Translating bioinformatics in oncology: guilt-by-profiling analysis and identification of KIF18B and CDCA3 as novel driver genes in carcinogenesis

CDCA gene family promotes progression and prognosis in lung adenocarcinoma

BACKGROUND

The cell division cycle-associated (CDCA) family participates in the cell cycle, and the dysregulation of its expression is associated with the development of several types of cancers. However, the roles of CDCAs in lung adenocarcinomas (LUAD) have not been investigated in systematic research.

METHODS

Using data retrieved from The Cancer Genome Atlas (TCGA), the expression of CDCAs in LUAD and normal tissues was compared, and survival analysis was performed using the data. Also, the correlation between clinical characteristics and the expression of CDCAs was assessed. Using data from cBioPortal, we investigated genetic alterations in CDCAs and their prognostic implications. Immunohistochemical analyses were performed to validate our findings from TCGA data. Following this, we created a risk score model to develop a nomogram. We also performed gene set enrichment analyses (GSEA), gene ontology, and KEGG pathway analysis. We used Timer to analyze the correlation between immune cell infiltration, tumor purity, and expression data.

RESULTS

Our results indicated that all CDCAs were expressed at high levels in LUAD; this could be associated with poor overall survival, as indicated in TCGA data. Univariate and multivariate Cox analyses revealed that CDCA4/5 could serve as independent risk factors. The results of immunohistochemical analyses confirmed our results. Based on the estimation of expression levels, clinical characteristics, alterations, and immune infiltration, the low-risk group of CDCA4/5 had a better prognosis than the high-risk group. Immune therapy is also a potential treatment option.

CONCLUSION

In conclusion, our findings indicate that CDCAs play important roles in LUAD, and CDCA4/5 can serve as diagnostic and prognostic biomarkers and therapeutic targets in LUAD.

Identification of the hub genes linked to zearalenone-induced hepatotoxicity in broiler chickens

Zearalenone (ZEN) is a mycotoxin found in food and feed that impairs the function of multiple organs, especially the liver. However, the specific mechanisms through which ZEN induces liver damage in broiler chickens are not well understood. Therefore, this study aimed to identify the key genes linked to the hepatotoxicity induced by ZEN exposure in broiler chickens. Gene expression data from ZEN-treated and control chicken embryo primary hepatocytes (CEPHs) were used to implement differential expression analysis. Totally, 436 differentially expressed genes (DEGs) were detected, in which 223 and 213 genes were up- and down-regulated in ZEN-treated CEPHs, respectively. Gene ontology analysis suggested that these DEGs were involved in various biological processes, including chromosome segregation, mitotic cytokinesis, mitotic cell cycle, cell division, and mitotic spindle organization. Pathway analysis showed that the DEGs were associated with p53, FoxO, ubiquitin-mediated proteolysis, cell cycle, and mismatch repair signaling pathways. Furthermore, the hub genes, including BRCA1, CDC45, CDCA3, CDKN3, CENPE, CENPF, CENPI, CENPM, CENPU, and CEP55, potentially contributed to ZEN-induced hepatotoxicity. In conclusion, our study provides the valuable insight into the mechanism underlying ZEN-induced hepatotoxicity in broiler chickens.

The role of kinesin family members in hepatobiliary carcinomas: from bench to bedside

As a major component of the digestive system malignancies, tumors originating from the hepatic and biliary ducts seriously endanger public health. The kinesins (KIFs) are molecular motors that enable the microtubule-dependent intracellular trafficking necessary for mitosis and meiosis. Normally, the stability of KIFs is essential to maintain cell proliferation and genetic homeostasis. However, aberrant KIFs activity may destroy this dynamic stability, leading to uncontrolled cell division and tumor initiation. In this work, we have made an integral summarization of the specific roles of KIFs in hepatocellular and biliary duct carcinogenesis, referring to aberrant signal transduction and the potential for prognostic evaluation. Additionally, current clinical applications of KIFs-targeted inhibitors have also been discussed, including their efficacy advantages, relationship with drug sensitivity or resistance, the feasibility of combination chemotherapy or other targeted agents, as well as the corresponding clinical trials. In conclusion, the abnormally activated KIFs participate in the regulation of tumor progression via a diverse range of mechanisms and are closely associated with tumor prognosis. Meanwhile, KIFs-aimed inhibitors also carry out a promising tumor-targeted therapeutic strategy that deserves to be further investigated in hepatobiliary carcinoma (HBC).

CDCA3 promotes the proliferation and migration of hypopharyngeal squamous cell carcinoma cells by activating the Akt/mTOR pathway

Hypopharyngeal squamous cell carcinoma (HSCC) is a highly invasive and fatal tumor with a poor prognosis in head and neck tumors. It is urgent to further study the molecular mechanism of HSCC progression and identify new effective therapeutic targets. Cell division cycle-related protein 3 (CDCA3) was reported overexpressed in several cancers and involved in tumor progression. However, the biological role of CDCA3 and its potential mechanism in HSCC remain undetermined. Reverse transcription quantitative polymerase chain reaction (RT-PCR) and immunohistochemistry were used to detect the expression levels of CDCA3 in HSCC tissue and matched peritumoral tissue. The effects of CDCA3 on cell proliferation, invasion, and migration were explored using the Celigo image cytometry assay, MTT assay, flow cytometric analysis, cell invasion, and migration assays. The results showed that CDCA3 was upregulated in HSCC tissue and FaDu cell line. Knockdown of CDCA3 inhibited the proliferation, invasion, and migration of FaDu cells and promoted apoptosis of FaDu cells. Furthermore, knockdown of CDCA3 blocked the cell cycle in the G0/G1 phase. Mechanistically, CDCA3 may play a role in tumor progression of HSCC through the Akt/mTOR signaling pathway. In summary, these results suggest that CDCA3 serves as an oncogene in HSCC and may be used as a prognostic indicator and a potential therapeutic target for HSCC.

Integrative Histology-Genomic Analysis Predicts Hepatocellular Carcinoma Prognosis Using Deep Learning

Cancer prognosis analysis is of essential interest in clinical practice. In order to explore the prognostic power of computational histopathology and genomics, this paper constructs a multi-modality prognostic model for survival prediction. We collected 346 patients diagnosed with hepatocellular carcinoma (HCC) from The Cancer Genome Atlas (TCGA), each patient has 1-3 whole slide images (WSIs) and an mRNA expression file. WSIs were processed by a multi-instance deep learning model to obtain the patient-level survival risk scores; mRNA expression data were processed by weighted gene co-expression network analysis (WGCNA), and the top hub genes of each module were extracted as risk factors. Information from two modalities was integrated by Cox proportional hazard model to predict patient outcomes. The overall survival predictions of the multi-modality model (Concordance index (C-index): 0.746, 95% confidence interval (CI): ±0.077) outperformed these based on histopathology risk score or hub genes, respectively. Furthermore, in the prediction of 1-year and 3-year survival, the area under curve of the model achieved 0.816 and 0.810. In conclusion, this paper provides an effective workflow for multi-modality prognosis of HCC, the integration of histopathology and genomic information has the potential to assist clinical prognosis management.

Upregulation of KIF18B facilitates malignant phenotype of esophageal squamous cell carcinoma by activating CDCA8/mTORC1 pathway

Background

Kinesin family member 18B (KIF18B) has been regarded as an oncogene that is abnormally overexpressed in some cancers, but its mechanism in esophageal squamous cell carcinoma (ESCC) remains unclear, which is thereby investigated in this study.

Methods

Bioinformatics analysis was performed to analyze the expression of KIF18B in esophageal carcinoma (ESCA). Quantitative real‐time polymerase chain reaction (qRT‐PCR) was used to detect KIF18B expression in ESCC cells. After KIF18B overexpression or cell division cycle associated 8 (CDCA8) deficiency, ESCC cells were subjected to determination of qRT‐PCR, Western blot, cell counting kit‐8 assay, flow cytometry, wound healing, and Transwell assay. The mechanism of KIF18B in the mechanistic target of rapamycin complex 1 (mTORC1) pathway was detected by Western blot.

Results

KIF18B was overexpressed in ESCA samples and ESCC cells. Upregulation of KIF18B enhanced the viability, accelerated cell cycle by elevating CDK4 and Cyclin D3 levels as well as promoted the migration and invasion by decreasing E‐cadherin level and increasing Vimentin and N‐cadherin levels in ESCC cells, which was counteracted by CDCA8 silencing. The expression of CDCA8 in ESCC cells was upregulated by KIF18B overexpression. KIF18B overexpression activated the mTORC1 pathway by upregulating phosphorylated (p)‐/p70S6K and p‐/mTOR levels in the ESCC cells, which was reversed by CDCA8 silencing.

Conclusion

KIF18B overexpression promotes the proliferation, migration, and invasion of ESCC cells via CDCA8‐mediated mTORC1 signaling pathway in vitro.

Cell Division Cycle-Associated Protein 3 (CDCA3) Is a Potential Biomarker for Clinical Prognosis and Immunotherapy in Pan-Cancer

CDCA3 is an essential regulator in cell mitosis and can regulate many physiological and pathological processes in the human body by stimulating certain proteins such as cell cycle regulatory proteins, transcription factors, and signal transduction molecules. Although several studies have shown that dysregulation of CDCA3 is a common phenomenon in human cancers, no systematic pan-cancer analysis has been performed. In this study, we comprehensively investigated the role of CDCA3 in 33 human cancer types by utilizing multiple cancer-related databases and bioinformatics analysis tools, including TCGA, GTEx, GEPIA, TIMER, STRING, Metascape, and Cytoscape. Evidence from bioinformatics databases shows that CDCA3 is overexpressed in almost all human cancer types, and its overexpression is significantly associated with survival in patients with more than ten cancer types. CDCA3 expression positively correlates with immune cell infiltration levels in multiple human cancer types. Furthermore, the results of the GSEA analysis revealed that overexpression of CDCA3 may promote the malignant progression of cancer by activating various oncogenic signaling pathways in human cancers. In conclusion, our pan-cancer analysis provides a comprehensive overview of the oncogenic role of CDCA3 in multiple human cancer types, suggesting that CDCA3 may serve as a potential therapeutic target and prognostic biomarker in multiple human cancer types.

Prognostic value of CDCA3 in kidney renal papillary cell carcinoma

Kidney renal papillary cell carcinoma (KIRP) is a type of low-grade malignant renal cell carcinoma. Huge challenges remain in the treatment of KIRP. Cell division cycle associated 3 (CDCA3) participates in human physiological and pathological processes. However, its role in KIRP has not been established. Here, we evaluated the prognostic value of CDCA3 in KIRP using a comprehensive bioinformatics approach. Data for CDCA3 expression in KIRP were obtained from online database. Different expression genes between high and low CDCA3 expression groups were identified and evaluated by performing Gene ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses. A gene set enrichment analysis was performed to elucidate the function and pathway differences between the different. Differences in immune cell infiltration between low and high CDCA3 expression groups were analyzed by a single-sample GSEA method for immune cells. A protein-protein interaction network was generated and hub genes were identified. UALCAN was used to analyze associations between the mRNA expression levels of CDCA3 in KIRP tissues with clinicopathologic parameters. The diagnostic efficacy of CDCA3 for KIRP was analyzed by ROC analysis. Logistic regression was used to analyze relationships between the clinicopathological characteristics and CDCA3 expression. Our results indicated that high CDCA3 mRNA expression is significantly associated with some clinicopathologic parameters in KIRP patients High CDCA3 mRNA expression associated with a shorter overall survival, progression-free interval, and disease-special survival. Taken together, CDCA3 is a potential target for the development of anti-KIRP therapeutics and is an efficient prognostic marker.

KIF18B promotes tumor progression in osteosarcoma by activating β-catenin

Objective: Osteosarcoma is a common primary highly malignant bone tumor. Kinesin family member 18B (KIF18B) has been identified as a potential oncogene involved in the development and metastasis of several cancer types. While KIF18B overexpression in osteosarcoma tissue is clearly detected, its specific function in the disease process remains to be established.

Methods:KIF18B expression was assessed in osteosarcoma tissues and cells. We additionally evaluated the effects of KIF18B on proliferation, migration, and invasion of osteosarcoma cells, both in vitro and in vivo.

Results: Our results showed overexpression of KIF18B in osteosarcoma tissues and cells. Knockdown of KIF18B induced G1/S phase arrest and significantly inhibited proliferation, migration, and invasion of osteosarcoma cells, both in vitro and in vivo. KIF18B regulated β-catenin expression at the transcriptional level by controlling nuclear aggregation of ATF2 and at the post-transcriptional level by interacting with the adenomatous polyposis coli (APC) tumor suppressor gene in osteosarcoma cells.

Conclusions: KIF18B plays a carcinogenic role in osteosarcoma by regulating expression of β-catenin transcriptionally via decreasing nuclear aggregation of ATF2 or post-transcriptionally through interactions with APC. Our collective findings support the potential utility of KIF18B as a novel prognostic biomarker for osteosarcoma.

Silencing of KIF18B restricts proliferation and invasion and enhances the chemosensitivity of breast cancer via modulating Akt/GSK-3β/β-catenin pathway

Kinesin family member 18B (KIF18B) is a new tumor-associated protein that contributes to the carcinogenesis of multiple malignancies. However, the detailed relevance of KIF18B in breast cancer has not been fully elucidated. This work aimed was to evaluate a possible relationship between KIF18B and breast cancer progression. Our findings show KIF18B is increased in breast cancer and demonstrate that high KIF18B level predicts a reduced survival rate. Cellular functional studies revealed that knockdown of KIF18B markedly reduces the proliferation, invasion, and epithelial-mesenchymal transition of breast cancer cells and enhances their chemosensitivity toward doxorubicin. Further studies showed that KIF18B modulates the level of phospho-Akt, phospho-glycogen synthase kinase-3β, and β-catenin. Notably, suppression of Akt abolished KIF18B-overexpression-induced increases in activation of Wnt/β-catenin pathway. In addition, re-expression of β-catenin reversed KIF18B-silencing-induced cancer-promoting effect. In vivo animal experiments elucidated that knockdown of KIF18B significantly weakened the tumorigenicity of breast cancer cells. Taken together, data of this study illustrate that KIF18B exerts a potential cancer-promoting function in breast cancer via enhancement of Wnt/β-catenin pathway through modulation of the Akt/GSK-3β axis.

KIF18B as a regulator in tumor microenvironment accelerates tumor progression and triggers poor outcome in hepatocellular carcinoma

BACKGROUND

The tumor microenvironment plays an important role in the progression and recurrence of tumors and immunotherapy outcomes. The use of immune checkpoint blockers to improve the overall survival rate of patients with advanced hepatocellular carcinoma has yielded inconsistent outcomes. We examined the tumor microenvironment-related genes for their clinical significance and biological functions in hepatocellular carcinoma.

METHODS

Bioinformatic analysis was performed to screen the differentially expressed genes and to identify the core gene of the tumor microenvironment in hepatocellular carcinoma. The expression of KIF18B in hepatocellular carcinoma cell lines and tumor samples was determined using western blotting, quantitative real-time polymerase chain reaction, and immunohistochemistry. The malignancy-promoting ability of KIF18B was evaluated using Cell Counting Kit-8, colony formation, cell proliferation, migration and invasion, and xenograft tumor assays.

RESULTS

KIF18B was identified as one of the core genes in the hepatocellular carcinoma microenvironment and was significantly associated with infiltrating immune cell subtypes and tumor cell stemness. Upregulation of KIF18B was associated with poor clinicopathological characteristics and poor patient outcomes; its downregulation inhibited the proliferation ability of hepatocellular carcinoma cells, which was consistent with the findings of in vivo experiments. Knockdown of KIF18B inhibited epithelial-mesenchymal transition which reduced the migration and invasion abilities of tumor cells. A pulmonary metastasis model confirmed that the downregulation of KIF18B inhibited hepatocellular carcinoma cell metastasis in vivo.

CONCLUSION

KIF18B could be a useful marker for determining the treatment outcomes of immune checkpoint blockers in the context of hepatocellular carcinoma.

Kinesin family member 18B regulates the proliferation and invasion of human prostate cancer cells

Expression of kinesin family member 18B (KIF18B), an ATPase with key roles in cell division, is deregulated in many cancers, but its involvement in prostate cancer (PCa) is unclear. Here, we investigated the expression and function of KIF18B in human PCa specimens and cell lines using bioinformatics analyses, immunohistochemical and immunofluorescence microscopy, and RT-qPCR and western blot analyses. KIF18B was overexpressed in PCa specimens compared with paracancerous tissues and was associated with poorer disease-free survival. In vitro, KIF18B knockdown in PCa cell lines promoted cell proliferation, migration, and invasion, and inhibited cell apoptosis, while KIF18B overexpression had the opposite effects. In a mouse xenograft model, KIF18B overexpression accelerated and promoted the growth of PCa tumors. Bioinformatics analysis of control and KIF18B-overexpressing PCa cells showed that genes involved in the PI3K-AKT-mTOR signaling pathway were significantly enriched among the differentially expressed genes. Consistent with this observation, we found that KIF18B overexpression activates the PI3K-AKT-mTOR signaling pathway in PCa cells both in vitro and in vivo. Collectively, our results suggest that KIF18B plays a crucial role in PCa via activation of the PI3K-AKT-mTOR signaling pathway, and raise the possibility that KIF18B could have utility as a novel biomarker for PCa.

Prognostic Cancer Gene Expression Signatures: Current Status and Challenges

Current staging systems of cancer are mainly based on the anatomical extent of disease. They need refinement by biological parameters to improve stratification of patients for tumor therapy or surveillance strategies. Thanks to developments in genomic, transcriptomic, and big-data technologies, we are now able to explore molecular characteristics of tumors in detail and determine their clinical relevance. This has led to numerous prognostic and predictive gene expression signatures that have the potential to establish a classification of tumor subgroups by biological determinants. However, only a few gene signatures have reached the stage of clinical implementation so far. In this review article, we summarize the current status, and present and future challenges of prognostic gene signatures in three relevant cancer entities: breast cancer, colorectal cancer, and hepatocellular carcinoma.

Kinesin Superfamily Member 18B (KIF18B) Promotes Cell Proliferation in Colon Adenocarcinoma

BACKGROUND

The role of kinesin superfamily proteins (KIFs) has been reported in a variety of tumors and KIFs contributed to the proliferation of cancer cells. But few studies were focus on colon adenocarcinoma.

METHODS

Through bioinformatics analysis and immunohistochemistry (IHC) assays, the expression of KIF18B in colon adenocarcinoma tissues was determined. Stable KIF18B-depleted cell lines were constructed using lentivirus-mediated shRNA of KIF18B. Cell colony formation assay and CCK8 assay were performed to assess cell proliferation degree, and the expression level of KI67 and PCNA was used to indicate cell proliferation in vitro and verified using xenograft tumors in vivo.

RESULTS

KIF18B is highly expressed in colon adenocarcinoma tissues and has a negative correlation with the prognosis and tumor grade of colon adenocarcinoma. Interfering with KIF18B inhibits cell proliferation in vitro and in vivo.

CONCLUSION

KIF18B can be used as a prognostic marker for colon adenocarcinoma and may be a therapeutic target for colon adenocarcinoma treatment.

Circ_0001421 facilitates glycolysis and lung cancer development by regulating miR-4677-3p/CDCA3

BACKGROUND

Lung cancer (LC) is a malignant tumor originating in the bronchial mucosa or gland of the lung. Circular RNAs (circRNAs) are proved to be key regulators of tumor progression. However, the regulatory effect of circ_0001421 on lung cancer tumorigenesis remains unclear.

METHODS

The expression levels of circ_0001421, microRNA-4677-3p (miR-4677-3p) and cell division cycle associated 3 (CDCA3) were detected by quantitative real-time polymerase chain reaction (qRT-PCR). Methyl thiazolyl tetrazolium (MTT), Transwell and Tumor formation assays were performed to explore the role of circ_0001421 in LC. Glucose consumption and lactate production were examined by a Glucose assay kit and a Lactic Acid assay kit. Western blot was utilized to examine the protein levels of Hexokinase 2 (HK2) and CDCA3. The interaction between miR-4677-3p and circ_0001421 or CDCA3 was confirmed by dual-luciferase reporter assay.

RESULTS

Circ_0001421 was increased in LC tissues and cells, and knockdown of circ_0001421 repressed cell proliferation, migration, invasion and glycolysis in vitro. Meanwhile, circ_0001421 knockdown inhibited LC tumor growth in vivo. Mechanistically, circ_0001421 could bind to miR-4677-3p, and CDCA3 was a target of miR-4677-3p. Rescue assays manifested that silencing miR-4677-3p or CDCA3 overexpression reversed circ_0001421 knockdown-mediated suppression on cell proliferation, migration, invasion and glycolysis in LC cells.

CONCLUSION

Circ_0001421 promoted cell proliferation, migration, invasion and glycolysis in LC by regulating the miR-4677-3p/CDCA3 axis, which providing a new mechanism for LC tumor progression.

Silencing KIF18B enhances radiosensitivity: identification of a promising therapeutic target in sarcoma

Background

Sarcomas are rare heterogeneous tumours, derived from primitive mesenchymal stem cells, with more than 100 distinct subtypes. Radioresistance remains a major clinical challenge for sarcomas, demanding urgent for effective biomarkers of radiosensitivity.

Methods

The radiosensitive gene Kinesin family member 18B (KIF18B) was mined through bioinformatics with integrating of 15 Gene Expression Omnibus (GEO) datasets and The Cancer Genome Atlas (TCGA) database. We used radiotherapy-sh-KIF18B combination to observe the anti-tumour effect in sarcoma cells and subcutaneous or orthotopic xenograft models. The KIF18B-sensitive drug T0901317 (T09) was further mined to act as radiosensitizer using the Genomics of Drug Sensitivity in Cancer (GDSC) database.

Findings

KIF18B mRNA was significantly up-regulated in most of the subtypes of bone and soft tissue sarcoma. Multivariate Cox regression analysis showed that KIF18B high expression was an independent risk factor for prognosis in sarcoma patients with radiotherapy. Silencing KIF18B or using T09 significantly improved the radiosensitivity of sarcoma cells, delayed tumour growth in subcutaneous and orthotopic xenograft model, and elongated mice survival time. Furthermore, we predicted that T09 might bind to the structural region of KIF18B to exert radiosensitization.

Interpretation

These results indicated that sarcomas with low expression of KIF18B may benefit from radiotherapy. Moreover, the radiosensitivity of sarcomas with overexpressed KIF18B could be effectively improved by silencing KIF18B or using T09, which may provide promising strategies for radiotherapy treatment of sarcoma.

Fundings

A full list of funding can be found in the Funding Sources section.

Coexpression Network Analysis of Genes Related to the Characteristics of Tumor Stemness in Triple-Negative Breast Cancer

Cancer stem cells (CSCs) are subsets of cells with the ability of self-renewal and differentiation in neoplasm, which are considered to be related to tumor heterogeneity. It has been reported that CSCs act on tumorigenesis and tumor biology of triple-negative breast cancer (TNBC). However, the key genes that cause TNBC showing stem cell characteristics are still unclear. We combined the RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA) database and mRNA expression-based stemness index (mRNAsi) to further analyze mRNAsi with regard to molecular subtypes, tumor depth, and pathological staging characteristics of breast cancer (BC). Secondly, we extract the differential gene expression of tumor vs. normal group and TNBC vs. other subtypes of BC group, respectively, and intersect them to achieve precise results. We used a weighted gene coexpression network analysis (WGCNA) to screen significant gene modules and the functions of selected genes including BIRC5, CDC25A, KIF18B, KIF2C, ORC1, RAD54L, and TPX2 were carried out through gene ontology (GO) functional annotation. The Oncomine, bc-GenExMiner v4.4, GeneMANIA, Kaplan-Meier Plotter (KM-plotter), and GEPIA were used to verify the expression level and functions of key genes. In this study, we found that TNBC had the highest stem cell characteristics in BC compared with other subtypes. The lower the mRNAsi score, the better the overall survival and treatment outcome. Seven key genes of TNBC were screened and functional annotation indicated that there were strong correlations between them, relating to nuclear division, organelle fission, mitotic nuclear division, and other events that determine cell fate. Among these genes, we found four genes that were highly associated with adverse survival events. Seven key genes identified in this study were found to be closely related to the maintenance of TNBC stemness, and the overexpression of four showed earlier recurrence. The overall survival (OS) curves of all key genes between differential expression level crossed at around nine-year follow-up, which was consistent with the trend of the OS curve related to mRNAsi. These findings may provide new ideas for screening therapeutic targets in order to depress TNBC stemness.

Kinesin family members KIF2C/4A/10/11/14/18B/20A/23 predict poor prognosis and promote cell proliferation in hepatocellular carcinoma

Kinesin superfamily proteins (KIFs) comprise a family of molecular motors that transport membranous organelles and protein complexes in a microtubule- and ATP-dependent manner, with multiple roles in cancers. Little is known about the function of KIFs in hepatocellular carcinoma (HCC). Here, we investigate the roles of KIFs in the prognosis and progression of HCC. Upregulation of eight KIFs (KIF2C, KIF4A, KIF10, KIF11, KIF14, KIF18B, KIF20A, and KIF23) was found to be significantly associated with the tumor stage and pathological tumor grade of HCC patients. Additionally, a high expression of these eight KIFs was significantly associated with shorter overall survival (OS) and disease-free survival (DFS) in patients with HCC. Cox regression analysis showed the mRNA expression levels of these eight KIF members to be independent prognostic factors for worse outcomes in HCC. Moreover, a risk score model based on the mRNA levels of the eight KIF members effectively predicted the OS rate of patients with HCC. Additional experiments revealed that downregulation of each of the eight KIFs effectively decreased the proliferation and increased the G1 arrest of liver cancer cells in vitro. Taken together, these results indicate that KIF2C/4A/10/11/14/18B/20A/23 may serve as prognostic biomarkers for survival and potential therapeutic targets in HCC patients.

Weighted Gene Coexpression Network Analysis of Features That Control Cancer Stem Cells Reveals Prognostic Biomarkers in Lung Adenocarcinoma

Purpose We aimed to identify new prognostic biomarkers of lung adenocarcinoma (LUAD) based on cancer stem cell theory.

Materials and Methods: RNA-seq and microarray data were obtained with clinical information downloaded from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Weighted gene coexpression network analysis (WGCNA) was applied to identify significant module and hub genes. The hub genes were validated via microarray data from GEO, and a prognostic signature with prognostic hub genes was constructed.

Results LUAD patients enrolled from TCGA had a higher mRNA expression-based stemness index (mRNAsi) in tumor tissue than in adjacent normal tissue. Some clinical features and prognoses were found to be highly correlated with mRNAsi. WGCNA found that the green module and blue module were the most significant modules related to mRNAsi; 50 key genes were identified in the green module and were enriched mostly in the cell cycle, chromosome segregation, chromosomal region and microtubule binding. Six hub genes were revealed through the protein-protein interaction (PPI) network and Molecular Complex Detection (MCODE) plugin of Cytoscape software. Based on external verification with the GEO database, these six genes are not only expressed at different levels in LUAD and normal tissues but also associated with different clinical features. In addition, the construction of a prognostic signature with three hub genes showed high predictive value.

Conclusion mRNAsi-related biomarkers may suggest a new potential treatment strategy for LUAD.

Overexpression of kinesin superfamily members as prognostic biomarkers of breast cancer

BACKGROUND

Kinesin superfamily (KIFs) has a long-reported significant influence on the initiation, development, and progress of breast cancer. However, the prognostic value of whole family members was poorly done. Our study intends to demonstrate the value of kinesin superfamily members as prognostic biomarkers as well as a therapeutic target of breast cancer.

METHODS

Comprehensive bioinformatics analyses were done using data from TCGA, GEO, METABRIC, and GTEx. LASSO regression was done to select tumor-related members. Nomogram was constructed to predict the overall survival (OS) of breast cancer patients. Expression profiles were testified by quantitative RT-PCR and immunohistochemistry. Transcription factor, GO and KEGG enrichments were done to explore regulatory mechanism and functions.

RESULTS

A total of 20 differentially expressed KIFs were identified between breast cancer and normal tissue with 4 (KIF17, KIF26A, KIF7, KIFC3) downregulated and 16 (KIF10, KIF11, KIF14, KIF15, KIF18A, KIF18B, KIF20A, KIF20B, KIF22, KIF23, KIF24, KIF26B, KIF2C, KIF3B, KIF4A, KIFC1) overexpressed. Among which, 11 overexpressed KIFs (KIF10, KIF11, KIF14, KIF15, KIF18A, KIF18B, KIF20A, KIF23, KIF2C, KIF4A, KIFC1) significantly correlated with worse OS, relapse-free survival (RFS) and distant metastasis-free survival (DMFS) of breast cancer. A 6-KIFs-based risk score (KIF10, KIF15, KIF18A, KIF18B, KIF20A, KIF4A) was generated by LASSO regression with a nomogram validated an accurate predictive efficacy. Both mRNA and protein expression of KIFs are experimentally demonstrated upregulated in breast cancer patients. Msh Homeobox 1 (MSX1) was identified as transcription factors of KIFs in breast cancer. GO and KEGG enrichments revealed functions and pathways affected in breast cancer.

CONCLUSION

Overexpression of tumor-related KIFs correlate with worse outcomes of breast cancer patients and can work as potential prognostic biomarkers.

Context-Specific Coordinately Regulatory Network Prioritize Breast Cancer Genetic Risk Factors

Breast cancer (BC) is one of the most common tumors, leading the causes of cancer death in women. However, the pathogenesis of BC still remains unclear, and the atlas of BC-associated risk factors is far from complete. In this study, we constructed a BC-specific coordinately regulatory network (CRN) to prioritize potential BC-associated protein-coding genes (PCGs) and non-coding RNAs (ncRNAs). We integrated 813 BC sample transcriptome data from The Cancer Genome Atlas (TCGA) and eight types of regulatory relationships to construct BC-specific CRN, including 387 transcription factors (TFs), 174 microRNAs (miRNAs), 407 long non-coding RNAs (lncRNAs), and 905 PCGs. After that, the random walk with restart (RWR) method was performed on the CRN by using the known BC-associated factors as seeds, and potential BC-associated risk factors were prioritized. The leave-one-out cross-validation (LOOCV) was utilized on the BC-specific CRN and achieved an area under the curve (AUC) of 0.92. The performances of common CRN, common protein-protein interaction (PPI) network, and BC-specific PPI network were also evaluated, demonstrating that the context-specific CRN prioritizes BC risk factors. Functional analysis for the top 100-ranked risk factors in the candidate list revealed that these factors were significantly enriched in cancer-related functions and had significant semantic similarity with BC-related gene ontology (GO) terms. Differential expression analysis and survival analysis proved that the prioritized risk factors significantly associated with BC progression and prognosis. In total, we provided a computational method to predict reliable BC-associated risk factors, which would help improve the understanding of the pathology of BC and benefit disease diagnosis and prognosis.

The role of the CDCA gene family in ovarian cancer

Background

Ovarian cancer is a frequently-occurring reproductive system malignancy in females, which leads to an annual of over 100 thousand deaths worldwide.

Methods

The electronic databases, including GEPIA, ONCOMINE, Metascape, and Kaplan-Meier Plotter, were used to examine both survival and transcriptional data regarding the cell division cycle associated (CDCA) gene family among ovarian cancer patients.

Results

All CDCA genes expression levels were up-regulated in ovarian cancer tissues relative to those in non-carcinoma ovarian counterparts. Besides, CDCA5/7 expression levels were related to the late tumor stage. In addition, the Kaplan-Meier Plotter database was employed to carry out survival analysis, which suggested that ovarian cancer patients with increased CDCA2/3/5/7 expression levels had poor overall survival (OS) (P<0.05). Moreover, ovarian cancer patients that had up-regulated mRNA expression levels of CDCA2/5/8 had markedly reduced progression-free survival (PFS) (P<0.05); and up-regulated CDCA4 expression showed remarkable association with reduced post-progression survival (PPS) (P<0.05). Additionally, the following processes were affected by CDCA genes alterations, including R-HAS-2500257: resolution of sister chromatid cohesion; GO:0051301: cell division; CORUM: 1118: Chromosomal passenger complex (CPC, including CDCA8, INCENP, AURKB and BIRC5); CORUM: 127: NDC80 kinetochore complex; M129: PID PLK1 pathway; and GO: 0007080: mitotic metaphase plate congression, all of which were subjected to marked regulation since the alterations affected CDCA genes.

Conclusions

Up-regulated CDCA gene expression in ovarian cancer tissues probably played a crucial part in the occurrence of ovarian cancer. The up-regulated CDCA2/3/5/7 expression levels were used as the potential prognostic markers to improve the poor ovarian cancer survival and prognostic accuracy. Moreover, CDCA genes probably exerted their functions in tumorigenesis through the PLK1 pathway.

KIF18B promotes hepatocellular carcinoma progression through activating Wnt/β-catenin-signaling pathway

This study aimed to investigate the functional roles of kinesin family member 18B (KIF18B) in hepatocellular carcinoma (HCC) development, as well as the related molecular mechanisms. Tissue specimens were collected from 105 patients with HCC, and the messenger RNA (mRNA) and protein levels of KIF18B were detected using quantitative real-time polymerase chain reaction and immunohistochemistry assays, respectively. The χ² test was performed to estimate the association of KIF18B with clinical characteristics of patients with HCC. Effects of KIF18B expression on biological behaviors of HCC cells were detected by clone formation, 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide, and transwell assays. The expression patterns of proteins were investigated using Western blot analysis. HCC tissues and cell lines showed significant upregulation of KIF18B at both mRNA and protein levels (p > .05, for all). Furthermore, the elevated KIF18B expression was positively correlated with the tumor-node-metastasis stage (p = .015) and lymph node metastasis (p = .007). Knockdown of KIF18B might suppress HCC cell clone formation, proliferation, migration, and invasion in vitro. Besides, the activity of Wnt/β-catenin pathway was also significantly inhibited after the KIF18B knockdown. However, the antitumor actions caused by KIF18B knockdown might be reversed by lithium chloride treatment, which was the inducer of Wnt/β-catenin-signaling pathway. KIF18B may serve as an oncogene in HCC through enhancing the activity of Wnt/β-catenin pathway.

KIF18B promotes the proliferation of pancreatic ductal adenocarcinoma via activating the expression of CDCA8

Pancreatic cancer is one of the malignant tumors with the worst prognosis, and the 5-year survival rate of this disease is less than 1%. About 90% of pancreatic cancer is pancreatic ductal adenocarcinoma (PDAC), and targeting therapy has become a promising treatment for PDAC in recent years. To improve the survival rate, novel therapeutic targets for PDAC are still urgently needed. KIF18B was initially identified as a member of the kinesin family and involved in multiple cellular processes, such as separation of chromosomes in mitosis. Recently, it was found that KIF18B was involved in the growth and development of multiple cancers. However, the potential link between KIF18B and PDAC is still unclear. In this study, we demonstrated that KIF18B was highly expressed in human PDAC tissues, and related with the poor prognosis and clinical features, such as tumor size (*p = .013) and pTNM stage (*p = .025), of patients with PDAC. We further found that KIF18B knockdown blocked the cell proliferation of PDAC in vitro and in vivo, and the cell cycle was arrested caused by KIF18B depletion. Additionally, we also found that KIF18B bound to the promoter region of the cell division cycle associated 8 and thus activated its transcription. Taken together, this study explored the molecular mechanism underlying KIF18B promoting PDAC and provided a novel therapeutic target of this disease.

Deep learning for inferring gene relationships from single-cell expression data

Several methods were developed to mine gene-gene relationships from expression data. Examples include correlation and mutual information methods for coexpression analysis, clustering and undirected graphical models for functional assignments, and directed graphical models for pathway reconstruction. Using an encoding for gene expression data, followed by deep neural networks analysis, we present a framework that can successfully address all of these diverse tasks. We show that our method, convolutional neural network for coexpression (CNNC), improves upon prior methods in tasks ranging from predicting transcription factor targets to identifying disease-related genes to causality inference. CNNC's encoding provides insights about some of the decisions it makes and their biological basis. CNNC is flexible and can easily be extended to integrate additional types of genomics data, leading to further improvements in its performance.

Kinesin family member 18B: A contributor and facilitator in the proliferation and metastasis of cutaneous melanoma

Melanoma is the most aggressive type of cutaneous tumor and the occurrence of metastasis makes it resistant to almost all available treatment and becomes incorrigible. Hence, identifying metastasis-related biomarkers and effective therapeutic targets will assist in preventing metastasis and ameliorating cutaneous melanoma. In our present study, we reported kinesin family member 18B (KIF18B) as a novel contributor in cutaneous melanoma proliferation and metastasis, and it was found to be of great significance in predicting the prognosis of cutaneous melanoma patients. Bioinformatics analysis based on ONCOMINE, The Cancer Genome Atlas, and Genotype-Tissue Expression database revealed that KIF18B was highly expressed in cutaneous melanoma and remarkably correlated with unfavorable clinical outcomes. Consistently, the results of the quantitative real-time polymerase chain reaction exhibited that the expression of KIF18B was significantly higher in cutaneous melanoma cell lines than that in normal cells. In vitro, biological assays found that knockdown of KIF18B in cutaneous melanoma cells noticeably repressed cell proliferation, migration, and invasion, while inducing cell apoptosis. Moreover, the protein expression of E-cadherin was enhanced while the expression of N-cadherin, vimentin, and Snail was decreased in M14 cells after knocking down KIF18B. In addition, the phosphorylation of phosphoinositide 3-kinase (PI3K) and extracellular-signal-regulated kinase (ERK) was significantly suppressed in M14 cells with silenced KIF18B. Above all, our results indicated that the repression of cutaneous melanoma cell migration and proliferation caused by KIF18B depletion suggested an oncogenic role of KIF18B in cutaneous melanoma, which acts through modulating epithelial-mesenchymal transition and ERK/PI3K pathway.

Loss of alanine-glyoxylate and serine-pyruvate aminotransferase expression accelerated the progression of hepatocellular carcinoma and predicted poor prognosis

BACKGROUND

Accumulated studies reported abnormal gene expression profiles of hepatocellular carcinoma (HCC) by cDNA microarray. We tried to merge cDNA microarray data from different studies to search for stably changed genes, and to find out better diagnostic and prognostic markers for HCC.

METHODS

A systematic review was performed by searching publications indexed in Pubmed from March 1, 2001 to July 1, 2016. Studies that reporting cDNA microarray profiles in HCC, containing both tumor and nontumor data and published in English-language were retrieved. The differentially expressed genes from eligible studies were summarized and ranked according to the frequency. High frequency genes were subjected to survival analyses. The expression and prognostic value of alanine-glyoxylate and serine-pyruvate aminotransferase (AGXT) was further evaluated in HCC datasets in Oncomine and an independent HCC tissue array cohort. The role of AGXT in HCC progression was evaluated by proliferation and migration assays in a human HCC cell line.

RESULTS

A total of 43 eligible studies that containing 1917 HCC patients were included, a list of 2022 non redundant abnormally expressed genes in HCC were extracted. The frequencies of reported genes were ranked. We finally obtained a list of only five genes (AGXT; ALDOB; CYP2E1; IGFBP3; TOP2A) that were differentially expressed in tumor and nontumor tissues across studies and were significantly correlated to HCC prognosis. Only AGXT had not been reported in HCC. Reduced expression of AGXT reflected poor differentiation of HCC and predicts poor survival. Knocking down of AGXT enhanced cell proliferation and migration of HCC cell line.

CONCLUSIONS

The present study supported the feasibility and necessity of systematic review on discovering new and reliable biomarkers for HCC. We also identified a list of high frequency prognostic genes and emphasized a critical role of AGXT deletion during HCC progression.

Clinical Significance And Integrative Analysis Of Kinesin Family Member 18B In Lung Adenocarcinoma

Background

Kinesin family member 18B (KIF18B) is a member of the kinesin-8 superfamily, and functions as an oncogene in human cancers. However, its expression profile and role in lung adenocarcinoma (LUAD) remain unclear.

Materials and methods

We examined the expression profile of KIF18B using quantitative real-time reverse transcription polymerase chain reaction and immunohistochemistry in fresh clinical samples. Using data downloaded from the Cancer Genome Atlas database and Gene Expression Omnibus, we explored the clinical significance of KIF18B, potential mechanisms of its dysregulation and its underlying biological function in LUAD.

Results

KIF18B was significantly over-expressed in LUAD tissues relative to normal tissues. High KIF18B expression was associated with smoking history, positive nodal invasion, advanced clinical stage, death status and poorer prognosis. Cox regression analyses revealed that KIF18B overexpression was an independent prognostic biomarker for poor overall survival (OS) and recurrence-free survival in LUAD. In addition, KIF18B mutation was observed in 2.2% of LUAD cases. DNA copy number variation was correlated with upregulated expression of KIF18B in LUAD tissues and cell lines. The methylation level of some KIF18B DNA CpG sites was negatively associated with its mRNA expression. KIF18B was predictively targeted by miR-125a-5p, which was downregulated in LUAD tissues, inversely correlated with KIF18B mRNA expression and significantly associated with poor OS. Furthermore, gene set enrichment analysis revealed that genes positively co-expressed with KIF18B were mainly enriched in cell cycle signaling pathways.

Conclusion

Our results indicate that KIF18B is a promising prognostic biomarker for LUAD. DNA amplification, hypomethylation as well as miR-125a-5p downregulation may be involved in the mechanism of KIF18B dysregulation in LUAD. KIF18B might function as a novel oncogene through cell cycle regulation pathways in LUAD.

Bioinformatics Analysis Suggests the Combined Expression of AURKB and KIF18B Being an Important Event in the Development of Clear Cell Renal Cell Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common type of renal cell carcinoma with high metastatic rate and high mortality rate, needing to find potential therapeutic targets and develop new therapy methods. The bioinformatics analysis was used in this study to find the targets. Firstly, the expression profile of ccRCC obtained from The Cancer Genome Atlas (TCGA) database and GSE53757 dataset were used to identify the significant up-regulated genes. IL20RB, AURKB and KIF18B with the top efficiency of capable of diagnosis ccRCC from para cancer tissue, were over-expressed in ccRCC samples, and expressed increasedly with the development of ccRCC. There was the closest correlation between AURKB and KIF18B in these three over-expressed genes. AURKB (high) or KIF18B (high) were all significantly correlated with higher T, N, M stage, G grade and shorter overall survival (OS) of ccRCC patients. Furthermore, the ccRCC patients with AURKB (high) + KIF18B (high) showed worse clinical characteristics and prognosis. Multivariate COX regression analysis indicated AURKB (high) and KIF18B (high) were all the independent prognostic risk factor without considering the interaction of AURKB and KIF18B. Moreover, considering the combination of each other, only AURKB (high) + KIF18B (high) expression was an independent prognostic risk factor for ccRCC patients, but not other situations. Collectively, AURKB was closely associated with KIF18B, and the combined expression of AURKB and KIF18B may be of great significance in ccRCC.

KIF18B as a regulator in microtubule movement accelerates tumor progression and triggers poor outcome in lung adenocarcinoma

KIF18B is involved in several tumor progression and exerts critical effects on microtubule growth during mitosis, but its role in lung adenocarcinoma still remains rare. Hence, we attempted to explore the biological function of KIF18B in lung adenocarcinoma. We first analyzed the expressional pattern of KIF18B in lung adenocarcinoma, and detected the correlation between KIF18B expression and clinical characteristics in lung adenocarcinoma based on The Cancer Genome Atlas (TCGA) database and Oncomine dataset. Subsequently, cell counting kit-8 (CCK-8) assay, wound-healing analysis, and transwell method were performed to assess the effects of KIF18B in lung adenocarcinoma cells. Quantitative real-time reverse transcription-PCR (qRT-PCR) and western blotting were utilized to measure the mRNA and protein expression levels. Our results illustrated that KIF18B expression was significantly up-regulated in lung adenocarcinoma samples compared to normal specimens. High levels of KIF18B were associated with unfavorable prognosis of lung adenocarcinoma patients. Down-regulation of KIF18B in lung adenocarcinoma cells inhibited cell prolifartion, migration, and invasion. Western blot assay demonstrated that KIF18B knockdown markedly decreased Rac1-GTP expression, an important marker of migration and invasion in tumors. Moreover, the phosphorylation of AKT and mTOR expression levels were attenuated after KIF18B knockdown. Taken together, these data enhanced the point that KIF18B might promote lung adenocarcinoma cell proliferation, migration, and invasion by activating Rac1 and mediating the AKT/mTOR signaling pathway.

Genome‑wide investigation of the clinical significance and prospective molecular mechanisms of kinesin family member genes in patients with lung adenocarcinoma

The current study aimed to identify the potential clinical significance and molecular mechanisms of kinesin (KIF) family member genes in lung adenocarcinoma (LUAD) using genome-wide RNA sequencing (RNA-seq) datasets derived from The Cancer Genome Atlas (TCGA) database. Clinical parameters and RNA-seq data of patients with LUAD from the TCGA database enabled the assessment of the clinical significance of KIF genes, while the potential mechanisms of their interactions in LUAD were investigated by gene set enrichment analysis (GSEA). A gene signature with potential prognostic value was constructed via a stepwise multivariable Cox analysis. In total, 23 KIF genes were identified to be differentially expressed genes (DEGs) between the LUAD tumor and adjacent non-cancerous tissues. Of these, 8 differentially expressed KIF genes were strongly found to be strongly associated with the overall survival of patients with LUAD. Three of these genes were found to be able to be grouped as a potential prognostic gene signature. Patients with higher risk scores calculated using this gene signature were found to have a markedly higher risk of mortality (adjusted P=0.003; adjusted HR, 1.576; 95% CI, 1.166–2.129). Time-dependent receiver operating characteristic analysis indicated that this prognostic signature was able to accurately predict patient prognosis with an area under curve of 0.636, 0.643,0.665, 0.670 and 0.593 for the 1-, 2-, 3-, 4- and 5-year survival, respectively. This prognostic gene signature was identified as an independent risk factor for LUAD and was able to more accurately predict prognosis in comparison to other known clinical parameters, as shown via comprehensive survival analysis. GSEA enrichment revealed that that KIF14, KIF18B and KIF20A mediated basic cell physiology through the regulation of the cell cycle, DNA replication, and DNA repair biological processes and pathways. On the whole, the findings of this study identified 23 KIF genes that were DEGs between LUAD tumor and adjacent non-cancerous tissues. In total, 8 of these genes had the potential to function as prognostic and diagnostic biomarkers in patients with LUAD.

Bioinformatics analysis of molecular genetic targets and key pathways for hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is the second leading cause of death among cancers worldwide. In this study, we aimed to identify the molecular target genes and detect the key mechanisms of HCC. Three gene expression profiles (GSE84006, GSE14323, GSE14811) and two miRNA expression profiles (GSE40744, GSE36915) were analyzed to determine the molecular target genes, microRNAs (miRNAs) and the potential molecular mechanisms in HCC.

Methods

All profiles were extracted from the Gene Expression Omnibus database. The identification of the differentially expressed genes (DEGs) was analyzed by the GEO2R method. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and gene ontology (GO) enrichment analysis performed database for Integrated Discovery, Visualization and Annotation. The miRNA-gene network and protein–protein interaction (PPI) network were correlated by the Cytoscape software. The key target genes were identified by the CytoHubba plugin, Molecular Complex Detection (MCODE) plugin and miRNA-gene network. The identified hub genes were testified for survival curve using the Kaplan–Meier plotter database.

Results

Expression profiles had 592 overlapped DEGs. The majority of the DEGs were enriched in membrane-bounded organelles and intracellular membrane-bounded organelles. These DEGs were significantly enriched in metabolic, protein processing in the endoplasmic reticulum and thyroid cancer pathways. PPI network analysis showed these genes were mostly involved in the pathogenic Escherichia coli infection and the regulation of actin cytoskeleton pathways. Combining these results, we identified 10 key genes involving in the progression of HCC. Finally, PLK1, PRCC, PRPF4 and PSMA7 exhibited higher expression levels in HCC patients with poor prognosis than those for lower expression via Kaplan–Meier plotter database.

Conclusion

PLK1, PRCC, PRPF4 and PSMA7 could be potential biomarkers or therapeutic targets for HCC. Meanwhile, the metabolic pathway, protein processing in the endoplasmic reticulum and the thyroid cancer pathway may play vital roles in the progression of HCC.

Random gene sets in predicting survival of patients with hepatocellular carcinoma

Despite multiple publications, molecular signatures predicting the course of hepatocellular carcinoma (HCC) have not yet been integrated into clinical routine decision-making. Given the diversity of published signatures, optimal number, best combinations, and benefit of functional associations of genes in prognostic signatures remain to be defined. We investigated a vast number of randomly chosen gene sets (varying between 1 and 10,000 genes) to encompass the full range of prognostic gene sets on 242 transcriptomic profiles of patients with HCC. Depending on the selected size, 4.7 to 23.5% of all random gene sets exhibit prognostic potential by separating patient subgroups with significantly diverse survival. This was further substantiated by investigating gene sets and signaling pathways also resulting in a comparable high number of significantly prognostic gene sets. However, combining multiple random gene sets using "swarm intelligence" resulted in a significantly improved predictability for approximately 63% of all patients. In these patients, approx. 70% of all random 50-gene containing gene sets resulted in equal and stable prediction of survival. For all other patients, a reliable prediction seems highly unlikely for any selected gene set. Using a machine learning and independent validation approach, we demonstrated a high reliability of random gene sets and swarm intelligence in HCC prognosis. Ultimately, these findings were validated in two independent patient cohorts and independent technical platforms (microarray, RNASeq). In conclusion, we demonstrate that using "swarm intelligence" of multiple gene sets for prognosis prediction may not only be superior but also more robust for predictive purposes. KEY MESSAGES: Molecular signatures predicting HCC have not yet been integrated into clinical routine Depending on the selected size, 4.7 to 23.5% of all random gene sets exhibit prognostic potential; independent of the technical platform (microarray, RNASeq) Using "swarm intelligence" resulted in a significantly improved predictability In these patients, approx. 70% of all random 50-gene containing gene sets resulted in equal and stable prediction of survival Overall, "swarm intelligence" is superior and more robust for predictive purposes in HCC.

Identification of prognostic biomarkers in colorectal cancer using a long non-coding RNA-mediated competitive endogenous RNA network

Colorectal cancer (CRC) is a highly malignant gastrointestinal tumor accompanied by poor prognosis. Long non-coding RNA (lncRNA) plays an important role in the progression and physiology of tumors as it competes with endogenous RNAs, including miRNA and mRNA. In the present study, a multi-step computational method was used to build a CRC-related functional lncRNA-mediated competitive endogenous RNA (ceRNA) network (LMCN). lncRNAs with more degrees and betweenness centrality (BC) were screened out as hub lncRNAs. Then functional enrichment analyses of lncRNAs were carried out from the Gene Ontology (GO) and Reactome pathway databases based on the 'guilt by association' principle. As a result, lncRNAs in the LMCN displayed specific topological characteristics in accordance with the regulatory correlation of coding mRNAs in CRC pathology. HCP5, EPB41L4A-AS1, SNHG12, and LINC00649 were screened out as hub lncRNAs which were more significantly related to the development and prognosis of CRC. The hub lncRNAs in CRC were obviously involved in functions of cell cycle arrest, vacuolar transport, histone modification, and in pathways of GPCR, signaling by Rho GTPases, axon guidance pathways, meaning that they might be potential biomarkers for diagnosis, evaluation and gene-targeted therapy of CRC. Thus, the LMCN construction method could accelerate lncRNA discovery and therapeutic development in CRC.

Emerging Insights into the Function of Kinesin-8 Proteins in Microtubule Length Regulation

Proper regulation of microtubules (MTs) is critical for the execution of diverse cellular processes, including mitotic spindle assembly and chromosome segregation. There are a multitude of cellular factors that regulate the dynamicity of MTs and play critical roles in mitosis. Members of the Kinesin-8 family of motor proteins act as MT-destabilizing factors to control MT length in a spatially and temporally regulated manner. In this review, we focus on recent advances in our understanding of the structure and function of the Kinesin-8 motor domain, and the emerging contributions of the C-terminal tail of Kinesin-8 proteins to regulate motor activity and localization.

CDCA3 mediates p21-dependent proliferation by regulating E2F1 expression in colorectal cancer

Dysregulated cell cycle progression serves a crucial role in tumor development. Cell division cycle-associated 3 (CDCA3) is considered a trigger of mitotic entry; it is an important part of the S phase kinase-associated protein 1/Cullin/F-box ubiquitin ligase complex and mediates the destruction of mitosis-inhibitory kinase wee1. However, little is known about the role of CDCA3 in cancer, particularly colorectal cancer (CRC). The present study aimed to explore the biological and clinical significance of CDCA3 in CRC growth and progression. CDCA3 expression was significantly associated with tumor progression and poor survival. Overexpression of CDCA3 increased proliferation in LoVo CRC cells, whereas CDCA3 knockdown in SW480 CRC cells led to decreased proliferation, in vitro and in vivo. Further mechanistic investigations demonstrated that reduced CDCA3 expression resulted in G1/S phase transition arrest, which was attributed to a significant accumulation of p21 in SW480 cells; conversely, increased CDCA3 expression promoted G1/S phase transition through decreased p21 accumulation in LoVo cells. It was also demonstrated that CDCA3 was able to regulate the expression of transcription factor E2F1, thereby repressing p21 expression. Taken together, these results suggested that overexpression of CDCA3 may serve a crucial role in tumor malignant potential and that CDCA3 may be used as a prognostic factor and a potential therapeutic target in CRC.

CDCA3 promotes cell proliferation by activating the NF-κB/cyclin D1 signaling pathway in colorectal cancer

Cell division cycle associated 3 (CDCA3) is required for mitotic entry, and mediates the degradation of the inhibitory kinase Wee1. New evidence suggests CDCA3 plays a role in tumor promotion. However, little is known about the relevance of CDCA3 in colorectal cancer(CRC), especially in the regulation of NF-κB activity. In this study, we found that colorectal tumors significantly expressed more CDCA3 than non-cancer tissues. In addition, CDCA3 promoted CRC cell proliferation in vitro. Furthermore, downregulation of CDCA3 not only induced cell cycle arrest but also facilitated apoptosis. Mechanistically, CDCA3 activates the NF-κB signaling pathway by interacting with TRAF2 in CRC. Together, these results define a tumor-supportive role for CDCA3, which may also provide a new promising strategy for treating CRC.

KIF18B promotes tumor progression through activating the Wnt/β-catenin pathway in cervical cancer

Background

KIF18B was identified as a potential oncogene by analysis of The Cancer Genome Atlas database.

Materials and methods

We assessed KIF18B expression and explored its clinical significance in cervical cancer tissues. We have also evaluated the effects of KIF18B on cervical cancer cell proliferation, migration, and invasion both in vitro and in vivo.

Results

Our results show that KIF18B is overexpressed in cervical cancer tissues and is associated with a large primary tumor size, an advanced FIGO stage, and an advanced tumor grade. Knockdown of KIF18B induces cell cycle G1-phase arrest and inhibits the proliferation, migration, and invasion of cervical cancer cells, whereas its overexpression promotes proliferation, migration, and invasion in these cells. Moreover, silencing of KIF18B reduces expression of CyclinD1, β-catenin, C-myc, and p-GSK3β expression.

Conclusion

These data suggest that KIF18B can serve as a novel oncogene that promotes the tumorigenicity of cervical cancer cells by activating Wnt/β-catenin signaling pathway.

Distinct expression of CDCA3, CDCA5, and CDCA8 leads to shorter relapse free survival in breast cancer patient

Breast cancer is a dangerous disease that results in high mortality rates for cancer patients. Many methods have been developed for the treatment and prevention of this disease. Determining the expression patterns of certain target genes in specific subtypes of breast cancer is important for developing new therapies for breast cancer. In the present study, we performed a holistic approach to screening the mRNA expression of six members of the cell division cycle-associated gene family (CDCA) with a focus on breast cancer using the Oncomine and The Cancer Cell Line Encyclopedia (CCLE) databases. Furthermore, Gene Expression-Based Outcome for Breast Cancer Online (GOBO) was also used to deeply mine the expression of each CDCA gene in clinical breast cancer tissue and breast cancer cell lines. Finally, the mRNA expression of the CDCA genes as related to breast cancer patient survival were analyzed using a Kaplan-Meier plot. CDCA3, CDCA5, and CDCA8 mRNA expression levels were significantly higher than the control sample in both clinical tumor sample and cancer cell lines. These highly expressed genes in the tumors of breast cancer patients dramatically reduced patient survival. The interaction network of CDCA3, CDCA5, and CDCA8 with their co-expressed genes also revealed that CDCA3 expression was highly correlated with cell cycle related genes such as CCNB2, CDC20, CDKN3, and CCNB1. CDCA5 expression was correlated with BUB1 and TRIP13, while CDCA8 expression was correlated with BUB1 and CCNB1. Altogether, these findings suggested CDCA3, CDCA5, and CDCA8 could have a high potency as targeted breast cancer therapies.

The Transcriptomic Signature Of Disease Development And Progression Of Nonalcoholic Fatty Liver Disease

A longitudinal molecular model of the development and progression of nonalcoholic fatty liver disease (NAFLD) over time is lacking. We have recently validated a high fat/sugar water-induced animal (an isogenic strain of C57BL/6 J:129S1/SvImJ mice) model of NAFLD that closely mimics most aspects of human disease. The hepatic transcriptome of such mice with fatty liver (8 weeks), steatohepatitis with early fibrosis (16–24 weeks) and advanced fibrosis (52 weeks) after initiation of the diet was evaluated and compared to mice on chow diet. Fatty liver development was associated with transcriptional activation of lipogenesis, FXR-RXR, PPAR-α mediated lipid oxidation and oxidative stress pathways. With progression to steatohepatitis, metabolic pathway activation persisted with additional activation of IL-1/inhibition of RXR, granulocyte diapedesis/adhesion, Fc macrophage activation, prothrombin activation and hepatic stellate cell activation. Progression to advanced fibrosis was associated with dampening of metabolic, oxidative stress and cell stress related pathway activation but with further Fc macrophage activation, cell death and turnover and activation of cancer-related networks. The molecular progression of NAFLD involves a metabolic perturbation which triggers subsequent cell stress and inflammation driving cell death and turnover. Over time, inflammation and fibrogenic pathways become dominant while in advanced disease an inflammatory-oncogenic profile dominates.

Silymarin-mediated regulation of the cell cycle and DNA damage response exerts antitumor activity in human hepatocellular carcinoma

A novel module-search algorithm method was used to screen for potential signatures and investigate the molecular mechanisms of inhibiting hepatocellular carcinoma (HCC) growth following treatment with silymarin (SM). The modules algorithm was used to identify the modules via three major steps: i) Seed gene selection; ii) module search by seed expansion and entropy minimization; and iii) module refinement. The statistical significance of modules was computed to select the differential modules (DMs), followed by the identification of core modules using the attract method. Pathway analysis for core modules was implemented to identify the biological functions associated with the disease. Subsequently, results were verified in an independent sample set using reverse transcription polymerase chain reaction (RT-PCR). In total, 18 seed genes and 12 DMs (modules 1-12) were identified. The core modules were isolated using gene expression data. Overall, there were 4 core modules (modules 11, 5, 6 and 12). Additionally, DNA topoisomerase 2-binding protein 1 (TOPBP1), non-structural maintenance of chromosomes condensing I complex subunit H, nucleolar and spindle associated protein 1 (NUSAP1) and cell division cycle associated 3 (CDCA3) were the initial seed genes of module 11, 5, 6 and 12, respectively. Pathway results revealed that cell cycle signaling pathway was enriched by all core modules simultaneously. RT-PCR results indicated that the level of CDCA3, TOPBP1 and NUSAP1 in SM-treated HCC samples was markedly decreased compared with that in non-SM-treated HCC. No statistically significant difference between the transcriptional levels of CDCA3 in SM-treated and non-treated HCC groups was identified, although CDCA3 expression was increased in the treated group compared with the untreated group. Furthermore, although the expression level of TOPBP1 and NUSAP1 in the SM-treated group was decreased compared with that in the normal group, no significant difference was observed. From the results of the present study it can be inferred that TOPBP1, NUSAP1 and CDCA3 of the core modules may serve notable functions in SM-associated growth suppression of HCC.

Kinesin superfamily: roles in breast cancer, patient prognosis and therapeutics

Breast cancer pathobiology is known to be influenced by the differential expression of a group of proteins called the kinesin superfamily (KIFs), which is instrumental in the intracellular transport of chromosomes along microtubules during mitosis. During cellular division, kinesins are strictly regulated through temporal synthesis so that they are present only when needed. However, their misregulation may contribute to uncontrolled cell growth owing to premature sister chromatid separation, highlighting their importance in cancer. This review covers the functions of kinesins in normal and breast cancer cells, the use of kinesins for breast cancer patient prognosis, and the targeting of these molecules for therapeutics. A better understanding of KIF proteins may be pivotal to improved disease outcomes for breast cancer patients.

Mitotic read-out genes confer poor outcome in luminal A breast cancer tumors

Luminal breast tumors have been classified into A and B subgroups, with the luminal A being associated with a more favorable clinical outcome. Unfortunately, luminal A tumors do not have a universally good prognosis. We used transcriptomic analyses using public datasets to evaluate the differential expression between normal breast tissue and breast cancer, focusing on upregulated genes included in cell cycle function. Association of selected genes with relapse free survival (RFS) and overall survival (OS) was performed using the KM Plotter Online Tool (http://www.kmplot.com). Seventy-seven genes were differentially expressed between normal and malignant breast tissue. Only five genes were associated with poor RFS and OS. The mitosis-related genes GTSE1, CDCA3, FAM83D and SMC4 were associated with poor outcome specifically in Luminal A tumors. The combination of FAM83D and CDCA3 for RFS and GTSE1 alone for OS showed the better prediction for clinical outcome. CDCA3 was amplified in 3.4% of the tumors, and FAM83D and SMC4 in 2.3% and 2.2%, respectively. In conclusion, we describe a set of genes that predict detrimental outcome in Luminal A tumors. These genes may have utility for stratification in trials of antimitotic agents or cytotoxic chemotherapy, or as candidates for direct target inhibition.

Tumor-infiltrating B cells producing antitumor active immunoglobulins in resected HCC prolong patient survival

BACKGROUND & AIMS

The immunological microenvironment of HCC influences patient outcome, however, the role of B cells remains unclear. This study investigated effects of local B-cell infiltration in HCC cohorts on patient survival and immunological and molecular tumor microenvironment.

RESULTS

Unsupervised gene expression analysis of full cancer transcriptomes (N=2158) revealed a highly co-regulated immunological cluster in HCC that mainly contained immunoglobulin fragments. More specifically, in an independent patient cohort (N=242) that compares HCC with non tumorous liver tissue high expression of these B-cell associated genes was associated with better patient outcome (P=0.0149). Conclusively, the immunohistochemical analysis of another independent cohort of resected HCCs (N=119) demonstrated that infiltration of HCCs by CD20⁺ cells (P=0.004) and CD79a⁺ cells (P=0.038) at the infiltrative margin were associated with prolonged patient survival. Further, the immunoglobulin fragments that were identified in the gene expression analysis were detected at high levels in patients with dense B-cell infiltration.

METHODS

Gene expression of 2 independent HCC tissue databases was compared using microarrays. Additionally, tissue of resected HCCs was stained for CD20, CD79a and immunoglobulins and analysed for the respective cell numbers separately for tumor, infiltrative margin and distant liver stroma. These findings were correlated with clinical data and patient outcome.

CONCLUSIONS

Infiltration of HCCs by B cells is associated with prolonged patient survival. Further, a distinct B-cell like immunoglobulin profile of HCCs was identified that goes along with better patient outcome. We suggest that B cells contribute to local tumor control by secreting increased levels of immunoglobulins with antitumor activity.

Expression of CDCA3 Is a Prognostic Biomarker and Potential Therapeutic Target in Non-Small Cell Lung Cancer

INTRODUCTION

NSCLC is the leading cause for cancer-related deaths worldwide. New therapeutic targets are needed, as development of resistance to current treatment, such as platinum-based chemotherapy, is inevitable. The purpose of this study was to determine the functional relevance and therapeutic potential of cell division cycle associated 3 protein (CDCA3) in NSCLC.

METHODS

The expression of CDCA3 in squamous and nonsquamous NSCLC was investigated by using bioinformatics, Western blot analysis of matched tumor and normal tissue, and immunohistochemistry of a tissue microarray. The function of CDCA3 in NSCLC was determined by using several in vitro assays with small interfering RNA depleting CDCA3 in a panel of three immortalized human bronchial epithelial cell (HBEC) lines and seven NSCLC cell lines.

RESULTS

In this study, cell division cycle associated 3 gene (CDCA3) transcripts were identified as highly increased in NSCLC versus in nonmalignant tissue, with high levels of CDCA3 being associated with poor patient prognosis. CDCA3 protein was also increased in NSCLC tissue and expression was limited to tumor cells. CDCA3 expression was similarly increased in a panel of NSCLC cell lines compared with in three HBEC lines. Although depletion of CDCA3 in the HBEC lines did not affect cellular proliferation, depletion of CDCA3 expression markedly reduced the proliferation of all NSCLC cell lines. CDCA3 depletion caused a defective G2/M-phase cell cycle progression, upregulation of p21 independent of p53, and induction of cellular senescence.

CONCLUSIONS

Our findings highlight CDCA3 as a prognostic factor and potential novel therapeutic target in NSCLC through inhibition of tumor growth and promotion of tumor senescence.

Cell division cycle 20 overexpression predicts poor prognosis for patients with lung adenocarcinoma

The cell division cycle 20, a key component of spindle assembly checkpoint, is an essential activator of the anaphase-promoting complex. Aberrant expression of cell division cycle 20 has been detected in various human cancers. However, its clinical significance has never been deeply investigated in non-small-cell lung cancer. By analyzing The Cancer Genome Atlas database and using some certain online databases, we validated overexpression of cell division cycle 20 in both messenger RNA and protein levels, explored its clinical significance, and evaluated the prognostic role of cell division cycle 20 in non-small-cell lung cancer. Cell division cycle 20 expression was significantly correlated with sex (p = 0.003), histological classification (p < 0.0001), and tumor size (p = 0.0116) in non-small-cell lung cancer patients. In lung adenocarcinoma patients, overexpression of cell division cycle 20 was significantly associated with bigger primary tumor size (p = 0.0023), higher MKI67 level (r = 0.7618, p < 0.0001), higher DNA ploidy level (p < 0.0001), and poor prognosis (hazard ratio = 2.39, confidence interval: 1.87-3.05, p < 0.0001). However, in lung squamous cell carcinoma patients, no significant association of cell division cycle 20 expression was observed with any clinical parameter or prognosis. Overexpression of cell division cycle 20 is associated with poor prognosis in lung adenocarcinoma patients, and its overexpression can also be used to identify high-risk groups. In conclusion, cell division cycle 20 might serve as a potential biomarker for lung adenocarcinoma patients.

The Use of Translational Research Platforms in Clinical and Biomedical Data Exploration

The rise of precision medicine combined with the variety of biomedical data sources and their heterogeneous nature make the integration and exploration of information that they retain more complicated. In light of these issues, translational research platforms were developed as a promising solution. Research centers have used translational tools for the study of integrated data for hypothesis development and validation, cohort discovery and data-exploration. For this article, we reviewed the literature in order to determine the use of translational research platforms in precision medicine. These tools are used to support scientists in various domains regarding precision medicine research. We identified eight platforms: BRISK, iCOD, iDASH, tranSMART, the recently developed OncDRS, as well as caTRIP, cBio Cancer Portal and G-DOC. The last four platforms explore multidimensional data specifically for cancer research. We focused on tranSMART, for it is the most broadly used platform, since its development in 2012.

Targeted sequencing in chromosome 17q linkage region identifies familial glioma candidates in the Gliogene Consortium

Glioma is a rare, but highly fatal, cancer that accounts for the majority of malignant primary brain tumors. Inherited predisposition to glioma has been consistently observed within non-syndromic families. Our previous studies, which involved non-parametric and parametric linkage analyses, both yielded significant linkage peaks on chromosome 17q. Here, we use data from next generation and Sanger sequencing to identify familial glioma candidate genes and variants on chromosome 17q for further investigation. We applied a filtering schema to narrow the original list of 4830 annotated variants down to 21 very rare (<0.1% frequency), non-synonymous variants. Our findings implicate the MYO19 and KIF18B genes and rare variants in SPAG9 and RUNDC1 as candidates worthy of further investigation. Burden testing and functional studies are planned.