ANLN Plays a Critical Role in Human Lung Carcinogenesis through the Activation of RHOA and by Involvement in the Phosphoinositide 3-Kinase/AKT Pathway

Novel genome-wide DNA methylation profiling reveals distinct epigenetic landscape, prognostic model and cellular composition of early-stage lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) has been a leading cause of cancer-related mortality worldwide. Early intervention can significantly improve prognosis. DNA methylation could occur in the early stage of tumor. Comprehensive understanding the epigenetic landscape of early-stage LUAD is crucial in understanding tumorigenesis.

METHODS

Enzymatic methyl sequencing (EM-seq) was performed on 23 tumors and paired normal tissue to reveal distinct epigenetic landscape, for compared with The Cancer Genome Atlas (TCGA) 450K methylation microarray data. Then, an integrative analysis was performed combined with TCGA LUAD RNA-seq data to identify significant differential methylated and expressed genes. Subsequently, the prognostic risk model was constructed and cellular composition was analyzed.

RESULTS

Methylome analysis of EM-seq comparing tumor and normal tissues identified 25 million cytosine-phosphate-guanine (CpG) sites and 30,187 differentially methylated regions (DMR) with a greater number of untraditional types. EM-seq identified a significantly higher number of CpG sites and DMRs compared to the 450K microarray. By integrating the differentially methylated genes (DMGs) with LUAD-related differentially expressed genes (DEGs) from the TCGA database, we constructed prognostic model based on six differentially methylated-expressed genes (MEGs) and verified our prognostic model in GSE13213 and GSE42127 dataset. Finally, cell deconvolution based on the in-house EM-seq methylation profile was used to estimate cellular composition of early-stage LUAD.

CONCLUSIONS

This study firstly delves into novel pattern of epigenomic DNA methylation and provides a multidimensional analysis of the role of DNA methylation revealed by EM-seq in early-stage LUAD, providing distinctive insights into its potential epigenetic mechanisms.

Differential whole-genome doubling based signatures for improvement on clinical outcomes and drug response in patients with breast cancer

Whole genome doublings (WGD), a hallmark of human cancer, is pervasive in breast cancer patients. However, the molecular mechanism of the complete impact of WGD on survival and treatment response in breast cancer remains unclear. To address this, we performed a comprehensive and systematic analysis of WGD, aiming to identify distinct genetic alterations linked to WGD and highlight its improvement on clinical outcomes and treatment response for breast cancer. A linear regression model along with weighted gene co-expression network analysis (WGCNA) was applied on The Cancer Genome Atlas (TCGA) dataset to identify critical genes related to WGD. Further Cox regression models with random selection were used to optimize the most useful prognostic markers in the TCGA dataset. The clinical implication of the risk model was further assessed through prognostic impact evaluation, tumor stratification, functional analysis, genomic feature difference analysis, drug response analysis, and multiple independent datasets for validation. Our findings revealed a high aneuploidy burden, chromosomal instability (CIN), copy number variation (CNV), and mutation burden in breast tumors exhibiting WGD events. Moreover, 247 key genes associated with WGD were identified from the distinct genomic patterns in the TCGA dataset. A risk model consisting of 22 genes was optimized from the key genes. High-risk breast cancer patients were more prone to WGD and exhibited greater genomic diversity compared to low-risk patients. Some oncogenic signaling pathways were enriched in the high-risk group, while primary immune deficiency pathways were enriched in the low-risk group. We also identified a risk gene, ANLN (anillin), which displayed a strong positive correlation with two crucial WGD genes, KIF18A and CCNE2. Tumors with high expression of ANLN were more prone to WGD events and displayed worse clinical survival outcomes. Furthermore, the expression levels of these risk genes were significantly associated with the sensitivities of BRCA cell lines to multiple drugs, providing valuable insights for targeted therapies. These findings will be helpful for further improvement on clinical outcomes and contribution to drug development in breast cancer.

Screening of miRNAs as prognostic biomarkers and their associated hub targets across Hepatocellular carcinoma using survival-based bioinformatics approach

BACKGROUND

The hepatocellular carcinoma (HCC) incident rate is gradually increasing yearly despite all the research and efforts taken by scientific communities and governing bodies. Approximately 90% of all liver cancer cases belong to HCC. Usually, HCC patients approach the treatment in the late stages of this malignancy which becomes the primary cause of high mortality rate. The knowledge about molecular pathogenesis of HCC is limited and needs more attention from researchers to identify the driver genes and miRNAs, which causes to translate this information into clinical practice. Therefore, the key regulators identification of miRNA-mRNA regulatory network is essential to identify HCC-associated genes.

METHODOLOGY

We extracted microRNA (miRNA) and messenger RNA (mRNA) expression datasets of normal and tumor HCC patient samples from UCSC Xena followed by identifying differentially expressed genes (DEGs) and differentially expressed miRNAs (DEMs). Univariate and multivariate cox-proportional hazard models were utilized to identify DEMs having significant association with overall survival (OS). Kaplan-Meier (KM) plotter was used to validate the presence of prognostic DEMs. A risk-score model was used to evaluate the effectiveness of KM-plotter validated DEMs combination on risk of samples. Target DEGs of prognostic miRNAs were identified via sources such as miRTargetLink and miRWalk followed by their validation in an external microarray cohort and enrichment analysis.

RESULTS

562 DEGs and 388 DEMs were identified followed by seven prognostic miRNAs (i.e., miR-19a, miR-19b, miR-30d-5p, miR-424-5p, miR-3677-5p, miR-3913-5p, miR-7705) post univariate, multivariate, risk-score model evaluation and KM-plotter analyses. ANLN, MRO, CPEB3 were their targets and were also validated in GSE84005 dataset.

CONCLUSIONS

The findings of this study decipher that most significant miRNAs and their identified target genes have association with apoptosis, inflammation, cell cycle regulation and cancer-related pathways, which appear to contribute to HCC pathogenesis and therefore, the discovery of new targets.

Vasculogenic mimicry-associated novel gene signature predicted prognosis and response to immunotherapy in lung adenocarcinoma

BACKGROUNDS

It was highlighted by recent studies on the biological significance of vasculogenic mimicry (VM) in tumorigenicity and progression. However, it is unclear whether VM also plays a potential role in immune regulation and tumor microenvironment (TME) formation.

METHODS

To identify patterns of VM alterations and VM-associated genetic features in non-small cell lung adenocarcinoma, we have screened 309 VM regulators and performed consensus molecular typing by the NMF algorithm. The ssGSEA and CIBORSORT algorithms were employed to measure the relative infiltration of distinct immune cell subpopulations. Individual tumors with immune responses were evaluated for alteration patterns of VM with typing-based differential genes.

RESULTS

In 490 LUAD samples, two distinctive VM alteration patterns connected to different clinical outcomes and biochemical pathways were established. TME characterization showed that the observed VM patterns were primarily saturated with cell proliferation and metabolic pathways and higher in immune cell infiltration of the C1 type. Vasculogenic mimicry-related genes (VMRG) risk scores were constructed to divide patients with lung adenocarcinoma into subgroups with high and low scores. Patients with lower scores had better immunological scores and longer survival times. Upon further investigation, higher scores were positively correlated with higher tumor mutation burden (TMB), M1-type macrophages and immune checkpoint molecules. Nevertheless, in two other immunotherapy cohorts, individuals with lower scores had enhanced immune responses and long-lasting therapeutic benefits. Finally, we monitored the ANLN gene from the VMRG model, which was highly expressed in lung adenocarcinoma tissues and negatively correlated with prognosis; it was also highly expressed in lung adenocarcinoma cell lines, and knockdown of ANLN elicited low expression of VEGFA, MMP2 and MMP9.

CONCLUSION

This study highlights that VM modifications are significantly associated with the diversity and complexity of TME, revealing new features of the immune microenvironment in lung adenocarcinoma and providing a new strategy for immunotherapy. Screening ANLN as a critical target for vasculogenic mimicry in lung adenocarcinoma provides a novel perspective for the targeted treatment of lung adenocarcinoma.

Screening ANLN and ASPM as bladder urothelial carcinoma-related biomarkers based on weighted gene co-expression network analysis

Introduction: Bladder cancer (BLCA) is one of the most common malignancies in the urinary system with a poor prognosis and high treatment costs. Identifying potential prognostic biomarkers is significant for exploring new therapeutic and predictive targets of BLCA.

Methods: In this study, we screened differentially expressed genes using the GSE37815 dataset. We then performed a weighted gene co‐expression network analysis (WGCNA) to identify the genes correlated with the histologic grade and T stage of BLCA using the GSE32548 dataset. Subsequently, Kaplan Meier survival analysis and Cox regression were used to further identify prognosis‐related hub genes using the datasets GSE13507 and TCGA‐BLCA. Moreover, we detected the expression of the hub genes in 35 paired samples, including BLCA and paracancerous tissue, from the Shantou Central Hospital by qRT‐polymerase chain reaction.

Results: This study showed that Anillin (ANLN) and Abnormal spindle-like microcephaly-associated gene (ASPM) were prognostic biomarkers for BLCA. High expression of ANLN and ASPM was associated with poor overall survival.The qRT‐PCR results revealed that ANLN and ASPM genes were upregulated in BLCA, and there was a correlation between the expression of ANLN and ASPM in cancer tissues and paracancerous tissue. Additionally, the increasing multiples in the ANLN gene was obvious in high-grade BLCA.

Discussion: In summary, this preliminary exploration indicated a correlation between ANLN and ASPM expression. These two genes, serving as the risk factors for BLCA progression, might be promising targets to improve the occurrence and progression of BLCA.

Targeting USP10 induces degradation of oncogenic ANLN in esophageal squamous cell carcinoma

Anillin (ANLN) is a mitosis-related protein that promotes contractile ring formation and cytokinesis, but its cell cycle-dependent degradation mechanisms in cancer cells remain unclear. Here, we show that high expression of ANLN promotes cytokinesis and proliferation in esophageal squamous cell carcinoma (ESCC) cells and is associated with poor prognosis in ESCC patients. Furthermore, the findings of the study showed that the deubiquitinating enzyme USP10 interacts with ANLN and positively regulates ANLN protein levels. USP10 removes the K11- and K63-linked ubiquitin chains of ANLN through its deubiquitinase activity and prevents ANLN ubiquitin-mediated degradation. Importantly, USP10 promotes contractile ring assembly at the cytokinetic furrow as well as cytokinesis by stabilizing ANLN. Interestingly, USP10 and the E3 ubiquitin ligase APC/C co-activator Cdh1 formed a functional complex with ANLN in a non-competitive manner to balance ANLN protein levels. In addition, the macrolide compound FW-04-806 (F806), a natural compound with potential for treating ESCC, inhibited the mitosis of ESCC cells by targeting USP10 and promoting ANLN degradation. F806 selectively targeted USP10 and inhibited its catalytic activity but did not affect the binding of Cdh1 to ANLN and alters the balance of the USP10-Cdh1-ANLN complex. Additionally, USP10 expression was positively correlated with ANLN level and poor prognosis of ESCC patients. Overall, targeting the USP10-ANLN axis can effectively inhibit ESCC cell-cycle progression.

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.

Analysis of prognostic model based on immunotherapy related genes in lung adenocarcinoma

Lung cancer is one of the most common malignant tumors, and ranks high in the list of mortality due to cancers. Lung adenocarcinoma (LUAD) is the most common subtype of lung cancer. Despite progress in the diagnosis and treatment of lung cancer, the prognosis of these patients remains dismal. Therefore, it is crucial to identify the predictors and treatment targets of lung cancer to provide appropriate treatments and improve patient prognosis. In this study, the gene modules related to immunotherapy were screened by weighted gene co-expression network analysis (WGCNA). Using unsupervised clustering, patients in The Cancer Genome Atlas (TCGA) were divided into three clusters based on the gene expression. Next, gene clustering was performed on the prognosis-related differential genes, and a six-gene prognosis model (comprising PLK1, HMMR, ANLN, SLC2A1, SFTPB, and CYP4B1) was constructed using least absolute shrinkage and selection operator (LASSO) analysis. Patients with LUAD were divided into two groups: high-risk and low-risk. Significant differences were found in the survival, immune cell infiltration, Tumor mutational burden (TMB), immune checkpoints, and immune microenvironment between the high- and low-risk groups. Finally, the accuracy of the prognostic model was verified in the Gene Expression Omnibus (GEO) dataset in patients with LUAD (GSE30219, GSE31210, GSE50081, GSE72094).

Identifying the genes impacted by cell proliferation in proteomics and transcriptomics studies

Hypothesis-free high-throughput profiling allows relative quantification of thousands of proteins or transcripts across samples and thereby identification of differentially expressed genes. It is used in many biological contexts to characterize differences between cell lines and tissues, identify drug mode of action or drivers of drug resistance, among others. Changes in gene expression can also be due to confounding factors that were not accounted for in the experimental plan, such as change in cell proliferation. We combined the analysis of 1,076 and 1,040 cell lines in five proteomics and three transcriptomics data sets to identify 157 genes that correlate with cell proliferation rates. These include actors in DNA replication and mitosis, and genes periodically expressed during the cell cycle. This signature of cell proliferation is a valuable resource when analyzing high-throughput data showing changes in proliferation across conditions. We show how to use this resource to help in interpretation of in vitro drug screens and tumor samples. It informs on differences of cell proliferation rates between conditions where such information is not directly available. The signature genes also highlight which hits in a screen may be due to proliferation changes; this can either contribute to biological interpretation or help focus on experiment-specific regulation events otherwise buried in the statistical analysis.

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.

ARHGEF40 promotes non-small cell lung cancer proliferation and invasion via the AKT-Wnt axis by binding to RhoA

Rho guanine nucleotide exchange factor 40 (ARHGEF40) is a member of the Dbl-family of guanine nucleotide factor proteins. However, its expression pattern and biological function in malignant tumors, notably in nonsmall cell lung cancer (NSCLC) are currently unknown. The present study demonstrated that ARHGEF40 was highly expressed in NSCLC specimens and that its expression was significantly associated with advanced TNM stage (p < 0.001), lymph node metastasis (p = 0.002), and poor prognosis (p = 0.0056). In addition, ARHGEF40 accelerated nuclear translocation of the key component β-catenin and increased the expression levels of the Wnt signaling pathway targets c-myc, cyclin D1 and MMP7. Moreover, it promoted lung cancer cell proliferation and invasion in vitro and in vivo. To elucidate the underlying molecular mechanism, the current study demonstrated that ARHGEF40 could induce activation of the Wnt signaling pathway by increasing the phosphorylation levels of AKT and GSK3β via interaction with RhoA. Moreover, the Dbl homology (DH)-pleckstrin homology (PH) domain of ARHGEF40 was responsible for this interaction. Its deletion abolished the binding, which blocked the activation of the Wnt signaling. Taken together, the data indicated that ARHGEF40 promoted the malignant phenotype of lung cancer cells by activating the AKT-Wnt axis. This was achieved by its interaction with RhoA via the DH-PH domain. ARHGEF40 may serve as a novel target for NSCLC treatment.

Pan-cancer analysis of the prognostic and immunological role of ANLN: An onco-immunological biomarker

Anillin actin-binding protein (ANLN) is crucially involved in cell proliferation and migration. Moreover, ANLN is significantly in tumor progression in several types of human malignant tumors; however, it remains unclear whether ANLN acts through common molecular pathways within different tumor microenvironments, pathogeneses, prognoses and immunotherapy contexts. Therefore, this study aimed to perform bioinformatics analysis to examine the correlation of ANLN with tumor immune infiltration, immune evasion, tumor progression, immunotherapy, and tumor prognosis. We observed increased ANLN expression in multiple tumors, which could be involved in tumor cell proliferation, migration, infiltration, and prognosis. The level of ANLN methylation and genetic alteration was associated with prognosis in numerous tumors. ANLN facilitates tumor immune evasion through different mechanisms, which involve T-cell exclusion in different cancer types and tumor-infiltrating immune cells in colon adenocarcinoma, kidney renal clear cell carcinoma, liver hepatocellular carcinoma, and prostate adenocarcinoma. Additionally, ANLN is correlated with immune or chemotherapeutic outcomes in malignant cancers. Notably, ANLN expression may be a predictive biomarker for the response to immune checkpoint inhibitors. Taken together, our findings suggest that ANLN can be used as an onco-immunological biomarker and could serve as a hallmark for tumor screening, prognosis, individualized treatment design, and follow-up.

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.

Targeting anillin inhibits tumorigenesis and tumor growth in hepatocellular carcinoma via impairing cytokinesis fidelity

Targeting cytokinesis can suppress tumor growth by blocking cell division and promoting apoptosis. We aimed to characterize key cytokinesis regulator in hepatocellular carcinoma (HCC) progression, providing insights into identifying promising HCC therapeutic targets. The unbiased bioinformatic screening identified Anillin actin binding protein (ANLN) as a critical cytokinesis regulator involved in HCC development. Functional assay demonstrated that knockdown of ANLN inhibited HCC growth by inducing cytokinesis failure and DNA damage, leading to multinucleation and mitotic catastrophe. Mechanistically, ANLN acts as a scaffold to strengthen interaction between RACGAP1 and PLK1. ANLN promotes PLK1-mediated RACGAP1 phosphorylation and RhoA activation to ensure cytokinesis fidelity. To explore the function of ANLN in HCC tumorigenesis, we hydrodynamically transfected c-Myc and NRAS plasmids into Anln^+/+, Anln^+/-, and Anln^-/- mice through tail vein injection. Hepatic Anln ablation significantly impaired c-Myc/NRAS-driven hepatocarcinogenesis. Moreover, enhanced hepatic polyploidization was observed in Anln ablation mice, manifesting as increasing proportion of cellular and nuclear polyploidy. Clinically, ANLN is upregulated in human HCC tissues and high level of ANLN is correlated with poor patients' prognosis. Additionally, the proportion of cellular polyploidy decreases during HCC progression and ANLN level is significantly correlated with cellular polyploidy proportion in human HCC samples. In conclusion, ANLN is identified as a key cytokinesis regulator contributing to HCC initiation and progression. Our findings revealed a novel mechanism of ANLN in the regulation of cytokinesis to promote HCC tumorigenesis and growth, suggesting targeting ANLN to inhibit cytokinesis may be a promising therapeutic strategy for HCC.

Development and Validation of a Novel Hypoxia Score for Predicting Prognosis and Immune Microenvironment in Rectal Cancer

Hypoxia plays a major role in various tumor types. However, few studies have concentrated on the prognostic model of hypoxia-related genes in rectal cancer and the effect of hypoxia on neutrophil-mediated immunosuppression. We performed Kaplan–Meier analysis, random survival forest analysis, and Cox regression analysis on 342 hypoxia-related genes, constructed hypoxia score in the Gene Expression Omnibus (GEO) cohort, and verified them in the Cancer Genome Atlas (TCGA) cohort. Then the patients were divided into two groups according to the risk level. The overall survival rate of the high-risk (HRisk) group was significantly higher than that of the low-risk (LRisk) group (GEO, p < 0.001; TCGA, p = 0.016). Through receiver operating characteristic and decision curve analysis, the nomogram based on hypoxia score has excellent prediction ability. Functional enrichment analysis showed that hypoxia, metastasis, inflammation, immunity, and other related pathways were enriched. The HRisk group was associated with lower tumor purity, higher immune and stromal score, higher neutrophils, and lower activated memory CD4 + T cells. More importantly, the checkpoint of neutrophil-mediated immunosuppression increased in the HRisk group. In conclusion, a hypoxia score based on 5 hypoxia-related genes can be used to predict the prognosis of rectal cancer and ANLN with a cancer-suppressing effect and SRPX (Sushi Repeat Containing Protein X-Linked) with a cancer-promoting effect may be potential therapeutic targets for rectal cancer.

Screening and Validation of Significant Genes with Poor Prognosis in Pathologic Stage-I Lung Adenocarcinoma

Background

Although more pathologic stage-I lung adenocarcinoma (LUAD) was diagnosed recently, some relapsed or distantly metastasized shortly after radical resection. The study aimed to identify biomarkers predicting prognosis in the pathologic stage-I LUAD and improve the understanding of the mechanisms involved in tumorigenesis.

Methods

We obtained the expression profiling data for non-small cell lung cancer (NSCLC) patients from the NCBI-GEO database. Differentially expressed genes (DEGs) between early-stage NSCLC and normal lung tissue were determined. After function enrichment analyses on DEGs, the protein-protein interaction (PPI) network was built and analyzed with the Search Tool for the Retrieval of Interacting Genes (STRING) and Cytoscape. Overall survival (OS) and mRNA levels of genes were performed with Kaplan–Meier analysis and Gene Expression Profiling Interactive Analysis (GEPIA). qPCR and western blot analysis of hub genes in stage-I LUAD patients validated the significant genes with poor prognosis.

Results

A total of 172 DEGs were identified, which were mainly enriched in terms related to management of extracellular matrix (ECM), receptor signaling pathway, cell adhesion, activity of endopeptidase, and receptor. The PPI network identified 11 upregulated hub genes that were significantly associated with OS in NSCLC and highly expressed in NSCLC tissues compared with normal tissues by GEPIA. Elevated expression of ANLN, EXO1, KIAA0101, RRM2, TOP2A, and UBE2T were identified as potential risk factors in pathologic stage-I LUAD. Except for ANLN and KIAA0101, the hub genes mRNA levels were higher in tumors compared with adjacent non-cancerous samples in the qPCR analysis. The hub genes protein levels were also overexpressed in tumors. In vitro experiments showed that knockdown of UBE2T in LUAD cell lines could inhibit cell proliferation and cycle progression.

Conclusions

The DEGs can probably be used as potential predictors for stage-I LUAD worse prognosis and UBE2T may be a potential tumor promoter and target for treatment.

Comprehensive Analysis of ANLN in Human Tumors: A Prognostic Biomarker Associated with Cancer Immunity

Background

Anillin (ANLN), a ubiquitously expressed actin-binding protein, plays a critical tumor-promoting role in cell growth, migration, and cytokinesis. Numerous studies have suggested that ANLN is upregulated in many cancer types, as well as significantly associated with patient prognosis and malignant cancer characteristics. Herein, we performed an integrated pan-cancer analysis of ANLN and highlighted its underlying mechanism, which may benefit further exploration of the potential therapeutic options for cancer.

Methods

ANLN expression data were extracted from online databases, including TCGA, GTEx, and CCLE databases. The TIMER database was used to study the association between ANLN expression with immune checkpoint genes and immunocyte infiltration. The ScanNeo pipeline was adopted for neoantigen discovery. KEGG analysis and the STRING tool were used to elucidate the potential mechanism of ANLN in cancer development.

Results

ANLN is abnormally overexpressed in almost all cancer tissues compared with normal tissues. The high-ANLN expression level was positively associated with various malignant characteristics, suggesting its potential role in the immune microenvironment and poor prognosis. In addition, ANLN expression was correlated with the number of neoantigens and different phosphorylation pattern in various cancer types, revealing a functional role of genetic mutation accumulation and high phosphorylation in ANLN-mediated oncogenesis. Moreover, we found that ANLN was an important regulatory factor participating in many signaling events, especially the cell cycle and nucleocytoplasmic transport pathways.

Conclusions

ANLN expression is generally overexpressed in various types of cancers, and it may have an important influence on tumor progression and development. ANLN expression is significantly associated with the immune checkpoint biomarkers and tumor immunity. Together, these findings suggest that ANLN may be a predictive marker for patient prognosis across cancers.

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.

Integrated Analysis of Circular RNA-Associated ceRNA Network Reveals Potential circRNA Biomarkers in Human Breast Cancer

Circular RNA (circRNA) is closely related to tumorigenesis and cancer progression. Yet, the roles of cancer-specific circRNAs in the circRNA-related ceRNA network of breast cancer (BRCA) remain unclear. The aim of this study was to construct a ceRNA network associated with circRNA and to explore new therapeutic and prognostic targets and biomarkers for breast cancer. We downloaded the circRNA expression profile of BRCA from Gene Expression Omnibus (GEO) microarray datasets and downloaded the miRNA and mRNA expression profiles of BRCA from The Cancer Genome Atlas (TCGA) database. Differentially expressed mRNAs (DEmRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed circRNAs (DEcircRNAs) were identified, and a competitive endogenous RNA (ceRNA) regulatory network was constructed based on circRNA-miRNA pairs and miRNA-mRNA pairs. Gene ontology and pathway enrichment analyses were performed on mRNAs regulated by circRNAs in ceRNA networks. Survival analysis and correlation analysis of all mRNAs and miRNAs in the ceRNA network were performed. A total of 72 DEcircRNAs, 158 DEmiRNAs, and 2762 DE mRNAs were identified. The constructed ceRNA network contains 60 circRNA-miRNA pairs and 140 miRNA-mRNA pairs, including 40 circRNAs, 30 miRNAs, and 100 mRNAs. Functional enrichment indicated that DEmRNAs regulated by DEcircRNAs in ceRNA networks were significantly enriched in the PI3K-Akt signaling pathway, microRNAs in cancer, and proteoglycans in cancer. Survival analysis and correlation analysis of all mRNAs and miRNAs in the ceRNA network showed that 13 mRNAs and 6 miRNAs were significantly associated with overall survival, and 48 miRNA-mRNA interaction pairs had a significant negative correlation. A PPI network was established, and 21 hub genes were determined from the network. This study provides an effective bioinformatics basis for further understanding of the molecular mechanisms and predictions of breast cancer. A better understanding of the circRNA-related ceRNA network in BRCA will help identify potential biomarkers for diagnosis and prognosis.

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.

MiR-16-5p suppresses breast cancer proliferation by targeting ANLN

BACKGROUND

In recent years, gene expression-based analysis has been used for disease biomarker discovery, providing ways for better diagnosis, leading to improvement of clinical treatment efficacy. This study aimed to explore the role of miR-16-5p and ANLN in breast cancer (BC).

METHODS

Cohort datasets of BC were obtained from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) and analyzed by bioinformatics tools. qRT-PCR and western blotting were applied to validate ANLN and its protein expression. A dual-luciferase reporter assay was used to prove the regulatory relationship of miR-16-5p and ANLN. Finally, MTT, wound healing, Transwell invasion and flow cytometry analyses of the cell cycle and apoptosis were performed to assess cell proliferation, migration, invasion, cell cycle and apoptosis, respectively.

RESULTS

A total of 195 differentially expressed genes (DEGs) and 50 overlapping microRNAs (miRNAs) were identified. Among these DEGs and miRNAs, ANLN, associated with poor overall survival in BC, overlapped in the GSE29431, GSE42568, TCGA and GEPIA2 databases. Moreover, ANLN was highly expressed, while miR-16-5p was lower in BC cells than in breast epithelial cells. Then, we confirmed that ANLN was directly targeted by miR-16-5p in BC cells. Over-expression of miR-16-5p and knock-down of ANLN remarkably inhibited cell proliferation and migration as well as cell invasion, arrested the cells in G2/M phase and induced apoptosis in BC cells.

CONCLUSIONS

These findings suggest that miR-16-5p restrains proliferation, migration and invasion while affecting cell cycle and promotes apoptosis by regulating ANLN, thereby providing novel candidate biomarkers for the diagnosis and treatment of BC.

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.

Identification of Hub Genes in Pancreatic Ductal Adenocarcinoma Using Bioinformatics Analysis

Background:

To address the biomarkers that correlated with the prognosis of patients with PDCA using bioinformatics analysis.

Methods:

The raw data of genes were obtained from the Gene Expression Omnibus. We screened differently expressed genes (DEGs) by Rstudio. Database for Annotation, Visualization and Intergrated Discovery was used to investigate their biological function by Gene Ontology(GO) and Kyoto Encyclopedia of Genes (KEGG) analysis. Protein-protein interaction of these DEGs were analyzed based on the Search Tool for the Retrieval of Interacting Genes database (STRING) and visualized by Cytoscape. Genes calculated by Cyto-Hubba with degree >10 were identified as hub genes. Then, the identified hub genes were verified by UALCAN online analysis tool to evaluate the prognostic value in PDCA.

Results:

Three expression profiles (GSE15471, GSE16515 and GSE32676) were downloaded from GEO database. The three sets of DEGs exhibited an intersection consisting of 223 genes (214 upregulated DEGs and 9 downregulated DEGs). GO analysis showed that the 223 DEGs were significantly enriched in extracellular exosome, plasma membrane and extracellular space. ECM-receptor interaction, PI3K-Akt signaling pathway and Focal adhesion were the most significantly enriched pathway according to KEGG analysis. By combining the results of Cytohubba, 30 hub genes with a high degree of connectivity were picked out. Finally, we candidated 3 biomarkers by UALCAN online survival analysis, including CEP55, ANLN and PRC1.

Conclusion:

we identified CEP55, ANLN and PRC1 may be the potential biomarkers and therapeutic targets of PDCA, which used for prognostic assessment and scheme selection.

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.

Overexpression of anillin is related to poor prognosis in patients with hepatocellular carcinoma

BACKGROUND

Anillin (ANLN) is required for tumor growth. It has been proven that knockdown of ANLN effectively reduces the occurrence of hepatocellular carcinoma (HCC) in transgenic mice. However, the functional role of ANLN in HCC patients remains to be elucidated.

METHODS

Both microarray and TCGA project were used for the analyses of ANLN expression and regulation in HCC. The effect of ANLN on proliferation and cell cycle was detected by CCK-8, colony formation assay and flow cytometry. ANLN expression was measured by immunohistochemistry. Correlation between ANLN expression and clinicopathological features was assessed by Pearson Chi-square test and 5-year overall survival after liver resection was evaluated by Kaplan-Meier method.

RESULTS

Increased copy number, decreased methylation levels in the CpG island and upregulated histone hypermethylation of ANLN were found in HCC. Knockdown of ANLN inhibited proliferation and induced G2/M phase arrest in SMMC-7721 cells. ANLN was mainly expressed in the nucleus and showed significantly higher expression levels in cancerous tissues than those in paired adjacent tissues. Moreover, nuclear ANLN expression levels in HCC metastases were significantly higher than those in primary HCC. The results of Cox proportional hazards regression model suggested that ANLN nuclear expression in HCC was an independent risk factor for poor 5-year overall survival of patients after liver resection.

CONCLUSIONS

ANLN is a potential therapeutic target for HCC. Patients with nuclear ANLN overexpression in HCC tissue may need adjuvant therapy after liver resection.

Identifying molecular insight of synergistic complexities for SARS-CoV-2 infection with pre-existing type 2 diabetes

The ongoing COVID-19 outbreak, caused by SARS-CoV-2, has posed a massive threat to global public health, especially to people with underlying health conditions. Type 2 diabetes (T2D) is lethal comorbidity of COVID-19. However, its pathogenetic link remains unclear. This research aims to determine the genetic factors and processes contributing to the synergistic severity of SARS-CoV-2 infection among T2D patients through bioinformatics approaches. We analyzed two sets of transcriptomic data of SARS-CoV-2 infection obtained from lung epithelium cells and PBMCs, and two sets of T2D data from pancreatic islet cells and PBMCs to identify the associated differentially expressed genes (DEGs) followed by their functional enrichment analyses in terms of protein-protein interaction (PPI) to detect hub-proteins and associated comorbidities, transcription factors (TFs), microRNAs (miRNAs) as well as the potential drug candidates. In PPI analysis, four potential hub-proteins (i.e., BIRC3, C3, MME, and IL1B) were identified among 25 DEGs shared between the disease pair. Enrichment analyses using the mutually overlapped DEGs revealed the most prevalent GO and cell signalling pathways, including TNF signalling, cytokine-cytokine receptor interaction, and IL-17 signalling, which are related to cytokine activities. Furthermore, as significant TFs, we identified IRF1, KLF11, FOSL1, and CREB3L1 while miRNAs including miR-1-3p, 34a-5p, 16–5p, 155–5p, 20a-5p, and let-7b-5p were found to be noteworthy. The findings illustrated the significant association between COVID-19 and T2D at the molecular level. These genetic determinants can further be explored for their specific roles in disease progression and therapeutic intervention, while significant pathways can also be studied as molecular checkpoints. Finally, the identified drug candidates may be evaluated for their potency to minimize the severity of COVID-19 patients with pre-existing T2D.

A tumor microenvironment-related mRNA-ncRNA signature for prediction early relapse and chemotherapeutic sensitivity in early-stage lung adenocarcinoma

OBJECTIVES

Postoperative early relapse of early-stage lung adenocarcinoma is implicated in poor prognosis. The purpose of our study was to develop an integrated mRNA and non-coding RNA (ncRNA) signature to identify patients at high risk of early relapse in stage I-II lung adenocarcinoma who underwent complete resection.

METHODS

Early-stage lung adenocarcinoma data from Gene Expression Omnibus database were divided into training set and testing set. Propensity score matching analysis was performed between patients in early relapse group and long-term nonrelapse group from training set. Transcriptome analysis, random survival forest and LASSO Cox regression model were used to build an early relapse-related multigene signature. The robustness of the signature was evaluated in testing set and RNA-Seq dataset from The Cancer Genome Atlas (TCGA). The chemotherapy sensitivity, tumor microenvironment and mutation landscape related to the signature were explored using bioinformatics analysis.

RESULTS

Twelve mRNAs and one ncRNA were selected. The multigene signature achieved a strong power for early relapse prediction in training set (HR 3.19, 95% CI 2.16-4.72, P < 0.001) and testing set (HR 2.91, 95% CI 1.63-5.20, P = 0.002). Decision curve analyses revealed that the signature had a good clinical usefulness. Groups divided by the signature exhibited different chemotherapy sensitivity, tumor microenvironment characteristics and mutation landscapes.

CONCLUSIONS

Our results indicated that the integrated mRNA-ncRNA signature may be an innovative biomarker to predict early relapse of early-stage lung adenocarcinoma, and may provide more effective treatment strategies.

ANLN Enhances Triple-Negative Breast Cancer Stemness Through TWIST1 and BMP2 and Promotes its Spheroid Growth

ANLN is frequently upregulated in triple-negative breast cancer (TNBC) and its high expression in tumors are significantly associated with poor survival and recurrence, thereby it has been proposed to function as a prognostic marker for breast cancer. However, the specific function and molecular mechanisms by which ANLN promotes TNBC tumorigenesis remain elusive. Using multiomic profiling, we recently uncovered ANLN as a TNBC-specific gene driven by super-enhancer. Here, by Crispr/Cas9 editing, we showed that knockout of ANLN inhibits spheroid growth of TNBC. Interestingly, its effect on cell proliferation in 2D cultures is minimal. ANLN depletion inhibits mammosphere formation and clonogenicity potently, suggesting its important function in regulating cancer stem cells (CSCs). We screened a panel of stem cell-related genes and uncovered several CSC genes regulated by ANLN. We further identify TWIST1 and BMP2 as essential genes that mediate ANLN’s function in stemness but not spheroid growth. These findings may contribute to search for effective targeted therapies to treat TNBC.

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.

Exome hits demystified: The next frontier

Severe mental illnesses such as schizophrenia and bipolar disorder have complex inheritance patterns, involving both common and rare variants. Whole exome sequencing is a promising approach to find out the rare genetic variants. We had previously reported several rare variants in multiplex families with severe mental illnesses. The current article tries to summarise the biological processes and pattern of expression of genes harbouring the aforementioned variants, linking them to known clinical manifestations through a methodical narrative review. Of the 28 genes considered for this review from 7 families with multiple affected individuals, 6 genes are implicated in various neuropsychiatric manifestations including some variations in the brain morphology assessed by magnetic resonance imaging. Another 15 genes, though associated with neuropsychiatric manifestations, did not have established brain morphological changes whereas the remaining 7 genes did not have any previously recorded neuropsychiatric manifestations at all. Wnt/b-catenin signaling pathway was associated with 6 of these genes and PI3K/AKT, calcium signaling, ERK, RhoA and notch signaling pathways had at least 2 gene associations. We present a comprehensive review of biological and clinical knowledge about the genes previously reported in multiplex families with severe mental illness. A 'disease in dish approach' can be helpful to further explore the fundamental mechanisms.

Actin-binding protein anillin promotes the progression of hepatocellular carcinoma in vitro and in mice

Hepatocellular carcinoma (HCC) is a common type of tumor with high mortality worldwide. Investigations associated with the molecular etiology of HCC and screening novel therapeutic targets are still urgently in need. Anillin (ANLN), as a type of evolutionarily conserved actin-binding protein, is involved in multiple cellular processes. ANLN widely affected the progression and metastasis of several types of cancer, and its overexpression was frequently demonstrated in previous studies. The present study demonstrated high expression of ANLN in human HCC tissues, which was also associated the prognosis of patients with HCC. The associations between ANLN expression and the clinicopathological features were determined, including the number of tumor nodes (P=0.011) and tumor size (P=0.003) of patients with HCC. It was found that ANLN promoted cell proliferation, invasion and migration of HCC cells in vitro, and affected tumor growth in vivo. Therefore, ANLN is suggested as a promising therapeutic target for the treatment of HCC.

Molecular basis of functional exchangeability between ezrin and other actin-membrane associated proteins during cytokinesis

The mechanism that mediates the interaction between the contractile ring and the plasma membrane during cytokinesis remains elusive. We previously found that ERM (Ezrin/Radixin/Moesin) proteins, which usually mediate cellular pole contraction, become over-accumulated at the cell equator and support furrow ingression upon the loss of other actin-membrane associated proteins, anillin and supervillin. In this study, we addressed the molecular basis of the exchangeability between ezrin and other actin-membrane associated proteins in mediating cortical contraction during cytokinesis. We found that depletion of anillin and supervillin caused over-accumulation of the membrane-associated FERM domain and actin-binding C-terminal domain (C-term) of ezrin at the cleavage furrow, respectively. This finding suggests that ezrin differentially shares its binding sites with these proteins on the actin cytoskeleton or inner membrane surface. Using chimeric mutants, we found that ezrin C-term, but not the FERM domain, can substitute for the corresponding anillin domains in cytokinesis and cell proliferation. On the other hand, either the membrane-associated or the actin/myosin-binding domains of anillin could not substitute for the corresponding ezrin domains in controlling cortical blebbing at the cell poles. Our results highlight specific designs of actin- or membrane-associated moieties of different actin-membrane associated proteins with limited exchangeability, which enables them to support diverse cortical activities on the shared actin-membrane interface during cytokinesis.

Defining super-enhancer landscape in triple-negative breast cancer by multiomic profiling

Breast cancer is a heterogeneous disease, affecting over 3.5 million women worldwide, yet the functional role of cis-regulatory elements including super-enhancers in different breast cancer subtypes remains poorly characterized. Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer with a poor prognosis. Here we apply integrated epigenomic and transcriptomic profiling to uncover super-enhancer heterogeneity between breast cancer subtypes, and provide clinically relevant biological insights towards TNBC. Using CRISPR/Cas9-mediated gene editing, we identify genes that are specifically regulated by TNBC-specific super-enhancers, including FOXC1 and MET, thereby unveiling a mechanism for specific overexpression of the key oncogenes in TNBC. We also identify ANLN as a TNBC-specific gene regulated by super-enhancer. Our studies reveal a TNBC-specific epigenomic landscape, contributing to the dysregulated oncogene expression in breast tumorigenesis.

ANLN, Regulated by SP2, Promotes Colorectal Carcinoma Cell Proliferation via PI3K/AKT and MAPK Signaling Pathway

BACKGROUND

Aberrant expression of Anillin (ANLN) has been shown to function in the development of multiple cancers. However, its effects on colorectal carcinoma (CRC) remain unclear. We aimed to explore the role of ANLN in CRC development.

METHODS

By real-time quantitative polymerase chain reaction (RT-qPCR), Western blot, and immunohistochemistry (IHC), we assessed the expression level of ANLN in CRC tissues and cell lines. The role of ANLN in CRC cell proliferation was evaluated by CCK-8 assays, colony formation assays, EdU assays and cell cycle assays. A mouse tumorigenic model was established to evaluate the in vivo function of ANLN.

RESULTS

We found that ANLN was overexpressed in CRC tissues and cell lines. Highly expressed ANLN correlated with tumor size, tumor number, and stage in patients with CRC. Silencing ANLN in CRC cell lines suppressed proliferation both in vitro and in vivo and induced G0/G1 cell cycle arrest. Downregulation of ANLN led to reduced phosphorylated levels of AKT and ERK. However, total AKT protein showed no change. SP2, a critical transcription factor, was implicated in the upregulation of ANLN.

CONCLUSIONS

Our study demonstrated that ANLN regulates CRC cell proliferation via the PI3K/AKT and MAPK pathways, indicating that ANLN may represent a novel and effective target for CRC treatment.

A prognosis-related molecular subtype for early-stage non-small lung cell carcinoma by multi-omics integration analysis

Background

Early-stage non-small cell lung carcinoma (NSCLC) accounts for more than 80% of lung cancer, which is a kind of cancer with high heterogeneity, so the genetic heterogeneity and molecular subtype should be explored.

Methods

Partitioning Around Medoid algorithm was used to acquire the molecular subtype for early-stage NSCLC based on prognosis-related mRNAs and methylation sites. Random forest (RF) and support vector machine (SVM) were used to build prediction models for subtypes.

Results

Six prognosis-related subtypes for early-stage NSCLC, including 4 subtypes for lung squamous cell carcinoma (LUSC) and 2 subtypes for lung adenocarcinoma (LUAD), were identified. There were highly expressed and hypermethylated gene regions for LUSC-C1 and LUAD-C2, highly expressed region for LUAD-C1, and hypermethylated regions for LUSC-C3 and LUSC-C4. Molecular subtypes for LUSC were mainly determined by DNA methylation (14 mRNAs and 362 methylation sites). Molecular subtypes for LUAD were determined by both mRNA and DNA methylation information (143 mRNAs and 458 methylation sites). Ten methylation sites were selected as biomarkers for prediction of LUSC-C1 and LUSC-C3, respectively. Nine genes and 1 methylation site were selected as biomarkers for LUAD subtype prediction. These subtypes can be predicted by the selected biomarkers with RF and SVM models.

Conclusions

In conclusion, we proposed a prognosis-related molecular subtype for early-stage NSCLC, which can provide important information for personalized therapy of patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-07846-0.

Spatiotemporal dissection of the cell cycle with single-cell proteogenomics

The cell cycle, over which cells grow and divide, is a fundamental process of life. Its dysregulation has devastating consequences, including cancer^1-3. The cell cycle is driven by precise regulation of proteins in time and space, which creates variability between individual proliferating cells. To our knowledge, no systematic investigations of such cell-to-cell proteomic variability exist. Here we present a comprehensive, spatiotemporal map of human proteomic heterogeneity by integrating proteomics at subcellular resolution with single-cell transcriptomics and precise temporal measurements of individual cells in the cell cycle. We show that around one-fifth of the human proteome displays cell-to-cell variability, identify hundreds of proteins with previously unknown associations with mitosis and the cell cycle, and provide evidence that several of these proteins have oncogenic functions. Our results show that cell cycle progression explains less than half of all cell-to-cell variability, and that most cycling proteins are regulated post-translationally, rather than by transcriptomic cycling. These proteins are disproportionately phosphorylated by kinases that regulate cell fate, whereas non-cycling proteins that vary between cells are more likely to be modified by kinases that regulate metabolism. This spatially resolved proteomic map of the cell cycle is integrated into the Human Protein Atlas and will serve as a resource for accelerating molecular studies of the human cell cycle and cell proliferation.

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 a prognostic factor and is correlated with genovariation in pancreatic cancer based on databases analysis

Pancreatic cancer has a low survival rate globally. Anillin (ANLN) is involved in the pathogenesis of pancreatic cancer (PC). The present study used databases and reverse transcription-quantitative PCR to investigate the association between ANLN expression, clinical variables and the survival rate of patients with pancreatic cancer. Gene expression of ANLN in normal and cancer tissues was analyzed using data from The Cancer Genome Atlas, Oncomine and Gene Expression database of Normal and Tumor tissues 2 and ANOVA, and the association between ANLN mRNA expression and ANLN genovariation was analyzed using cBioPortal. The association between ANLN expression and the survival, clinical, pathological and prognostic characteristics of PC was analyzed using Kaplan-Meier (K-M) survival analysis, Kruskal Wallis and Mann Whitney-U tests, and logistic and Cox regression models. Gene Set Enrichment Analysis (GSEA) revealed the molecular pathways underpinning ANLN function in PC. Overexpression of ANLN was observed in PC cells (normal vs. tumor, P<0.01) and tissues (normal vs. tumor, P=0.008). Enhanced ANLN expression was associated with high tumor grade (grade 1 vs. grade 3, odds ratio: 5.662, P<0.001). However, ANLN expression was not associated with other clinical features (all P>0.05). K-M analysis suggested that increased ANLN expression was associated with poor survival (P=0.002). Univariate and multivariate analysis revealed the ANLN is an independent prognostic factor for PC (P<0.001). GSEA demonstrated the p53, cell cycle, DNA replication, mismatch repair, nucleotide excision repair and PC pathways were associated with low expression of ANLN. Overall, ANLN is more highly expressed in PC compared with in normal tissue, and is associated with poor differentiation. The expression of ANLN may be a novel prognostic marker of poor survival. Finally, ANLN exert its functions in PC through the p53, cell cycle, DNA replication, mismatch repair and nucleotide excision repair and pathways.

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.

Apical stress fibers enable a scaling between cell mechanical response and area in epithelial tissue

Biological systems tailor their properties and behavior to their size throughout development and in numerous aspects of physiology. However, such size scaling remains poorly understood as it applies to cell mechanics and mechanosensing. By examining how the Drosophila pupal dorsal thorax epithelium responds to morphogenetic forces, we found that the number of apical stress fibers (aSFs) anchored to adherens junctions scales with cell apical area to limit larger cell elongation under mechanical stress. aSFs cluster Hippo pathway components, thereby scaling Hippo signaling and proliferation with area. This scaling is promoted by tricellular junctions mediating an increase in aSF nucleation rate and lifetime in larger cells. Development, homeostasis, and repair entail epithelial cell size changes driven by mechanical forces; our work highlights how, in turn, mechanosensitivity scales with cell size.

ANLN Directly Interacts with RhoA to Promote Doxorubicin Resistance in Breast Cancer Cells

Background

Chemotherapy resistance is the leading cause of cancer treatment failure. This research was conducted to explore a potential link between actin-binding protein anillin (ANLN) and doxorubicin resistance in breast cancer.

Materials and Methods

We compared ANLN expression and 50% inhibition concentration (IC50) of doxorubicin in human breast cancer cells (MDA-MB-231) and human breast cancer cells with doxorubicin resistance (MDA-MB-231/ADM). Co-immunoprecipitation was used to investigate the interaction between ANLN and RhoA. The cell viability, apoptosis, gene and protein expression were estimated by MTT, flow cytometry, quantitative real-time PCR and western blot.

Results

The doxorubicin resistance in MDA-MB-231/ADM cells (IC50 = 19.40 ± 1.16 μg/mL) was significantly higher than that in MDA-MB-231 cells (IC50 = 1.65 ± 0.23 μg/mL). ANLN was up-regulated in MDA-MB-231/ADM cells compared to MDA-MB-231 cells. Furthermore, ANLN overexpression promoted cell viability and inhibited apoptosis of MDA-MB-231 cells. The gene and protein expression of multidrug resistance (MDR1) and cancer resistance protein (BCRP) were enhanced by ANLN overexpression in MDA-MB-231 cells. ANLN silencing suppressed cell viability and the expression of MDR1 and BCRP and facilitated apoptosis in MDA-MB-231/ADM cells. Moreover, ANLN promoted RhoA activation by interacting with RhoA. ANLN up-regulation enhanced cell viability and the expression of MDR1 and BCRP and decreased apoptosis of MDA-MB-231 cells. The influence conferred by ANLN overexpression was effectively abolished by C3 transferase.

Conclusion

This work revealed that ANLN promoted doxorubicin resistance in breast cancer cells by activating RhoA. Thus, our study suggests a novel target for breast cancer treatment.

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.

Proteomic analysis enables distinction of early- versus advanced-stage lung adenocarcinomas

Background

A gel‐free proteomic approach was utilized to perform in‐depth tissue protein profiling of lung adenocarcinoma (ADC) and normal lung tissues from early and advanced stages of the disease. The long‐term goal of this study is to generate a large‐scale, label‐free proteomics dataset from histologically well‐classified lung ADC that can be used to increase further our understanding of disease progression and aid in identifying novel biomarkers.

Methods and results

Cases of early‐stage (I‐II) and advanced‐stage (III‐IV) lung ADCs were selected and paired with normal lung tissues from 22 patients. The histologically and clinically stratified human primary lung ADCs were analyzed by liquid chromatography‐tandem mass spectrometry. From the analysis of ADC and normal specimens, 4863 protein groups were identified. To examine the protein expression profile of ADC, a peak area‐based quantitation method was used. In early‐ and advanced‐stage ADC, 365 and 366 proteins were differentially expressed, respectively, between normal and tumor tissues (adjusted P‐value < .01, fold change ≥ 4). A total of 155 proteins were dysregulated between early‐ and advanced‐stage ADCs and 18 were suggested as early‐specific stage ADC. In silico functional analysis of the upregulated proteins in both tumor groups revealed that most of the enriched pathways are involved in mRNA metabolism. Furthermore, the most overrepresented pathways in the proteins that were unique to ADC are related to mRNA metabolic processes.

Conclusions

Further analysis of these data may provide an insight into the molecular pathways involved in disease etiology and may lead to the identification of biomarker candidates and potential targets for therapy. Our study provides potential diagnostic biomarkers for lung ADC and novel stage‐specific drug targets for rational intervention.

Characterization of KIF20A as a prognostic biomarker and therapeutic target for different subtypes of breast cancer

The aim of the present study was to identify novel prognostic biomarkers and therapeutic targets for breast cancer; thus, genes that are frequently overexpressed in several types of breast cancer were screened. Kinesin family member 20A (KIF20A) was identified as a candidate molecule during this process. Immunohistochemical staining performed using tissue microarrays from 257 samples of different breast cancer subtypes revealed that KIF20A was expressed in 195 (75.9%) of these samples, whereas it was seldom expressed in normal breast tissue. KIF20A protein was expressed in all types of breast cancer observed. However, it was more frequently expressed in human epidermal growth factor receptor 2 (HER2)‑positive and triple‑negative breast cancer than in the luminal type. Moreover, KIF20A expression was significantly associated with the poor prognosis of patients with breast cancer. A multivariate analysis indicated that KIF20A expression was an independent prognostic factor for patients with breast cancer. The suppression of endogenous KIF20A expression using small interfering ribonucleic acids or via treatment with paprotrain, a selective inhibitor of KIF20A, significantly inhibited breast cancer cell growth through cell cycle arrest at the G2/M phase and subsequent mitotic cell death. These results suggest that KIF20A is a candidate prognostic biomarker and therapeutic target for different types of breast cancer.

CDK1-PLK1/SGOL2/ANLN pathway mediating abnormal cell division in cell cycle may be a critical process in hepatocellular carcinoma

This study aims to investigate the potential mechanisms and identify core biomarkers of Hepatocellular carcinoma (HCC). The profile GSE113850 was downloaded to analyze the differentially expressed genes. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction network analysis were used to reveal the main signal pathways of the differentially expressed genes (DEGs) and hub genes. The correlation between core gene expression and pathological stages, the disease-free survival analysis, the overall survival analysis were analyzed by Gene Expression Profiling Interactive Analysis. Furthermore, we reidentified the expression level of core genes of carcinoma tissues and para-carcinoma tissues from 14 HCC patients with real-time reverse transcription-polymerase chain reaction analysis (RT-PCR) and western blotting. After SK-Hep1 cell was treated with cyclin-dependent kinase 1 (CDK1) siRNA for 72 h, we detected the expression of the core genes and fluorescence-activated cell sorting analysis. A total of 378 DEGs were found. GO and KEGG analysis revealed that the DEGs were mainly enriched in the cell cycle. There were positive correlations among CDK1, polo-like kinase 1, shugoshin2 and anillin actin-binding protein. Moreover, the expression levels of four core genes were related to the HCC occurrence, pathological stages, and survivorship curve. The clinical HCC specimens verified the higher expression level of core genes by real-time RT-PCR. The transfection of siCDK1 in SK-Hep1 resulted in a disordered cell cycle. Furthermore, CDK1 knockdown suppressed the expression of PLK1, ANLN, and SGOL2. The CDK1-PLK1/SGOL2/ANLN pathway mediating abnormal cell division in the cell cycle might be a critical process in HCC.

Identification of a new p53 responsive element in the promoter region of anillin

The expression of anillin mRNA and protein is regulated in a cell cycle‑dependent manner. However, the mechanism underlying this process is unclear. Previous studies analyzing the sequence of the 5'‑untranslated region of anillin have unveiled several putative p53 binding sites. Therefore, the present study hypothesized that the anillin gene may be repressed by p53 and that the commonly observed mutation (or loss of function) of p53 may serve a role in this phenotype. Bioinformatic analysis of the anillin promoter region revealed potential p53 responsive elements. Of those identified, 2 were able to bind p53 protein, as determined via a chromatin immunoprecipitation assay. Although it was hypothesized that DNA damage and resultant p53 expression would repress anillin expression, the results revealed that anillin mRNA and protein expression levels were negatively regulated by DNA damage in the wild‑type p53 cells, but not in the isogenic p53 null cells. Furthermore, DNA sequences encompassing the p53 binding site downregulated luciferase transgenes in a p53 dependent manner. Taken together, these data indicated that anillin was negatively regulated by p53 and that anillin overexpression observed in cancer may be a p53‑mediated phenomenon. The data from the present study provided further evidence for the role of p53 in the biologically crucial process of cytokinesis.

Identifying Tumorigenesis and Prognosis-Related Genes of Lung Adenocarcinoma: Based on Weighted Gene Coexpression Network Analysis

Lung adenocarcinoma is the most frequently diagnosed subtype of nonsmall cell lung cancer. The molecular mechanisms of the initiation and progression of lung adenocarcinoma remain to be further determined. This study aimed to screen genes related to the progression of lung adenocarcinoma. By weighted gene coexpression network analysis (WGCNA), we constructed a free-scale gene coexpression network to evaluate the correlations between multiple gene sets and patients' clinical traits, then further identify predictive biomarkers. GSE11969 was obtained from the Gene Expression Omnibus (GEO) database which contained the gene expression data of 90 lung adenocarcinoma patients. Data of the Cancer Genome Atlas (TCGA) were employed as the validation cohort. After the average linkage hierarchical clustering, a total of 9 modules were generated. In the clinical significant module (R = 0.44, P < 0.0001), we identified 29 network hub genes. Subsequent verification in the TCGA database showed that 11 hub genes (ANLN, CDCA5, FLJ21924, LMNB1, MAD2L1, RACGAP1, RFC4, SNRPD1, TOP2A, TTK, and ZWINT) were significantly associated with poor survival data of lung adenocarcinomas. Besides, the results of receiver operating characteristic curves indicated that the mRNA levels of this group of genes exhibited high specificity and sensitivity to distinguish malignant lesions from nonmalignant tissues. Apart from mRNA levels, we found that the protein abundances of these 11 genes were remarkably upregulated in lung adenocarcinomas compared with normal tissues. In conclusion, by the WGCNA method, a panel of 11 genes were identified as predictive biomarkers for tumorigenesis and poor prognosis of lung adenocarcinomas.