Expression profiles of non-small cell lung cancers on cDNA microarrays: identification of genes for prediction of lymph-node metastasis and sensitivity to anti-cancer drugs

Based on machine learning, CDC20 has been identified as a biomarker for postoperative recurrence and progression in stage I & II lung adenocarcinoma patients

Objective

By utilizing machine learning, we can identify genes that are associated with recurrence, invasion, and tumor stemness, thus uncovering new therapeutic targets.

Methods

To begin, we obtained a gene set related to recurrence and invasion from the GEO database, a comprehensive gene expression database. We then employed the Weighted Gene Co-expression Network Analysis (WGCNA) to identify core gene modules and perform functional enrichment analysis on them. Next, we utilized the random forest and random survival forest algorithms to calculate the genes within the key modules, resulting in the identification of three crucial genes. Subsequently, one of these key genes was selected for prognosis analysis and potential drug screening using the Kaplan-Meier tool. Finally, in order to examine the role of CDC20 in lung adenocarcinoma (LUAD), we conducted a variety of in vitro and in vivo experiments, including wound healing assay, colony formation assays, Transwell migration assays, flow cytometric cell cycle analysis, western blotting, and a mouse tumor model experiment.

Results

First, we collected a total of 279 samples from two datasets, GSE166722 and GSE31210, to identify 91 differentially expressed genes associated with recurrence, invasion, and stemness in lung adenocarcinoma. Functional enrichment analysis revealed that these key gene clusters were primarily involved in microtubule binding, spindle, chromosomal region, organelle fission, and nuclear division. Next, using machine learning, we identified and validated three hub genes (CDC45, CDC20, TPX2), with CDC20 showing the highest correlation with tumor stemness and limited previous research. Furthermore, we found a close association between CDC20 and clinical pathological features, poor overall survival (OS), progression-free interval (PFI), progression-free survival (PFS), and adverse prognosis in lung adenocarcinoma patients. Lastly, our functional research demonstrated that knocking down CDC20 could inhibit cancer cell migration, invasion, proliferation, cell cycle progression, and tumor growth possibly through the MAPK signaling pathway.

Conclusion

CDC20 has emerged as a novel biomarker for monitoring treatment response, recurrence, and disease progression in patients with lung adenocarcinoma. Due to its significance, further research studying CDC20 as a potential therapeutic target is warranted. Investigating the role of CDC20 could lead to valuable insights for developing new treatments and improving patient outcomes.

Integration of artificial intelligence in lung cancer: Rise of the machine

The goal of oncology is to provide the longest possible survival outcomes with the therapeutics that are currently available without sacrificing patients' quality of life. In lung cancer, several data points over a patient's diagnostic and treatment course are relevant to optimizing outcomes in the form of precision medicine, and artificial intelligence (AI) provides the opportunity to use available data from molecular information to radiomics, in combination with patient and tumor characteristics, to help clinicians provide individualized care. In doing so, AI can help create models to identify cancer early in diagnosis and deliver tailored therapy on the basis of available information, both at the time of diagnosis and in real time as they are undergoing treatment. The purpose of this review is to summarize the current literature in AI specific to lung cancer and how it applies to the multidisciplinary team taking care of these complex patients.

KDELR2-KIF20A axis facilitates bladder cancer growth and metastasis by enhancing Golgi-mediated secretion

Background

Bladder cancer (BCa) is a fatal form of cancer worldwide associated with a poor prognosis. Identifying novel drivers of growth and metastasis hold therapeutic potential for the disease. Transport homeostasis between the endoplasmic reticulum and Golgi and the secretion of matrix metalloproteinases (MMPs) mediated by Golgi have been reported to be closely associated with tumor progression. However, to date, mechanistic studies remain limited.

Results

Here, we identified KDELR2 as a potential risk factor with prognostic value in patients with BCa, especially those harbouring the KDELR2 amplification. In addition, we found that KDELR2 is a regulator of BCa cell proliferation and tumorigenicity based on bioinformatic analysis with functional studies. Mechanistically, we revealed that KDELR2 could regulate the expression of KIF20A, thus stimulating the expression of MMP2, MMP9 and MKI67. Functionally, the overexpression of KDELR2 and KIF20A markedly promoted proliferation, migration, and invasion in vitro and enhanced tumor growth in vivo, while knockdown of KDELR2 and KIF20A exerted the opposite effects. And the overexpression of KDELR2 also enhanced lymph node metastasis in vivo.

Conclusions

Collectively, our findings clarified a hitherto unexplored mechanism of KDELR2-KIF20A axis in increasing Golgi-mediated secretion of MMPs to drive tumor progression in BCa.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12575-022-00174-y.

UBE2T regulates epithelial–mesenchymal transition through the PI3K-AKT pathway and plays a carcinogenic role in ovarian cancer

Background

Ubiquitin-binding enzyme E2T (UBE2T), a member of the E2 family of the ubiquitin–proteasome pathway, is associated with tumorigenesis of varioustumours; however, its role and mechanism in ovarian cancer remain unclear.

Results

Our study revealed that UBE2T is highly expressed in ovarian cancer; this high expression was closely related to poor prognosis. Immunohistochemistry was used to validate the high expression of UBE2T in ovarian cancer. This is the first study to demonstrate that UBE2T expression is higher in ovarian cancer with BRCA mutation. Moreover, we demonstrated that UBE2T gene silencing significantly inhibited ovarian cancer cell proliferation and invasion. The epithelial–mesenchymal transition (EMT) of ovarian cancer cells and phosphatidylinositol 3 kinase/protein kinase B (PI3K-AKT) pathway were significantly inhibited. Adding the mechanistic target of rapamycin activator MHY1485 activated the PI3K-AKT pathway and significantly restored the proliferative and invasive ability of ovarian cancer cells. Furthermore, a tumorigenesis experiment in nude mice revealed that tumour growth on mice body surface and tumour tissue EMT were significantly inhibited after UBE2T gene silencing.

Conclusions

This study demonstrated that UBE2T regulates EMT via the PI3K-AKT pathway and plays a carcinogenic role in ovarian cancer. Moreover, UBE2T may interact with BRCA to affect ovarian cancer occurrence and development. Hence, UBE2T may be a valuable novel biomarker for the early diagnosis and prognosis and treatment of ovarian cancer. Further, UBE2T inhibition may be effective for treating ovarian cancer.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13048-022-01034-9.

KIF20A promotes the development of fibrosarcoma via PI3K-Akt signaling pathway

Adult fibrosarcoma is an aggressive subtype of soft tissue sarcoma (STS), in which high expression of KIF20A indicates a poor prognosis. However, the precise role of KIF20A in fibrosarcoma progression remains unknown. In this study, we initially examined KIF20A expression and function in the human fibrosarcoma cell line HT-1080. The results showed that KIF20A was highly expressed in HT-1080, knockdown of KIF20A impaired cell proliferation, migration, invasion and induced G2/M arrest and cell apoptosis. Transcriptome study suggested that PI3K-Akt signal pathway was involved in these biological changes. We confirmed that PI3K-Akt and NF-κB signaling pathways were impaired after the down-regulation of KIF20A, which can be reversed by the Akt activator SC79 in HT-1080 in vitro. In a xenograft mouse model, knockdown of KIF20A inhibited tumor growth, Ki67 expression and liver metastasis. Taken together, our results suggested that KIF20A promoted fibrosarcoma progression via PI3K-Akt signaling pathway and might be a potential therapeutic target for fibrosarcoma.

PLUS: Predicting cancer metastasis potential based on positive and unlabeled learning

Metastatic cancer accounts for over 90% of all cancer deaths, and evaluations of metastasis potential are vital for minimizing the metastasis-associated mortality and achieving optimal clinical decision-making. Computational assessment of metastasis potential based on large-scale transcriptomic cancer data is challenging because metastasis events are not always clinically detectable. The under-diagnosis of metastasis events results in biased classification labels, and classification tools using biased labels may lead to inaccurate estimations of metastasis potential. This issue is further complicated by the unknown metastasis prevalence at the population level, the small number of confirmed metastasis cases, and the high dimensionality of the candidate molecular features. Our proposed algorithm, called Positive and unlabeled Learning from Unbalanced cases and Sparse structures (PLUS), is the first to use a positive and unlabeled learning framework to account for the under-detection of metastasis events in building a classifier. PLUS is specifically tailored for studying metastasis that deals with the unbalanced instance allocation as well as unknown metastasis prevalence, which are not considered by other methods. PLUS achieves superior performance on synthetic datasets compared with other state-of-the-art methods. Application of PLUS to The Cancer Genome Atlas Pan-Cancer gene expression data generated metastasis potential predictions that show good agreement with the clinical follow-up data, in addition to predictive genes that have been validated by independent single-cell RNA-sequencing datasets.

Metastasis is the major cause of cancer-related deaths, and evaluations of metastasis risk are essential for tailored treatment of cancer patients. Existing methods often build a classifier using the clinical metastasis diagnoses as binary responses or detect genomic features significantly associated with metastasis-related survival outcomes. However, these methods tend to identify genomic predictors that have little consistency across different cancer types. Thus, there is an urgent need for a powerful tool to characterize the cancer metastasis potential applicable across a wide span of cancer types. Computational assessment of metastasis potential based on large-scale transcriptomic cancer data is challenging because metastasis events are not always clinically detectable, which results in biased estimations of metastasis potential. Our proposed algorithm, called PLUS, considers patients with metastasis diagnosis as positive instances and the remainder as unlabeled instances, meaning they are either metastatic or non-metastatic. Such a classifier given by PLUS rendered concordance between the predicted cancer metastasis and observed metastasis survival outcomes in the follow-up data for almost all cancer types considered. The selected genes were found to perform functions consistent with experimental research findings and are capable of clustering the single cells based on their levels of metastasis potential.

Ubiquitin-conjugating enzyme E2T regulates cell proliferation and migration in cholangiocarcinoma

Ubiquitin-conjugating enzyme E2T (UBE2T) is overexpressed in several human cancer cells, but a role in cholangiocarcinoma (CAA) progression has not been investigated. We analyzed the expression of UBE2T in CAA tissues. Then, we generated UBE2T deregulation models in which it was overexpressed or silenced, and examined the effects on CAA malignant progression by flow cytometry, western blot, MTT assay, wound healing assay and transwell assay. We report the involvement of UBE2T in CAA malignant progression. UBE2T was found to be highly expressed in human CAA cells both in vitro and in vivo. Overexpression of UBE2T significantly enhanced epithelial-to-mesenchymal transition, proliferation, migration and invasion of CAA cells in vitro, while silencing UBE2T had opposing effects. Furthermore, UBE2T appears to exert its effects via the mammalian target of rapamycin (mTOR) pathway as the cellular effects caused by UBE2T overexpression are inhibited by the mTOR inhibitor rapamycin. Our findings suggest that UBE2T may have potential as a new therapeutic target for the prevention or treatment of CAA.

Prediction of Lymph-Node Metastasis in Cancers Using Differentially Expressed mRNA and Non-coding RNA Signatures

Accurate prediction of lymph-node metastasis in cancers is pivotal for the next targeted clinical interventions that allow favorable prognosis for patients. Different molecular profiles (mRNA and non-coding RNAs) have been widely used to establish classifiers for cancer prediction (e.g., tumor origin, cancerous or non-cancerous state, cancer subtype). However, few studies focus on lymphatic metastasis evaluation using these profiles, and the performance of classifiers based on different profiles has also not been compared. Here, differentially expressed mRNAs, miRNAs, and lncRNAs between lymph-node metastatic and non-metastatic groups were identified as molecular signatures to construct classifiers for lymphatic metastasis prediction in different cancers. With this similar feature selection strategy, support vector machine (SVM) classifiers based on different profiles were systematically compared in their prediction performance. For representative cancers (a total of nine types), these classifiers achieved comparative overall accuracies of 81.00% (67.96-92.19%), 81.97% (70.83-95.24%), and 80.78% (69.61-90.00%) on independent mRNA, miRNA, and lncRNA datasets, with a small set of biomarkers (6, 12, and 4 on average). Therefore, our proposed feature selection strategies are economical and efficient to identify biomarkers that aid in developing competitive classifiers for predicting lymph-node metastasis in cancers. A user-friendly webserver was also deployed to help researchers in metastasis risk determination by submitting their expression profiles of different origins.

Inhibition of KIF20A by BKS0349 reduces endometriotic lesions in a xenograft mouse model

Several studies have suggested a possible etiological association between ovarian endometriosis and ovarian cancer. Evidence has shown that KIF20A overexpression might confer a malignant phenotype to ovarian tumors by promoting proliferation and inhibiting apoptosis. However, no data about the role of KIF20A in endometriosis have been described. In this study, the human endometrium (n = 4) was transfected by mCherry adenovirus and intraperitoneally implanted in mice. Subsequently, mice were divided in three groups (n = 8/group) that were treated with Vehicle, BKS0349 (KIF20A-antagonist) or cabergoline (dopamine receptor agonist) for 21 days. mCherry-labeled endometriotic lesions were monitored over time using the IVIS Imaging System. Mice were sacrificed 72 h after the last administration; proliferation was evaluated by immunohistochemistry and apoptosis by TUNEL. CCND1 gene expression (G1 phase-related gene) was measured by qRT-PCR. A significant reduction in mCherry-fluorescent signal was observed in the BKS0349 group after treatment ended (D24) compared with D0 (P-value = 0.0313). Moreover, the mCherry signal on D24 showed a significant decrease in the BKS0349 group compared with controls (P-value = 0.0303), along with significant size reduction of endometriotic lesions observed in the BKS0349 group compared with control on D24 (P-value = 0.0006). Functional studies showed a significant reduction in proliferating cells in the BKS0349-treated group compared with controls (P-value = 0.0082). In addition, CCND1 expression was decreased in the BKS0349 group compared with control (P-value = 0.049) at D24 and a significant increase in apoptotic cells among endometriotic lesions in BKS0349-treated mice was observed compared with control (P-value = 0.0317). Based on these findings, we concluded that BKS0349 induces apoptosis and inhibits cell proliferation, reducing endometriotic lesion size and suggesting KIF20A inhibition by BKS0349 as a novel therapeutic treatment for endometriosis.

Application of artificial intelligence in clinical non-small cell lung cancer

Lung cancer is the most common cause of cancer death in the world. Early diagnosis, screening and precise individualized treatment can significantly reduce the death rate of lung cancer. Artificial intelligence (AI) has been shown to be able to help clinicians make more accurate judgments and decisions in many ways. It has been involved in the screening of lung cancer, the judgment of benign and malignant degree of pulmonary nodules, the classification of histological cancer, the differentiation of histological subtypes, the identification of genomics, the judgment of the effectiveness of treatment and even the prognosis. AI has shown that it can be an excellent assistant for clinicians. This paper reviews the application of AI in the field of non-small cell lung cancer and describes the relevant progress. Although most of the studies to evaluate the clinical application of AI in non-small cell lung cancer have not been repeatable and generalizable, the research results highlight the efforts to promote the clinical application of AI technology and influence the future treatment direction.

Prediction of tumor metastasis from sequencing data in the era of genome sequencing

Tumor metastasis is the key reason for the high mortality rate of tumor. Growing number of scholars have begun to pay attention to the research on tumor metastasis and have achieved satisfactory results in this field. The advent of the era of sequencing has enabled us to study cancer metastasis at the molecular level, which is essential for understanding the molecular mechanism of metastasis, identifying diagnostic markers and therapeutic targets and guiding clinical decision-making. We reviewed the metastasis-related studies using sequencing data, covering detection of metastasis origin sites, determination of metastasis potential and identification of distal metastasis sites. These findings include the discovery of relevant markers and the presentation of prediction tools. Finally, we discussed the challenge of studying metastasis considering the difficulty of obtaining metastatic cancer data, the complexity of tumor heterogeneity and the uncertainty of sample labels.

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

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

Short Keynote Paper: Mainstreaming Personalized Healthcare-Transforming Healthcare Through New Era of Artificial Intelligence

Medicine has entered the digital era, driven by data from new modalities, especially genomics and imaging, as well as new sources such as wearables and Internet of Things. As we gain a deeper understanding of the disease biology and how diseases affect an individual, we are developing targeted therapies to personalize treatments. There is a need for technologies like Artificial Intelligence (AI) to be able to support predictions for personalized treatments. In order to mainstream AI in healthcare we will need to address issues such as explainability, liability and privacy. Developing explainable algorithms and including AI training in medical education are many of the solutions that can help alleviate these concerns.

KIF20A promotes cellular malignant behavior and enhances resistance to chemotherapy in colorectal cancer through regulation of the JAK/STAT3 signaling pathway

BACKGROUND/AIMS

Kinesin family member 20A (KIF20A) is upregulated in multiple cancers and plays important roles in promoting malignant behavior, whereas its exact role in CRC remains unknown.

RESULTS

Both genomic and protein expression levels showed that KIF20A was upregulated in CRC. Further functional analyses revealed that KIF20A had a crucial role in improving cell proliferation and resistance to chemotherapy in CRC. Finally, we provided distinct mechanistic evidence that KIF20A achieved all of its pathological functions in CRC by activating the JAK/STAT3 pathway.

CONCLUSION

Our results suggested that KIF20A regulated a set of malignant characteristics in CRC by activating the JAK/STAT3 pathway. Our findings indicate a new direction for the development of more effective therapeutic treatments for CRC.

METHODS

Three Gene Expression Omnibus datasets and The Cancer Genome Atlas datasets were used to investigate the expression level of KIF20A in CRC. Further experiments included immunohistochemical staining, western blot analysis, qRT-PCR, gene silencing, and a cell-injected xenograft mouse model to investigate the interaction between KIF20A and the JAK/STAT3 signaling pathway in both patient-derived specimens and CRC cell lines.

E2 ubiquitin-conjugating enzymes in cancer: Implications for immunotherapeutic interventions

Despite the medical advances of the 21st century, the incidence of cancer continues to increase and the search for a universal cure remains a major health challenge. Our lack of understanding the complex pathophysiology of the tumor microenvironment has hindered the development and efficiency of anti-cancer therapeutic strategies. The tumor microenvironment, composed of multiple cellular and non-cellular components, enables tumor-promoting processes such as proliferation, angiogenesis, migration and invasion, metastasis, and drug resistance. The ubiquitin-mediated degradation system is involved in several physiologic processes including cell cycling, signal transduction, receptor downregulation, endocytosis and transcriptional regulation. Ubiquitination includes attachment of ubiquitin to target proteins via E1 (activating), E2 (conjugating) and E3 (ligating) enzymes. Several studies have shown that E2 enzymes are dysregulated in variety of cancers. Multiple investigations have demonstrated the involvement of E2s in various tumor-promoting processes including DNA repair, cell cycle progression, apoptosis and oncogenic signaling. E2 enzymes consist of 40 members that facilitate ubiquitin-substrate conjugation thereby modulating the stability and interaction of various proteins. As such, E2s are potential biomarkers as diagnostic, prognostic and therapeutic tools. In this review, we discuss the role of E2s in modulating various types of cancer.

Identification of differentially expressed genes between primary lung cancer and lymph node metastasis via bioinformatic analysis

Lung cancer (LC), with its high morbidity and mortality rates, is one of the most widespread and malignant neoplasms. Mediastinal lymph node metastasis (MLNM) severely affects postoperative survival of patients with LC. Additionally, the molecular mechanisms of LC with MLNM (MM LC) remain not well understood. To identify the key biomarkers in its carcinogenesis and development, the datasets GSE23822 and GSE13213 were obtained from the Gene Expression Omnibus database. The differentially expressed genes (DEGs) were identified, and the Database for Annotation, Visualization and Integrated Discovery was used to perform functional annotations of DEGs. Search Tool for the Retrieval of Interacting Genes and Cytoscape were utilized to obtain the protein-protein interaction (PPI) network, and to analyze the most significant module. Subsequently, a Kaplan-Meier plotter was used to analyze overall survival (OS). Additionally, one co-expression network of the hub genes was obtained from cBioPortal. A total of 308 DEGs were identified in the two microarray datasets, which were mainly enriched during cellular processes, including the Gene Ontology terms ‘cell’, ‘catalytic activity’, ‘molecular function regulator’, ‘signal transducer activity’ and ‘binding’. The PPI network was composed of 315 edges and 167 nodes. Its significant module had 11 hub genes, and high expression of actin β, MYC, arginine vasopressin, vesicle associated membrane protein 2 and integrin subunit β1, and low expression of NOTCH1, synaptojanin 2 and intersectin 2 were significantly associated with poor OS. In summary, hub genes and DEGs presented in the present study may help identify underlying targets for diagnostic and therapeutic methods for MM LC.

Mechanisms of the Ase1/PRC1/MAP65 family in central spindle assembly

During cytokinesis, the organization of the spindle midzone and chromosome segregation is controlled by the central spindle, a microtubule cytoskeleton containing kinesin motors and non-motor microtubule-associated proteins. The anaphase spindle elongation 1/protein regulator of cytokinesis 1/microtubule associated protein 65 (Ase1/PRC1/MAP65) family of microtubule-bundling proteins are key regulators of central spindle assembly, mediating microtubule crosslinking and spindle elongation in the midzone. Ase1/PRC1/MAP65 serves as a complex regulatory platform for the recruitment of other midzone proteins at the spindle midzone. Herein, we summarize recent advances in understanding of the structural domains and molecular kinetics of the Ase1/PRC1/MAP65 family. We summarize the regulatory network involved in post-translational modifications of Ase1/PRC1 by cyclin-dependent kinase 1 (Cdk1), cell division cycle 14 (Cdc14) and Polo-like kinase 1 (Plk1) and also highlight multiple functions of Ase1/PRC1 in central spindle organization, spindle elongation and cytokinesis during cell division.

KIF20A Affects the Prognosis of Bladder Cancer by Promoting the Proliferation and Metastasis of Bladder Cancer Cells

Objective

To investigate the expression of kinesin family member 20A (KIF20A) in bladder cancer, the effect of KIF20A on the proliferation and metastasis of bladder cancer cells, and the effect of KIF20A expression on the prognosis of bladder cancer patients.

Methods

Bladder cancer tissue and its adjacent tissues were collected from tumour patients. The mRNA and protein expression levels of KIF20A in the tissue samples were detected by qRT-PCR and western blot. Immunohistochemical (IHC) staining was used to identify the expression and distribution of KIF20A proteins in the tissue samples. The relationship between the KIF20A expression and the clinical pathology of bladder cancer was analysed. The effect of the differential expression of KIF20A on the prognosis of patients with bladder cancer was analysed by the TCGA database. The plasmid was transfected into the bladder cell lines T24 and 5637 to construct two stable cell lines with knocked down KIF20A. The effect of KIF20A expression on the proliferation and invasion of T24 and 5637 bladder cells was explored in vitro using the abovementioned stable cell lines. The effect of the KIF20A expression on the proliferation of bladder cancer cells was evaluated by a mouse xenograft model.

Results

The expression of KIF20A was significantly higher in the bladder cancer tissues than in the adjacent control tissues. The expression of KIF20A was significantly associated with the degree of pathological differentiation of bladder cancer. Patients with a higher expression of KIF20A had a higher tumour grade and a more advanced stage. The mean survival of patients with a high KIF20A expression was significantly lower than the mean survival of patients with a low KIF20A expression. The in vitro experiments demonstrated that the knockdown of KIF20A significantly inhibited T24 and 5637 cell proliferation and invasion. The in vivo experiments showed that the knockdown of KIF20A significantly inhibited the proliferation of the bladder tumours.

Conclusion

KIF20A promotes the proliferation and metastasis of bladder cancer cells. Bladder cancer patients with a high KIF20A expression have a worse tumour differentiation and a poor prognosis. KIF20A may become an independent factor that affects the prognosis of bladder cancer patients and a therapeutic target for bladder cancer.

ZWINT is the next potential target for lung cancer therapy

PURPOSE

We aimed to analyze the expression of ZWINT, NUSAP1, DLGAP5, and PRC1 in tumor tissues and adjacent tissues with public data.

METHODS

The expression patterns of four genes were detected in cancer tissues and adjacent tissues by qRT-PCR. The overall survival analysis was used to explore these genes in lung adenocarcinoma and squamous cell carcinoma patients. Knockdown assays were used to select the most suitable gene among these four genes. Cell function assays with the knockdown gene were conducted in A549 and NCL H226 cells. The role of the knockdown gene in lung cancer was dissected in a mice tumor model. Transcriptome sequencing analyses with the knockdown gene were analyzed.

RESULTS

Overexpression of these genes was significantly detected in cancer tissues (P < 0.01). Overall survival revealed that high expression of these genes is closely related with poor prognosis of lung adenocarcinoma patients (P < 0.05). Knockdown of ZWINT reduced proliferation in NCI H226 and A549 cells (P < 0.05). Knockdown also inhibited cell migration, invasion, apoptosis, and colony formation (P < 0.05). ZWINT knockdown reduced tumor volume (P < 0.05). Transcriptome sequencing of ZWINT knockdown-treated A549 and NCI H226 cells indicated that 100 and 426 differentially expressed genes were obtained, respectively. Gene ontology analysis suggested that binding, biological regulation, and multicellular organismal processes were the most enriched. KEGG analysis revealed that TNF, P53, and PI3K signal networks would be the most potential ZWINT-related pathways and were identified by Western blot analysis.

CONCLUSIONS

ZWINT may be a novel target for lung cancer therapy.

Clinically Relevant Post-Translational Modification Analyses-Maturing Workflows and Bioinformatics Tools

Post-translational modifications (PTMs) can occur soon after translation or at any stage in the lifecycle of a given protein, and they may help regulate protein folding, stability, cellular localisation, activity, or the interactions proteins have with other proteins or biomolecular species. PTMs are crucial to our functional understanding of biology, and new quantitative mass spectrometry (MS) and bioinformatics workflows are maturing both in labelled multiplexed and label-free techniques, offering increasing coverage and new opportunities to study human health and disease. Techniques such as Data Independent Acquisition (DIA) are emerging as promising approaches due to their re-mining capability. Many bioinformatics tools have been developed to support the analysis of PTMs by mass spectrometry, from prediction and identifying PTM site assignment, open searches enabling better mining of unassigned mass spectra-many of which likely harbour PTMs-through to understanding PTM associations and interactions. The remaining challenge lies in extracting functional information from clinically relevant PTM studies. This review focuses on canvassing the options and progress of PTM analysis for large quantitative studies, from choosing the platform, through to data analysis, with an emphasis on clinically relevant samples such as plasma and other body fluids, and well-established tools and options for data interpretation.

DNA methylation regulates Microtubule-associated tumor suppressor 1 in human non-small cell lung carcinoma

Microtubule associated tumor suppressor 1 (MTUS1) has been recognized as a tumor suppressor gene in multiple cancers. However, the molecular mechanisms underlying the regulation of MTUS1 are yet to be investigated. This study aimed to clarify the significance of DNA methylation in silencing MTUS1 expression. We report that MTUS1 acts as tumor suppressor in non-small cell lung carcinoma (NSCLC). Analysis of in silico database and subsequent knockdown of DNMT1 suggested an inverse correlation between DNMT1 and MTUS1 function. Interestingly, increased methylation at MTUS1 promoter is associated with low expression of MTUS1. Treatment with DNA methyltransferases (DNMTs) inhibitor, 5-aza-2'-deoxycytidine (AZA) leads to both reduced promoter methylation accompanied with enrichment of H3K9Ac and enhanced MTUS1 expression. Remarkably, knockdown of MTUS1 showed increased proliferation and migration of NSCLC cells in contrast to diminished proliferation and migration, upon treatment with AZA. We concluded that low expression of MTUS1 correlates to DNA methylation and histone deacetylation in human NSCLC.

Identification of Candidate Biomarkers Correlated With the Pathogenesis and Prognosis of Non-small Cell Lung Cancer via Integrated Bioinformatics Analysis

Background and Objective: Non-small cell lung cancer (NSCLC) accounts for 80-85% of all patients with lung cancer and 5-year relative overall survival (OS) rate is less than 20%, so that identifying novel diagnostic and prognostic biomarkers is urgently demanded. The present study attempted to identify potential key genes associated with the pathogenesis and prognosis of NSCLC. Methods: Four GEO datasets (GSE18842, GSE19804, GSE43458, and GSE62113) were obtained from the Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between NSCLC samples and normal ones were analyzed using limma package, and RobustRankAggreg (RRA) package was used to conduct gene integration. Moreover, Search Tool for the Retrieval of Interacting Genes database (STRING), Cytoscape, and Molecular Complex Detection (MCODE) were utilized to establish protein-protein interaction (PPI) network of these DEGs. Furthermore, functional enrichment and pathway enrichment analyses for DEGs were performed by Funrich and OmicShare. While the expressions and prognostic values of top genes were carried out through Gene Expression Profiling Interactive Analysis (GEPIA) and Kaplan Meier-plotter (KM) online dataset. Results: A total of 249 DEGs (113 upregulated and 136 downregulated) were identified after gene integration. Moreover, the PPI network was established with 166 nodes and 1784 protein pairs. Topoisomerase II alpha (TOP2A), a top gene and hub node with higher node degrees in module 1, was significantly enriched in mitotic cell cycle pathway. In addition, Interleukin-6 (IL-6) was enriched in amb2 integrin signaling pathway. The mitotic cell cycle was the most significant pathway in module 1 with the highest P-value. Besides, five hub genes with high degree of connectivity were selected, including TOP2A, CCNB1, CCNA2, UBE2C, and KIF20A, and they were all correlated with worse OS in NSCLC. Conclusion: The results showed that TOP2A, CCNB1, CCNA2, UBE2C, KIF20A, and IL-6 may be potential key genes, while the mitotic cell cycle pathway may be a potential pathway contribute to progression in NSCLC. Further, it could be used as a new biomarker for diagnosis and to direct the synthesis medicine of NSCLC.

Identification of candidate biomarkers and pathways associated with SCLC by bioinformatics analysis

Small cell lung cancer (SCLC) is one of the highly malignant tumors and a serious threat to human health. The aim of the present study was to explore the underlying molecular mechanisms of SCLC. mRNA microarray datasets GSE6044 and GSE11969 were downloaded from Gene Expression Omnibus database, and the differentially expressed genes (DEGs) between normal lung and SCLC samples were screened using GEO2R tool. Functional and pathway enrichment analyses were performed for common DEGs using the DAVID database, and the protein-protein interaction (PPI) network of common DEGs was constructed by the STRING database and visualized with Cytoscape software. In addition, the hub genes in the network and module analysis of the PPI network were performed using CentiScaPe and plugin Molecular Complex Detection. Finally, the mRNA expression levels of hub genes were validated in the Oncomine database. A total of 150 common DEGs with absolute fold-change >0.5, including 66 significantly downregulated DEGs and 84 upregulated DEGs were obtained. The Gene Ontology term enrichment analysis suggested that common upregulated DEGs were primarily enriched in biological processes (BPs), including ‘cell cycle’, ‘cell cycle phase’, ‘M phase’, ‘cell cycle process’ and ‘DNA metabolic process’. The common downregulated genes were significantly enriched in BPs, including ‘response to wounding’, ‘positive regulation of immune system process’, ‘immune response’, ‘acute inflammatory response’ and ‘inflammatory response’. Kyoto Encyclopedia of Genes and Genomes pathway analysis identified that the common downregulated DEGs were primarily enriched in the ‘complement and coagulation cascades’ signaling pathway; the common upregulated DEGs were mainly enriched in ‘cell cycle’, ‘DNA replication’, ‘oocyte meiosis’ and the ‘mismatch repair’ signaling pathways. From the PPI network, the top 10 hub genes in SCLC were selected, including topoisomerase IIα, proliferating cell nuclear antigen, replication factor C subunit 4, checkpoint kinase 1, thymidylate synthase, minichromosome maintenance protein (MCM) 2, cell division cycle (CDC) 20, cyclin dependent kinase inhibitor 3, MCM3 and CDC6, the mRNA levels of which are upregulated in Oncomine SCLC datasets with the exception of MCM2. Furthermore, the genes in the significant module were enriched in ‘cell cycle’, ‘DNA replication’ and ‘oocyte meiosis’ signaling pathways. Therefore, the present study can shed new light on the understanding of molecular mechanisms of SCLC and may provide molecular targets and diagnostic biomarkers for the treatment and early diagnosis of SCLC.

KIF20A expression as a prognostic indicator and its possible involvement in the proliferation of ovarian clear‑cell carcinoma cells

Kinesin family member 20A (KIF20A), which is involved in cytokinesis and intracellular transportation, has been recently reported to be upregulated in several malignancies and may contribute to chemotherapeutic resistance. We examined the distribution and expression of KIF20A in clear‑cell carcinoma (CCC) of the ovary to elucidate its clinical significance and molecular mechanism. Paraffin sections from ovarian CCC tissues (N=43) were immunostained with KIF20A antibody, and the staining intensities were semi‑quantitatively evaluated. Furthermore, we investigated whether silencing of KIF20A contributes to the proliferation‑inhibitory potential using CCC cells. During the observational period, 18 patients (41.9%) developed recurrence. The median time to recurrence was 11.5 months. Patients in the high KIF20A expression group showed poorer progression‑free survival (PFS) and overall survival (OS) than those in the low expression group (P=0.0443 and P=0.0478, respectively). In multivariable analyses, KIF20A expression was also a significantly independent indicator of PFS and a marginally significant indicator of OS [PFS: HR (high vs. low), 5.488; 95% CI, 1.410‑24.772 (P=0.0136); OS: HR, 2.835; 95% CI, 0.854‑11.035, (P=0.0897)]. In in vitro studies, the ovarian CCC cell proliferation was significantly decreased by KIF20A silencing or in the presence of KIF20A inhibitor in CCC cells. Cell cycle G2/M arrest and a higher apoptosis‑induced fraction were more frequently observed in si‑KIF20A‑transfected CCC cells than in the control cells. Although the present study was preliminary, these data indicate the possible involvement of KIF20A in the proliferation of CCC, suggesting that targeting this molecule may contribute to reversing the malignant potential consequently affecting the oncologic outcome of CCC patients.

Role of artificial intelligence in the care of patients with nonsmall cell lung cancer

BACKGROUND

Lung cancer is the leading cause of cancer death worldwide. In up to 57% of patients, it is diagnosed at an advanced stage and the 5-year survival rate ranges between 10%-16%. There has been a significant amount of research using machine learning to generate tools using patient data to improve outcomes.

METHODS

This narrative review is based on research material obtained from PubMed up to Nov 2017. The search terms include "artificial intelligence," "machine learning," "lung cancer," "Nonsmall Cell Lung Cancer (NSCLC)," "diagnosis" and "treatment."

RESULTS

Recent studies support the use of computer-aided systems and the use of radiomic features to help diagnose lung cancer earlier. Other studies have looked at machine learning (ML) methods that offer prognostic tools to doctors and help them in choosing personalized treatment options for their patients based on molecular, genetics and histological features. Combining artificial intelligence approaches into health care may serve as a beneficial tool for patients with NSCLC, and this review outlines these benefits and current shortcomings throughout the continuum of care.

CONCLUSION

We present a review of the various applications of ML methods in NSCLC as it relates to improving diagnosis, treatment and outcomes.

Cell cycle-related and expression-elevated protein in tumor overexpression is associated with proliferation behaviors and poor prognosis in non-small-cell lung cancer

The cell cycle‐related and expression‐elevated protein in tumor (CREPT) is overexpressed in several human malignancies. However, the clinical relevance of CREPT expression and its biological role in non‐small‐cell lung cancer (NSCLC) remains unclear. In this study, we detected the expression of CREPT in both NSCLC tissues and cell lines by immunohistochemistry, Western blot analysis, and RT‐PCR. The correlation between CREPT expression and clinicopathologic features was analyzed in 271 NSCLC patients. The prognostic value of CREPT expression was evaluated by Kaplan–Meier analysis and Cox regression analysis. CREPT was overexpressed in Calu‐1 cell lines by using plasmid vector and its biological function was explored both in vitro and in vivo. We found that CREPT was significantly overexpressed in NSCLC compared with paired adjacent non‐tumor tissues, and the expression level of CREPT was correlated with tumor differentiation, lymph node metastasis, and clinical stage. Kaplan–Meier analysis showed that the recurrence‐free survival and overall survival of high CREPT expression groups were significantly shorter than those of the low CREPT expression group. Multivariate analysis identified that CREPT might be an independent biomarker for the prediction of NSCLC prognosis. Overexpression of CREPT increased cell proliferation and enhanced the migration and invasion ability of Calu‐1 cells (a human NSCLC cell line with relative low CRPET expression) in vitro. Moreover, CREPT overexpression promoted tumor growth in a nude mice model. These results suggest that CREPT is closely relevant to the proliferation of NSCLC cells and it might be a potential prognostic marker in NSCLC patients.

PRC1: Linking Cytokinesis, Chromosomal Instability, and Cancer Evolution

Cytokinesis is the final event of the cell cycle dividing one cell into two daughter cells. The protein regulator of cytokinesis (PRC)1 is essential for cytokinesis and normal cell cleavage. Deregulation of PRC1 causes cytokinesis defects that promote chromosomal instability (CIN) and thus tumor heterogeneity and cancer evolution. Consistently, abnormal PRC1 expression correlates with poor patient outcome in various malignancies, which may be caused by PRC1-mediated CIN and aneuploidy. Here, we review the physiological functions of PRC1 in cell cycle regulation and its contribution to tumorigenesis and intratumoral heterogeneity. We discuss targeting PRC1 within the complementary approaches of either normalizing CIN in aneuploid cancers or creating chromosomal chaos in genomically stable cancers to induce apoptosis.

Characterization of KIF11 as a novel prognostic biomarker and therapeutic target for oral cancer

Oral cancer has a high mortality rate, and its incidence is increasing gradually worldwide. As the effectiveness of standard treatments is still limited, the development of new therapeutic strategies is eagerly awaited. Kinesin family member 11 (KIF11) is a motor protein required for establishing a bipolar spindle in cell division. The role of KIF11 in oral cancer is unclear. Therefore, the present study aimed to assess the role of KIF11 in oral cancer and evaluate its role as a prognostic biomarker and therapeutic target for treating oral cancer. Immunohistochemical analysis demonstrated that KIF11 was expressed in 64 of 99 (64.6%) oral cancer tissues but not in healthy oral epithelia. Strong KIF11 expression was significantly associated with poor prognosis among oral cancer patients (P=0.034), and multivariate analysis confirmed its independent prognostic value. In addition, inhibition of KIF11 expression by transfection of siRNAs into oral cancer cells or treatment of cells with a KIF11 inhibitor significantly suppressed cell proliferation, probably through G2/M arrest and subsequent induction of apoptosis. These results suggest that KIF11 could be a potential prognostic biomarker and therapeutic target for oral cancer.

miR-196b, miR-378a and miR-486 are predictive biomarkers for the efficacy of vaccine treatment in colorectal cancer

MicroRNAs (miRNAs/miRs) regulate the levels of transcripts and serve a critical function in the regulation of tumor microenvironments. Therefore, miRNA levels in cancer tissues are thought to be potential biomarkers for immunotherapy. From a phase I trial of a vaccine treatment using 5 human leukocyte antigen (HLA)-A*2402-restricted peptides (registration no. UMIN000004948), colorectal cancer (CRC) tissues were obtained from 8 patients and normal colorectal tissues from 5 patients via surgery. From a phase II trial using the same peptides (registration no. UMIN000001791), CRC tissues were obtained from 16 patients from the HLA-A*2402-matched group and 10 patients from the HLA-A*2402-unmatched group. These tissues were used for miRNA microarray analysis. As the first step, cancer tissues from the phase I study were used and 10 candidate miRNAs were selected by comparing the miRNA expression between two groups; one with improved prognosis and the other with poor prognosis. The miRNAs were subsequently validated using the cases enrolled in the phase II study. Significantly improved prognoses were identified in 16 patients in the HLA-A*2402-matched group with high expression of miR-196b-5p and low expression of miR-378a-3p and miR-486-5p. There was no difference in prognosis in the 10 patients in the HLA-A*2402-unmatched group. Therefore, high miR-196b expression and low miR-378a-3p and miR-486-5p expression were indicated as useful biomarkers for prediction of the efficacy of vaccine treatment for patients with metastatic CRC. In a planned phase III study, expression levels of these 3 miRNAs (miR-196b-5p, miR-378a-3p and miR-486-5p) may be useful biomarkers for assessing patients who are likely to have an improved outcome following vaccination.

Quantitative analysis and clonal characterization of T-cell receptor β repertoires in patients with advanced non-small cell lung cancer treated with cancer vaccine

With the development of cancer immunotherapy that may activate T cells, a practical and quantitative method to improve monitoring and/or prediction of immunological response of patients as a predictive biomarker is of importance. To examine possible biomarkers for a therapeutic cancer vaccine containing a mixture of three epitope peptides derived from cell division-associated 1, lymphocyte antigen 6 complex locus K and insulin-like growth factor-II mRNA-binding protein 3, T-cell receptor β (TCRβ) repertoires of blood samples from 24 patients with human leukocyte antigen-A*2402-positive non-small cell lung cancer were characterized prior to and following 8 weeks of the cancer vaccine treatment, by applying a next-generation sequencing method. It was identified that 14 patients with overall survival (OS) times of ≥12 months had significantly lower TCRβ diversity indexes in samples prior to treatment, compared with 10 patients who succumbed within 1 year (P=0.03). In addition, patients with a high level of activated CD8⁺ T cells that are defined by a high granzyme A/CD8 ratio had favorable OS rates (log-rank test, P=0.04). The TCRβ diversity index and immunogenic gene markers following vaccine administration may serve as predictive or monitoring biomarkers for cancer vaccine treatment.

Knockdown of UBE2T Inhibits Osteosarcoma Cell Proliferation, Migration, and Invasion by Suppressing the PI3K/Akt Signaling Pathway

Ubiquitin-conjugating enzyme E2T (UBE2T), a member of the E2 family, was found to be overexpressed in a great many cancers such as bladder cancer, lung cancer, and prostate cancer. However, there have been no reports on the role of UBE2T in osteosarcoma. In this study, we tried to make the effects of UBE2T on osteosarcoma clear. The study results showed that UBE2T was overexpressed in osteosarcoma tissues and cell lines. Moreover, UBE2T knockdown inhibited osteosarcoma cell proliferation, migration, and invasion. We also observed that UBE2T downregulation could suppress the activity of the PI3K/Akt signaling pathway. Therefore, we concluded that UBE2T exerted its inhibitory effects on osteosarcoma cells via suppressing the PI3K/Akt signaling pathway. These findings indicated that UBE2T may be a potential therapeutic target for osteosarcoma treatment.

Identification of differentially-expressed genes between early-stage adenocarcinoma and squamous cell carcinoma lung cancer using meta-analysis methods

Lung adenocarcinoma (AC) and squamous cell lung carcinoma (SCC) are two major subtypes of non-small cell lung cancer (NSCLC). Previous studies have demonstrated that fundamental differences exist in the underlying mechanisms of tumor development, growth and invasion between these subtypes. The investigation of differentially-expressed genes (DEGs) between these two NSCLC subtypes is useful for determining and understanding such differences. The present study aimed to identify those DEGs using meta-analysis and the data from four microarray experiments, consisting of 164 AC and 161 SCC samples. Raw gene expression values were converted into the probability of expression (POE) representing the differentially-expressed probability of a gene and expression barcode values representing its expression status. The results indicated that when applying a meta-analysis using barcode values, heterogeneity in genes across studies was less severe than when applying a meta-analysis using POE values. DEGs in each meta-analysis method overlapped substantially (P=1.3×10^-4), but the barcode method yielded a lower global false discovery rate. Based on this and several other performance statistics, it was concluded that the barcode approach outperformed the POE method. Finally, using those DEGs, ontology and pathway analyses were conducted. A number of genes and enriched pathways were found to be closely associated with NSCLC.

ABCB1 2677G>T/A variant enhances chemosensitivity to anti-cancer agents acting on microtubule dynamics through LAMP1 inhibition

Overexpression of ABCB1 associated with single nucleotide variants in cancers was reported to encode a protein responsible for drug resistance. We studied chemosensitivity-related genes associated with ABCB1 2677G>T/A variant. The associated genes were identified based on the results of the significance analysis of microarray, and then prediction accuracy was evaluated using the prediction analysis of microarray. Functional assay of the selected gene was performed by using siRNA and drug accumulation study. A higher frequency of chemoresistance to microtubule-modulating agents was found in cell lines with wild-type ABCB1 compared to cell lines with 2677G>T/A ABCB1 variant. Based on the pharmacogenetic association study with 2677 variant, we identified seven genes that could predict chemosensitivity to microtubule dynamics modulators. The classification accuracy with these seven genes was 90.0%, and the predicted probability was 0.73. LAMP1 was the only gene that was commonly related to chemosensitivity. LAMP1 expression levels were relatively higher in chemoresistant ABCB1 wild-type compared to chemosensitive polymorphic cells. But, there was no difference in ABCB1 expression levels between the two groups. Following LAMP1 siRNA, chemosensitivity was restored due to increased intracellular drug accumulation in wild type cell line. In conclusion, ABCB1 2677G>T/A variant enhances chemosensitivity on microtubule dynamics through LAMP1 inhibition.

Prediction of the efficacy of immunotherapy by measuring the integrity of cell-free DNA in plasma in colorectal cancer

We previously reported a phase II study of a cancer vaccine using five novel peptides recognized by HLA‐A*2402‐restricted CTL in combination with oxaliplatin‐containing chemotherapy (FXV study) as first‐line therapy for patients with metastatic colorectal cancer and demonstrated the safety and promising potential of our five‐peptide cocktail. The objective of this analysis was to identify predictive biomarkers for identifying patients who are likely to receive a clinical benefit from immunochemotherapy. Circulating cell‐free DNA (cfDNA) in plasma has been reported to be a candidate molecular biomarker for the efficacy of anticancer therapy. Unlike uniformly truncated small‐sized DNA released from apoptotic normal cells, DNA released from necrotic cancer cells varies in size. The integrity of plasma cfDNA (i.e. the ratio of longer fragments [400 bp] to shorter fragments [100 bp] of cfDNA), may be clinically useful for detecting colorectal cancer progression. We assessed plasma samples collected from 93 patients prior to receiving immunochemotherapy. The cfDNA levels and integrity were analyzed by semi‐quantitative real‐time PCR. Progression‐free survival was significantly better in patients with a low plasma cfDNA integrity value than in those with a high value (P = 0.0027). Surprisingly, in the HLA‐A*2402‐matched group, patients with a low plasma cfDNA integrity value had significantly better progression‐free survival than those with a high value (P = 0.0015). This difference was not observed in the HLA‐A*2402‐unmatched group. In conclusion, the integrity of plasma cfDNA may provide important clinical information and may be a useful predictive biomarker of the outcome of immunotherapy in metastatic colorectal cancer.

Cell division cycle associated 1 as a novel prognostic biomarker and therapeutic target for oral cancer

Oral cavity carcinoma (OCC) is one of the most common causes of cancer-related death worldwide and has poor clinical outcome after standard therapies. Therefore, new prognostic biomarkers and therapeutic targets for OCC are urgently needed. We selected cell division cycle associated 1 (CDCA1) as a candidate OCC biomarker. Immunohistochemical analysis confirmed that CDCA1 protein was expressed in 67 of 99 OCC tissues (67.7%), but not in healthy oral epithelia. CDCA1 expression was significantly associated with poor prognosis in OCC patients (P=0.0244). Knockdown of CDCA1 by siRNAs significantly increased apoptosis of tumor cells. These data suggest that CDCA1 represents a novel prognostic biomarker and therapeutic target for OCC.

Biomarker development in the precision medicine era: lung cancer as a case study

Precision medicine relies on validated biomarkers with which to better classify patients by their probable disease risk, prognosis and/or response to treatment. Although affordable 'omics'-based technology has enabled faster identification of putative biomarkers, the validation of biomarkers is still stymied by low statistical power and poor reproducibility of results. This Review summarizes the successes and challenges of using different types of molecule as biomarkers, using lung cancer as a key illustrative example. Efforts at the national level of several countries to tie molecular measurement of samples to patient data via electronic medical records are the future of precision medicine research.

Elevated expression of UBE2T exhibits oncogenic properties in human prostate cancer

Increased expression of ubiquitin-conjugating enzyme E2T (UBE2T) is reported in human prostate cancer. However, whether UBE2T plays any functional role in prostate cancer development remains unknown. We here report the first functional characterization of UBE2T in prostate carcinogenesis. Prostate cancer tissue array analysis confirmed upregulation of UBE2T in prostate cancer, especially these with distant metastasis. Moreover, higher level of UBE2T expression is associated with poorer prognosis of prostate cancer patients. Ectopic expression of UBE2T significantly promotes prostate cancer cell proliferation, motility and invasion, while UBE2T depletion by shRNA significantly inhibits these abilities of prostate cancer cells. Xenograft mouse model studies showed that overexpression of UBE2T promotes whereas UBE2T depletion inhibits tumor formation and metastasis significantly. Collectively, we identify critical roles of UBE2T in prostate cancer development and progression. These findings may serve as a framework for future investigations designed to more comprehensive determination of UBE2T as a potential therapeutic target.

Centrosomal Protein of 55 Regulates Glucose Metabolism, Proliferation and Apoptosis of Glioma Cells via the Akt/mTOR Signaling Pathway

Introduction: Glioma is one of the most common and most aggressive brain tumors in humans. The molecular and cellular mechanisms responsible for the onset and the progression of glioma are elusive and controversial. Centrosomal protein of 55 (CEP55) was initially described as a highly coiled-coil protein that plays critical roles in cell division, but was recently identified as being overexpressed in many human cancers. The function of CEP55 has not previously been characterized in glioma. We aim to discover the effect and mechanism of CEP55 in glioma development.

Method: qRT-PCR and immunohistochemistry were used to analyze CEP55 expression. Glucose uptake, western blot, MTS, CCK-8, Caspase-3 activity and TUNEL staining assays were performed to investigate the role and mechanism of CEP55 on glioma cell process.

Results: We found that the levels of CEP55 expression were upregulated in glioma. In addition, CEP55 appeared to regulate glucose metabolism of glioma cells. Furthermore, knockdown of CEP55 inhibited cell proliferation and induced cell apoptosis in glioma. Finally, we provided preliminary evidence that knockdown of CEP55 inhibited glioma development via suppressing the activity of Akt/mTOR signaling.

Conclusions: Our results demonstrated that CEP55 regulates glucose metabolism, proliferation and apoptosis of glioma cells via the Akt/mTOR signaling pathway, and its promotive effect on glioma tumorigenesis can be a potential target for glioma therapy in the future.

Ubiquitin-Conjugating Enzyme E2T is an Independent Prognostic Factor and Promotes Gastric Cancer Progression

Ubiquitin-conjugating enzyme E2T (UBE2T) is a member of the E2 family that mediates the ubiquitin-proteasome system and regulates gene expression. It is a major oncogene in several cancers such as lung cancer and breast cancer, while the potential functions of UBE2T in gastric cancer (GC) remains largely unknown. Here, we identified the roles of UBE2T in GC progression and its potential to act as a prognostic marker of GC. Our data demonstrated that UBE2T was significantly upregulated in gastric cancer tissues, and the high expression of UBE2T was significantly correlated with poor differentiation, high T classification, and poor prognosis. In vitro experiments indicated that UBE2T promoted cell proliferation and inhibited cell cycle arrest. In addition, we observed that UBE2T modulated cell mobility by inducing epithelial-mesenchymal transition. Collectively, these findings suggest that UBE2T plays an important role in the tumorigenesis of gastric cancer and could act as a potential independent prognostic factor for cancer therapy.

Profile of farletuzumab and its potential in the treatment of solid tumors

Folate receptor (FR) α expression in normal tissues is restricted to a subpopulation of epithelial cells. In contrast, FRα is overexpressed in epithelial ovarian cancer (EOC) and non-small-cell lung carcinoma. Therefore, FRα is considered a promising therapeutic target for EOC and non-small-cell lung carcinoma. Farletuzumab (MORAb-003) is a humanized monoclonal antibody of immunoglobulin G subtype 1 kappa, targeting human FRα. To date, Phase I/II clinical trials have clearly demonstrated the feasibility and safety of farletuzumab as a treatment option against solid tumors. However, in Phase III clinical trial that was conducted to verify the combined effect of paclitaxel-carboplatin combination therapy and farletuzumab for patients with recurrent EOC, improvement in progression-free survival was not statistically significant. This result might be owing to the fact that the eligibility criteria for these studies did not include FRα expression. The significance of FRα as a predictive/prognostic biomarker remains unclear. In addition, there is currently no established biomarker to predict the response and toxicities among patients receiving farletuzumab therapy. Furthermore, the primary mechanism of action of farletuzumab has not yet been identified. Therefore, further research to identify the mechanism of farletuzumab in tumor suppression is necessary to clarify the full potential of this chemotherapeutic agent.

New MKLP-2 inhibitors in the paprotrain series: Design, synthesis and biological evaluations

Members of the kinesin superfamily are involved in key functions during intracellular transport and cell division. Their involvement in cell division makes certain kinesins potential targets for drug development in cancer chemotherapy. The two most advanced kinesin targets are Eg5 and CENP-E with inhibitors in clinical trials. Other mitotic kinesins are also being investigated for their potential as prospective drug targets. One recently identified novel potential cancer therapeutic target is the Mitotic kinesin-like protein 2 (MKLP-2), a member of the kinesin-6 family, which plays an essential role during cytokinesis. Previous studies have shown that inhibition of MKLP-2 leads to binucleated cells due to failure of cytokinesis. We have previously identified compound 1 (paprotrain) as the first selective inhibitor of MKLP-2. Herein we describe the synthesis and biological evaluation of new analogs of 1. Our structure-activity relationship (SAR) study reveals the key chemical elements in the paprotrain family necessary for MKLP-2 inhibition. We have successfully identified one MKLP-2 inhibitor 9a that is more potent than paprotrain. In addition, in vitro analysis of a panel of kinesins revealed that this compound is selective for MKLP-2 compared to other kinesins tested and also does not have an effect on microtubule dynamics. Upon testing in different cancer cell lines, we find that the more potent paprotrain analog is also more active than paprotrain in 10 different cancer cell lines. Increased selectivity and higher potency is therefore a step forward toward establishing MKLP-2 as a potential cancer drug target.

Integrated analyses of copy number variations and gene differential expression in lung squamous-cell carcinoma

Background

Although numerous efforts have been made, the pathogenesis underlying lung squamous-cell carcinoma (SCC) remains unclear. This study aimed to identify the CNV-driven genes by an integrated analysis of both the gene differential expression and copy number variation (CNV).

Results

A higher burden of the CNVs was found in 10–50 kb length. The 16 CNV-driven genes mainly located in chr 1 and chr 3 were enriched in immune response [e.g. complement factor H (CFH) and Fc fragment of IgG, low affinity IIIa, receptor (FCGR3A)], starch and sucrose metabolism [e.g. amylase alpha 2A (AMY2A)]. Furthermore, 38 TFs were screened for the 9 CNV-driven genes and then the regulatory network was constructed, in which the GATA-binding factor 1, 2, and 3 (GATA1, GATA2, GATA3) jointly regulated the expression of TP63.

Conclusions

The above CNV-driven genes might be potential contributors to the development of lung SCC.

Revisiting the transcriptional analysis of primary tumours and associated nodal metastases with enhanced biological and statistical controls: application to thyroid cancer

Background:

Transcriptome profiling has helped characterise nodal spread. The interpretation of these data, however, is not without ambiguities.

Methods:

We profiled the transcriptomes of papillary thyroid cancer nodal metastases, associated primary tumours and primary tumours from N0 patients. We also included patient-matched non-cancerous thyroid and lymph node samples as controls to address some limits of previous studies.

Results:

The transcriptomes of patient-matched primary tumours and metastases were more similar than those of unrelated metastases/primary pairs, as previously reported in other organ systems. This similarity partly reflected patient background. Lymphoid tissues in the metastases confounded the comparison of patient-matched primary tumours and metastases. We circumvented this with an original data adjustment, revealing a differential expression of stroma-related gene signatures also regulated in other organs. The comparison of N0 vs N+ primary tumours uncovered a signal irreproducible across independent data sets. This signal was also detectable when comparing the non-cancerous thyroid tissues adjacent to N0 and N+ tumours, suggesting a cohort-specific bias also likely present in previous similarly sized studies. Classification of N0 vs N+ yielded an accuracy of 63%, but additional statistical controls absent in previous studies revealed that this is explainable by chance alone. We used large data sets from The Cancer Genome Atlas: N0 vs N+ classification was not better than random for most cancers. Yet, it was significant, but of limited accuracy (<70%) for thyroid, breast and head and neck cancers.

Conclusions:

The clinical potential of gene expression to predict nodal metastases seems limited for most cancers.

Identification of Subtype-Specific Prognostic Genes for Early-Stage Lung Adenocarcinoma and Squamous Cell Carcinoma Patients Using an Embedded Feature Selection Algorithm

The existence of fundamental differences between lung adenocarcinoma (AC) and squamous cell carcinoma (SCC) in their underlying mechanisms motivated us to postulate that specific genes might exist relevant to prognosis of each histology subtype. To test on this research hypothesis, we previously proposed a simple Cox-regression model based feature selection algorithm and identified successfully some subtype-specific prognostic genes when applying this method to real-world data. In this article, we continue our effort on identification of subtype-specific prognostic genes for AC and SCC, and propose a novel embedded feature selection method by extending Threshold Gradient Descent Regularization (TGDR) algorithm and minimizing on a corresponding negative partial likelihood function. Using real-world datasets and simulated ones, we show these two proposed methods have comparable performance whereas the new proposal is superior in terms of model parsimony. Our analysis provides some evidence on the existence of such subtype-specific prognostic genes, more investigation is warranted.

Beyond cytokinesis: the emerging roles of CEP55 in tumorigenesis

CEP55 was initially identified as a pivotal component of abscission, the final stage of cytokinesis, serving to regulate the physical separation of two daughter cells. Over the past 10 years, several studies have illuminated additional roles for CEP55 including regulating the PI3K/AKT pathway and midbody fate. Concurrently, CEP55 has been studied in the context of cancers including those of the breast, lung, colon and liver. CEP55 overexpression has been found to significantly correlate with tumor stage, aggressiveness, metastasis and poor prognosis across multiple tumor types and therefore has been included as part of several prognostic 'gene signatures' for cancer. Here by discussing in depth the functions of CEP55 across different effector pathways, and also its roles as a biomarker and driver of tumorigenesis, we assemble an exhaustive review, thus commemorating a decade of research on CEP55.

Test on existence of histology subtype-specific prognostic signatures among early stage lung adenocarcinoma and squamous cell carcinoma patients using a Cox-model based filter

Background

Non-small cell lung cancer (NSCLC) is the predominant histological type of lung cancer, accounting for up to 85% of cases. Disease stage is commonly used to determine adjuvant treatment eligibility of NSCLC patients, however, it is an imprecise predictor of the prognosis of an individual patient. Currently, many researchers resort to microarray technology for identifying relevant genetic prognostic markers, with particular attention on trimming or extending a Cox regression model.

Adenocarcinoma (AC) and squamous cell carcinoma (SCC) are two major histology subtypes of NSCLC. It has been demonstrated that fundamental differences exist in their underlying mechanisms, which motivated us to postulate the existence of specific genes related to the prognosis of each histology subtype.

Results

In this article, we propose a simple filter feature selection algorithm with a Cox regression model as the base. Applying this method to real-world microarray data identifies a histology-specific prognostic gene signature. Furthermore, the resulting 32-gene (32/12 for AC/SCC) prognostic signature for early-stage AC and SCC samples has superior predictive ability relative to two relevant prognostic signatures, and has comparable performance with signatures obtained by applying two state-of-the art algorithms separately to AC and SCC samples.

Conclusions

Our proposal is conceptually simple, and straightforward to implement. Furthermore, it can be easily adapted and applied to a range of other research settings.

Reviewers

This article was reviewed by Leonid Hanin (nominated by Dr. Lev Klebanov), Limsoon Wong and Jun Yu.

Electronic supplementary material

The online version of this article (doi:10.1186/s13062-015-0051-z) contains supplementary material, which is available to authorized users.

Kif20a inhibition reduces migration and invasion of pancreatic cancer cells

BACKGROUND

The Translational Genome Research Network in Pancreatic Cancer performed a meta-analysis of publicly available various high-throughput gene analysis panels to identify drugable targets. There, the most differentially expressed gene between normal and cancerous pancreas was Kif20a. The aim of the study was to verify this expression pattern and further characterize Kif20a in pancreatic cancer.

MATERIALS AND METHODS

Detailed expression analyses were carried out in pancreatic tissues and in a wide panel of pancreatic cells including ductal adenocarcinoma (PDAC) and neuroendocrine-cancer cell lines as well as immortalized human pancreatic ductal epithelial and primary stellate cells using quantitative real-time polymerase chain reaction, immunohistochemistry, immunofluorescence, and immunoblot analyses. Effects on proliferation, apoptosis, and cell cycle were assessed by MTT assays, caspase-cleavage assays, and fluorescence-activated cell sorting analysis after Kif20a silencing. Cell motility was assessed by migration and invasion assays as well as time-lapse microscopy.

RESULTS

Mean Kif20a messenger RNA expression was 18.4-fold upregulated in PDAC tissues compared with that in the normal pancreas. In line, neuroendocrine-cancer cell lines display a 1.6-fold increase and ductal adenocarcinoma cell lines a 11-fold increase of Kif20a messenger RNA (P = 0.009) in comparison with primary stellate cells. A 7.3-fold overexpression was also found in immortalized pancreatic ductal epithelial cells. Kif20a silencing with small interfering RNA molecules resulted in an inhibition of proliferation, motility, and invasion of pancreatic cancer cell lines.

CONCLUSIONS

Targeting Kif20a reduces proliferation, migration, and invasion of pancreatic cancer cells. Together with its significant overexpression in PDAC, this makes it a potential target for diagnostic and interventional purposes.

A unique hinge binder of extremely selective aminopyridine-based Mps1 (TTK) kinase inhibitors with cellular activity

Mps1, also known as TTK, is a dual-specificity kinase that regulates the spindle assembly check point. Increased expression levels of Mps1 are observed in cancer cells, and the expression levels correlate well with tumor grade. Such evidence points to selective inhibition of Mps1 as an attractive strategy for cancer therapeutics. Starting from an aminopyridine-based lead 3a that binds to a flipped-peptide conformation at the hinge region in Mps1, elaboration of the aminopyridine scaffold at the 2- and 6-positions led to the discovery of 19c that exhibited no significant inhibition for 287 kinases as well as improved cellular Mps1 and antiproliferative activities in A549 lung carcinoma cells (cellular Mps1 IC₅₀=5.3 nM, A549 IC₅₀=26 nM). A clear correlation between cellular Mps1 and antiproliferative IC₅₀ values indicated that the antiproliferative activity observed in A549 cells would be responsible for the cellular inhibition of Mps1. The X-ray structure of 19c in complex with Mps1 revealed that this compound retains the ability to bind to the peptide flip conformation. Finally, comparative analysis of the X-ray structures of 19c, a deamino analogue 33, and a known Mps1 inhibitor bound to Mps1 provided insights into the unique binding mode at the hinge region.