Competing endogenous RNAs in human astrocytes: crosstalk and interacting networks in response to lipotoxicity.

Neurodegenerative diseases (NDs) are characterized by a progressive deterioration of neuronal function, leading to motor and cognitive damage in patients. Astrocytes are essential for maintaining brain homeostasis, and their functional impairment is increasingly recognized as central to the etiology of various NDs. Such impairment can be induced by toxic insults with palmitic acid (PA), a common fatty acid, that disrupts autophagy, increases reactive oxygen species, and triggers inflammation. Although the effects of PA on astrocytes have been addressed, most aspects of the dynamics of this fatty acid remain unknown. Additionally, there is still no model that satisfactorily explains how astroglia goes from being neuroprotective to neurotoxic. Current incomplete knowledge needs to be improved by the growing field of non-coding RNAs (ncRNAs), which is proven to be related to NDs, where the complexity of the interactions among these molecules and how they control other RNA expressions need to be addressed. In the present study, we present an extensive competing endogenous RNA (ceRNA) network using transcriptomic data from normal human astrocyte (NHA) cells exposed to PA lipotoxic conditions and experimentally validated data on ncRNA interaction. The obtained network contains 7 lncRNA transcripts, 38 miRNAs, and 239 mRNAs that showed enrichment in ND-related processes, such as fatty acid metabolism and biosynthesis, FoxO and TGF-ß signaling pathways, prion diseases, apoptosis, and immune-related pathways. In addition, the transcriptomic profile was used to propose 22 potential key controllers lncRNA/miRNA/mRNA axes in ND mechanisms. The relevance of five of these axes was corroborated by the miRNA expression data obtained in other studies. MEG3 (ENST00000398461)/hsa-let-7d-5p/ATF6B axis showed importance in Parkinson's and late Alzheimer's diseases, while AC092687.3/hsa-let-7e-5p/[SREBF2, FNIP1, PMAIP1] and SDCBP2-AS1 (ENST00000446423)/hsa-miR-101-3p/MAPK6 axes are probably related to Alzheimer's disease development and pathology. The presented network and axes will help to understand the PA-induced mechanisms in astrocytes, leading to protection or injury in the CNS under lipotoxic conditions as part of the intricated cellular regulation influencing the pathology of different NDs. Furthermore, the five corroborated axes could be considered study targets for new pharmacologic treatments or as possible diagnostic molecules, contributing to improving the quality of life of millions worldwide.

Network pharmacology and topological analysis on tibolone metabolites and their molecular mechanisms in traumatic brain injury.

Traumatic brain injury (TBI) is a pathology of great social impact, affecting millions of people worldwide. Despite the scientific advances to improve the management of TBI in recent years, we still do not have a specific treatment that controls the inflammatory process after mechanical trauma. The discovery and implementation of new treatments is a long and expensive process, making the repurpose of approved drugs for other pathologies a clinical interest. Tibolone is a drug in use for the treatment of symptoms associated with menopause and has been shown to have a broad spectrum of actions by regulating estrogen, androgen and progesterone receptors, whose activation exerts potent anti-inflammatory and antioxidant effects. In the present study, we aimed to investigate the therapeutic potential of the tibolone metabolites 3α-Hydroxytibolone, 3ß-Hydroxytibolone, and Δ4-Tibolone as a possible therapy in TBI using network pharmacology and network topology analysis. Our results demonstrate that the estrogenic component mediated by the α and ß metabolites can regulate synaptic transmission and cell metabolism, while the Δ metabolite may be involved in modulating the post-TBI inflammatory process. We identified several molecular targets, including KDR, ESR2, AR, NR3C1, PPARD, and PPARA, which are known to play critical roles in the pathogenesis of TBI. Tibolone metabolites were predicted to regulate the expression of key genes involved in oxidative stress, inflammation, and apoptosis. Overall, the repurposing of tibolone as a neuroprotective treatment for TBI holds promise for future clinical trials. However, further studies are needed to confirm its efficacy and safety in TBI patients.

Palmitic Acid Upregulates Type I Interferon-Mediated Antiviral Response and Cholesterol Biosynthesis in Human Astrocytes.

Chronic intake of a high-fat diet increases saturated fatty acids in the brain causing the progression of neurodegenerative diseases. Palmitic acid is a free fatty acid abundant in the diet that at high concentrations may penetrate the blood-brain barrier and stimulate the production of pro-inflammatory cytokines, leading to inflammation in astrocytes. The use of the synthetic neurosteroid tibolone in protection against fatty acid toxicity is emerging, but its transcriptional effects on palmitic acid-induced lipotoxicity remain unclear. Herein, we performed a transcriptome profiling of normal human astrocytes to investigate the molecular mechanisms by which palmitic acid causes cellular damage to astrocytes, and whether tibolone could reverse its detrimental effects. Astrocytes undergo a profound transcriptional change at 2 mM palmitic acid, affecting the expression of 739 genes, 366 upregulated and 373 downregulated. However, tibolone at 10 nM does not entirely reverse palmitic acid effects. Additionally, the protein-protein interaction reveals two novel gene clustering modules. The first module involves astrocyte defense responses by upregulation of pathways associated with antiviral innate immunity, and the second is linked to lipid metabolism. Our data suggest that activation of viral response signaling pathways might be so far, the initial molecular mechanism of astrocytes in response to a lipotoxic insult by palmitic acid, triggered particularly upon increased expression levels of IFIT2, IRF1, and XAF1. Therefore, this novel approach using a global gene expression analysis may shed light on the pleiotropic effects of palmitic acid on astrocytes, and provide a basis for future studies addressed to elucidate these responses in neurodegenerative conditions, which is highly valuable for the design of therapeutic strategies.

Characterization and expression of domains of Alphaherpesvirus bovine 1/5 envelope glycoproteins B in Komagataella phaffi.

BACKGROUND: Bovine herpes virus (BoHV 1 and BoHV-5) are the causative agents of infectious bovine rhinotracheitis (IBR). IBR is responsible for important economic losses in the cattle industry. The envelope glycoprotein B (gB) is essential for BoHV infection of cattle's upper respiratory and genital tract. gB is one of the main candidate antigens for a potential recombinant vaccine since it induces a strong and persistent immune response. RESULTS: In this study, gB of BoHV-1 and BoHV-5 was characterized in terms of function, structure, and antigenicity through bioinformatics tools. gB showed conserved sequence and structure, so, both domains named PH Like 1 and 2 domains of each virus were selected for the design of a bivalent vaccine candidate. The immunoinformatic study showed that these two domains have epitopes recognizable by B and T lymphocytes, followed by this, the cDNA domains from BoHV-1/5 gB (Domains-gB) were transformed into the yeast Komagataella phaffii GS115 (previously known as Pichia pastoris). A recombinant protein with molecular weight of about 110 kDa was obtained from the culture media. The vaccine candidate protein (Domains-gB) was recognized by a monoclonal antibody from a commercial ELISA kit used for IBR diagnostic, which may suggest that the epitopes are conserved of the entire infectious virus. CONCLUSION: Overall, it was shown that the recombinant domains of BoHV-1/5 gB have antigenic and immunogenic properties similar to the native gB. This vaccine candidate is promising to be used in future studies to assess its immunogenicity in an animal model.

Control Theory and Systems Biology: Potential Applications in Neurodegeneration and Search for Therapeutic Targets.

Control theory, a well-established discipline in engineering and mathematics, has found novel applications in systems biology. This interdisciplinary approach leverages the principles of feedback control and regulation to gain insights into the complex dynamics of cellular and molecular networks underlying chronic diseases, including neurodegeneration. By modeling and analyzing these intricate systems, control theory provides a framework to understand the pathophysiology and identify potential therapeutic targets. Therefore, this review examines the most widely used control methods in conjunction with genomic-scale metabolic models in the steady state of the multi-omics type. According to our research, this approach involves integrating experimental data, mathematical modeling, and computational analyses to simulate and control complex biological systems. In this review, we find that the most significant application of this methodology is associated with cancer, leaving a lack of knowledge in neurodegenerative models. However, this methodology, mainly associated with the Minimal Dominant Set (MDS), has provided a starting point for identifying therapeutic targets for drug development and personalized treatment strategies, paving the way for more effective therapies.

Modulation of Small RNA Signatures by Astrocytes on Early Neurodegeneration Stages; Implications for Biomarker Discovery.

Diagnosis of neurodegenerative disease (NDD) is complex, therefore simpler, less invasive, more accurate biomarkers are needed. small non-coding RNA (sncRNA) dysregulates in NDDs and sncRNA signatures have been explored for the diagnosis of NDDs, however, the performance of previous biomarkers is still better. Astrocyte dysfunction promotes neurodegeneration and thus derived scnRNA signatures could provide a more precise way to identify of changes related to NDD course and pathogenesis, and it could be useful for the dissection of mechanistic insights operating in NDD. Often sncRNA are transported outside the cell by the action of secreted particles such as extracellular vesicles (EV), which protect sncRNA from degradation. Furthermore, EV associated sncRNA can cross the BBB to be found in easier to obtain peripheral samples, EVs also inherit cell-specific surface markers that can be used for the identification of Astrocyte Derived Extracellular Vesicles (ADEVs) in a peripheral sample. By the study of the sncRNA transported in ADEVs it is possible to identify astrocyte specific sncRNA signatures that could show astrocyte dysfunction in a more simpler manner than previous methods. However, sncRNA signatures in ADEV are not a copy of intracellular transcriptome and methodological aspects such as the yield of sncRNA produced in ADEV or the variable amount of ADEV captured after separation protocols must be considered. Here we review the role as signaling molecules of ADEV derived sncRNA dysregulated in conditions associated with risk of neurodegeneration, providing an explanation of why to choose ADEV for the identification of astrocyte-specific transcriptome. Finally, we discuss possible limitations of this approach and the need to improve the detection limits of sncRNA for the use of ADEV derived sncRNA signatures.

Network pharmacology reveals multitarget mechanism of action of drugs to be repurposed for COVID-19.

The coronavirus disease 2019 pandemic accelerated drug/vaccine development processes, integrating scientists all over the globe to create therapeutic alternatives against this virus. In this work, we have collected information regarding proteins from SARS-CoV-2 and humans and how these proteins interact. We have also collected information from public databases on protein-drug interactions. We represent this data as networks that allow us to gain insights into protein-protein interactions between both organisms. With the collected data, we have obtained statistical metrics of the networks. This data analysis has allowed us to find relevant information on which proteins and drugs are the most relevant from the network pharmacology perspective. This method not only allows us to focus on viral proteins as the main targets for COVID-19 but also reveals that some human proteins could be also important in drug repurposing campaigns. As a result of the analysis of the SARS-CoV-2-human interactome, we have identified some old drugs, such as disulfiram, auranofin, gefitinib, suloctidil, and bromhexine as potential therapies for the treatment of COVID-19 deciphering their potential complex mechanism of action.

MicroRNA: A Linking between Astrocyte Dysfunction, Mild Cognitive Impairment, and Neurodegenerative Diseases.

The importance of miRNAs in cellular processes and their dysregulation has taken significant importance in understanding different pathologies. Due to the constant increase in the prevalence of neurodegenerative diseases (ND) worldwide and their economic impact, mild cognitive impairment (MCI), considered a prodromal phase, is a logical starting point to study this public health problem. Multiple studies have established the importance of miRNAs in MCI, including astrocyte regulation during stressful conditions. Additionally, the protection mechanisms exerted by astrocytes against some damage in the central nervous system (CNS) lead to astrocytic reactivation, in which a differential expression of miRNAs has been shown. Nevertheless, excessive reactivation can cause neurodegeneration, and a clear pattern defining the equilibrium point between a neuroprotective or detrimental astrocytic phenotype is unknown. Therefore, the miRNA expression has gained significant attention to understand the maintenance of brain balance and improve the diagnosis and treatment at earlier stages in the ND. Here, we provide a comprehensive review of the emerging role of miRNAs in cellular processes that contribute to the loss of cognitive function, including lipotoxicity, which can induce chronic inflammation, also considering the fundamental role of astrocytes in brain homeostasis.

New Drug Design Avenues Targeting Alzheimer's Disease by Pharmacoinformatics-Aided Tools.

Neurodegenerative diseases (NDD) have been of great interest to scientists for a long time due to their multifactorial character. Among these pathologies, Alzheimer's disease (AD) is of special relevance, and despite the existence of approved drugs for its treatment, there is still no efficient pharmacological therapy to stop, slow, or repair neurodegeneration. Existing drugs have certain disadvantages, such as lack of efficacy and side effects. Therefore, there is a real need to discover new drugs that can deal with this problem. However, as AD is multifactorial in nature with so many physiological pathways involved, the most effective approach to modulate more than one of them in a relevant manner and without undesirable consequences is through polypharmacology. In this field, there has been significant progress in recent years in terms of pharmacoinformatics tools that allow the discovery of bioactive molecules with polypharmacological profiles without the need to spend a long time and excessive resources on complex experimental designs, making the drug design and development pipeline more efficient. In this review, we present from different perspectives how pharmacoinformatics tools can be useful when drug design programs are designed to tackle complex diseases such as AD, highlighting essential concepts, showing the relevance of artificial intelligence and new trends, as well as different databases and software with their main results, emphasizing the importance of coupling wet and dry approaches in drug design and development processes.

Tibolone Pre-Treatment Ameliorates the Dysregulation of Protein Translation and Transport Generated by Palmitic Acid-Induced Lipotoxicity in Human Astrocytes: A Label-Free MS-Based Proteomics and Network Analysis.

Excessive accumulation and release of fatty acids (FAs) in adipose and non-adipose tissue are characteristic of obesity and are associated with the leading causes of death worldwide. Chronic exposure to high concentrations of FAs such as palmitic acid (pal) is a risk factor for developing different neurodegenerative diseases (NDs) through several mechanisms. In the brain, astrocytic dysregulation plays an essential role in detrimental processes like metabolic inflammatory state, oxidative stress, endoplasmic reticulum stress, and autophagy impairment. Evidence shows that tibolone, a synthetic steroid, induces neuroprotective effects, but its molecular mechanisms upon exposure to pal remain largely unknown. Due to the capacity of identifying changes in the whole data-set of proteins and their interaction allowing a deeper understanding, we used a proteomic approach on normal human astrocytes under supraphysiological levels of pal as a model to induce cytotoxicity, finding changes of expression in proteins related to translation, transport, autophagy, and apoptosis. Additionally, tibolone pre-treatment showed protective effects by restoring those same pal-altered processes and increasing the expression of proteins from cell survival processes. Interestingly, ARF3 and IPO7 were identified as relevant proteins, presenting a high weight in the protein-protein interaction network and significant differences in expression levels. These proteins are related to transport and translation processes, and their expression was restored by tibolone. This work suggests that the damage caused by pal in astrocytes simultaneously involves different mechanisms that the tibolone can partially revert, making tibolone interesting for further research to understand how to modulate these damages.

Identification of HMGCR, PPGARG and prohibitin as potential druggable targets of dihydrotestosterone for treatment against traumatic brain injury using system pharmacology.

BACKGROUND: Traumatic Brain Injury (TBI) has long-term devastating effects for which there is no accurate and effective treatment for inflammation and chronic oxidative stress. As a disease that affects multiple signalling pathways, the search for a drug with a broader spectrum of pharmacological action is of clinical interest. The fact that endocrine disruption (e.g hypogonadism) has been observed in TBI patients suggests that endogenous therapy with testosterone, or its more androgenic derivative, dihydrotestosterone (DHT), may attenuate, at least in part, the TBI-induced inflammation, but the underlying molecular mechanisms by which this occurs are still not completely clear. AIMS AND METHODS: In this study, the main aim was to investigate proteins that may be related to the pathophysiological mechanism of TBI and also be pharmacological targets of DHT in order to explore a possible therapy with this androgen using network pharmacology. RESULTS AND CONCLUSIONS: We identified 2.700 proteins related to TBI and 1.567 that are potentially molecular targets of DHT. Functional enrichment analysis showed that steroid (p-value: 2.1-22), lipid metabolism (p-value: 2.8-21) and apoptotic processes (p-value: 5.2-21) are mainly altered in TBI. Furthermore, being mitochondrion an organelle involved on these molecular processes we next identified that out of 32 mitochondrial-related proteins 3-hydroxy-3-methyl-glutaryl-coenzyme A reductase (HMGCR), peroxisome proliferator activated receptor gamma (PPGARG) and prohibitin are those found highly regulated in the network and potential targets of DHT in TBI. In conclusion, the identification of these cellular nodes may prove to be essential as targets of DHT for therapy against post-TBI inflammation.

Integrated Metabolomics and Lipidomics Reveal High Accumulation of Glycerophospholipids in Human Astrocytes under the Lipotoxic Effect of Palmitic Acid and Tibolone Protection.

Lipotoxicity is a metabolic condition resulting from the accumulation of free fatty acids in non-adipose tissues which involves a series of pathological responses triggered after chronic exposure to high levels of fatty acids, severely detrimental to cellular homeostasis and viability. In brain, lipotoxicity affects both neurons and other cell types, notably astrocytes, leading to neurodegenerative processes, such as Alzheimer (AD) and Parkinson diseases (PD). In this study, we performed for the first time, a whole lipidomic characterization of Normal Human Astrocytes cultures exposed to toxic concentrations of palmitic acid and the protective compound tibolone, to establish and identify the set of potential metabolites that are modulated under these experimental treatments. The study covered 3843 features involved in the exo- and endo-metabolome extracts obtained from astrocytes with the mentioned treatments. Through multivariate statistical analysis such as PCA (principal component analysis), partial least squares (PLS-DA), clustering analysis, and machine learning enrichment analysis, it was possible to determine the specific metabolites that were affected by palmitic acid insult, such as phosphoethanolamines, phosphoserines phosphocholines and glycerophosphocholines, with their respective metabolic pathways impact. Moreover, our results suggest the importance of tibolone in the generation of neuroprotective metabolites by astrocytes and may be relevant to the development of neurodegenerative processes.

Fatty Acids: An Insight into the Pathogenesis of Neurodegenerative Diseases and Therapeutic Potential.

One of the most common lipids in the human body is palmitic acid (PA), a saturated fatty acid with essential functions in brain cells. PA is used by cells as an energy source, besides being a precursor of signaling molecules and protein tilting across the membrane. Although PA plays physiological functions in the brain, its excessive accumulation leads to detrimental effects on brain cells, causing lipotoxicity. This mechanism involves the activation of toll-like receptors (TLR) and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) pathways, with the consequent release of pro-inflammatory cytokines, increased production of reactive oxygen species (ROS), endoplasmic reticulum (ER) stress, and autophagy impairment. Importantly, some of the cellular changes induced by PA lead to an augmented susceptibility to the development of Alzheimer's and Parkinson´s diseases. Considering the complexity of the response to PA and the intrinsic differences of the brain, in this review, we provide an overview of the molecular and cellular effects of PA on different brain cells and their possible relationships with neurodegenerative diseases (NDs). Furthermore, we propose the use of other fatty acids, such as oleic acid or linoleic acid, as potential therapeutic approaches against NDs, as these fatty acids can counteract PA's negative effects on cells.

The Emerging Role of Long Non-Coding RNAs and MicroRNAs in Neurodegenerative Diseases: A Perspective of Machine Learning.

Neurodegenerative diseases (NDs) are characterized by progressive neuronal dysfunction and death of brain cells population. As the early manifestations of NDs are similar, their symptoms are difficult to distinguish, making the timely detection and discrimination of each neurodegenerative disorder a priority. Several investigations have revealed the importance of microRNAs and long non-coding RNAs in neurodevelopment, brain function, maturation, and neuronal activity, as well as its dysregulation involved in many types of neurological diseases. Therefore, the expression pattern of these molecules in the different NDs have gained significant attention to improve the diagnostic and treatment at earlier stages. In this sense, we gather the different microRNAs and long non-coding RNAs that have been reported as dysregulated in each disorder. Since there are a vast number of non-coding RNAs altered in NDs, some sort of synthesis, filtering and organization method should be applied to extract the most relevant information. Hence, machine learning is considered as an important tool for this purpose since it can classify expression profiles of non-coding RNAs between healthy and sick people. Therefore, we deepen in this branch of computer science, its different methods, and its meaningful application in the diagnosis of NDs from the dysregulated non-coding RNAs. In addition, we demonstrate the relevance of machine learning in NDs from the description of different investigations that showed an accuracy between 85% to 95% in the detection of the disease with this tool. All of these denote that artificial intelligence could be an excellent alternative to help the clinical diagnosis and facilitate the identification diseases in early stages based on non-coding RNAs.

Use of a neuron-glia genome-scale metabolic reconstruction to model the metabolic consequences of the Arylsulphatase a deficiency through a systems biology approach.

Metachromatic leukodystrophy (MLD) is a human neurodegenerative disorder characterized by progressive damage on the myelin band in the nervous system. MLD is caused by the impaired function of the lysosomal enzyme Arylsulphatase A (ARSA). The physiopathology mechanisms and the biochemical consequences in the brain of ARSA deficiency are not entirely understood. In recent years, the use of genome-scale metabolic (GEM) models has been explored as a tool for the study of the biochemical alterations in MLD. Previously, we modeled the metabolic consequences of different lysosomal storage diseases using single GEMs. In the case of MLD, using a glia GEM, we previously predicted that the metabolism of glycosphingolipids and neurotransmitters was altered. The results also suggested that mitochondrial metabolism and amino acid transport were the main reactions affected. In this study, we extended the modeling of the metabolic consequences of ARSA deficiency through the integration of neuron and glial cell metabolic models. Cell-specific models were generated from Recon2, and these were used to create a neuron-glial bi-cellular model. We propose a workflow for the integration of this type of model and its subsequent study. The results predicted the impairment pathways involved in the transport of amino acids, lipids metabolism, and catabolism of purines and pyrimidines. The use of this neuron-glial GEM metabolic reconstruction allowed to improve the prediction capacity of the metabolic consequences of ARSA deficiency, which might pave the way for the modeling of the biochemical alterations of other inborn errors of metabolism with central nervous system involvement.

In silico interactions of statins with cell death-inducing DNA fragmentation factor-like effector A (CIDEA).

Statins are the low-density lipoproteins (LDL)-cholesterol-lowering drugs of first choice and are used to prevent the increased risk of cardiovascular and cerebrovascular diseases. Although some of their effects are well known, little is known about their ability to regulate other lipid-related proteins which control apoptotic mechanisms. The aim of this study was to explore whether statins can bind to cell death-inducing DNA fragmentation factor-like effector A (CIDEA), which might be a possible pleiotropic mechanism of action of these drugs on the modulation of apoptosis and lipid metabolism. The structures of statins were subjected to molecular docking and dynamics with the human CIDEA protein to investigate the interaction pattern and identify which residues are important. The docking results indicated that atorvastatin and rosuvastatin showed the best interaction energy (-8.51 and -8.04 kcal/mol, respectively) followed by fluvastatin (-7.39), pitavastatin (-6.5), lovastatin (-6.23), pravastatin (-6.04) and simvastatin (-5.29). Atorvastatin and rosuvastatin were further subjected to molecular dynamics at 50 ns with CIDEA and the results suggested that rosuvastatin-CIDEA complex had lower root-mean square deviation and root-mean square fluctuation when compared with atorvastatin-CIDEA. Since two arginine residues -ARG19 and ARG22-were identified to be common for the interaction with CIDEA, a single-point mutation was induced in these residues to determine whether they are important for binding interaction. Mutation of these two residues seemed to affect mostly the interaction of atorvastatin with CIDEA, suggesting that they are important for the binding and therefore indicate another possible metabolic mechanism of the pleiotropic effects of this statin.

Brain lipidomics as a rising field in neurodegenerative contexts: Perspectives with Machine Learning approaches.

Lipids are essential for cellular functioning considering their role in membrane composition, signaling, and energy metabolism. The brain is the second most abundant organ in terms of lipid concentration and diversity only after adipose tissue. However, in the central system (CNS) lipid dysregulation has been linked to the etiology, progression, and severity of neurodegenerative diseases such as Alzheimers, Parkinson, and Multiple Sclerosis. Advances in the human genome and subsequent sequencing technologies allowed us the study of lipidomics as a promising approach to diagnosis and treatment of neurodegeneration. Lipidomics advances rapidly increased the amount and quality of data allowing the integration with other omic types as well as implementing novel bioinformatic and quantitative tools such as machine learning (ML). Integration of lipidomics data with ML, as a powerful quantitative predictive approach, led to improvements in diagnostic biomarker prediction, clinical data integration, network, and systems approaches for neural behavior, novel etiology markers for inflammation, and neurodegeneration progression and even Mass Spectrometry image analysis. In this sense, by exploiting lipidomics data with ML is possible to improve the identification of new biomarkers or unveil new molecular mechanisms associated with lipid impairment across neurodegeneration. In this review, we present the lipidomic neurobiology state-of-the-art highlighting its potential applications to study neurodegenerative conditions. Also, we present theoretical background, applications, and advances in the integration of lipidomics with ML. This review opens the door to new approaches in this rising field.

A Bioinformatics Study of the Involved Mechanisms in Relapse and Drug Resistance of Tamoxifen-Treated Breast Cancer.

BACKGROUND: Breast cancer is currently among the most common causes of mortality in women. Estrogen and its subsequent signaling pathways play an important role in the occurrence of breast cancer relapse. Tamoxifen is the most common breast cancer treatment option in ER+ patients, which acts as an adjuvant endocrinotherapy with X-ray and surgery. This approach is recommended as the first-line treatment and has increased the survival rate of breast cancer patients and reduced the relapse cases. However, we can observe resistance to tamoxifen and relapse cases in one-third of patients treated with this drug, which has become a major concern. OBJECTIVE: The precise mechanisms of relapse and resistance to tamoxifen have not yet been identified and were explored in this study. METHODS: Microarray profiles of relapse and relapse-free patients were investigated to explain the processes leading to relapse and possibly to tamoxifen resistance. RESULTS: According to the preliminary analysis, 1460 genes showed increased expression while 1132 genes showed decreased expression. According to our default for inclusion (-2LogFC≥ + 2), 36 genes had increased expression (upregulated) while 33 genes had decreased expression (down-regulated). CONCLUSION: It seems that the mechanisms of resistance and relapse are multifactorial, and tumor cells induce relapse and resistance to tamoxifen through cell proliferation, survival, invasion, angiogenesis, extracellular matrix secretion, pump and membrane changes, and immune evasion.