP in A549/DDP cells transfected with shRNA‑circ‑PVT1, whereas it was inactivated by DDP in A549 cells transfected with circ‑PVT1 overexpression plasmid. Furthermore, the decreased cell viability, proliferation, invasion and migration induced by shRNA‑circ‑PVT1 could be abated by transfection with miR‑429 inhibitor and pcDNA3.1‑FOXK1. In conclusion, interference of circ‑PVT1 inhibits the progression of lung ADC and enhances its sensitivity to DDP via miR‑429/FOXK1, which may provide a theoretical basis for the use of novel targets in the treatment of lung ADC.

Circular RNA circ-MMP11 Contributes to Lapatinib Resistance of Breast Cancer Cells by Regulating the miR-153-3p/ANLN Axis

Background

Drug-resistance is a major obstacle to the treatment of breast cancer. Circular RNA (circRNA) circ-MMP11 has been reported to be promoting the progression of breast cancer. This study is designed to explore the role and mechanism of circ-MMP11 in lapatinib resistance in breast cancer.

Methods

Circ-MMP11, microRNA-153-3p (miR-153-3p), and Anillin (ANLN) levels were detected by real-time quantitative polymerase chain reaction (RT-qPCR). Cell viability, number of colonies, apoptosis, migration, and invasion were detected by 3-(4,5-dimethyl-2-thiazolyl)-2,5-diphenyl-2-H-tetrazolium bromide (MTT), colony formation, flow cytometry, and transwell assays, respectively. Exosomes were exerted and detected by differential centrifugation and a transmission electron microscope. The protein levels of CD63, CD9, and ANLN were assessed by western blot assay. The binding relationship between miR-153-3p and circ-MMP11 or ANLN was predicted by circinteractome or starbase, and then verified by a dual-luciferase reporter assay and RNA pull-down assay. The biological role of circ-MMP11 on breast cancer tumor growth and drug resistance was detected by the xenograft tumor model in vivo.

Results

Circ-MMP11 and ANLN were highly expressed, and miR-153-3p was decreased in LR breast cancer tissues and cells. Circ-MMP11 could be transported by exosomes. Furthermore, circ-MMP11 knockdown promoted lapatinib sensitivity by repressing cell viability, colony number, migration, invasion, and boosting apoptosis in LR breast cancer cells. Circ-MMP11 deficiency improved the drug sensitivity of breast cancer in vivo. Mechanically, circ-MMP11 could regulate ANLN expression through sponging miR-153-3p.

Conclusion

Circ-MMP11 could be transferred by exosomes in breast cancer cells. And circ-MMP11 functioned as a sponge of miR-153-3p to regulate ANLN expression, thereby promoting lapatinib resistance in breast cancer cells, providing therapeutic targets for the treatment of breast cancer.

ANLN promotes carcinogenesis in oral cancer by regulating the PI3K/mTOR signaling pathway

Background

Oral cancer is a malignant disease that threatenshuman life and greatly reducespatientquality of life. ANLN was reported to promote the progression of cancer. This study aims to investigate the role of ANLNin oral cancer and the underlying molecular mechanism.

Methods

ANLN expression was downregulated by RNAi technology. The effect of ANLN on cell behaviors, including proliferation, cell cycle progression, invasion, and apoptosis, was detected. Western blotting analysis was used to explore the mechanism by whichANLN functions in oral cancer.

Results

Data from TCGA database showed that ANLN was expressed at significantly higher levels in tumor tissues thanin normal control tissues. Patients with higher ANLN expression exhibitedshorter survivaltimes. ANLN was alsoabundantly expressedin the cancer cell lines CAL27 and HN30. When ANLN was knocked down in CAL27 and HN30 cells, cell proliferation and colony formation weredecreased. The cell invasion ability was also inhibited. However, the cell apoptosis rate was increased. In addition, the levels of critical members of the PI3K signaling pathway, includingPI3K, mTOR, Akt, and PDK-1, were significantlyreducedafter ANLN was knocked down in CAL27 cells.

Conclusions

ANLN contributes to oral cancerprogressionand affects activation ofthe PI3K/mTOR signaling pathway. This study providesa new potential targetfor drug development and treatment in oral cancer.

Identification of novel biomarkers involved in pulmonary arterial hypertension based on multiple-microarray analysis

Pulmonary arterial hypertension (PAH) is a life-threatening chronic cardiopulmonary disorder. However, studies providing PAH-related gene expression profiles are scarce. To identify hub genes involved in PAH, we investigate two microarray data sets from gene expression omnibus (GEO). A total of 150 differentially expressed genes (DEGs) were identified by limma package. Enriched Gene Ontology (GO) annotations and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways of DEGs mostly included mitotic nuclear division, ATPase activity, and Herpes simplex virus one infection. Ten hub genes from three significant modules were ascertained by Cytoscape (CytoHubba). Gene set enrichment analysis (GSEA) plots showed that transcription elongation factor complex was the most significantly enriched gene set positively correlated with the PAH group. At the same time, solute proton symporter activity was the most significantly enriched gene set positively correlated with the control group. Correlation analysis between hub genes suggested that SMC4, TOP2A, SMC2, KIF11, KIF23, ANLN, ARHGAP11A, SMC3, SMC6 and RAD50 may involve in the pathogenesis of PAH. Then, the miRNA-target genes regulation network was performed to unveil the underlying complex association among them. Finally, RNA extracted from monocrotaline (MCT)-induced Rat-PAH model lung artery tissues were to conduct quantitative real-time PCR (qRT-PCR) to validate these hub genes. In conclusion, our study offers new evidence for the underlying molecular mechanisms of PAH as well as attractive targets for diagnosis and treatment of PAH.

A new 7-gene survival score assay for pancreatic cancer patient prognosis prediction

Gene expression features that are valuable for pancreatic ductal adenocarcinoma (PDAC) prognosis are still largely unknown. We aimed to explore pivotal molecular signatures for PDAC progression and establish an efficient survival score to predict PDAC prognosis. Overall, 163 overlapping genes were identified from three statistical methods, including differentially expressed genes (DEGs), coexpression network analysis (WGCNA), and target genes for miRNAs that were significantly related to PDAC patients' overall survival (OS). Then, according to the optimal value of the cross-validation curve (lambda = 0.031), 7 non-zero coefficients (ARNTL2, DSG3, PTPRR, ANLN, S100A14, ANKRD22, and TSPAN7) were selected to establish a prognostic prediction model of PDAC patients. We further confirmed the expression level of 7 genes using RT-PCR, western blot, and immunohistochemistry staining in PDAC patients' tissues. Our results showed that the ROC curve of the 7-mRNA model indicated good predictive ability for 1- and 2-year OS in three datasets (TCGA: 0.71, 0.69; ICGC: 0.8, 0.74; GEO batch: 0.61, 0.7, respectively). The hazard ratio (HR) of the low-risk group had a similar significant result (TCGA: HR = 0.3723; ICGC: HR = 0.2813; GEO batch: HR = 0.4999; all P < 0.001). Furthermore, Log-rank test results in three cohorts showed that the 7-mRNA assay excellently predicted the prognosis and metastasis, especially in TNM stage I&II subgroups of PDAC. In conclusion, the strong validation of our 7-mRNA signature indicates the promising effectiveness of its clinical application, especially in patients with TNM stages I&II.

Actin-binding protein Anillin promotes the progression of gastric cancer in vitro and in mice

BACKGROUND

To detect the expression levels of actin-binding protein anillin (ANLN) in human gastric cancer (GC) tissues and explore the possible involvement of ANLN in GC cell proliferation, migration, and invasion.

METHODS

The bioinformation analysis was performed in TCGA database to explore the expression of ANLN in human GC tissues and the difference of ANLN expression between multiple types of cancers. IHC assays and clinical pathological analysis were performed to confirm ANLN expression and its correlation with clinical features of GC patients. Colony formation, CCK-8, wound closure, and transwell assays were performed to detect its effects on GC cell proliferation, migration, and invasion in vitro. Tumor growth was also measured using a xenograft animal model.

RESULTS

We found the high expression of ANLN in human GC tissues based on the results from TCGA database and IHC staining. We further noticed ANLN depletion resulted in the inhibition of GC cell proliferation, migration, and invasion. Our data further confirmed that ANLN contributed to tumor growth of GC cells in vivo.

CONCLUSIONS

We confirmed the involvement of ANLN in GC progression and thought ANLN could serve as a promising therapeutic target for GC.

Anillin is an emerging regulator of tumorigenesis, acting as a cortical cytoskeletal scaffold and a nuclear modulator of cancer cell differentiation

Remodeling of the intracellular cytoskeleton plays a key role in accelerating tumor growth and metastasis. Targeting different cytoskeletal elements is important for existing and future anticancer therapies. Anillin is a unique scaffolding protein that interacts with major cytoskeletal structures, e.g., actin filaments, microtubules and septin polymers. A well-studied function of this scaffolding protein is the regulation of cytokinesis at the completion of cell division. Emerging evidence suggest that anillin has other important activities in non-dividing cells, including control of intercellular adhesions and cell motility. Anillin is markedly overexpressed in different solid cancers and its high expression is commonly associated with poor prognosis of patient survival. This review article summarizes rapidly accumulating evidence that implicates anillin in the regulation of tumor growth and metastasis. We focus on molecular and cellular mechanisms of anillin-dependent tumorigenesis that include both canonical control of cytokinesis and novel poorly understood functions as a nuclear regulator of the transcriptional reprogramming and phenotypic plasticity of cancer cells.

LncRNA XIST promotes chemoresistance of breast cancer cells to doxorubicin by sponging miR-200c-3p to upregulate ANLN

The resistance of breast cancer cells to drugs is a major obstacle to effective cancer chemotherapy. Here, we study the function mechanisms of long non-coding RNA XIST in chemoresistance of breast cancer to doxorubicin. We examined the 50% inhibitive concentration of doxorubicin to MDA-MB-231 and MDA-MB-231/ADM cells, showing that the doxorubicin resistance of MDA-MB-231/ADM cells was much higher than MDA-MB-231 cells. The gene or protein expression of XIST and ANLN were also higher in MDA-MB-231/ADM cells than that in MDA-MB-231 cells. Moreover, XIST overexpression promoted cell proliferation and inhibited apoptosis of doxorubicin-treated MDA-MB-231 cells by promoting ANLN expression. XIST silencing inhibited cell proliferation and promoted apoptosis of doxorubicin-treated MDA-MB-231/ADM cells by inhibiting ANLN expression. Luciferase reporter assay showed that XIST functioned as a competing endogenous RNA to repress miR-200c-3p, which controlled its downstream target ANLN. In conclusion, these data reveal that XIST promotes chemoresistance of breast cancer cells to doxorubicin by sponging miR-200c-3p to upregulate ANLN. This work explores the relationship between lncRNA XIST and doxorubicin resistance in breast cancer cells and highlights a novel therapeutic target for the treatment of breast cancer.

Pristimerin exerts antitumor activity against MDA-MB-231 triple-negative breast cancer cells by reversing of epithelial-mesenchymal transition via downregulation of integrin β3

Background

Pristimerin, a natural flavonoid compound, has potential anti-tumor activities. These activities have been illustrated in various cancer cell lines, including MDA-MB-231 cells. MDA-MB-231 cells are a representative mesenchymal subtype of triple negative breast cancer (MES-TNBC) cell line. Currently, the main treatment for patients with advanced MES-TNBC is cytotoxic chemotherapy. We tried to examine the role and effect of pristimerin on epithelial–mesenchymal transition (EMT) in MDA-MB-231 cells.

Methods

The effects of pristimerin on the proliferation of MDA-MB-231 cells were investigated by cloning formation growth assay. In vitro transwell and adhesion assays were performed for cell invasion and adhesion. The expression levels of EMT markers in E-cadherin and N-cadherin were examined by western blotting. We also established overexpressed- and silenced-integrin β3 cell lines to evaluate the role of integrin β3 in mediating the EMT reversion events in MDA-MB-231 cells.

Results

Pristimerin inhibited cell proliferation, and its inhibitory effect was dose-dependent. We demonstrated that pristimerin reserved EMT by upregulating E-cadherin and downregulating N-cadherin expression. Meanwhile, we revealed that pristimerin inhibited mRNA and protein expression of integrin β3, which is a key heterodimeric transmembrane receptor associated with EMT. These inhibitory effects and reversion of EMT were enhanced when integrin β3 was knockdown in MDA-MB-231 cells, while the overexpression of integrin β3 attenuated these effects. In vivo studies using xenograft mouse model demonstrated that pristimerin inhibited tumor growth.

Conclusions

Our findings provide important insights into the effects of pristimerin on inhibiting cancer progression and EMT reversion by suppression of integrin β3.

Role of Anillin in Tumour: From a Prognostic Biomarker to a Novel Target

Anillin (ANLN), an actin-binding protein, reportedly plays a vital role in cell proliferation and migration, particularly in cytokinesis. Although there have been findings pointing to a contribution of ANLN to the development of cancer, the association of ANLN to cancer remains not fully understood. Here, we gather evidence to determine the applicability of ANLN as a prognostic tool for some types of cancer, and the impact that ANLN has on the hallmarks of cancer. We searched academic repositories including PubMed and Google Scholar to find and review studies related to cancer and ANLN. The conclusion is that ANLN could be a potent target for cancer treatment, but the roles ANLN, other than in cytokinesis and its influence on tumour microenvironment remodeling in cancer development, must be further elucidated, and specific ANLN inhibitors should be found.

Comprehensive Analysis of Competing Endogenous RNA (ceRNA) Network Based on RNAs Differentially Expressed in Lung Adenocarcinoma Using The Cancer Genome Atlas (TCGA) Database

Background

The aim of this study was to explore a comprehensive analysis of the competing endogenous (ceRNA) network of lung adenocarcinoma and predict its regulatory mechanism and prognosis correlation based on The Cancer Genome Atlas (TCGA) database.

Material/Methods

The genes expression data from 535 lung adenocarcinoma cases and 59 normal tissue cases were acquired and downloaded from TCGA database, and differentially expressed messenger RNA (mRNA), long noncoding RNA (lncRNA) and microRNA (miRNA) were selected primarily by “edgeR” package in R software, which further constructs lncRNA-miRNA-mRNA ceRNA network. We then proceed to carry out Gene Ontology enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and Kaplan-Meier survival analysis of the mRNAs involved in the ceRNA network.

Results

There are 3 mRNAs (ANLN, IGFBP1, and TFAP2A) in differentially expressed genes, 4 lncRNAs (AC015923.1, FGF12-AS2, LINC00211, and MED4-AS1), and 2 miRNAs (miR-31 and miR-490) associated with the prognostic of lung adenocarcinoma. Besides, LINC00461 and has-mir-139 as key nodes were found in the ceRNA network. Significantly, miR-31 shows the greatest prognostic value related to the adverse effect of the prognostic of lung adenocarcinoma (P<0.001).

Conclusions

By analyzing the expression data of lung adenocarcinoma in TCGA database, we found that 3 mRNAs, 4 lncRNAs, and 2 miRNAs were screened as potential prognostic factors for lung adenocarcinoma. In addition, LINC00461 and has-mir-139 are 2 important regulatory network nodes in lung adenocarcinoma ceRNA.

Identification of Core Prognosis-Related Candidate Genes in Cervical Cancer via Integrated Bioinformatical Analysis

Purposes

Cervical cancer (CC) is one of the highest frequently occurred malignant gynecological tumors with high rates of morbidity and mortality. Here, we aimed to identify significant genes associated with poor outcome. Materials and methods. Differentially expressed genes (DEGs) between CC tissues and normal cervical tissues were picked out by GEO2R tool and Venn diagram software. Database for Annotation, Visualization and Integrated Discovery (DAVID) was performed to analyze gene ontology (GO) and Kyoto Encyclopedia of Gene and Genome (KEGG) pathway. The protein-protein interactions (PPIs) of these DEGs were visualized by Cytoscape with Search Tool for the Retrieval of Interacting Genes (STRING). Afterwards, Kaplan-Meier analysis was applied to analyze the overall survival among these genes. The Gene Expression Profiling Interactive Analysis (GEPIA) was applied for further validation of the expression level of these genes.

Results

The mRNA expression profile datasets of GSE63514, GSE27678, and GSE6791 were downloaded from the Gene Expression Omnibus database (GEO). In total, 76 CC tissues and 35 normal tissues were collected in the three profile datasets. There were totally 73 consistently expressed genes in the three datasets, including 65 up-regulated genes and 8 down-regulated genes. Of PPI network analyzed by Molecular Complex Detection (MCODE) plug-in, all 65 up-regulated genes and 4 down-regulated genes were selected. The results of the Kaplan-Meier survival analysis showed that 3 of the 65 up-regulated genes had a significantly worse prognosis, while 3 of the 4 down-regulated genes had a significantly better outcome. For validation in GEPIA, 4 of 6 genes (PLOD2, ANLN, AURKA, and AR) were confirmed to be significantly deregulated in CC tissues compared to normal tissues.

Conclusion

We have identified three up-regulated (PLOD2, ANLN, and AURKA) and a down-regulated DEGs (AR) with poor prognosis in CC on the basis of integrated bioinformatical methods, which could be regarded as potential therapeutic targets for CC patients.

Expression of OPN3 in lung adenocarcinoma promotes epithelial-mesenchymal transition and tumor metastasis

Background

Lung adenocarcinoma is the most common pathological lung cancer and an important cause of cancer‐related death. Metastasis is a major underlying reason for poor prognosis of lung adenocarcinoma. Opsin3 (OPN3), a member of the guanine nucleotide‐binding protein‐coupled receptor superfamily, has been identified to affect the apoptosis of hepatoma cells by modulating the phosphorylation of Akt and Bcl2/Bax. However, the expression and role of OPN3 in lung adenocarcinoma remains unclear.

Methods

Opsin3 expression in lung adenocarcinoma tissues was detected by western blot, qPCR, and immunohistochemistry. Changes in cell migration and invasion ability resulting from the change of OPN3 expression level were detected by wound healing and transwell migration assays. Changes in the markers of epithelial‐mesenchymal transformation were detected by western blot and qPCR.

Results

Opsin3 expression in lung adenocarcinoma tissues was higher than that in normal lung tissues. Patients with high expression of OPN3 had lower survival rates. Owing to overexpression of OPN3, the HCC827 cells showed enhanced invasion and migration ability in vitro. Upon decreasing the expression of OPN3, the invasion and migration ability of the A549 cells decreased.

Conclusion

Our study demonstrated for the first time that OPN3 gene enhanced the metastasis in lung adenocarcinoma, and its overexpression promoted epithelial‐mesenchymal transition.

Key points

A significant finding of the study was that OPN3 acted an oncogene in promoting lung adenocarcinoma metastasis. Our study complemented the research on the expression and function of OPN3 in lung adenocarcinoma.