Oncogenic Impact of TONSL, a Homologous Recombination Repair Protein at the Replication Fork, in Cancer Stem Cells.

We investigated the role of TONSL, a mediator of homologous recombination repair (HRR), in stalled replication fork double-strand breaks (DSBs) in cancer. Publicly available clinical data (tumors from the ovary, breast, stomach and lung) were analyzed through KM Plotter, cBioPortal and Qomics. Cancer stem cell (CSC)-enriched cultures and bulk/general mixed cell cultures (BCCs) with RNAi were employed to determine the effect of TONSL loss in cancer cell lines from the ovary, breast, stomach, lung, colon and brain. Limited dilution assays and ALDH assays were used to quantify the loss of CSCs. Western blotting and cell-based homologous recombination assays were used to identify DNA damage derived from TONSL loss. TONSL was expressed at higher levels in cancer tissues than in normal tissues, and higher expression was an unfavorable prognostic marker for lung, stomach, breast and ovarian cancers. Higher expression of TONSL is partly associated with the coamplification of TONSL and MYC, suggesting its oncogenic role. The suppression of TONSL using RNAi revealed that it is required in the survival of CSCs in cancer cells, while BCCs could frequently survive without TONSL. TONSL dependency occurs through accumulated DNA damage-induced senescence and apoptosis in TONSL-suppressed CSCs. The expression of several other major mediators of HRR was also associated with worse prognosis, whereas the expression of error-prone nonhomologous end joining molecules was associated with better survival in lung adenocarcinoma. Collectively, these results suggest that TONSL-mediated HRR at the replication fork is critical for CSC survival; targeting TONSL may lead to the effective eradication of CSCs.

Clinical and biochemical relevance of monounsaturated fatty acid metabolism targeting strategy for cancer stem cell elimination in colon cancer.

Lipid metabolism is associated with colon cancer prognosis and incidence. Stearoyl-CoA desaturase 1 (SCD1), which converts fully saturated fatty acids (SFAs) to monounsaturated fatty acids (MUFAs), has been suggested as a vulnerable target for selective elimination of cancer stem cells (CSCs). However, the clinical significance and physiological role of SCD1 in CSCs has not been well demonstrated. Here, we showed the clinical and biochemical relevance of blocking SCD1 to target CSCs by analyzing human colon cancer data from TCGA and through lipidomic profiling of CSCs with or without SCD1 inhibition using mass spectrometry. Positive associations between SCD1 expression and colorectal cancer patient clinical status and the expression of CSC-related genes (WNT and NOTCH signaling) were found based on TCGA data analysis. Lipidomic profiling of CSCs and bulk cancer cells (BCCs) using mass spectrometry revealed that colon CSCs contained a distinctive lipid profile, with higher free MUFA and lower free SFA levels than in BCCs, suggesting that enhanced SCD1 activity generates MUFAs that may support WNT signaling in CSCs. In addition, all identified phosphatidyl-ethanolamine-containing MUFAs were found at higher levels in CSCs. Interestingly, we observed lower phosphatidyl-serine (18:1/18:0), phosphatidyl-choline (PC; p-18:0/18:1)), and sphingomyelin (SM; d18:1/20:0 or d16:1/22:0) levels in CSCs than in BCCs. Of those, SCD1 inhibition, which efficiently diminished free MUFA levels, increased those specific PC and SM and MUFAs in CSCs promptly. These results suggest that these specific lipid composition is critical for CSC stem cell maintenance. In addition, not only free MUFAs, which are known to be required for WNT signaling, but also other phospholipids, such as SM, which are important for lipid raft formation, may mediate other cell signaling pathways that support CSC maintenance. Comparison of the lipidomic profiles of colon cancer cells with those of previously reported for glioma cells further demonstrated the tissue specific characteristics of lipid metabolism in CSCs.

Loss-of-function screens of druggable targetome against cancer stem-like cells.

Cancer stem-like cells (CSLCs) contribute to the initiation and recurrence of tumors and to their resistance to conventional therapies. In this study, small interfering RNA (siRNA)-based screening of ∼4800 druggable genes in 3-dimensional CSLC cultures in comparison to 2-dimensional bulk cultures of U87 glioma cells revealed 3 groups of genes essential for the following: survival of the CSLC population only, bulk-cultured population only, or both populations. While diverse biologic processes were associated with siRNAs reducing the bulk-cultured population, CSLC-eliminating siRNAs were enriched in a few functional categories, such as lipid metabolism, protein metabolism, and gene expression. Interestingly, siRNAs that selectively reduced CSLC only were found to target genes for cholesterol and unsaturated fatty acid synthesis. The lipidomic profile of CSLCs revealed increased levels of monounsaturated lipids. Pharmacologic blockage of these target pathways reduced CSLCs, and this effect was eliminated by addition of downstream metabolite products. The present CSLC-sensitive target categories provide a useful resource that can be exploited for the selective elimination of CSLCs.-Song, M., Lee, H., Nam, M.-H., Jeong, E., Kim, S., Hong, Y., Kim, N., Yim, H. Y., Yoo, Y.-J., Kim, J. S., Kim, J.-S., Cho, Y.-Y., Mills, G. B., Kim, W.-Y., Yoon, S. Loss-of-function screens of druggable targetome against cancer stem-like cells.

Patient sample-oriented analysis of gene expression highlights extracellular signatures in breast cancer progression.

Although a large collection of cancer cell lines are useful surrogates for patient samples, the physiological relevance of observed molecular phenotypes in cell lines remains controversial. Because transcriptome data are a representative set of molecular phenotypes in cancers, we systematically analyzed the discrepancy of global gene expression profiles between patient samples and cell lines in breast cancers. While the majority of genes exhibited general consistency between patient samples and cell lines, the expression of genes in the categories of extracellular matrix, collagen trimers, receptor activity, catalytic activity and transporter activity were significantly up-regulated only in tissue samples. Genes in the extracellular matrix, particularly collagen trimers, showed a wide variation of expression in tissue, but minimal expression and variation in cell lines. Further analysis of tissue samples exclusively revealed that collagen genes exhibited a cancer stage-dependent expressional variation based on their supramolecular structure. Prognostic collagen biomarkers associated with survival rate were also readily predicted from tissue-oriented transcriptome analysis. This study presents the limitations of cell lines and the exclusive features of tissue samples in terms of functional categories of the cancer transcriptome.

MACE: mutation-oriented profiling of chemical response and gene expression in cancers.

SUMMARY: The mutational status of specific cancer lineages can affect the sensitivity to or resistance against cancer drugs. The MACE database provides web-based interactive tools for interpreting large chemical screening and gene expression datasets of cancer cell lines in terms of mutation and lineage categories. GI50 data of chemicals against individual NCI60 cell lines were normalized and organized to statistically identify mutation- or lineage-specific chemical responses. Similarly, DNA microarray data on NCI60 cell lines were processed to analyze mutation- or lineage-specific gene expression signatures. A combined analysis of GI50 and gene expression data to find potential associations between chemicals and genes is also a capability of this system. This database will provide extensive, systematic information to identify lineage- or mutation-specific anticancer agents and related gene targets. AVAILABILITY AND IMPLEMENTATION: The MACE web database is available at http://mace.sookmyung.ac.kr/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. CONTACT: yoonsj@sookmyung.ac.kr.

Dissecting the global variation of gene expression for the functional interpretation of transcriptome data.

To perform their biological functions, individual genes exhibit varying ranges of expression levels. Thus, considering the intrinsic variability of gene expression can improve geneset-based functional analyses which are typically used to interpret transcriptome data. Through the extensive quantitative analysis of the expressional variability of individual genes using large collections of transcriptome and proteome data, we found the existence of the intrinsic variability of gene expression at the transcriptional level. Interestingly, genes under post-translational regulation were not sensitively regulated at the transcriptional level. Because genes have intrinsically different levels of regulation at the transcription and translation stages, the functional geneset-based interpretation of transcriptome data should only include genes that are significantly varied at the transcriptional level. Thus, by removing genes with low transcriptional variation from the DNA microarray data, we showed that geneset enrichment analysis could provide improved resolution in prioritizing target functional pathways in several different experimental datasets.

Current advances in comprehensive omics data mining for oncology and cancer research.

The availability of a large amount of multiomics data enables data-driven discovery studies on cancers. High-throughput data on mutations, gene/protein expression, immune scores (tumor-infiltrating cells), drug screening, and RNAi (shRNAs and CRISPRs) screening are major integrated components of patient samples and cell line datasets. Improvements in data access and user interfaces make it easy for general scientists to carry out their data mining practices on integrated multiomics data platforms without computational expertise. Here, we summarize the extent of data integration and functionality of several portals and software that provide integrated multiomics data mining platforms for all cancer studies. Recent progress includes programming interfaces (APIs) for customized data mining. Precalculated datasets assist noncomputational users in quickly browsing data associations. Furthermore, stand-alone software provides fast calculations and smart functions, guiding optimal sampling and filtering options for the easy discovery of significant data associations. These efforts improve the utility of cancer omics big data for noncomputational users at all levels of cancer research. In the present review, we aim to provide analytical information guiding general scientists to find and utilize data mining tools for their research.

RRM2 Is a CTNNB1 Transport Regulator Promoting Colon Cancer Progression.

BACKGROUND/AIM: The cytoplasmic retention and stabilization of CTNNB1 (ß-catenin) in response to Wnt is well documented in playing a role in tumor growth. Here, through the utilization of a multiplex siRNA library screening strategy, we investigated the modulation of CTNNB1 function in tumor cell progression by ribonucleoside-diphosphate reductase subunit M2 (RRM2). MATERIALS AND METHODS: We conducted a multiplex siRNA screening assay to identify targets involved in CTNNB1 nuclear translocation. In order to examine the effect of inhibition of RRM2, selected from the siRNA screening results, we performed RRM2 knockdown and assayed for colon cancer cell viability, sphere formation assay, and invasion assay. The interaction of RRM2 with CTNNB1 and its impact on oncogenesis was examined using immunoprecipitation, immunoblotting, immunocytochemistry, and RT-qPCR. RESULTS: After a series of screening and filtration steps, we identified 26 genes that were potentially involved in CTNNB1 nuclear translocation. All candidate genes were validated in various cell lines. The results revealed that siRNA-mediated knockdown of RRM2 reduces the nuclear translocation of CTNNB1. This reduction was accompanied by a decrease in cell count, resulting in a suppressive effect on tumor cell growth. CONCLUSION: High throughput siRNA screening is an attractive strategy for identifying gene functions in cancers and the interaction between RRM2 and CTNNB1 is an attractive drug target for regulating RRM2-CTNNB1-related pathways in cancers.

The regulatory mechanism of the LY6K gene expression in human breast cancer cells.

LY6K is a cancer biomarker and a therapeutic target that induces invasion and metastasis. However, the molecular mechanisms that determine human LY6K transcription are completely unknown. To elucidate the mechanisms involved in human LY6K gene regulation and expression, multiple cis-elements were predicted using TRANSFAC software, and the LY6K regulatory region was identified using the luciferase assay in the human LY6K gene promoter. We performed ChIP, EMSA, and supershift assays to investigate the transcription factor activity on the LY6K promoter, and the effect of a SNP and CpG site methylation on AP-1 transcription factor binding affinity. AP-1 and the CREB transcription factor bound to LY6K promoter within -550/-1, which was essential for LY6K expression, but only the AP-1 heterodimer, JunD, and Fra-1, modulates LY6K gene transcriptional level. A decrease in LY6K was associated with the SNP242 C allele, a polymorphic G/C-SNP at the 242 nucleotide in the LY6K promoter region (rs2585175), or methylation of the CpG site, which was closely located with the AP-1 site by interfering with binding of the AP-1 transcription factor to the LY6K promoter. Our findings reveal an important role for AP-1 activation in promoting LY6K gene expression that regulates cell mobility of breast cancer cells, whereas the SNP242 C allele or methylation of the CpG site may reduce the risk of invasion or metastasis by interfering AP-1 activation.

Systematic analysis of genotype-specific drug responses in cancer.

A systematic understanding of genotype-specific sensitivity or resistance to anticancer agents is required to provide improved patient therapy. The availability of an expansive panel of annotated cancer cell lines enables comparative surveys of associations between genotypes and compounds of various target classes. Thus, one can better predict the optimal treatment for a specific tumor. Here, we present a statistical framework, cell line enrichment analysis (CLEA), to associate the response of anticancer agents with major cancer genotypes. Multilevel omics data, including transcriptome, proteome and phosphatome data, were integrated with drug data based on the genotypic classification of cancer cell lines. The results reproduced known patterns of compound sensitivity associated with particular genotypes. In addition, this approach reveals multiple unexpected associations between compounds and mutational genotypes. The mutational genotypes led to unique protein activation and gene expression signatures, which provided a mechanistic understanding of their functional effects. Furthermore, CLEA maps revealed interconnections between TP53 mutations and other mutations in the context of drug responses. The TP53 mutational status appears to play a dominant role in determining clustering patterns of gene and protein expression profiles for major cancer genotypes. This study provides a framework for the integrative analysis of mutations, drug responses and omics data in cancers.

NDRG2 is involved in the oncogenic properties of renal cell carcinoma and its loss is a novel independent poor prognostic factor after nephrectomy.

BACKGROUND: Although NDRG2 is a candidate tumor suppressor, its exact role in renal cell carcinoma (RCC) is not fully understood. We investigated the functional role of NDRG2 and its clinical relevance in RCC tumorigenesis. METHODS: NDRG2 expression and its clinical implications in clear cell RCC were evaluated. Biological function was assessed by a proliferation assay, anchorage-independent growth assay, and wound healing and transwell migration assays in RCC cell lines overexpressing NDRG2 coupled with an investigation of the effects of NDRG2 expression on the epithelial-mesenchymal transition (EMT). RESULTS: NDRG2 was differentially expressed in patients with RCC. A loss of NDRG2 was significantly associated with a higher proportion of tumors >10 cm and a high nuclear grade. Furthermore, multivariate analyses indicated that a loss of NDRG2 was an independent poor prognostic factor for patient survival (recurrence-free survival, hazard ratio 7.901; disease-specific survival, hazard ratio 15.395; overall survival, hazard ratio 11.339; P < 0.001 for all parameters). NDRG2 expression inhibited the anchorage-independent growth and migration of RCC cells. NDRG2 expression also modulated the expression of EMT-related genes such as Snail, Slug, and SIP1, and it decreased EMT signaling in RCC cells. Finally, NDRG2 recovered E-cadherin expression in E-cadherin-negative RCC cells. CONCLUSIONS: These results indicate that a lack of NDRG2 is associated with oncogenic properties through the loss of its role as a tumor suppressor, and that NDRG2 is an independent poor prognostic factor predicting survival in clear cell RCC, suggesting that it can serve as a novel prognostic biomarker.

ARL2 is required for homologous recombination repair and colon cancer stem cell survival.

ARL2 regulates the dynamics of cytological components and is highly expressed in colon cancer tissues. Here, we report novel roles of ARL2 in the cell nucleus and colon cancer stem cells (CSCs). ARL2 is expressed at relatively low levels in K-RAS active colon cancer cells, but its expression is induced in CSCs. Depletion of ARL2 results in M phase arrest exclusively in non-CSC cultured cells; in addition, DNA break stress accumulates in CSCs leading to apoptosis. ARL2 expression is positively associated with the expression of all six RAD51 family genes, which are essential for homologous recombination repair (HRR). Furthermore, ARL2 is required for HRR and detected within chromatin compartments. These results demonstrate the requirement of ARL2 in colon CSC maintenance, which possibly occurs through mediating double-strand break DNA repair in the nucleus.

Screening of the siGPCR library in combination with cisplatin against lung cancers.

The screening of siRNAs targeting 390 human G protein-coupled receptors (GPCRs) was multiplexed in combination with cisplatin against lung cancer cells. While the cell viability measure hardly captured the anticancer effect of siGPCRs, the direct cell count revealed the anticancer potential of diverse GPCRs (46 hits with > twofold growth inhibition, p-value < 0.01). In combined treatment with cisplatin, siRNAs against five genes (ADRA2A, F2RL3, NPSR1, NPY and TACR3) enhanced the anti-proliferation efficacy on cancer cells and reduced the self-recovery ability of surviving cells after the removal of the combined treatment. Further on-target validation confirmed that the knockdown of TACR3 expression exhibited anticancer efficacy under both single and combined treatment with cisplatin. Q-omics ( http://qomics.io ) analysis showed that high expression of TACR3 was unfavorable for patient survival, particularly with mutations in GPCR signaling pathways. The present screening data provide a useful resource for GPCR targets and biomarkers for improving the efficacy of cisplatin treatment.

MicroRNA-dependent inhibition of WEE1 controls cancer stem-like characteristics and malignant behavior in ovarian cancer.

Cancer stem-like cells (CSCs) have been suggested to be responsible for chemoresistance and tumor recurrence owing to their self-renewal capacity and differentiation potential. Although WEE1 is a strong candidate target for anticancer therapies, its role in ovarian CSCs is yet to be elucidated. Here, we show that WEE1 plays a key role in regulating CSC properties and tumor resistance to carboplatin via a microRNA-dependent mechanism. We found that WEE1 expression is upregulated in ovarian cancer spheroids because of the decreased expression of miR-424 and miR-503, which directly target WEE1. The overexpression of miR-424/503 suppressed CSC activity by inhibiting WEE1 expression, but this effect was reversed on the restoration of WEE1 expression. Furthermore, we demonstrated that NANOG modulates the miR-424/503-WEE1 axis that regulates the properties of CSCs. We also demonstrated the pharmacological restoration of the NANOG-miR-424/503-WEE1 axis and attenuation of ovarian CSC characteristics in response to atorvastatin treatment. Lastly, miR-424/503-mediated WEE1 inhibition re-sensitized chemoresistant ovarian cancer cells to carboplatin. Additionally, combined treatment with atorvastatin and carboplatin synergistically reduced tumor growth, chemoresistance, and peritoneal seeding in the intraperitoneal mouse models of ovarian cancer. We identified a novel NANOG-miR-424/503-WEE1 pathway for regulating ovarian CSCs, which has potential therapeutic utility in ovarian cancer treatment.

Sanguinarine is an allosteric activator of AMP-activated protein kinase.

We found that a natural product, Sanguinarine, directly interacts with AMPK and enhances its enzymatic activity. Cell-based assays confirmed that cellular AMPK and the downstream acetyl-CoA carboxylase (ACC) were phosphorylated after Sanguinarine treatment. Sanguinarine was shown to exclusively activate AMPK holoenzymes containing α1γ1 complexes, and it activated both ß1- and ß2-containing isotypes of AMPK. Furthermore, a docking study suggested that Sanguinarine binds AMPK at the cleft between the ß and γ domains whereas the physiological activator, AMP, binds at the well-characterized γ domain pocket. In summary, we report that Sanguinarine is a novel, direct activator of AMPK that binds by a unique allosteric mechanism different from that of the natural AMPK ligand, AMP, and other known AMPK activators. These studies have direct applications to the pharmacological study of AMPK activation and the potential development of new therapeutics.

Global analysis of microarray data reveals intrinsic properties in gene expression and tissue selectivity.

MOTIVATION: It is expected that individual genes have intrinsically different variability in the global expressional trend among them. Thus, the consideration of gene-specific expressional properties will help us to distinguish target-selective gene expression over non-selective over-expression. RESULTS: The re-standardization and integration of heterogeneous microarray datasets, available from public databases, have enabled us to determine the global expression properties of individual genes across a wide variety of experimental conditions and samples. The global averages and SDs of expression for each gene in the integrated microarray datasets were found to be intrinsic properties, which were consistent among independent collections of datasets using different microarray platforms. Using the gene-specific intrinsic parameters to rescale the microarray data, we were able to distinguish novel selective gene expression [cartilage oligomeric matrix protein (COMP) and Collagen X] in breast cancer tissues from non-selective over-expression, a difference that has not been detectable by conventional methods. AVAILABILITY AND IMPLEMENTATION: The web-based tool for GS-LAGE is available at http://lage.sookmyung.ac.kr

NetCSSP: web application for predicting chameleon sequences and amyloid fibril formation.

The calculation of contact-dependent secondary structure propensity (CSSP) is a unique and sensitive method that detects non-native secondary structure propensities in protein sequences. This method has applications in predicting local conformational change, which typically is observed in core sequences of protein aggregation and amyloid fibril formation. NetCSSP implements the latest version of the CSSP algorithm and provides a Flash chart-based graphic interface that enables an interactive calculation of CSSP values for any user-selected regions in a given protein sequence. This feature also can quantitatively estimate the mutational effect on changes in native or non-native secondary structural propensities in local sequences. In addition, this web tool provides precalculated non-native secondary structure propensities for over 1,400,000 fragments that are seven-residues long, collected from PDB structures. They are searchable for chameleon subsequences that can serve as the core of amyloid fibril formation. The NetCSSP web tool is available at http://cssp2.sookmyung.ac.kr/.

Q-omics: Smart Software for Assisting Oncology and Cancer Research.

The rapid increase in collateral omics and phenotypic data has enabled data-driven studies for the fast discovery of cancer targets and biomarkers. Thus, it is necessary to develop convenient tools for general oncologists and cancer scientists to carry out customized data mining without computational expertise. For this purpose, we developed innovative software that enables user-driven analyses assisted by knowledge-based smart systems. Publicly available data on mutations, gene expression, patient survival, immune score, drug screening and RNAi screening were integrated from the TCGA, GDSC, CCLE, NCI, and DepMap databases. The optimal selection of samples and other filtering options were guided by the smart function of the software for data mining and visualization on Kaplan-Meier plots, box plots and scatter plots of publication quality. We implemented unique algorithms for both data mining and visualization, thus simplifying and accelerating user-driven discovery activities on large multiomics datasets. The present Q-omics software program (v0.95) is available at http://qomics.sookmyung.ac.kr.

Targeting a Lipid Desaturation Enzyme, SCD1, Selectively Eliminates Colon Cancer Stem Cells through the Suppression of Wnt and NOTCH Signaling.

The elimination of the cancer stem cell (CSC) population may be required to achieve better outcomes of cancer therapy. We evaluated stearoyl-CoA desaturase 1 (SCD1) as a novel target for CSC-selective elimination in colon cancer. CSCs expressed more SCD1 than bulk cultured cells (BCCs), and blocking SCD1 expression or function revealed an essential role for SCD1 in the survival of CSCs, but not BCCs. The CSC potential selectively decreased after treatment with the SCD1 inhibitor in vitro and in vivo. The CSC-selective suppression was mediated through the induction of apoptosis. The mechanism leading to selective CSC death was investigated by performing a quantitative RT-PCR analysis of 14 CSC-specific signaling and marker genes after 24 and 48 h of treatment with two concentrations of an inhibitor. The decrease in the expression of Notch1 and AXIN2 preceded changes in the expression of all other genes, at 24 h of treatment in a dose-dependent manner, followed by the downregulation of most Wnt- and NOTCH-signaling genes. Collectively, we showed that not only Wnt but also NOTCH signaling is a primary target of suppression by SCD1 inhibition in CSCs, suggesting the possibility of targeting SCD1 against colon cancer in clinical settings.

1,3-Diphenyl-1H-pyrazole derivatives as a new series of potent PPARγ partial agonists.

A new series of PPARγ partial agonists, 1,3-diphenyl-1H-pyrazole derivatives, were identified using an improved virtual screening scheme combining ligand-centric and receptor-centric methods. An in vitro assay confirmed the nanomolar binding affinity of 1,3-diphenyl-1H-pyrazole derivatives such as SP3415. We also characterized the competitive antagonism of SP3415 against rosiglitazone at micromolar concentrations. They showed a PPARγ partial agonistic activity similar to that of a known PPARγ drug, pioglitazone, in a cell-based transactivation assay. Furthermore, the structure-activity relationships of the pyrazole derivatives were investigated through comparative molecular field analysis and binding mode analysis, which provided new insight concerning their partial agonistic effect on PPARγ.