64 research outputs found
Genetic and epigenetic drivers of neuroendocrine tumours (NET).
No full textNeuroendocrine tumours (NET) of the gastrointestinal tract and the lung are a rare and heterogeneous group of tumours. The molecular characterization and the clinical classification of these tumours have been evolving slowly and show differences according to organs of origin. Novel technologies such as next-generation sequencing revealed new molecular aspects of NET over the last years. Notably, whole-exome/genome sequencing (WES/WGS) approaches underlined the very low mutation rate of well-differentiated NET of all organs compared to other malignancies, while the engagement of epigenetic changes in driving NET evolution is emerging. Indeed, mutations in genes encoding for proteins directly involved in chromatin remodelling, such as DAXX and ATRX are a frequent event in NET. Epigenetic changes are reversible and targetable; therefore, an attractive target for treatment. The discovery of the mechanisms underlying the epigenetic changes and the implication on gene and miRNA expression in the different subgroups of NET may represent a crucial change in the diagnosis of this disease, reveal new therapy targets and identify predictive markers. Molecular profiles derived from omics data including DNA mutation, methylation, gene and miRNA expression have already shown promising results in distinguishing clinically and molecularly different subtypes of NET. In this review, we recapitulate the major genetic and epigenetic characteristics of pancreatic, lung and small intestinal NET and the affected pathways. We also discuss potential epigenetic mechanisms leading to NET development
Abstract 3159: Lysosomal membrane permeabilization as potential mediator of resistance in pancreatic neuroendocrine tumors
No full textAbstract
Sunitinib, an anti-angiogenic tyrosine kinase inhibitor, is approved for treatment of pancreatic neuroendocrine tumors (pNETs). However, its efficacy is greatly limited due to resistance. Sunitinib is a lysosomotropic drug, thus accumulates in lysosomes, leading to their destabilization and to lysosomal membrane permeabilization (LMP), which in turn can lead to cell death. Autophagy might be activated for clearance of damaged lysosomes, thus promote survival and act as a mechanism of resistance. We found that the autophagy inhibitor chloroquine increases sunitinib efficacy in pNET cell lines and in a transgenic mouse model of pNETs. Interestingly, chloroquine is a lysosomotropic drug as well and the response towards sunitinib and chloroquine in pNET cell lines correlated with lysosome-associated membrane protein 2 (LAMP2) levels, which influence lysosome stability. We hypothesized that sunitinib and the combination with chloroquine induce LMP in pNETs and that LMP leads to activation of the transcription factor EB (TFEB), master regulator of genes involved in lysosomal biogenesis and autophagy, leading to therapy resistance. We found that LMP increased upon combined treatment of sunitinib and chloroquine compared to single treatment in pNET cell lines. Treatment of pNET cell lines with sunitinib or chloroquine led to activation of TFEB as assessed by nuclear/cytoplasmic fractionation and western blotting. Additionally, sunitinib significantly increased the expression of TFEB target genes, which were further upregulated upon combination with chloroquine. Interestingly, activation of TFEB and upregulation of TFEB target genes was more pronounced in the more resistant pNET cell line with respect to reduced viability and increased apoptosis. Our data indicate that sunitinib and chloroquine activate TFEB in pNET cell lines, leading to autophagy as a survival mechanism. Upon massive LMP or if autophagy is dysfunctional, cell death is induced. Based on our data, we suggest the combination of sunitinib and chloroquine as a treatment option for pNET patients and that TFEB could be an interesting therapeutic target in combination with lysosomotropic drugs.
Citation Format: Tabea Wiedmer, Rasmus M. Frank, Mario P. Tschan, Aurel Perren, Ilaria Marinoni. Lysosomal membrane permeabilization as potential mediator of resistance in pancreatic neuroendocrine tumors [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 3159. doi:10.1158/1538-7445.AM2017-3159</jats:p
3D Primary Cell Culture: A Novel Preclinical Model For Pancreatic Neuroendocrine Tumors (PanNETs)
No full textMolecular mechanisms underlying the development and progression of PanNET are still insufficiently understood. Efficacy of currently approved PanNET therapies is limited. While novel treatment options are being developed, patient stratification permitting more personalized treatment selection in PanNET is yet not feasible since no predictive markers are established. The lack of representative in vitro and in vivo models as well as the rarity and heterogeneity of PanNET are prevailing reasons for this. In this study, we describe an in vitro 3D human primary PanNET culture system as a novel preclinical model for more personalized therapy selection. We present a screening platform allowing multi-center sample collection and drug screening in 3D cultures of human primary PanNET cells. We demonstrate that primary cells isolated from PanNET patients and cultured in vitro form islet-like tumoroids. Islet-like tumoroids retain the neuroendocrine phenotype and are viable for at least two weeks in culture with high success rate (86%). Viability can be monitored continuously allowing for a per-well normalization. In a proof-of-concept study, islet-like tumoroids were screened with three clinically approved therapies for PanNET: Sunitinib, everolimus and temozolomide. Islet-like tumoroids display varying in vitro response profiles to distinct therapeutic regimes. Treatment response of islet-like tumoroids (IC50) differs also between patient samples. We believe that the presented human PanNET screening platform is suitable for personalized drug testing in a larger patient cohort and a broader application will help in identifying novel markers predicting treatment response and in refining PanNET therapy
Autophagy inhibition improves sunitinib efficacy in pancreatic neuroendocrine tumors via a lysosome-dependent mechanism.
No full textIncreasing the efficacy of approved systemic treatments in metastasized pancreatic neuroendocrine tumors (PanNETs) is an unmet medical need. The anti-angiogenic tyrosine kinase inhibitor sunitinib is approved for PanNET treatment. Additionally, sunitinib is a lysosomotropic drug and such drugs can induce lysosomal membrane permeabilization as well as autophagy. We investigated sunitinib-induced autophagy as a possible mechanism of PanNET therapy resistance. Sunitinib accumulated in lysosomes and induced autophagy in PanNET cell lines. Adding the autophagy inhibitor chloroquine reduced cell viability in cell lines and in primary cells isolated from PanNET patients. The same treatment combination reduced tumor burden in the Rip1Tag2 transgenic PanNET mouse model. The combination of sunitinib and chloroquine reduced recovery and induced apoptosis in vitro, whereas single treatments did not. Knockdown of key autophagy proteins in combination with sunitinib showed similar effect as chloroquine. Sunitinib also induced lysosomal membrane permeabilization, which further increased in the presence of chloroquine or knockdown of lysosome-associated membrane protein (LAMP2). Both combinations led to cell death. Our data indicate that chloroquine increases sunitinib efficacy in PanNET treatment via autophagy inhibition and lysosomal membrane permeabilization. We suggest that adding chloroquine to sunitinib treatment will increase efficacy of PanNET treatment and that such patients should be included in respective ongoing clinical trials
Hypo-methylation mediates chromosomal instability in pancreatic NET.
No full textDAXX and or ATRX loss occur in 40% of pancreatic neuro-endocrine tumors (PanNETs). PanNETs negative for DAXX or ATRX show an increased risk of relapse. The tumor-associated pathways activated upon DAXX or ATRX loss and how this event may induce chromosomal instability (CIN) and alternative lengthening telomeres (ALT) are still unknown. Both DAXX and ATRX are involved in DNA methylation regulation. DNA methylation of heterochromatin and of non-coding sequences is extremely important for the maintenance of genomic stability. We analysed the association of DAXX and or ATRX loss and CIN with global DNA methylation in human PanNET samples and the effect of DAXX knock down on methylation and cell proliferation. We assessed LINE1 as well as global DNA methylation in 167 PanNETs and we found that DAXX and or ATRX negative tumors and tumors with CIN were hypo-methylated. DAXX knock-down in PanNET cell lines blocked cells in G1/G0 phase and seemed to increase CIN in QGP-1 cells. However, no direct changes in DNA methylation were observed after DAXX knock down in vitro. In conclusion our data indicate that epigenetic changes are crucial steps in the progression of PanNETs loss and suggest that DNA methylation is the mechanism via which CIN is induced, allowing clonal expansion and selection
Chlorita tamaninii Wagner 1959
No full textChlorita cf. tamaninii Wagner, 1959 (Fig. 4) First record from Switzerland: Ticino, Ludiano, Ronco Pizzotti, vineyard, [46 ° 24 ’ 57.92 ’’ N; 8 ° 58 ’ 11.39 ’’ E, 459 m], 2 ♂♂, 1 ♀, 21.06. 2011, D-vac, leg. & det. Valeria. Trivellone Distribution in Europe:Italy, Switzerland. Remarks:In total 24 species of the genus Chlorita Fieber are known from the Palaeartic region. Four of them: C. subulata (Ribaut, 1933), C. viridula (Fallen, 1806), C. tamaninii Wagner, 1959 and C. paolii (Ossiannilsson, 1939) belong to the Chlorita viridula species group and are closely related. Wagner (1959) published a key to distinguish the above-mentioned species. Up to now, in Switzerland only C. viridula (Ribaut 1933, Cerutti 1939) and C. paolii (Trivellone &Pollini Paltrinieri 2011) were recorded. In 2011, the first author had collected specimens with aedeagus morphological characteristics quite different from C. viridula and C. paolii. According to the key after Wagner (1959), two main subgroups of species were recognized based on the characteristics of the appendages of the aedeagus: appendages without ablunt tooth and convergent in the viridula-subulata subgroup; and appendages with ablunt tooth and divergent in the paolii-tamaninii subgroup. The appendages of the examined specimens do neither coincide perfectly with the first, nor with the second subgroup. The following description of aspecimen is proposed as reference to further collections. Determination:The genital plate with parameres and the appendices of the anal tube are illustrated in Figs 4 A and 4 B, respectively; they are similar to C. viridula after Le Quesne &Payne (1981). In the male, aedeagus with apair of recurved appendages, longer than main stem, without tooth along outer margin; but hardly S-shaped in the middle (Fig. 4C) and ending in sharp-hooked apices (Fig. 4D).Published as part of Valeria Trivellone, Eva Knop, Tabea Turrini, Line Andrey, Jean-Yves Humbert & Gernot Kunz, 2015, New and remarkable leafhoppers and planthoppers (Hemiptera: Auchenorrhyncha) from Switzerland, pp. 273-284 in Mitteilungen Der Schweizerischen Entomologischen Gesellschaft 88 on page 278, DOI: 10.5281/zenodo.3399
TabeaSonnenschein/GenSynthPop: R-package for Generating Representative Spatially Explicit Synthetic Populations
No full textInstructions for R-package: GenSynthPop Author: Tabea Sonnenschein, Utrecht University
This package contains a set of functions that help prepare stratified census datasets to generate conditional propensities, combines the conditional propensities with spatial marginal distributions to generate a representative population and validates that the produced agents have a similar distribution as the initial spatial marginal datasets and the stratified datasets. The generated population is representative for a city or the spatial extent that is fed into the algorithms and can be used for simulation purposes, such as an agent-based model. The smaller the spatial units of the spatial marginal distributions, the more spatially resolved the agents will be too.
Overview of functions For Data Preparation
crosstabular_to_singleside_df: Crosstabular Stratified Table to Single Sided Variable Combination - Counts Table
restructure_one_var_marginal: Restructures a single-sided stratified dataframe so that the classes of one column/variable of interest are seperate columns
varclass_harmonization: Harmonize the classes of a variable across datasets
aggreg_stratdata_in_harmonclasses: Aggregating a stratified dataset into the newly added harmonised classes
add_spatial_units_to_agent_df: Add a new spatial unit to the agent dataframe based on a unit map
For Initiating the Agent Dataframe
gen_agent_df: Generating an agent dataframe of the population size and assigning a unique ID
distr_agent_neigh_age_group: Populating the agent_df with age_group and neigh_ID attributes distributed like a given neighborhood marginal distribution
For Conditional Propensity calculation
calc_propens_agents: Calculating the conditional propensity to have an attribute based on conditional variables
strat_prop_from_sep_cond_var: Creates a stratified propensity table from separate conditional variable joint distributions
For Attribute Assignment based on conditional and marginal distributions
distr_attr_strat_neigh_stats_binary: Distributing attributes across agent population based on conditional proabilities and neighborhood totals for binary attributes
distr_attr_strat_neigh_stats_3plus: Distributing attributes across agent population based on conditional proabilities and neighborhood totals for attributes with 3 or more classes
distr_attr_cond_prop: Assigning Attributes purely based on conditional probabilities
For Validation
crossvalid: Cross validation with the neighborhood and stratified marginal distributions
Installing package in R
install.packages("devtools")
library(devtools)
install_github("TabeaSonnenschein/GenSynthPop")
library(GenSynthPop)
Looking up documentation for a function There is extensive documentation for the functions within R
Example:
?crosstabular_to_singleside_df
help(crosstabular_to_singleside_df)
Should there be remaining questions, shoot me an email: [email protected]
Instructions
Start by collecting neighborhood marginal distributions of age_groups. It is recommended to go as spatially resolved as you can (smallest spatial unit) but it depends on what you want to use the synthetic agent population for. You theoretically can even use provincial or national administrative areas, if this is your project scope and goal. We go for neighborhoods because we want to create an urban ABM.
apply gen_agent_df for the sum of all age groups in all neighborhoods. This will be the population size.
use this new agent_df and the neighborhood marginal distribution dataframe in the distr_agent_neigh_age_group code to distribute the agents across neighborhoods and age groups.
Read the stratified dataframe with the conditional variable and the variable of interest (that you want to add), for example sex by agegroup, since we already added that one. Make sure that the classes of the conditional variables correspond to the ones in the agent_df. For that you can use varclass_harmonization. If the stratified dataset has been assigned larger harmosed classes, the marginal distributions have to be aggregated, for which you can use: aggreg_stratdata_in_harmonclasses. If instead of the stratified dataset, the agent_df was assigned larger harmonised classes, then no aggregation is necessary, because the new harmonised attribute can be used for calculating the propensities in step 5. Additionally to restructure and prepare the data so that it can be read by calc_propens_agents, you can use the data preparation functions: crosstabular_to_singleside_df and restructure_one_var_marginal
Use calc_propens_agents to generate propensities to have the attribute of interest based on the co-variance with the conditional variable that is already in the agent_df (e.g. the likelihood to be female based on the agegroup). This function takes the stratified dataframe, generates the propensities for the conditional variables and adds the given propensity for each agent to the agent_df. If you have a non-binary variable (3 or more classes) then calculate the propensities for every class of the variable (e.g. "low education", "middle education", "high education").
Depending on if your variable is binary or not, use distr_attr_strat_neigh_stats_binary or distr_attr_strat_neigh_stats_3plus by reading the neighborhood marginal distributions for the variable of interest, and the propensities calculated in step 5 to distribute the attribute of interest across the agent population accordingly.
Use crossvalid to validate that the generated distribution corresponds to the neighborhood and stratified distributions.
Repeat steps 4,5,6,7 for any new variable that you want to add to the agent dataframe. The more attributes are added, the more conditional variables can be use (e.g. using age, sex, migrationbackground, household size, as conditional variables for being "employed" or not). However, as many might assume the availability of census and stratified data has its limit :), but that depends on the geographic location and the year of interest.
you can look at the Example_Application_GenSynthPop.R script for an example application of the functions in the package
Longitudinal Data Collection in Continental Europe: Experiences from the Survey of Health, Ageing and Retirement in (SHARE)
No full textKetogenic diet does not promote triple-negative and luminal mammary tumor growth and metastasis in experimental mice
No full textVol.:(0123456789)1 3Clinical & Experimental Metastasis
https://doi.org/10.1007/s10585-023-10249-z
RESEARCH PAPER
Ketogenic diet does not promote triple-negative and luminal
mammary tumor growth and metastasis in experimental mice
Meret Grube1 · Arno Dimmler2 · Anja Schmaus1 · Rafael Saup1 · Tabea Wagner 1 · Boyan K. Garvalov 1 ·
Jonathan P. Sleeman1,3 · Wilko Thiele 1
Received: 17 October 2023 / Accepted: 21 November 2023
© The Author(s) 2023
Abstract
Ketogenic diets (KDs) can improve the well-being and quality of life of breast cancer patients. However, data on the effects
of KDs on mammary tumors are inconclusive, and the influence of KDs on metastasis in general remains to be investigated.
We therefore assessed the impact of a KD on growth and metastasis of triple negative murine 4T1 mammary tumors, and
on the progression of luminal breast tumors in an autochthonous MMTV-PyMT mouse model. We found that KD did not
influence the metastasis of 4T1 and MMTV-PyMT mammary tumors, but impaired 4T1 tumor cell proliferation in vivo, and
also temporarily reduced 4T1 primary tumor growth. Notably, the ketogenic ratio (the mass of dietary fat in relation to the
mass of dietary carbohydrates and protein) that is needed to induce robust ketosis was twice as high in mice as compared to
humans. Surprisingly, only female but not male mice responded to KD with a sustained increase in blood β-hydroxybutyrate
levels. Together, our data show that ketosis does not foster primary tumor growth and metastasis, suggesting that KDs can
be safely applied in the context of luminal breast cancer, and may even be advantageous for patients with triple negative
tumors. Furthermore, our data indicate that when performing experiments with KDs in mice, the ketogenic ratio needed to
induce ketosis must be verified, and the sex of the mice should also be taken into account
Engineering-Dienstleistungen in der Automobilindustrie: Verbreitung, Kooperationsformen und arbeitspolitische Konsequenzen
No full text"This contribution deals with the notion of wage labour in a fundamental perspective. Both the current theoretical debate as well as new empirical findings about the development of wage labour are summed up. The starting point of the reasoning is a short outline of the different forms as well as of the historical development of wage labour, which initially mainly was industrial work. The contribution then enters into the question how the fundamental coordination problems of work - the transformation and opportunism problem - are managed in the context of a power asymmetrical employment relation between labour and capital. And, how the achievement motivation of the employees can be secured under these circumstances. The thesis is proposed that the interaction of the company level - with its decision, negotiation and organisation processes - with the given labour market structures is of special significance for the regulation of the relations between wage labour and capital and the design of employment relations. To analyse these interrelationships, the author resort to newer concepts of 'company employment systems' for one thing and to considerations from the 'segmentation theory approach' to labour market research for another thing. In conclusion, the increased flexibility of hitherto standardised forms of regulating the employment relations and the decreasing importance of so-called normal employment relationships are identified as specific characteristics of new development trends of wage labour." (author's abstract
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