In the last 10 years the company has run multiple projects from clients from Europe, US, Canada and Japan; participated in many international collaborative research projects, currently 12 ongoing; more than 60 publications have arisen from our technology. Download our Track Record for further information:
Most relevant peer-reviewed Anaxomics publicationsᐯ
In-silico simulated prototype-patients using TPMS technology to study a potential adverse effect of sacubitril and valsartan
Journal and year: PLOS ONE, 2020 [+]
Unveiling the mechanism of action of a drug is key to understand the benefits and adverse reactions of a medication in an organism. However, in complex diseases such as heart diseases there is not a unique mechanism of action but a wide range of different responses depending on the patient. Exploring this collection of mechanisms is one of the clues for a future personalized medicine. The Therapeutic Performance Mapping System (TPMS) is a Systems Biology approach that generates multiple models of the mechanism of action of a drug. Each molecular mechanism generated could be associated to particular individuals, here defined as prototype-patients, hence the generation of models using TPMS technology may be used for detecting adverse effects to specific patients. TPMS operates by (1) modelling the responses in humans with an accurate description of a protein network and (2) applying a Multilayer Perceptron-like and sampling strategy to find all plausible solutions. In the present study, TPMS is applied to explore the diversity of mechanisms of action of the drug combination sacubitril/valsartan. We use TPMS to generate a wide range of models explaining the relationship between sacubitril/valsartan and heart failure (the indication), as well as evaluating their association with macular degeneration (a potential adverse effect). Among the models generated, we identify a set of mechanisms of action associated to a better response in terms of heart failure treatment, which could also be associated to macular degeneration development. Finally, a set of 30 potential biomarkers are proposed to identify mechanisms (or prototype-patients) more prone of suffering macular degeneration when presenting good heart failure response. All prototype-patients models generated are completely theoretical and therefore they do not necessarily involve clinical effects in real patients. Data and accession to software are available at http://sbi.upf.edu/data/tpms/
Authors: Jorba G, Aguirre-Plans J, Junet V, Segú-Vergés C, Ruiz JL, Pujol A, Fernández-Fuentes N, Mas JM, Oliva B.Download original article
Methods to Develop an in silico Clinical Trial: Computational Head-to-Head Comparison of Lisdexamfetamine and Methylphenidate
Journal and year: Frontiers in Psychiatry, 2021 [+]
Regulatory agencies encourage computer modeling and simulation to reduce the time and cost of clinical trials. Although still not classified in formal guidelines, system biology-based models represent a powerful tool for generating hypotheses with great molecular detail. Herein, we have applied a mechanistic head-to-head in silico clinical trial (ISCT) between two treatments for attention-deficit/hyperactivity disorder, to wit lisdexamfetamine (LDX) and methylphenidate (MPH). The ISCT was generated through three phases comprising (i) the molecular characterization of drugs and pathologies, (ii) the generation of adult and children virtual populations (vPOPs) totaling 2,600 individuals and the creation of physiologically based pharmacokinetic (PBPK) and quantitative systems pharmacology (QSP) models, and (iii) data analysis with artificial intelligence methods. The characteristics of our vPOPs were in close agreement with real reference populations extracted from clinical trials, as did our PBPK models with in vivo parameters. The mechanisms of action of LDX and MPH were obtained from QSP models combining PBPK modeling of dosing schemes and systems biology-based modeling technology, i.e., therapeutic performance mapping system. The step-by-step process described here to undertake a head-to-head ISCT would allow obtaining mechanistic conclusions that could be extrapolated or used for predictions to a certain extent at the clinical level. Altogether, these computational techniques are proven an excellent tool for hypothesis-generation and would help reach a personalized medicine.
Authors: Gutiérrez-Casares, JR., J. Quintero, G. Jorba, V. Junet, V. Martínez, T. Pozo-Rubio, B. Oliva, X. Daura, JM. Mas and C. MontotoDownload original article
Head to head evaluation of second generation ALK inhibitors brigatinib and alectinib as first-line treatment for ALK+ NSCLC using an in silico systems biology-based approach
Journal and year: Oncotarget, 2021 [+]
Around 3–7% of patients with non-small cell lung cancer (NSCLC), which represent 85% of diagnosed lung cancers, have a rearrangement in the ALK gene that produces an abnormal activity of the ALK protein cell signaling pathway. The developed ALK tyrosine kinase inhibitors (TKIs), such as crizotinib, ceritinib, alectinib, brigatinib and lorlatinb present good performance treating ALK+ NSCLC, although all patients invariably develop resistance due to ALK secondary mutations or bypass mechanisms. In the present study, we compare the potential differences between brigatinib and alectinib’s mechanisms of action as first-line treatment for ALK+ NSCLC in a systems biology-based in silico setting. Therapeutic performance mapping system (TPMS) technology was used to characterize the mechanisms of action of brigatinib and alectinib and the impact of potential resistances and drug interferences with concomitant treatments. The analyses indicate that brigatinib and alectinib affect cell growth, apoptosis and immune evasion through ALK inhibition. However, brigatinib seems to achieve a more diverse downstream effect due to a broader cancer-related kinase target spectrum. Brigatinib also shows a robust effect over invasiveness and central nervous system metastasis-related mechanisms, whereas alectinib seems to have a greater impact on the immune evasion mechanism. Based on this in silico head to head study, we conclude that brigatinib shows a predicted efficacy similar to alectinib and could be a good candidate in a first-line setting against ALK+ NSCLC. Future investigation involving clinical studies will be needed to confirm these findings. These in silico systems biology-based models could be applied for exploring other unanswered questions.
Authors: Carcereny C, Fernández-Nistal A, López A, Montoto C, Naves A, Segú-Vergés C, Coma M, Jorba G, Oliva B, Mas JM.Download original article
Application of systems biology-based in silico tools to optimize treatment strategy identification in Still's disease
Journal and year: Arthritis Research & Therapy, 2021 [+]
Background: Systemic juvenile idiopathic arthritis (sJIA) and adult-onset Still’s disease (AOSD) are manifestations ofan autoinflammatory disorder with complex pathophysiology and significant morbidity, together also termed Still’sdisease. The objective of the current study is to set in silico models based on systems biology and investigate theoptimal treat-to-target strategy for Still’s disease as a proof-of-concept of the modeling approach
Methods: Molecular characteristics of Still’s disease and data on biological inhibitors of interleukin (IL)-1 (anakinra,canakinumab), IL-6 (tocilizumab, sarilumab), and glucocorticoids as well as conventional disease-modifying antirheumatic drugs (DMARDs, methotrexate) were used to construct in silico mechanisms of action (MoA) models bymeans of Therapeutic Performance Mapping System (TPMS) technology. TPMS combines artificial neuronal networks, sampling-based methods, and artificial intelligence. Model outcomes were validated with published expression data from sJIA patients.
Results: Biologicals demonstrated more pathophysiology-directed efficiency than non-biological drugs. IL-1 blockade mainly acts on proteins implicated in the innate immune system, while IL-6 signaling blockade has a weaker effect on innate immunity and rather affects adaptive immune mechanisms. The MoA models showed that in the autoinflammatory/systemic phases of Still’s disease, in which the innate immunity plays a pivotal role, the IL1β-neutralizing antibody canakinumab is more efficient than the IL-6 receptor-inhibiting antibody tocilizumab. MoA models reproduced 67% of the information obtained from expression data.
Conclusions: Systems biology-based modeling supported the preferred use of biologics as an immunomodulatory treatment strategy for Still’s disease. Our results reinforce the role for IL-1 blockade on innate immunity regulation, which is critical in systemic autoinflammatory diseases. This further encourages early use on Still’s disease IL-1 blockade to prevent the development of disease or drug-related complications. Further analysis at the clinical level will validate the findings and help determining the timeframe of the window of opportunity for canakinumab treatment.
Keywords: Systems biology, Systemic juvenile idiopathic arthritis, Adult-onset Still’s disease, Treat-to-target, Artificial intelligence, Machine learning, Personalized medicine
Authors: Segú-Vergés C, Coma M, Kessel C, Smeets S, Foell D, Aldea A.
Elucidating the Mechanism of Action of the Attributed Immunomodulatory Role of Eltrombopag in Primary Immune Thrombocytopenia: An In Silico Approach
Journal and year: International Journal of Molecular Sciences, 2021 [+]
Eltrombopag is a thrombopoietin receptor (MPL) agonist approved for the treatment of primary immune thrombocytopenia (ITP). Recent evidence shows that some patients may sustain platelet counts following eltrombopag discontinuation. The systemic immunomodulatory response that resolves ITP in some patients could result from an increase in platelet mass, caused either by the direct action of eltrombopag on megakaryocytes through MPL stimulation, or potential MPL-independent actions on other cell types. To uncover the possible mechanisms of action of eltrombopag, in silico analyses were performed, including a systems biology-based approach, a therapeutic performance mapping system, and structural analyses. Through manual curation of the available bibliography, 56 key proteins were identified and integrated into the ITP interactome analysis. Mathematical models (94.92% mean accuracy) were obtained to elucidate potential MPLdependent pathways in non-megakaryocytic cell subtypes. In addition to the effects on megakaryocytes and platelet numbers, the results were consistent with MPL-mediated effects on other cells, which could involve interferon-gamma, transforming growth factor-beta, peroxisome proliferator-activated receptor-gamma, and forkhead box protein P3 pathways. Structural analyses indicated that effects on three apoptosis-related proteins (BCL2L1, BCL2, BAX) from the Bcl-2 family may be off-target effects of eltrombopag. In conclusion, this study proposes new hypotheses regarding the immunomodulatory functions of eltrombopag in patients with ITP.
Authors: Lozano ML, Segú-Vergés C, Coma M, Álvarez-Roman MT González-Porras JR, Gutiérrez L, Valcárcel D, Butta N.Download original article
Antigen-stimulated PBMC transcriptional protective signatures for malaria immunization
Journal and year: Science Translational Medicine, 2020 [+]
Identifying immune correlates of protection and mechanisms of immunity accelerates and streamlines the development of vaccines. RTS,S/AS01E, the most clinically advanced malaria vaccine, has moderate efficacy in African children. In contrast, immunization with sporozoites under antimalarial chemoprophylaxis (CPS immunization) can provide 100% sterile protection in naïve adults. We used systems biology approaches to identifying correlates of vaccine-induced immunity based on transcriptomes of peripheral blood mononuclear cells from individuals immunized with RTS,S/AS01E or chemoattenuated sporozoites stimulated with parasite antigens in vitro. Specifically, we used samples of individuals from two age cohorts and three African countries participating in an RTS,S/AS01E pediatric phase 3 trial and malaria-naïve individuals participating in a CPS trial. We identified both preimmunization and postimmunization transcriptomic signatures correlating with protection. Signatures were validated in independent children and infants from the RTS,S/AS01E phase 3 trial and individuals from an independent CPS trial with high accuracies (>70%). Transcription modules revealed interferon, NF-κB, Toll-like receptor (TLR), and monocyte-related signatures associated with protection. Preimmunization signatures suggest that priming the immune system before vaccination could potentially improve vaccine immunogenicity and efficacy. Last, signatures of protection could be useful to determine efficacy in clinical trials, accelerating vaccine candidate testing. Nevertheless, signatures should be tested more extensively across multiple cohorts and trials to demonstrate their universal predictive capacity. http://sbi.upf.edu/data/tpms/
Authors: Moncunill G, Scholzen A, Mpina M, Nhabomba A, Hounkpatin AB, Osaba L, Valls R, Campo JJ, Sanz H, Jairoce C, Williams NA, Pasini EM, Arteta D, Maynou J, Palacios L, Duran-Frigola M, Aponte JJ, Kocken CHM, Agnandji ST, Mas JM, Mordmuller B, Daubenberger C, Sauerwein R, Dobaño C.Link to the original article
In-silico drug repurposing study predicts the combination of pirfenidone and melatonin as a promising candidate therapy to reduce SARS-CoV-2 infection progression and respiratory distress caused by cytokine storm
Journal and year: PLOS ONE, 2020 [+]
From January 2020, COVID-19 is spreading around the world producing serious respiratory symptoms in infected patients that in some cases can be complicated by the severe acute respiratory syndrome, sepsis and septic shock, multiorgan failure, including acute kidney injury and cardiac injury. Cost and time efficient approaches to reduce the burthen of the disease are needed. To find potential COVID-19 treatments among the whole arsenal of existing drugs, we combined system biology and artificial intelligence-based approaches. The drug combination of pirfenidone and melatonin has been identified as a candidate treatment that may contribute to reduce the virus infection. Starting from different drug targets the effect of the drugs converges on human proteins with a known role in SARS-CoV-2 infection cycle. Simultaneously, GUILDify v2.0 web server has been used as an alternative method to corroborate the effect of pirfenidone and melatonin against the infection of SARS-CoV-2. We have also predicted a potential therapeutic effect of the drug combination over the respiratory associated pathology, thus tackling at the same time two important issues in COVID-19. These evidences, together with the fact that from a medical point of view both drugs are considered safe and can be combined with the current standard of care treatments for COVID-19 makes this combination very attractive for treating patients at stage II, non-severe symptomatic patients with the presence of virus and those patients who are at risk of developing severe pulmonary complications.
Authors: Artigas L, Coma M, Matos-Filipe P, Aguirre-Plans J, Farrés J, Valls R, Fernandez-Fuentes N, de la Haba-Rodriguez J, Olvera A, Barbera J, Morales R, Oliva B, Mas JM.Download original article
Systems biology drug screening identifies statins as enhancers of current therapies in chronic lymphocytic leukemia
Journal and year: Scientific Reports, 2020 [+]
Chronic lymphocytic leukemia (CLL) is a B lymphoid malignancy highly dependent on the microenvironment. Despite new targeted therapies such as ibrutinib and venetoclax, disease progression and relapse remain an issue. CLL cell interactions with the supportive tissue microenvironment play a critical role in disease pathogenesis. We used a platform for drug discovery based on systems biology and artifcial intelligence, to identify drugs targeting key proteins described to have a role in the microenvironment. The selected compounds were screened in CLL cell lines in the presence of stromal cells to mimic the microenvironment and validated the best candidates in primary CLL cells. Our results showed that the commercial drug simvastatin was the most efective and selective out of the tested compounds. Simvastatin decreased CLL cell survival and proliferation as well as cell adhesion. Importantly, this drug enhanced the antitumor efect of venetoclax and ibrutinib. We proposed that systems biology approaches combined with pharmacological screening could help to fnd new drugs for CLL treatment and to predict new combinations with current therapies. Our results highlight the possibility of repurposing widely used drugs such as statins to target the microenvironment and to improve the efcacy of ibrutinib or venetoclax in CLL cells.
Authors: Gimenez N, Tripathi R, Giró A, Rosich L, López-Guerra M, López-Oreja I, Playa-Albinyana H, Arenas F, Mas JM, Pérez-Galán P, Delgado J, Campo E, Farrés J, Colomer D.
Neuroprotective Drug for Nerve Trauma Revealed Using Artificial Intelligence
Journal and year: Scientific Reports, 2018 [+]
Here we used a systems biology approach and artificial intelligence to identify a neuroprotective agent for the treatment of peripheral nerve root avulsion. Based on accumulated knowledge of the neurodegenerative and neuroprotective processes that occur in motoneurons after root avulsion, we built up protein networks and converted them into mathematical models. Unbiased proteomic data from our preclinical models were used for machine learning algorithms and for restrictions to be imposed on mathematical solutions. Solutions allowed us to identify combinations of repurposed drugs as potential neuroprotective agents and we validated them in our preclinical models. The best one, NeuroHeal, neuroprotected motoneurons, exerted anti-inflammatory properties and promoted functional locomotor recovery. NeuroHeal endorsed the activation of Sirtuin 1, which was essential for its neuroprotective effect. These results support the value of network-centric approaches for drug discovery and demonstrate the efficacy of NeuroHeal as adjuvant treatment with surgical repair for nervous system trauma.
Authors: Romeo-Guitart D, Fores J, Herrando-Grabulosa M, Valls R, Leiva-Rodriguez T, Galea E, Gonzalez-Perez F, Navarro X, Petegnie, V, Bosch A, Coma M, Mas J M, Casas C.Download original article
Most relevant congress participationsᐯ
Exploring the synergistic effects of cabozantinib (cabo) and a programmed cell death protein 1 (PD1) inhibitor in metastatic renal cell carcinoma (mRCC) with artificial intelligence (AI)
Congress and year: Genitourinary Cancers Symposium: American Society of Clinical Oncology, 2021 [+]
Background: Nonclinical and clinical data suggest that cabo with a PD1 inhibitor provides synergistic antitumor activity in patients with mRCC, possibly by a cabo-induced switch to an immunopermissive tumor microenvironment. We used a complementary, unbiased, AI approach to gain a holistic view of the complex interplay between multiple pathways, cells and molecules and identify the mechanisms that may underpin this synergism.
Methods: Biological targets associated with mRCC pathophysiology or drug actions were identified from proteomic, genomic and transcriptomic databases and literature. Using systems- and AI-based technology, the data were integrated using machine learning into mathematical models of the human mRCC protein network topology. The combined effects of cabo and a PD1 inhibitor on biological targets were simulated assuming target receptors were fully activated or fully inhibited. Relevant effects on known cancer processes (e.g. angiogenesis, metastasis, cell proliferation, immune evasion) were identified using artificial neural networks. Biologically plausible synergistic mechanisms were described with sampling methods.
Results: Inhibition of VEGF/VEGFR and GAS6/TAMR axes by cabo enhanced the known effects of PD1 inhibitors on immune evasion mechanisms by modulating multiple humoral and cellular components of the innate and adaptive immune responses. PD1 inhibitors further enhanced the anti-angiogenic and tumor pro-apoptotic effects of cabo by modulating pro- and anti-angiogenic factors and T cell cytotoxicity..
Conclusions: These data provide a mechanistic rationale and further support for the beneficial combination of cabo and a PD1 inhibitor and may guide future nonclinical and clinical research.
Authors: Authors: Costa L, Castellano D, Puente J, Martin L, Anido U, Gómez J, Duran I.Link to the original abstract
Application of systems biology-based in silico tools to optimize treatment strategy in Still's disease
Congress and year: PReS, 2020 [+]
Introduction:Systemic Juvenile Idiopathic Arthritis (sJIA) and Adult Onset Still's Disease (AOSD) are manifestations of an autoinflammatory disorder with complex pathophysiology and significant morbidity, together also termed Still’s disease.
Objectives:To investigate the optimal treat-to-target strategy for Still’s disease by in silico models based on systems biology. Methods:Molecular characteristics of Still’s disease and data on biological inhibitors of interleukin (IL)-1 (anakinra, canakinumab), IL-6 (tocilizumab, sarilumab), glucocorticoids as well as conventional disease-modifying anti-rheumatic drugs (DMARDs, methotrexate) were used to construct in silico mechanisms of action (MoA) models by means of Therapeutic Performance Mapping System technology (TPMS). TPMS combines artificial neuronal networks (ANN), samplingbased methods and artificial intelligence. The models were validated with publicly available expression data from sJIA patients.
Results:Biologicals demonstrated more pathophysiology-directed efficiency than non-biological drugs. IL-1 blockade mainly acts on the innate immune system, while IL-6 signaling blockade has a weaker activity on the innate immunity and rather affects the adaptive immunity. The MoA models showed that the IL-1β inhibitor canakinumab is more efficient than the IL-6 receptor inhibiting antibody tocilizumab in the autoinflammatory/systemic phases of Still’s disease. MoA models reproduced 67% of the information obtained from expression data.
Conclusion:Systems biology-based modelling supported the preferred use of biologics as immunomodulatory treatment strategy for Still’s disease. This further encourages early IL-1β blockade in initial autoinflammatory/systemic phases of Still’s disease to prevent the development of disease or drug-related complications. Further studies are needed to determine the optimal timeframe of the window of opportunity for canakinumab treatment.
Authors: Coma M, Segu-Verges C, Kessel C, Smeets S, Foell D, Aldea A.Download original abstract
Application of systems biology-based in silico tools to optimize treatment strategy in Still's disease
Congress and year: EULAR E-Congress , 2020 [+]
Background: Systemic Juvenile Idiopathic Arthritis (sJIA) and Adult Onset Still’s Disease (AOSD) are manifestations of an autoinflammatory disorder with complex pathophysiology and significant morbidity, together also termed Still’s disease.
Objectives: To investigate the optimal treat-to-target strategy for Still’s disease by in silico models based on systems biology.
Methods: Molecular characteristics of Still’s disease and data on biological inhibitors of interleukin (IL)-1 (anakinra, canakinumab), IL-6 (tocilizumab, sarilumab), glucocorticoids as well as conventional disease-modifying anti-rheumatic drugs (DMARDs, methotrexate) were used to construct in silico mechanisms of action (MoA) models by means of Therapeutic Performance Mapping System technology (TPMS). TPMS combines artificial neuronal networks (ANN), sampling-based methods and artificial intelligence. The models were validated with publicly available expression data from sJIA patients.
Results: Biologicals demonstrated more pathophysiology-directed efficiency than non-biological drugs. IL-1 blockade mainly acts on the innate immune system, while IL-6 signaling blockade has a weaker activity on the innate immunity and rather affects the adaptive immunity. The MoA models showed that the IL-1β inhibitor canakinumab is more efficient than the IL-6 receptor inhibiting antibody tocilizumab in the autoinflammatory/systemic phases of Still’s disease. MoA models reproduced 67% of the information obtained from expression data.
Conclusion: Systems biology-based modelling supported the preferred use of biologics as immunomodulatory treatment strategy for Still’s disease. This further encourages early IL-1β blockade in initial autoinflammatory/systemic phases of Still’s Disease to prevent the development of disease or drug-related complications. Further studies are needed to determine the optimal timeframe of the window of opportunity for canakinumab treatment.
Disclosure of Interests: : None declared
Authors: Coma M, Segu-Verges C, Kessel C, Smeets S, Foell D, Aldea A.Download original abstract
Application of Systems Biology-Based In Silico Tools for Optimal Treatment Strategy Identification in Still’s Disease
Congress and year: ACR/ARP Annual Meeting, 2019 [+]
Background/Purpose: Systemic JIA (sJIA) and Adult Onset Still’s Disease may represent a disease continuum1 of the same autoinflammatory disorder, Still’s Disease. Current challenges in its management include the complex disease clinical phenotypes (systemic/rheumatic symptoms) and the absence of optimal treatment guidelines. Several efforts are being made to identify the best targeted strategy to take advantage of the “window of opportunity” and prevent complications and damage2. Systems biology-based methods are becoming reliable tools to understand the molecular effects of drugs in complex clinical settings. In this study, we constructed in silico models to explore and compare the mode of action (MoA) in Still’s Disease of current biologicals, anakinra (ANA), canakinumab (CAN) and tocilizumab (TCZ), in addition to non-biological drugs such as corticosteroids and methotrexate, aiming to advance towards an optimal treatment approach.
Methods: Therapeutic Performance Mapping System was used to create Still’s Disease pathophysiology and drug MoA models. Drugs’ efficacies were compared using artificial neuronal networks, and detailed MoA of IL-1β and IL-6 blockers was modeled using sampling methods. Available expression data in sJIA patients was used for model validation (GSE80060, GSE21521, GSE8361, GSE7753, GSE76492).
Results: The models reflected human physiology ( >90% accuracy) and Still’s Disease pathophysiology (Figure 1A). Biologicals were found more efficient than non-biologicals (Table 1). IL-1 blockers behaved similarly (CAN as IL-1β-specific blocker was used for further analyses) and presented an innate immune system-centered mechanism, while TCZ acted over the adaptive immune system. A detailed evaluation of the MoA of CAN and TCZ on the innate immune system showed some well-known proteins (Figure 1B) differentially modulated. While CAN inhibits NF-κB, CXCL8 and S100A9 more effectively, CD64 (FCGR1A) is preferentially inhibited by TCZ. The CAN and TCZ MoA models reproduced 67% of the information obtained from expression data (Figure 2).
Conclusion: The created in silico Still’s Disease models reproduce known clinical and molecular findings, which render them a good tool for future patient profiling, biomarker identification and treatment strategy designing. According to the models, the biologicals tested for proof-of-concept purposes provide a more pathophysiology-directed MoA than non-biological drugs, and are similarly effective on both systemic and rheumatic disease features. IL-1 blockers, specifically CAN, might be more efficient than TCZ in initial autoinflammatory/systemic phases of Still’s Disease that is dominated by innate immune dysregulation. Key innate immune mediators are hereby proposed to explain the differences observed between CAN and TCZ MoA. Our systems biology data may thus support the development of therapeutic strategies fostering early intervention with CAN during the window of opportunity to prevent the development of destructive chronic arthritis and treatment- or disease-associated complications long-term.
Authors: Segu-Verges C, Coma M, Kessel C, Smeets S, Foell D, Aldea A.Link to the original abstract
miRNome analyses reveal that activity of CAF expressed podoplanin in the tumour microenvironment is modulated by exosome miRNAs involved in PTEN/PI3K/AKT/mTOR signalling
Congress and year: AACR (American Association for Cancer Research) Annual Meeting, 2017 [+]
Background: In breast cancer, cancer associated fibroblasts (CAF) express podoplanin but little is known about its mechanism of expression and modulation. This might be crucial for cancer cell movements and for the ability to escape from the tumor site. Podoplanin showed anti-adhesive activity towards tumor and immune cells. A key control of tumor microenvironment is exerted by microRNAs on gene expression. Therefore miRNAs profiling was performed with 3D-Gene microarray technology on a breast CAF model, on cell lysates and on secreted exosomes, in hypoxia versus normoxia culture conditions.
Methods: Systems biology enrichment analyses were carried out through bioinformatics using mathematical models that simulate in silico the behaviour of human physiology. Targets linked to the set of differential miRNAs, both up-regulated and down-regulated, have been analyzed with various methods including a hypergeometric distribution method. Processes linked to hypoxia, glycosylation, angiogenesis, extracellular matrix and pathways associated with PI3K-AKT, mTOR, P53 and chemokines signaling were studied.
Results: We showed that podoplanin expression strongly affected miRNAs involved in these processes. Hypoxia increased expression of miR-210, miR-21 and miR-29b in cells over-expressing podoplanin. miR-21 is an oncogenic regulator in most cancer cells through its downstream target proteins among which stands the tumor suppressor PTEN, a candidate to alleviate hypoxia in tumors, regulating tumor angiogenesis and modulating tumor hypoxia. miR-29b is a tumor suppressor, it also correlates with PTEN repression.
Conclusion: We highlighted miRNA regulation of podoplanin expression through downregulation of upstream genes for tumor suppressor PTEN. The combination of miRNome analysis and systems biology bioinformatics uncovered potential miRNAs involved in the regulation of podoplanin activity in CAF. Such data analysis may be applied to protein and mRNA biomarkers and extended to other pathology pathways.
Authors: Tejchman A, Mennesson E, Fixe I, Foucher A, Perera S, Artigas L, Mas JM, Grillon C, Ugorski M, Normand N, Kieda C.Link to the original abstract
Urinary proteome analysis identified neprilysin and VCAM as key proteins in the development of diabetic nephropathy
Congress and year: 26th European Meeting on Hypertension and Cardiovascular Protection - ESH, 2016 [+]
Objective: Diabetic nephropathy (DN) is the major cause of end-stage renal disease. Renin-angiotensin system (RAS) inhibition is the preferred treatment to slow its progression. We have studied the urinary proteomes of patients with DN (high albuminuria) to investigate the pathophysiology of renal disease and identify disease markers and predictors of clinical outcome.
Design and method: We included diabetic men with (n = 9) and without DN (n = 12) (control cohort). Data collection included clinical and laboratory evaluation of blood and urine at baseline (control cohort and DN-basal), and in patients with DN after 3 months of losartan treatment (DN-treated). Urinary proteome was analyzed and quantified by Tandem Mass Tag (TMT) labeling on a LTQ-Orbitrap mass spectrometer.
Results: Patients enrolled in the study showed no differences regarding basic clinical parameters. Urinary proteome analysis have identified 166 differentially excreted proteins when comparing the proteomes of controls and DN patients, 27 comparing DN-treated and DN-basal patients, and 182 among patients DN-treated and controls. Systems biology approach comprising functional proteomic networks and artificial neural networks (TPMS technology) have identified 80 key proteins involved in the pathophysiology of DN and 15 key proteins involved in the efficacy of losartan. There are 7 proteins identified in the urine proteome that are essential in both DN pathophysiology and treatment efficacy. Vascular cell adhesion molecule-1 (VCAM-1) and the angiotensin-metabolizing neutral endopeptidase neprilysin (NEP) stand out from the other identified proteins because they are the only ones that are DN effectors. They are differentially expressed in the urinary proteome and are also key proteins in both DN pathophysiology and RAS inhibition efficacy.
Conclusions: NEP is a membrane-bound zinc-containing metalloproteinase showing great abundance in the brush border of proximal renal tubular cells. NEP is responsible for the processing and catabolism of several vasoactive peptides including angiotensin II and endothelin which may explain its pathogenic role in the development of DN.
Authors: Bardaji B, Guillen-Gómez E, Ferrer S, Brotons C, Knepper M, Carrascal M, Abian J, Mas JM, Calero F, Ballarín J, Fernández-Llama P.Link to the original abstract