The promise of PARP-inhibitors(PARPis) in the management of epithelial ovarian cancer(EOC) is tempered by the fact that approximately 50% of patients with homologous recombination (HR)-proficient tumors do not respond well to these agents. Combination of PARPis with agents that inhibit HR may represent an effective strategy to enhance their activity in HR-proficient tumors. Using a bioinformatics approach, we identified that heat shock protein 90 inhibitors(HSP90i) may suppress HR and thus revert HR-proficient to HR-deficient tumors. Analysis of publicly available gene expression data showed that exposure of HR-proficient breast cancer cell lines to HSP90i 17-AAG downregulated HR, ATM and Fanconi Anemia pathways. In HR-proficient EOC cells, 17-AAG suppressed HR as assessed using the RAD51 foci formation assay and this was further confirmed using the Direct Repeat-GFP reporter assay. Furthermore, 17-AAG downregulated BRCA1 and/or RAD51 protein levels, and induced significantly more γH2AX activation in combination with olaparib compared to olaparib alone. Finally, sublethal concentrations of 17-AAG sensitized HR-proficient EOC lines to olaparib and carboplatin but did not affect sensitivity of the HR-deficient OVCAR8 line arguing that the 17-AAG mediated sensitization is dependent on suppression of HR. These results provide a preclinical rationale for using a combination of olaparib/17-AAG in HR-proficient EOC. Epithelial ovarian cancer (EOC) is characterized by frequent genetic and epigenetic alterations in gene members of the homologous recombination (HR) DNA repair pathway. In particular, approximately 50% of high grade serous cancers harbor molecular alterations in the HR pathway which include germline and somatic BRCA1/2 mutations in 15% and 6-7% of them respectively -5. PARPiThe promise of PARP inhibitors in the management of EOC is tempered by the fact that HR-proficient EOCs do not respond well to these agents, suggesting that the remaining approximately 50% of EOC patients  do not benefit from this novel class of drugs. Combination of PARPis with agents that inhibit HR may represent an effective strategy to enhance activity of PARPis in HR proficient tumors and thus potentially expand use of these agents beyond patients with HR deficient EOCs.In order to identify candidate agents that may directly or indirectly inhibit HR, we used the Connectivity Map, a reference collection of gene expression signatures that have been generated by exposing cultured human cell lines to a variety of small molecule drugs, 13. By We queried a previously developed gene expression signature of BRCAness to the CApplication of the top performing genes of the BRCAness signature to the Connectivity Map identified a number of interesting compounds Figure  with higGiven that the Connectivity Map identified HSP90is as candidate agents that suppress HR, we evaluated whether the transcriptional response to HSP90is affects HR pathway and HR pathway genes in cancer cell lines. We queried GEO for publicly available gene expression data of response to HSP90is and identified one microarray dataset assessing the transcriptional response of breast cancer cell lines to HSP90i 17-AAG . 17-AAG is an HSP90 inhibitor that has been evaluated in clinical trials in various malignancies, and is currently in the most advanced stage of clinical development of all HSP90is. Furthermore, unlike geldanamycin, it is not hepatotoxic and is therefore appropriate for clinical use.This microarray dataset included gene expression data of the HR proficient  and HR deficient  breast cancer cell lines exposed to 17-AAG or control. We assessed 17-AAG induced changes in the expression levels of genes of the HR pathway both at an individual gene level and at a global pathway level.Strikingly, in the HR proficient breast cancer cell lines, pathway analysis revealed that exposure to 17-AAG statistically significantly downregulated HR (p<0.005), ATM (p=0.015) signaling and Fanconi Anemia (p<0.005) pathways, which are involved in repair of double strand breaks and interstrand crosslinks  assay. As shown in Figure To further confirm the results of the RAD51 foci formation assay we used the Direct Repeat-GFP (DR-GFP) reporter system previously developed to assay HR in mammalian cells , 18. DR-We evaluated whether 17-AAG downregulates HR pathway genes in HR proficient ovarian cancer cell lines as predicted by the microarray data in the breast cancer cell lines  compared to olaparib alone. Furthermore, sublethal concentrations of 17-AAG enhanced cytotoxicity of HR proficient EOC cells to carboplatin and olaparib. Of note, 17-AAG also enhanced sensitivity to the combination of olaparib and carboplatin inducing significant killing even with very low olaparib and carboplatin doses . ConversIt is important to underscore that the 17-AAG doses of 10-100nM that were used in our experiments were sublethal in the ovarian cancer cell lines employed in our study although they are reportedly fully cytostatic in other settings Ref. 26-28). One reason may be because HSP90-inhibitors induce HSP70 (a known pharmacodynamic marker of 17-AAG therapy) which bears anti-apoptotic effects [-28. One In conclusion, sublethal concentrations of the HSP90i 17-AAG suppress HR and enhance sensitivity of HR proficient ovarian cancer cells to platinum and PARPis. These results provide a preclinical rationale for using a combination of 17-AAG and olaparib and/or carboplatin in EOCs that are HR proficient either at baseline or at the time of development of platinum or PARPi resistance.We used our previously developed, publicly available, gene expression signature of BRCAness which asWe accessed Agilent-014850 Whole Human Genome Microarray expression data of 17-AAG treated breast cancer cell lines that werCells were plated at 1000 cells per well on a 96-well plate in sextuplicate and treated with PARP inhibitor and/or carboplatin with or without 17 AAG at indicated concentrations on the next day. After 5 days, cell viability was quantified by Celltiter Glo.6 U2OS cells carrying DR-GFP reporter were plated on a 12-well plate overnight, treated with 17 AAG at indicated concentrations for 24 hr, and transfected with 500 ng of I-SceI expression plasmid using Lipofectamine 2000. After 48 h, GFP-positive cells were assayed by FACScan.HR assay was performed as previously reported , 18, 31.Cells plated on glass slides were fixed for 10 min with 4% (v/v) paraformaldehyde and permeabilized for 10 min with 1% (v/v) Triton X-100 in PBS. Cells were rinsed with PBS and incubated with RAD51 (Santa Cruz) primary antibody diluted in PBS with 5% goat serum for 2 hrs at room temperature (RT). Cells were washed, incubated with secondary antibody  diluted in PBS with 5% goat serum for 1 hr at RT in the dark, and washed before being mounted using Dapi Fuoromount-G (SouthernBiotech). Slides were visualized by Zeiss Axioplan microscope and RAD51 focus-positive cells (with > 10 foci) were quantified by comparing 100 cells.The immunoblots were done as described previously , 33 withThis work was supported by the Ovarian Cancer Research Fund Program Project Grant to Dr Matulonis and Dr Konstantinopoulos.


The human sulfatase 1 (hSulf-1) gene encodes an endosulfatase that functions to inhibit the heparin-binding growth factor signaling, including the basic fibroblast growth factor (bFGF)-mediated pathway, by desulfating the cell surface heparan sulfate proteoglycans (HSPGs). bFGF could stimulate cell cycle progression and inhibit cell apoptosis, this biological effect can be reversed by hSulf-1. However, molecular mechanisms have not been fully reported. In the current study, by reactivation of hSulf-1 expression and function in the hSulf-1-negative hepatocellular carcinoma (HCC) cell lines and HCC xenograft tumors, we found that hSulf-1 blocked the bFGF effect on the promotion of cell cycle and inhibition of apoptosis. The bFGF-stimulated activation of protein kinase B (AKT) and extracellular signal-regulated kinase (ERK) pathways was suppressed by hSulf-1, which led to a decreased expression of the target genes Cyclin D1 and Survivin, then finally induced cell cycle arrest and apoptosis in HCC cells. Our data suggested that hSulf-1 may be a suitable target for cancer therapy. Survival of cancer cells depends on the activation of a series of signaling pathways. In most of cancers, various growth factors and their receptors are overexpressed, such as the basic fibroblast growth factor (bFGF) -3, epideLoss of cell cycle control and inhibition of cell apoptosis lead to uncontrolled cell proliferation and tumor progression in majority of cancers. bFGF is considered to play an important role in stimulating the proliferation of various cancer cells. It can induce cancer cell proliferation by activating or expressing G1-S phase proteins, including E2F-1, cdks and cyclins, through the reactive oxygen species/phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) pathway in colon cancer ,15. bFGFSince hSulf-1 plays a negative regulatory role in bFGF signaling pathways, and bFGF functions to promote cell cycle progression in human cancers as aforementioned, it is supposed that hSulf-1 can regulate cancer cell cycle and control cancer programmed cell death, such as apoptosis. However, there is no enough evidence to clarify the relationship between hSulf-1 function and cell cycle regulation. In this study, bFGF was used to stimulate the cell cycle progression in HCC cell lines, hSulf-1 was re-expressed by adenoviral vector to block the bFGF-mediated signaling pathways, and the regulatory effects and mechanisms of hSulf-1 on HCC cell cycle control were investigated in the in vitro experiments. The antitumor efficacy of hSulf-1 involved in cell cycle control was also validated in HCC cancer xenografts in nude mice. This study gave a new insight into the function of hSulf-1 as a negative regulator of cell cycle, which will help to design a novel strategy of hSulf-1 gene therapy in HCC target treatment.The HCC and hepatocyte lines were cultured in media containing bFGF. By Western blot, the expression of hSulf-1 was positive in the normal hepatocyte WRL-68 and L02 cell lines, weak positive in the MHCC97L and BEL-7404 cell lines, and completely negative in the MHCC97H and SMMC-7721 cell lines Fig. , hSulf-1Cells cultured in media containing bFGF were infected with adenovirus Ad5-hSulf1. The expression of hSulf-1 was increasingly positive in the 4 HCC cell lines and did not changed in the normal hepatocyte lines Fig. . This teAs aforementioned, the expression of hSulf-1 can inhibit bFGF-stimulated cell cycle progression and induces cell apoptosis in HCC cells. The activity of downstream signaling was examined and found that bFGF increased the phosphorylation levels of AKT and ERK in the MHCC97H and SMMC-7721 cell lines. After infected with Ad5-hSulf1 and the HCC cells expressed hSulf-1, the phosphorylation levels of AKT and ERK were markedly decreased  % at concentration of 1,000 nmol/L. Cell viability was sharply declined in Ad5-hSulf1-preconditioned SMMC-7721 cells, being (18.69 ± 5.55) % at rapamycin concentration of 1,000 nmol/L Fig. . The parThe xenograft tumor models were established with both the parental SMMC-7721 cells and the bFGF-cultured SMMC-7721 cells. Apparently, the bFGF-cultured SMMC-7721 model had characteristics of earlier tumor formation and quicker growth than the parental SMMC-7721 model. After treated with Ad5-hSulf1, the tumor inhibitory rates were 43.43% and 53.92% in the parental SMMC-7721 model and the bFGF-cultured SMMC-7721 model, respectively, demonstrating that the tumor growth suppression of Ad5-hSulf1 was more effective in the bFGF-cultured SMMC-7721 model Fig. . There wThe xenograft tumors of the bFGF-cultured SMMC-7721 model were examined immunohistochemically. The expression of hSulf-1 and the percentage of apoptosis were increased. The expression of Cyclin D1 and Survivin was decreased in the Ad5-hSulf1-treated group, compared with the blank control group Fig. ; Table 2The hSulf-1 expression can diminish the cascade phosphorylation of a series of kinases including the extracellular signal-regulated kinase (ERK) and serine/threonine kinase (AKT), and followed by inactivation of downstream signaling pathways. This mechanism plays a distinct part in the inhibition of malignant transformation and cancer growth -24. Our The bFGF expression can promote cancer cell proliferation by activating the PI3K/AKT and MAPK/ERK pathways in cancer ,15. bFGFThe current study found that the bFGF product promotes cell cycle progression and inhibits cell apoptosis in hSulf-1-negative HCC cell lines and HCC xenograft tumors, the outstanding feature was that the percentages of G0/G1-phase and the percentages of cell apoptosis were decreased and the percentages of S-phase were increased in the HCC cell lines, but the changes in cell cycle and apoptosis had no significant difference in the normal hepatocyte cell lines. By reactivation of hSulf-1 expression and function in hSulf-1-negative HCC cell lines, the effect of bFGF on cell cycle progression and apoptosis was reversed, demonstrating that there is a relationship between hSulf-1 and bFGF functions.To further investigate the molecular mechanism of hSulf-1 effect on cancer cell cycle and apoptosis, we found that the reactivation of hSulf-1 expression and function in hSulf-1-negative HCC cell lines can downregulate the phosphorylation of AKT and ERK and inhibit the activity of bFGF-induced AKT and ERK signaling in HCC cells, then finally led to cell cycle arrest and cell apoptosis by suppressing the expression of Cyclin D1. This phenomenon was approved in HCC xenograft tumor in nude mice. Cyclin D1 is the key and initial regulator in cell cycle control -29. By bMoreover, the study also demonstrated that inhibition of AKT and ERK signaling by hSulf-1 led to a decrease of Survivin expression in HCC cell lines and xenograft tumors. The overexpression of Cyclin D1 also increases Survivin expression . BecauseTo conclude, this study gave a convincing evidence to demonstrate that hSulf-1 is a sulfatase and can reverse the effect of bFGF on cell cycle and cell apoptosis by inhibiting bFGF-mediated receptor tyrosine kinase signaling and decreasing the expression of Cyclin D1 and Survivin. Therefore, the current study suggested that hSulf-1 plays an important role in the regulation of cell cycle and apoptosis and may be considered as a potential target in HCC therapy.The HCC cell lines, MHCC97H, MHCC97L, SMMC-7721, BEL-7404, and the normal hepatocyte lines, WRL-68 and L02, were purchased from the Shanghai Cell Bank . All cell lines were cultured in media according to the provider's instruction. The preconditioned cells used in the in vitro experiments were cultured in media containing 20 ng/ml bFGF , or in media containing 0 to 1,000 nmol/L rapamycin . Cells were also preconditioned by infection of adenovirus   at a mul6 cells/well and harvested. The procedures of propidium iodide (PI) staining, Annexin V/PI staining, and the examinations of cell cycle and apoptosis by flow cytometer  were operated as described previously [Cells were cultured in 6-well plates at 1×10eviously .The expression of indicated factors was examined by Western blot, with the primary antibodies including rabbit anti-hSulf-1, mouse anti-human total AKT (t-AKT), rabbit anti-human phosphorylated AKT (p-AKT) ; rabbit anti-human total ERK1/2 (t-ERK) and phosphorylated ERK (p-ERK), mouse anti-human Cyclin D1 ; rabbit anti-human Survivin ; and mouse anti-human glyceraldehydes 3-phosphate dehydrogenase (GAPDH) . Signals were visualized by ECL chemiluminescence. Equal protein loading was assessed by the expression of GAPDH.6 cells were seeded in 6-well plates and transfected with siRNAs at a concentration of 10 μg/well using Lipofectamine 2000 . Cells were harvested at 48 h later after transfection and examined for the indicated factors.The siRNAs of AKT and ERK were synthesized . The Akt-siRNA targets the sequence 1338-1360 bp (21 bp target + 2 bp overhang: gactacctgcactcggagaagaa) of Akt1 gene (NM_005163.2). The ERK-siRNA targets the sequence 903-925 bp (acctgaattgtatcatcaacat) of ERK1 gene (NM_002746.2). A mock control siRNA  was synchronously synthesized. Totally 104 cells/well for 48 h, and measured by Cell Proliferation Kit I  to determine the cell viability according to the kit protocol.The parental and preconditioned cells were cultured in 96-well plates at 1×10The animal study was approved by the animal ethics committee of Second Military Medical University . All animal study procedures were performed in compliance with the Guide for the Care and Use of Laboratory Animals of the US Department of Health and Human Services.6 cells per mouse), respectively, into the right flanks of 30 BALB/c (nu/nu) mice . The xenograft tumors were about 0.5 cm in diameters after two weeks later in the bFGF-cultured SMMC-7721 model and after three weeks later in the parental SMMC-7721 model. Mice in every model were separated randomly into 3 groups: the Ad5-hSulf1-treated group, Ad5-EGFP-treated group and control groups, 5 mice per group. The Ad5-hSulf1 and Ad5-EGFP groups were intratumorally injected with 2×108 pfu viruses, one injection every other day and totally 5 injections with total dose of 109 pfu viruses per mouse. Mice in the control group were injected with the same volume of viral preservation solution . Tumor volume was measured according to the previously reported method and formula [3) approved by the animal ethics committee.The xenograft tumor models were established by subcutaneously injecting the parental SMMC-7721 cells and the bFGF-cultured SMMC-7721 cells  according to reference . The perP values less than 0.05 were considered statistically significant.The experimental data from 3 times of independent in vitro experiments, as well as in vivo experimental data from 5 mice per group, were presented as ‘mean ± standard deviation (SD)’, and analyzed by one-way analysis of variance (ANOVA). When the data were statistically different among the multiple groups, the SNK-q test was used to conduct the multiple comparison. The statistical analysis software package PASW Statistics 18 was used.


Human-induced pluripotent stem cells (iPSCs) are derived from differentiated somatic cells using defined factors and provide a renewable source of autologous cells for cell therapy. Many reprogramming methods have been employed to generate human iPSCs, including the use of integrating vectors and non-integrating vectors. Maintenance of the genomic integrity of iPSCs is highly desirable if the cells are to be used in clinical applications. Here, using the Affymetrix Cytoscan HD array, we investigated the genomic aberration profiles of 19 human cell lines: 5 embryonic stem cell (ESC) lines, 6 iPSC lines derived using integrating vectors (“integrating iPSC lines”), 6 iPSC lines derived using non-integrating vectors (“non-integrating iPSC lines”), and the 2 parental cell lines from which the iPSCs were derived. The genome-wide copy number variation (CNV), loss of heterozygosity (LOH) and mosaicism patterns of integrating and non-integrating iPSC lines were investigated. The maximum sizes of CNVs in the genomes of the integrating iPSC lines were 20 times higher than those of the non-integrating iPSC lines. Moreover, the total number of CNVs was much higher in integrating iPSC lines than in other cell lines. The average numbers of novel CNVs with a low degree of overlap with the DGV and of likely pathogenic CNVs with a high degree of overlap with the ISCA  database were highest in integrating iPSC lines. Different single nucleotide polymorphisms (SNP) calls revealed that, using the parental cell genotype as a reference, integrating iPSC lines displayed more single nucleotide variations and mosaicism than did non-integrating iPSC lines. This study describes the genome stability of human iPSCs generated using either a DNA-integrating or non-integrating reprogramming method, of the corresponding somatic cells, and of hESCs. Our results highlight the importance of using a high-resolution method to monitor genomic aberrations in iPSCs intended for clinical applications to avoid any negative effects of reprogramming or cell culture. Human-induced pluripotent stem cellsare derived from differentiated somatic cells using defined factors. Like human embryonic stem cells, iPSCs are capable of unlimited proliferation and of differentiating into all cell types of the body. The generation of patient-specific iPSCs holds promise for regenerative medicine because they can provide a renewable source of autologous cells for cell therapy without the risk of immune rejection. Retrovirus- or lentivirus-based delivery systems have served as mainstream methods of generating iPSCs, although three independent groups successfully generated mouse iPSCs using tetraploid complementation to conclusively demonstrate that iPSCs are equivalent to ESCs in terms of pluripotency–3. HowevMany reprogramming methods have been employed to generate human iPSCs without genome-integrating DNA elements. These methods use, for example, episomal vectors, adenoviral vectors, Sendai viral vectors, plasmids, synthetic mRNA, miRNA, protein transduction and small molecules–12. All Genomic stability is critical for clinical applications of human iPSCs. Because genetic aberrations have been strongly associated with cancer, it is important that iPSCs prepared for clinical use are free from cancer-associated genomic alterations. Recently, several studies have identified genomic abnormalities such as chromosomal aneuploidy and translocations, megabase-scale duplications and deletions, and point mutations in iPSCs. Laurent et al have reported increased subchromosomal CNVs in pluripotent cell samples, with the enriched CNVs located in specific genomic regions. They alAll experiments were approved by the ethical committee of The Third Affiliated Hospital of Guangzhou Medical University. The tissue donors provided their written informed consent for participation. Briefly, the donors were informed that their tissues would be used for scientific research and that the research results would be published in a scientific research journal but that their names will not be listed in the paper. The donors were not compensated for their donation. Human amniotic fluid (AF) cell lines, fetal fibroblast (FF) cell lines and human ES cell lines were independently established in our laboratory ,17. AF cHuman ESC and iPSC lines were cultured on Matrigel-coated tissue culture dishes  with mTeSR1  at 37°C and 5% CO2 in a 100% humidified atmosphere incubator. The culture medium was refreshed daily until the cells were ready to passage or harvest. Cells were passaged using 1 mg/ml dispase (Gibco) every 3–4 days.Genomic DNA was extracted and purified with QIAamp DNA Blood Mini Kit  according to the manufacturer’s instructions. RNA digestion was performed at 37°C for 1 hour using RNase (QIAGEN). The concentration and quality of the DNA samples were determined using a spectrophotometer  and 1% agarose gel electrophoresis.The Affymetrix Cytoscan HD array , which interrogates 2,696,550 copy number markers across the human genome, was used to characterize cell lines of interest to determine whether there are different associations with de novo CNVs generated using different reprogramming methods. For each sample, 250 ng of input genomic DNA was amplified and labeled according to the manufacturer's instructions. HybridiqRT-PCR was performed to validate CNV calls. SYBR Green assays were performed in triplicate and the predicted copy number was calculated based on the equation: CN = 2*(2^(-ΔΔCt)).The Gene Expression Omnibus (GEO) accession number for the Affymetrix Cytoscan HD array data which has been submitted to Gene Expression Omnibus in this paper is GSM 1704973–GSM 1704991.Previous studies have shown that CNVs are generated during the reprogramming process. To investigate the effect of integrating and non-integrating reprogramming methods on genomic integrity of iPSCs, high-resolution CNV and SNP genotyping (Affymetrix Cytoscan HD array) was performed on 19 samples comprising 2 somatic cell lines, 5 hESC lines, 6 iPSC lines generated by the integrating method and 6 iPSC lines generated by the non-integrating method . These cLarge deletions (>1 Mb) of chromosome 13 were observed in the integrating line iPS-FF-2. In lines iPS-FF-g and iPS-FF-h, 7 large deletions were identified in chromosomes 1, 3, 8, 10, 16, 17 and 22. The line iPS-FF-h had five large duplications of the short arm of chromosome 2. A large deletion of chromosome 13 was observed in iPS-AF-3 . The maxIn addition to these large deletions and duplications, recurrent CNVs associated with each reprogramming method were individually identified in the human pluripotent stem cell samples. We had previously observed that the validation rate for small deletions, which are usually detected at a higher frequency in pluripotent cells, was significantly lower than that for small duplications. Therefore, for subsequent analyses, we focused on recurrent de novo duplications relative to the parental cell line. In both the lines iPS-FF-g and iPS-FF-h, we saw duplications of approximately 100 kb located at 7q21.11 (this duplications contain an OMIM gene: SEAM3E) as well as 7q31.32 (this duplications contain an OMIM gene: CADPS2) . These dOn the other hand, no significant differences in the total number of CNVs were observed in the pluripotent cells derived from the two somatic cell sources . No aberWe generated a list of 33,506 common CNVs identified in 1,038 healthy individuals and of DGVs. These common CNVs could be considered to be mostly functionally neutral. We designated as “novel CNVs” the set of CNVs that were identified in our study and overlapped to a low extent (<10%) with common CNVs. The average number of novel CNVs was 0.5 in somatic cells, 1.0 in human ESCs, 1.0 in non-integrating iPSCs, and 9.3 in integrating iPSCs. The novel CNV fraction was significantly higher in early-passage integrated iPSC lines, while the fraction in non-integrating iPSC lines was as low as the fraction in somatic cell lines . A set oIn AF cell lines and AF-derived iPSCs, 33 CNVs were detected that overlapped with CNVs in integrating iPSCs, while eight other CNVs were detected that only overlapped with CNVs in non-integrating iPSCs . Gene onIn both integrating and non-integrating iPSC lines, 72.5% of 2-copy LOH fragments  originated from the parental cells and were stably maintained without any recovery of heterozygosity. LOH fragments were recurrently found in the X chromosome, which accounted for 25.4% of the total number . The intGenetic mosaicism resulted from the de novo generation of CNVs, followed by selection for less damaged cells during propagation. From the microarray data, no mosaicism was detected in non-integrating iPSC lines, while mosaicism was clearly evident in approximately 38%-48% of integrating iPSC lines . MoreoveiPSCs present an ideal system for distinguishing between the effects of reprogramming and those of cell passaging on genome stability,20. ThisSchlaeger et al performed a small-scale genome-wide aCGH analysis and found that the majority of CNVs were preexisting and that the frequency of possible de novo aberrations was uniformly low among representative patient-derived human iPSC lines obtained by diverse methods. In thisHussein et al. concluded that the reprogramming process is associated with a high mutation rate in the resultant early-passage human iPSC lines: novel CNVs in human iPSCs were mostly generated during the reprogramming process. Early-pDifferential expression and DNA methylation in somatic cells, hESCs and iPSCs have already been reported in previous studies,17,24. AThe possible mechanisms responsible for reprogramming-induced CNVs are still under exploration. A series of recent studies investigated mutations reminiscent of those induced by replication stress and found CNVs located in regions of genomic fragility, such as common fragile sites and subtelomeric regions,26. UnliGenomic stability is critical for the clinical use of induced pluripotent stem cells and should be assessed frequently at the endpoint of every treatment. The results of our present study highlight the importance of determining the molecular mechanisms involved in reprogramming somatic cells to be pluripotent, as well as the necessity for optimizing reprogramming and culture conditions to improve genetic stability of iPSCs and their safety for clinical cell therapy.S1 FigThe iPSCs differentiated into various tissues, including ectoderm , mesoderm (cartilage) and endoderm (glandular tissues).(TIF)Click here for additional data file.


Preclinical evaluations of chemotherapies depend on clinically relevant animal models for pancreatic cancer. The injection of syngeneic murine adenocarcinoma cells is one efficient option to generate carcinomas in mice with an intact immune system. However, this option is constrained by the paucity of appropriate cell lines.The murine pancreatic adenocarcinoma cell lines 6606PDA and 7265PDA were compared to the 6606l cell line isolated from a liver metastasis from mice suffering from pancreatic cancer. In tissue culture 6606PDA and 6606l proliferated faster than 7265PDA. 7265PDA cells were, however, significantly more sensitive to gemcitabine as assessed by BrdU-incorporation and trypan blue exclusion assays in vitro. Within 1 week after injection of either one of these three cell lines into the pancreas of C57BL/6J mice, carcinomas were observed by T2 weighted magnetic resonance imaging and histology. Three weeks after injecting 6606PDA or 6606l cells large carcinomas could be characterized, which were surrounded by extensive desmoplastic reaction. After injection of 7265PDA cells, however, remission of cancer was observed between the first and the third week. Compared to 6606PDA cell derived carcinomas a higher apparent diffusion coefficient was quantified by diffusion weighted magnetic resonance imaging in these tumors. This correlated with reduced cancer cell density observed on histological sections.All three cell lines can be used in vitro for testing combinatorial therapies with gemcitabine. The 6606PDA and 6606l cell lines but not the 7265PDA cell line can be used for evaluating distinct therapies in a syngeneic carcinoma model using C57BL/6J mice. Diffusion-weighted MRI proved to be an appropriate method to predict tumor remission. Although multiple radiation therapies and chemotherapies in addition to surgical intervention have been evaluated over the last decades, the 5-year survival rate of pancreatic cancer patients is still only 7 % . RecentlThe evaluation of therapies in tissue culture along with the analysis in an orthotopic cancer model combines the advantages of in vitro studies with the advantages of a clinically relevant animal model , 6. TissHowever, only few cell lines are available for PDA in a syngeneic orthotopic cancer model. Panc02 cells, derived from C57BL/6 mice after treating the animals with 3-methyl-cholanthrene, were originally characterized more than 30 years ago . These pThe purpose of this study was to compare the characteristics of two novel cell lines, 7265PDA and 66061, with 6606PDA cells in vitro. In addition, we evaluated these cell lines in a mouse model after orthotopic injection by analyzing tumor growth using magnetic resonance imaging (MRI) at two different time points.When plated on tissue culture dishes, the cells of the murine cell lines, 6606PDA and 6606l, showed a similar morphology. At low cell density these cells had a stretched fibroblast like appearance Fig. a. HoweveIn order to evaluate if these cell lines are sensitive to gemcitabine, an established drug for chemoterapy, we treated all three cell lines with distinct concentrations of gemcitabine and quantified cell proliferation indirectly by WST-assay Fig. a, b or dIn order to evaluate, if these cell lines can be used in a syngeneic orthotopic pancreas carcinoma model, these cells were injected into the pancreas head of C57BL/6J mice on day 0 and the pancreata were analyzed during the early phase (on day 5–7) and during the late phase, on day 20 or 21 Fig. a. After nu/nu mice with 7265PDA cells and observed that all mice developed carcinomas within 21 days . The remission of carcinomas after injection of 7265PDA cells in C57BL/6J mice suggests that this mouse strain is not syngeneic to this cell line. Indeed, information obtained from the laboratory of David Tuveson  suggests that this cell line was isolated from a mouse with a mixed Bl6/129 background. Thus, for 7265PDA cells the use of immunocompromised mouse strains or mice with matched histocompatibility will be mandatory.To monitor tumors, we assessed the pancreata of mice by 7 T MRI during the early phase day 5 or 6) and during the late phase of tumor growth (day 20). Carcinomas could be identified during the early phase irrespective of the cell line used  all three cell lines will be useful in studying novel combinatorial therapies in vitro using gemcitabine, (2) the 6606PDA and 6606l cells might be very suitable in studying various aspects of cancer immunology in C57BL/6J mice, and that (3) diffusion weighted MRI can be used to define immune mediated cancer rejection.G12D oncogene in the pancreas [R172H and KRASG12D. These three cell lines were a generous gift from Prof. Tuveson  and were isolated in his lab according to Schreiber et al. [3 cells per well in a 12 well plate and counting cells after 24, 48, 72, or 96 h. Expansion of cells was also determined indirectly by WST-assay after plating of 4 × 103 cells per well in a 96 well plate, growing the cells 48 h, and determining cell metabolism with the Cell Proliferation Reagent WST-1 . To evaluate inhibition of proliferation by gemcitabine 4 × 103 cells per well were plated in a 96 well plate, grown for 24 h, and treated with the indicated concentration of gemcitabine and the BrdU labeling reagent  for additional 24 h. The incorporation of BrdU was then quantified with the colorimetric Cell Proliferation ELISA (Roche Diagnostics). To evaluate induction of cell death by gemcitabine 3 × 104 cells per well were plated in a 24 well plate, incubated for 24 h, and treated with 625 nM gemcitabine or medium lacking gemcitabine for additional 48 h. Cell death was then quantified by trypan blue staining solution .The murine cell lines, 6606PDA and 6606l, were isolated from pancreatic carcinoma or a liver metastasis detected in a mouse after p48-cre induced expression of the KRASpancreas . The 726r et al. . Brieflynu/nu mice were purchased from The Jackson Laboratory  and bred in our local animal facility. Mice were kept on water and standard laboratory chow ad libitum and all experiments were executed in accordance with German legislation and the EU-directive 2010/63/EU. As published previously, laparotomy was performed on anesthetized mice (1.2–2.5 % isoflurane), 2.5 × 105 carcinoma cells were injected  into the pancreas head, and the abdominal cavity was closed by sutures [Male C57BL/6J and NMRI-Foxn1 sutures . For paiBlood glucose concentrations were measured with the blood glucose meter Contour  and the tissue was sampled on days defined in Fig. 3, 24 slices, acquisition time: 9:46 min).MRI was performed on anesthetized (1.2–2.5 % isoflurane) mice at day 5–6 and day 20. Animals were scanned in 7 T small animal MRI  with a whole mouse body coil . The imaging protocol included morphological T2 weighted turbo spin echo (T2w-TSE) and diffusion weighted imaging (DWI). Tumor sizes were assessed in high resolution T2-weighted images of transversal plane images  TR: 9000 ms; TE: 85 ms; FA: 90°; FoV: 35 mm × 35 mm; matrix: 256 × 256; 10 slices of 0.7 mm per slice.The ADC value was calculated from echo planar imaging DWI-sequence  and ImageJ  for ROI placement during ADC evaluation. For evaluation of necrosis and vital tumor tissue T2w images and ADC-maps were superimposed. For each carcinoma the mean ADC of three ROIs, fitted to the outer tumor tissue rim, was calculated.Data presentation and statistics were performed as described previously , 23. The


Overall, no correlation was found between trametinib IC50 values and inhibition of ERK signaling. Inhibition of ERK phosphorylation was observed at trametinib concentrations not affecting proliferation, and sensitivity of cell proliferation to trametinib was found in cell lines with low ERK phosphorylation. Evidence was found for synergy between trametinib and either everolimus, NVP-BEZ235 or GSK2126458, but this was cell line specific. The results have implications for the clinical application of PI3K/mTOR and MEK inhibitors.Cellular signaling pathways involving mTOR, PI3K and ERK have dominated recent studies of breast cancer biology, and inhibitors of these pathways have formed a focus of numerous clinical trials. We have chosen trametinib, a drug targeting MEK in the ERK pathway, to address two questions. Firstly, does inhibition of a signaling pathway, as measured by protein phosphorylation, predict the antiproliferative activity of trametinib? Secondly, do inhibitors of the mTOR and PI3K pathways synergize with trametinib in their effects on cell proliferation? A panel of 30 human breast cancer cell lines was chosen to include lines that could be classified according to whether they were ER and PR positive, HER2 over-expressing, and “triple negative”. Everolimus (targeting mTOR), NVP-BEZ235 and GSK2126458 (both targeting PI3K/mTOR) were chosen for combination experiments. Inhibition of cell proliferation was measured by IC The MAPK (Mitogen activated protein kinase) pathway (RAS-RAF-MEK-ERK) and PI3K-AKT-mTOR pathways play dominant roles in regulating diverse cellular processes, including proliferation and survival, in breast cancer. These pathways have been identified as important for breast cancer behavior for a number of years V600E or V600K mutations Since MEK is the downstream effector of BRAF, MEK inhibition is an attractive strategy to block activation of the MAPK pathway and could also potentially block reactivation of the MAPK pathway in BRAF inhibitor–resistant disease We have chosen trametinib in vivo compared with single agents alone in neuroendocrine tumors Recently, co-targeting the PI3K and RAS pathways was shown to be an effective therapy Culture conditions have been described previously Tamoxifen was purchased from Sigma . Everolimus and trametinib were purchased from Selleck Chemicals . Trametinib was also obtained from Jinan Trio Pharmatech co., Ltd . NVP-BEZ235 3H-thymidine was added to each well and incubated for 6 h, after which the cells were harvested onto glass fiber filters using an automated TomTec harvester. Filters were incubated with Betaplate Scint and thymidine incorporation measured in a Trilux/Betaplate counter. Effects of inhibitors on cell proliferation were determined relative to the incorporation of 3H-thymidine into DNA of control (non-drug-treated) cells.Cell proliferation was measured using thymidine incorporation in which 3000 cells were seeded in 96 well plates in the presence of varying concentrations of inhibitors for 3 days. Briefly, 0.04 µCi of Breast cancer cell lines were grown to log-phase, washed twice with ice-cold PBS, and lysed in SDS lysis buffer according to the manufacturer’s protocol . Protein concentration was quantified using the bicinchoninic acid reagent (Sigma). Cell lysates containing 25 µg of protein were separated by SDS-PAGE gel electrophoresis, and transferred to PVDF membranes (Millipore). Membranes were immunoblotted with antibodies against phospho-Akt (S473), total Akt, phospho-p70S6K (T389), total p70S6K, phospho-rpS6 (S235/236), total rpS6, phospho-ERK (T202/Y204), total ERK, , tubulin (Sigma), and actin (Millipore). Bound antibody was visualized using SuperSignal West Pico  or ECL plus  and the chemiluminescence detection system by Fujifilm Las-3000. Densitometry was performed using ImageJ. The relative intensity of phosphorylated proteins was normalized using either tubulin or actin as the standard. The fold change was then calculated between MCF7 and BT20 as standard reference.http://www.combosyn.com/) was used to calculate combination index.The Chou-Talalay method for drug combination is based on the median-effect equation and was used to indicate drug interactions p<0.05 denotes a statistically significant difference. T-test or Mann-Whitney Rank Sum Test was used for comparison between two groups. Correlation analysis was performed with Spearman’s rank correlation coefficient (R) and statistical significance (P) using SigmaPlot. Values of P<0.05 were considered to be statistically significant.Data were analyzed using a one-way ANOVA coupled with multiple comparisons versus treatment control applying the Holm-Sidak method correction, where 3H-thymidine incorporation proliferation assay. Results were compared to those of everolimus, NVP-BEZ235 and GSK2126458  expression: MCF-7 and T47D were ER+, SKBr3 was HER2+ and MDA-MB-231 was triple-negative. PI3K and MAPK pathway usage was analyzed by western blots . The celK2126458  and 3. MK2126458 . Lower lK2126458 . For theThe cellular response of the cell lines to trametinib was then assessed by measuring phosphorylation of ERK . PhosphoAlthough trametinib did not inhibit proliferation of the MCF-7, T47D and SKBr3 lines at the concentrations at which it fully suppressed ERK phosphorylation, it was possible that its effect on ERK phosphorylation could sensitize these cells to inhibition by other drugs. We therefore measured the effects of combinations of trametinib and PI3K/mTOR inhibitors   and 6. TSince no significant changes in growth inhibition with concurrent inhibitors treatment were observed in MDA-MB-231 cells , drug ef50 values) by trametinib. However, estrogen receptor positive breast cancer cell lines showed significant resistance  to trametinib (p  = 0.04).The observation  that MDA50 values of less than 20 nM, while MCF-7 parental (IC50 = 305 nM), TamC3 and TamR3 (both with IC50 > 1000 nM) showed relative resistance to trametinib. No significant correlation was observed between the degree of ERK phosphorylation and trametinib sensitivity  MCF-7 tamoxifen-resistant sub-lines sitivity .50 values, trametinib sensitivity varied over a range of more than 180-fold. This range may reflect both the activity of the pathway and differences in drug uptake; trametinib is an inhibitor of ATP-binding cassette efflux transporters such as p-glycoprotein (see MEKINIST Trametinib tablet product monograph), but differences in uptake/efflux should not affect the relationship between sensitivity and pathway utilization. In our series of cell lines, sensitivity did not seem to be related to mutational status , with or without ERK activation, cannot predict growth sensitivity. Rapamycin and AKT inhibitor uniformly abrogated mTOR inhibition-induced AKT activation but failed to induce antitumor responses in a subset of head and neck cancers In conclusion, the lack of efficacy of protein phosphorylation measurement as a predictor of trametinib sensitivity adds to the difficulty of identifying predictive biomarkers for targeted anticancer therapy. Furthermore, utilization of the MEK-ERK signaling pathways, as determined by phosphorylation of signaling components, varied widely across a series of cell lines and did not directly reflect mutation of genes coding these components Figure S1Drug combination effect on PARP in MCF-7, T47D and SKBr3 cell lines after 24 h as demonstrated by immunoblotting with anti-PARP antibodies.(EPS)Click here for additional data file.Figure S2Phosphorylation of p70S6K, AKT, and ERK in the breast cancer cell lines, including MCF-7 and its sub-lines . Immunoblots with antibodies specific for phosphorylated and total protein are indicated below the corresponding control. Tubulin or actin are the loading control. Bands are normalized to tubulin or actin control and expressed as the mean from two experiments. The immunoblot for MCF-7 and its fulvestrant sub-lines were adapted from Leung et al. (TIF)Click here for additional data file.


Combination of HLM006474 with cisplatin and gemcitabine demonstrate little synergy; however, HLM006474 synergizes with paclitaxel. Surprisingly, we discovered that brief treatment of cells with HLM006474 led to an increase of E2F3 protein levels (due to de-repression of these promoter sites). Since paclitaxel sensitivity has been shown to correlate with E2F3 levels, we hypothesized that HLM006474 synergy with paclitaxel may be mediated by transient induction of E2F3. To test this, H1299 cells were depleted of E2F3a and E2F3b with siRNA and treated with paclitaxel. Assays of proliferation showed that both siRNAs significantly reduced paclitaxel sensitivity, as expected. Taken together, these results suggest that HLM006474 may have efficacy in lung cancer and may be useful in combination with taxanes.The CDK/Rb/E2F pathway is commonly disrupted in lung cancer, and thus, it is predicted that blocking the E2F pathway would have therapeutic potential. To test this hypothesis, we have examined the activity of HLM006474  in lung cancer cell lines as a single agent and in combination with other compounds. HLM006474 reduces the viability of both SCLC and NSCLC lines with a biological IC The retinoblastoma protein  is widely recognized as one of the most important tumor suppressors in humans. Along with the similar “pocket” proteins p107 and p130, it is responsible for regulating cell cycle progression Depending upon context, E2F family members can serve as transcriptional activators that drive cell cycle progression or transcriptional repressors which restrain cell cycle progression RB1 gene is intact, inhibitors of CDK4 and 6 would represent a potential way to target this pathway. This hypothesis has been examined in several clinical trials and preliminary results in breast cancer are very promising The CDK/Rb/E2F pathway is disrupted in virtually every instance of human lung cancer, the leading cause of cancer-related death worldwide 50 of HLM006474 is relatively high (30 µM), it has found use as a tool compound In vivo studies indicate that the effects of 6474 treatment on different cell lines included a reduction in cell proliferation and an increase in apoptosis and reduced invasion in a three-dimensional tissue culture model system 50 that varies between 15 and 75 µM. Combination of HLM006474 with common chemotherapeutic agents cisplatin and gemcitabine demonstrates little synergy; however, HLM006474 synergizes with paclitaxel. Taken together, these results suggest that HLM006474 may have efficacy against cancers in which E2F is deregulated and may be useful in combination with other drugs that target cell cycle components.The benefit of CDK inhibitors may be limited to tumors in which the Rb protein remains WT and functional, and thus, reagents that could target this pathway downstream of Rb might be useful in cancers where Rb is commonly mutated (such as lung cancer). To test this hypothesis, we have examined the activity of HLM006474 against a panel of lung cancer cell lines. HLM006474  is a small molecule pan-inhibitor of E2F-DNA binding Mycoplasma. SCLC cell lines were grown in RPMI 1640 with 10% FBS and 1% pen/strep. NSCLC cell lines were cultured in RPMI 1640 with 10% FBS without antibiotics. HLM006474 was synthesized and validated by the Moffitt Chemistry Core as previously described Lung cancer cell lines were obtained from ATCC or originators and were provided by the Moffitt SPORE in Lung Cancer Cell Core facility. All lines are authenticated by genotyping and maintained free of et alCells plated at ∼50% confluency in 6-well plates were transfected using Lipofectamine 2000 (Life Technologies) according to vendor instructions with 200 pmol of either siGENOME Non-Targeting siRNA #2 (Dharmacon) or siRNA targeting E2F3a or E2F3b as described in a paper by Hurst 2. The next day, the drugs were diluted in media and 6 µL of these dilutions added to appropriate wells using an automated pipetting station. Four replicate wells were used for each drug concentration. The cells were incubated with the drug for 120 hours, at which time, 5 µl CellTiter-Blue reagent  was added. Cell viability was assessed by the ability of the remaining treated cells to bioreduce resazurin to resorufin (579 nm Ex/584 nm Em). Fluorescence was read with a Synergy HT microplate reader . IC50s were determined using a sigmoidal equilibrium model regression using XLfit version 4.3.2 (ID Business Solutions Ltd.) and is defined as the concentration of drug required for a 50% reduction in growth/viability. For 3--5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium (MTS) cell viability assays, CellTiter 96 AQueous One Solution from Promega was added according to vendor instructions to cells for 2 hours following treatment with drug at the noted dose for 72 hours. All experiments were performed in triplicate and repeated at least three times.The antiproliferative activity of compounds and their combinations was evaluated using a high-throughput CellTiter-Blue cell viability assay (Promega), as previously described 50 values obtained from single drug cell viability assays were used to design combination experiments. For 6474 combinations with cisplatin, gemcitabine and paclitaxel these ratios were 1∶1, 500∶1 and 4000∶1, respectively. For drug combination experiments, the cell viability assays were performed and the results analyzed for synergistic, additive, or antagonistic effects using the combination index (CI) method developed by Chou and Talalay The ICWestern blots were performed as previously described 5′-GCTGGACCACCTGATGAATATC-3′), E2F1 R (5′-TCTGCAATGCTACGAAGGTCCTG-3′), E2F3a/b F (5′-CGTCTCTTGGTCTGCTCAC-3′), E2F3a/b R (5′-CACTTCTGCTGCCTTGTTC-3′), E2F4 F (5′- CTGAAGAGTGTGAGTGGTC -3′), E2F4 R (5′- GCAGAGGTGGAGGTGTAG -3′), tubulin F (5′-GGGGCTGGGTAAATGGCAAA-3′), tubulin R (5′-TGGCACTGGCTCTGGGTTCG-3′), MCM2 F (5′-CTGTGTGTGGTGAGGGACAC-3′), MCM2 R (5′-CTTGTCCTGGTCCATCTGGT-3′), MCM10 F (5′-CGTCAGTGAGCAGCATGAAT-3′), MCM10 R (5′-TCCCGTTCCCATTTGTAGAG-3′), CCNE2 F (5′-CAGGTTTGGAGTGGGACAGT-3′), CCNE2 R (5′-ACTTCCTCCAGCATAGCCAA-3′), GAPDH F (5′-GAGTCAACGGATTTGGTCGT-3′), and GAPDH R (5′-TTGATTTTGGAGGGATCTCG-3′).RNA was harvested from cells using the RNeasy mini kit from Qiagen. Reverse transcription polymerase chain reaction (PCR) was then performed using the iScript cDNA synthesis kit (Bio-Rad). This cDNA was then utilized in real-time PCR using either iQ SYBR Green Supermix (Bio-Rad) or PerfeCTa SYBR Green SuperMix . E2F1, E2F3, E2F4, tubulin, MCM2, MCM10, CCNE2, and GAPDH primers were ordered from Integrated DNA Technologies. Primer sequences are as follows: E2F1 F  and expression of the control gene (tubulin) was calculated for each cell line at each time point. The difference between each of the non-0 hour time points and the 0 hour time point readings for each gene in each cell line was calculated using T-Tests with Welch's correction. The paclitaxel IC50 in seventeen lung cancer cell lines  µM, which is essentially identical to the biochemical IC50 of 29.8 . Surprisingly, protein levels of both E2F3a and b isoforms increased in early time points . Levels of the E2F1 protein increased more modestly following treatment, peaking between 6 and 12 hours and returning to baseline levels after 24 hours. In real-time PCR analysis with tubulin as a control, E2F3 mRNA levels increased significantly after 3 hours of treatment and then decreased in each subsequent time point  and gemcitabine . In contrast, 6474 weakly synergizes with paclitaxel . To further explore the nature of the synergy between 6474 and paclitaxel, H1299 cells were treated with modest doses of each drug alone or in combination and utilized in Western blot analysis. The appearance of cleaved PARP in cells treated with the drug combination confirms that the combination of 6474 and paclitaxel induces more apoptosis than either drug alone , but showed no synergy with cisplatin  or gemcitabine .Having established that 6474 has anti-proliferative effects on lung cancer cell lines, but may influence E2F-regulated genes in a complex manner, we sought to determine if 6474 would synergize with chemotherapeutic drugs commonly used in lung cancer treatment. H1299 cells were treated with 6474 alone and in combination with cisplatin, gemcitabine and paclitaxel. Combinations were chosen based on the IC50 of each cell line , and then these values were correlated to the paclitaxel logIC99 cells Fig 4A. The CDK/Rb/E2F pathway represents a good target for the treatment of various solid tumors. Although development has been slow due to toxicity of early compounds, CDK inhibitors are starting to gain traction in clinical trials We propose the model in We have demonstrated that HLM006474 is effective in lung cancer cell lines. Furthermore, we have shown that 6474 synergizes well with paclitaxel, potentially due to 6474's effects on E2F3 levels. Taken together, these results suggest that potent, specific activator E2F inhibition may be useful in the treatment of NSCLC in the future , and that E2F3 levels may be a good predictor of paclitaxel sensitivity in NSCLC.


Breast cancer researchers use cell lines to model myriad phenomena ranging from DNA repair to cancer stem cell phenotypes. Though appropriate, and even requisite, for many studies, the suitability of cell lines as tumour models has come into question owing to possibilities of tissue culture artefacts and clonal selection. These issues are compounded by the inability of cancer cells grown in isolation to fully model the in situ tumour environment, which also contains a plethora of non-tumour cell types. It is thus important to understand similarities and differences between cancer cell lines and the tumours that they represent so that the optimal tumour models can be chosen to answer specific research questions.In the present study, we compared the RNA-sequencing transcriptomes of a collection of breast cancer cell lines to transcriptomes obtained from hundreds of tumours using The Cancer Genome Atlas. Tumour purity was accounted for by analysis of stromal and immune scores using the ESTIMATE algorithm so that differences likely resulting from non-tumour cells could be accounted for.We found the transcriptional characteristics of breast cancer cell lines to mirror those of the tumours. We identified basal and luminal cell lines that are most transcriptionally similar to their respective breast tumours. Our comparison of expression profiles revealed pronounced differences between breast cancer cell lines and tumours, which could largely be attributed to the absence of stromal and immune components in cell culture. A focus on the Wnt pathway revealed the transcriptional downregulation or absence of several secreted Wnt antagonists in culture. Gene set enrichment analysis suggests that cancer cell lines have enhanced proliferation and glycolysis independent of stromal and immune contributions compared with breast cancer cells in situ.This study demonstrates that many of the differences between breast cancer cell lines and tumours are due to the absence of stromal and immune components in vitro. Hence, extra precautions should be taken when modelling extracellular proteins in vitro. The specific differences discovered emphasize the importance of choosing an appropriate model for each research question.The online version of this article (doi:10.1186/s13058-015-0613-0) contains supplementary material, which is available to authorized users. Since the establishment of the HeLa cell line in 1951, cell lines have been an integral part of cancer research, and their use has tremendously advanced understanding of molecular cancer biology ) was calculated for 975 breast tumours by multiplying the scaled estimate data by 10c (where c is Pearson’s correlation coefficient) as the distance and Ward’s agglomeration method (ward.D2). The 5000 most variable genes were also used to compute the Pearson’s correlation coefficient of all the cell line–tumour pairs in a subtype-specific manner. The cell lines were ranked based on their average correlation with all tumours of their respective subtype. Significant differences in relative transcript abundances between cell lines and tumours were calculated with Welch’s t test, and p values were corrected for multiple testing using the Benjamini-Hochberg method. Enrichment for functionally related genes between the two datasets was tested using Generally Applicable Gene-set Enrichment  with Kynductor:  gene setr|>0.2) were filtered from the list of differentially expressed genes, and a new ranked list was generated. Stromal and immune correlations were calculated for each gene set by averaging the stromal and immune Pearson’s correlation coefficients of the essential genes (as determined using the GAGE package).Stromal and immune scores were defined for tumours by ESTIMATE scores  using RNASeqV2 data as previously described , and acc2 copy number value above 0.2 or below −0.2. Selected mutational events were considered if they were found to be significantly altered from or in associated healthy tissue in the original TCGA study ) in cell culture, and researchers have drawn conclusions about their absence and mechanisms of action in this context [SFRPs to be high in tumours and strongly correlated with stromal scores, we should recognize that looking at these proteins in tumour cell monoculture may not be appropriate. In fact, given their roles as matricellular proteins, it would not be surprising if their effects in vivo are quite different than those observed in vitro.A fundamental limitation of cell culture models is that the environment created by culture conditions is markedly different from the breast cancer microenvironment . The los context –44. Hower = −0.27). Thus, the expansion of malignant cells in cell culture likely plays a role in the upregulation of this gene set. However, none of the other upregulated proliferative/metabolic gene sets display this correlation. This suggests, on the one hand, that either the derivation process or the continuous culturing of cell lines selects for a highly proliferative subset of cells. On the other hand, many of the underrepresented gene sets were matrix- or immune-related and tightly correlated with stromal or immune scores, once again indicating that loss of the stromal and immune compartments has pronounced consequences in transcriptional programs observed in cell culture.In broader investigations using gene set enrichment analysis, we observed an enrichment in cell line proliferative and metabolic gene sets, similar to those reported in other studies –47. The Important efforts are being made to systematically compare tumours and cell lines using DNA mutation, copy number and gene expression data from a diverse spectrum of tumour types , 13, 35.


Another hallmark in cancer is the reprogrammed chemotaxis pathways in favour of tumor cell dissemination.Cancer cells, even in the presence of available oxygen, have a glycolysis enhancement. The “aerobic glycolysis” is known as the Warburg effect and it is considered one of the fundamental hallmarks of metabolic alteration during malignant transformation. A feature of many tumors is also a change into ions equilibrium, with particular reference to KThe doubling population time of 5 mM K:D-rib treated Hs 578T (HTB-126 ® ATCC) cell line is reduce by 30% respect to the control. During the chemotactic invasion assay, the relative number of motile and invasive cells, counted inside the FBS-AGAR spot, shows a decrease with the maintenance of the treatment reaching the 25% after nine days. Hs 578Bst (HTB-125 ® ATCC) non-tumor cell line treated for nineteen days with 5 mM K:D-rib was split twice as well as the control. No morphological change was visible in the treated respect to untreated cells.in vitro with the capability of Hs 578 T cell line to migrate under chemotactic stimuli. Despite this, K:D-rib solution, does not exhibit any appreciable toxicity as confirmed by the proliferation assay accomplished on Hs 578Bst cell line.We demonstrate that the synergic action of potassium bicarbonate and D-ribose has effect on Hs 578T cancer cell line proliferation reducing the cell cycle time. At 5 mM concentration, K:D-rib is able to modify the tumorigenic potential of human breast cancer cell line Hs 578T, interfering  The role of D-ribose in the energetic metabolism  and ll known ,[7]. It adruplex . Agents adruplex ; so physOur most recent work demonstrates that the 5 mM K:D-rib solution slows the replication of the Hs 578T cell line and has a cytostatic effect on canine carcinoma cell line (A72) . The effIt is well known that cancer cells show an increase in the consumption of sugars, in particular glucose, named “Warburg Effect” ,16]. Th. Th16]. + through the plasma membrane to carry out this transport . Th. Th27]. The data of the chemoinvasion assay and the results from the cancer and not cancer cell proliferation demonstrate that the 5 mM K:D-rib water solution is a powerful inhibitor of cancer potential and a strong antiproliferative agent. Despite this, K:D-rib solution, does not exhibit any appreciable toxicity as confirmed by the proliferation assay accomplished on Hs 578Bst cell line.LB had a INBB grant supported by Valsè Pantellini Foundation that has specific interest in the study of Potassium Bicarbonate and D-Ribose compounds.AAB, IO; SC declare that they have no competing interests.LB contributed in the experimental design, carried out the experiments with particular reference of Chemotactic invasion assay. AAB was involved in the cell counting using the ImageJ program and results discussion. IO contributed to results discussion and manuscript revision. The SC analyzed and interpreted the data, and contributed in drafting and manuscript revision. All of the authors read the manuscript, contributed in correcting it and approving its final version.


The receptor tyrosine kinase (RTK) EGFR is overexpressed and mutated in NSCLC. These mutations can be targeted by RTK inhibitors (TKIs) such as erlotinib. Chromatin-modifying agents may offer a novel therapeutic approach by sensitizing tumor cells to TKIs.EGFR mutant, adenocarcinoma), A549  and NCI-H460  were analyzed by SNP6.0 array. Changes in proliferation after panobinostat  and erlotinib treatment were quantified by WST-1 assay and apoptosis by Annexin V/7-AAD flow cytometry. Abundance of target proteins and histone marks  was determined by immunoblotting.The NSCLC cell lines HCC827 (EGFR wt cell lines A549 and NCI-H460 were quite insensitive to the growth-inhibitory effect of erlotinib (IC50 70-100 μM), compared to HCC827 (IC50 < 0.02 μM). All three cell lines were sensitive to PS treatment . The combination of both drugs further reduced proliferation in HCC827 and in A549, but not in NCI-H460. PS alone induced differentiation and expression of p21WAF1/CIP1 and p53 and decreased CHK1 in all three cell lines, with almost no further effect when combined with erlotinib. In contrast, combination treatment additively decreased pEGFR, pERK and pAKT in A549. Both drugs synergistically induced acH3 in the adenocarcinoma lines. Surprisingly, we also observed induction of H3K4 methylation marks after erlotinib treatment in HCC827 and in A549 that was further enhanced by combination with PS.As expected, the PS sensitized lung adenocarcinoma cells to the antiproliferative effects of erlotinib. In these cell lines, the drug combination also had a robust, not previously described effect on histone H3 acetylation and H3K4 methylation. EGFR) mutational status  . Amplifications of KRAS could be confirmed for A549 (KRAS mut) and the KRAS wt HCC287 [MET, which are closely linked to TKI resistance [ALK, BRAF and PI3K,  variations by SNP array, since copy number amplifications of oncogene  which wet HCC287 . None ofsistance , 26. No K, Table .Table 1CEGFR wildtype cells with an erlotinib concentration of 2 μM. Additionally, we performed extensive dose-findings to determine the most effective but also least toxic doses for PS in combination with erlotinib  plays a major role in the metastatic behavior of NSCLC. Also, loss of the epithelial marker E-cadherin is a hallmark in the development of TKI resistance . In HCC8As expected, PS robustly induced acetyl-histone H3 (acH3). Erlotinib had no effect on H3 acetylation, but it enhanced the effect of PS on acH3 (in HCC827 and A549). In NCI-H460, it modestly induced acH3 after 24 h, but the combination treatment did not lead to an additive effect compared to PS alone  and of KDM5B (NCI-H460). Losses were detected of KDM1A and KDM4A (A549) and KDM1A and KDM2A (NCI-H460). No copy number changes could be seen for histone methyltransferases SETD1A, SETD1B, KMT2A/B/C/D . We found gains for DM5A HCC87 and of EGFR genotype [The introduction of tyrosine kinase inhibitors antagonizing overactivated or amplified EGFR has strikingly expanded the therapeutic armamentarium in non-small cell lung cancer. However, development of resistance to TKIs is a major clinical problem, since it occurs in almost all patients receiving these drugs for prolonged periods. Therefore strategies to overcome secondary resistance to TKIs have been investigated. These include the usage of epigenetically active agents such as HDACis. In NSCLC, this structurally diverse group of compounds has been tested pre-clinically and in part also already clinically. While single agent HDACi treatment has only modest activity, drug combinations with chemotherapy have been studied, with some trials being positive , others genotype . The comgenotype .In the present study, we attempted to unravel mechanisms of action of the combination treatment of PS with erlotinib in NSCLC cell lines representing different histological subtypes and different genotypes. The combination treatment revealed variable responses: whereas proliferation of the adenocarcinoma cell lines was significantly reduced, the large-cell carcinoma cell line did not respond.We also hypothesized that the inhibitory effect of erlotinib on EGFR phosphorylation would be enhanced by the HDAC inhibitor, which could indeed be demonstrated for A549 cells and, to a much lesser degree, for HCC827. Cooperative negative effects on downstream signals, e.g. ERK and AKT were also seen only in these two cell lines. Interestingly, in HCC827 erlotinib hardly reduced phospho-EGFR levels and even upregulated phospho-ERK expression. These findings suggest the, already described, partial outgrowth of a TKI-insensitive cell clone. NCI-H460 displayed no change in phospho-AKT expression and phospho-ERK was even upregulated after PS  treatment, underlining the insensitivity to TKIs as seen in the proliferation experiments.WAF1/CIP1 and p53 varied broadly, with EGFR wt cell lines being overall more sensitive. Here, especially NCI-H460 showed an additive effect of both drugs on p21WAF1/CIP1 expression and p53 was upregulated by PS only. This previously described [WAF1/CIP1 and p53 was also present in A549. In HCC827 cells erlotinib counteracted the impact of PS on p21WAF1/CIP1 expression; p53 was reduced by PS with no effect of erlotinib. We could also confirm the correlation between HDAC inhibition and p21WAF1/CIP1/p53-dependent downregulation of CHK1 [WAF1/CIP1/p53 upregulation and CHK1 downregulation and inhibition provides a reasonable mechanism for the observed growth inhibition after HDACi treatment.Similarly, induction of p21escribed  PS-induc of CHK1 . AdditioHDAC inhibitors have been demonstrated to also affect histone methylation, as we could recently show in a model of acute myeloid leukemia . TherefoEGFR mutations, to the antiproliferative effects of the TKI erlotinib, warranting further development of this approach within a clinical phase II trial. Our study suggests that the mechanism of action of resensitization involves reactivation of different sets of tumor suppressor genes. We were able to show that this is mediated by inducing an active chromatin configuration via deposition of activating histone marks, such as H3 acetylation and H3K4 methylation. This general strategy may become even more relevant in the future, since resistance to EGFR T790M-specific third generation kinase inhibitors, like AZD9291 and Rociletinib (CO-1686), already occur in the clinic which needs to be overcome or might even be prevented [Pan-HDAC inhibitors such as PS may provide a viable option to (re) sensitize NSCLC cells, particularly of adenocarcinoma subtype with revented .


Clinical responses to anti-cancer therapies often only benefit a defined subset of patients. Predicting the best treatment strategy hinges on our ability to effectively translate genomic data into actionable information on drug responses.in vitro drug responses. We presented an efficient in-silico pipeline for integrating heterogeneous cell line data sources with the simultaneous modeling of drug response values across all the drugs and cell lines. Potential signature genes correlated with drug response (sensitive or resistant) in different cancer types were identified. Using signature genes, our collaborative filtering-based drug response prediction model outperformed the 44 algorithms submitted to the DREAM competition on breast cancer cells. The functions of the identified drug response related signature genes were carefully analyzed at the pathway level and the synthetic lethality level. Furthermore, we validated these signature genes by applying them to the classification of the different subtypes of the TCGA tumor samples, and further uncovered their in vivo implications using clinical patient data.To achieve this goal, we compiled a comprehensive collection of baseline cancer genome data and drug response information derived from a large panel of cancer cell lines. This data set was applied to identify the signature genes relevant to drug sensitivity and their resistance by integrating CNVs and the gene expression of cell lines with Our work may have promise in translating genomic data into customized marker genes relevant to the response of specific drugs for a specific cancer type of individual patients. Comparisons have shown that cell lines mirror many aspects of tumor molecular pathobiology. Measurements of their genetic characteristics [Massive chemical compounds are currently being investigated for their potential use as anti-cancer drugs. Although a few of the compounds have been successfully used to treat defined patient subsets, a large set of the compounds is poorly characterized. It remains a great challenge to match the compounds with the subset of patients most likely to benefit from them. The ideal data set to achieve this goal would include the systematically characterized drug responses/sensitivities across a large cohort of patients. However, for most of the compounds tested, eristics , 2 and teristics –5, as weeristics –9.in vitro cell line data for drug response identification, another issue that arises is drug resistance. It should be noted that a precise definition of “drug response” includes both “sensitive” and “resistant” response, where “sensitivity” refers to the effectiveness of different cell line responses to different drug perturbations, while “resistance” means the reduced effectiveness of a drug in the perturbation of a cell line. However previous literatures often mention “drug response” and “drug sensitivity” as two alternative claims of the same concept. Therefore in our study, for most cases readers can take “drug sensitivity” and “drug response” as identical terms. In addition, cancer drug resistance can be broadly divided into two categories, primary and acquired resistance [in vitro cell line systems also provide us with an irresistible opportunity to uncover anti-cancer primary drug resistance mechanisms. Similar studies to this will provide useful insights for clinical trials if patient data are incorporated.Coupled with the accumulated sistance , 11. Whisistance . With thin vitro cell line systems is still lacking. Furthermore, the implications of in vitro screening for the in vivo samples is also worthy of investigation.NCI-60 represents the pioneering cell line panel, where the responses of 60 genomically characterized cell lines have been measured for several thousands of compounds . Recentlin-silico pipeline to identify signature genes that may correlate with drug response, especially primary drug resistance for different cancer types. We achieved this by integrating an analysis of transcriptional profiles with genomic characteristics, specifically the copy number variation of cell lines based on in vitro drug responses. Second, we presented a novel collaborative filtering-based drug sensitivity prediction model and measured it against the launched NCI-DREAM challenge on breast cancer cells by using the signature genes. Third, we conducted a comprehensive analysis of the identified signature genes related to drug resistance after excluding the cancer cell lines with disparate Copy Number Variations (CNVs) or mutation profiles. Fourth, we validated these signature genes and uncovered their implications in vivo using clinical patient data.In this study, we aimed to collect and curate comprehensive drug-cell line response data from various cell line data sources, and then based on this integrated dataset, we achieved the following goals: First, we designed a novel and efficient i.e., the transcriptional profiles (the gene expression) and the CNV profiles. As suggested in two high impact studies on drug response analysis [It should be noted that in our study we focused on the integration of the two cell line profiles, analysis , 6, geneanalysis , 16. It analysis . As indianalysis . In a luanalysis . Neverthanalysis –24; (2) Materials and Methods). This dataset was applied to identify the signature genes relevant to drug sensitivity and to further their resistance by integrating CNVs and the gene expression of cell lines with in vitro drug responses. We designed an efficient in-silico pipeline to achieve this goal and identified the signature genes with simultaneous modeling of drug response values across all the drugs and cell lines. The pipeline efficiently integrates heterogeneous cell line data sources and has proven to be highly accurate in in predicting sensitivity   was usedwpc-index) [wpc-index of 0.583. The concordance index (c-index) is a nonparametric scoring method that provides a measure of similarity between two lists of measurements or ranks [Furthermore, Group Sparse Lasso was used to derive signature genes relevant to drug responses of a given cancer type based on transcriptional information . By using signature genes, we tested our prediction method on data released from the NCI-DREAM drug sensitivity prediction challenge . As all c-index)  of 0.589or ranks . The aboRibosome” was the most significantly enriched pathway for the signature genes of breast cancer, SCLC, NSCLC and skin cancer  and IGFBP3 (Gene B) correlated to Gefitinib sensitivity. It has been reported that IGFBP3 is under-expressed in Gefitinib-resistant cells, and the addition of recombinant IGFBP3 restored the ability of Gefitinib to downregulate PI3K/AKT signaling and inhibit cell growth [IGFBP3 could induce sensitivity to EGFR-TKI Gefitinib.A large body of evidence points out that the onset of synthetic lethality (SL) may provide a useful tool for overcoming drug resistance to anticancer regimens. Here, we mapped the targets of the 94 collected drugs and the selected signature genes to a well curated dataset of the SL gene pairs and synthetic dosage lethality (SDL) gene pairs, as presented in the work of Livnat Jerby-Arnon  See Mat. Most ofl growth . This inin vitro cell line systems for tumor samples. The gene expression data of tumor samples were retrieved from the TCGA for breast cancer and non-small cell lung cancer (NSCLC), given that other cancer types in our cell line study are not included in the TCGA. The signature genes selected for the two types of cancer cells were separately used to cluster the breast tumor samples and the NSCLC samples. We performed an unsupervised hierarchical cluster analysis for breast tumor samples using signature genes related to drug sensitivity in breast cancer cells. From Figure in vivo.In this study we aimed to investigate the implications of the drug sensitivity related genes identified in the Based on the selected signature genes related to drug sensitivities, we further screened the drug primary resistance related genes based on the integration of gene expression profiles with CNV. Our basic assumptions for primary drug resistance gene screening were that: (1) Drug resistance genes were also drug response related. In other words, we screened drug resistance genes from the former selected signature genes related to drug sensitivities (responses); (2) for each drug tested on multiple cell lines for a specific cancer type, we sorted the cell lines according to their response values (measured in pIC50) in an ascending pattern, and the expression levels of the drug resistance genes in the top activity as well as the bottom activity of the cell lines needed to be well-correlated with the corresponding cell line activities. This can be achieved by, first, making discretization of the cell line activity data to automatically categorize the cell line as sensitive, moderate or resistant to the drug perturbation. Then the spearman correlation of the expression levels of the genes in the sensitive and resistant cell lines with the activity of the sensitive and resistant cell lines can be calculated; (3) the CNV levels of the drug resistance genes in the top activity as well as the bottom activity of the cell lines needed to be well-correlated with the corresponding cell line activities.Based on these criteria, for each drug we identified signature genes related to primary drug resistance as listed in in vitro cell line systems for patient samples, we collected gene expression microarray data obtained from 24 breast cancer tumor biopsies through a clinical trial, which measured the responses of patients to docetaxel neoadjuvant treatment [TOP2A as a potential indicator of drug response to docetaxel in breast cancer. In our cell line analysis, the expression and CNV of TOP2A demonstrated a high correlation with the cell line activity profile for the drug docetaxel. TOP2A was downregulated in resistant tumor samples in contrast to sensitive samples  relevant to drug activity to cisplatin on breast cancer cells were derived from the signature genes for breast cancers  . The Mils Figure . Upregulll death . The mecll death . The indn Figure . It can t cancer –41, and er cells . [43, 44s Figure , they maABCB1, ABCC1 (MRP1) as well as other transporters have been characterized in previous studies for their roles in drug resistance [TOP2A showed a higher expression value and higher CNV values in breast cancer cells sensitive to doxorubicin than those in the resistant cells, while S100P and S100A4 showed lower expression values and lower CNV values in the sensitive cells than those in the resistant ones. Doxorubicin induces cancer cell death by many mechanisms, the most notable is Top2A poisoning, and also the down-regulation of Top2A is obviously detected in doxorubicin resistant MCF7 cells [S100P and S100A4 has been described in doxorubicin-resistant cell lines [BLVRB, MGST1 and H19 have been linked to multidrug resistance, including resistance to doxorubicin [H19 has been found to increase cellular doxorubicin accumulation levels via suppressing MDR1/P-glycoprotein expression which is important in decreasing doxorubicin accumulation levels [ST3GAL1 encodes asialytransferase which participates in the sialylation that is associated with doxorubicin resistance [MRP1) [PRMT6 may also relate to the PI3K/AKT mechanism via PTEN. PTEN is a tumor suppressor gene that inhibits the PI3K pathway, and lower PRMT6 expression may result in increased PTEN expression, decreased cell cycle progression and increased breast cancer cell apoptosis [Doxorubicin is a naturally occurring anthracycline antibiotic that is broadly considered the most active single agent available for the treatment of breast cancer . On the sistance . In our F7 cells . Overexpll lines , 47. BLVorubicin –50. H19 sistance . A possie [MRP1) . PRMT6 mpoptosis .in-silico pipeline to identify signature genes that may be relevant to drug sensitivity, and that further identifies drug resistance genes for different cancer types, by using an integrative analysis of gene expression profiles with copy number variations (CNVs) of cell lines as well as their in vitro drug responses; (2) we presented a novel collaborative filtering based drug sensitivity prediction model, which outperformed the 44 algorithms submitted to the DREAM competition using breast cancer cell data; (3) the functions of the identified signature genes related to drug sensitivities were carefully analyzed at the pathway level, the synthetic lethality level, as well as applied to the classification of the different subtypes of the TCGA tumor samples. Additionally, our in-silico pipeline has shown promise in: (1) translating genomic data into customized maker genes relevant to the resistance of specific drugs in individual patients with a specific cancer type; and (2) serving as the bridge to explore common mechanisms between primary resistance and acquired resistance to a given drug.In the current study, we collected a comprehensive compilation of drug-cell line response data from a large panel of cancer cell lines. Leveraging this dataset, we achieved the following three goals: (1) we designed a novel and efficient in-silico pipeline, which incorporates collaborative filtering based algorithms together with Group Sparse Lasso, achieved superior performance in predicting drug responses and identifying signature genes that may correlate with drug sensitivity and drug resistance. This model allows for the integration of different data sources unlike traditional statistical models. According to the DREAM competition, gene expression microarrays consistently provided the best predictive power among the individual profiling data sets of DNA copy-number variations, transcript expressions, mutations, DNA methylation and protein abundance [in-silico pipeline to the selected signature genes with relevant drug sensitivities for breast cancer, we achieved a wpc-index of 0.589 in the DREAM competition, which was superior to all the other reported approaches.Testing a large number of cell lines and compounds is one important prerequisite for achieving remarkable power in predicting drug responses. Here, we curated a large compilation of drug-cell line response information, consisting of 94 drugs on 608 cancer cell lines. Using the simultaneous modeling of drug responses across all the drugs and cell lines from the large dataset, our A great disparity was observed in the signature genes identified for the 5 different cancer types, which indicates that genes relevant to drug resistance are highly dependent on the disease type. As somatic mutations and genomic plasticity associated with cancer are the foundation of drug resistance , cancer Based on previous studies which have demonstrated that DNA CNVs are influential factors in altered gene expression levels in cancer, CNV information on the corresponding cancer cells was integrated with the selected signature genes to help identify these potential maker genes that may correlate to resistance of a specific drug in a specific cancer cell type. To our knowledge, this is the first time that baseline copy number variation has been integrated with the gene expression of cancer cell lines in identifying maker genes relevant to drug resistance. The marker genes identified for each drug were quite different, and this also implies that genes relevant to drug resistance are highly drug-specific. The current limitation of our method is that we can only identify genes relevant to drug resistance in the pre-collected drugs, totaling 94 at present. Nevertheless, with the rapid accumulation of high-throughput experiments such as the LINCS project, our method will eventually be applied to massive compound data.TOP2A, which encodes the key enzyme involved in DNA replication was proposed as the marker gene most relevant to docetaxel-resistance in breast cancer patients. In addition, the potential maker genes relevant to cisplatin-resistance in TNBC patients were involved in cell communication, which has been correlated with cell death induced by cisplatin [in-silico pipeline provides the opportunity to translate genomic data derived from baseline cancer cell lines into actionable, and individualized maker genes relevant to the resistance of specific drugs in clinical applications.The potential indicator role of the genes in resistance to the corresponding drugs was also explored in the clinical cancer patients. For docetaxel, a well-established clinically anti-mitotic chemotherapy medication that works by interfering with cell division, the gene isplatin . AlthougIn addition to primary or intrinsic resistance, acquired resistance also exists. Primary resistance is a pre-existing resistance that is present prior to the exposure to a given drug. In contrast, acquired resistance develops in tumors that were initially sensitive to the drug, after exposure to this drug . In thisin vitro cell line and drug perturbation data, rather than the validation of the identified genes. Such methods will prove invaluable in the exploration of cancer resistance mechanisms when, in the near future, we will be able to access millions of drug perturbation data generated from in vitro cell line systems and the individual patients receiving personalized medical care.Finally, the rational of our identified drug sensitivity or resistance related genes remains to be further validated by more comprehensive experimental tests, while the basic goal of the current study was to provide an efficient framework for identifying such genes based on the accumulated The gene expression, copy-number variation (CNV), and cancer cell line mutation data was retrieved from a website compiling genomic information on 947 human cancer cell lines, namely the Cancer Cell Line Encyclopedia (CCLE) . We usedin vitro) were all set to pIC50 = −log10 (IC50M). In total, there were 168 drugs tested on 608 cancer cell lines with all three genomic data types of cancer cell lines available.Drug information and drug response measures IC50) were retrieved and curated from the CCLE website together with two other large pharmacogenomic studies, including the Cancer Genome Project (CGP): Genomics of Drug Sensitivity in Cancer (GDSC) 0 were re. IC50 meIt should be noted that the IC50 data of some of the 168 drugs were scattered across multiple cancer types. Drugs missing too much IC50 data (with missing data on > 40% of the 608 cancer cell lines) were removed. Finally, 94 drugs were included for further study. All of these data are available in in-silico pipeline was set up to identify the signature genes relevant to drug sensitivity and resistance for different cancer types. A collaborative filtering based algorithm [Once the baseline cancer genome and drug response data were carefully collected and curated, an efficient lgorithm  was appllgorithm . We furtS S ∈ ℝ94×608; (ii) a similarity matrix of cell lines measured as the cosine similarity of features of cell lines (gene expression profiles of cell lines), denoted as S ≈ TUV, where k is the dimensionality of the low-dimensional representation.  was used as the dose-response value as it was used in DREAM algorithms. A weighted, probabilistic concordance-index (wpc-index) was used to evaluate the final performance of our collaborative filtering model.We tested our collaborative filtering model on the data released from the NCI-DREAM drug sensitivity prediction challenge . ParticiS ≈ TUV. In the Group Sparse Lasso process, with corresponding feature matrices DF ∈ ℝ h194× and DF ∈ ℝ l×h2, where h1 is the length of Pubchem fingerprint and h2 represents the amount of genes in the expression profile, l is the number of cell lines for a specific cancer type. The feature selection task for the drug structure or genes on the whole genome could be treated as the l1 / ql -norm regularized multi-class least squares problem, which resulted in two sparse feature weight matrices P ∈ ℝ1×kh and Q ∈ ℝ 2×kh, where U ≈ D PF and V ≈ CQF. There were several rows in these two feature matrices with zero elements, indicating that the corresponding features were not important and were not selected  occurs when the inhibition of two genes is lethal while the inhibition of each individual gene is not. Gene A and gene B form an SL pair if the inactivation of gene A renders the essentiality of gene B, while the two genes form a synthetic dosage lethality (SDL) pair if the over-activity of gene A renders gene B essential. In the work of Livnat Jerby-Arnon , SL and Gene expression data of breast cancer and non-small cell lung cancer (NSCLC) tumor samples were retrieved from TCGA. In total, gene expression profiles were curated for 396 breast tumor samples with prior knowledge of their mRNA-expression subtypes: luminal A, luminal B, HER2E, and basal-like. Gene expression profiles were also collected for 540 samples and 548 samples of squamous NSCLC patients and adenocarcinoma NSCLC patients respectively. First, the gene expression data on breast tumor samples was picked out for the signature genes derived from breast cancer cell lines. Then, the gene expression data was used to perform unsupervised hierarchical clustering of these tumor samples. The NSCLC samples were clustered in a similar way. It should be noted that the gene expression data on tumor samples was not available for all of the selected signature genes . As thisAs the main purpose of this study was to investigate drug resistance with the cell line expression profiles, interference from CNVs and mutations was excluded. An outlier detection process was designed to make sure that the cancer cell lines kept a concordant CNV and mutation background but with different expression backgrounds. Outlier detection was performed on CNV and mutation data respectively. For each profile, a cell line was defined as an outlier if the Euclidean Distance to the geometrical center of these cell lines fell into the furthest 10% ranked ones and was removed after further analysis. It should be noted that all silent mutations were excluded, nor were they used to perform the outlier detection.Qualitative Representation method, which was first introduced by us to address the discretization of microarray data [Qualitative Representation is to represent the cell line activity in a qualitative or semi-quantitative manner by considering the whole distribution of the activities  in an ascending pattern, and the expression levels of the drug resistance genes in the top activity as well as the bottom activity of the cell lines needed to correlate well with the corresponding cell line activities. This can be achieved by firstly making discretization of the cell line activity data to automatically categorize the cell line into sensitive, moderate or resistant to drug perturbation. Such an automatic discretization was performed by an ray data . The baserred in . As a reThe spearman correlation calculated between drug activity in the sensitive and resistant cell lines and the gene expression in the sensitive and resistant cell lines was > 0.7.The genes should show the same tendency between the spearman correlation value of drug activity and the gene expression and that of drug activity and CNV (both positive or both negative).Drug resistance related genes were screened when the following criteria were satisfied:We collected clinical trial datasets that assessed tumor gene expression before drug treatment (using expression microarrays) and subsequently measured a clear drug response phenotype. Patients needed to have been treated with monotherapeutic drugs among the 94 collected drugs tracked in this study. Additionally, sensitivities to the particular drug needed to have been quantified on the cell lines of the same cancer type. Finally, we obtained two datasets with one for docetaxel  (GEO accWe also collected datasets of acquired resistance with gene expression profiles at different stages during the development of acquired resistance. As the tested drug needed to fall within the 94 collected drugs, we obtained only one eligible dataset for dororubicin  (ArrayEx


We have previously reported that the tetrahydrotetramethylnaphthalene (TMN) derivative TMNAA is a selective inhibitor of Adult T-cell Leukemia (ATL) and HTLV-1-infected cell lines but not non-ATL cell lines and peripheral blood mononuclear cells (PBMCs). In this study, several derivatives of TMNAA were synthesized and examined for their inhibitory effect on the proliferation of various T cell lines and PBMCs by a tetrazolium dye method. The modes of cell death and cell cycle arrest were also examined by flow cytometry. Among the compounds, MN417 having a tetrahydrotetramethylbenzophenanthridinone structure was found to be a more potent inhibitor of ATL and HTLV-1-infected cell lines than TMNAA. The 50% inhibitory concentrations (IC50s) of MN417 and TMNAA for ATL and HTLV-1-infected cell lines, including S1T and MT-2 cells, were 0.59-6.6 and 2.2-34.2 μM, respectively, depending on the test cell lines. In contrast, the IC50s of MN417 and TMNAA for non-ATL cell lines, such as MOLT-4 and CEM cells, were > 20 and > 100 µM, respectively. The elimination of the TMN moiety from MN417 failed to inhibit the proliferation of ATL and HTLV-1-infected cell lines, suggesting that the TMN moiety was required for the selective inhibition of these cell lines. Furthermore, both MN417 and TMNAA hardly induced apoptosis and cell cycle arrest. Thus, although the target molecule for inhibition of ATL cells remains to be elucidated, the compounds may have potential as novel and selective chemotherapeutic agents ATL.


Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma in children. Since patients with high-risk RMS have limited treatment options and a poor prognosis, and late complications including growth disturbance and secondary cancer induced by chemotherapy or radiation therapy are essential problems, novel therapies are urgently needed. C-type natriuretic peptide (CNP) has physiological activity mainly for mesenchymal cells to inhibit cell proliferation. We hypothesized that CNP attenuates proliferation of human RMS, a malignant mesenchymal tumor and provide rationale for using CNP to treat RMS.Gene expression of guanylyl cyclase B (GC-B), receptor of the CNP in rhabdomyosarcoma clinical samples and cell lines was assessed by using quantitative polymerase chain reaction. To ascertain biological activity of CNP in RMS cells, cyclic guanosine monophosphate (cGMP), the second messenger molecule which is produced by the activation of GC-B and serves as the major signaling molecule was measured following addition of CNP. However, cGMP is quickly degraded by phosphodiesterases and thereby biological activity becomes deactivated. Therefore, sildenafil, a selective inhibitor of phosphodiesterase 5 (PDE5) was added to CNP to prolong or enhance the effects of physiological processes mediated by cGMP by inhibiting its degradation. The in vitro and in vivo efficacy of CNP and sildenafil was evaluated alone and in combination.GC-B expression was seen in all alveolar and embryonal clinical samples which had higher GC-B expression than RMS cell lines. Since RD and RMS-YM cell lines had considerably lower GC-B expression than the clinical samples and KYM-1 and RH30 had no detectable expression, GC-B stable expression cell lines, RD-GC-B was established to mimic the clinical samples. CNP increased the rate of cGMP accumulation in RMS cells depending on concentration of this peptide. Combinations of CNP and sildenafil synergistically inhibited cell growth of RD-GC-B cells by inhibiting extracellular-signal-regulated kinase (Erk), the major signal for cell proliferation in RMS. The synergistic effect on growth and reduction of phosphorylated Erk as tumor pharmacodynamic biomarker were also confirmed in a mouse xenograft model.These results suggest that CNP in combination with sildenafil may have clinical efficacy for treating RMS patients.