Role of mitochondria and cardiolipins in growth inhibition of breast cancer cells by retinoic acid

Role of mitochondria and cardiolipins in growth inhibition of breast cancer cells by retinoic acid

October 2019

Terao M, Goracci L, Celestini V, Kurosaki M, Bolis M, Di Veroli A, Vallerga, A, Fratelli M, Lupi M, Corbelli A, Fiordaliso F, Gianni M, Paroni G, Zanetti A, Cruciani G, Garattini E.

Abstract

Background

All-trans-retinoic-acid (ATRA) is a promising agent in the prevention/treatment of breast-cancer. There is growing evidence that reprogramming of cellular lipid metabolism contributes to malignant transformation and progression. Lipid metabolism is implicated in cell differentiation and metastatic colonization, and it is involved in the mechanisms of sensitivity/resistance to different anti-tumor agents. The role played by lipids in the anti-tumor activity of ATRA has never been studied. 

Methods

We used 16 breast cancer cell-lines whose degree of sensitivity to the anti-proliferative action of ATRA is known. We implemented a non-oriented mass-spectrometry based approach to define the lipidomic profiles of each cell-line grown under basal conditions and following treatment with ATRA. To complement the lipidomic data, untreated and retinoid treated cell-lines were also subjected to RNA-sequencing to define the perturbations afforded by ATRA on the whole-genome gene-expression profiles. The number and functional activity of mitochondria were determined in selected ATRA-sensitive and -resistant cell-lines. Bio-computing approaches were used to analyze the high-throughput lipidomic and transcriptomic data. 

Results

ATRA perturbs the homeostasis of numerous lipids and the most relevant effects are observed on cardiolipins, which are located in the mitochondrial inner membranes and play a role in oxidative phosphorylation. ATRA reduces the amounts of cardiolipins, and the effect is associated with the growth-inhibitory activity of the retinoid. Down-regulation of cardiolipins is due to a reduction of mitochondria, which is caused by an ATRA-dependent decrease in the expression of nuclear genes encoding mitochondrial proteins. This demonstrates that ATRA anti-tumor activity is due to a decrease in the amounts of mitochondria causing deficits in the respiration/energy-balance of breast-cancer cells. 

Conclusions

The observation that ATRA anti-proliferative activity is caused by a reduction in the respiration and energy balance of the tumor cells has important ramifications for the therapeutic action of ATRA in breast cancer. The study may open the way to the development of rational therapeutic combinations based on the use of ATRA and anti-tumor agents targeting the mitochondria. 

 

Software-aided workflow for predicting protease-specific cleavage sites using physicochemical properties of the natural and unnatural amino acids in peptide-based drug discovery

Software-aided workflow for predicting protease-specific cleavage sites using physicochemical properties of the natural and unnatural amino acids in peptide-based drug discovery

January 2019.

Radchenko T; Fontaine F; Morettoni L; Zamora I

Abstract

Peptide drugs have been used in the treatment of multiple pathologies. During peptide discovery, it is crucially important to be able to map the potential sites of cleavages of the proteases. This knowledge is used to later chemically modify the peptide drug to adapt it for the therapeutic use, making peptide stable against individual proteases or in complex medias. In some other cases it needed to make it specifically unstable for some proteases, as peptides could be used as a system to target delivery drugs on specific tissues or cells. The information about proteases, their sites of cleavages and substrates are widely spread across publications and collected in databases such as MEROPS.

Therefore, it is possible to develop models to improve the understanding of the potential peptide drug proteolysis. We propose a new workflow to derive protease specificity rules and predict the potential scissile bonds in peptides for individual proteases. WebMetabase stores the information from experimental or external sources in a chemically aware database where each peptide and site of cleavage is represented as a sequence of structural blocks connected by amide bonds and characterized by its physicochemical properties described by Volsurf descriptors. Thus, this methodology could be applied in the case of non-standard amino acid. A frequency analysis can be performed in WebMetabase to discover the most frequent cleavage sites.

These results were used to train several models using logistic regression, support vector machine and ensemble tree classifiers to map cleavage sites for several human proteases from four different families (serine, cysteine, aspartic and matrix metalloproteases). Finally, we compared the predictive performance of the developed models with other available public tools PROSPERous and SitePrediction. 

High resolution Mass Spectrometry with automated data analysis to support structural elucidation of degradation impurities of small peptides

High resolution Mass Spectrometry with automated data analysis to support structural elucidation of degradation impurities of small peptides

AAPS 2019 PHARMSCI 360, San Antonio (United States of America)… 03 November, 2019 

Abstract

Structural elucidation of drug substance related impurities in drug products to identify specific degradation pathways is important for the development of formulated drugs, optimization of manufacturing process and in certain cases a requirement for regulatory submissions. The present work utilized an in-silico data processing tool MassChemSite, which has been developed to automate data analysis and to facilitate the structural elucidation of drug degradants by LC-MS/MS. The software was customized to work on structure modifications introduced by common degradation chemistries for small peptides. 

WebMetabase: cleavage sites analysis tool for natural and unnatural substrates from diverse data source

WebMetabase: cleavage sites analysis tool for natural and unnatural substrates from diverse data source

February 2019.

Radchenko T; Fontaine F; Morettoni L; Zamora I

Abstract

More than 150 peptide therapeutics are globally in clinical development. Many enzymatic barriers should be crossed by a successful drug to be prosperous in such a process. Therefore, the new peptide drugs must be designed preventing the potential protease cleavage to make the compound less susceptible to protease reaction. We present a new data analysis tool developed in WebMetabase, an approach that stores the information from liquid chromatography mass spectrometry-based experimental data or from external sources such as the MEROPS database. The tool is a chemically aware system where each peptide substrate is presented as a sequence of structural blocks (SBs) connected by amide bonds and not being limited to the natural amino acids. Each SB is characterized by its pharmacophoric and physicochemical properties including a similarity score that describes likelihood between a SB and each one of the other SBs in the database. This methodology can be used to perform a frequency analysis to discover the most frequent cleavage sites for similar amide bonds, defined based on the similarity of the SB that participate in such a bond within the experimentally derived and/or public database. 

Lipidomics-Based Approach to Evaluating the Risk of Clinical Hepatotoxicity Potential of Drugs in 3D Human Microtissues

Lipidomics-Based Approach to Evaluating the Risk of Clinical Hepatotoxicity Potential of Drugs in 3D Human Microtissues

January 2021

Goracci L, Valeri A, Sciabola S, Aleo MD, Moritz W, Lichtenberg J, Cruciani, G. A Novel

Abstract

The importance of adsorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis is expected to grow substantially due to recent failures in detecting severe toxicity issues of new chemical entities during preclinical/clinical development. 

Traditionally, safety risk assessment studies for humans have been conducted in animals during advanced preclinical or clinical phase of drug development. However, potential drug toxicity in humans now needs to be detected in the drug discovery process as soon as possible without reliance on animal studies. The “omics”, such as genomics, proteomics, and metabolomics, have recently entered pharmaceutical research in both drug discovery and drug development, but to the best of our knowledge, no applications in high-throughput safety risk assessment have been attempted so far. This paper reports an innovative method to anticipate adverse drug effects in an early discovery phase based on lipid fingerprints using human three-dimensional microtissues. The risk of clinical hepatotoxicity potential was evaluated for a data set of 22 drugs belonging to five different therapeutic chemical classes and with various drug-induced liver injury effect. The treatment of microtissues with repeated doses of each drug allowed collecting lipid fingerprints for five time points (2, 4, 7, 9, and 11 days), and multivariate statistical analysis was applied to search for correlations with the hepatotoxic effect. The method allowed clustering of the drugs based on their hepatotoxic effect, and the observed lipid impairments for a number of drugs was confirmed by literature sources. Compared to traditional screening methods, here multiple interconnected variables (lipids) are measured simultaneously, providing a snapshot of the cellular status from the lipid perspective at a molecular level. Applied here to hepatotoxicity, the proposed workflow can be applied to several tissues, being tridimensional microtissues from various origins.