Because cell lines acquire additional mutations in culture, it is important to understand to what extent HCC cell lines retain the genetic landscapes of primary HCCs. Most HCC cell lines were established during the last century, precluding comparison between cell lines and primary cancers. In this study, 9 Chinese HCC cell lines with matched patient-derived cells at low passages (PDCs) were established in the defined culture condition. Whole genome analyses of 4 HCC cell lines showed that genomic mutation landscapes, including mutations, copy number alterations (CNAs) and HBV integrations, were highly stable during cell line establishment. Importantly, genetic alterations in cancer drivers and druggable genes were reserved in cell lines. HCC cell lines also retained gene expression patterns of primary HCCs during in vitro culture. Finally, sequential analysis of HCC cell lines and PDCs at different passages revealed their comparable and stable genomic and transcriptomic levels if maintained within proper passages. These results show that HCC cell lines largely retain the genomic and transcriptomic landscapes of primary HCCs, thus laying the rationale for testing HCC cell lines as preclinical models in precision medicine.Hepatocellular carcinoma (HCC) cell lines are useful  In past decades, cancer cell lines have played important roles in cancer studies for both dissecting molecular mechanisms and developing new drugs1TP53 mutations were retained in 53 out of 62 pairs of the matched leukemia cell lines and primary cancer cellsCDKN2A homozygous deletions with the original tumors1011in vitro intermediate to assess genetic changes in cell lines. However, there has yet to be any careful characterization between cancer cells at early passages and established cell lines.To that end, several studies have generated new cancer cell lines and compared these cell lines to their matched primary cancers. Data from these studies provide evidence supporting the similarity between cancer cell lines and primary cancersTERT promoter, TP53 and CTNNB1Hepatocellular carcinoma (HCC), the major type of liver cancer, has emerged as the second most common cause of cancer-related deathin vitro culture, cell lines retain the genetic landscape of the matched primary HCCs. These data showed that HCC cell lines represent primary HCCs with high fidelity. Moreover, sequential analysis at different passages showed that HCC cell lines are similar to HCC cells of early passages at the genomic and transcriptomic levels, suggesting a comparable power of both cellular models to represent primary HCCs.In this study, 9 cell lines from Chinese HCC patients were established. Whole genome sequencing (WGS) was performed in 4 matched cell lines, PDCs and HCCs and RNAseq was performed to characterized transcriptome in 9 pairs of cell lines and PDCs and 6 matched primary HCCs. Notably, comparison of cell lines and HCCs demonstrated that, during long-term In order to perform a direct comparison of HCC cell lines and matched primary cancers, we established new cancer cell lines from HCC specimens of Chinese patients . A slighin vitro for more than 20 passages (passage 20–38). We obtained cells at passage 2–8 to represent early passages during the establishment of cell lines (Table S2). These cell lines were named Chinese Liver Cancer cell lines (CLCs). “T” and “PDC” were added after cell line names to indicate the matched primary HCCs and PDCs, respectively. All cell lines and matched HCCs were authenticated using short tandem repeat (STR) profiling to exclude cross contamination (Table S3). These cell lines grew as an adherent monolayer  was performed in 4 cell lines and their matched HCCs and PDCs to a mean mappable sequencing depth of 31.68 × . These four HCC patients were selected to represent the heterogeneity of primary HCCs in terms of age, tumor size, serum AFP level and immunohistochemical staining of Hep-1, a marker of differentiation (Table S1). On average, up to 93.88% of the genome was covered at ≥10× depth. About 3–4 million high-quality single nucleotide variations (SNVs) and insertion and deletion (InDel) variations were identified in each sample using Isaac Whole Genome Sequencing pipeline . More thTo determine whether global SNV patterns were stable during the establishment of cell lines, unsupervised hierarchical clustering was performed using whole genome germline SNVs . HCC celTP53 mutations were identified in HCC cell lines, but did not pass the filter for SNV calling quality in matched primary HCCs in CLC 5, 11, 13 . TP53 mutations were supported by sequencing reads in HCCs with VAFs greater than 90% , and HBV integrations, 11, 13 . To detethan 90% . TP53 muand PDCs . By manuA total of 232–377 putative protein-altering somatic mutations were eventually identified in each HCC cell line, primary HCC and PDC . UnsuperCCND1-FGF19 and homozygous deletion of 16p13 containing AXIN1. CCNE1 was amplified in both CLC16 primary HCC and the matched cell line.Previous studies showed that HCCs had extensive copy number alterations16TERT gene promoter23The 4 HCC cell lines analyzed by WGS were all derived from HBV-infected patients. HBV DNA promotes liver carcinogenesis by integration into the host genome and activation of cancer genes13TP53, CTNNB1 and ARID1A, which are critical in HCC developmentTP53, mutations in TERT promoter, AXIN1 and APC which differed across the matched cell lines, primary HCCs and PDCs, were also validated using Sanger sequencing (Table S5). Analysis of recently summarized driver gene alterationsTERT promoter located 124-bp upstream of the start codon, which accounts for 93% of TERT promoter mutations in HCCTERT promoter. This pattern was in line with the mutually exclusive occurrence of the TERT promoter mutations and HBV integration in HCCTP53 mutations , including 1 nonsense mutation and 2 missense mutations, were observed in 3 HCC cell lines and their matched primary HCCs , a database collecting somatic mutations in human cancersCTNNB1, which is mutated in 11%–37% of primary HCCsAXIN1 were detected in the cell line CLC5 and matched primary HCC. Interestingly, APC mutation was detected in primary HCC and PDC, but not in CLC13 cell line, which may be attributed to intratumoral heterogeneity and cell population selection during cultureARID1A and KMT2B were detected in two HCC cell lines and matched primary HCCs. Mutations in PI3K or MAPK pathways were not detected, likely reflecting their low mutation frequencies in HCC. We next estimated the VAFs of these driver mutations from whole genome sequencing and found that the VAFs remained comparable across the matched cell lines, primary HCCs and PDCs (Table S7).Recent studies of whole genome sequencing of HCCs have identified a panel of cancer driver genes, such as ary HCCs . These TCCND1-FGF19 amplification was present in 2 primary HCCs and cell lines We next analyzed whether alterations of druggable genes were retained in cell lines. By examining protein-altering mutations in druggable genesll lines . AmplifiPSMD4, TAPT1, AKR1D1, SNCAIP and SNX13. However, frequencies of the 5 mutations were extremely low (no more than 2 cases) among more than 20,000 tested cancer samples in COSMIC database (Table S9), implicating that these mutations are unlikely key cancer driver mutations. Cell line-specific mutant genes were also compared to 572 known cancer genes in Cancer Gene Census database15ATR (L608X) in CLC16, which was not a candidate cancer driver gene in HCCCompared to the matched HCCs, there were 17–47 protein-altering mutations specific to each HCC cell line, representing 5.7–11.4% of total protein-altering somatic mutations . A totalin vitro culture, which contains specialized extracellular matrix and a high concentration of serum and growth factors in the mediumWe next determined whether these cell line-specific mutations correlated with any pathways using Gene Set Enrichment Analysisin vitro, likely due to clonal selection of HCC cells during the culture. With passages increasing, additional mutations were gained at the rate of around 0.5 mutations per passage . Around 75% of genes showed positive correlations in expression levels between cell lines and matched primary HCCs. These results indicated that HCC cell lines maintained gene expression patterns of primary HCCs.To determine whether HCC cell lines were similar to matched primary HCCs at the transcription level, we performed RNAseq for all cell lines and PDCs and 6 matched primary HCCs. RNA for primary HCCs CLC5T, CLC6T and CLC7T were degraded and not qualified for RNAseq. By unsupervised hierarchical clustering, we found that the matched cell lines, primary HCCs and PDCs clustered together , demonstP value < 0.05 where P values were corrected for multiple hypothesis testing using Benjamini-Hochberg method. After setting a loose threshold of the uncorrected P value to 0.05, only 88 DEGs were detected with a fold change >2 or <1/2 , detecting mutations in a minor cell population (<1%) is challenging for WGS due to sequencing depth5in vitro cultures lack the proper extracellular matrix presented in vivo38It should be noted that additional genetic changes were detected in cell lines and PDCs. By STR analysis (Table S3) and WGS, we found loss of chromosome Y (LOY) in three cell lines . Interestingly, our data were consistent with one previous study in which 18 out of 21 male liver cancer cell lines showed LOY35in vitro model that highly recapitulate the molecular and phenotypic characteristics of primary cancersin vitro culture at early passages. It is true that additional few mutations occurred from PDC to cell line, but nearly all of these mutations were unrelated to cancer driver genes. HCC cell lines used in our study were at passages 20–38. Over-passaged cells may introduce much more alterationsin vitro models and suggest that HCC cell lines may have the potential comparable to that of PDCs in modeling primary HCCs and make drug screening more convenient.During the establishment of cell lines, we analyzed PDCs at early passages. Due to short-term culture, PDCs are often taken as an In summary, we showed that HCC cell lines largely represent the mutational and transcriptomic landscapes of matched primary HCCs. These genetically validated HCC cell lines will be deposited in public cell line banks and provide new models for HCCs in functional screening of new therapeutic targets and drug development. With advances in novel technologies, such as HCC organoids, more HCC cell lines would be established at high success rates382. The primary culture medium were based on RPMI1640 (HyClone), supplemented with 10% fetal bovine serum , 110 μg/mL sodium pyruvate, 10 μg/mL insulin, 5.5 μg/mL transferrin, 40 ng/mL EGF and 6.7 ng/mL sodium selenite (Gibco). On the next day, nearly all the adherent cells showed epithelial-like morphology. Wash with PBS once and change fresh primary culture medium to remove dead cells and blood cells. The primary culture medium were then refreshed every three days. During cell line establishment, epithelial cells were frequently contaminated by fast-growing fibroblast cells. Fibroblast were removed by differential trypsination or scratch by pipetting tips. Because not all the cancer cells from patients overexpress typical cancer or epithelial markers, such as EpCAM, we haven’t sorted isolated cells using these markers to enrich cancer cells. Instead, we observed that during the first several days, nearly all of the adherent cells show epithelial morphology. Epithelial clones were pick out to make sure that epithelial cells were purified and avoid fibroblast contamination. Once confluent, epithelial cells were digested by 0.05% trypsin-EDTA for passage at a ratio of 1:3. Established cell lines were maintained in primary culture medium in a humidified incubator at 37 °C with 5% CO2. All the cell lines retained continuous proliferation from passage 10. Cells with more than 20 passages were regarded as cell lines. All the cell lines were authenticated by STR analysis and tested for mycoplasma regularly to avoid contamination. For the passages of PDC, we consulted published work and ongoing project with our own experience. In cell line factory project in Broad Institute (http://www.broadinstitute.org/cellfactory#home), cells through passage 5 were highlighted. In recent reports, passage 1–4 were analyzed as PDCs10All the fresh cancer tissues were surgically resected from Chinese hepatocellular carcinoma patients with the informed consent. The study was approved by the ethical committee of the participating hospitals and methods were carried out in accordance with the approved guidelines. HCC tissues were rinsed twice with PBS. Both necrotic tissues and apparently normal tissues were discarded. The remainder were finely minced with scissors to small fragments (1 to 2 mm in diameter) and digested by 0.1% Collagenase Type IV (Gibco) in PBS for 30 min at 37 °C with shaking occasionally in a 15 mL or 50 mL centrifuge tube (Corning). Then cell suspensions were filtered by 70 μm cell strainer to remove large fragments and centrifuged consecutively at 1000 rpm, 800 rpm and 600 rpm for 5 min, respectively. Cancer cells were resuspended using primary culture medium and transferred to collagen-coated dishes for culture overnight in a humidified incubator at 37 °C with 5% COCells at different passages were seeded into 12-well plates at a density of 50,000–200,000 cells for different cells. Cell numbers in different wells were counted at Day 1 (24 hours after seeding cells), 3, 5, 7.HCC tissues were fixed overnight and stained with haematoxylin and eosin for pathological evaluation as previously describedGenomic DNA was extracted using Qiagen DNeasy kit. Sequencing library was constructed and paired-end 150 bp read length sequencing was performed on Hiseq X TEN platform according to the manufacturer’s instructions to achieve mean sequencing depth of >30. Sequencing reads were mapped to hg19 human reference genome by Isaac Alignment software with default parameters to obtain BAM files. Isaac Variant Caller was used to call variants with quality scores GQX >30 and generate the filtered VCF files and raw Genome VCF (gVCF) files. SNVs and InDels with low quality were filtered out from VCF files but retained in gVCF files. Considering the relatively low accuracy for InDel identification, we only considered SNVs for the downstream analysis. ANNOVAR43Mutation status of TP53, AXIN1, APC, CDKN2A and TERT promoter were confirmed by PCR and Sanger sequencing (Table S5). TP53 mutations and AXIN1 mutation were filtered out in WGS, but validated using Sanger sequencing. For CLC13 HCC, PDC and cell line, TERT promoter mutation in CLC13PDC and APC mutation in CLC13 HCC and cell line were not reported even in raw VCF files, but examined using Sanger sequencing. Primer sequences were provided in Table S11.Control-FREECHBV integration was identified and annotated by Virus-ClipWhole genome SNVs from 12 samples were merged and unsupervised hierarchical clustering was performed using complete linkage method. Distance between pairs of samples were calculated using Euclidean distance method. Clustering of protein-altering somatic mutations and HBV integration sites was done with the same parameters. For CNAs, gene copy numbers were used as input in the clustering by Manhattan distance method.Cell line- or PDC-specific protein-altering mutations were identified by comparing VCF files with curated SNVs of HCC cell lines or PDCs to those of the matched primary HCCs. Mutations which were present in HCC cell lines or PDCs, but absent in primary HCCs, were considered as cell line- or PDC-specific mutations. Pathway enrichment were performed using the online tool of the Molecular Signatures Database (MSigDB) to calculate the overlapping of the gene list to the canonical pathways from the public pathway databasesin vitro cell lines and primary HCCs were separately centered and normalized, and then merged to perform unsupervised hierarchical clusteringTotal RNA was extracted using Trizol (Invitrogen) according to the manufacturer’s instructions. Single-end 100 bp read length sequencing was performed on Illumina Hiseq 2000 sequencer. The reads were mapped to the human reference genome (hg19) using TophatPaired Mann-Whitney tests were used to calculate the statistical significance of DEGs from FPKM values. Two thresholds were applied to identify significant DEGs between cell lines and PDCs: 1) fold change >2 or <1/2 and the Benjamini-Hochberg corrected P value < 0.05; 2) fold change >2 or <1/2 and unadjusted P value < 0.05.Statistical analysis and data visualization were performed using R software and Graphpad Prism software. P values were calculated by statistical methods denoted in each analysis. A two-tailed P < 0.05 was taken to indicate statistical significance unless illustrated otherwise.Accession codes: Genome data has been deposited at the European Genome-phenome Archive , which is hosted at the EBI, under accession number EGAS00001001678. RNAseq data have been deposited in NCBI’s Gene Expression Omnibus under the accession number GSE78236.How to cite this article: Qiu, Z. et al. Hepatocellular carcinoma cell lines retain the genomic and transcriptomic landscapes of primary human cancers. Sci. Rep.6, 27411; doi: 10.1038/srep27411 (2016).


Therefore, we evaluated antitumor effects of a PKM2 inhibitor in murine models of NSCLC. Mice tolerated intra-tumoral administration of the PKM2 inhibitor  up to 500 µg/kg/day without any evidence of visible toxicity or weight loss. Despite its anti-proliferative activities in vitro, the PKM2 inhibitor did not mediate significant antitumor effects in NSCLC tumor xenografts. The mechanism of lack of activity in vivo is not clear. It is possible that PMK2 inhibitor levels were not sufficient or sustained in vivo for a measurable antitumor effect.Non-small cell lung cancer (NSCLC) is the most common cause of cancer related mortality worldwide and in need of new treatment options. Previously, we have shown that 97 genes are overexpressed in 9 primary NSCLC cell lines by DNA microarray technology. Pyruvate kinase M2 (PKM2), an allosteric isoform of pyruvate kinase and metabolic enzyme necessary for aerobic glycolysis and cell proliferation, was identified to be over-expressed in the NSCLC cell lines. Real-time qRT-PCR and immunohistochemistry (IHC) techniques confirmed the microarrays results. Consistent with the over-expression of PKM2, all 9 NSCLC cell lines showed higher PKM2 enzyme activity than normal lung cell lines. Since a chemical inhibitor of PKM2 decreased PKM2 enzyme activity and proliferation of NSCLC cell lines, we hypothesized that PKM2 inhibitors may have a role in antitumor effects in vitro and in vivo. Gene silencing in cells transfected with plasmids encoding shRNAs was confirmed by IHC, which showed >80% silencing measured by NIKON-S-Element software at the protein level. In clonogenic assays, we observed >50% fewer colonies in two PKM2 silenced NSCLC cell lines compared to mock transfected controls. In subcutaneous xenograft tumor models in athymic nude mice, preliminary results showed that PKM2-silenced tumors grew significantly slower compared to mock transfected tumors (p < 0.05). These results suggest that PKM2 may be a target for cancer therapy. Additionally, given its over-expression in NSCLC, it may also serve as a target for immunotherapy. Studies are ongoing to confirm these results, understand a mechanism of tumor response, and determine whether patients generate immune responses to PKM2.To further study whether PKM2 was a target for therapy, we silenced the PKM2 gene in the H1299 and H358 NSCLC cell lines using RNAi and proliferative activity of tumors was assessed


Circulating soluble-α-Klotho (s-Klotho) results from TM-Klotho shedding and acts on Phosphate (P) and Calcium (Ca) tubular transport. Decreased TM-Klotho, described in experimental chronic kidney disease (CKD), prevents actions of FGF23 and lessens circulating s-Klotho. Thus, levels of s-Klotho could represent a marker of CKD-MBD. To evaluate the clinical significance of s-Klotho in CKD we assayed serum s-Klotho and serum FGF23 in 68 patients . s-Klotho was lower than normal  in renal patients and its reduction was detectable since CKD stage 2 (P < .01). s-Klotho correlated positively with eGFR and serum calcium (Cas) and negatively with serum phosphate (Ps), PTH and FGF23. FGF23 was higher than normal  with significantly increased levels since CKD stage 2 (P < .001). Our data indicate a negative effect of renal disease on circulating s-Klotho starting very early in CKD. Assuming that s-Klotho mirrors TM-Klotho synthesis, low circulating s-Klotho seems to reflect the ensuing of tubular resistance to FGF23, which, accordingly, is increased. We endorse s-Klotho as an early marker of CKD-MBD.Transmembrane  Importa ADAM 17 , 7. In p ADAM 17  and acti ADAM 17 . In summExperimental models of CKD evidence early reduction of renal Klotho mRNA expression and of both TM-Klotho and s-Klotho , 12, andAvailable data on serum levels of s-Klotho in CRF patients almost invariably describe reduced values, a finding referred to a primary proportional reduction of TM-Klotho, as described in animal studies –18. MoreIn the present study, we evaluated the diagnostic performance of s-Klotho in our CKD population of patients by using the most accredited commercial s-Klotho assay . We aimeWe enrolled in the study, from our outpatient unit, eligible patients who gave informed consent. Inclusion criteria were white race, age 18–80 years, on conservative therapy with no evidence of acute underlying illness and naïve to treatment with any active or precursor metabolite of vitamin D.2-vitaminD , fibroblast growth factor-23 (FGF23), and soluble-α-Klotho (s-Klotho). We also collected fasting spot urine samples from all participants at the time of blood sampling to measure creatinine, phosphate, and calcium. In each patient, we recorded clinical parameters and prescribed therapies.Fasting blood samples were drawn from all participants to measure creatinine (Crs), albumin, calcium (Ca), phosphate (P), parathyroid hormone (PTH), 25(OH)-vitamin D (25D), 1,25(OH)We classified CKD stage according to the National Kidney Foundation Disease Outcomes Quality Initiative clinical practice guidelines (KDOQI) .2) negative urinary dipstick and no evidence of acute or chronic underlying illness.Thirty normal subjects, recruited among the employees and fellows attending our Unit, served as control to obtain our reference values in particular for s-Klotho and FGF23. They were 14 males and 16 females, 35.0 ± 12.4 years of age with normal renal function , albumin (bromcresol purple method), Ca , and P (ammonium molybdate method) were assayed by routine, standard colorimetric techniques with a Technicon RA-500 analyzer .Serum PTH was assayed by an immunoradiometric technique  based on a double antibody against the intact molecule; our normal values are within 10–55 pg/mL, with intra- and interassay variations of 6.5% and 9.8%, respectively.125I-based radioimmunoassay. Intra- and interassay coefficients of variation were 10.8% and 9.4%, respectively.Serum 25D determination was done with a commercial kit  that included sample purification with acetonitrile followed by a 125I-based radioimmunoassay. Intra- and interassay coefficients of variation were <12% and <14%, respectively. The normal range observed in our laboratory was between 19.5 and 67.0 pg/mL.Serum levels of 1,25D were measured with a radioimmunoassay according to the manufacturer's protocol  including a monoclonal immunoextraction, followed by quantitation with a standard Serum levels of FGF23 were assayed with a commercially available kit  that utilizes a 2-site ELISA for the full-length molecule. Two specific murine monoclonal antibodies recognized the biologically active FGF23, with a lower limit of detection of 3 pg/mL, and inter- and intraassay coefficients of variation of <5%. This assay has been demonstrated to be the most sensitive among the 3 different methods available . In 30 nα-Klotho IBL was <5 and <8%, respectively. Measurements in serum and EDTA plasma samples were in agreement  and linearity was tested by dilution in two samples with a concentration of 1929 and 2864 pg/mL. In one sample, 2-, 4-, and 8-time dilutions gave results as expected . In our experience, in 30 normal subjects we obtained a mean value of 845 ± 330 pg/mL (range 2048–481 pg/mL).Serum levels of soluble alpha-Klotho were assayed with a novel enzyme-linked immunosorbent assay (ELISA) method detecting human s-Klotho developed first by establishing a monoclonal antibody with strong affinity for human Klotho protein, recognizing with high selectivity the tertiary protein structure of its extracellular domain . This ELISA system can specifically detect and measure the circulating serum s-Klotho levels in humans . It was −1.154  ×  age−0.203  ×  0.742 if female) [We estimated glomerular filtration rate (eGFR) according to the abbreviated modification of diet in renal disease (MDRD) equation  .Data are expressed as means ± SD for Gaussian variables or median and IQR when normality was not tenable.We used Kolmogorov-Smirnov test to evaluate normality of continuous measurements.Spearman correlation was used to assess monotonic covariation of measurements. Tests on Spearman correlation were Bonferroni adjusted for multiplicity. Nonparametric ANOVA  was used to compare measurements among groups and post-hoc comparisons in pairs were conducted by Bonferroni adjusted Mann-Whitney tests.P-values <0.05 were considered as statistically significant.Log-measurements were confirmed to be normally distributed and were used as outcomes in multivariate regression models. The final multivariate model was obtained by minimizing the Akaike information criterion via a forward stepwise regression. All tests are two tailed and (adjusted) Analyses were performed using the open source software package R version 3.0.2.n = 22 (32%); stage 3, n = 28 (41%); stage 4, n = 18 (27%)).For this study we recruited sixty-eight CKD patients, and their clinical and biochemical parameters are reported in Tables P < .0001, P < 0002, s-Klotho levels in our CKD patients were significantly lower (519 ± 183 versus 845 ± 330 pg/mL, ρ = −0.33,  P < .01, ρ = 0.43,  P < .001, ρ = −0.66,  P < .0001, In patients s-Klotho and FGF23 were negatively correlated (P < .01; stage 3 = 529 ± 160, pg/mL, P < .001; stage 4 = 393 ± 142, pg/mL; P < .001. P < .001; stage 3 = 57 ± 28, pg/mL, P < .002; stage 4 = 136 ± 58, pg/mL, P < .001. When we evaluated s-Klotho in the different CKD stages, we found reduced levels since CKD stage 2, with a more significant reduction in CKD stages 3 and 4 (reference values = 845 ± 330, pg/mL; stage 2 = 611 ± 191, pg/mL, ρ = −0.28,  P < .05, ρ = −0.28,  P < .05, ρ = 0.30,  P < .01, 4PO, and FECa.s-Klotho correlated negatively with PTH (ρ = 0.43,  P < .001, ρ = 0.51,  P < .001, 4PO (ρ = 0.47,  P < .001, ρ = −0.39,  P < .001, Ca.FGF23 levels correlated positively with PTH (In agreement with experimental models of CKD , 12 and Ca. Therefore, we should guess a more complex interplay with other changing parameters like eGFR, PTH, and 1,25D.Renal function negatively affected s-Klotho levels with detectable reduction starting from CKD stage 2. Since s-Klotho is normally excreted in the urine –9, this 4PO. Since s-Klotho and FGF23 correlate negatively in CKD but exert a similar positive effect on renal expression of NaPi2a, it is possible that the action of s-Klotho is shadowed by FGF23. Finally, the negative relationship with PTH should be regarded as secondary to reduced renal function.The negative relationship we found between s-Klotho and serum P is interesting due to the reported direct effect of circulating s-Klotho on the renal expression of NaPi2a. However, no correlation was evident with renal FE4PO. Multivariate analysis evidenced eGFR and 1,25D as best predictors. These data suggest that bone cells somehow sense the reduction of eGFR very early and increase FGF23 synthesis mainly aiming at reducing 1,25D synthesis. In agreement, in a mice model of CKD administration of FGF23 antibodies resulted in a significant and dose dependent increase of 1,25D [Serum levels of FGF23 were higher than normal in our CKD population with increments detectable since CKD stage 2. Correlations of FGF23 were negative with eGFR and 1,25D, and positive with PTH, Ps and FEof 1,25D . In our Interestingly in our study, a negative relationship emerged between s-Klotho and FGF23. This favors the hypothesis that s-Klotho, whose circulating levels are strongly related to renal function and are most probably secondary to reduced expression of TM-Klotho, can be regarded as a sensitive biomarker of TM-Klotho expression, useful to appreciate early development of tubular resistance to FGF23. Consequently, bone synthesis of FGF23 is increased. A recent paper with histologic data from patients with glomerulonephritis showed parallel reduction of renal Klotho and of s-Klotho together with increments in FGF23, which is in agreement with our data . TransgeSignificantly in our study, levels of s-Klotho and of FGF23 are roughly halved and, respectively, doubled in a population with an average eGFR of 45 mL/min/1,73 but with substantially normal values of Ca and P and with mean values of 1,25D and of PTH, respectively, at the lower and higher upper limits of normality. This confirms that changes in serum Ca and P are not reliable to detect early CKD-MBD, while s-Klotho seems more sensitive than PTH and 1,25D.Limitations of our study are several. First, the number of evaluated patients is rather low. In fact, an increased number of cases would have reinforced the reliability of our results that, however, are in line with published data in the literature. Second, we did not include CKD stage 1 patients and this does not allow us to verify if s-Klotho diminish even in case of “normal” renal function. Certainly, this important issue warrants further investigations. Third, we did not measure urinary s-Klotho. Effectively, evidence of reduced urinary Klotho in our experience would have reinforced the hypothesis of reduced renal synthesis. However, scanty, available papers report reduced urinary Klotho in patients with renal failure  and in aIn conclusion, our results favor the hypothesis that renal Klotho synthesis diminishes early in renal disease and that s-Klotho proportionally lessens; bone detects these changes somehow and increases FGF23 production. Accordingly, s-Klotho represents an early marker of renal damage and of ensuing CKD-MBD, indicative of the cross-talk between bone and kidney.


EGFRWT/ALKnon-rearranged NSCLC cell lines.We aimed to understand the dependence of MEK and m-TOR inhibition in KRASM and KRASWT NSCLC cell lines, we determined growth inhibition (GI) following maximal reduction in p-ERK and p-S6RP caused by trametinib (MEK inhibitor) and AZD2014 (m-TOR inhibitor), respectively.In a panel of vs 18%, P<10−4). There was no significant difference in GI caused by maximal m-TOR compared with maximal m-TOR+MEK inhibition. However, GI caused by the combination was significantly greater in the KRASM cell lines .GI caused by maximal m-TOR inhibition was significantly greater than GI caused by maximal MEK inhibition in the cell line panel (52% EGFRWT/ALKnon-rearranged NSCLC cells. The combination of MEK and m-TOR inhibition was most effective in KRASM cells.m-TOR inhibition was more critical to GI than MEK inhibition in  EGFR mutant and ALK rearranged lung cancer, there are currently no molecularly targeted agents licensed for use in the remainder of adenocarcinomas (NSCLC-adeno-EGFRWT/ALKnon-rearranged). There have been recent advances in the treatment of NSCLC-adeno with the introduction of immune checkpoint inhibitors. However, response rates and median overall survival are low with 19% and 12.2 months, respectively . Although EGFR , and gene fusions of which KRAS mutations form the largest group  following maximal inhibition of MEK or m-TOR in NSCLC-adeno-KRASM  and three KRASWT  cell lines, were purchased from ATCC-LGC Standards . Trametinib and AZD2014 were sourced from Selleckchem .A panel of six NSCLC cell lines, including three Maximal reduction of p-ERK1/2  and p-S6RP (Ser235/236) was determined by exposing the cell lines to increasing concentrations of Trametinib and AZD2014 over 24 h and quantifying p-ERK1/2 and p-S6RP by ELISA  following manufacturer's instructions. Experiments were conducted in triplicates.Cell lines were exposed to concentrations of Trametinib and AZD2014 shown to maximally inhibit MEK and m-TOR signalling, respectively, for 72 h. The effects of inhibiting these nodes alone or in combination on cell growth were studied using a WST-1 assay . Experiments were carried out in triplicates.Data are reported as means±s.d. Statistical significance was evaluated by non-parametric Mann–Whitney's tests. Results were subjected to statistical analysis by using the GraphPad Prism software package, v6.01 .EGFRWT/ALKnon-rearranged cell lines were exposed to increasing concentrations of Trametinib and AZD2014 over 24 h and the concentrations of Trametinib and AZD2014 to cause maximal reduction in levels of p-ERK and p-S6RP were determined (NSCLC-adeno-termined .vs 52%(SD13), P<0.0001, respectively, in all cell lines (KRASM and KRASWT cell lines with GI of 0%(SD6) vs 36%(SD12), P<0.0001 and 43%(SD7) vs 61%(SD11), P=0.0002, respectively  ll lines . These dectively .P=0.089). However, there was a significant difference of GI caused by inhibition of MEK signalling alone, compared with the combination of maximal MEK+m-TOR signalling inhibition, 18%(SD22) vs 64%(SD21), P<0.0001 (data not shown). Importantly, in KRASM cell lines, inhibition of m-TOR+MEK signalling caused significantly greater GI than inhibition of m-TOR or MEK signalling alone, 79%(SD14) vs 61%(SD11), P=0.017 and 79%(SD14) vs 36(SD12), P<0.0001  when compared with GI caused by maximal m-TOR+MEK inhibition  was not significant . This observation is in line with previously published literature (KRASWT cell lines within the group of EGFRWT/ALKnon-rearranged cell lines.In the NSCLC cell lines studied, we have shown for the first time that maximal inhibition of m-TOR caused significantly more GI compared with maximal MEK inhibition. This is interesting as most efforts of clinically developing signal transduction inhibitors in NSCLC-adeno-There have been few single agent studies of m-TOR inhibitors in lung cancer and with very low response rates of 0–5% , while AKRASM lung cancers (KRASM NSCLC (Preclinical studies have suggested combinations of m-TOR and MEK inhibitors in KRASM NSCLC. Toxicity limits such combinations and intermittent schedules are the only way to deliver drugs at doses that are pharmacodynamically active. In case of toxicity, our data suggest dose interruptions/reductions should be considered in inhibitors of MEK signalling rather than inhibitors of m-TOR signalling. This approach will help refine doses/schedules of MEK and PI3K pathway inhibitors to provide new treatment paradigms for KRASM NSCLC.The combinations of MEK inhibitors and m-TOR inhibitors or more broadly PI3K pathway inhibitors should be evaluated in


Bacillus subtilis 573 and a glycoprotein (BioEG) produced by Lactobacillus paracasei subsp. paracasei A20 was evaluated. Both biosurfactants were tested against two breast cancer cell lines, T47D and MDA-MB-231, and a non-tumour fibroblast cell line (MC-3 T3-E1), specifically regarding cell viability and proliferation. Surfactin was found to decrease viability of both breast cancer cell lines studied. A 24 h exposure to 0.05 g l-1 surfactin led to inhibition of cell proliferation as shown by cell cycle arrest at G1 phase. Similarly, exposure of cells to 0.15 g l-1 BioEG for 48 h decreased cancer cells’ viability, without affecting normal fibroblasts. Moreover, BioEG induced the cell cycle arrest at G1 for both breast cancer cell lines. The biosurfactant BioEG was shown to be more active than surfactin against the studied breast cancer cells. The results gathered in this work are very promising regarding the biosurfactants potential for breast cancer treatment and encourage further work with the BioEG glycoprotein.Biosurfactants are molecules with surface activity produced by microorganisms that can be used in many biomedical applications. The anti-tumour potential of these molecules is being studied, although results are still scarce and few data are available regarding the mechanisms underlying such activity. In this work, the anti-tumour activity of a surfactin produced by  Biosurfactants are molecules with surface activity produced by a number of microorganisms and that can be used in many biomedical applications . The cha et al. ), which a et al. ; Golek ea et al. ; Madhu aa et al. ; Moldes a et al. ; Tahmoura et al. ; 2011b]LactobaciBacillus subtilis HSO121 on Bcap-37 breast cancer cell lines and demonstrated that these compounds induced apoptosis in a dose-dependent manner. Furthermore, their results indicated that the disturbance of the cellular fatty acid composition of breast cancer cell lines, by lipopeptides, was related with apoptosis. In addition, several other lipopeptides (isoforms of surfactin and fengycin) were also found to have potent cytotoxic effects against the human colon cancer cell lines HCT15 and HT29 . Since Bacillus subtilis 573 and a glycoprotein (BioEG) produced by Lactobacillus paracasei subsp. paracasei A20 against two breast cancer cell lines, T47D and MDA-MB-231, was evaluated specifically regarding cell viability and proliferation. The biosurfactants’ effects on the viability of a non-tumour fibroblast cell line (MC-3 T3-E1) were also evaluated.In this work, the anti-tumour activity of a surfactin produced by Bacillus subtilis strain 573 previously isolated and characterized in our lab : NaCl 10.0; tryptone 10.0; yeast extract 5.0. The pH was adjusted to 7.0.a et al. ; Pereiraa et al. ) was useSurfactin production was conducted in 1 L flasks containing 400 ml of LB medium. The flasks were inoculated with 1% of a pre-culture grown in the same medium for 24 h. Cultures were incubated at 37°C for 72 h without agitation. At the end of the fermentation, cells were removed from the broth by centrifugation .To recover the surfactin, cell-free supernatants were subjected to an acid precipitation as described elsewhere . BrieflLactobacillus paracasei subsp. paracasei A20.Production and recovery of a glycoprotein biosurfactant from Lactobacillus paracasei subsp. paracasei A20 isolated in a Portuguese dairy industry and previously reported as a biosurfactant-producing strain  (strain2PO4/K2HPO4 and 150 mM NaCl with pH adjusted to 7.0) in a proportion 6:1. The bacteria were left at room temperature for 2 h with gentle stirring for biosurfactant release, as previously described  and washed twice with acidic water (pH 2.0). Afterwards the precipitate was dissolved in distilled water by adjusting the pH to 7.0 with NaOH 1 M, dialyzed against demineralized water at 4°C in a Cellu-Sep© membrane (cut-off 6000–8000 Da), freeze-dried and stored until further use.For glycoprotein BioEG production in flasks, 600 ml MRSLac broth was inoculated with 1% of an overnight pre-culture grown in the same medium. The culture was incubated for 48 h at 37°C and 120 rpm. At the end of the fermentation, cells were harvested by centrifugation , washed twice in demineralized water, and resuspended in phosphate-buffered saline . Subseqa et al. ; Van Hooa et al. ). Briefl2 atmosphere at 37°C. The culture medium used was the Dulbecco’s modified Eagle medium  supplemented with 10% fetal bovine serum  and 1% penicillin/streptomycin (Invitrogen).Breast cancer cell lines were kindly provided by the Institute of Molecular Pathology and Immunology of the University of Porto . The MDA-MB-231 cell line was established from a pleural effusion obtained from a 51-yr-old female patient with breast cancer. Also, the T47D cell line was isolated from a pleural effusion obtained from a 54-yr-old female patient with an infiltrating ductal carcinoma of the breast. A non-tumour fibroblast cell line, mouse embryo fibroblast 3 T3 cells (MC-3 T3-E1), was used as a control. All cells were maintained in an incubator with a 5% CO-1) and four of BioEG . Biosurfactant stock solutions were prepared in PBS. Control experiments using the non-tumour MC-3 T3-E1 cell line were also conducted. The cell viability was determined using the MTS -5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium) method. A commercial kit was used according to the manufacturer instructions . In these experiments, 100 μl of cell suspension was added to each well of a 96-well plate. Additionally, control wells were included consisting of DMEM medium, PBS and the biosurfactants prepared in PBS at the concentrations under study. When a cell concentration of 1×105 cells ml-1 was obtained, adequate volumes of the biosurfactant solutions were added to the wells and incubated for 24, 48 and 72 h. Afterwards, 20 μl of the Cell Titter 96 AQueous One Solution Cell Proliferation Assay reagent (MTS) was added to each well and left in the incubator  for 2 h after which the cell viability was quantified by recording the absorbance at 490 nm.Breast cancer cells were exposed to five concentrations of surfactin , corresponding to the concentration of compound that inhibits 50% of the cell growth, was determined. The results are expressed as percentage of viable cells compared to the control and represent an average of 3 independent cultures with 3 wells per concentration in each experiment. Each exposure time was studied in triplicate with independent cultures.5. Then, the medium was removed and replaced by fresh medium containing biosurfactants (0.05 g l-1 surfactin or 0.15 g l-1 BioEG). After 24 h (for surfactin) or 48 h (for BioEG), cells were trypsinized, washed with 5 ml PBS and finally centrifuged . The cell pellet was resuspended in 500 μl PBS and kept in ice for 15 min. Cell suspension was readily mixed with 1.5 ml ethanol 96% at -20°C, and the final mixture was kept in ice during 15 min to allow cell fixation.Cells were grown in petri dishes (diameter 55 mm) until the total cell number reached 5×10-1) was added to the mixture, vortexed and incubated at 37°C for 15 min. Subsequently, 60 μl of propidium iodide (PI) at 0.5 mg ml-1 was added to the previous mixture. The final mixture was again mixed in the vortex and kept in the dark for 30 min until analysis on a flow cytometer . The cell cycle analysis using the non-tumour cell line MC-3 T3-E1 was conducted only for the experiments with the BioEG biosurfactant. Three independent analyses were performed for each cell line and experimental condition. The flow cytometry results were analyzed with the software FlowJo version 7.6. .Afterwards, cell suspension was washed twice with PBS and resuspended in 500 μl of PBS. A volume of 50 μl of RNAse A .B. subtilis 573 isolated by our research group, and a glycoprotein (herein named BioEG) produced by L. paracasei subsp. paracasei A20 isolated in a Portuguese dairy industry.In this work, the potential anti-tumour activity of two biosurfactants against two breast cancer cell lines was evaluated. Specifically, we used a surfactin produced by Surfactin was tested in five concentrations for three exposure times against T47D and MDA-MB-231 breast cancer cell lines. The effect of the biosurfactant on a non-tumour cell line (MCT-3 T3-E1) was also evaluated. Figure Positive controls (without surfactin) were included and correspond to 100% cell viability. Negative controls, containing only medium and surfactin at each studied concentration, were also included to eliminate any possible interference with the method.-1 surfactin for 48 and 72 h.The results obtained clearly show a decrease in the percentage of viable cells with increasing surfactin concentrations and exposure times, thus suggesting its cytostatic/cytotoxic effect against the studied breast cancer cell lines. However, for the highest surfactin concentration studied, a significant decrease of the total number of cells was observed, probably due to a prevalence of a detergent-like effect leading to cell membrane disruption . Globally, the differences observed between exposure times  and concentrations  were found to be statistically significant.Based on these findings, 0.5 g l-1 surfactin. Compared with the control, this concentration decreased MDA-MB-231 cell viability between 50 and 75% depending on the exposure time.For MDA-MB-231 cell line  and concentrations  were significant. Furthermore, the concentration of surfactin that inhibits 50% of cell growth (GI50) for each exposure time and breast cancer cell line was determined. The GI50 values were found to be higher for MDA-MB-231 cells  than for T47D .The differences obtained for all surfactin concentrations studied were statistically significant , except for the lowest concentration. Moreover, the ANOVA results showed that the differences observed between exposure times  led to a considerable amount of cell death, since only few viable cells were present in the sample after incubation under such conditions. These results suggest the prevalence of a detergent-like effect under these conditions.The results gathered in Figure -1 of BioEG was found to be effective in decreasing T47D cell viability . Moreover, different concentrations  and exposure times  were found to significantly influence the effect of BioEG.A concentration of 0.15 g ly Figure A to 72%,-1 of BioEG, leading to final values of 73%, 53% and 37% for an exposure time of 24, 48 and 72 h, respectively. Also in this case all the differences observed among different concentrations and exposure times were found to be statistically significant.Regarding the MDA-MB-231 cell line ; 0.20 ± 0.04 (48 h); and 0.06 ± 0.01 (72 h). For T47D, The GI values determined were above 0.20 ± 0.01 (24 h); 0.18 ± 0.02 (48 h); and 0.14 ± 0.01 (72 h). It is possible to observe that BioEG has a high anticancer potential, especially in MDA-MB-231 cells.-1 surfactin. As shown in Table The evaluation of cell proliferation through analysis of cell cycle was performed by flow cytometry for both cell lines subjected to a 24 h exposure to 0.05 g l-1 BioEG in cell cycle of T47D and MDA-MB-231 cells after 48 h exposure. Like surfactin, BioEG also induced a G1 arrest in both cell lines associated with a decrease of cells at S and G2 phases. However, the effect was stronger in the T47D cell line, contrary to what occurred in the MTS results. The discrepancy between BioEG and surfactin effectiveness in cell cycle arrest may be the result of different mechanisms of action being in place in different cell lines. Additionally, BioEG did not affect significantly the cell cycle of MC-3 T3-E1 cells  produced by Lactobacillus paracasei subsp. paracasei A20 were evaluated for their effect on breast cancer cells viability and proliferation. Two breast cancer cell lines, T47D and MDA-MB-231, and a non-tumour fibroblast cell line (MC-3 T3-E1) were used. Surfactin was shown to have a cytotoxic effect against T47D and MDA-MB-231 breast cancer cells, which is in accordance with other studies reported in the literature using other types of cancer cells  that hain situ release of the cyclic peptide.Since surfactin has never been tested in humans, to prevent future complications several strategies have been explored envisaging its use as a safe therapeutic agent. Symmank et al.  reporteSurfactin is an amphipathic molecule that has been reported as a plasma membrane destabilization agent, thus disturbing its integrity . The keCao et al. ,2011) de de2011])-1 BioEG was higher. The breast cancer cell lines used in this work have different features that may be responsible for the different behaviors observed when exposed to BioEG. The most important difference between these two cell lines is the absence of estrogen receptor (ER) in MDA-MB-231 cells. Additionally, the ER negative cell line also lacks E-cadherin and desmoplaquin I/II contrarily to the T47D cell line . On thes et al. ). Data cs et al. ; O’Lone s et al. ; Sommerss et al. ), and ths et al. ) and itss et al. ). The abs et al. ). Viment-1) did not affect cell viability or even promoted it slightly, which shows some specificity of this glycoprotein to cancer cells. Although very promising, this result is still preliminary and further experiments using non-tumour breast epithelial cells should be conducted.To our knowledge, this is the first report on the use of BioEG against cancer cell lines and there are also no reports on the toxicity of this biosurfactant against non-tumour cells. Interestingly, we found that the exposure of the non-tumour MC-3 T3-E1 fibroblast cell line up to 48 h to several concentrations of BioEG . HoweveBacillus subtilis natto TK-1 negatively influences the cell cycle progression of MCF7 breast cancer cells. In that study, surfactin was found to decrease about 22.2% the G1 phase, the S phase remained constant and an increase of 16.6% of the G2 phase was observed , which is typical of apoptosis induction. This may be attributable to the mutation of the p53 gene present in both studied breast cancer cell lines, which is known to confer resistance to death by apoptosis  re re2011])o et al. ). Cell po et al. ) demonstr et al. ). In suma et al. ; Pinto eInterestingly, the biosurfactant BioEG seems to have a more secure profile when exposed to non-tumour cells. Besides not affecting cell viability up to 48 h of exposure, BioEG did not affect significantly the cell cycle of fibroblasts (MC-3 T3-E1 cells). Contrary to breast cancer cells, there was a small increase of cells at S phase, which may indicate a promotion of cell proliferation in view of the higher number of cells synthesizing DNA. These results represent an important finding as it seems that BioEG not only can be used as a chemotherapeutic agent, but also in many other biomedical applications, such as invasive surgery recovery. BioEG proved to selectively affect the two breast cancer cell lines under study, and although the non-tumour cells (control cells) are not from human breast, the results are promising and open the possibility of using the biosurfactant on tissue regeneration.Currently, the studies explaining the mechanisms by which biosurfactants exert their anti-tumour activity are scarce. Nevertheless, from this work it was found that these molecules action is not limited to their effect on cell membranes (membrane disruption), although it is still unclear if biosurfactants can be internalized by cells or if they act via modulating signalling transduction by binding to membrane receptors or by disrupting anchorage of signalling proteins on membrane lipid domains. Moreover, it is reasonable to expect that breast cancer cells present different response profiles when exposed to biosurfactants due to their different molecular signatures. However, no significant differences could be found between cancer cells with or without estrogen receptor, so we can suggest that the biosurfactants activity is not related with the presence of such receptor.In summary, the results gathered in this work are very encouraging regarding the biosurfactants potential for breast cancer treatment and even for other biomedical applications; nevertheless further research on their mechanisms of action is required.The authors declare that they have no competing interests.CD carried out the cytotoxicity and cell proliferation studies, and participated in the interpretation and discussion of the results. EJG carried out the production of the biosurfactants and helped to draft the manuscript. CFL participated in the design of the study, in the analysis and discussion of the cell cycle experiments, and helped to draft the manuscript. LRR conceived of the study, participated in its design and coordination, performed the statistical analysis and drafted the manuscript. All authors read and approved the final manuscript.


Dear Editor,Human pluripotent stem cells including human embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) are cells displaying abilities of unlimited self-renewal and differentiation into any somatic cell type. These unique properties make them increasingly attractive for novel applications in disease modeling, drug discovery, and cell therapy  patient  containing Penicillin-Streptomycin, and then cultured in mesenchymal cell medium and renal epithelial cell medium respectively for 1–2 weeks. In total, we established 5 EMC lines from healthy donors and 16 UC lines from healthy individuals and type II DM patients. These primary EMCs and UCs proliferate well and could be passaged for at least 6 passages in culture. Next, two EMC lines and two UC lines from healthy individuals and one UC line from a DM patient were randomly chosen and subjected to cellular reprogramming. A normal fibroblast line isolated from a 9-year old donor -based differentiation assays. As shown in Fig. We further examined the Next, we investigated the potency of the iPSCs in directed cell differentiations. PPs and NSCs were chosen because of their value in potential applications. In order to generate PPs, iPSCs were firstly treated with a combination of activin A and Wnt3a to initiate the definitive endoderm cell (DE) differentiation, a step resulting in 95% endodermal progenitors co-expressing FOXA2 and SOX17 Fig. . These rIn summary, we demonstrated here that integration-free iPSCs can be efficiently and consistently obtained from non-invasively acquired human EMCs and UCs, even in a defective disease context (i.e. type II DM) Fig. L. Given Supplementary material 1 (PDF 292 kb)Below is the link to the electronic supplementary material.


Drosophila genome, we resequenced the genomes of 19 tissue-culture cell lines and generated RNA-Seq profiles.Structural rearrangements of the genome resulting in genic imbalance due to copy number change are often deleterious at the organismal level, but are common in immortalized cell lines and tumors, where they may be an advantage to cells. In order to explore the biological consequences of copy number changes in the bantam, an anti-apoptosis miRNA. Third, even when copy number changes seemed distinct between lines, there was strong evidence that they supported a common phenotypic outcome. For example, we found that proto-oncogenes were over-represented in one cell line (S2-DRSC), whereas tumor suppressor genes were under-represented in another (Kc167).Our work revealed dramatic duplications and deletions in all cell lines. We found three lines of evidence indicating that copy number changes were due to selection during tissue culture. First, we found that copy numbers correlated to maintain stoichiometric balance in protein complexes and biochemical pathways, consistent with the gene balance hypothesis. Second, while most copy number changes were cell line-specific, we identified some copy number changes shared by many of the independent cell lines. These included dramatic recurrence of increased copy number of the PDGF/VEGF receptor, which is also over-expressed in many cancer cells, and of in vitro. This has implications for other cell-level natural selection progressions, including tumorigenesis.Our study illustrates how genome structure changes may contribute to selection of cell lines The online version of this article (doi:10.1186/gb-2014-15-8-r70) contains supplementary material, which is available to authorized users. While genes do generally come in pairs, there are a number of situations where gene copy number deviates from fully diploid . Some ofMechanisms responsible for different copy number classes vary. The major cause of whole chromosomal copy number change is mis-segregation at mitosis or meiosis, due to non-disjunction, checkpoint defects, cohesion defects, merotelic attachment of microtubules to kinetochores, multipolar mitotic spindles, or recombination or repair events generating dicentric and acentric chromosomes , 10. SegDrosophila and humans, extensive copy number change results in death during development [Drosophila this is unlikely due to specific drivers, but rather the additive effect of multiple copy number changes [At the organismal level, changes in copy number are often associated with a range of abnormalities, including death, developmental defects or delay, psychiatric disorders, spontaneous abortions, and cancers , 14. Somelopment , 20. In  changes .Candida albicans altered copy number of genes is believed to mediate antibiotic resistance [The effect of copy number change on fitness is context-dependent. For example, in crop plants polyploids often produce larger fruits or flowers . Unbalansistance . Similarsistance . Indeed,sistance . This lisistance . These sDrosophila melanogaster cells are diploid, with three pairs of autosomes and one pair of sex chromosomes, with females having two Xs and males having a single X and a Y chromosome. The number of X chromosomes determines sex [D. melanogaster tissue-culture cells. As previously demonstrated by resequencing S2 cells [Euploid ines sex , and theines sex , 28. Theines sex . The smaines sex . To undeS2 cells , we founD. melanogaster reference genome to identify the relative copy number of each gene. In two cases, we resequenced libraries made from independent cultures, grown in different labs (S2-DRSC and Cl.8) to assay copy number stability, and found excellent agreement. For the Cl.8 line, we found that the overall genome copy number structure was 99.6% identical. For the highly rearranged S2-DRSC line, we observed 87.2% copy number agreement between two independent cultures, suggesting that even these highly aberrant copy number states are relatively stable. Below, we describe the structure of these genomes in order of degree of copy number change.To determine copy number genome-wide, we performed next generation DNA sequencing (DNA-Seq) on naked DNA harvested from 19 modENCODE cell lines –41 and cS1 cell line. We observed a DNA-density peak at 1.47 from DNA-Seq of S1 cells, suggesting that a segmental duplication of autosomal DNA occurred in this line (approximately 50% increase) on a baseline diploid karyotype, since there was no DNA block with intermediate DNA content between approximately 1.5 and 1. Another example is Kc167 cells, which had at least four levels of relative read-count ratios centered on 0.58, 0.77, 1.03 and 1.29. This distribution of DNA densities was consistent with tetraploidy. In the majority of cases, this simple analysis yielded a clear ploidy estimate. We scored BG3-c2, Cl.8, D20-c2, D20-c5, D4-c1, L1, S1, W2, and D8 cell lines as minimally diploid, and S2-DRSC, S2R+, S3, Sg4, Kc167, D16-c3, and D17-c3 cell lines as minimally tetraploid. Our results for D9 and mbn2 cell line ploidy were inconclusive, due to the presence of multiple regions of relative read densities that were not ratios of whole numbers.We first determined basal genome ploidy status from ratiometric DNA-Seq data. We took advantage of the extensive copy number deviations in the cell lines to make this determination. In our DNA-Seq analysis of the cell lines, we set the mean peak of DNA-Seq read count density at ‘1’ to reflect the relative nature of the measurements and plotted X-chromosome and autosomal DNA-Seq densities separately  showed good agreement. These data suggest that even if the cell-to-cell karyotypes differ, the distribution of karyotypes is stable in the population of cells from a given line.Interestingly, the karyotypes of individual cells varied in all lines Figure . Prima fDrosophila. Sexual identity is fixed early in development by Sex-lethal (Sxl) autoregulation [We identified frequent numeric aberrations of the X, Y, and fourth chromosomes. X chromosome karyotype is a natural copy number deviation that determines sex in gulation , so deviS2-DRSC, BG3-c2, Cl.8, D20-c2, D20-c5, D4-c1, L1, mbn2, S1, S3, Sg4 and W2 lines showed under-representation of reads mapping to the X chromosome (X:A <0.75), suggesting that they are male, or female cells that have lost X chromosome sequence. Similarly, by these criteria Kc167, D8, D9, D16-c3 and D17-c3 cells appear to be female (X:A >0.75), but might also be male with extensive X chromosome duplications. Cytological analysis confirmed these findings  localizes to the X chromosome and hyper-activates gene expression to balance transcription levels to that of autosomes [Sxl pre-mRNAs controls SXL protein production, which in turn regulates MSL formation by modulating msl-2 splicing and protein levels. Sxl also regulates sex differentiation via the splicing of transformer (tra) pre-mRNA [D9 cells, we observed that the two RNA components of the male-specific MSL complex (roX1 and roX2) genes were expressed at female levels in the cell lines with X:A >0.75 , suggesting that observed DNA-Seq copy number values were due to the female identity of the cells used to establish these cultures. Similarly, cell lines that had an X:A <0.75  expressed roX1 and/or roX2 at male levels, which was again consistent with the deduced sex. The expression of msl-2, tra, and Sxl were also consistent with sex karyotype. Overall, the cell lines with a X:A >0.75 showed female expression, while those with a ratio of <0.75 showed male expression ; however, there was some ambiguity. For example, D9 expressed intermediate levels of roX1, male levels of msl-2 and female tra. We suggest that in the majority of cases X chromosome karyotype is the result of the sex of the source animals, but where karyotype and sex differentiation status are ambiguous, the X chromosome copy number may be due to gains/losses during culture.To determine sexual identity we analyzed the expression of sex-determination genes and isoforms from RNA-Seq data compared to those from 100 different lines of sexed ts Table . In Drosutosomes . The altpre-mRNA , 45. ExcroX genes were expressed in whole adult males (not shown), while in the cell lines, sometimes only one roX gene was highly expressed. To determine if expression of a single roX gene was sufficient for MSL-complex-mediated dosage compensation, we measured X chromosome gene expression relative to autosomes. Overall transcript levels from genes from the X chromosomes in the cells that expressed roX genes at male levels were not significantly different from those of autosomes , suggesting that having a single roX is sufficient for normal X chromosome dosage compensation in these cell lines.Interestingly, both functionally redundant D. melanogaster Y chromosome is not currently assembled, but some Y-chromosome genes are known. DNA-Seq reads were mapped on the Y chromosome (chrYHet) in a minority of the male cell lines  and we observed Y chromosomes by cytology in BG3-c2, Cl.8 and S1 lines  was also consistent with karyograms and reflects loss of Y chromosomes . The Y chromosome bears only a few fertility genes  that should be of little consequence outside the germline. Frequent loss suggests that there is little selective pressure to maintain a Y in tissue culture cells.We observed frequent loss of the Y chromosome from the male cell lines. The Cl.8 cells where overall genome structure is relatively intact diploidy, the number of fourth chromosomes varied from 0 to 3. This observation was also supported by DNA-Seq results, which demonstrated clear decrease of copy number -corrected permutation test).Lastly, we observed widespread loss/gain of the short (approximately 1.4 Mb) fourth chromosome in cell lines by both DNA-Seq and cytology  are derived from a single ancestral cell line and differ by divergence, the majority of the cell lines were isolated independently, suggesting that similarities in genome structure occurred by convergent evolution under constant selection for growth in culture. Our investigation revealed 89 regions of the genome covering a total of approximately 9.3 Mb showing strong enrichment for increased copy number . Among those segments, 51 regions were longer than 5 kb. We also found 19 regions covering approximately 2.9 Mb with significant enrichment for decreases in copy number; 14 of these regions were longer than 5 kb. Driver genes promoting growth in culture may be located in these regions.While the overall genome structures were cell line-specific, we did observe regions of recurrent copy number change. While some of the cell lines . The most overlapping segment within this region was a duplication region of approximately 30 kb. There are six annotated genes in this core duplicated segment , UDP-galactose 4′-epimerase , CG3402, Mediator complex subunit 30 and UV-revertible gene 1 (Rev1). When we asked if any of these specific genes showed increased copy number in the other cell lines, even if segmental structure was lacking, we found that CR43334 and Rev1 had higher copy numbers in five additional cell lines. As another example, an approximately 19 kb duplication region in chromosome 2 L was found in 10 different cell lines (combined P < 1.0e-17). This region included only one gene, PDGF- and VEGF-receptor related (Pvr), suggesting that copy number for this gene is highly selected for in cell culture. If genes in these recurrent copy number increase regions were drivers, then we would expect that they would be expressed in the cells. Indeed, pri-bantam and Pvr genes were highly expressed in the cell lines  were found in 10/19 cell lines . This suggests that there are regions in the genome that suffer frequent breaks in tissue-culture cells. Investigation of hot spots revealed 18 containing long terminal repeats (LTRs) or long interspersed elements (LINEs) in the reference assembly, and an additional 9 regions showed simple DNA repeats within the 1 kb (±1 kb) windows. These observations are consistent with reports of overrepresentation of sequence repeats at copy number breakpoints [P = 4.07e-10, Fisher’s exact test), but not precise locations. These data suggest that there were both structural features in the genome that promoted generation of copy number changes and selection that determined which copy number changes were retained.Creation of common copy number changes would be facilitated by repeated breakage at ‘hot spots’ in the genome due to regions of microhomology or longer stretches due to structures such as inserted transposons. In the absence of selection, the extant breakpoint distribution would map the positions of such hot spots. We mapped breakpoints by examining read-count fluctuations in every 1 kb window over the genome to identify 2,411 locations with breaks in at least one of the 19 cell lines Figure . Among takpoints , and witakpoints , 47. ForS2-DRSC, S2R+, mbn2, Kc167, D8, D9 and D17-c3) mRNA level was positively correlated with gene dose. There was no correlation between gene expression and gene dose in Sg4 cells. Even in the cases where the correlation was positive, the correlation was usually not linear, as has been previously observed [P < 0.05, Mann-Whitney U test). Similarly, overall gene expression of the low copy number genes was moderately higher than expected on a per copy basis , restricted to histone H3K9 di- and tri-methylation marks, and their related proteins  Kc167 cells . Additionally, we found increased copy numbers of genes encoding members of the dREAM complex in S2-DRSC, mbn2, S1 and S2R + cells. The dREAM complex represses differentiation-specific gene expression [If there has been selection for particular advantageous copy number configurations in the cell lines, then this should result in a coherent pattern of events in terms of specific cellular activities such as growth control. As a first pass analytical tool, we performed Gene Ontology (GO) term enrichment analysis to determine if copy number changes were associated with particular functions Figure . Tissue pression , 52, conP < 0.001) between copy number class and function were with genes having cell cycle, metabolic, or reproduction-related GO terms (reproduction-related categories contain many of the cell cycle genes due to the high rates of cell divisions in the germline relative to somatic cells in adult Drosophila). Interestingly, genes with cell cycle-related functions were enriched in both high copy number regions in S2-DRSC and low copy regions in Kc167 cells (P < 0.001 for both). The context of this dichotomy was informative. Genes with high copy numbers in S2-DRSC cells included Ras oncogene at 85D, string, Cyclin D, cdc2, and other positive regulators of cell cycle progression, or mitotic entry. These data suggest selection for growth occurred in S2-DRSC cells. In contrast, tumor suppressor genes, and negative regulators of cell cycle, including Retinoblastoma-family protein (Rbf), Breast cancer 2 early onset homolog (Brca2), and wee, were preferentially found in the low copy number regions of Kc167 cells, suggesting that inhibitors of cell growth were selected against in Kc167 cells. Thus, both the high copy number and low copy number events can be explained by selection for proliferation.The most significant associations . These copy number changes were not due to passenger effects as stoichiometry-preserving changes in copy number were still evident after filtering for nearby genes (P = 0.03). Examples included the genes encoding Vacuolar H+ ATPase  and Dim γ-tubulin (DGT) complexes (P = 0.004), where members were among high copy number genes . By examining complexes where we failed to score a simple correlation, we uncovered more complicated patterns where sub-components of the complex show correlated and anti-correlated copy number changes. A good illustration is the proteasome . In contrast, proteins composing the base and alpha-type subunits of the 20S core were dominated by copy number gains . This suggests that the actual occurrence of coherent copy number changes among genes encoding protein complex members may be higher than what we report here.There were 142 protein-protein interaction networks that contained at least one gene product encoded from copy number change regions Figure A. Among Drosophila reference genome. Some cell lines, such as Cl.8, D4-c1, and W2, have relatively intact genomes. In contrast, the cell lines that are more widely used in the Drosophila community, such as S2-DRSC, Kc167, and S2R+, show extensive copy number change for >40% of the genome. Some of copy number differences might simply reflect genome structures in the source animal. For example, we have observed similar genome structures for D20-c2 and D20-c5, which were generated from the same original animals. Retention of the source genome structure would suggest that copy number change can be quite stable during cell passage, although many of the cell lines were derived from the same genotype of flies and have been rarely used since freezing. We also inferred change of genome structure over time. For example, we observed structural discrepancies between S2-DRSC and S2R + cell lines, even though these cell lines were derived from the original S2 cells circa 1972 [S2-DRSC has been grown very extensively in multiple labs since it was established, S2R + spent more than 25 years in a freezer, and has been grown sparingly in the 15 years since [in vitro culture of S2 cells contributed to the changes. Unfortunately, records for passages and transfers of cell lines among labs are anecdotal at best, so we cannot estimate change per passage. Nevertheless, cell line genome structure suggests that some elements of initial genotype are conserved, while most copy number changes are acquired. Locations of many copy number changes were shared among several cell lines, even those with clearly different sources, indicating that recurrent copy number changes have occurred.In our study, we provide copy number maps for 19 cell lines that display copy number differences relative to the rca 1972 . While SDrosophila[Drosophila animal populations and the copy number regions we identified in the cell lines. This suggests that the combination of hot spots for breaks and selective forces are distinct at the animal and cellular levels.Recurrence depends on a combination of biased generation of rearrangements and selection for the resulting copy number changes. Syntenic blocks reveal patterns of genome structure in rosophila, 56. Howrosophila. Similarrosophila identifirosophila–61. InteDrosophila S2-DRSC cells [Drosophila[Drosophila[The amount of transcript produced from genes with a given copy number is a function of both the gene dose and secondary changes in the rest of the genome, including feedback regulation and buffering due to kinetics . The sumSC cells , adult Drosophila, 64, 65,rosophila have shorosophila, 53, 64.bantam gene, and there was higher expression of the bantam microRNA (miRNA) in those cell lines. bantam is an anti-apoptotic miRNA that suppresses the pro-apoptotic function of Wrinkled (a.k.a. hid) and prevents proliferation-induced cell death [bantam was the most abundant miRNA in 25 cell lines, which were surveyed in the small-RNA component of modENCODE [bantam gene are drivers providing selective advantages to cell lines.One of the more striking observations suggests that pro-survival gene copy number has been under heavy selection. For example, almost 80% of the cell lines acquired additional copies of the pri-ll death . Indeed,odENCODE . This stPvr gene is duplicated in 10 cell lines. Pvr also promotes anti-apoptotic survival, as loss of Pvr causes apoptosis and reduces the number of hemocytes in Drosophila embryos, which can be rescued by the pan-caspase inhibitor p35 [Pvr and the PDGF/VEGF receptor ligand encoding PDGF- and VEGF-related factor 2 genes are highly expressed in the cell lines where the copy numbers of those genes have increased [Pvr reduces viability of cells and decreased mitotic as well as cytokinetic indexes in S2, S2R+, and Kc167 cells [Supporting the apoptosis suppression hypothesis, we also discovered that the platelet-derived growth factor (PDGF)/vascular endothelial growth factor (VEGF) receptor-encoding itor p35 . Pvr andncreased . This su67 cells –72.bantam and Pvr, many genes involved in the JNK pathway [S2-DRSC and Kc167 cell lines. For example, basket (encoding JNK) was located in a duplicated region in S2-DRSC cells. In contrast, Kc167 had fewer copies of puckered (encoding mitogen-activated protein kinase phosphatase) that functions to negatively regulate JNK activity. Finally, the kayak gene (encoding FOS), a downstream target of JNK, was found at a highly duplicated region of chromosome 3R (10 copies). These conditions of potentially high JNK activity in both cell lines would induce apoptosis in normal cells [Support for copy number modification of apoptosis responses is extensive. In addition to  pathway  showed cal cells , 75. HowDrosophila has two important initiator caspases [S2-DRSC and Kc167 cells. The inhibition of the caspase pathways can also be mediated by inhibitor of apoptosis proteins (IAPs). Drosophila has at least two genes that encodes IAP-like proteins and inhibit caspases; thread (encoding IAP1) and Inhibitor of Apoptosis 2 (Iap2) [S2-DRSC cells. In combination with JNK, these copy number changes might help cells grow in culture while minimizing apoptosis. Indeed, RNA interference-mediated depletion of thread or Iap2 results in reduced cell viability and increased apoptosis in S2, S2R+, or Kc167 cells [S2 cells [Drosophila cell lines in the study of tumorigenesis.caspases , Death-r2 (Iap2) . While t67 cells , 78, 79,S2 cells . This suCyclin E, or string genes, were located in high copy regions in 4 different cell lines and were never represented in low copy number segments among 19 cell lines. In contrast, well-known negative regulators of the cell cycle, such as Rbf and Brca2, were often found in low copy number regions, and never found in high copy number regions. In addition to the cell cycle, or apoptosis-related genes, frequent duplication (15 cell lines) of Rev1, which is near bantam, is also of note. Yeast Rev1p is required for mutagenic bypass to help repair a range of DNA lesions [Drosophila REV1 regulates a switch between highly processive DNA polymerases to lesion bypassing polymerases, such as DNA polymerase zeta and eta[Rev1 gene may contribute to hypermutability of the cell lines. However, it is also possible that Rev1 copy number is simply driven by linkage to bantam as a passenger.Copy numbers of cell cycle-regulator genes may also contribute to the proliferative nature of the cell lines. Positive regulators of the cell cycle, such as the  lesions . Similara and eta. This raOur results strongly suggest that copy number is a potent way for cells to evolve to culture conditions Figure . We suggDrosophila cell lines suggest that the power of Drosophila genetics can be applied to human diseases with copy number etiology.It seems likely that copy number changes are a generic feature of tissue culture cells and tumors, which share an uninhibited growth phenotype. Genomic aberrations, sustaining a proliferative state, and resisting cell death are hallmarks of cancer , 85. TheKc167 cells were cultured in the serum-free medium CCM-3  rather than in Schneider’s medium with 10% serum, and S2-DRSC and BG3-c2 were cultured in M3 + BPYE in place of Schneider’s medium. Cells were harvested at plateau for DNA extraction.The cell lines used for DNA resequencing and RNA-Seq were grown and harvested as described , except 7 cells were rinsed in phosphate-buffered saline and incubated with 2 mg of Proteinase K  for 2 hours at 37°C, phenol-chloroform extracted, and ethanol precipitated. Resuspended nucleic acid was digested with 50 μg of RNaseA (Amresco 0675) for 1 hour at 37°C. Final ethanol precipitation was performed with 0.3 M  NaOAc. Resuspended DNA was fragmented to less than 800 bp by sonication. Libraries were prepared as described , with the exception of an additional gel extraction (size select for 150 to 200 bp) after the PCR step .BG3-c2, Cl.8, S2-DRSC, and Kc167 was performed with the Illumina-based short-read sequencing platform. They were run for 36 cycles on a GAII or HiSeq 2000 (Illumina). The other cell lines used in this study, as well as an independent set of Cl.8, were sequenced to have either 76 or 100 bp paired-end reads on a GAII or HiSeq 2000 . We also re-analyzed S2-DRSC sequencing data from a previous study.DNA resequencing of BG3-c2, Cl.8, S2-DRSC, and Kc167 was performed as unstranded paired-end sequencing with 37 bp read-length. The other cell lines were paired-end sequenced to 76, 78, 100 or 108 bp read-length in a strand-specific manner .For RNA libraries, the extraction of total RNA from the cell lines was previously described . RNA-SeqChIP-chip datasets were from the modENCODE Data Coordination Center (DCC)  and are D. melanogaster genome that we obtained from UCSC genome browser . We mapped with Bowtie 0.12.8 for reads shorter than 50 bp, or Bowtie2 2.0.2 for longer read lengths [We aligned both DNA and RNA sequencing data to the reference  lengths , 90. We D20-c5. We used tetraploid-baseline for D20-c5, from the karyogram. For D9 and mbn2 cell lines, we performed further calculations based on tetraploidy. When karyograms suggest a mixed population of diploid and tetraploid cells, we used our estimation from DNA-Seq as our baselines to account for the detectable copy number segments .The alignment results were used to obtain ratiometric DNA densities in 1 kb windows using FREEC 5.7 . For segSamtools v.0.1.18  was usedWe used the GEM mappability program (GEnome Multitool) packages to define regions with poor mappability, and marked any 1 kb windows with less than 90% mappability as unknown . We geneP-values of 1 kb window copy number changes. We adjusted P-values using the Benjamini-Hochberg method for the multiple hypothesis correction [P-values where specific regions were described. Analysis of breakpoints was performed with custom scripts written in R. We used sequence for the breakpoints that were found from five or more cell lines to find potential motifs with the MEME suite  [To calculate significance of copy number changes among cell lines, we performed permutation tests. We randomly shuffled locations of 1 kb windows within a cell line genome-wide one million times to determine rrection . Stoufferrection  was usedm 50 bp) .mod(mdg4) since these caused errors in downstream analysis. RNA-Seq results were aligned to the genome using TopHat 2.0.6 [For RNA-Seq analysis, we used Ensembl release 67  of Flybaat 2.0.6 . TopHat at 2.0.6 . Option at 2.0.6 .We analyzed sex-specific splicing events using Spanki 0.4.0  . We usedP < 0.001 as a cutoff of correlation (r > 0.2 for X chromosome).ChIP signals from microarray datasets were based on normalized intensity ratio  in wiggle format files. Areas under the wiggle histograms were calculated and normalized with the length of regions of interest using R. We determined ChIP signals for 1 kb upstream of transcription start and gene body regions separately. Pearson’s correlation was used to analyze the relationship between copy number and ChIP signal. We used r > 0.1 and P < 0.01, and integrated copy number information (S2R + cell line) with an R script. Differences in the number of genes showing copy number change from the expected value were tested by Fisher’s hypergeometric test. Significance of the number of DPIM clusters with coherent copy number change was tested by permutation tests . We used Cytoscape 2.8.3 to visualize networks [Lists of genes in the protein-protein interaction network were from the Drosophila Protein interaction Map (DPIM) . We usednetworks . To acconetworks , 56.P-values were corrected with the Holm-Bonferroni method [S2-DRSC and Kc167 cell copy number are in Additional file For the GO analysis, we used a Cytoscape plugin, BiNGO 2.44 . A hyperi method . Gene liCells were treated with 1 mM colchicine for 2 hours to disrupt the mitotic spindle. After phosphate-buffered saline washing, we added hypotonic solution (0.5% sodium citrate) by gently dropping (5 ml into a 15 ml tube) and incubated for 10 minutes at room temperature. We centrifuged the cells to remove supernatant, then fixed cells by adding 3:1 (v:v) ice-cold mix of methanol and acetic acid (5 ml) drop-wise. The step was repeated. The supernatant was discarded and the cells were resuspended in 100 μl of fixative and 10 μl was spread and air-dried on a microscope slide. DAPI (1.5 mg/ml) in Vectashield  was used for staining. Chromosome preparations were analyzed using a Zeiss Axioplan fluorescence microscope  equipped with a CCD camera . We used Adobe Photoshop to align the karyograms. Detailed interpretation of mitotic spreads is provided in Additional files Cl.8 (#2), BG3-c2, Kc167, and S2-DRSC are in the GEO under accessions GSM697064-5, GSM498672-3, GSM498670-1, and GSM498668-9. Data for the other cell lines as well as Oregon R results used in this study are in the SRA under accessions SRA052953 . S2-DRSC (#1) [All sequencing data described in this manuscript can be found in the Gene Expression Omnibus (GEO) and the SRA. DNA-Seq data for RSC (#1)  is archiChIP-chip results  are in tKaryograms of all cell lines used in this study.(PDF 61 KB)Additional file 1:A summary of the number of chromosomes and whole chromosome copy number changes from the karyograms.(PDF 4 MB)Additional file 2:Genome-wide copy number in cell lines and copy number breakpoints (1 kb level).(ZIP 6 MB)Additional file 3:Genome-wide copy number and expression data (gene level).(XLSX 7 MB)Additional file 4:


In this report, we showed that two tumor cell characteristics, namely the malignancy and drug-resistance status can be evaluated by their membrane resealing response. Specifically, membrane pores in a number of pairs of cancer and normal cell lines originated from nasopharynx, lung and intestine were introduced by nano-mechanical puncturing. Interestingly, such nanometer-sized holes in tumor cells can reseal ~2–3 times faster than those in the corresponding normal cells. Furthermore, the membrane resealing time in cancer cell lines exhibiting resistance to several leading chemotherapeutic drugs was also found to be substantially shorter than that in their drug-sensitive counterparts, demonstrating the potential of using this quantity as a novel marker for future cancer diagnosis and drug resistance detection. Finally, a simple model was proposed to explain the observed resealing dynamics of cells which suggested that the distinct response exhibited by normal, tumor and drug resistant cells is likely due to the different tension levels in their lipid membranes, a conclusion that is also supported by direct cortical tension measurement. Currently, diagnosis of cancers largely relies on biopsy1468Interestingly, accumulating evidence has shown that the physical properties of cells are intimately related to their pathological state1011121314151718In this study, we used a mechanical puncturing approach see  to creat−1 after removal of the indenter. Membrane pores in the nasopharyngeal carcinoma (NPC) cell line, HONE1 were created by a 500 nm -radius AFM indenter . SpontanTo examine whether such a huge difference is a general feature between cancer and normal cells, we systematically examined the resealing response in cell lines derived from three anatomical positions, namely, nasopharynx , lung  and intestine . Interestingly, cancer cells were found to always reseal 200% to 300% times faster than the corresponding normal ones irrespective of the organs from which they were established .More surprisingly, the resealing behavior of cancer cells also appears to be influenced by their drug-resistance status. Specifically, two pairs of cancer cell lines with and without resistance to Cisplatin (i.e. HONE1-EBV CisR & HK1-LMP1 CisR versus HONE1-EBV & HK1-LMP1 respectively), a drug widely used in treating head, neck and ovarian cancer patients, and one pair of NPC cell lines with and without resistance to AUY922, a drug targeting heat shock protein-90 (HSP90), were tested. All drug resistant cell lines exhibit a much shortened resealing time as compared to their non-resistant counterparts . Another21Finally, to further confirm the reverse trend between the resealing time and drug-resistant characteristic, we developed a series of HONE1 sub-lines with gradual increase of resistance to AUY922 by pulsing HONE1 with the drug repeatedly for 6 months . Again, To better understand the distinct resealing response observed here, recall that, from a thermodynamics point of view, the free energy of a membrane pore, with radius r, can be expressed as2324BT is the thermal energy and D is a parameter representing how fast the pore edge can move. Following this reasoning, the pore radius as a function of time is predicted to be,where γ is the lipid bilayer tension while σ is the edge energy (or line tension) associated with the peripheral of the pore . Physica0 being the initial radius of the hole . Given that the structure and diffusivity of lipid molecules in different cells are unlikely to vary significantly, the values of σ and D should be more or less the same across cell types  of cells was measured via nano-indentation (refer to m (generated by the passive deformation of the actin cortex as well as the active contraction of myosin motors inside) is expected to be much larger than γm and γ exists, that is a higher level of γm will be accompanied by a higher level of γ and vice versa. Secondly, we monitored the resealing response of A549 cells treated with Jasplakinolide (Jas), Cytochalasin D (CytD) and Blebbistatin (Blebst). Jas and CytD are known to disrupt the actomyosin assembly in the cell cortex while the contractility of myosin will be inhibited by Blebst  and corresponding normal  cell lines were measured by rate-jump indentation see . As showIn summary, here we demonstrated the potential of using membrane resealing time as a novel marker in differentiating cancer cells from their normal counterparts. Specifically, it was shown that the membrane pores in various cancer cell lines derived from three anatomical positions,  all reseal 200% to 300% faster than those in the corresponding normal ones. More interestingly, we found that there is a strong correlation between the resealing response of tumor cells and their capability to resist anti-cancer drugs with a clearly shortened resealing time in different cancer cells with resistance against commonly used drugs including Cisplatin, AUY922 and Erlotinib. Given that current drug sensitivity tests, no matter by colony, dye exclusion assays or other biochemical means, often require days to even weeks to complete and the results generated are usually far from accurate enough for clinical decision making. Our approach may provide an alternative for achieving rapid drug-resistance identification in the future.Our analysis and cortical tension measurement suggest that the distinct resealing response is likely due to the different tension levels in the lipid membrane of cells. Actually, previous studied have indeed found that several cancer  cells have a lower cortical tension (or elasticity)11283032® II AFM . A probe with a flat ended silicon nitride tip  of diameter of 1, 2 or 3 μm, and a cantilever spring constant of 0.035 N/m, was used. The AFM tip was first made to indent into the cell at a speed of 0.2 μm/s until an indentation depth of 0.4 μm was reached. This was followed by holding for 30 s, and then retraction at a speed of 0.1 μm/s. Size evolution of the hole in the plasma membrane was captured by time-lapse images, taken at a rate of 10 frames/sec, and then quantitatively analyzed by a MATLAB program . Specifically, HONE1 cells were washed with ice-cold PBS three times and incubated with fluorescent CT-B. Then anti-CT-B antibody was added to crosslink the CT-B in the lipid rafts into patches readily to be visualized by fluorescence microscopy. Cells were kept at 37 °C with 5% COSupply of HSP-90 inhibitor drug, AUY922 was obtained from Novartis Pharmaceuticals (HK) Ltd. The NPC sub-line (HONE1-AUY922-R) which is resistant to AUY922 was established by pulsing HONE1 cell line with 30 nM AUY922 repeatedly every two to three days for six months until drug resistance is developed. The cisplatin-resistant cell lines (HK1-LMP1 CisR and HONE1-EBV CisR) were provided by Professor Brigette Ma & Dr. Eric Wong from the Department of Clinical Oncology, Chinese University of Hong Kong. The whole series of lung cancer cell lines with and without resistance to the anti-EGFR targeted drug, Erlotinib were acquired from ATCC. For other details of cell lines and drug resistance nature, please refer to The same protocol used in the mechanical puncture tests, without the retraction stage at the end, was adopted here. In particular, the contact force between the cell and the cylindrical probe during the indenting and subsequent holding stages was recorded which, in conjunction with a simple model, enabled the so-called cortical tension of cells to be estimated .