Identification and validation of key genes associated with non-small-cell lung cancer

Identification of hub genes and pathways in hepatitis B virus-associated hepatocellular carcinoma: A comprehensive in silico study

Background and Aim

The hepatitis B virus (HBV) is one of the most common causes of liver cancer in the world. This study aims to provide a better understanding of the mechanisms involved in the development and progression of HBV-associated hepatocellular carcinoma (HCC) by identifying hub genes and the pathways related to their functions.

Methods

GSE83148 and GSE94660 were selected from the Gene Expression Omnibus (GEO) database, differentially expressed genes (DEGs) with an adjusted p-value < 0.05 and a |logFC| ≥1 were identified. Common DEGs of two data sets were identified using the GEO2R tool. The Kyoto Encyclopedia of Genes and Genomes (KEGG) and gene ontology (GO) databases were used to identify pathways. Protein-protein interactions (PPIs) analysis was performed by using the Cytoscap and Gephi. A Gene Expression Profiling Interactive Analysis (GEPIA) analysis was carried out to confirm the target genes.

Results

One hundred and ninety-eight common DEGs and 49 hub genes have been identified through the use of GEO and PPI, respectively. The GO and KEGG pathways analysis showed DEGs were enriched in the G1/S transition of cell cycle mitotic, cell cycle, spindle, and extracellular matrix structural constituent. The expression of four genes (TOP2A, CDK1, CCNA2, and CCNB2) with high scores in module 1 were more in tumor samples and have been identified by GEPIA analysis.

Conclusion

In this study, the hub genes and their related pathways involved in the development of HBV-associated HCC were identified. These genes, as potential diagnostic biomarkers, may provide a potent opportunity to detect HBV-associated HCC at the earliest stages, resulting in a more effective treatment.

MiR-1976/NCAPH/P65 axis inhibits the malignant phenotypes of lung adenocarcinoma

Lung adenocarcinoma (LUAD) is a malignancy with an abysmal survival rate. High metastasis is the leading cause of the low survival rate of LUAD. NCAPH, an oncogene, is involved in the carcinogenesis of LUAD. However, the regulation of NCAPH in LUAD remains controversial. In this work, we identified an up-regulation of NCAPH in LUAD tissues. Patients who expressed more NCAPH had shorter overall survival (OS). Furthermore, NCAPH overexpression promoted LUAD cell migration while inhibiting apoptosis. MiR-1976 and miR-133b were predicted to target NCAPH expression by searching TargetScan and linkedomics databases. Following that, we confirmed that miR-1976 suppressed NCAPH by directly targeting a 7-bp region of NCAPH 3' untranslated regions (UTR). In addition, increased expression of miR-1976 decreased the proliferation & migration and promoted apoptosis of LUAD cells, and the re-introduction of NCAPH reversed these influences. Furthermore, the xenograft and metastasis mouse models also confirmed that miR-1976 inhibited tumor growth and metastasis in vivo by targeting NCAPH. Finally, we found that MiR-1976 targeting NCAPH blocked the activation of NF-κB. In conclusion, miR-1976 inhibits NCAPH activity in LUAD and acts as a tumor suppressor. The miR-1976/NCAPH/NF-κB axis may, in the future, represent crucial diagnostic and prognostic biomarkers and promising therapeutic options.

Kinesin-7 CENP-E in tumorigenesis: Chromosome instability, spindle assembly checkpoint, and applications

Kinesin motors are a large family of molecular motors that walk along microtubules to fulfill many roles in intracellular transport, microtubule organization, and chromosome alignment. Kinesin-7 CENP-E (Centromere protein E) is a chromosome scaffold-associated protein that is located in the corona layer of centromeres, which participates in kinetochore-microtubule attachment, chromosome alignment, and spindle assembly checkpoint. Over the past 3 decades, CENP-E has attracted great interest as a promising new mitotic target for cancer therapy and drug development. In this review, we describe expression patterns of CENP-E in multiple tumors and highlight the functions of CENP-E in cancer cell proliferation. We summarize recent advances in structural domains, roles, and functions of CENP-E in cell division. Notably, we describe the dual functions of CENP-E in inhibiting and promoting tumorigenesis. We summarize the mechanisms by which CENP-E affects tumorigenesis through chromosome instability and spindle assembly checkpoints. Finally, we overview and summarize the CENP-E-specific inhibitors, mechanisms of drug resistances and their applications.

NCAPH drives breast cancer progression and identifies a gene signature that predicts luminal a tumour recurrence

BACKGROUND

Luminal A tumours generally have a favourable prognosis but possess the highest 10-year recurrence risk among breast cancers. Additionally, a quarter of the recurrence cases occur within 5 years post-diagnosis. Identifying such patients is crucial as long-term relapsers could benefit from extended hormone therapy, while early relapsers might require more aggressive treatment.

METHODS

We conducted a study to explore non-structural chromosome maintenance condensin I complex subunit H's (NCAPH) role in luminal A breast cancer pathogenesis, both in vitro and in vivo, aiming to identify an intratumoural gene expression signature, with a focus on elevated NCAPH levels, as a potential marker for unfavourable progression. Our analysis included transgenic mouse models overexpressing NCAPH and a genetically diverse mouse cohort generated by backcrossing. A least absolute shrinkage and selection operator (LASSO) multivariate regression analysis was performed on transcripts associated with elevated intratumoural NCAPH levels.

RESULTS

We found that NCAPH contributes to adverse luminal A breast cancer progression. The intratumoural gene expression signature associated with elevated NCAPH levels emerged as a potential risk identifier. Transgenic mice overexpressing NCAPH developed breast tumours with extended latency, and in Mouse Mammary Tumor Virus (MMTV)-NCAPHErbB2 double-transgenic mice, luminal tumours showed increased aggressiveness. High intratumoural Ncaph levels correlated with worse breast cancer outcome and subpar chemotherapy response. A 10-gene risk score, termed Gene Signature for Luminal A 10 (GSLA10), was derived from the LASSO analysis, correlating with adverse luminal A breast cancer progression.

CONCLUSIONS

The GSLA10 signature outperformed the Oncotype DX signature in discerning tumours with unfavourable outcomes, previously categorised as luminal A by Prediction Analysis of Microarray 50 (PAM50) across three independent human cohorts. This new signature holds promise for identifying luminal A tumour patients with adverse prognosis, aiding in the development of personalised treatment strategies to significantly improve patient outcomes.

Integrated multi-omics analysis for lung adenocarcinoma in Xuanwei, China

BACKGROUND

Xuanwei lung cancer (XWLC) is well-known for its high incidence and mortality. However, the molecular mechanism is still unclear.

METHODS

We performed a comprehensive transcriptomic, proteomic, and phosphoproteomic characterization of tumors and matched normal adjacent tissues from three XWLC patients with lung adenocarcinoma (LUAD).

RESULTS

Integrated transcriptome and proteome analysis revealed dysregulated molecules and pathways in tumors and identified enhanced metabolic-disease coupling. Non-coding RNAs were widely involved in post-transcriptional regulatory mechanisms to coordinate the progress of LUAD and partially explained the molecular differences between RNA and protein expression patterns. Phosphoproteome provided evidence support for new phosphate sites, reporting the potential roles of core kinase family members and key kinase pathways involved in metabolism, immunity, and homeostasis. In addition, by comparing with the previous LUAD researches, we emphasized the higher degree of oxidative phosphorylation in Xuanwei LUAD and pointed that VIPR1 deficiency aggravated metabolic dysfunction.

CONCLUSION

Our integrated multi-omics analysis provided a powerful resource for a systematic understanding of the molecular structure of XWLC and proposed therapeutic opportunities based on redox metabolism.

Prognostic and immune correlation analysis of mitochondrial autophagy and aging-related genes in lung adenocarcinoma

PURPOSE

Mitophagy and aging (MiAg) are very important pathophysiological mechanisms contributing to tumorigenesis. MiAg-related genes have prognostic value in lung adenocarcinoma (LUAD). However, prognostic, and immune correlation studies of MiAg-related genes in LUAD are lacking.

METHODS

MiAg differentially expressed genes (DEGs) in LUAD were obtained from public sequencing datasets. A prognostic model including MiAg DEGs was constructed according to patients divided into low- and high-risk groups. Gene Ontology, gene set enrichment analysis, gene set variation analysis, CIBERSORT immune infiltration analysis, and clinical characteristic correlation analyses were performed for functional annotation and correlation of MiAgs with prognosis in patients with LUAD.

RESULTS

Seven MiAg DEGs of LUAD were identified: CAV1, DSG2, DSP, MYH11, NME1, PAICS, PLOD2, and the expression levels of these genes were significantly correlated (P < 0.05). The RiskScore of the MiAg DEG prognostic model demonstrated high predictive ability of overall survival of patients diagnosed with LUAD. Patients with high and low MiAg phenotypic scores exhibited significant differences in the infiltration levels of eight types of immune cells (P < 0.05). The multi-factor DEG regression model showed higher efficacy in predicting 5-year survival than 3- and 1-year survival of patients with LUAD.

CONCLUSIONS

Seven MiAg-related genes were identified to be significantly associated with the prognosis of patients diagnosed with LUAD. Moreover, the identified MiAg DEGs might affect the immunotherapy strategy of patients with LUAD.

FGFR3 and FGFR4 overexpression in juvenile nasopharyngeal angiofibroma: impact of smoking history and implications for personalized management

Lifestyle factors, including smoking, have been linked to neoplastic diseases, and reports suggest an association between smoking and overexpression of FGFR (fibroblast growth factor receptor) in certain neoplasms. This study aims to assess the expression of FGFR3 and FGFR4 genes in patients with and without a history of smoking.A total of 118 participants were recruited, including 83 Juvenile Nasopharyngeal Angiofibroma (JNA) patients and 35 healthy participants, the JNA patients were further stratified as smokers and nonsmokers. Total RNA was extracted from the blood & saliva sample by using TRIzol reagent, and quantified using a Nanodrop, and then subjected to gene expression analysis of FGFR3/4 using RT-PCR. Immunohistochemistry analysis was employed using fresh biopsies of JNA to validate the findings. All experiments were performed in triplicates and analysed using the Chi-Square test (P < 0.05). Smokers exhibited significantly lower total RNA concentrations across all sample types (P < 0.001). The study revealed significant upregulation of both FGFR3/4 genes in JNA patients (P < 0.05). Moreover, FGFR3 expression was significantly higher among smokers 66% (95% CI: 53-79%) compared to non-smokers 22% (95% CI: 18-26%). Immunohistochemistry analysis demonstrated moderate to strong staining intensity for FGFR3 among smokers. The study highlights the overexpression of FGFR3/4 genes in JNA patients, with a stronger association observed among smokers. Furthermore, medical reports indicated higher rates of recurrence and bleeding intensity among smokers. These findings emphasize the potential role of FGFR3 as a key molecular factor in JNA, particularly in the context of smoking.

An integrative analysis of GEO data to identify possible therapeutic biomarkers of prostate cancer and targeting potential protein through Zea mays phytochemicals by virtual screening approaches

Prostate cancer (PC) is a prevalent type of cancer among men. Delaying the treatment of patients with upgraded or upstaged cancer may lead to unmanageable circumstances. The aim of this study is to contribute to the finding of biomarkers that are specific to PC and identify drug candidates derived from plants. The information about cancer is critical for clinicians to make decisions about patient treatment in the era of precision medicine. Advances in genomics technology have opened up new possibilities for identifying genes that are associated with cancer, including PC. This study identifies novel differentially expressed genes for PC. The seven PC microarray datasets were selected from the National Center for Biotechnology Information (NCBI)/Gene Expression Omnibus (GEO). The differentially expressed genes (DEGs) were found based on a fold change of |logFC| ≥ 1 and an adjusted p-value of <0.05. The DEGs were further studied using several bioinformatics tools, including STRING, CytoHubba, SRplot, Coremine Medical database, FunRich and GeneMANIA, cBioPortal. The six new potential biomarkers, GAGE2A, GAGE12G, GAGE2E, GAGE13, GAGE12F and CSAG1 were identified. These biomarkers are associated with biological processes (BPs) such as cell division, and gene expression regulation, so these genes may have a crucial role in PC progression and may serve as potential biomarkers for PC. A total of 497 phytochemicals from corn plants have been screened against the target protein and found LTS0176591 as the best lead molecule with docking score of -6.31 kcal/mol. Further, molecular mechanics-generalized born surface area (MM-GBSA), molecular dynamics simulation, principal component analysis (PCA), free energy landscape (FEL) and molecular mechanics-Poisson-Boltzmann surface area (MM-PBSA) were carried out to validate the findings.Communicated by Ramaswamy H. Sarma.

Cyclin-Dependent Kinase Inhibitor 2A is a Key Regulator of Cell Cycle Arrest and Senescence in Endothelial Colony-Forming Cells in Moyamoya Disease

OBJECTIVE

Endothelial colony-forming cells (ECFCs) have been reported to play an important role in the pathogenesis of moyamoya disease (MMD). We have previously observed stagnant growth in MMD ECFCs with functional impairment of tubule formation. We aimed to verify the key regulators and related signaling pathways involved in the functional defects of MMD ECFCs.

METHODS

ECFCs were cultured from peripheral blood mononuclear cells of healthy volunteers (normal) and MMD patients. Low-density lipoproteins uptake, flow cytometry, high content screening, senescence-associated β-galactosidase, immunofluorescence, cell cycle, tubule formation, microarray, real-time quantitative polymerase chain reaction, small interfering RNA transfection, and western blot analyses were performed.

RESULTS

The acquisition of cells that can be cultured for a long time with the characteristics of late ECFCs was significantly lower in the MMD patients than the normal. Importantly, the MMD ECFCs showed decreased cellular proliferation with G1 cell cycle arrest and cellular senescence compared to the normal ECFCs. A pathway enrichment analysis demonstrated that the cell cycle pathway was the major enriched pathway, which is consistent with the results of the functional analysis of ECFCs. Among the genes associated with the cell cycle, cyclin-dependent kinase inhibitor 2A (CDKN2A) showed the highest expression in MMD ECFCs. Knockdown of CDKN2A in MMD ECFCs enhanced proliferation by reducing G1 cell cycle arrest and inhibiting senescence through the regulation of CDK4 and phospho retinoblastoma protein.

CONCLUSION

Our study suggests that CDKN2A plays an important role in the growth retardation of MMD ECFCs by inducing cell cycle arrest and senescence.

NCAPH Drives Breast Cancer Progression and Identifies a Gene Signature that Predicts Luminal A Tumor Recurrence

Despite their generally favorable prognosis, luminal A tumors paradoxically pose the highest ten-year recurrence risk among breast cancers. From those that relapse, a quarter of them do it within five years after diagnosis. Identifying such patients is crucial, as long-term relapsers could benefit from extended hormone therapy, whereas early relapsers may require aggressive treatment. In this study, we demonstrate that NCAPH plays a role in the pathogenesis of luminal A breast cancer, contributing to its adverse progression in vitro and in vivo. Furthermore, we reveal that a signature of intratumoral gene expression, associated with elevated levels of NCAPH, serves as a potential marker to identify patients facing unfavorable progression of luminal A breast cancer. Indeed, transgenic mice overexpressing NCAPH generated breast tumors with long latency, and in MMTV-NCAPH/ErbB2+ double-transgenic mice, the luminal tumors formed were more aggressive. In addition, high intratumoral levels of Ncaph were associated with worse breast cancer evolution and poor response to chemotherapy in a cohort of genetically heterogeneous transgenic mice generated by backcrossing. In this cohort of mice, we identified a series of transcripts associated with elevated intratumoral levels of NCAPH, which were linked to adverse progression of breast cancer in both mice and humans. Utilizing the Least Absolute Shrinkage and Selection Operator (LASSO) multivariate regression analysis on this series of transcripts, we derived a ten-gene risk score. This score is defined by a gene signature (termed Gene Signature for Luminal A 10 or GSLA10) that correlates with unfavorable progression of luminal A breast cancer. The GSLA10 signature surpassed the Oncotype DX signature in discerning tumors with unfavorable outcomes (previously categorized as Luminal A by PAM50) across three independent human cohorts. This GSLA10 signature aids in identifying patients with Luminal A tumors displaying adverse prognosis, who could potentially benefit from personalized treatment strategies.

BIRC5 Inhibition Is Associated with Pyroptotic Cell Death via Caspase3-GSDME Pathway in Lung Adenocarcinoma Cells

Lung adenocarcinoma (LUAD) is a prevalent type of thoracic cancer with a poor prognosis and high mortality rate. However, the exact pathogenesis of this cancer is still not fully understood. One potential factor that can contribute to the development of lung adenocarcinoma is DNA methylation, which can cause changes in chromosome structure and potentially lead to the formation of tumors. The baculoviral IAP repeat containing the 5 (BIRC5) gene encodes the Survivin protein, which is a multifunctional gene involved in cell proliferation, migration, and invasion of tumor cells. This gene is elevated in various solid tumors, but its specific role and mechanism in lung adenocarcinoma are not well-known. To identify the potential biomarkers associated with lung adenocarcinoma, we screened the methylation-regulated differentially expressed genes (MeDEGs) of LUAD via bioinformatics analysis. Gene ontology (GO) process and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were applied to investigate the biological function and pathway of MeDEGs. A protein-protein interaction (PPI) network was employed to explore the key module and screen hub genes. We screened out eight hub genes whose products are aberrantly expressed, and whose DNA methylation modification level is significantly changed in lung adenocarcinoma. BIRC5 is a bona fide marker which was remarkably up-regulated in tumor tissues. Flow cytometry analysis, lactate dehydrogenase release (LDH) assay and Micro-PET imaging were performed in A549 cells and a mouse xenograft tumor to explore the function of BIRC5 in cell death of lung adenocarcinoma. We found that BIRC5 was up-regulated and related to a high mortality rate in lung adenocarcinoma patients. Mechanically, the knockdown of BIRC5 inhibited the proliferation of A549 cells and induced pyroptosis via caspase3/GSDME signaling. Our findings have unraveled that BIRC5 holds promise as a novel biomarker and therapeutic target for lung adenocarcinoma. Additionally, we have discovered a novel pathway in which BIRC5 inhibition can induce pyroptosis through the caspase3-GSDME pathway in lung adenocarcinoma cells.

The potential bioactive ingredients and hub genes of five TCM prescriptions against lung adenocarcinoma were explored based on bioinformatics

Analysis of the commonness of several prescriptions of traditional Chinese medicine (TCM) in the treatment of lung adenocarcinoma (LUAD) based on bioinformatics. Searched the TCM prescriptions for the treatment of LUAD in the literature published in the database, searched ingredients in the TCM through TCMSP and Swiss target prediction databases (OB ≥ 30%, DL > 0.18, Caco-2 > 0), and predicted the potential targets. GEO database retrieved LUAD gene chip data and screened (P < 0.05, | log2 (fold change) |> 1). The biological function, hub gene selection and survival period, immune infiltration, methylation, copy number variations (CNVs), and single-nucleotide variants (SNV) of hub genes were analyzed by DAVID, STRING, Kaplan-Meier plotter database, Cytoscape software, GSCALite database, and TIMER2.0. In this study, 5 TCM prescriptions were analyzed, and a total of 173 ingredients were obtained through database search, including 35 coincidence ingredients, a total of 603 potential targets, 621 LUAD-related genes, 16 up-regulated genes, and 31 down-regulated genes. A total of 61 terms of biological process (BP), 14 terms of cellular component (CC), and 14 terms of molecular function (MF) were obtained. Twenty core genes were obtained, including 15 genes with different survival periods, which were closely related to immune cells (B cell, CD8 + T cell, CD4 + T cell, macrophage, neutrophil, and dendritic cells). The low expression of ADRB2 and MAOA and the high expression of AUARK, CDK1, KIF11, MIF, TOP2A, and TTK were associated with the survival rate of LUAD patients (P < 0.05). Baicalein, Arachidonate, Hederagenin, and hub genes may become potential drugs and potential targets for LUAD treatment. Evaluated the efficacy of TCM in the treatment of LUAD from macro to micro, mined the hub genes, and predicted the mechanism of action, so as to lay the foundation for the development of new drugs of TCM, prescription optimization, or disease control.

Identification of hub genes and pathways in lung metastatic colorectal cancer

BACKGROUND

Colorectal cancer (CRC) is one of the most prevalent types of malignant tumours. Metastasis is the leading cause of cancer-related mortality, with lung metastases accounting for 32.9% of all metastatic CRCs. However, since the biological mechanism of lung metastatic CRC is poorly understood, limited therapeutic targets are available. In the present study, we aimed to identify the key genes and molecular processes involved in CRC lung metastasis.

METHODS

The differentially expressed genes (DEGs) between primary and lung metastatic CRC patients were obtained from the Gene Expression Omnibus (GEO) database via the GEO2R tool. The enriched biological processes and pathways modulated by the DEGs were determined with Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome Gene Sets analyses. The search tool Retrieval of Interacting Genes (STRING) and Cytoscape were used to construct a protein-protein interaction (PPI) network among DEGs.

RESULTS

The DEGs were enriched in surfactant metabolism, cell-cell communication and chemokine signaling pathways. The defined hub genes were included CLU, SFTPD, CCL18, SPP1, APOE, BGN and MMP3. Among them, CLU, SFTPD and CCL18 might be associated with the specific lung tropism metastasis in CRC. In addition, the expression and prognostic values of the hub genes in CRC patients were verified in database of The Cancer Genome Atlas (TCGA) and GEO. Moreover, the protein levels of the hub genes were detected in primary and lung metastatic CRC cells, serum or tissues. Furthermore, SFTPD was confirmed to facilitate cellular proliferation and lung metastasis in CRC.

CONCLUSION

This bioinformatics study may provide a better understanding of the candidate therapeutic targets and molecular mechanisms for CRC lung metastasis.

Comprehensive pan-cancer analysis identifies centromere associated protein E as a novel prognostic and immunological biomarker in human tumors

Centromere-associated protein E (CENP-E), a core component of the kinetochore, mediates chromosome congression and spindle microtubule capture during mitosis. Partial experimental evidence has illustrated the carcinogenic effects of CENPE in tumors, but the corresponding pan-cancer analysis of CENPE still lacking. Based on public databases, including the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), and Human Protein Atlas (HPA), we take an array of bioinformatics methods to investigate the potential oncogenic roles of CENPE. Then, we validated CENPE, cell cycle-related proteins, and immune checkpoint molecule findings expression in clinical colon cancer samples by western blot. Our results showed that CENPE was up-regulated in almost all tumors, and the expression level of CENPE was associated with worse overall survival (OS) and disease-specific survival (DSS) in patients. The strong relationship between CENPE with gene mutation and MMR has also been validated. Moreover, CENPE gene expression was positively correlated with immune checkpoint molecular, and reversely correlated with infiltration levels of most immune cells. In the human colon cancer tissues, the expression of CENPE, cell cycle-related proteins, and immune checkpoint molecules were significantly higher than in the adjacent normal tissues. Our results indicated that CENPE can function as an oncogene in various cancers, and may be regarded as a promising prognostic and diagnostic biomarker in cancer treatment.

Identification of IRAK1BP1 as a candidate prognostic factor in lung adenocarcinoma

Introduction

Lung cancer is one of the major causes of cancer-related mortality worldwide. High-throughput RNA sequencing (RNA-seq) of surgically removed tumors has been used to identify new biomarkers of lung cancer; however, contamination by non-tumor cells in the tumor microenvironment significantly interferes with the search for novel biomarkers. Tumor organoids, as a pre-clinical cancer model, exhibit similar molecular characteristics with tumor samples while minimizing the interference from other cells.

Methods and Results

Here we analyzed six RNA-seq datasets collected from different organoid models, in which cells with oncogenic mutations were reprogrammed to mimic lung adenocarcinoma (LUAD) tumorigenesis. We uncovered 9 LUAD-specific biomarker genes by integrating transcriptomic data from multiple sources, and identified IRAK1BP1 as a novel predictor of LUAD disease outcome. Validation with RNA-seq and microarray data collected from multiple patient cohorts, as well as patient-derived xenograft (PDX) and lung cancer cell line models confirmed that IRAK1BP1 expression was significantly lower in tumor cells, and had no correlation with known markers oflung cancer prognosis. In addition, loss of IRAK1BP1 correlated with the group of LUAD patients with worse survival; and gene-set enrichment analysis using tumor and cell line data implicated that high IRAK1BP1 expression was associated with suppression of oncogenic pathways.

Discussion

In conclusion, we demonstrate that IRAK1BP1 is a promising biomarker of LUAD prognosis.

Recent Developments and Challenges in Molecular-Targeted Therapy of Non-Small-Cell Lung Cancer

Treatment of lung cancer with conventional therapies, which include radiation, surgery, and chemotherapy results in multiple undesirable adverse or side effects. The major clinical challenge in developing new drug therapies for lung cancer is resistance, which involves mutations and disturbance in various signaling pathways. Molecular abnormalities related to epidermal growth factor receptor (EGFR), v-Raf murine sarcoma viral oncogene homolog B1 (B-RAF) Kirsten rat sarcoma virus (KRAS) mutations, translocation of the anaplastic lymphoma kinase (ALK) gene, mesenchymal-epithelial transition factor (MET) amplification have been studied to overcome the resistance and to develop new therapies for non-small cell lung cancer (NSCLC). But, inevitable development of resistance presents limits the clinical benefits of various new drugs. Here, we review current progress in the development of molecularly targeted therapies, concerning six clinical biomarkers: EGFR, ALK, MET, ROS-1, KRAS, and B-RAF for NSCLC treatment.

Evaluating the Expression and Prognostic Value of Genes Encoding Microtubule-Associated Proteins in Lung Cancer

Microtubule-associated proteins (MAPs) play essential roles in cancer development. This study aimed to identify transcriptomic biomarkers among MAP genes for the diagnosis and prognosis of lung cancer by analyzing differential gene expressions and correlations with tumor progression. Gene expression data of patients with lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC) from the Cancer Genome Atlas (TCGA) database were used to identify differentially expressed MAP genes (DEMGs). Their prognostic value was evaluated by Kaplan-Meier and Cox regression analysis. Moreover, the relationships between alterations in lung cancer hallmark genes and the expression levels of DEMGs were investigated. The candidate biomarker genes were validated using three independent datasets from the Gene Expression Omnibus (GEO) database and by quantitative reverse transcription polymerase chain reaction (qRT-PCR) on clinical samples. A total of 88 DEMGs were identified from TCGA data. The 20 that showed the highest differential expression were subjected to association analysis with hallmark genes. Genetic alterations in TP53, EGFR, PTEN, NTRK1, and PIK3CA correlated with the expression of most of these DEMGs. Of these, six candidates-NUF2, KIF4A, KIF18B, DLGAP5, NEK2, and LRRK2-were significantly differentially expressed and correlated with the overall survival (OS) of the patients. The mRNA expression profiles of these candidates were consistently verified using three GEO datasets and qRT-PCR on patient lung tissues. The expression levels of NUF2, KIF4A, KIF18B, DLGAP5, NEK2, and LRRK2 can serve as diagnostic biomarkers for LUAD and LUSC. Moreover, the first five can serve as prognostic biomarkers for LUAD, while LRRK2 can be a prognostic biomarker for LUSC. Our research describes the novel role and potential application of MAP-encoding genes in clinical practice.

Integration of TE Induces Cancer Specific Alternative Splicing Events

Alternative splicing of messenger RNA (mRNA) precursors contributes to genetic diversity by generating structurally and functionally distinct transcripts. In a disease state, alternative splicing promotes incidence and development of several cancer types through regulation of cancer-related biological processes. Transposable elements (TEs), having the genetic ability to jump to other regions of the genome, can bring about alternative splicing events in cancer. TEs can integrate into the genome, mostly in the intronic regions, and induce cancer-specific alternative splicing by adjusting various mechanisms, such as exonization, providing splicing donor/acceptor sites, alternative regulatory sequences or stop codons, and driving exon disruption or epigenetic regulation. Moreover, TEs can produce microRNAs (miRNAs) that control the proportion of transcripts by repressing translation or stimulating the degradation of transcripts at the post-transcriptional level. Notably, TE insertion creates a cancer-friendly environment by controlling the overall process of gene expression before and after transcription in cancer cells. This review emphasizes the correlative interaction between alternative splicing by TE integration and cancer-associated biological processes, suggesting a macroscopic mechanism controlling alternative splicing by TE insertion in cancer.

Identification of autophagy-related biomarkers in patients with pulmonary arterial hypertension based on bioinformatics analysis

Autophagy participates in the regulation of pulmonary arterial hypertension (PAH). However, the role of autophagy-related genes (ARGs) in the pathogenesis of the PAH is still unclear. This study aimed to identify the ARGs in PAH via bioinformatics analysis. A microarray dataset (GSE113439) was downloaded from the Gene Expression Omnibus database to identify differentially expressed ARGs (DEARGs). Protein–protein interactions network, gene ontology, and Kyoto Encyclopedia of Genes and Genomes enrichment analyses were performed to screen hub genes and the underlying molecular mechanisms of PAH. Finally, the mRNA expression of the hub genes was validated using the GSE53408 dataset. Twenty-six DEARGs were identified, all of which were upregulated. Enrichment analyses revealed that these DEARGs were mainly enriched in the nucleotide-binding oligomerization domain (NOD)-like receptor signaling pathway, PI3K-Akt signaling pathway, response to hypoxia, response to nutrient levels, and autophagy. Among these hub genes, the mRNA expression levels of HSP90AA1, HIF1A, MET, IGF1, LRRK2, CLTC, DNM1L, MDM2, RICTOR, and ROCK2 were significantly upregulated in PAH patients than in healthy individuals. Ten hub DEARGs were identified and may participate in the pathogenesis of the PAH via the regulation of autophagy. The present study may provide novel therapeutic targets for PAH prevention and treatment and expand our understanding of PAH.

Multi-omics data integration for subtype identification of Chinese lower-grade gliomas: a joint similarity network fusion approach

Lower-grade gliomas (LGG), characterized by heterogeneity and invasiveness, originate from the central nervous system. Although studies focusing on molecular subtyping and molecular characteristics have provided novel insights into improving the diagnosis and therapy of LGG, there is an urgent need to identify new molecular subtypes and biomarkers that are promising to improve patient survival outcomes. Here, we proposed a joint similarity network fusion (Joint-SNF) method to integrate different omics data types to construct a fused network using the Joint and Individual Variation Explained (JIVE) technique under the SNF framework. Focusing on the joint network structure, a spectral clustering method was employed to obtain subtypes of patients. Simulation studies show that the proposed Joint-SNF method outperforms the original SNF approach under various simulation scenarios. We further applied the method to a Chinese LGG data set including mRNA expression, DNA methylation and microRNA (miRNA). Three molecular subtypes were identified and showed statistically significant differences in patient survival outcomes. The five-year mortality rates of the three subtypes are 80.8%, 32.1%, and 34.4%, respectively. After adjusting for clinically relevant covariates, the death risk of patients in Cluster 1 was 5.06 times higher than patients in other clusters. The fused network attained by the proposed Joint-SNF method enhances strong similarities, thus greatly improves subtyping performance compared to the original SNF method. The findings in the real application may provide important clues for improving patient survival outcomes and for precision treatment for Chinese LGG patients. An R package to implement the method can be accessed in Github at https://github.com/Sameerer/Joint-SNF.

The Role of CEP55 Expression in Tumor Immune Response and Prognosis of Patients with Non-small Cell lung Cancer

Background: With the continuous advancement of diagnostic methods, more and more early-stage Non-small cell lung cancer (NSCLC) patients are diagnosed. Although many scholars have devoted substantial efforts to investigate the pathogenesis and prognosis of NSCLC, its molecular mechanism is still not well explained. Methods: We retrieved three gene datasets GSE10072, GSE19188 and GSE40791 from the Gene Expression Omnibus (GEO) database and screened and identified differentially expressed genes (DEGs). Then, we performed KEGG and GO functional enrichment analysis, survival analysis, risk analysis and prognosis analysis on the selected hub genes. We constructed a protein-protein interaction (PPI) network, and used the STRING database and Cytoscape software. Results: The biological process analysis showed that these genes were mainly enriched in cell division and nuclear division. Survival analysis showed that the genes of CEP55 (centrosomal protein 55), NMU (neuromedin U), CAV1 (Caveolin 1), TBX3 (T-box transcription factor 3), FBLN1 (fibulin 1) and SYNM (synemin) may be involved in the development, invasion or metastasis of NSCLC (P<0.05, logFC>1). Prognostic analysis and independent prognostic analysis showed that the expression of these hub gene-related mRNAs was related to the prognostic risk of NSCLC. Risk analysis showed that the selected hub genes were closely related to the overall survival time of patients with NSCLC. Conclusion: The DEGs and hub genes screened and identified in this study will help us to understand the molecular mechanisms of NSCLC, and CEP55 expression affects the survival and prognosis of patients with NSCLC, and participates in tumor immune response.

NCAPH is a prognostic biomarker and associated with immune infiltrates in lung adenocarcinoma

Non-SMC condensin I complex subunit H (NCAPH) plays a regulatory role in various cancers. However, its role in prognosis and immune infiltrates in lung adenocarcinoma (LUAD) remains unclear. This study examined the expression of NCAPH in tumor tissues and its association with immune infiltrates and prognostic roles in LUAD patients. Patients characteristics were obtained from The Cancer Genome Atlas (TCGA). Integrated analysis of TCGA showed that NCAPH was overexpressed across cancers, including LUAD. NCAPH expression was verified by quantitative polymerase chain reaction and western blotting in 20 LUAD matched tissues. High NCAPH expression was significantly related to T, N, M, pathologic stage, primary therapy outcome and smoking status according to the Wilcoxon rank sum test. Cox and Kaplan-Meier analyses showed that the NCAPH-high group was associated with shorter OS. The PFI and DSS in the NCAPH-high group were significantly decreased. Multivariate analysis showed that NCAPH was an independent predictive factor for poor prognosis. Gene set enrichment analysis demonstrated that the G2/M checkpoint, ncRNA metabolic, memory B cells, KRAS, E2F targets and MIER1 process were significantly associated with NCAPH expression. Single-sample Gene Set Enrichment Analysis indicated that NCAPH expression was associated with levels of Th2 and mast cells. The impact of NCAPH on malignant phenotypes was evaluated by MTT, transwell, cell cycle and apoptosis assays in vitro. The malignant phenotype of LUAD cells was inhibited if NCAPH was knocked down. In conclusion, this research indicates that NCAPH could be a potential factor for predicting prognosis and a new biomarker in LUAD.

Transposons: Unexpected players in cancer

Transposons are repetitive DNA sequences encompassing about half of the human genome. They play a vital role in genome stability maintenance and contribute to genomic diversity and evolution. Their activity is regulated by various mechanisms considering the deleterious effects of these mobile elements. Various genetic risk factors and environmental stress conditions affect the regulatory pathways causing alteration of transposon expression. Our knowledge of the biological role of transposons is limited especially in various types of cancers. Retrotransposons of different types (LTR-retrotransposons, LINEs and SINEs) regulate a plethora of genes that have a role in cell reprogramming, tumor suppression, cell cycle, apoptosis, cell adhesion and migration, and DNA repair. The regulatory mechanisms of transposons, their deregulation and different mechanisms underlying transposon-mediated carcinogenesis in humans focusing on the three most prevalent types, lung, breast and colorectal cancers, were reviewed. The modes of regulation employed include alternative splicing, deletion, insertion, duplication in genes and promoters resulting in upregulation, downregulation or silencing of genes.

Hydroxysteroid 17-Beta Dehydrogenase 6 Is a Prognostic Biomarker and Correlates with Immune Infiltrates in Hepatocellular Carcinoma

BACKGROUND

Hepatocellular carcinoma (HCC) is a common malignancy worldwide with poor outcomes. Therefore, it is important to identify a valuable prognostic biomarker for HCC. The present study aimed to identify novel prognostic biomarkers for HCC and evaluate the potential role of hub genes in HCC.

METHODS

Weighted gene co-expression network analysis and protein-protein interaction analysis were performed to identify important potential prognostic genes. The expression of hub genes was confirmed by the GEPIA, Oncomine, UALCAN, and HPA database. Furthermore, survival analysis of hub genes was performed using the Kaplan-Meier plotter database. Finally, we investigated the association between hub genes and immune factors in HCC through GSEA, the TIMER, and TISIDB database.

RESULTS

HSD17B6 expression was significantly lower in HCC than in normal tissues. Low HSD17B6 expression is associated with poorer overall survival and progression-free survival in HCC patients, particularly at medium disease stages (stage II and III or grade III). HSD17B6 showed a strong correlation with tumor-infiltrating B cells, CD4 + and CD8 + T cells, macrophages, neutrophils, and dendritic cells. Somatic copy number alteration might be the main cause of the negative correlation between HSD17B6 expression and immune infiltration. HSD17B6 expression in HCC negatively correlated with the expression of several immune cell markers, including exhausted T cell markers, PD-1 and CTLA-4, suggesting its role in regulating tumor immunity.

CONCLUSIONS

HSD17B6 is a potential prognostic biomarker that determines cancer progression and is correlated with tumor immune cells infiltration in HCC.

Clinical Value and Potential Mechanism of miRNA-33a-5p in Lung Squamous Cell Carcinoma

This study is aimed at thoroughly exploring the expression status, clinical significance, and underlying molecular mechanism of miRNA-33a-5p in lung squamous cell carcinoma (LUSC). Here, we detected miRNA-33a-5p in 20 samples from patients with LUSCs and 20 matching non-LUSC specimens by in-house quantitative real-time PCR (RT-qPCR). Relationship between miRNA-33a-5p expression and clinicopathological traits was investigated from materials derived from miRNA sequencing and miRNA microarrays. A pool standard mean difference (SMD) and summary receiver operating characteristic curves (SROC) were calculated to evaluate the integrated expression value of miRNA-33a-5p in LUSC. Twelve online platforms were applied to select potential target genes of miRNA-33a-5p. The differentially expressed genes (DEGs) of LUSC and the candidate target genes of miRNA-33a-5p were overlapped to acquire a set of specific genes for further analyses of the Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and protein–protein interaction (PPI) network. miRNA-33a-5p overexpressed in LUSC was supported by 706 LUSC and 261 non-LUSC samples gathering from RT-qPCR, miRNA-seq, and public miRNA microarrays. The pooled SMD was 0.56 (95% CI: -0.01-1.05), and the area under the curve (AUC) of the SROC was 0.78 (95% CI: 0.74-0.82). A total of 240 genes were identified as potential target genes of miRNA-33a-5p for functional enrichment analyses; the results suggested that these target genes may participate in several vital biological processes that promote the proliferation and progression of LUSC. miRNA-33a-5p may play an essential role in the occurrence and development of LUSC by targeting hub genes (ETS1, EDNRB, CYR61, and LRRK2) derived from the PPI network. In summary, our results indicated that miRNA-33a-5p may contribute as a prospective therapeutic target in LUSC.

Long non-coding RNA MIR31HG as a prognostic predictor for malignant cancers: A meta- and bioinformatics analysis

Background

The possible regulatory mechanism of MIR31HG in human cancers remains unclear, and reported results of the prognostic significance of MIR31HG expression are inconsistent.

Methods

The meta‐analysis and related bioinformatics analysis were conducted to evaluate the role of MIR31HG in tumor progression.

Results

The result showed that high MIR31HG expression was not related to prognosis. However, in the stratified analysis, we found that the overexpression of MIR31HG resulted in worse OS, advanced TNM stage, and tumor differentiation in respiratory system cancers. Moreover, our results also found that MIR31HG overexpression was related to shorter OS in cervical cancer patients and head and neck tumors. In contrast, the MIR31HG was lower in digestive system tumors which contributed to shorter overall survival, advanced TNM stage, and distant metastasis. Furthermore, the bioinformatics analysis showed that MIR31HG was highly expressed in normal urinary bladder, small intestine, esophagus, stomach, and duodenum and low in colon, lung, and ovary. The results obtained from FireBrowse indicated that MIR31HG was highly expressed in LUSC, CESC, HNSC, and LUAD and low in STAD and BLCA. Gene Ontology analysis showed that the co‐expressed genes of MIR31HG were most enriched in the biological processes of peptide metabolism and KEGG pathways were most enriched in Ras, Rap1, and PI3K‐Akt signaling pathway.

Conclusion

MIR31HG may serve as a potential biomarker in human cancers.

HSD17B6 downregulation predicts poor prognosis and drives tumor progression via activating Akt signaling pathway in lung adenocarcinoma

Lung adenocarcinoma is one of the most frequent tumor subtypes, involving changes in a variety of oncogenes and tumor suppressor genes. Hydroxysteroid 17-Beta Dehydrogenase 6 (HSD17B6) could synthetize dihydrotestosterone, abnormal levels of which are associated with progression of multiple tumors. Previously, we showed that HSD17B6 inhibits malignant progression of hepatocellular carcinoma. However, the mechanisms underlying inhibiting tumor development by HSD17B6 are not clear. Moreover, its role in lung adenocarcinoma (LUAD) is yet unknown. Here, we investigated its expression profile and biological functions in LUAD. Analysis of data from the LUAD datasets of TCGA, CPTAC, Oncomine, and GEO revealed that HSD17B6 mRNA and protein expression was frequently lower in LUAD than in non-neoplastic lung tissues, and its low expression correlated significantly with advanced tumor stage, large tumor size, poor tumor differentiation, high tumor grade, smoking, and poor prognosis in LUAD. In addition, its expression was negatively regulated by miR-31-5p in LUAD. HSD17B6 suppressed LUAD cell proliferation, migration, invasion, epithelial-mesenchymal transition (EMT), and radioresistance. Furthermore, HSD17B6 overexpression in LUAD cell lines enhanced PTEN expression and inhibited AKT phosphorylation, inactivating downstream oncogenes like GSK3β, β-catenin, and Cyclin-D independent of dihydrotestosterone, revealing an underlying antitumor mechanism of HSD17B6 in LUAD. Our findings indicate that HSD17B6 may function as a tumor suppressor in LUAD and could be a promising prognostic indicator for LUAD patients, especially for those receiving radiotherapy.

Identification of immunization-related new prognostic biomarkers for papillary renal cell carcinoma by integrated bioinformatics analysis

Background

Despite papillary renal cell carcinoma (pRCC) being the second most common type of kidney cancer, the underlying molecular mechanism remains unclear. Targeted therapies in the past have not been successful because of the lack of a clear understanding of the molecular mechanism. Hence, exploring the underlying mechanisms and seeking novel biomarkers for pursuing a precise prognostic biomarker and appropriate therapies are critical.

Material and methods

In our research, the differentially expressed genes (DEGs) were screened from the TCGA and GEO databases, and a total of 149 upregulated and 285 downregulated genes were sorted. This was followed by construction of functional enrichment and protein–protein interaction (PPI) network, and then the top 15 DEGs were selected for further analysis. The P4HB gene was chosen as our target gene by repetitively validating multiple datasets, and higher levels of P4HB expression predicted lower overall survival (OS) in patients with pRCC.

Results

We found that P4HB not only connects with immune cell infiltration and co-expression with PD-1, PD-L2, and CTLA-4, but also has a strong connection with the newly discovered hot gene, TOX.

Conclusion

We speculate that P4HB is a novel gene involved in the progression of pRCC through immunomodulation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-021-01092-w.

Comprehensive Analysis to Identify Enhancer-Regulated Inflammation-Associated Genes in Lung Adenocarcinoma

Objective

The purpose of this study was to identify prognostic inflammatory markers regulated by enhancers in lung adenocarcinoma (LUAD).

Methods

Inflammatory indices of 490 LUAD patients in TCGA database were calculated using genomic variation analysis (GSVA). Patients were divided into high- and low-inflammatory index groups. Fraction of 22 infiltrating immune cells was estimated using the Cell type Identification By Estimating Relative Subsets Of RNA Transcripts (CIBERSORT). Gene set enrichment analysis (GSEA) was used to analyze gene enrichment. Differentially expressed genes were screened based on TCGA database. The H3K27ac ChIP-seq of A549 cells in GEO database (GSE42374) was analyzed to identify super enhancers. Kaplan-Meier method and multivariate Cox proportional hazards models were used for survival analysis. CCK8 and RT-qPCR were used for cellular level verification.

Results

Inflammation was associated with better outcome in LUAD patients. Anti-cancer immune cell fractions were upregulated in high-inflammatory index group. Genes enriched in inflammation-related signaling pathways were positively correlated with high-inflammatory index group. A total of 146 upregulated genes regulated by enhancers were screened, of which five genes including GDF10, HPGDS, ABCA8, SLIT3 and ADAMTS8 had significant influence on prognosis. ChIP-seq analysis showed that TGFβ+TNFα treatment promoted the enhancer activation of the five genes. Cellular experiments revealed that there was no significant effect of TGFβ treatment on the five genes expression. TNFα treatment upregulated the five genes expression, while the BET-bromodomain inhibitor JQ1 restored the effect of TNFα. Overexpression of the five genes significantly inhibited the proliferation of A549 and H1299 cells.

Conclusion

GDF10, HPGDS, ABCA8, SLIT3 and ADAMTS8 were identified as enhancer-regulated prognostic inflammation-related biomarkers, and the expression of these genes inhibited proliferation of LUAD cells.

Transcriptomic Analyses Reveal B-Cell Translocation Gene 2 as a Potential Therapeutic Target in Ovarian Cancer

Ovarian cancer is the most common and aggressive type of tumor of the female reproductive system. Two factors account for this detrimental clinical presentation: (i) the lack of early detection methods and (ii) the inherently aggressive nature of this malignancy. Currently, transcriptomic analyses have become important tools to identify new targets in different cancer types. In this study, by measuring expression levels in ovarian cancer samples and stem cell samples, we identified 24 tumor suppressor genes consistently associated with poor prognosis. Combined results further revealed a potential therapeutic candidate, BTG2, which belongs to the antiproliferative gene family. Our results showed that BTG2 expression regulated ovarian cancer cell proliferation via G1/S phase cell cycle arrest by regulating Cyclin D1, CDK4, p-AKT, and p-ERK expression. BTG2 also inhibited cell migration by modulating MMP-2 and MMP-9 expression. Furthermore, xenograft models confirmed a growth inhibitory effect of BTG2 in ovarian cancer in vivo. BTG2 was significantly associated with ovarian cancer FIGO stage and grade in the clinic. Our findings indicated that BTG2 exerts a suppressive impact on ovarian cancer and could be a potential biomarker.

Interaction between DNMT3B and MYH11 via hypermethylation regulates gastric cancer progression

BACKGROUND

Gastric cancer (GC) has an unwelcoming prognosis when diagnosed at an advanced stage. The purpose of this study was to examine the expression of myosin heavy chain 11 (MYH11) in GC and mechanisms related.

METHODS

The MYH11 expression in GC was investigated via the SangerBox platform. MYH11 expression in GC tissues and cell lines was examined by immunohistochemistry, RT-qPCR, and western blot. The relationship between MYH11 expression and patients' prognosis was analyzed. The effects of MYH11 on the biological behaviors of GC cells were investigated by gain-of-function experiments. Bioinformatics analysis was used to find genes with relevance to MYH11 expression in GC. The relationship was verified by luciferase and ChIP-qPCR assays, followed by rescue assay validation. The causes of MYH11 downregulation in GC were verified by quantitative methylation-specific PCR. Finally, the effect of MYH11 on tumor growth was examined.

RESULTS

MYH11 was downregulated in GC and predicted poor prognoses. MYH11 reverted the malignant phenotype of GC cells. MYH11 repressed the TNFRSF14 expression by binding to the TNFRSF14 promoter. TNFRSF14 reversed the inhibitory effect of MYH11 on the malignant phenotype of GC cells. The methylation of the MYH11 promoter was elevated in GC, which was correlated with the elevated DNMT3B in GC. Overexpression of DNMT3B repressed transcription of MYH11 by promoting its methylation. Also, MYH11 upregulation inhibited tumor growth.

CONCLUSION

DNMT3B inhibits MYH11 expression by promoting its DNA methylation, thereby attenuating the repressive effect of MYH11 on the transcriptional of TNFRSF14 and promoting the progression of GC.

Identification of the miRNA signature and key genes in colorectal cancer lymph node metastasis

BACKGROUND

Because its metastasis to the lymph nodes are closely related to poor prognosis, miRNAs and mRNAs can serve as biomarkers for the diagnosis, prognosis, and therapy of colorectal cancer (CRC). This study aimed to identify novel gene signatures in the lymph node metastasis of CRC.

METHODS

GSE56350, GSE70574, and GSE95109 datasets were downloaded from the Gene Expression Omnibus (GEO) database, while data from 569 colorectal cancer cases were also downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed miRNAs (DE-miRNAs) were calculated using R programming language (Version 3.6.3), while gene ontology and enrichment analysis of target mRNAs were performed using FunRich ( http://www.funrich.org ). Furthermore, the mRNA-miRNA network was constructed using Cytoscape software (Version 3.8.0). Gene expression levels were verified using the GEO datasets. Similarly, quantitative real-time PCR (qPCR) was used to examine expression profiles from 20 paired non-metastatic and metastatic lymph node tissue samples obtained from patients with CRC.

RESULTS

In total, five DE-miRNAs were selected, and 34 mRNAs were identified after filtering the results. Moreover, two key miRNAs (hsa-miR-99a, hsa-miR-100) and one gene (heparan sulfate-glucosamine 3-sulfotransferase 2 [HS3ST2]) were identified. The GEO datasets analysis and qPCR results showed that the expression of key miRNA and genes were consistent with that obtained from the bioinformatic analysis. A novel miRNA-mRNA network capable of predicting the prognosis and confirmed experimentally, hsa-miR-99a-HS3ST2-hsa-miR-100, was found after expression analysis in metastasized lymph node tissue from CRC samples.

CONCLUSION

In summary, miRNAs and genes with potential as biomarkers were found and a novel miRNA-mRNA network was established for CRC lymph node metastasis by systematic bioinformatic analysis and experimental validation. This network may be used as a potential biomarker in the development of lymph node metastatic CRC.

Differentiation between thyroid-associated orbitopathy and Graves' disease by iTRAQ-based quantitative proteomic analysis

Graves' ophthalmopathy, also known as thyroid-associated orbitopathy (TAO), is the most common inflammatory eye disease in adults. The most common etiology for TAO is Graves' disease (GD); however, proteomic research focusing on differences between GD and TAO is limited. This study aimed to identify differentially expressed proteins between thyroid-associated orbitopathy (TAO) and GD. Furthermore, we sought to explore the pathogenesis of TAO and elucidate the differentiation process via specific markers. Serum samples of three patients with TAO, GD, and healthy controls, respectively, were collected. These samples were measured using the iTRAQ technique coupled with mass spectrometry. Differentially expressed proteins in TAO and GD were identified by proteomics; 3172 quantified proteins were identified. Compared with TAO, we identified 110 differential proteins (27 proteins were upregulated and 83 were downregulated). In addition, these differentially expressed proteins were closely associated with cellular processes, metabolic processes, macromolecular complexes, signal transduction, and the immune system. The corresponding functions were protein, calcium ion, and nucleic acid binding. Among the differential proteins, MYH11, P4HB, and C4A were markedly upregulated in TAO patients and have been reported to participate in apoptosis, autophagy, the inflammatory response, and the immune system. A protein-protein interaction network analysis was performed. Proteomics demonstrated valuable large-scale protein-related information for expounding the pathogenic mechanism underlying TAO. This research provides new insights and potential targets for studying GD with TAO.

Identification of Hub Genes Associated With Melanoma Development by Comprehensive Bioinformatics Analysis

Introduction

This study aimed to identify important genes associated with melanoma to further develop new target gene therapies and analyze their significance concerning prognosis.

Materials and methods

Gene expression data for melanoma and normal tissue were downloaded from three databases. Differentially co-expressed genes were identified by WGCNA and DEGs analysis. These genes were subjected to GO, and KEGG enrichment analysis and construction of the PPI visualized with Cytoscape and screened for the top 10 Hub genes using CytoHubba. We validated the Hub gene's protein levels with an immunohistochemical assay to confirm the accuracy of our analysis.

Results

A total of 435 differentially co-expressed genes were obtained. Survival curves showed that high expression of FOXM1,\ EXO1, KIF20A, TPX2, and CDC20 in melanoma patients with 5 of the top 10 hub genes was associated with reduced overall survival (OS). Immunohistochemistry showed that all five genes were expressed at higher protein levels in melanoma than in paracancerous tissues.

Conclusion

FOXM1, EXO1, KIF20A, TPX2, and CDC20 are prognosis-associated core genes of melanoma, and their high expression correlates with the low prognosis of melanoma patients and can be used as biomarkers for melanoma diagnosis, treatment, and prognosis prediction.

Similarity and difference of pathogenesis among lung cancer subtypes suggested by expression profile data

Lung cancer is difficult to diagnose, has a high mortality rate and a high recurrence rate. By grouping and analyzing the gene expression in lung cancer samples, we selected the differentially expressed genes (DEGs) in total lung cancers or each subgroup, and then searched for the similarities and differences among these. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment were performed, in addition to predictable cell proliferation or immune-related pathways, 'hemostasis', 'coagulation' and 'viral myocarditis' were also enriched in common DEGs, while specific functions or pathways were enriched in different subgroups. This may have implications for the treatment of total lung cancer or different subtypes. Through bioinformatics analysis, hub genes were obtained from total lung cancer and each subgroup respectively. Survival analysis of common hub genes led us to find that ZWINT, A2M, POLR2H and KIF11 are associated with unclassified lung cancer survival. For the construction of miRNA regulatory network, miR-16-5p was related to all of these four genes, and its expression is significantly different between lung cancers and normal samples. Combined with the hub genes of each subtype, it may have the ability of early screening and typing.

Detailed Molecular Mechanism and Potential Drugs for COL1A1 in Carboplatin-Resistant Ovarian Cancer

Carboplatin resistance in ovarian cancer (OV) is a major medical problem. Thus, there is an urgent need to find novel therapeutic targets to improve the prognosis of patients with carboplatin-resistant OV. Accumulating evidence indicates that the gene COL1A1 (collagen type I alpha 1 chain) has an important role in chemoresistance and could be a therapeutic target. However, there have been no reports about the role of COL1A1 in carboplatin-resistant OV. This study aimed to establish the detailed molecular mechanism of COL1A1 and predict potential drugs for its treatment. We found that COL1A1 had a pivotal role in carboplatin resistance in OV by weighted gene correlation network analysis and survival analysis. Moreover, we constructed a competing endogenous RNA network (LINC00052/SMCR5-miR-98-COL1A1) based on multi-omics data and experiments to explore the upstream regulatory mechanisms of COL1A1. Two key pathways involving COL1A1 in carboplatin resistance were identified by co-expression analysis and pathway enrichment: the "ECM-receptor interaction" and "focal adhesion" Kyoto Encyclopedia of Genes and Genomes pathways. Furthermore, combining these results with those of cell viability assays, we proposed that ZINC000085537017 and quercetin were potential drugs for COL1A1 based on virtual screening and the TCMSP database, respectively. These results might help to improve the outcome of OV in the future.

Knowledge-Guided "Community Network" Analysis Reveals the Functional Modules and Candidate Targets in Non-Small-Cell Lung Cancer

Non-small-cell lung cancer (NSCLC) represents a heterogeneous group of malignancies that are the leading cause of cancer-related death worldwide. Although many NSCLC-related genes and pathways have been identified, there remains an urgent need to mechanistically understand how these genes and pathways drive NSCLC. Here, we propose a knowledge-guided and network-based integration method, called the node and edge Prioritization-based Community Analysis, to identify functional modules and their candidate targets in NSCLC. The protein–protein interaction network was prioritized by performing a random walk with restart algorithm based on NSCLC seed genes and the integrating edge weights, and then a “community network” was constructed by combining Girvan–Newman and Label Propagation algorithms. This systems biology analysis revealed that the CCNB1-mediated network in the largest community provides a modular biomarker, the second community serves as a drug regulatory module, and the two are connected by some contextual signaling motifs. Moreover, integrating structural information into the signaling network suggested novel protein–protein interactions with therapeutic significance, such as interactions between GNG11 and CXCR2, CXCL3, and PPBP. This study provides new mechanistic insights into the landscape of cellular functions in the context of modular networks and will help in developing therapeutic targets for NSCLC.

Development of a Prognostic Signature Based on Single-Cell RNA Sequencing Data of Immune Cells in Intrahepatic Cholangiocarcinoma

Analysis of single-cell RNA sequencing (scRNA-seq) data of immune cells from the tumor microenvironment (TME) may identify tumor progression biomarkers. This study was designed to investigate the prognostic value of differentially expressed genes (DEGs) in intrahepatic cholangiocarcinoma (ICC) using scRNA-seq. We downloaded the scRNA-seq data of 33,991 cell samples, including 17,090 ICC cell samples and 16,901 ICC adjacent tissue cell samples regarded as normal cells. scRNA-seq data were processed and classified into 20 clusters. The immune cell clusters were extracted and processed again in the same way, and each type of immune cells was divided into several subclusters. In total, 337 marker genes of macrophages and 427 marker genes of B cells were identified by comparing ICC subclusters with normal subclusters. Finally, 659 DEGs were obtained by merging B cell and macrophage marker genes. ICC sample clinical information and gene expression data were downloaded. A nine-prognosis-related-gene (PRG) signature was established by analyzing the correlation between DEGs and overall survival in ICC. The robustness and validity of the signature were verified. Functional enrichment analysis revealed that the nine PRGs were mainly involved in tumor immune mechanisms. In conclusion, we established a PRG signature based on scRNA-seq data from immune cells of patients with ICC. This PRG signature not only reflects the TME immune status but also provides new biomarkers for ICC prognosis.

Identification of Potential Hub Genes Related to Diagnosis and Prognosis of Hepatitis B Virus-Related Hepatocellular Carcinoma via Integrated Bioinformatics Analysis

Hepatocellular carcinoma (HCC) is a common malignant cancer with poor survival outcomes, and hepatitis B virus (HBV) infection is most likely to contribute to HCC. But the molecular mechanism remains obscure. Our study intended to identify the candidate potential hub genes associated with the carcinogenesis of HBV-related HCC (HBV-HCC), which may be helpful in developing novel tumor biomarkers for potential targeted therapies. Four transcriptome datasets (GSE84402, GSE25097, GSE94660, and GSE121248) were used to screen the 309 overlapping differentially expressed genes (DEGs), including 100 upregulated genes and 209 downregulated genes. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment were used to explore the biological function of DEGs. A PPI network based on the STRING database was constructed and visualized by the Cytoscape software, consisting of 209 nodes and 1676 edges. Then, we recognized 17 hub genes by CytoHubba plugin, which were further validated on additional three datasets (GSE14520, TCGA-LIHC, and ICGC-LIRI-JP). The diagnostic effectiveness of hub genes was assessed with receiver operating characteristic (ROC) analysis, and all hub genes displayed good performance in discriminating TNM stage I patient samples and normal tissue ones. For prognostic analysis, two prognostic key genes (TOP2A and KIF11) out of the 17 hub genes were screened and used to develop a prognostic signature, which showed good potential for overall survival (OS) stratification of HBV-HCC patients. Gene Set Enrichment Analysis (GSEA) was performed in order to better understand the function of this prognostic gene signature. Finally, the miRNA-mRNA regulatory relationships of all hub genes in human liver were predicted using miRNet. In conclusion, the current study gives further insight on the pathogenesis and carcinogenesis of HBV-HCC, and the identified DEGs provide a promising direction for improving the diagnostic, prognostic, and therapeutic outcomes of HBV-HCC.

Screening and Identification of Potential Biomarkers in Hepatitis B Virus-Related Hepatocellular Carcinoma by Bioinformatics Analysis

Hepatocellular carcinoma (HCC) is one of the most lethal cancers globally. Hepatitis B virus (HBV) infection might cause chronic hepatitis and cirrhosis, leading to HCC. To screen prognostic genes and therapeutic targets for HCC by bioinformatics analysis and determine the mechanisms underlying HBV-related HCC, three high-throughput RNA-seq based raw datasets, namely GSE25599, GSE77509, and GSE94660, were obtained from the Gene Expression Omnibus database, and one RNA-seq raw dataset was acquired from The Cancer Genome Atlas (TCGA). Overall, 103 genes were up-regulated and 127 were down-regulated. A protein–protein interaction (PPI) network was established using Cytoscape software, and 12 pivotal genes were selected as hub genes. The 230 differentially expressed genes and 12 hub genes were subjected to functional and pathway enrichment analyses, and the results suggested that cell cycle, nuclear division, mitotic nuclear division, oocyte meiosis, retinol metabolism, and p53 signaling-related pathways play important roles in HBV-related HCC progression. Further, among the 12 hub genes, kinesin family member 11 (KIF11), TPX2 microtubule nucleation factor (TPX2), kinesin family member 20A (KIF20A), and cyclin B2 (CCNB2) were identified as independent prognostic genes by survival analysis and univariate and multivariate Cox regression analysis. These four genes showed higher expression levels in HCC than in normal tissue samples, as identified upon analyses with Oncomine. In addition, in comparison with normal tissues, the expression levels of KIF11, TPX2, KIF20A, and CCNB2 were higher in HBV-related HCC than in HCV-related HCC tissues. In conclusion, our results suggest that KIF11, TPX2, KIF20A, and CCNB2 might be involved in the carcinogenesis and development of HBV-related HCC. They can thus be used as independent prognostic genes and novel biomarkers for the diagnosis of HBV-related HCC and development of pertinent therapeutic strategies.

Identification and Validation of Novel Genes in Anaplastic Thyroid Carcinoma via Bioinformatics Analysis

Purpose

The conventional interventions of anaplastic thyroid carcinoma (ATC) patients are mainly through surgery, chemotherapy, and radiotherapy; however, it is hardly to improve survival rate. We aimed to investigate the differential expressed genes (DEGs) between ATC and normal thyroid gland through bioinformatics analysis of the microarray datasets and find new potential therapeutic targets for ATC.

Methods

Microarray datasets GSE9115, GSE29265, GSE33630, GSE53072, and GSE65144 were downloaded from Gene Expression Omnibus (GEO) database. Compared with the normal tissue, GEO2R was conducted to screen the DEGs in each chip under the condition of |log FC| > l, adjusted P‐values (adj. P) < 0.05. The Retrieval of Interacting Genes (STRING) database was used to calculate PPI networks of DEGs with a combined score >0.4 as the cut-off criteria. The hub genes in the PPI network were visualized and selected according to screening conditions in Cytoscape software. In addition, the novel genes in ATC were screened for survival analysis using Kaplan–Meier plotter from those hub genes and validated by RT-qPCR.

Results

A total of 284 overlapping DEGs were obtained, including 121 upregulated and 161 downregulated DEGs. A total of 232 DEGs were selected by STRING database. The 50 hub genes in the PPI network were chosen according to three screening conditions. In addition, the Kaplan–Meier plotter database confirmed that high expressions of ANLN, CENPF, KIF2C, TPX2, and NDC80 were negatively correlated with poor overall survival of ATC patients. Finally, RT-qPCR experiments showed that KIF2C and CENPF were significantly upregulated in ARO cells and CAL-62 cells when compared to Nthy-ori 3–1 cells, TPX2 was upregulated only in CAL-62 cells, while ANLN and NDC80 were obviously decreased in ARO cells and CAL-62 cells.

Conclusion

Our study suggested that CENPF, KIF2C, and TPX2 might play a significant role in the development of ATC, which could be further explored as potential biomarkers for the treatment of ATC.

Constructing a global transcriptional regulatory landscape for early non-small cell lung cancer to identify hub genes and key pathways

This study aimed to investigate the potential pathogenesis of early non-small cell lung cancer (NSCLC), including lung adenocarcinoma (LUAD) and lung squamous cell carcinoma (LUSC), by constructing a global transcriptional regulatory landscape to identify hub genes and key pathways. A total of 1,206 differentially expressed genes (DEGs) in early NSCLC were identified compared to normal lung tissue samples in GSE33532 and GSE29013. DEGs-related protein-protein interaction networks (PPIs) were constructed based on the STRING database and were then modularly analyzed using the ClusterOne tool. The enrichment analysis revealed that multiple modules were significantly involved in pathways such as the TNF signaling pathway, PPAR signaling pathway and PI3K/AKt signaling pathway. Ten genes were identified as hub genes in the PPIs and also found up-regulated at protein level. The prognostic value of the hub genes and the ten hub gene set variation score varied according to the different pathological types of NSCLC, which suggested the ten hub gene expression patterns can reflect the heterogeneity of two types of NSCLC. In conclusion, by carrying out a series of in-depth analyses, hub genes and key pathways associated with early NSCLC were identified by a global transcriptional regulatory landscape.

Comprehensive Genomic Analysis Reveals the Prognostic Role of LRRK2 Copy-Number Variations in Human Malignancies

Genetic alterations of leucine-rich repeat kinase 2 (LRRK2), one of the most important contributors to familial Parkinson’s disease (PD), have been hypothesized to play a role in cancer development due to demographical and preclinical data. Here, we sought to define the prevalence and prognostic significance of LRRK2 somatic mutations across all types of human malignancies by querying the publicly available online genomic database cBioPortal. Ninety-six different studies with 14,041 cases were included in the analysis, and 761/14,041 (5.4%) showed genetic alterations in LRRK2. Among these, 585 (76.9%) were point mutations, indels or fusions, 168 (22.1%) were copy number variations (CNVs), and 8 (1.0%) showed both types of alterations. One case showed the somatic mutation R1441C. A significant difference in terms of overall survival (OS) was noted between cases harboring somatic LRRK2 whole deletions, amplifications, and CNV-unaltered cases (median OS: 20.09, 57.40, and 106.57 months, respectively; p = 0.0008). These results suggest that both LRRK2 amplifications and whole gene deletions could play a role in cancer development, paving the way for future research in terms of potential treatment with LRRK2 small molecule inhibitors for LRRK2-amplified cases.

NCAPH is upregulated in endometrial cancer and associated with poor clinicopathologic characteristics

BACKGROUND

Recently, NCAPH (non-SMC condensin I complex subunit H), a regulatory subunit of the condensin complex, has captured our attention in various cancer studies. However, the function of NCAPH in endometrial cancer (EC) remains unclear. Our study aims to investigate the role of NCAPH in EC.

METHODS

The expression of NCAPH in EC tissues and normal tissues was predicted by The Cancer Genome Atlas (TCGA). The Kaplan-Meier analysis was performed to evaluate the impact of NCAPH expression on EC patients' survival. Logistic regression was used to study the correlation of NCAPH expression with clinicopathologic characteristics. Molecular mechanisms behind NCAPH in EC were evaluated by Gene Set Enrichment Analysis, genetic mutations, copy number variation, and DNA methylation level.

RESULTS

NCAPH was significantly upregulated in EC (p = 1e-24), and its expression level was significantly related to the more advanced International Federation of Gynecology & Obstetrics (FIGO) stage (stage IV vs. stage I: odd ratio.[OR] = 3.7), higher grade (poor vs. well & moderate: OR = 5.3), serous histology subtype (SEA vs. EEA: OR = 8.5), myometrial invasion (≥50 vs. < 50 invasion: OR = 1.8), metastasis (vs. no metastasis: OR = 2.5), and with-tumor status (vs. free of tumor: OR = 2.3) (all p were less than .05). The Gene Set Enrichment Analysis method indicated that MITOTIC_SPINDLE, G2M_CHECKPOINT, MYC_TARGETS_V1, E2F_TARGETS, MYC_TARGETS_V2, and MTORC1_SIGNALING were involved in the upregulated NCAPH group. NCAPH hypomethylation, amplified copy number variations and genetic mutations; all played a contributive role in NCAPH upregulation.

CONCLUSIONS

These results reveal NCAPH functions as oncogene and promote the development of EC.

Downexpression of HSD17B6 correlates with clinical prognosis and tumor immune infiltrates in hepatocellular carcinoma

Background

Hydroxysteroid 17-Beta Dehydrogenase 6 (HSD17B6), a key protein involved in synthetizing dihydrotestosterone, is abundant in the liver. Previous studies have suggested a role for dihydrotestosterone in modulating progress of various malignancies, and HSD17B6 dysfunction was associated with lung cancer and prostate cancer. However, little is known about the detailed role of HSD17B6 in hepatocellular carcinoma (HCC).

Methods

Clinical implication and survival data related to HSD17B6 expression in patients with HCC were obtained through TCGA, ICGC, ONCOMINE, GEO and HPA databases. Survival analysis plots were drawn with Kaplan–Meier Plotter. The ChIP-seq data were obtained from Cistrome DB. Protein–Protein Interaction and gene functional enrichment analyses were performed in STRING database. The correlations between HSD17B6 and tumor immune infiltrates was investigated via TIMER and xCell. The proliferation, migration and invasion of liver cancer cells transfected with HSD17B6 were evaluated by the CCK8 assay, wound healing test and transwell assay respectively. Expression of HSD17B6, TGFB1 and PD-L1 were assessed by quantitative RT-PCR.

Results

HSD17B6 expression was lower in HCC compared to normal liver and correlated with tumor stage and grade. Lower expression of HSD17B6 was associated with worse OS, PFS, RFS and DSS in HCC patients. HNF4A bound to enhancer and promoter regions of HSD17B6 gene, activating its transcription, and DNA methylation of HSD17B6 promoter negatively controlled the expression. HSD17B6 and its interaction partners were involved in androgen metabolism and biosynthesis in liver. HSD17B6 inhibited tumor cell proliferation, migration and invasion in liver cancer cells and low expression of HSD17B6 correlated with high immune cells infiltration, relative reduction of immune responses and multiple immune checkpoint genes expression in HCC, probably by regulating the expression of TGFB1.

Conclusions

This study indicate that HSD17B6 could be a new biomarker for the prognosis of HCC and an important negative regulator of immune responses in HCC.

Bioinformatics Analysis Reveals Biomarkers With Cancer Stem Cell Characteristics in Lung Squamous Cell Carcinoma

Background

Tumor stem cells play important roles in the survival, proliferation, metastasis and recurrence of tumors. We aimed to identify new prognostic biomarkers for lung squamous cell carcinoma (LUSC) based on the cancer stem cell theory.

Methods

RNA-seq data and relevant clinical information were downloaded from The Cancer Genome Atlas (TCGA) database. Weighted gene coexpression network analysis (WGCNA) was applied to identify significant modules and hub genes, and prognostic signatures were constructed with the prognostic hub genes.

Results

LUSC patients in the TCGA database have higher mRNA expression-based stemness index (mRNAsi) in tumor tissue than in adjacent normal tissue. In addition, some clinical features and outcomes were highly correlated with the mRNAsi. WGCNA revealed that the pink and yellow modules were the most significant modules related to the mRNAsi; the top 10 hub genes in the pink module were enriched mostly in epidermal development, the secretory granule membrane, receptor regulator activity and the cytokine-cytokine receptor interaction. The protein–protein interaction (PPI) network revealed that the top 10 hub genes were significantly correlated with each other at the transcriptional level. In addition, the top 10 hub genes were all highly expressed in LUSC, and some were differentially expressed in different TNM stages. Regarding the survival analysis, the nomogram of a prognostic signature with three hub genes showed high predictive value.

Conclusion

mRNAsi-related hub genes could be a potential biomarker of LUSC.

Identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma

Aim:

To screen and identify key genes related to the development of smoking-induced lung adenocarcinoma (LUAD).

Materials & methods:

We obtained data from the GEO chip dataset GSE31210. The differentially expressed genes were screened by GEO2R. The protein interaction network of differentially expressed genes was constructed by STRING and Cytoscape. Finally, core genes were screened. The overall survival time of patients with the core genes was analyzed by Kaplan–Meier method. Gene ontology and Kyoto encyclopedia of genes and genomes bioaccumulation was calculated by DAVID.

Results:

Functional enrichment analysis indicated that nine key genes were actively involved in the biological process of smoking-related LUAD.

Conclusion:

23 core genes and nine key genes among them were correlated with adverse prognosis of LUAD induced by smoking.

An atlas of transposable element-derived alternative splicing in cancer

Transposable element (TE)-derived sequences comprise more than half of the human genome, and their presence has been documented to alter gene expression in a number of different ways, including the generation of alternatively spliced transcript isoforms. Alternative splicing has been associated with tumorigenesis for a number of different cancers. The objective of this study was to broadly characterize the role of human TEs in generating alternatively spliced transcript isoforms in cancer. To do so, we screened for the presence of TE-derived sequences co-located with alternative splice sites that are differentially used in normal versus cancer tissues. We analysed a comprehensive set of alternative splice variants characterized for 614 matched normal-tumour tissue pairs across 13 cancer types, resulting in the discovery of 4820 TE-generated alternative splice events distributed among 723 cancer-associated genes. Short interspersed nuclear elements (Alu) and long interspersed nuclear elements (L1) were found to contribute the majority of TE-generated alternative splice sites in cancer genes. A number of cancer-associated genes, including MYH11, WHSC1 and CANT1, were shown to have overexpressed TE-derived isoforms across a range of cancer types. TE-derived isoforms were also linked to cancer-specific fusion transcripts, suggesting a novel mechanism for the generation of transcriptome diversity via trans-splicing mediated by dispersed TE repeats. This article is part of a discussion meeting issue 'Crossroads between transposons and gene regulation'.

Clinical and prognostic significance of MYH11 in lung cancer

Myosin heavy chain 11 (MYH11), encoded by the MYH11 gene, is a protein that participates in muscle contraction through the hydrolysis of adenosine triphosphate. Although previous studies have demonstrated that MYH11 gene expression levels are downregulated in several types of cancer, its expression levels have rarely been investigated in lung cancer. The present study aimed to explore the clinical significance and prognostic value of MYH11 expression levels in lung cancer and to further study the underlying molecular mechanisms of the function of this gene. The Oncomine database showed that the MYH11 expression levels were decreased in lung cancer compared with those noted in the normal lung tissue (P<0.05). Kaplan-Meier plotter results revealed that the decreased MYH11 expression levels were correlated with poor prognosis in lung cancer patients. Among the lung cancer cases with gene alteration of MYH11, mutation was the most common of all alteration types. Coexpedia and Metascape analyses revealed that the target genes were primarily enriched in ‘muscle contraction’, ‘contractile fiber part’, ‘actin cytoskeleton’ and the ‘adherens junction’. These results indicated that MYH11 is a potential novel drug target and prognostic indicator of lung cancer.