Co-expression network analysis identified KIF2C in association with progression and prognosis in lung adenocarcinoma

Silencing of KIF2C enhances the sensitivity of hepatocellular carcinoma cells to cisplatin through regulating the PI3K/AKT/MAPK signaling pathway

In the treatment of unresectable advanced hepatocellular carcinoma (HCC), cisplatin is administered transhepatic arterially for local treatment, but the clinical application of cisplatin drugs is frequently hindered by the emergence of drug resistance. Kinesin family member 2C( KIF2C ) has been shown as oncogene in a variety of tumors. Nevertheless, its effect on cisplatin sensitivity has yet to be ascertained. Herein, we aim to investigate the impact of the KIF2C gene on cisplatin sensitivity within HCC and the plausible underlying molecular mechanism. We examined the expression level of the KIF2C gene in HCC cells by real-time quantitative reverse transcription PCR and Western blot analysis, and analyzed bioinformatically by The Gene Expression Omnibus database and The Cancer Genome Atlas database. The KIF2C gene was silenced using the small interfering RNA technology, and its effect on cisplatin drug sensitivity in HCC cells was evaluated by flow cytometry, cell proliferation, cell migration, and invasion assays. Our results indicated that KIF2C was highly expressed in HCC cells. KIF2C silencing inhibits HCC cell proliferation, migration and invasion, promotes apoptosis, and keeps the cell cycle in G2 phase. In addition, KIF2C silencing enhanced the sensitivity of HCC cells to cisplatin. KIF2C silencing down-regulates the expression levels of phosphatidylinositol 3-kinase (PI3K), protein kinase B (AKT) and mitogen-activated protein kinase 3 (MAPK3) proteins. In conclusion, KIF2C silencing amplifies the sensitivity of HCC cells to cisplatin by regulating the PI3K/AKT/MAPK signaling pathway. Consequently, targeting KIF2C shows great application potential as a strategy for enhancing the effectiveness of HCC treatment.

KIF2C/MCAK a prognostic biomarker and its oncogenic potential in malignant progression, and prognosis of cancer patients: a systematic review and meta-analysis as biomarker

KIF2C/MCAK (KIF2C) is the most well-characterized member of the kinesin-13 family, which is critical in the regulation of microtubule (MT) dynamics during mitosis, as well as interphase. This systematic review briefly describes the important structural elements of KIF2C, its regulation by multiple molecular mechanisms, and its broad cellular functions. Furthermore, it systematically summarizes its oncogenic potential in malignant progression and performs a meta-analysis of its prognostic value in cancer patients. KIF2C was shown to be involved in multiple crucial cellular processes including cell migration and invasion, DNA repair, senescence induction and immune modulation, which are all known to be critical during the development of malignant tumors. Indeed, an increasing number of publications indicate that KIF2C is aberrantly expressed in multiple cancer entities. Consequently, we have highlighted its involvement in at least five hallmarks of cancer, namely: genome instability, resisting cell death, activating invasion and metastasis, avoiding immune destruction and cellular senescence. This was followed by a systematic search of KIF2C/MCAK's expression in various malignant tumor entities and its correlation with clinicopathologic features. Available data were pooled into multiple weighted meta-analyses for the correlation between KIF2Chigh protein or gene expression and the overall survival in breast cancer, non-small cell lung cancer and hepatocellular carcinoma patients. Furthermore, high expression of KIF2C was correlated to disease-free survival of hepatocellular carcinoma. All meta-analyses showed poor prognosis for cancer patients with KIF2Chigh expression, associated with a decreased overall survival and reduced disease-free survival, indicating KIF2C's oncogenic potential in malignant progression and as a prognostic marker. This work delineated the promising research perspective of KIF2C with modern in vivo and in vitro technologies to further decipher the function of KIF2C in malignant tumor development and progression. This might help to establish KIF2C as a biomarker for the diagnosis or evaluation of at least three cancer entities.

KIF2C: An important factor involved in signaling pathways, immune infiltration, and DNA damage repair in tumorigenesis

BACKGROUNDS

Poorly regulated mitosis and chromosomal instability are common characteristics in malignant tumor cells. Kinesin family member 2 C (KIF2C), also known as mitotic centromere-associated kinesin (MCAK) is an essential component during mitotic regulation. In recent years, KIF2C was shown to be dysregulated in several tumors and was involved in many aspects of tumor self-regulation. Research on KIF2C may be a new direction and target for anti-tumor therapy.

OBJECT

The article aims at reviewing current literatures and summarizing the research status of KIF2C in malignant tumors as well as the oncogenic signaling pathways associated with KIF2C and its role in immune infiltration.

RESULT

In this review, we summarize the KIF2C mechanisms and signaling pathways in different malignant tumors, and briefly describe its involvement in pathways related to classical chemotherapeutic drug resistance, such as MEK/ERK, mTOR, Wnt/β-catenin, P53 and TGF-β1/Smad pathways. KIF2C upregulation was shown to promote tumor cell migration, invasion, chemotherapy resistance and inhibit DNA damage repair. It was also highly correlated with microRNAs, and CD4 +T cell and CD8 +T cell tumor immune infiltration.

CONCLUSION

This review shows that KIF2C may function as a new anticancer drug target with great potential for malignant tumor treatment and the mitigation of chemotherapy resistance.

KIF2C promotes clear cell renal cell carcinoma progression via activating JAK2/STAT3 signaling pathway

BACKGROUND

Clear cell renal cell carcinoma (ccRCC) is one of the most common malignant tumors that can be highly aggressive. Despite advances in the exploration of its underlying molecular biology, the clinical outcome for advanced ccRCC is still unsatisfied. Recently, more attention was paid to the functions of Kinesin family member 2C (KIF2C) in cancer progression, while the specific function of KIF2C in ccRCC has not been sufficiently elucidated. The present study aims to investigate the role of KIF2C in the progression of ccRCC and reveal potential mechanisms.

METHODS

Expression of KIF2C in ccRCC tissues and adjacent normal tissue was compared and the association of KIF2C expression level with tumor grade, stage, and metastasis were analyzed using online web tool. Kaplan-Meier survival was performed to detect the association of KIF2C expression and patient' prognosis. Stably cell lines with KIF2C knockdown or overexpression were constructed by lentivirus infection. CCK-8, colony formation, scratch healing, and transwell invasion assays were carried out to explore the effect of KIF2C knockdown or overexpression on the proliferation, migration, and invasion of ccRCC cells. Gene set enrichment analysis (GSEA) was conducted to reveal signaling pathways associated with KIF2C expression. The effect of KIF2C on JAK2/STAT3 signaling pathway were explored by western blot assay.

RESULTS

KIF2C expression was significantly upregulated in ccRCC tissues and was higher with the increase of tumor grade, stage, and metastasis. Higher expression of KIF2C was correlated with worse overall survival and diseases free survival in ccRCC patients. Silence of KIF2C inhibited proliferation, migration, and invasion in ccRCC cells. Conversely, overexpression of KIF2C had the opposite effect. GSEA results showed that JAK/STAT signaling pathway was markedly enriched in KIF2Chigh group. Pearson' correlation revealed that KIF2C expression was significantly associated with genes in JAK2/STAT3 signaling. Western blot results showed that KIF2C knockdown decreased protein expression of p-JAK2 and p-STAT3, and KIF2C overexpression increased the phosphorylation of JAK2 and STAT3. AG490, a JAK2/STAT3 signaling inhibitor, could partly impair the tumor-promoting effects of KIF2C in ccRCC.

CONCLUSION

KIF2C expression was significantly upregulated in ccRCC and correlated with tumor grade, stage, metastasis, and patients' prognosis. KIF2C promoted ccRCC progression via activating JAK2/STAT3 signaling pathway, and KIF2C might be a novel target in ccRCC therapy.

Structure-based virtual screening and molecular docking approaches to identify potential inhibitors against KIF2C to combat glioma

Glioma, a kind of malignant brain tumor, is extremely lethal. Kinesin family member 2C (KIF2C) was found to have an aberrant expression in several cancer types, including lung cancer and glioma. KIF2C may therefore be a useful therapeutic target for the treatment of glioma. In the current study, new drug candidates that may function as KIF2C enzyme inhibitors were discovered. MTi OpenScreen was used to carry out the structure-based virtual screening of an inbuilt drug library containing 150,000 compounds. These compounds belong to different classes, such as natural product-based compounds (NP-lib), purchasable approved drugs (Drugs-lib), and food constituents compound collection (FOOD-lib). Based on their binding affinities, a total of 84 compounds were further pushed to calculate ADMET properties. The compounds (16) meeting the ADMET cutoff ranges were then further docked to the receptor to find their plausible binding modes using the Glide tool's standard precision (SP) technique. The docking results were examined using the Glide gscore, and the best binding compounds (Rimacalib and Sarizotan) were chosen to test their stability with KIF2C protein through molecular dynamics (MD) simulation. Similarly, Principal Component Analysis and cross-correlation matrix were also examined. The MM/GBSA binding free energies showed a considerable energy contribution in the binding of hits with the KIF2C. Collectively, these findings strongly suggest the potential of the lead compounds to inhibit the biological function of KIF2C, emphasizing the need for further investigation in this area.Communicated by Ramaswamy H. Sarma.

Bioinformatical analysis of the key differentially expressed genes for screening potential biomarkers in Wilms tumor

Wilms tumor (WT) is the most common pediatric renal malignant tumor in the world. Overall, the prognosis of Wilms tumor is very good. However, the prognosis of patients with anaplastic tumor histology or disease relapse is still poor, and their recurrence rate, metastasis rate and mortality are significantly increased compared with others. Currently, the combination of histopathological examination and molecular biology is essential to predict prognosis and guide the treatment. However, the molecular mechanism has not been well studied. Genetic profiling may be helpful in some way. Hence, we sought to identify novel promising biomarkers of WT by integrating bioinformatics analysis and to identify genes associated with the pathogenesis of WT. In the presented study, the NCBI Gene Expression Omnibus was used to download two datasets of gene expression profiles related to WT patients for the purpose of detecting overlapped differentially expressed genes (DEGs). The DEGs were then uploaded to DAVID database for enrichment analysis. In addition, the functional interactions between proteins were evaluated by simulating the protein-protein interaction (PPI) network of DEGs. The impact of selected hub genes on survival in WT patients was analyzed by using the online tool R2: Genomics Analysis and Visualization Platform. The correlation between gene expression and the degree of immune infiltration was assessed by the Estimation of Stromal and Immune cells in Malignant Tumor tissues using the Expression (ESTIMATE) algorithm and the single sample GSEA. Top 12 genes were identified for further study after constructing a PPI network and screening hub gene modules. Kinesin family member 2C (KIF2C) was identified as the most significant gene predicting the overall survival of WT patients. The expression of KIF2C in WT was further verified by quantitative real-time polymerase chain reaction and immunohistochemistry. Furthermore, we found that KIF2C was significantly correlated with immune cell infiltration in WT. Our present study demonstrated that altered expression of KIF2C may be involved in WT and serve as a potential prognostic biomarker for WT patients.

Investigating the role of Kinesin family in lung adenocarcinoma via integrated bioinformatics approach

Lung cancer is the leading cause of mortality from cancer worldwide. Lung adenocarcinoma (LUAD) is a type of non-small cell lung cancer (NSCLC) with highest prevalence. Kinesins a class of motor proteins are shown to be involved in carcinogenesis. We conducted expression, stage plot and survival analyses on kinesin superfamily (KIF) and scrutinized the key prognostic kinesins. Genomic alterations of these kinesins were studied thereafter via cBioPortal. A protein-protein interaction network (PPIN) of selected kinesins and 50 closest altering genes was constructed followed by gene ontology (GO) term and pathway enrichment analyses. Multivariate survival analysis based on CpG methylation of selected kinesins was performed. Lastly, we conducted tumor immune infiltration analysis. Our results found KIF11/15/18B/20A/2C/4A/C1 to be significantly upregulated and correlated with poor survival in LUAD patients. These genes also showed to be highly associated with cell cycle. Out of our seven selected kinesins, KIFC1 showed the highest genomic alteration with highest number of CpG methylation. Also, CpG island (CGI) cg24827036 was discovered to be linked to LUAD prognosis. Therefore, we deduced that reducing the expression of KIFC1 could be a feasible treatment strategy and that it can be a wonderful individual prognostic biomarker. CGI cg24827036 can also be used as a therapy site in addition to being a great prognostic biomarker.

LINC00491 Facilitates Tumor Progression of Lung Adenocarcinoma via Wnt/β-Catenin-Signaling Pathway by Regulating MTSS1 Ubiquitination

Background: Long non-coding RNAs have been reported to be involved in tumorigenesis and progression through different regulatory mechanisms. It has been reported that aberrantly expressed long non-coding RNA LINC00491 promotes malignancy in multiple tumors, while the role of LINC00491 in lung adenocarcinoma (LUAD) is little reported and the mechanism for regulating tumor progression has not been elucidated. Methods: RNA sequencing and the TCGA database were combined to screen differentially expressed lncRNAs that facilitate tumor progression. The expression level of LINC00491 was examined in LUAD clinical samples and in cell lines using RT-qPCR. In vitro experiments including colony formation assay, EdU assay, cell migration and invasion assay and wound healing assay, and in vivo experiments including xenografting subcutaneous tumors and lung metastasis models were performed to investigate the function of LINC00491 in LUAD tumor progressions. RNA pull-down, mass spectrometry, RIP assays and truncation experiments were carried out to explore the proteins binding to LINC00491 and the specific interactions between the RNA-protein complex. Results: Our results showed that LINC0491 was significantly upregulated in LUAD and positively correlated with poor survival. High LINC00491 expression promoted proliferation, migration and invasion, and resulted in a high metastatic burden in LUAD. Using pull-down assay and mass spectrometry, MTSS1 was found binding to LINC00491, and the conducted experiments verified the direct interaction between LINC00491 and MTSS1. Meanwhile, LINC00491 was found to regulate MTSS1 degradation by promoting the MTSS1 ubiquitination level and then activating the Wnt/β-catenin-signaling pathway. LINC00491/MTSS1/β-catenin may act as a complex to facilitate tumor progression. Conclusions: In summary, our results found a novel mechanism in which LINC00491 directly interacts with MTSS1 by affecting its ubiquitination modification to promote LUAD proliferation, migration and invasion, then activating the Wnt/β-catenin-signaling pathway, demonstrating its significant role in tumor progression and suggesting that the LINC00491/MTSS1/Wnt/β-catenin-signaling pathway could serve as a potential therapeutic target for lung adenocarcinoma in the future.

Identifying General Tumor and Specific Lung Cancer Biomarkers by Transcriptomic Analysis

The bioinformatic pipeline previously developed in our research laboratory is used to identify potential general and specific deregulated tumor genes and transcription factors related to the establishment and progression of tumoral diseases, now comparing lung cancer with other two types of cancer. Twenty microarray datasets were selected and analyzed separately to identify hub differentiated expressed genes and compared to identify all the deregulated genes and transcription factors in common between the three types of cancer and those unique to lung cancer. The winning DEGs analysis allowed to identify an important number of TFs deregulated in the majority of microarray datasets, which can become key biomarkers of general tumors and specific to lung cancer. A coexpression network was constructed for every dataset with all deregulated genes associated with lung cancer, according to DAVID’s tool enrichment analysis, and transcription factors capable of regulating them, according to oPOSSUM´s tool. Several genes and transcription factors are coexpressed in the networks, suggesting that they could be related to the establishment or progression of the tumoral pathology in any tissue and specifically in the lung. The comparison of the coexpression networks of lung cancer and other types of cancer allowed the identification of common connectivity patterns with deregulated genes and transcription factors correlated to important tumoral processes and signaling pathways that have not been studied yet to experimentally validate their role in lung cancer. The Kaplan–Meier estimator determined the association of thirteen deregulated top winning transcription factors with the survival of lung cancer patients. The coregulatory analysis identified two top winning transcription factors networks related to the regulatory control of gene expression in lung and breast cancer. Our transcriptomic analysis suggests that cancer has an important coregulatory network of transcription factors related to the acquisition of the hallmarks of cancer. Moreover, lung cancer has a group of genes and transcription factors unique to pulmonary tissue that are coexpressed during tumorigenesis and must be studied experimentally to fully understand their role in the pathogenesis within its very complex transcriptomic scenario. Therefore, the downstream bioinformatic analysis developed was able to identify a coregulatory metafirm of cancer in general and specific to lung cancer taking into account the great heterogeneity of the tumoral process at cellular and population levels.

Large-Scale Transcriptome Data Analysis Identifies KIF2C as a Potential Therapeutic Target Associated With Immune Infiltration in Prostate Cancer

Prostate cancer (PCa) is one of the most prevalent cancers of the urinary system. In previous research, Kinesin family member 2C (KIF2C), as an oncogene, has been demonstrated to have a key role in the incidence and progression of different cancers. However, KIF2C has not been reported in PCa. We combined data from different databases, including The Cancer Genome Atlas, the Cancer Cell Line Encyclopedia, Genotype Tissue-Expression, cBioPortal, and the Genomics of Drug Sensitivity in Cancer database, to explore the potential oncogenic role of KIF2C in PCa through a series of bioinformatics approaches, including analysis of the association between KIF2C and prognosis, clinicopathological features, gene mutations, DNA methylation, immune cell infiltration, and drug resistance. The results showed that KIF2C was significantly up-regulated in PCa. High KIF2C expression was associated with age, pathological stage, lymph node metastases, prostate-specific antigen (PSA), and Gleason score and significantly predicted an unfavorable prognosis in PCa patients. Results from Gene Set Enrichment Analysis (GSEA) suggested that KIF2C was involved in the cell cycle and immune response. KIF2C DNA methylation was reduced in PCa and was inversely linked with KIF2C expression. KIF2C was shown to have a strong relationship with the tumor microenvironment (TME), infiltrating cells, and immune checkpoint genes. Furthermore, high KIF2C expression was significantly resistant to a variety of MAPK signaling pathway-related inhibitors. Our study reveals that KIF2C may be a possible predictive biomarker for assessing prognosis in PCa patients with immune infiltration.

Identification of potential circular RNA biomarkers in lung adenocarcinoma: A bioinformatics analysis and retrospective clinical study

Non-small cell lung cancer (NSCLC) is one of the leading causes of cancer-associated mortality. Lung adenocarcinoma (LAC) is the most prevalent pathological subtype of NSCLC and accounts for ~40% of all lung cancer mortalities. There remains an urgent demand for the identification of novel biomarkers for the diagnosis and development of therapeutic strategies for LAC. In the present study, the profiles of the differentially-expressed circular RNAs (circRNAs) in LAC tissues compared with those in their corresponding non-cancerous tissues were obtained after analyzing the circRNA microarray dataset GSE101586. The expression pattern of the indicated circRNAs in the LAC tissues were subsequently verified using reverse transcription-quantitative PCR (RT-qPCR). The potential prognostic significance of these circRNAs in patients with LAC were then analyzed in a retrospective clinical study. A circRNA-microRNA (miR or miRNA)-mRNA regulatory network in LAC was established by using Cytoscape. In addition, a protein-protein interaction (PPI) network was plotted using the Search Tool for the Retrieval of Interacting Genes/Proteins and visualized through Cytoscape. The prognostic value of the hub genes found was then analyzed based on the Gene Expression Profiling Interactive Analysis database. In total, four differentially-expressed circRNAs were obtained from the GSE101586 microarray dataset, three of which (hsa_circ_0006220, hsa_circ_0072088 and hsa_circ_0001666) were confirmed by RT-qPCR to be highly expressed in LAC tissues. This retrospective clinical study revealed that higher expression levels of these three circRNAs were associated with poorer prognoses in patients with LAC. In addition, siRNA-mediated knockdown of these circRNAs was found to inhibit cell proliferation, migration and invasion in LAC cells. Following analysis of the molecular mechanism underlying these circRNAs, eight miRNAs, namely miR-520f, miR-1261, miR-1270, miR-620, miR-188-3p, miR-516b, miR-940 and miR-661, were identified with potential binding sites for these three circRNAs. Subsequently, 232 overlapped genes from the 795 upregulated genes in the LAC samples from The Cancer Genome Atlas database and 7,829 predicted target genes of the list of eight aforementioned miRNAs were obtained. A circRNA-miRNA-mRNA network was then constructed. A PPI network was established, with six hub genes, namely kinesin family member (KIF) 2C, KIF18B, maternal embryonic leucine zipper kinase, baculoviral IAP repeat-containing 5, polo-like kinase 1 and cytoskeleton-associated protein 2-like, determined from this network. Higher expression levels of each of these hub genes were found to be associated with poorer prognoses of patients with LAC. To conclude, data from the present study suggested that circRNAs hsa_circ_0006220, hsa_circ_0072088 and hsa_circ_0001666 have the potential to be viable biomarkers and therapeutic targets for LAC.

Characterization of Kinesin Family Member 2C as a Proto-Oncogene in Cervical Cancer

Kinesin family member 2C (KIF2C) is known as an oncogenic gene to regulate tumor progression and metastasis. However, its pan-cancer analysis has not been reported. In this study, we comprehensively analyzed the characteristics of KIF2C in various cancers. We found that KIF2C was highly expressed and corresponded to a poor prognosis in various cancers. We also found a significant correlation between KIF2C and clinicopathological characteristics, particularly in cervical cancer, which is the most common gynecological malignancy and is the second leading cause of cancer-related deaths among women worldwide. KIF2C mutation is strongly associated with the survival rate of cervical cancer, and KIF2C expression was significantly upregulated in cervical cancer tissues and cervical cancer cells. Moreover, KIF2C promoted cervical cancer cells proliferation, invasion, and migration in vitro and as well increased tumor growth in vivo. KIF2C knockdown promotes the activation of the p53 signaling pathway by regulating the expression of related proteins. The rescue assay with KIF2C and p53 double knockdown partially reversed the inhibitory influence of KIF2C silencing on cervical cancer processes. In summary, our study provided a relatively comprehensive description of KIF2C as an oncogenic gene and suggested KIF2C as a therapeutic target for cervical cancer.

Identification of HMMR as a prognostic biomarker for patients with lung adenocarcinoma via integrated bioinformatics analysis

Background

Lung adenocarcinoma (LUAD) is the most prevalent tumor in lung carcinoma cases and threatens human life seriously worldwide. Here we attempt to identify a prognostic biomarker and potential therapeutic target for LUAD patients.

Methods

Differentially expressed genes (DEGs) shared by GSE18842, GSE75037, GSE101929 and GSE19188 profiles were determined and used for protein-protein interaction analysis, enrichment analysis and clinical correlation analysis to search for the core gene, whose expression was further validated in multiple databases and LUAD cells (A549 and PC-9) by quantitative real-time PCR (qRT-PCR) and western blot analyses. Its prognostic value was estimated using the Kaplan-Meier method, meta-analysis and Cox regression analysis based on the Cancer Genome Atlas (TCGA) dataset and co-expression analysis was conducted using the Oncomine database. Gene Set Enrichment Analysis (GSEA) was performed to illuminate the potential functions of the core gene.

Results

A total of 115 shared DEGs were found, of which 24 DEGs were identified as candidate hub genes with potential functions associated with cell cycle and FOXM1 transcription factor network. Among these candidates, HMMR was identified as the core gene, which was highly expressed in LUAD as verified by multiple datasets and cell samples. Besides, high HMMR expression was found to independently predict poor survival in patients with LUAD. Co-expression analysis showed that HMMR was closely related to FOXM1 and was mainly involved in cell cycle as suggested by GSEA.

Conclusion

HMMR might be served as an independent prognostic biomarker for LUAD patients, which needs further validation in subsequent studies.

Study on the expression of TOP2A in hepatocellular carcinoma and its relationship with patient prognosis

Background

Hepatocellular carcinoma (HCC) is a primary liver cancer with a high mortality rate. However, the molecular mechanism of HCC formation remains to be explored and studied.

Objective

To investigate the expression of TOP2A in hepatocellular carcinoma (HCC) and its prognosis.

Methods

The data set of hepatocellular carcinoma was downloaded from GEO database for differential gene analysis, and hub gene was identified by Cytoscape. GEPIA was used to verify the expression of HUB gene and evaluate its prognostic value. Then TOP2A was selected as the research object of this paper by combining literature and clinical sample results. Firstly, TIMER database was used to study TOP2A, and the differential expression of TOP2A gene between normal tissues and cancer tissues was analyzed, as well as the correlation between TOP2A gene expression and immune infiltration of HCC cells. Then, the expression of top2a-related antibodies was analyzed using the Human Protein Atlas database, and the differential expression of TOP2A was verified by immunohistochemistry. Then, SRTING database and Cytoscape were used to establish PPI network for TOP2A and protein–protein interaction analysis was performed. The Oncomine database and cBioPortal were used to express and identify TOP2A mutation-related analyses. The expression differences of TOP2A gene were identified by LinkedOmics, and the GO and KEGG pathways were analyzed in combination with related genes. Finally, Kaplan–Meier survival analysis was performed to analyze the clinical and prognosis of HCC patients.

Results

TOP2A may be a new biomarker and therapeutic target for hepatocellular carcinoma.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02439-0.

Circular RNA circ_0010235 sponges miR-338-3p to play oncogenic role in proliferation, migration and invasion of non-small-cell lung cancer cells through modulating KIF2A

BACKGROUND

Circular RNA microarray analysis showed hsa_circ_0010235 (circ_0010235) was highly upregulated in non-small-cell lung cancer (NSCLC) patients; however, its role in carcinogenesis and development of NSCLC cells was unrevealed. Here, we intended to investigate role and mechanism of circ_0010235 in NSCLC proliferation, migration and invasion.

METHODS AND RESULTS

Expression of circ_0010235, microRNA (miR)-338-3p and kinesin family member 2A (KIF2A) was detected by quantitative real-time PCR, western blotting and immunohistochemistry (IHC). Cell progression was measured by cell-counting kit-8 assay, 5-ethynyl-2-deoxyuridine (EdU) assay, flow cytometry, transwell assay, western blotting, IHC and xenograft experiment. The relationship among circ_0010235, miR-338-3p and KIF2A was determined by dual-luciferase reporter assay, RNA immunoprecipitation and Pearson's correlation analysis. Expression of circ_0010235 was increased in human NSCLC tissues and cells, accompanied with miR-338-3p downregulation and KIF2A upregulation. Essentially, circ_0010235 could sponge miR-338-3p via target binding, and miR-338-3p downstream targeted KIF2A. Functionally, exhaustion of circ_0010235 induced apoptosis rate of NSCLC cells and curbed cell viability, EdU incorporation, migration rate and invasion rate, accompanied with higher E-cadherin and lower N-cadherin expression. Additionally, re-expression of miR-338-3p prompted above similar effects in NSCLC cells in vitro. Contrarily, miR-338-3p blockage partially counteract the effects of circ_0010235 exhaustion; plus, restoration of KIF2A could attenuate miR-338-3p role, as well. Notably, interfering circ_0010235 delayed tumour growth of NSCLC cells by promoting miR-338-3p and E-cadherin expression, and depressing KIF2A, ki-67 and N-cadherin expression.

CONCLUSIONS

circ_0010235 could be a novel identified oncogenic circRNA in NSCLC, and targeting miR-338-3p/KIF2A axis was one regulatory mechanism underlying circ_0010235.KEY MESSAGECirc_0010235 was an upregulated circRNA in NSCLC patients and cells.Interfering circ_0010235 restrained NSCLC cell proliferation and metastasis in vitro and in vivo.miR-338-3p per se suppressed NSCLC in vitro and its downregulation diminished the tumour-suppressive role of circ_0010235 blockage in NSCLC cells.miR-338-3p could downstream target KIF2A and be sponged by circ_0010235.

Mitotic Centromere-Associated Kinesin (MCAK/KIF2C) Regulates Cell Migration and Invasion by Modulating Microtubule Dynamics and Focal Adhesion Turnover

The microtubule (MT) cytoskeleton is crucial for cell motility and migration by regulating multiple cellular activities such as transport and endocytosis of key components of focal adhesions (FA). The kinesin-13 family is important in the regulation of MT dynamics and the best characterized member of this family is the mitotic centromere-associated kinesin (MCAK/KIF2C). Interestingly, its overexpression has been reported to be related to increased metastasis in various tumor entities. Moreover, MCAK is involved in the migration and invasion behavior of various cell types. However, the precise molecular mechanisms were not completely clarified. To address these issues, we generated CRISPR/dCas9 HeLa and retinal pigment epithelium (RPE) cell lines overexpressing or downregulating MCAK. Both up- or downregulation of MCAK led to reduced cell motility and poor migration in malignant as well as benign cells. Specifically, it's up- or downregulation impaired FA protein composition and phosphorylation status, interfered with a proper spindle and chromosome segregation, disturbed the assembly and disassembly rate of FA, delayed cell adhesion, and compromised the plus-tip dynamics of MTs. In conclusion, our data suggest MCAK act as an important regulator for cell motility and migration by affecting the actin-MT cytoskeleton dynamics and the FA turnover, providing molecular mechanisms by which deregulated MCAK could promote malignant progression and metastasis of tumor cells.

Laryngeal Squamous Cell Carcinoma: Clinical Significance and Potential Mechanism of Cell Division Cycle 45

Background: Cell division cycle 45 (CDC45) plays an important role in the occurrence and development of numerous carcinomas, but its effect in laryngeal squamous cell carcinoma (LSCC) remains unclear. Materials and Methods: The messenger RNA and protein expression levels of CDC45 in LSCC were evaluated with a t test and the standard mean difference (SMD). The ability of CDC45 expression to distinguish the LSCC was assessed through receiver operating characteristic (ROC) curves. Gene set enrichment analysis (GSEA), protein-protein interaction, public databases, and online tools were used to explore the potential molecular mechanism of CDC45 in LSCC. Results: A high expression of CDC45 was identified in LSCC (SMD = 2.61, 95% confidence interval [1.62-3.61]). Through ROC curves, the expression of CDC45 makes it feasible to distinguish the LSCC group from the non-LSCC counterpart. CDC45 was relevant to the progression-free interval of LSCC patients (log-rank p = 0.03). GSEAs show that CDC45 is related to the cell cycle. CDC45, CDC6, KIF2C, and AURKB were identified as hub genes of LSCC. E2F1 may be the regulatory transcription factor of CDC45. Conclusions: High expression of CDC45 likely demonstrates carcinogenic effects in LSCC, and CDC45 is a potential target in screening and treatment of LSCC.

A Systematic Analysis Identifies Key Regulators Involved in Cell Proliferation and Potential Drugs for the Treatment of Human Lung Adenocarcinoma

Lung adenocarcinoma (LUAD) is one of the most common and malignant cancer types. Abnormal cell proliferation, exemplified by cell cycle and cell division dysregulation, is one of the most prominent hallmarks of cancer and is responsible for recurrence, metastasis, and resistance to cancer therapy. However, LUAD-specific gene regulation and clinical significance remain obscure. Here, by using both tissues and cells from LUAD and normal lung samples, 434 increased and 828 decreased genes of biological significance were detected, including 127 cell cycle-associated genes (95 increased and 32 decreased), 66 cell division-associated genes (56 increased and 10 decreased), and 81 cell proliferation-associated genes (34 increased and 47 decreased). Among them, 12 increased genes (TPX2, CENPF, BUB1, PLK1, KIF2C, AURKB, CDKN3, BUB1B, HMGA2, CDK1, ASPM, and CKS1B) and 2 decreased genes (TACC1 and MYH10) were associated with all the three above processes. Importantly, 2 (CDKN3 and CKS1B) out of the 11 increased genes (except HMGA2) are previously uncharacterized ones in LUAD and can potentially be prognostic markers. Moreover, PLK1 could be a promising therapeutic target for LUAD. Besides, protein–protein interaction network analysis showed that CDK1 and CDC20 were the hub genes, which might play crucial roles in cell proliferation of LUAD. Furthermore, transcriptional regulatory network analysis suggested that the transcription factor E2F1 could be a key regulator in controlling cell proliferation of LUAD via expression modulation of most cell cycle-, cell division-, and cell proliferation-related DEGs. Finally, trichostatin A, hycanthone, vorinostat, and mebeverine were identified as four potential therapeutic agents for LUAD. This work revealed key regulators contributing to cell proliferation in human LUAD and identified four potential therapeutic agents for treatment strategy.

Activation of the TGF-β1/Smad signaling by KIF2C contributes to the malignant phenotype of thyroid carcinoma cells

Kinesin family member 2C (KIF2C) has been identified as a potential oncogene in various types of human cancers; however, the role of KIF2C in thyroid cancer has not yet been elucidated. Quantitative real-time polymerase chain reaction and western blotting were employed for gene expression analysis. Cell Counting Kit-8 and ethynyl-2'-deoxyuridine assays were performed to examine cell proliferation. Cell migration and invasion were assessed by wound-healing and transwell invasion assays. Results showed that KIF2C expression was upregulated in thyroid carcinoma cell lines. In addition, upregulation of KIF2C promoted the proliferation, migration, and invasion of thyroid carcinoma cells, while downregulation of KIF2C exerted the opposite effects. Overexpression of KIF2C induced the activation of transforming growth factor-β1 (TGF-β1)/Smad signaling in thyroid carcinoma cells. However, inhibition of TGF-β1/Smad signaling through silencing TGF-β1 attenuated the promoting effects of KIF2C overexpression on the malignant phenotype of thyroid carcinoma cells. Besides, overexpression of TGF-β1 suppressed the inhibitory effect of KIF2C knockdown on the proliferation and metastasis of thyroid carcinoma cells. In conclusion, our findings demonstrated that KIF2C contributed to the malignant phenotype of thyroid carcinoma cells by inducing the activation of TGF-β1/Smad signaling, thus uncovering a novel mechanism for thyroid carcinoma progression.

KIF2C promotes the proliferation of hepatocellular carcinoma cells in vitro and in vivo

Hepatocellular carcinoma (HCC) is one of the most common malignancies with high mortality and morbidity rates. In recent years, HCC targeted therapy has gained increasing attention. Due to the heterogeneity and high metastasis of HCC, more effective therapeutic targets are needed. Kinesin family member 2C (KIF2C), also known as mitotic centromere-associated kinesin, is a microtubule-based motor protein which is involved in a variety of important cellular processes, such as mitosis. The effects of KIF2C on cancer progression and development have been widely studied; however, its potential effects on HCC remains unclear. In the present study, high expression of KIF2C in human HCC tissues was demonstrated using The Cancer Genome Atlas database and immunohistochemistry assays. KIF2C expression was associated with HCC prognosis, including overall survival and disease-free survival. KIF2C expression was also associated with clinical pathological characteristics including the number of tumor nodes (P=0.015) and tumor size (P=0.009). KIF2C knockdown inhibited the proliferation of HCC cells in vitro, confirmed by MTT and colony formation assays, and suppressed tumor growth in mice which was confirmed by a xenograft mouse model. Together, the results suggested that KIF2C may serve as a promising therapeutic target for the treatment of HCC.

Prognostic value of microRNA-4521 in non-small cell lung cancer and its regulatory effect on tumor progression

Background

Non-small cell lung cancer (NSCLC) is a malignant tumor with the highest mortality rate in our country. It has been found in many studies that microRNA-4521 (miR-4521) is abnormally expressed and plays a role in clear cell renal cell carcinoma and other cancers.

Objective

The purpose of this study was to explore the relationship between miR-4521 expression and clinical prognosis, as well as its influence on cell biological behavior.

Methods

The expression differences of miR-4521 in NSCLC tissues and cells were examined by qRT-PCR technology. Kaplan–Meier survival analysis and Cox regression analysis were used to analyze the clinical information and survival status of patients to explore the relationship. Using the vitro cell MTT assay, Transwell assay, and western-blot analysis, the effects of miR-4521 on cell proliferation, migration, and invasion were analyzed.

Results

The expression of miR-4521 in NSCLC tissues and cells was significantly downregulated. miR-4521 can be used as an independent prognostic factor. The survival rate of the miR-4521 low expression group was lower, which was significantly related to poor prognosis. In addition, the low expression of miR-4521 significantly promoted cell proliferation, migration, and invasion with highly expressed related protein levels. FOXM1 might be a direct target of miR-4521.

Conclusion

The results of this study showed that the low expression of miR-4521 indicated the poor prognosis of NSCLC and promoted cell proliferation, migration, and invasion by targeting FOXM1.

Identification of prognostic markers by weighted gene co-expression network analysis in non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is one of the fatal tumors and is associated with a poor prognosis. Cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT) was used to quantify the proportions of 22 types of immune cells. Weighted gene co-expression network analysis (WGCNA) was established from the GSE37745 data, and key modules correlating most with CD8⁺ T cell infiltration were determined. Genes that manifested a high module connectivity in the key module were identified as hub genes. Three bioinformatics online databases were used to evaluate hub gene expression levels in tumor and normal tissues. Finally, survival analysis was conducted for these hub genes. In this study, we chose four hub genes (AURKB, CDC20, TPX2 and KIF2C) based on the comprehensive bioinformatics analyses. All hub genes were overexpressed in tumor tissue, and high expression of AURKB, CDC20, TPX2, and KIF2C correlated with the poor prognosis of these patients. In vitro experiments confirmed that CDC20 knockdown inhibited cell proliferation and growth. The above results indicated that AURKB, CDC20, TPX2, and KIF2C are potential CD8⁺ T cell infiltration-related biomarkers and therapeutic targets.

[Progress in Single-cell RNA Sequencing of Lung Adenocarcinoma]

肺腺癌（lung adenocarcinoma, LUAD）是临床上肺癌最常见的亚型，是癌症相关死亡最主要的原因之一。过去十几年中，随着薄层计算机断层扫描（computed tomography, CT）广泛用于常规肺癌筛查，影像学上表现为小结节的LUAD发病率显著增高，其发生发展机制复杂，个体预后差异显著。尽管近年来针对LUAD的靶向和免疫疗法取得了重大进展，但肿瘤细胞的耐药性始终未得到有效解决，从而限制了患者获益。随着人类基因组计划的完成，以测序为基本手段的基因组学及转录组学进入临床和科研人员的视野。单细胞测序作为近年来受到高度关注的新型测序手段，与二代测序相比，其能在单细胞水平上对细胞群体进行特异性分析，揭示出每种细胞类型独特的变化，在单细胞水平上对许多异质基质细胞和癌细胞进行较精准地评估，从而揭示了分子成分的复杂性以及与非恶性组织中相应成分的区别。综上，通过单细胞测序深入了解LUAD发生发展机制和肿瘤微环境（tumor microenvironment, TME）的异质性及其耐药性形成机制，从而发现新的治疗靶点是临床医生和基础科学家迫切的需求。本文综合论述了单细胞测序在LUAD中的具体应用和研究进展。

Identification of VWF as a Novel Biomarker in Lung Adenocarcinoma by Comprehensive Analysis

Lung adenocarcinoma (LUAD) is one of the most malignant tumors with high morbidity and mortality worldwide due to the lack of reliable methods for early diagnosis and effective treatment. It’s imperative to study the mechanism of its development and explore new biomarkers for early detection of LUAD. In this study, the Gene Expression Omnibus (GEO) dataset GSE43458 and The Cancer Genome Atlas (TCGA) were used to explore the differential co-expressed genes between LUAD and normal samples. Three hundred sixity-six co-expressed genes were identified by differential gene expression analysis and Weighted Gene Co-expression Network Analysis (WGCNA) method. Those genes were mainly enriched in ameboidal-type cell migration (biological process), collagen-containing extracellular matrix (cell component), and extracellular matrix structure constituent (molecular function). The protein-protein network (PPI) was constructed and 10 hub genes were identified, including IL6, VWF, CDH5, PECAM1, EDN1, BDNF, CAV1, SPP1, TEK, and SELE. The expression level of hub genes was validated in the GEPIA database, compared with normal tissues, VWF is lowly expressed and SPP1 is upregulated in LUAD tissues. The survival analysis showed increased expression of SPP1 indicated unfavorable prognosis whereas high expression of VWF suggested favorable prognosis in LUAD (p < 0.05). Based on the immune infiltration analysis, the relationship between SPP1 and VWF expression and macrophage, neutrophil, and dendritic cell infiltration was weak in LUAD. Quantitative real-time PCR (qRT-PCR) and western blotting were used to validate the expression of VWF and SPP1 in normal human bronchial epithelial (HBE) cell and three LUAD cell lines, H1299, H1975, and A549. Immunohistochemistry (IHC) was further performed to detect the expression of VWF in 10 cases LUAD samples and matched normal tissues. In summary, the data suggest that VWF is a potential novel biomarker for prognosis of LUAD.

A six-long noncoding RNA model predicts prognosis in lung adenocarcinoma

Background

The incidence and mortality of lung cancer rank first among various malignant tumors. The lack of clear molecular classification and effective individualized treatment greatly limits the treatment benefits of patients. Long non-coding RNAs (lncRNAs) have been demonstrated widely involve in tumor progressing, and been proved easy to detect for occupying majority in transcriptome. However, less work focuses on studying the potency of lncRNAs as molecular typing and prognostic indicator in lung cancer.

Methods

Based on the 448 lung adenocarcinoma (LUAD) samples and the expression of 14,127 lncRNAs from the Cancer Genome Atlas (TCGA) database, we constructed a co-expression network using weighted gene co-expression network analysis. Then based on the feature module and the overall survival of patients, we constructed a risk score model through Cox proportional hazards regression and verified it with a validation cohort. Finally, according to the median of risk score, the function of this model was enriched.

Results

We identified a module containing 123 lncRNAs that is related with the prognosis of LUAD. Using univariate and multivariate Cox proportional hazards regression with lasso regression, six lncRNAs were identified to construct a risk score model. The calculation formula shown as follows: risk score = (−0.3057 × EXP_VIM-AS1) + (0.9678 × EXP_AC092811.1) + (1.0829 × EXP_NFIA-AS1) + (−0.3505 × EXP_AL035701.1) + (3.9378 × EXP_AC079336.4) + (−0.2810 × EXP_AL121790.2). Six-lncRNA model can be used as an independent prognostic indicator in LUAD (P<0.001) and the area under the 5-year receiver operating characteristic (ROC) curve is 0.715.

Conclusions

We developed a six-lncRNA model, which could be used for predicting prognosis and guiding medical treatment in LUAD patients.

Integration of gene profile to explore the hub genes of lung adenocarcinoma: A quasi-experimental study

BACKGROUND

Lung cancer is a leading cause of morbidity diseases worldwide, but the key mechanisms of lung cancer remain elusive. This study aims to integrate of GSE 118370 and GSE 32863 profile and identify the key genes and pathway involved in human lung adenocarcinoma.

METHODS

R software (RStudio, Version info: R 3.2.3, Forrester, USA) were utilized to find the differentially expressed genes. All the differentially expressed genes were analyzed by gene ontology, kyoto encyclopedia of genes and genomes. Protein-protein interaction networks were constructed by STRING database and analyzed by Cytohubber and Module. The cancer genome atlas database was used to verification the expression of hub genes. Quantitative reverse transcription-PCR was used to verify the bio-information results.

RESULTS

Sixty-four lung adenocarcinoma and 64 adjacent normal tissues were used for integration analysis. Five hundred ninety-nine co-expression genes were locked. Biological processes mainly enriched in angiogenesis. Cellular component focused on extracellular exosome and molecular function aimed on protein disulfide isomerase activity. Cytohubber analysis showed that GNG11, FPR2, P4HB, PIK3R1, CDC20, ADCY4, TIMP1, IL6, CXC chemokine ligand (CXCL)12, and GAS6 acted as the hub genes during lung adenocarcinoma. Module analysis presented Chemokine signaling pathway was a key pathway. Quantitative reverse transcription-PCR showed that the expression level of GNG11, FPR2, PIK3R1, ADCY4, IL6, CXCL12, and GAS6 were significantly decreased and P4HB, CDC20 and TIMP1 were increased in human adenocarcinoma tissues (P < .05). The cancer genome atlas online analysis showed GNG11 was not associated with survival.

CONCLUSIONS

This study firstly reported GNG11 acting as a hub gene in adenocarcinoma. GNG11 could be used as a biomarker for human adenocarcinoma. Chemokine signaling pathway might play important roles in lung adenocarcinoma.

Proteogenomic Characterization Reveals Therapeutic Vulnerabilities in Lung Adenocarcinoma

To explore the biology of lung adenocarcinoma (LUAD) and identify new therapeutic opportunities, we performed comprehensive proteogenomic characterization of 110 tumors and 101 matched normal adjacent tissues (NATs) incorporating genomics, epigenomics, deep-scale proteomics, phosphoproteomics, and acetylproteomics. Multi-omics clustering revealed four subgroups defined by key driver mutations, country, and gender. Proteomic and phosphoproteomic data illuminated biology downstream of copy number aberrations, somatic mutations, and fusions and identified therapeutic vulnerabilities associated with driver events involving KRAS, EGFR, and ALK. Immune subtyping revealed a complex landscape, reinforced the association of STK11 with immune-cold behavior, and underscored a potential immunosuppressive role of neutrophil degranulation. Smoking-associated LUADs showed correlation with other environmental exposure signatures and a field effect in NATs. Matched NATs allowed identification of differentially expressed proteins with potential diagnostic and therapeutic utility. This proteogenomics dataset represents a unique public resource for researchers and clinicians seeking to better understand and treat lung adenocarcinomas.

Functional characterization of MCAK/Kif2C cancer mutations using high-throughput microscopic analysis

The microtubule (MT)-depolymerizing activity of MCAK/Kif2C can be quantified by expressing the motor in cultured cells and measuring tubulin fluorescence levels after enough hours have passed to allow tubulin autoregulation to proceed. This method allows us to score the impact of point mutations within the motor domain. We found that, despite their distinctly different activities, many mutations that impact transport kinesins also impair MCAK/Kif2C's depolymerizing activity. We improved our workflow using CellProfiler to significantly speed up the imaging and analysis of transfected cells. This allowed us to rapidly interrogate a number of MCAK/Kif2C motor domain mutations documented in the cancer database cBioPortal. We found that a large proportion of these mutations adversely impact the motor. Using green fluorescent protein-FKBP-MCAK CRISPR cells we found that one deleterious hot-spot mutation increased chromosome instability in a wild-type (WT) background, suggesting that such mutants have the potential to promote tumor karyotype evolution. We also found that increasing WT MCAK/Kif2C protein levels over that of endogenous MCAK/Kif2C similarly increased chromosome instability. Thus, endogenous MCAK/Kif2C activity in normal cells is tuned to a mean level to achieve maximal suppression of chromosome instability.

Identification of core biomarkers associated with pathogenesis and prognostic outcomes of laryngeal squamous-cell cancer using bioinformatics analysis

PURPOSE

Despite advances in the treatment of laryngeal squamous-cell carcinoma (LSCC), the survival rate of LSCC remains poor. Thereby, it is urgent to identify novel diagnostic and prognostic biomarkers for LSCC. The study aimed to identify potential core genes associated with the pathogenesis and prognosis of LSCC.

METHODS

Differentially expressed genes between LSCC and normal laryngeal tissue samples were screened by an integrated analysis of data from GEO and TCGA databases. Core genes related to the pathogenesis and prognosis of LSCC were identified by employing protein-protein interaction network and Cox proportional hazards model analyses.

RESULTS

Ten hub genes (AURKA, AURKB, CDC45, KIF2C, NDC80, EXO1, TYMS, RAD51AP1, ITGA3, and UBE2T) that might be highly related to the pathogenesis of LSCC were identified. An eight-gene prognostic signature consisted of ZG16B, STATH, RTN4R, MSRA, CBX8, SLC5A1, EFNB1 and CNTFR was constructed with a good performance in predicting overall survivals.

CONCLUSION

Our findings might shed some new light on the pathogenesis of LSCC and help identify new therapeutic targets of LSCC.

Identification of Key Biomarkers in Bladder Cancer: Evidence from a Bioinformatics Analysis

Bladder cancer (BCa) is one of the most common malignancies and has a relatively poor outcome worldwide. However, the molecular mechanisms and processes of BCa development and progression remain poorly understood. Therefore, the present study aimed to identify candidate genes in the carcinogenesis and progression of BCa. Five GEO datasets and TCGA-BLCA datasets were analyzed by statistical software R, FUNRICH, Cytoscape, and online instruments to identify differentially expressed genes (DEGs), to construct protein‒protein interaction networks (PPIs) and perform functional enrichment analysis and survival analyses. In total, we found 418 DEGs. We found 14 hub genes, and gene ontology (GO) analysis revealed DEG enrichment in networks and pathways related to cell cycle and proliferation, but also in cell movement, receptor signaling, and viral carcinogenesis. Compared with noncancerous tissues, TPM1, CRYAB, and CASQ2 were significantly downregulated in BCa, and the other hub genes were significant upregulated. Furthermore, MAD2L1 and CASQ2 potentially play a pivotal role in lymph nodal metastasis. CRYAB and CASQ2 were both significantly correlated with overall survival (OS) and disease-free survival (DFS). The present study highlights an up to now unrecognized possible role of CASQ2 in cancer (BCa). Furthermore, CRYAB has never been described in BCa, but our study suggests that it may also be a candidate biomarker in BCa.

Identification of prognostic markers of lung cancer through bioinformatics analysis and in vitro experiments

Lung cancer is one of the most common types of cancer worldwide. Understanding the molecular mechanisms underlying the development and progression of lung cancer may improve early diagnosis, treatment and prognosis. The aim of the present study was to examine the pathogenesis of lung cancer and to identify potentially novel biomarkers. Gene expression datasets of patients with lung cancer were obtained from the Gene Expression Omnibus. Genes which were most closely associated with lung cancer (core genes) were screened by weighted gene co‑expression network analysis. In vitro cell based experiments were further utilized to verify the effects of the core genes on the proliferation of lung cancer cells, adhesion between cells and the matrix, and the associated metabolic pathways. Based on WGCNA screening, two gene modules and five core genes closely associated with lung cancer, including immunoglobulin superfamily member 10 (IGSF10) from the turquoise module, and ribonucleotide reductase regulatory subunit M2, protein regulator of cytokinesis 1, kinesin family member (KIF)14 and KIF2C from the brown module were identified as relevant. Survival analysis and differential gene expression analysis showed that there were significant differences in IGSF10 expression levels between the healthy controls and patients with lung cancer. In patients with lung cancer, IGSF10 expression was decreased, and the overall survival time of patients with lung cancer was significantly shortened. An MTT and colony formation assay showed that IGSF10‑knockout significantly increased proliferation of lung cancer cells, and Transwell assays and adhesion experiments further suggested that the adhesion between cells and the matrix was significantly increased in IGSF10‑knockout cells. Gene Set Enrichment Analysis showed that the expression level of IGSF10 was significantly associated with the activation of the integrin‑β1/focal adhesion kinase (FAK) pathway. Western blotting revealed that knockout of IGSF10 resulted in the activation of the integrin‑β1/FAK pathway, as the protein expression levels of integrin‑β1, phosphorylated (p)‑FAK and p‑AKT were significantly upregulated. Activation of the integrin‑β1/FAK pathway, following knockout of IGSF10, affected the proliferation and adhesion of lung cancer cells. Therefore, IGSF10 my serve as a potential prognostic marker of lung cancer.

Joint Transcriptomic Analysis of Lung Cancer and Other Lung Diseases

Background: Epidemiological and clinical evidence points cancer comorbidity with pulmonary chronic disease. The acquisition of some hallmarks of cancer by cells affected with lung pathologies as a cell adaptive mechanism to a shear stress, suggests that could be associated with the establishment of tumoral processes. Objective: To propose a bioinformatic pipeline for the identification of all deregulated genes and the transcriptional regulators (TFs) that are coexpressed during lung cancer establishment, and therefore could be important for the acquisition of the hallmarks of cancer. Methods: Ten microarray datasets (six of lung cancer, four of lung diseases) comparing normal and diseases-related lung tissue were selected to identify hub differentiated expressed genes (DEGs) in common between lung pathologies and lung cancer, along with transcriptional regulators through the utilization of specialized libraries from R language. DAVID bioinformatics tool for gene enrichment analyses was used to identify genes with experimental evidence associated to tumoral processes and signaling pathways. Coexpression networks of DEGs and TFs in lung cancer establishment were created with Coexnet library, and a survival analysis of the main hub genes was made. Results: Two hundred ten DEGs were identified in common between lung cancer and other lung diseases related to the acquisition of tumoral characteristics, which are coexpressed in a lung cancer network with TFs, suggesting that could be related to the establishment of the tumoral pathology in lung. The comparison of the coexpression networks of lung cancer and other lung diseases allowed the identification of common connectivity patterns (CCPs) with DEGs and TFs correlated to important tumoral processes and signaling pathways, that haven´t been studied to experimentally validate their role in the early stages of lung cancer. Some of the TFs identified showed a correlation between its expression levels and the survival of lung cancer patients. Conclusion: Our findings indicate that lung diseases share genes with lung cancer which are coexpressed in lung cancer, and might be able to explain the epidemiological observations that point to direct and inverse comorbid associations between some chronic lung diseases and lung cancer and represent a complex transcriptomic scenario.

Biomarker expression analysis in different age groups revealed age was a risk factor for breast cancer

The relationship between age and breast cancer is ambiguous. Here, we analyzed the differential expression pattern of long noncoding RNAs (lncRNAs) and messenger RNAs (mRNAs) in different age groups to provide an effective association between age and breast cancer risk at the molecular level. We integrated the microarray information from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) data sets. The patients were divided into young ( < 50 years) and old ( ≥ 50 years) age groups and evaluated by differential gene expression, weighted gene correlation network analysis (WGCNA), functional enrichment analyses, and coexpression analysis. To determine their potential clinical significance, univariate Cox regression analysis and survival assessment were conducted. We identified two lncRNAs (AL139280.1 and AP000851.1) and three mRNAs (MT1M, HBB, and TFPI2) as the risk markers, and Gene set enrichment analysis (GSEA) focusing on a single gene revealed that "pyrimidine metabolism," "cell cycle," and "P53 signaling pathway" were coenriched. These data demonstrated that age may be a risk factor for breast carcinogenesis and prognosis and provide an in-depth molecular characterization based on the expression patterns of lncRNAs and mRNAs.

Identification of five hub genes as monitoring biomarkers for breast cancer metastasis in silico

BACKGROUND

Breast cancer is one of the most common endocrine cancers among females worldwide. Distant metastasis of breast cancer is causing an increasing number of breast cancer-related deaths. However, the potential mechanisms of metastasis and candidate biomarkers remain to be further explored.

RESULTS

The gene expression profiles of GSE102484 were downloaded from the Gene Expression Omnibus (GEO) database. Weighted gene co-expression network analysis (WGCNA) was used to screen for the most potent gene modules associated with the metastatic risk of breast cancer, and a total of 12 modules were identified based on the analysis. In the most significant module (R2 = 0.68), 21 network hub genes (MM > 0.90) were retained for further analyses. Next, protein-protein interaction (PPI) networks were used to further explore the biomarkers with the most interactions in gene modules. According to the PPI networks, five hub genes (TPX2, KIF2C, CDCA8, BUB1B, and CCNA2) were identified as key genes associated with breast cancer progression. Furthermore, the prognostic value and differential expression of these genes were validated based on data from The Cancer Genome Atlas (TCGA) and Kaplan-Meier (KM) Plotter. Receiver operating characteristic (ROC) curve analysis revealed that the mRNA expression levels of these five hub genes showed excellent diagnostic value for breast cancer and adjacent tissues. Moreover, these five hub genes were significantly associated with worse distant metastasis-free survival (DMFS) in the patient cohort based on KM Plotter.

CONCLUSION

Five hub genes (TPX2, KIF2C, CDCA8, BUB1B, and CCNA2) associated with the risk of distant metastasis were extracted for further research, which might be used as biomarkers to predict distant metastasis of breast cancer.