Kounnis V.,University of Ioannina |
Svoboda M.,Medical University of Vienna |
Tzakos A.,University of Ioannina |
Sainis I.,University of Ioannina |
And 3 more authors.
OncoTargets and Therapy | Year: 2011
Background: Organic anion-transporting polypeptides (OATPs) are influx transporters that mediate intracellular uptake of selective endogenous and xenobiotic compounds. Identification of new molecular targets and discovery of novel targeted therapies is top priority for pancreatic cancer, which lacks any effective therapy. Materials and methods: We studied expression of OATP 1A2, 1B1, and 1B3 in pancreatic cancer tissue and in cell lines. Formalin-fixed paraffin-embedded biopsy material of 12 human pancreatic cancers was immunohistochemically assessed for protein expression of the three studied influx transporters. Immunohistochemistry was evaluated by experienced pathologists and quantified by use of an automated image analysis system. BxPC-3 and MIA PaCa-2 pancreatic cancer cell lines were used to quantify transcripts of OATP 1B1 and 1B3. Results: OATP 1A2, 1B1, and 1B3 proteins were found ubiquitously expressed in all studied cases. Quantification performed by HistoQuest system revealed that mean intensity was 53 for 1A2, 45 for 1B1, and 167 for OATP 1B1/1B3 on a range scale 0-250 units. At mRNA level, 1B1 and 1B3 were overexpressed in both studied cancer cell lines but not in normal pancreatic tissue. Conclusion: OATPs 1A2, 1B1, and 1B3 are highly expressed in pancreatic adenocarcinoma. We suggest that expression of these transporters in pancreatic cancer justify research efforts towards discovery of novel therapeutics targeting OATPs. © 2011 Kounnis et al, publisher and licensee Dove Medical Press Ltd.
Bangert C.,Medical University of Vienna |
Strober B.E.,New York University |
Cork M.,University of Sheffield |
Luger T.,Universitatsklinikum Munster |
And 7 more authors.
Dermatology | Year: 2011
Background: Topical pimecrolimus may maintain remissions of atopic dermatitis (AD) by inhibiting subclinical inflammation. Objective: To evaluate clinical and cytological effects of pimecrolimus in topical corticosteroid- treated and resolved AD lesions. Methods: Patients (n = 67) with resolved AD lesions were randomized to 3-week double-blind treatment with either pimecrolimus cream 1% or vehicle cream. Outcome measures were reduction in Eczema Area and Severity Index (EASI) and number of leukocytes in skin biopsies in all randomized patients who were evaluable at the end of study. Results: The proportion of patients with a localized EASI <2 at the end of study was higher with pimecrolimus cream 1% than with vehicle cream (73.5 vs. 39.4%, respectively). There was a significant decrease in the number of infiltrating CD45+ cells in pimecrolimus cream 1% compared with placebo cream (-88.2 vs. 43.2 cells/mm2, respectively, p = 0.047) and a slight but nonsignificant reduction in the number of dermal dendritic cells, Langerhans cells, T cells and macrophages with pimecrolimus versus vehicle cream. Limitations: This was an exploratory study. Conclusion: Topical pimecrolimus was effective at maintaining betamethasone-17α-valerate-induced AD remission by inhibiting recurrences of the inflammatory infiltrate in the skin. Copyright © 2010 S. Karger AG, Basel.
Agency: Cordis | Branch: H2020 | Program: MSCA-ITN-ETN | Phase: MSCA-ITN-2015-ETN | Award Amount: 3.66M | Year: 2016
The calcium sensing receptor (CaSR) is a class C Gprotein-coupled receptor that plays a pivotal role in systemic calcium metabolism by regulating parathyroid hormone secretion and urinary Ca excretion. Abnormal CaSR function is implicated in calciotropic disorders, and in non-calciotropic disorders such as Alzheimers disease (AD), cardiovascular disease (CVD), diabetes (DM), sarcopenia and cancer, which account for >25% of the global disease burden. The CaSR is a unique GPCR whose principal physiological ligand is the Ca2\ ion; it is expressed almost ubiquitously; interacts with multiple G subtypes regulating highly divergent downstream signalling pathways, depending on the cellular context. The CaSR Biomedicine is a fully translational project that utilises the concept of a single molecule, the CaSR, influencing a range of physiological and disease processes, to develop a unique, strong multidisciplinary and intersectoral scientific training programme preparing 14 young scientists to become specialists in GPCR biology and signalling. The objectives of CaSR Biomedicine are: 1. Educate and train Early Stage Researchers to become highly innovative scientists to enhance their career perspective. 2. Elucidate ligand- and tissue-dependent differences in CaSR physiology by examining its functions at cellular level and thus to contribute to the understanding of GPCR signalling in general. 3. Assess how CaSR function is altered in AD, CVD, DM, sarcopenia, and cancer, and to find innovative CaSR-based therapeutic approaches for these major, age-related disorders. 4. Establish long-lasting interdisciplinary and intersectoral cooperation among researchers and between researchers and industry, to strengthen the European Research Area. Therefore the CaSR Biomedicine will investigate the complexity of CaSR signalling and function to identify CaSR-based therapeutic approaches to diseases linked to changes in CaSR expression or function (AD, CVD, DM, sarcopenia, and cancer).
News Article | December 21, 2016
BALB-NeuT transgenic mice were obtained through collaboration with G. Forni and maintained in our facilities according to the European Union guidelines. All animal experiments were performed according to the EU and national institutional regulations. Mice were screened at 3–4 weeks of age for hemizygosity (neuT+/neuT−), and negative littermates served as wild-type BALB/c mice controls. Mammary glands of BALB-NeuT female mice were inspected twice a week and arising tumours were measured in two perpendicular diameters. Data acquisition for bone-marrow DCCs was performed in a blinded manner, whereas enumeration of lung metastasis was performed unblinded by two observers. All experimental animal procedures were approved and conducted according to German federal and state regulations (Government of Upper Palatinate, 55.2-2532.1-27/14). Mice were anaesthetized with midazolam 5 mg kg−1, fentanyl 0.05 mg kg−1, medetomidin 0.5 mg kg−1 by intraperitoneal injection. The thorax and abdomen were shaved; the skin was incised caudal to cranial along the midline. Fifty spheres were mixed with Matrigel (BD Biosciences: 356231, final concentration, 40%) and injected into the fourth right mammary gland of BALB/c mice (4 and 40-week-old mice). For tissue transplantation, a piece (approximately 1 mm3) of donor mammary tissue from 4-week-old BALB-NeuT mice (gland model) or primary tumours (primary tumour model) was implanted in the cleared mammary fat pad of recipient mice (4-week-old BALB/c mice). The skin was closed by a suture using polygelatin string (Ethicon) and anaesthesia was antagonized with flumazenil 0.5 mg kg−1, atipamezol 2.5 mg kg−1, naloxon 1.2 mg kg−1 by subcutaneous injection. Postoperative analgesia was achieved by buprenorphin (0.1 mg kg−1) by subcutaneous injection. Curative surgery or dissection was done when the diameter of tumours was between 5–10 mm. After surgery, mice were kept until we observed the first general signs of reduced health. After dissection, lungs were macroscopically inspected and individual metastases counted. Data were taken from ref. 8. Briefly, gland or tumour areas were calculated from 270 mammary glands or tumours of 27 mice assuming the shape of an ellipse or circle for each tumour. The tumour area of mammary glands without palpable (that is, not measurable by a caliper) tumours was set to 0.1 mm2 (that is, assuming a diameter of 350 μm of a total, circular hyperplastic lesion within a mammary gland) for lesions from 4–9-week-old mice and 0.4 mm2 for 11-week-old mice. The adjustment for 11-week-old mice was based on a microscopic evaluation showing an about 4-fold increase in hyperplastic lesions. Dissemination to the bone marrow was determined by the number of cytokeratin-positive cells per 106 bone-marrow cells (Extended Data Fig. 1a). Bone marrow was collected from femurs and tibiae. The bone marrow was rinsed with a 26-G needle with 1 ml of PBS. After density gradient centrifugation, 5 × 105 interphase cells were put on adhesion slides (Menzel). At least 106 cells per mouse were stained to detect positive cells. Blocking solution (5% rabbit serum in 1× TBS (50 mM Tris-base, 150 mM Nacl, pH 7.4)) was added to the slides to rehydrate the cells and to block unspecific binding of antibodies to the cells. After 20 min the blocking solution was discarded and primary antibody against cytokeratins 8 and 18 (CK8/18; all antibodies and working concentrations are in Supplementary Table 9) or guinea pig serum (the CK antibody originated from guinea pig) as control, was added and slides were incubated for 60 min. The primary antibody was discarded and the slides were washed 3× for 3 min in 1× TBS. The slides were incubated with the secondary antibody for 25 min, and then washed 3× for 3 min in 1× TBS followed by incubation with the ABC complex (Vector Laboratory) for 25 min. Finally, the development system of the BCIP/NBT (AP Conjugate Substrate Kit, Bio-Rad Laboratories GmbH, 1706432; Levamisol hydrochloride, Sigma-Aldrich GmbH, L-9756) for alkaline phosphatase enzymatic substrate was added for 10 min. The slides were washed 3× for 3 min and screened for CK8/18-positive cells. The positive cells were typically violet-to-black in colour. TUBO, a tumour cell line derived from a mouse primary mammary tumour of BALB-NeuT and known to express CK8/18, was used as a positive control. Laser microdissection (PALM MicroBeam from Carl Zeiss MicroImaging GmbH) was performed to dissect metastatic lesions from lungs, primary tumours and epithelial layers of mammary glands of BALB-NeuT mice at the time point of early lesions (7–9-week-old mice; examples are shown in Extended Data Fig. 1b), and BALB/c mice at different ages (description of samples is given in Supplementary Table 1). Small pieces adding up to 100,000 μm2 for each sample were catapulted into a cap with 10 μl paramagnetic, biotinylated, oligo-dT-peptide, nucleic-acid, bead suspension and lysis buffer (Active Motif, 29011). Extraction of mRNA and microarray experiments were performed as described previously40. Heatmaps in Fig. 1a were generated using Euclidean distance and complete linkage agglomerative clustering on row (gene)-wise standardized expression data (zero mean, unit standard deviation). Breast cancer cell lines (4T1, 66cl4, and 67NR) were provided by F. Miller. These cell lines were derived from a single mammary tumour that arose spontaneously in a wild-type BALB/cfC3H mouse. The MM3MG mouse mammary epithelial cell line derived from a BALB/c background was purchased from ATCC (ATCC CRL6376). The TUBO cell line is a cloned cell line established in vitro from a lobular carcinoma that arose spontaneously in a BALB-NeuT mouse (gift from G. Forni). All mouse and stably transduced cell lines were grown in DMEM medium (Pan-Biotech, P04-03500) supplemented with 10% (20% for TUBO cell line) FCS (Pan-Biotech: P30-3702), 2 mM l-glutamine (Pan-Biotech, P04-80100), 10 U ml−1 penicillin/streptomycin (Pan-Biotech, P06-07050). All human cell lines were purchased from ATCC and each cell line was maintained in medium recommended by ATCC. The origin of the cell lines was confirmed by short tandem repeat (STR) analysis (Cell-ID, Promega). All cells were incubated at 37 °C with 5% CO . Steroid hormones (progesterone, aldosterone, β-oestradiol, testosterone and hydrocortisone; all from Sigma-Aldrich) and RU486 (Sigma-Aldrich) were dissolved in ethanol. RANKL (mouse Rankl, Abcam, ab151200; human RANKL, Abcam, ab9958); WNT4 (mouse WNT4, R&D systems, 475-WN; human WNT4, Abnova, H00054361-P01); lapatinib (Santa Cruz Biotechnology, SC202205); IWP-2 (Sigma-Aldrich, I0536); RANKL-neutralizing antibody (Lifespan Biotech, LS-C150261) were dissolved according to the manufacturer’s instructions. All cell lines were routinely tested for mycoplasma and were found to be negative. Fresh mammary glands or primary tumours were digested with 200 units per ml collagenase I (Worthington Biotech, LS004196) and 1 μg ml−1 hyaluronidase (Sigma-Aldrich, 4272) in basal medium for 2 h at 37 °C. The basal medium consisted of DMEM/F12 (PAN biotech, P04-41450) supplemented with 10 mM HEPES buffer (Sigma-Aldrich, H0887), penicillin/streptomycin (Pan Biotech, P1-010) and 10 μg ml−1 insulin (Sigma-Aldrich, I9278). Digested tissue cells were centrifuged and re-suspended in basal medium. The cells were subsequently cultured at a density of 5 × 104 cells per ml in ultra-low adherent plates coated with 1.2% poly-HEMA (Sigma-Aldrich, P3932) or at a density of 2.6 × 104 cells per cm2 for adherent culture in DMEM medium (Pan-Biotech, P04-03500) supplemented with 10% FCS (Pan-Biotech, P30-3702), 2 mM l-glutamine (Pan-Biotech, P04-80100), 10 U ml−1 penicillin/streptomycin (Pan-Biotech, P06-07050). Sphere culture medium was basal medium supplemented with 2% B27 (Gibco, 17504044), 10 μg ml−1 EGF (Sigma-Aldrich, E9644), 10 ng ml−1 bFGF (Sigma-Aldrich, F0291), 20 ng ml−1 hIL6 (gift from S. Rose-John), 4 ng ml−1 heparin (Sigma-Aldrich, H3149), 5 ng ml−1 GRO-α (R&D systems, 275-GR). Concentrations of activators, inhibitors and other molecules are given in the main text, figures or legends. Sphere cultures were incubated at 37 °C with 5% CO and 7% O and cultures were screened for spheres after 10 days. Only spheres with a diameter over 50 μm were counted. The size of mammospheres was inspected under a light microscope and measured using Zeiss Axiovision software (Carl Zeiss) after 10 days. TUBO cells were cultured at 3 × 104 cells per cm2 for high density and 5.2 × 103 cells per cm2 for low-density experiments. Primary cells derived from primary tumours were cultured in 10.6 × 104 cells per cm2 for high-density and 2.2 × 103 cells per cm2 for low-density experiments. Density criteria for human cell lines were 100% confluency for high density and 20–30% confluency for low-density. For hormone treatment and comparisons between low and high-density experiments, cells were incubated for 76 h with fresh hormone treatment and washes (2× with PBS) at 24-h intervals. We avoided changing medium and washing during incubation of cells for miRNA analyses. In migration experiments we seeded 104 cells per well (24-well migration chambers) for low-density experiments for all cell lines and 5 × 104 cells per well for high-density experiments with TUBO cells and 4 × 104 for the other cell lines. Transwell inserts (Corning, 3419) with a microporous membrane of 0.4 μm were used to separate the upper and lower compartments. The microporous membrane allows only soluble factors to pass between the compartments. Early lesion cells were cultured in the lower chamber and primary tumour cells were cultured in the upper chamber. Both were cultured at a density of 106 cells per well of 6-well plates (DMEM with 10% FCS). Transwell inserts (Corning: 3422) with 8-μm pores were coated with 30% matrigel. 4 × 104 from cell lines and 105 cells isolated from tissue or dissociated spheres were resuspended in FCS-free medium (DMEM) before seeding. Cells were then seeded in 200 μl of FCS-free medium on top of the Matrigel layer and FCS medium (DMEM containing FCS) was added to the lower chamber. For additional treatments medium in both upper and lower compartments was supplemented with the reagents at concentrations specified in the text and figures. After incubating cells isolated from mammospheres or from freshly digested tissues for 72 h, inserts were removed and cells were fixed with methanol (−20 °C for 10 min) and stained with trypan blue. Cells were counted from 3 fields (4× magnification) when visualized under the microscope. For the combined migration/sphere formation assay, cells were placed on a layer of 30% Matrigel in the upper chamber and the lower chamber was coated with poly-HEMA. The mammosphere medium used is described above. After 72 h, inserts were removed, fixed and stained with trypan blue for single cell migration analysis. 600 μl fresh sphere medium was added to the lower chamber and cells were incubated for 11 days when spheres were counted (Fig. 2e and Extended Data Fig. 2g). Single-cell suspensions were cultured in 96-well plates (Corning Inc) and proliferation was evaluated by a XTT-colorimetric assay kit (Roche, 11465015001) based on the manufacturer’s instructions. Seeding concentration of cells was 3,000 cells per well. The experiment was performed with 6 technical replicates. The medium was supplemented with the tested factors or hormones and vehicle (see corresponding experiments) and was changed every second day. For PGR and HER2 immunohistochemistry of tissue sections, we used 5-μm sections of paraffin blocks placed onto poly-l-lysine-coated slides. Samples were dewaxed by two 5-min washes in xylene and rehydrated with graded alcohol by 5-min washes and a final wash in water. A standard Tris–EDTA buffer and pressure-cooking was used for antigen retrieval and then sections were blocked in 0.3% H O in TBS and 10% normal goat serum. Sections were incubated for 1 h with primary antibodies and, after washing, secondary antibodies (Vector laboratory, PK4001 or PK5000) were added based on the manufacturer’s recommended dilution (see Supplementary Table 9). After washing with PBS, sections were stained using the ABC detection system (Vector Laboratory) according to the manufacturer’s instruction. Visualization was performed with chromogen reagent (Dako, 10046560) according to manufacturer’s instructions. For staining of cells from monolayer cell cultures, cells were seeded onto 24-well culture plates at an appropriate density. After 72 h of incubation, cells were washed with PBS and fixed with 4% PFA for 10 min. Then, cells were permeabilized with 0.2% Triton X-100 followed by washing steps and blocking with 1% BSA in PBS at 37 °C and incubated with primary antibody (see Supplementary Table 9) for 1 h at room temperature. Cells were then washed 3× with PBS and incubated with labelled secondary antibody (Jackson ImmunoResearch Laboratory Inc) for 1 h at room temperature. For nuclear counterstaining, cells were incubated for 10 min with 0.5 μg ml−1 DAPI (Sigma-Aldrich). For the staining of spheres in differentiation experiments, mammospheres were picked and transferred to a 24-well cell-culture plate and incubated for 8 h in sphere medium in order to fix them to the surface. The subsequent staining protocol was as for monolayer cell culture staining. For staining of cells attached to the inserts from migration experiments, inserts were used directly after migration (see migration assay), for the blocking step and immunofluorescence staining, the monolayer cell culture staining procedure was applied. Images were captured on an AxioVert 200M microscopy (Carl Zeiss Microscopy). Tissue sections were stained with an automated staining machine (Ventana, BenchMark ULTRA). Tissue sections used for analysis were stained within the same run. Images of stained tissue sections were scanned with the TissueFAXSi-plus imaging system (TissueGnostics, Vienna, Austria; acquisition software: TissueFAXS v3.5.129) equipped with a digital Pixelink colour camera (PCO AG). Images for the analysis of HER2 and PGR staining were analysed with HistoQuest software v3.5.3.0185 (TissueGnostics). Using the HistoQuest software, two markers were created: haematoxylin as master marker (nucleus) and HER2 or PGR as non-master marker. To achieve optimal cell detection, the following parameters were adjusted: (i) nuclei size; (ii) discrimination by area; (iii) discrimination by grey and (iv) background threshold. For the evaluation of the HER2 staining intensity of cells or the percentage of PGR-expressing cells, histograms were created, allowing the visualization of corresponding cells in the source region of interest using the real-time back-gating feature. The cut-off discriminated between false events and specific signals according to cell size and intensity of staining. For HER2 staining, 38,675 primary tumour cells (6 regions, 1.99 mm2), 28,850 cells from hyperplastic regions (25 regions, 1.55 mm2) and 14,938 cells from non-transformed ducts (30 regions, 0.93 mm2) were analysed. For PGR, 12,269 cells of early lesions (hyperplasia, 7 weeks, 11 regions, 0.5 mm2), 12,702 cells of non-transformed (normal duct, 7 weeks, 56 regions, 0.7 mm2) and 25,357 primary tumour cells (9 regions, 1.3 mm2) were analysed (Fig. 1d). All mRNA extractions were performed using the RNeasy kit (Qiagen, 74104) according to the manufacturer’s instructions. For miRNA extraction, the miScript II RT Kit (Qiagen, 217004) was used. cDNA was generated using a reverse transcriptase kit (Qiagen, 205311 for total RNA and 218161 for miRNA). Finally, 25 ng of cDNA was used for qPCR. qPCR was performed using a LightCycler instrument (Roche) and Fast Start Master SYBR Green Kits (Roche). Data analysis was done using the RelQuant software (Roche) with a reference gene and a calibrator (reference) sample in every run. Mouse reference cDNA served as a positive control. Samples with unspecific products in the melting curve analysis were discarded from further analysis. Expression levels are given relative to Actb (β-actin) for gene expression analyses and Rnu6 for miRNA analyses (primer sequences are provided in Supplementary Table 10). All primers for mRNA analyses were synthesized by Eurofins MWG Operon, and by Qiagen for miRNA analyses. For comparison of miRNA levels in high-density and low-density regions (Extended Data Fig. 10b) of formalin-fixed paraffin-embedded samples, regions were punched out using a 1.5-mm puncher (PFM medical; 48115). Samples were incubated for 10 min at 70 °C followed by xylene–ethanol de-paraffinization and overnight proteinase K (0.5 μg μl−1, Roche 03115828001) digestion. Then miRNA extraction was performed using the miRNeasy kit. For comparison of miR-30a-5p and miR-9-5p between HERhigh/PGRhigh human mammary carcinomas and HER2high/PGR− carcinomas, miRNAs were extracted from freshly frozen samples using the miRNeasy kit. Expression of miR-9-5p and miR-30a-5p was normalized to HER2−/PGRhigh breast cancers (see Supplementary Table 6 for details on patients). PGR expression was carried out with a lentiviral construct encoding human PGR-B (GeneCopeia, Z5911). Lentiviral packaging was conducted as previously described41. Helper vectors were pSPAX2 and pMD2.G (Addgene). Selection was performed using 10 μg ml−1 of puromycin (Sigma-Aldrich, P8833). For Her2 expression pLXSN–NNeu (rat wild-type Neu/Her2) was used (obtained from L. Petti)42. Retroviral delivery of transgenes was performed as described previously43. Helper vectors were pCMV–VSV-G and pUMVC3 obtained from Addgene. Selection was performed using 1,000 μg ml−1 of G418 (Sigma-Aldrich, G9516 ). MM3MG cells were transduced with lentiviruses and/or retroviral vectors and cell colonies were selected using antibiotics. Positively transduced clones were expanded and screened for PGR and/or HER2 levels by western blot analysis and qPCR. Cell lysates were prepared using RIPA buffer (Sigma-Aldrich, R0278) and were analysed with the BCA protein assay kit (Thermo Scientific, 23227) to measure and their protein concentration was equalized. Quantified protein lysates were resolved on 6.5% SDS–PAGE gels, and transferred onto a polyvinylidene difluoride membrane (Millipore), and immunoblotted with the primary antibodies overnight followed by incubation with the horseradish peroxidase-conjugated secondary antibodies. The blots were visualized using a substrate kit (GE Healthcare, RPN2109) and bands were visualized by Imagequant LAS 4000 (GE Healthcare). The full blot images are shown in Supplementary Fig. 1. To prepare conditioned medium, TUBO cells were seeded at a density of 3 × 104 cells per cm2. After 4 days, medium was collected, centrifuged and filtered and used as conditioned medium. For exosome isolation we used an ultracentrifugation method as previously described44. Exosome pellets were resuspended in fresh medium and used for T47D cell line treatment. PGR expression was checked at different time points (4, 8, 24, and 48 h). For miRNA sequencing we used 4 × 106 cells and exosomes were isolated from confluent medium from TUBO cells. The miRNA cloning and sequencing was done as described previously45. All pooled samples were sequenced on a MiSeq system (Illumina) in a single-end run with 80 cycles using the MiSeq reagent kit v3. Data analysis was performed using in-house written scripts. Sequences were mapped—without any mismatches allowed—against mouse miRNAs listed in the miRBase v20 (June 2013; http://www.mirbase.org). The minimum length of reads was set to 18 nucleotides. Annotated miRNA-reads were normalized as RPM values according to the total number of mapped reads in the respective library. Mimic miRNAs were ordered from Eurofins MWG Operon Company and all sequences are listed in Supplementary Table 11. For miRNA transfection we used reverse transfection protocols according to instructions for RNAiMAX (Life Technology, 13778030) and with a 50 nM concentration of miRNA. DNA samples were extracted from freshly frozen samples using the DNeasy Blood & Tissue Kit (Qiagen, 69504). Genomic DNA labelling was done using the Agilent SureTag DNA Labelling Kit (Agilent, 5190-3400). Array CGH was performed on oligonucleotide-based SurePrint G3 Mouse CGH Microarray Kit, 4x180K (design code: 027411) according to the protocol provided by the manufacturer (Agilent Oligonucleotide Array-Based CGH for Genomic DNA Analysis, v.7.2, July 2012). Ancestral relations among matched samples of primary tumour and metastases were inferred using array CGH profiles. The array comparative genomic hybridization dataset consisted of 28 primary tumour samples with 1–3 corresponding metastasis samples (18 primary tumours with 1 metastasis; 4 with 2 metastases and 6 with 3 metastases). Positions of the probes on the array were mapped to the current mouse reference genome (mm10) using the liftOver tool46. No background correction was applied to the data47. The data were first normalized within arrays using Loess48. Then, log ratios were corrected for spatial artefacts using a median filter with an 11 × 11 block of probes49 and a between array scale normalization was applied50. Duplicate probes (having the same genomic position) were summarized by their median log ratio. The R package limma51 (v.3.28.1) was used for normalization within arrays and between arrays (with default parameters). In a final step, wavy patterns were removed from the data using an approach similar to ref. 52, but with modifications to account for broad copy-number alterations. For every sample and chromosome, correction was carried out as follows. Because the maximum number of broad copy-number alterations on any chromosome observed in the data was two, a piecewise constant function with two pieces was fitted to the log ratios to estimate these broad alterations. Each piece was required to be longer than 5% of the chromosome length to avoid spurious small pieces. The wavy pattern was estimated by fitting a Loess curve with a window size of 100 probes to the residuals of the piecewise constant function fit. To avoid smoothing true focal alterations, the weight of probes with an absolute log ratio deviation greater than 0.5 from the piecewise constant function were set to 0 for the Loess fit. The estimated wavy pattern was then subtracted from the log ratios resulting in corrected values. After normalization the log ratios were segmented using Circular Binary Segmentation as implemented in the R package DNAcopy53 (v.1.46.0). The default parameters were used except for α, which was set to 0.001. Segments with a length of 5 or less probes were merged with the closest adjacent segment. For every sample, states with means closer than 0.05 were merged iteratively beginning with the two states with closest means. When two states were merged the new mean was given by the mean of the two old state means weighted by the number of probes in every state. After state merging, the remaining segment means were adjusted to have a median of 0. These segmented copy number profiles were then deconstructed into underlying copy number events using Ziggurat Deconstruction54. All these steps where performed using R (v.3.3.0). Aberration events as defined by left and right change points, and aberration type were pooled across the matched samples of a single mouse to form a mouse-specific base set of aberration prototypes. For this, amplifications and deletions that were similar by more than 80% as measured by their Jaccard-index regarding probe support were merged into single prototypes using Jaccard-distance-based complete linkage clustering and union of supports. Individual primary tumour and metastases samples were then encoded according to presence (absence) of the prototypic aberrations, whereby the present prototype was called by the minimum Jaccard-distance. The resulting feature vectors were then used for phylogenetic tree inference. Phylogenetic trees were generated by assuming ideal (that is, error-free) data and inferring plausible common ancestors (intermediates) of aberration profiles by extracting shared features of an increasing number of samples, that is, evaluating common aberration events in sample pairs, triplets, quads, and so on, and organizing these ancestors according to hierarchical levels. Subsequently, admissible edges were constructed top-down between vertices allowing for two re-losses of acquired gains and no re-gains of any losses (this condition was also ensured globally for each path). Then all simple paths from the normal cell to the samples were generated using the Igraph R-package (v.1.0.0), combined into a directed acyclic graph and filtered for the fewest genomic changes along the graph and lowest number of intermediates (maximum parsimony). This resulted in one unique phylogenetic tree for each mouse. For CGH analysis of single DCCs, bone-marrow sampling of patients with M1 stage cancer was performed within the study protocol of the GEBDIS study at the Central Hospital in Augsburg after informed, written consent of patients was obtained. The ethics committees of the University of Munich (ethics vote number 007/02) and Regensburg (ethics vote number 07-079) approved bone marrow sampling (including patients with M0-stage cancer) and genomic analysis of isolated cells. For all patients informed, written consent was obtained. For bone-marrow sampling and analysis for cytokeratin-positive cells of patients from Tübingen (approval by the ethics committee of Tübingen University, reference number 560/2012R) all specimens were obtained after written, informed consent. Bone-marrow sample preparation, slide preparation, cytokeratin staining and cell isolation was performed as previously described5. Whole genome amplification was performed as previously described5, 55. The method has become commercially available as a kit (Ampli1, Silicon Biosystems). A histogram of copy-number alterations (Fig. 5e) was generated for human primary breast cancers (n = 1,637) derived from the Progenetix database (http://www.progenetix.net) and DCCs isolated from bone marrow of breast cancer patients without (M0, n = 94; see Supplementary Table 7 for clinical details of patients) and with metastasis (M1, n = 91). We analysed data of 2,239 patients from the Department of Oncology and Obstetrics, University of Tübingen. DCC status was assessed according to the consensus protocol23, using the anti-cytokeratin antibody A45B/B3 and by evaluating 2 × 106 bone-marrow cells. PGR expression of primary tumours was categorized into PGR staining scores 0–1 for absent expression; 2–8 for intermediate expression and 9–12 for high expression. HER2 status of primary tumours was categorized into the staining score 0 for absence of HER2 staining (IHC negative); score 1 and score 2 without HER2 amplification (IHC positive) and score 2 with HER2 amplification and 3 (which is known to be caused by HER2 amplification; FISH positive). Statistical analyses and estimation of variation within each group of data were performed using GraphPad Prism v.6 and R v.3.3.1. For in vivo DCC experiments of primary tumour compared to early lesion spheres, sample size was estimated using G*Power (v3). No statistical methods were used to predetermine sample size for other experiments. For each experiment, mouse numbers are given in the figures or the text. All in vitro and primary culture experiments were performed at least in triplicate and Student’s t-test was used for comparisons. For all other experiments we applied the D’Agostino-Pearson omnibus normality test. When sample size was sufficiently large (n ≥ 8) and were not distributed normally according to the D’Agostino-Pearson test (P ≤ 0.05) we applied the Mann–Whitney U-test. For gene signature evaluation in Figs 1c, 3d and Extended Data Fig. 1e, g, gene wise t-test P values were combined using Stouffer’s method. A linear regression test (F-test for slopes) was used to compare proliferation curves and tumour growth. For comparing numbers between different groups we applied Fisher’s exact test or if the sample numbers were at least 5 in each condition the χ2 test. In Fig. 1d one-way ANOVA was used. All P values are two-tailed. All P values (0.05 ≤ P ≤ 0.0001) and statistical tests are mentioned in either figures or legends. Genomatix (v2.0) (https://www.genomatix.de) was used for signalling pathway analysis and oPOSSUM (v1) (http://opossum.cisreg.ca/oPOSSUM3/) for transcription-factor binding-site enrichment. For miRNA-binding enrichment, we used DIANALAB (http://diana.cslab.ece.ntua.gr/) and for the identification of target miRNAs for single target genes the miRANDA software (http://www.microrna.org/microrna/home.do) was used. The experiments were not randomized. The miRNA sequencing data and microarray data are deposited at the Gene Expression Omnibus (GEO) database under accession number GSE68683. Analysed data for microarray and miRNAs can be found in Supplementary Data 1 and 2, respectively. The mouse ancestral CGH data are deposited at the GEO database under accession number GSE87469. All raw data for presented graphs and statistics are deposited in Source Data files. Further material and data other than what is presented here can be obtained from the corresponding author (C.A.K.) upon request.
PubMed | TissueGnostics GmbH, Johannes Gutenberg University Mainz, University of Regensburg and Paul Ehrlich Institute
Type: Journal Article | Journal: PloS one | Year: 2015
Characterization of host-pathogen interactions is a fundamental approach in microbiological and immunological oriented disciplines. It is commonly accepted that host cells start to change their phenotype after engulfing pathogens. Techniques such as real time PCR or ELISA were used to characterize the genes encoding proteins that are associated either with pathogen elimination or immune escape mechanisms. Most of such studies were performed in vitro using primary host cells or cell lines. Consequently, the data generated with such approaches reflect the global RNA expression or protein amount recovered from all cells in culture. This is justified when all host cells harbor an equal amount of pathogens under experimental conditions. However, the uptake of pathogens by phagocytic cells is not synchronized. Consequently, there are host cells incorporating different amounts of pathogens that might result in distinct pathogen-induced protein biosynthesis. Therefore, we established a technique able to detect and quantify the number of pathogens in the corresponding host cells using immunofluorescence-based high throughput analysis. Paired with multicolor staining of molecules of interest it is now possible to analyze the infection profile of host cell populations and the corresponding phenotype of the host cells as a result of parasite load.
Lohr J.,University of Heidelberg |
Ratliff T.,University of Heidelberg |
Huppertz A.,University of Heidelberg |
Ge Y.,German Cancer Research Center |
And 11 more authors.
Clinical Cancer Research | Year: 2011
Purpose: In glioma - in contrast to various other cancers - the impact of T-lymphocytes on clinical outcome is not clear. We investigated the clinical relevance and regulation of T-cell infiltration in glioma. Experimental Design: T-cell subpopulations from entire sections of 93 WHO°II-IV gliomas were computationally identified using markers CD3, CD8, and Foxp3; survival analysis was then done on primary glioblastomas (pGBM). Endothelial cells expressing cellular adhesion molecules (CAM) were similarly computationally quantified from the same glioma tissues. Influence of prominent cytokines (as measured by ELISA from 53 WHO°II-IV glioma lysates) on CAM-expression in GBM-isolated endothelial cells was determined using flow cytometry. The functional relevance of the cytokine-mediated CAM regulation was tested in a transmigration assay using GBM-derived endothelial cells and autologous T-cells. Results: Infiltration of all T-cell subsets increased in high-grade tumors. Most strikingly, within pGBM, elevated numbers of intratumoral effector T cells (Teff, cytotoxic and helper) significantly correlated with a better survival; regulatory T cells were infrequently present and not associated with GBM patient outcome. Interestingly, increased infiltration of Teff cells was related to the expression of ICAM-1 on the vessel surface. Transmigration of autologous T cells in vitro was markedly reduced in the presence of CAM-blocking antibodies. We found that TGF-β molecules impeded transmigration and downregulated CAM-expression on GBM-isolated endothelial cells; blocking TGF-β receptor signaling increased transmigration. Conclusions: This study provides comprehensive and novel insights into occurrence and regulation of T-cell infiltration in glioma. Specifically, targeting TGF-β1 and TGF-β2 might improve intratumoral T-cell infiltration and thus enhance effectiveness of immunotherapeutic approaches. ©2011 AACR.
Wohnsland S.,University of Heidelberg |
Burgers H.F.,University of Heidelberg |
Burgers H.F.,TissueGnostics GmbH |
Kuschinsky W.,University of Heidelberg |
Maurer M.H.,University of Heidelberg
Neurochemical Research | Year: 2010
Several questions concerning the survival of isolated neurons and neuronal stem and progenitor cells (NPCs) have not been answered in the past: (1) If lactate is discussed as a major physiological substrate of neurons, do neurons and NPCs survive in a glucose-free lactate environment? (2) If elevated levels of glucose are detrimental to neuronal survival during ischemia, do high concentrations of glucose (up to 40 mmol/L) damage neurons and NPCs? (3) Which is the detrimental factor in oxygen glucose deprivation (OGD), lack of oxygen, lack of glucose, or the combination of both? Therefore, in the present study, we exposed rat cortical neurons and NPCs to different concentrations of d-glucose ranging from 0 to 40 mmol/L, or 10 and 20 mmol/L l-lactate under normoxic and anoxic conditions, as well as in OGD. After 24 h, we measured cellular viability by biochemical assays and automated cytochemical morphometry, pH values, bicarbonate, lactate and glucose concentrations in the cell culture media, and caspases activities. We found that (1) neurons and NPCs survived in a glucose-free lactate environment at least up to 24 h, (2) high glucose concentrations >5 mmol/L had no effect on cell viability, and (3) cell viability was reduced in normoxic glucose deprivation to 50% compared to 10 mmol/L glucose, whereas cell viability in OGD did not differ from that in anoxia with lactate which reduced cell viability to 30%. Total caspases activities were increased in the anoxic glucose groups only. Our data indicate that (1) neurons and NPCs can survive with lactate as exclusive metabolic substrate, (2) the viability of isolated neurons and NPCs is not impaired by high glucose concentrations during normoxia or anoxia, and (3) in OGD, low glucose concentrations, but not low oxygen levels are detrimental for neurons and NPCs. © 2010 Springer Science+Business Media, LLC.
Agency: Cordis | Branch: FP7 | Program: MC-IAPP | Phase: FP7-PEOPLE-2013-IAPP | Award Amount: 3.02M | Year: 2013
Advances in digital pathology are generating huge volumes of whole slide and tissue microarray images which are providing new insights into the causes of some of todays most devastating diseases. They also present tremendous opportunities for developing and evaluating new and more effective treatments that may revolutionize the care of patients with cancers and other diseases. The challenge is to exploit the new and emerging digital pathology technologies effectively in order to process and model all the heterogeneous tissue-derived data. This requires joint research projects and collaborative programmes between academia and industry. Thus, biomedical scientists will be equipped with broad knowledge and tools of modern imaging and data processing as well as analysis technologies, whereas engineers with have an understanding of the complex disease processes and the clinical needs. This will help developing efficient and innovative products to fulfil the needs of digital pathology. The AIDPATH project addresses this challenge through a focused research, including research training aiming to knowledge sharing and career development in this emerging multidisciplinary field. AIDPATH will research and develop: a) state of the art medical image display technology for digital pathology, b) novel image analysis solutions and knowledge discovery tools for future pathology diagnosis and research and c) state of the art solutions for biomarker evaluation and quantification. The first application will be breast cancer, though the applicability of the implemented methods and tools to other major diseases will be analysed.
PubMed | Laboratory for Tumor Immunology, Health Science University, TissueGnostics GmbH, University Institute of Health Sciences and Medical University of Vienna
Type: Journal Article | Journal: PloS one | Year: 2016
Mast cells (MC) are bone marrow derived haematopoetic cells playing a crucial role not only in immune response but also in the tumor microenvironment with protumorigenic and antitumorigenic functions. The role of MC in primary cutaneous T-cell lymphomas (CTCL), a heterogeneous group of non-Hodgkin lymphomas with initial presentation in the skin, is largely unknown.To gain more accurate information about presence, number, distribution and state of activation (degranulated vs. non-degranulated) of MC in CTCL variants and clinical stages.We established a novel computer-aided tissue analysis method on digitized skin sections. Immunohistochemistry with an anti-MC tryptase antibody was performed on 34 biopsies of different CTCL subtypes and on control skin samples. An algorithm for the automatic detection of the epidermis and of cell density based CTCL areas was developed. Cells were stratified as being within the CTCL infiltrate, in P1 (a surrounding area 0-30 m away from CTCL), or in P2 (30-60 m away from CTCL) area.We found high MC counts within CTCL infiltrates and P1 and a decreased MC number in the surrounding dermis P2. Higher MC numbers were found in MF compared to all other CTCL subgroups. Regarding different stages of MF, we found significantly higher mast cell counts in stages IA and IB than in stages IIA and IIB. Regarding MC densities, we found a higher density of MC in MF compared to all other CTCL subgroups. More MC were non-degranulated than degranulated.Here for the first time an automated method for MC analysis on tissue sections and its use in CTCL is described. Eliminating error from investigator bias, the method allows for precise cell identification and counting. Our results provide new insights on MC distribution in CTCL reappraising their role in the pathophysiology of CTCL.
Tissuegnostics Gmbh | Date: 2010-04-23
The invention relates to a method for analyzing cells that are present as closed clusters. According to said method, a planar tissue preparation is subjected to an identification staining of the cell nuclei and a target structure staining of cell objects that is different from the identification staining. Digital images are recorded of the stained tissue preparation by means of an electronic image recording device and at least one image of a subsection of the tissue cut is displayed in at least one coloration. According to the inventive method, at least one parameter of the cell nuclei and at least one parameter of the cell objects labeled by target structure staining is restricted to a predetermined range of values. Cell nuclei and cell objects whose parameters correspond to the respective parameter range(s) are detected and optionally displayed using image processing algorithms in the image of said subsection. The image content of at least one image detected for the cell nuclei is correlated with the image content of at least one image detected for the target-structure stained cell objects to detect the individual cells. On the basis of the cell nuclei identified a cell growth or a cell enlargement is induced using a predetermined arithmetic algorithm to reconstruct the individual cells. In doing so it is made sure that neighboring cells do not fuse. The number of reconstructed individual cells is determined and/or the individual cells are divided into populations according to certain parameters.