Combinatorial measurement of CDKN1A/p21 and KIF20A expression for discrimination of DNA damage-induced clastogenicity

Morin reverses P-glycoprotein-mediated multidrug-resistance in KBChR-8-5 cancer cell lines

Multidrug resistance (MDR) during clinical chemotherapy for cancer has been considered a major obstacle to treatment efficacy. The involvement of adenosine triphosphate-binding cassette (ABC) transporters in the MDR mechanism significantly reduces the efficacy of chemotherapeutics. This study investigates the potential of morin, a dietary bioflavonoid, to overcome colchicine resistance in KBChR-8-5 MDR cells. The P-gp inhibitory activity by morin was measured by calcein-AM drug efflux assay. Western blot analysis was employed to evaluate P-gp messenger RNA and protein expressions following morin treatment. Flow cytometry analysis and acridine orange/ethidium bromide fluorescence staining were utilised to investigate the induction of apoptosis and cell cycle arrest upon treatment with morin and paclitaxel in combination. Additionally, polymerase chain reaction (PCR) array analysis was conducted to study the gene expression profiles related to MDR, apoptosis and cell cycle arrest during treatment with morin, paclitaxel or their combination. Morin exhibited a strong binding interaction with human P-gp. This was corroborated by drug efflux assays, which showed a reduction in P-gp efflux function with increasing morin concentration. Furthermore, morin and paclitaxel combination potentiated the induction of apoptosis and G2/M phase cell cycle arrest. Morin treatment significantly downregulated the gene expression of ABCB1 and P-gp membrane expressions in MDR cells. Additionally, PCR array gene expression analysis revealed that the combination treatment with morin and paclitaxel upregulated proapoptotic and cell cycle arrest genes while downregulating ABCB1 gene and antiapoptotic genes. Thus, morin effectively reversed paclitaxel resistance in KBChR-8-5 drug-resistant cancer cells and concluded that morin resensitized the paclitaxel resistance in KBChR8-5 drug-resistant cancer cells.

Comparative Analysis of Transcriptional Responses to Genotoxic and Non-Genotoxic Agents in the Blood Cell Model TK6 and the Liver Model HepaRG

Transcript signatures are a promising approach to identify and classify genotoxic and non-genotoxic compounds and are of interest as biomarkers or for future regulatory application. Not much data, however, is yet available about the concordance of transcriptional responses in different cell types or tissues. Here, we analyzed transcriptomic responses to selected genotoxic food contaminants in the human p53-competent lymphoblastoid cell line TK6 using RNA sequencing. Responses to treatment with five genotoxins, as well as with four non-genotoxic liver toxicants, were compared with previously published gene expression data from the human liver cell model HepaRG. A significant overlap of the transcriptomic changes upon genotoxic stress was detectable in TK6 cells, whereas the comparison with the HepaRG model revealed considerable differences, which was confirmed by bioinformatic data mining for cellular upstream regulators or pathways. Taken together, the study presents a transcriptomic signature for genotoxin exposure in the human TK6 blood cell model. The data demonstrate that responses in different cell models have considerable variations. Detection of a transcriptomic genotoxin signature in blood cells indicates that gene expression analyses of blood samples might be a valuable approach to also estimate responses to toxic exposure in target organs such as the liver.

Co-expression of cancer driver genes: IDH-wildtype glioblastoma-derived tumorspheres

BACKGROUND

Driver genes of GBM may be crucial for the onset of isocitrate dehydrogenase (IDH)-wildtype (WT) glioblastoma (GBM). However, it is still unknown whether the genes are expressed in the identical cluster of cells. Here, we have examined the gene expression patterns of GBM tissues and patient-derived tumorspheres (TSs) and aimed to find a progression-related gene.

METHODS

We retrospectively collected primary IDH-WT GBM tissue samples (n = 58) and tumor-free cortical tissue samples (control, n = 20). TSs are isolated from the IDH-WT GBM tissue with B27 neurobasal medium. Associations among the driver genes were explored in the bulk tissue, bulk cell, and a single cell RNAsequencing techniques (scRNAseq) considering the alteration status of TP53, PTEN, EGFR, and TERT promoter as well as MGMT promoter methylation. Transcriptomic perturbation by temozolomide (TMZ) was examined in the two TSs.

RESULTS

We comprehensively compared the gene expression of the known driver genes as well as MGMT, PTPRZ1, or IDH1. Bulk RNAseq databases of the primary GBM tissue revealed a significant association between TERT and TP53 (p < 0.001, R = 0.28) and its association increased in the recurrent tumor (p  < 0.001, R = 0.86). TSs reflected the tissue-level patterns of association between the two genes (p < 0.01, R = 0.59, n = 20). A scRNAseq data of a TS revealed the TERT and TP53 expressing cells are in a same single cell cluster. The driver-enriched cluster dominantly expressed the glioma-associated long noncoding RNAs. Most of the driver-associated genes were downregulated after TMZ except IGFBP5.

CONCLUSIONS

GBM tissue level expression patterns of EGFR, TERT, PTEN, IDH1, PTPRZ1, and MGMT are observed in the GBM TSs. The driver gene-associated cluster of the GBM single cells were enriched with the glioma-associated long noncoding RNAs.

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.

IFNAR2-dependent gene expression profile induced by IFN-α in Pteropus alecto bat cells and impact of IFNAR2 knockout on virus infection

Bats are important reservoirs of many viruses, which are capable of infecting the host without inducing obvious clinical diseases. Interferon and the downstream interferon regulated genes (IRGs) are known to act as the first line of defense against viral infections. Little is known about the transcriptional profile of genes being induced by interferon in bats and their role in controlling virus infection. In this study, we constructed IFNAR2 knockout bat cell lines using CRISPR technology and further characterized gene expression profiles induced by the most abundant IFN-α (IFN-α3). Firstly, we demonstrated that the CRISPR/Cas9 system is applicable for bat cells as this represents the first CRIPSR knockout cell line for bats. Our results showed the pleiotropic effect of IFN-α3 on the bat kidney cell line, PaKiT03. As expected, we confirmed that IFNAR2 is indispensable for IFN-a signaling pathway and plays an important role in antiviral immunity. Unexpectedly, we also identified novel IFNAR2-dependent IRGs which are enriched in pathways related to cancer. To our knowledge, this seems to be bat-specific as no such observation has been reported for other mammalian species. This study expands our knowledge about bat immunology and the cell line established can provide a powerful tool for future study into virus-bat interaction and cancer biology.

Systematic identification of an integrative network module during senescence from time-series gene expression

Background

Cellular senescence irreversibly arrests growth of human diploid cells. In addition, recent studies have indicated that senescence is a multi-step evolving process related to important complex biological processes. Most studies analyzed only the genes and their functions representing each senescence phase without considering gene-level interactions and continuously perturbed genes. It is necessary to reveal the genotypic mechanism inferred by affected genes and their interaction underlying the senescence process.

Results

We suggested a novel computational approach to identify an integrative network which profiles an underlying genotypic signature from time-series gene expression data. The relatively perturbed genes were selected for each time point based on the proposed scoring measure denominated as perturbation scores. Then, the selected genes were integrated with protein-protein interactions to construct time point specific network. From these constructed networks, the conserved edges across time point were extracted for the common network and statistical test was performed to demonstrate that the network could explain the phenotypic alteration. As a result, it was confirmed that the difference of average perturbation scores of common networks at both two time points could explain the phenotypic alteration. We also performed functional enrichment on the common network and identified high association with phenotypic alteration. Remarkably, we observed that the identified cell cycle specific common network played an important role in replicative senescence as a key regulator.

Conclusions

Heretofore, the network analysis from time series gene expression data has been focused on what topological structure was changed over time point. Conversely, we focused on the conserved structure but its context was changed in course of time and showed it was available to explain the phenotypic changes. We expect that the proposed method will help to elucidate the biological mechanism unrevealed by the existing approaches.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-017-0417-1) contains supplementary material, which is available to authorized users.