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Alpha-gal Syndrome

Asta Literature Retrieval: Pathophysiology and clinical mechanisms of Alpha-gal Syndrome. Core disease mechanisms, molecular and cellular pathwa...

2026-07-05
Asta MONDO:0100001 Model: Asta Scientific Corpus Retrieval 20 citations

Asta Literature Retrieval: Pathophysiology and clinical mechanisms of Alpha-gal Syndrome. Core disease mechanisms, molecular and cellular pathwa...

This report is retrieval-only and is generated directly from Asta results.

  • Papers retrieved: 20
  • Snippets retrieved: 20

Relevant Papers

[1] New therapeutic targets in rare genetic skeletal diseases

  • Authors: M. Briggs, Peter A. Bell, M. Wright, K. A. Pirog
  • Year: 2015
  • Venue: Expert Opinion on Orphan Drugs
  • URL: https://www.semanticscholar.org/paper/1363107f71ae6d2d60abca471cddf3da5d13644b
  • DOI: 10.1517/21678707.2015.1083853
  • PMID: 26635999
  • PMCID: 4643203
  • Citations: 39
  • Influential citations: 1
  • Summary: An overview of disease mechanisms that are shared amongst groups of different GSDs and potential therapeutic approaches that are under investigation are described to generate critical mass for the identification and validation of novel therapeutic targets and biomarkers.
  • Evidence snippets:
  • Snippet 1 (score: 0.393) > However, emerging knowledge suggests that the primary genetic defect may be less important than the cells' response to the expression of the mutant gene product [107]. Moreover, the largely overlooked response of a cell (i.e. chondrocyte) to the abnormal extracellular environment is also important for disease progression as illustrated by several GSDs discussed in this review. > It is important that 'omics'-based approaches and technologies are systematically applied to the study of rare GSDs so that definitive reference profiles and disease signatures are generated for each phenotype. These can then be used in a Systems Biology approach to identify both common and dissimilar pathological signatures and disease mechanisms. This approach is entirely dependent upon relevant in vitro and in vivo models (and also novel 'disease-mechanism phenocopies' [107]) for testing new diagnostic and prognostic tools and for determining the molecular mechanisms that underpin the pathophysiology so that effective therapeutic treatments can be developed and validated. This approach will eventually lead to personalized treatments and care strategies centred on shared disease mechanisms with the use of relevant biomarkers to monitor the efficacy of treatment and disease progression. > It is vital that all relevant stakeholders are involved from the outset in defining the appropriate outcomes of any potential therapeutic regime. The perceptions of a successful therapy can differ widely between the clinical academic community and the relevant patient-support groups and it is vital that there is engagement on all these issues. > In summary, the identification of causative genes and mutations for GSDs over the last 20 years, coupled with the generation and in-depth analysis of a plethora of relevant cell and mouse models, has derived new knowledge on disease mechanisms and suggested potential therapeutic targets. The fast-evolving hypothesis that clinically disparate diseases can share common disease mechanisms is a powerful concept that will generate critical mass for the identification and validation of novel therapeutic targets and biomarkers.

[2] Fabry Disease Screening in Patients with Idiopathic HCM or LVH: Data from the Multicentric Nationwide F-CHECK Study

  • Authors: R. Machado, I. Fortuna, S. Sousa, C. Costa, J. Calvão et al.
  • Year: 2025
  • Venue: Biomedicines
  • URL: https://www.semanticscholar.org/paper/dff83a780adcd863d456d11f144be49614816e4c
  • DOI: 10.3390/biomedicines13102530
  • PMID: 41153811
  • PMCID: 12561516
  • Summary: The observed 3.4% prevalence of Fabry disease highlights the importance of systematic FD screening among Portuguese patients with unexplained cardiomyopathy, extending beyond classic hypertrophic presentations to dilated forms.
  • Evidence snippets:
  • Snippet 1 (score: 0.386) > Fabry disease (FD) is a rare X-linked lysosomal storage disease (LSD) caused by mutations in the GLA gene, which encodes the enzyme alpha-galactosidase A (α-Gal A). The deficiency or absence of α-Gal A leads to the intracellular accumulation of globotriaosylceramide and related glycosphingolipids within lysosomes across various cell types and organ systems, including the kidneys, heart, and nervous systems [1]. The accumulation triggers a complex cascade of pathophysiological processes, such as cellular hypertrophy, fibrosis, and inflammation, that ultimately cause progressive organ damage, life-threatening complications, and increased risk of premature death [2,3]. > Clinically, FD is categorised into two major phenotypes: classic and later-onset. The classic phenotype is characterised by severely reduced (<3% of normal values) or absent α-Gal A activity and typically presents in early childhood with signs and symptoms such as cornea verticillata, acroparesthesias, and angiokeratomas [1,2]. Over time, patients often develop progressive multi-organ involvement, including chronic kidney disease with proteinuria, leading to end-stage renal failure, hypertrophic cardiomyopathy (HCM), sensorineural hearing loss, and cerebrovascular events. In contrast, the later-onset phenotype occurs in individuals with residual enzyme activity and usually lacks early symptoms. Clinical manifestations are often milder, delayed, or confined to a single organ, most commonly the heart, where significant pathology such as left ventricular hypertrophy (LVH) may emerge later in life [1]. > Cardiac involvement is the primary determinant of morbidity and mortality in FD [3,4]. Multiple cardiac cell types may be affected, resulting in various cardiac phenotypes and clinical presentations. While concentric HCM is the most frequent cardiac manifestation, other variants such as asymmetric LVH, apical HCM, or even systolic left ventricular (LV) dysfunction may occur.

[3] Targeting Hepatic Stellate Cells for the Prevention and Treatment of Liver Cirrhosis and Hepatocellular Carcinoma: Strategies and Clinical Translation

  • Authors: Hao Xiong, Jinsheng Guo
  • Year: 2025
  • Venue: Pharmaceuticals
  • URL: https://www.semanticscholar.org/paper/76e92127053136900f7e3f10e2c9278251ced5d2
  • DOI: 10.3390/ph18040507
  • PMID: 40283943
  • PMCID: 12030350
  • Citations: 15
  • Summary: HSC-targeted approaches using specific surface markers and receptors may enable the selective delivery of drugs, oligonucleotides, and therapeutic peptides that exert optimized anti-fibrotic and anti-HCC effects.
  • Evidence snippets:
  • Snippet 1 (score: 0.384) > Significant progress has been made in elucidating the cellular and molecular mechanisms of liver fibrosis; however, only a few findings have been successfully translated into clinical applications. Firstly, the high cost of drug development and target validation necessitates prolonged timelines and substantial financial investment. Secondly, as regulatory requirements become more stringent, there is an increasing demand for drugs with well-defined clinical efficacy and safety profiles. Moreover, the efficacy observed in animal models often fails to fully translate to clinical settings due to differences in pharmacokinetics, extracellular matrix (ECM) cross-linking, and disease pathophysiology. Despite advancements in anti-fibrotic drug development, accurately identifying ideal noninvasive biomarkers for fibrotic activity and establishing consensus on optimal clinical endpoints remain significant challenges [113,114]. > Currently, addressing the underlying cause remains the only proven strategy to halt or reverse liver fibrosis progression, while the development of effective anti-fibrotic therapies continues to pose a major challenge in liver disease management. Over the past few decades, substantial progress has been made in elucidating the cellular and molecular mechanisms underlying liver fibrosis. Liver fibrosis is a complex pathological change involving multiple cells, factors, and pathways, and the study of the cellular and molecular mechanisms of its occurrence and development provides an important theoretical basis and therapeutic target for clinical drug development. It is anticipated that improved animal models and well-designed clinical trials will facilitate the successful translation of anti-fibrotic research into effective clinical treatments in the near future.

[4] Rare Monogenic Diseases: Molecular Pathophysiology and Novel Therapies

  • Authors: I. Condò
  • Year: 2022
  • Venue: International Journal of Molecular Sciences
  • URL: https://www.semanticscholar.org/paper/6aece75e6947f102b657851b74e8b96df5e654c1
  • DOI: 10.3390/ijms23126525
  • PMID: 35742964
  • PMCID: 9223693
  • Citations: 19
  • Influential citations: 2
  • Summary: A rare disease is defined by its low prevalence in the general population and its presence in a very small number of people.
  • Evidence snippets:
  • Snippet 1 (score: 0.384) > The selective expression or the particular role of specific genes in a single tissue explains the appearance of organ-specific inherited diseases. This is the case of genetic disorders of the kidney, which include dominant and recessive forms of cystic diseases, and renal tubulopathies. Mutations in polycystin-1 (PKD1) or -2 (PKD2) genes lead to autosomaldominant polycystic kidney disease (ADPKD), whose gender-dependent phenotype was analyzed in the study by Talbi et al. [9]. These results, obtained in mice lacking PKD1 expression, show the involvement of intracellular Ca2+ levels in the more severe phenotype affecting male ADPKD animals. Altogether, identification of the molecular mechanisms underlying enhanced Ca2+ signaling and proliferation in cells from male kidneys may contribute to develop novel therapeutics for ADPKD [9]. The autosomal-recessive form of polycystic kidney disease (ARPKD) mostly arises from defects in the gene named polycystic kidney and hepatic disease 1 (PKHD1), whereas a minority of cases is linked to a second causative gene DZIP1L. To examine the still unclear molecular pathophysiology of ARPKD, Cordido et al. recapitulate known molecular disease mechanisms and possible therapeutic approaches, from cellular and animal models to clinical trials [10]. The knowledge of ARPKD pathogenic pathways, involving the epidermal growth factor receptor (EGFR) axis, the production of adenylyl cyclase adenosine 3 ,5 -cyclic monophosphate (cAMP) and the activation of several protein kinases, begins to stimulate possible pharmacological interventions [10]. Inherited loss of function in various electrolyte transport proteins located along the nephron leads to two types of kidney tubulopathy with overlapping clinical symptoms: Gitelman and Bartter syndromes. The review by Nuñez-Gonzalez et al. aims to explain the different molecular basis of these difficult to diagnose monogenic syndromes. Moreover, the authors provide an overview of current therapeutic approaches and highlight the presence of common and specific options for Gitelman and Bartter patients [11].

[5] Changes in Serum Proteomic Profiles at Different Stages of Pregnancy Toxemia in Goats

  • Authors: M. Uzti̇mür, C. N. Ünal, Gurler Akpinar
  • Year: 2025
  • Venue: Journal of Veterinary Internal Medicine
  • URL: https://www.semanticscholar.org/paper/4b9c488b5dbd65d7b26fd2ad9aed70e8c4b59942
  • DOI: 10.1111/jvim.70139
  • PMID: 40492724
  • PMCID: 12150350
  • Citations: 2
  • Summary: Understanding the serum proteome profiles of goats with pregnancy toxemia might help identify the proteomes and pathways responsible for the development of this disease and improve diagnosis and treatment.
  • Evidence snippets:
  • Snippet 1 (score: 0.380) > The pathophysiology and progression of this disease are not fully understood. > Traditional biomedical research has focused on the analysis of single genes, proteins, metabolites, or metabolic pathways in diseases. This molecular reductionist approach is based on the assumption that identifying genetic variations and molecular components will lead to new treatments for diseases [13][14][15][16]. However, many diseases are complex and multifactorial, and in order to determine the phenotype of such diseases, it is necessary to understand the changes that occur in more than one gene, pathway, protein, or metabolite at the cellular, tissue, and organismal levels [17][18][19]. Therefore, in recent years, proteomics, as one field of multi-omics technologies, has helped in evaluating the complex pathogenetic mechanisms of different diseases from a broad perspective and has made substantial contributions [20,21]. In veterinary medicine, proteomic analysis of metabolic diseases such as ketosis [16], hypocalcemia [22], and fatty liver [23] in dairy cows has contributed valuable insights for the definition of new pathophysiological pathways and new diagnosis and treatment protocols for these diseases. The proteomic approach can contribute importantly to a broad and detailed understanding of the changes that occur at the organismal level associated with the increase in BHBA concentration in goats with pregnancy toxemia. Our aim was to evaluate the serum protein profiles of goats with SPT or CPT using proteomic techniques to determine the proteomic profiles of these animals and to identify the relevant pathophysiological mechanisms.

[6] Human Dermal Fibroblast: A Promising Cellular Model to Study Biological Mechanisms of Major Depression and Antidepressant Drug Response

  • Authors: P. Mesdom, R. Colle, É. Lebigot, S. Trabado, Eric Deflesselle et al.
  • Year: 2020
  • Venue: Current Neuropharmacology
  • URL: https://www.semanticscholar.org/paper/79368e365458486de96794333613c12a6063bf54
  • DOI: 10.2174/1570159X17666191021141057
  • PMID: 31631822
  • PMCID: 7327943
  • Citations: 15
  • Summary: This review highlights the great and still underused potential of HDF, which stands out as a very promising tool in the understanding of MDD and AD mechanisms of action.
  • Evidence snippets:
  • Snippet 1 (score: 0.378) > Background: Human dermal fibroblasts (HDF) can be used as a cellular model relatively easily and without genetic engineering. Therefore, HDF represent an interesting tool to study several human diseases including psychiatric disorders. Despite major depressive disorder (MDD) being the second cause of disability in the world, the efficacy of antidepressant drug (AD) treatment is not sufficient and the underlying mechanisms of MDD and the mechanisms of action of AD are poorly understood. Objective The aim of this review is to highlight the potential of HDF in the study of cellular mechanisms involved in MDD pathophysiology and in the action of AD response. Methods The first part is a systematic review following PRISMA guidelines on the use of HDF in MDD research. The second part reports the mechanisms and molecules both present in HDF and relevant regarding MDD pathophysiology and AD mechanisms of action. Results HDFs from MDD patients have been investigated in a relatively small number of works and most of them focused on the adrenergic pathway and metabolism-related gene expression as compared to HDF from healthy controls. The second part listed an important number of papers demonstrating the presence of many molecular processes in HDF, involved in MDD and AD mechanisms of action. Conclusion The imbalance in the number of papers between the two parts highlights the great and still underused potential of HDF, which stands out as a very promising tool in our understanding of MDD and AD mechanisms of action

[7] Exploring the molecular mechanisms of subarachnoid hemorrhage and potential therapeutic targets: insights from bioinformatics and drug prediction

  • Authors: Yi Liu, Yang Zhang, Huan Wei, Li Wang, Lishang Liao
  • Year: 2025
  • Venue: Scientific Reports
  • URL: https://www.semanticscholar.org/paper/19a91d9c8cabec6a5a186729d545077e252ecb67
  • DOI: 10.1038/s41598-025-97642-8
  • PMID: 40229542
  • PMCID: 11997208
  • Citations: 1
  • Summary: The findings not only elucidate the molecular mechanisms underlying SAH but also provide robust bioinformatics and experimental evidence supporting IRN as a promising therapeutic candidate, offering novel insights for future intervention strategies in SAH.
  • Evidence snippets:
  • Snippet 1 (score: 0.371) > involved in SAH pathology. As a result, our understanding of the cellular composition and microenvironment in SAH remains incomplete 8 . > Advances in bioinformatics provide powerful tools to analyze large-scale gene expression data and understand complex biological processes. By integrating transcriptomic data with immune cell infiltration analysis, we can gain a deeper understanding of the molecular mechanisms underlying SAH and identify potential key genes as therapeutic targets 9,10 . Previous studies have indicated that inflammation, oxidative stress, and cell death play crucial roles in the development of SAH, processes that are often closely associated with changes in specific cell types and immune responses 11 . > The goal of this study is to explore the molecular mechanisms of SAH, with a focus on immune cell infiltration and its role in disease progression. We aim to identify key genes and signaling pathways associated with SAH and investigate potential therapeutic strategies. Specifically, we will examine Isorhynchophylline (IRN) as a potential treatment for SAH and analyze its effects on relevant targets and signaling pathways. Through a comprehensive understanding of the pathological features of SAH, this study aims to provide valuable insights into future clinical interventions and treatment strategies.

[8] 18O-assisted dynamic metabolomics for individualized diagnostics and treatment of human diseases

  • Authors: E. Nemutlu, Song Zhang, N. Juranic, A. Terzic, S. Macura et al.
  • Year: 2012
  • Venue: Croatian Medical Journal
  • URL: https://www.semanticscholar.org/paper/880f053c7f060db4b990e447d0a22c4b69372ddb
  • DOI: 10.3325/cmj.2012.53.529
  • PMID: 23275318
  • PMCID: 3541579
  • Citations: 30
  • Summary: The potential use of dynamic phosphometabolomic platform for disease diagnostics currently under development at Mayo Clinic is described and discussed briefly.
  • Evidence snippets:
  • Snippet 1 (score: 0.370) > Living cells represent an integrated and interacting network of genes, transcripts, proteins, small signaling molecules, and metabolites that define cellular phenotype and function. Traditionally the focus of biomedical research was on individual genes, single protein targets, single metabolites, and metabolic or signaling pathways. This "molecular reductionist" paradigm was based on the assumption that identifying genetic variations and molecular components would lead to discovery of cures for human diseases. However, most of diseases are complex and multi-factorial and the disease phenotype is determined by the alterations of multiple genes, pathways, proteins and metabolites (at cellular, tissue, and organismal levels). Therefore, an integrated "omics" approach is more viable direction for uncovering alterations in metabolic networks, disease mechanisms, and mechanisms of drug effects. > Recent advent of large-scale metabolomics and fluxomic (metabolite dynamics and metabolic flux analysis) completed the "omics revolution" (Figure 1), where genomics, transcriptomics, proteomics, metabolomics, and fluxomics all together complement phenotype determination of living organism. Such integrated "omics" cascades provide a framework for advances in system and network biology, integrative physiology, and system medicine as well as system pharmacology and regenerative medicine. Noteworthy is the "reverse omic" approach or "metabolomicsinformed pharmacogenomics, " where discovery of specific metabolite changes have led to discovery of genetic alterations (2). Therefore, bringing new "omics" technologies to clinical practice will improve disease diagnostics and treatment by targeting drugs and procedures for each unique transcriptomic and metabolomic profiles.

[9] Solving the Evidence Interpretability Crisis in Health Technology Assessment: A Role for Mechanistic Models?

  • Authors: E. Courcelles, J. Boissel, J. Massol, I. Klingmann, R. Kahoul et al.
  • Year: 2022
  • Venue: Frontiers in Medical Technology
  • URL: https://www.semanticscholar.org/paper/877d5b1b75599745f704a9c8371f74601ff17e2f
  • DOI: 10.3389/fmedt.2022.810315
  • PMID: 35281671
  • PMCID: 8907708
  • Citations: 6
  • Summary: Light is shed on different stakeholder's contributions and needs in the appraisal phase and how mechanistic modeling strategies and reporting can contribute to this effort to implement mechanistic models central in the evidence generation, synthesis, and appraisal of HTA so that the totality of mechanistic and clinical evidence can be leveraged by all relevant stakeholders.
  • Evidence snippets:
  • Snippet 1 (score: 0.368) > Example use of MIDD relevant to address uncertainty potentially also during HTA What is the optimal dosage in the clinical context? Physiologically based pharmacokinetic models can investigate dosing-regimens relevant for regulatory review and product labels (9) and can also mimic real-life adherence to prescribed treatment regimens (see also below) or pharmacology-relevant characteristics of special populations as well as drug-drug interactions. > What is the duration of the effectiveness, especially with chronic use of a treatment? Mechanistic models can predict the long-term disease progression by extrapolation of shorter-term findings under the constraints of how the components of the system function (and these constraints convey biological plausibility by design). An example is the use of a mechanism-based disease progression model for comparison of long-term effects of pioglitazone, metformin, and gliclazide on disease processes underlying Type 2 Diabetes Mellitus (10). Another example is prediction of long-term outcomes by short-term marker data as demonstrated by a semi-mechanistic approach in context of osteoporosis treatment (11). > What is the efficacy for relevant clinical outcomes? Mechanistic models combined with pharmacometric approaches can translate findings for one outcome to a range of other outcomes. An example of survival modeling on the back of a mechanistic description is the modeling framework for CD19-Specific CAR-T cell immunotherapy using a quantitative systems pharmacology model (12). > What is the size of the clinical effect dependent on patient characteristics and extrinsic factors? Data-driven modeling techniques can capture correlation within clinical data. Describing the clinical effect of a drug can also be based on mechanistic considerations. Such models either (a) link disease phenotypes to increasingly granular mathematical representations of pathophysiologic processes (top-down approach) or (b) derive functional, computable cellular networks from the molecular building blocks of genes and proteins to elucidate the impact of pathologic or therapeutic alterations on network operating states and hence clinical phenotype (bottom-up) [see (13)].

[10] Molecular insights into the premature aging disease progeria

  • Authors: Sandra Vidak, R. Foisner
  • Year: 2016
  • Venue: Histochemistry and Cell Biology
  • URL: https://www.semanticscholar.org/paper/60fb3b46bb7e42d5d08cc3b7cbc783b118300c31
  • DOI: 10.1007/s00418-016-1411-1
  • PMID: 26847180
  • PMCID: 4796323
  • Citations: 107
  • Influential citations: 4
  • Summary: Changes in mechanosignaling, altered chromatin organization and impaired genome stability, and changes in signaling pathways, leading to impaired regulation of adult stem cells, defective extracellular matrix production and premature cell senescence are discussed.
  • Evidence snippets:
  • Snippet 1 (score: 0.367) > The number of molecular biological studies aiming at the identification of lamin-mediated molecular disease mechanisms involved in HGPS increased tremendously following the surprising discovery that LMNA is causally linked to the premature aging disease HGPS in 2003. Despite numerous cellular pathways that were identified to be affected by the expression of the mutant lamin A protein (Fig. 2), the mechanistic details behind these effects are still unclear in most cases. Knowledge based on what was already known on lamin biology before the protein was linked to HGPS and findings on novel roles of lamins in diverse pathways in recent years allowed the launch of translational studies and the efficient search for drug targets and therapeutic approaches within a short time period. The results of the first clinical trials taught us that some improvements of the disease phenotypes can be achieved by FTI treatment, but they also made clear that we need a much better understanding of the underlying disease mechanisms to be able to tackle specific aspects of the disease in a more focused approach. It will also be important to elucidate which of the numerous pathways found to be impaired in HGPS are most relevant for and causally involved in the pathologies, and which ones are just bystanders.

[11] Molecular Genetics of Bartter Syndrome: Bridging Genotype–Phenotype Correlations and Precision Therapeutics

  • Authors: Lina Zhu, Yang Li, Yiyao Bao
  • Year: 2026
  • Venue: Current Issues in Molecular Biology
  • URL: https://www.semanticscholar.org/paper/a5e1ddccfa7d333834c4d32be123c71bfd573f83
  • DOI: 10.3390/cimb48040422
  • PMID: 42042082
  • PMCID: 13114623
  • Summary: A comprehensive framework to provide a comprehensive framework to facilitate precise diagnosis and individualized treatment strategies, ultimately advancing precision medicine in the management of Bartter syndrome is provided.
  • Evidence snippets:
  • Snippet 1 (score: 0.364) > Molecular genetic research on Bartter syndrome has made remarkable strides, elucidating the principal BS genes SLC12A1, KCNJ1, CLCNKB, BSND, and MAGED2 and their corresponding protein defects, thereby refining the molecular framework of disease classification while separating CaSR-associated Bartter-like disease from the core canonical BS spectrum. This progress has significantly deepened our understanding of the underlying pathophysiology and provided an essential framework for correlating genotypes with clinical phenotypes. However, the intricate relationship between genetic mutations and clinical manifestations remains complex and multifaceted, reflecting the profound heterogeneity of the syndrome. Addressing these diagnostic challenges and refining disease classification beyond traditional clinical criteria requires an integrative approach that seamlessly balances high-throughput sequencing technologies with rigorous functional studies. > The mechanisms by which these genetic mutations lead to protein dysfunction are diverse, encompassing critical defects in protein expression, impaired membrane localization, and direct functional impairments. Notably, aberrant protein folding, endoplasmic reticulum-associated degradation (ERAD), and splicing abnormalities have emerged as critical pathogenic pathways. These mechanistic insights not only enhance our fundamental understanding of the disease but also highlight highly promising therapeutic targets. While current treatments remain predominantly symptomatic, focusing primarily on managing electrolyte imbalances and associated complications, they inherently fail to address the underlying molecular defects driving the disease. > The precise identification of specific molecular defects opens innovative avenues for the development of targeted interventions aimed at correcting or compensating for specific protein abnormalities. For instance, molecular chaperones that assist in protein folding, agents that modulate aberrant splicing, and future gene-based strategies represent important experimental directions for mechanism-based therapy. Consequently, the future of Bartter syndrome management may increasingly move toward precision medicine tailored to the molecular pathology of individual patients. However, the transition from concept to clinical implementation will require substantial additional functional, translational, and trial-level evidence. Such mechanism-based strategies promise not only to alleviate clinical symptoms but to fundamentally modify disease progression, thereby drastically improving long-term prognosis and quality of life for patients.

[12] Nasopharyngeal Carcinoma Signaling Pathway: An Update on Molecular Biomarkers

  • Authors: W. Tulalamba, T. Janvilisri
  • Year: 2012
  • Venue: International Journal of Cell Biology
  • URL: https://www.semanticscholar.org/paper/307cb9186444d9dad6e2e3b53763be0de76de186
  • DOI: 10.1155/2012/594681
  • PMID: 22500174
  • PMCID: 3303613
  • Citations: 96
  • Influential citations: 5
  • Summary: The molecular signaling pathways in the NPC are discussed for the holistic view of NPC development and progression and the important insights toward NPC pathogenesis may offer strategies for identification of novel biomarkers for diagnosis and prognosis.
  • Evidence snippets:
  • Snippet 1 (score: 0.363) > In the pregenomic eras, highly integrated and complex circuitry of molecular signaling in NPC pathogenesis was only partially understood. Over the past decade, the knowledge of the molecular mechanisms in NPC carcinogenesis has been rapidly accumulated. Dysregulation and abnormal protein expression of molecules in certain signaling pathways involved in cellular functions including proliferation, adhesion, survival, and apoptosis has been demonstrated in the NPC cells. Detailed information on the complex network in signaling pathway leading to a coordinated pattern of gene expression and regulation in NPC will undoubtedly provide important clues to develop novel prognostic and therapeutic strategies for this cancer. Refining molecular markers into clinically relevant assays may assist in the detection of NPC in asymptomatic patients, as well as stage classification and monitoring disease progression and treatments. Furthermore, selective regulation of particular proteins targeting cancer cell proliferation, invasion, and apoptosis is a hopeful prospect for future anticancer therapy that slow disease progression and improve survival.

[13] Transcriptional profiling of Hutchinson-Gilford progeria patients identifies primary target pathways of progerin

  • Authors: Sandra Vidak, Sohyoung Kim, Tom Misteli
  • Year: 2026
  • Venue: Nucleus
  • URL: https://www.semanticscholar.org/paper/4bd99b0875508364d8672b6da5a50d024d485a53
  • DOI: 10.1080/19491034.2025.2611484
  • PMID: 41489464
  • PMCID: 12773485
  • Summary: To probe the clinical relevance of previously implicated cellular pathways and to address the extent of gene expression heterogeneity between patients, transcriptomic analysis of a comprehensive set of HGPS patients finds misexpression of several cellular pathways, including multiple signaling pathways, the UPR and mesodermal cell fate specification.
  • Evidence snippets:
  • Snippet 1 (score: 0.362) > Oxidative stress represents another key pathogenic mechanism in HGPS, as impaired NRF2 activity or increased reactive oxygen species (ROS) levels are sufficient to recapitulate HGPSassociated phenotypes [17,32,60]. Collectively, these findings underscore the multifactorial nature of HGPS pathogenesis, implicating interconnected signaling cascades involved in inflammation, oxidative stress, proteostasis, and vascular remodeling. Reassuringly, our findings indicate that many of the major pathways that have been described to contribute to HGPS phenotypes in mouse and cellular disease models are also misregulated in progeria patients, and targeting these pathways may provide therapeutic avenues to mitigate disease severity and improve outcomes in HGPS. > Although individuals with HGPS typically exhibit a characteristic set of clinical features, such as craniofacial abnormalities, growth retardation, and cardiovascular complications, there is notable variability in the age of onset, severity, and progression of symptoms between patients [7,9]. At the cellular level, HGPS is associated with several hallmark abnormalities, including nuclear envelope defects, decreased expression of several nuclear proteins and epigenetic marks, mitochondrial dysfunction, and increased cellular senescence [1,11,30,31,61]. These cellular phenotypes also exhibit considerable variation between patients, possibly contributing to differences in clinical outcomes. Our results indicate that even though some degree of transcriptional heterogeneity between the individual patients exists, the majority of patients exhibit misregulation of a set of shared pathways, suggesting that these pathways are universal driver mechanisms in HGPS. Further work is needed to understand the molecular and genetic factors that underlie inter-individual variability in disease expression and progression. > A limitation of pathway analysis of HGPS patient samples is to distinguish the pathways which are directly targeted by the disease-causing progerin protein and the emergence of adaptive secondary response pathways during progression of the disease in patients during their lifetime. The same caveat applies to the use of cell-based models used in the study of HGPS disease mechanisms.

[14] Integrating multi-omics and machine learning strategies to explore the “gene-protein-metabolite” network in ischemic heart failure with Qi deficiency and blood stasis syndrome

  • Authors: Jingjing Wei, Aolong Wang, Peng Yu, Yang Sun, Wenjun Wu et al.
  • Year: 2025
  • Venue: Chinese Medicine
  • URL: https://www.semanticscholar.org/paper/8694948133c11b52a604b21e8d2cdeef641b2819
  • DOI: 10.1186/s13020-025-01151-9
  • PMID: 40671145
  • PMCID: 12269143
  • Citations: 4
  • Summary: This study provides a comprehensive characterization of the molecular features of QXXY syndrome in IHF patients, highlighting key pathways and biomarkers linked to energy metabolism dysregulation, chronic inflammation, and coagulation abnormalities.
  • Evidence snippets:
  • Snippet 1 (score: 0.360) > Recent advancements in multi-omics technologies, including transcriptomics, proteomics, and metabolomics, have revolutionized the exploration of molecular mechanisms underlying complex diseases. By integrating these approaches, it is possible to construct comprehensive "gene-protein-metabolite" networks that capture the intricate interactions driving disease progression [7]. These networks can unveil key biomarkers and pathways associated with specific disease phenotypes, offering novel insights into disease mechanisms and potential therapeutic targets. In recent years, the integration of multi-omics methodologies and computational biology has garnered significant attention for elucidating the mechanisms of TCM syndromes. For instance, Jie Wang et al. employed an integrated strategy combining RNA-seq, data-independent acquisition (DIA) proteomics, and untargeted metabolomics to analyze 90 clinical samples of coronary heart disease, constructing a "geneprotein-metabolite" network for coronary heart disease with phlegm and blood stasis syndrome [8]. Similarly, Weidong Zhang et al. utilized a combined approach of proteomics, metabolomics, and network pharmacology to systematically investigate the biological basis of two TCM syndromes in coronary heart disease: Cold Congealing and Qi Stagnation (CCQS) and Qi Stagnation and Blood Stasis (QSBS) [9]. Despite these advancements, significant challenges persist in understanding QXXY syndrome in IHF, including reliance on singleomics approaches, limited depth of studies, inability to cross-validate findings, and insufficient validation of conclusions. Collectively, a multi-omics approach holds immense potential to elucidate the molecular signatures of QXXY syndrome, thereby bridging the gap between TCM theory and modern biomedical science. > In this study, we employed an integrated multi-omics strategy combined with computational biology to investigate the biological basis of QXXY syndrome in IHF patients. We enrolled 100 participants, comprising 40 IHF patients with QXXY syndrome (IHF-QXXY), 40 IHF patients without QXXY syndrome (IHF-NQXXY), and 20 healthy controls (HC).

[15] Mechanistic Models of Signaling Pathways Reveal the Drug Action Mechanisms behind Gender-Specific Gene Expression for Cancer Treatments

  • Authors: C. Çubuk, F. Can, M. Peña-Chilet, J. Dopazo
  • Year: 2020
  • Venue: Cells
  • URL: https://www.semanticscholar.org/paper/e40f7a3b8f72ba01374ba00fbf308a47a3fa5dd4
  • DOI: 10.3390/cells9071579
  • PMID: 32610626
  • PMCID: 7408716
  • Citations: 9
  • Summary: Despite the existence of differences in gene expression across numerous genes between males and females having been known for a long time, these have been mostly ignored in many studies, including drug development and its therapeutic use. In fact, the consequences of such differences over the disease mechanisms or the drug action mechanisms are completely unknown. Here we applied mechanistic mathematical models of signaling activity to reveal the ultimate functional consequences that gender-s...
  • Evidence snippets:
  • Snippet 1 (score: 0.357) > Therefore, a proper interpretation of the effect that differences in gene expression have over phenotypes, such as drug response or disease progression, involves understanding the mechanisms of the disease or the mode of action of drugs, which can be interpreted through mechanistic models of cell signaling [12] or cell metabolism [13]. Mechanistic models have helped to understand the disease mechanisms behind different cancers [14,15], including neuroblastoma [16,17], breast cancer [18], rare diseases [19], complex diseases [20], the mechanisms of action of drugs [21,22], and other biologically interesting scenarios such as the molecular mechanisms that explain how stress-induced activation of brown adipose tissue prevents obesity [23] or the molecular mechanisms of death and the post-mortem ischemia of a tissue [24]. Among the few available proposals of mechanistic modeling algorithms that model different aspects of signaling pathway activity, Hipathia has demonstrated having superior sensitivity and specificity [12]. > Here, we propose the use of mechanistic models [13,14] of signaling activity related with cancer hallmarks [25], other cancer-related signaling pathways, and some extra relevant cellular functions to understand the functional consequences of the gender bias in gene expression. Such mechanistic models use gene expression data to produce an estimation of profiles of signaling or metabolic circuit activity within pathways [13,14]. An interesting property of mechanistic models is that they can be used not only to understand molecular mechanisms of disease or of drug action but also to predict the potential consequences of gene perturbations over the circuit activity in a given condition [26]. Actually, in a recent work, our group has successfully predicted therapeutic targets in cancer cell lines with a precision over 60% [15]. Therefore, we will use this mechanistic framework to understand what is the molecular basis of the different effects of cancer drugs by directly simulating their effect in the patients. This approach has recently been used by us to understand the generation of resistances in cancer at the single cell level in glioblastoma [27].

[16] Clinical Phenotypes of Cardiovascular and Heart Failure Diseases Can Be Reversed? The Holistic Principle of Systems Biology in Multifaceted Heart Diseases

  • Authors: K. Lourida, G. Louridas
  • Year: 2022
  • Venue: Cardiogenetics
  • URL: https://www.semanticscholar.org/paper/3960806730c4c1115f527e22d6d0a76536570ec5
  • DOI: 10.3390/cardiogenetics12020015
  • Citations: 4
  • Influential citations: 1
  • Summary: Only by understanding the complexity of chronic heart diseases and explaining the interrelationship between different interconnected biological networks can the probability for clinical phenotypes reversal be increased.
  • Evidence snippets:
  • Snippet 1 (score: 0.356) > Treatment with ACEIs, ARBs, and β-blockers impedes deterioration of myocardial function as well as clinical deterioration caused by the deleterious impact of the compensatory systems [58,59]. Therefore, the therapy with ACEIs, ARBs, and β-blockers is the appropriate therapy to block LV remodeling and HF progression and reduce symptoms and/or mortality [55]. > In general, the HF syndrome demonstrates a modular construction with predictable behavior of functional clinical phenotypes having a strong impact on biological networks from epigenetic, cellular to regulatory systems [18]. The importance of individual genes for the pathogenesis and clinical progression of the HF syndrome is restricted to the hypertrophic and dilated cardiomyopathies. It seems that some HF patients have a complex multigenic inheritance, but the importance of individual genes is limited. In contrast, the significant role of epigenetics, proteomics, and metabolomics is increased; but, the complete genetic network system and the interactions between multiomics systems are still uncertain [60]. Multimodal systems that include genetic networks, multiomics, metabolic pathways, environmental factors, and sophisticated disease-related clinical networks are required to be integrated and provide a new holistic and realistic picture. > Significant breakthroughs have been made to understand many of the pathophysiological mechanisms of HFrEF but the natural pathophysiological history and clinical progression of HFpEF still remains inadequately defined [39]. The subclinical progression of pre-clinical diastolic dysfunction (PDD) of LV "to clinical phenotype of HFpEF and the further clinical progression to some more complex clinical models with multi-organ involvement . . . continue to be poorly understood" [40]. Prospective studies are expected to clarify the natural history and clinical progression of HFpEF and define the LV remodeling mechanisms involved. The pathophysiology of LV systolic dysfunction is different to the diastolic dysfunction, as systolic dysfunction is considered a disease of calcium handling and diastolic dysfunction is regarded as a disease of increased myofilament sensitivity to calcium [61][62][63].

[17] The Potential of iPSCs for the Treatment of Premature Aging Disorders

  • Authors: C. Compagnucci, E. Bertini
  • Year: 2017
  • Venue: International Journal of Molecular Sciences
  • URL: https://www.semanticscholar.org/paper/581917de0fd4d572ad6df509124da8c3de3e0c3c
  • DOI: 10.3390/ijms18112350
  • PMID: 29112121
  • PMCID: 5713319
  • Citations: 12
  • Influential citations: 2
  • Summary: Modeling premature aging with induced pluripotent stem cells (iPSCs) offers the possibility to study these disorders during self-renewal and differentiation into relevant cell types, and allows researchers to understand pathophysiological mechanisms and enables the performance of drug screenings.
  • Evidence snippets:
  • Snippet 1 (score: 0.355) > Premature aging disorders including Hutchinson-Gilford progeria syndrome (HGPS) and Werner syndrome, are a group of rare monogenic diseases leading to reduced lifespan of the patients. Importantly, these disorders mimic several features of physiological aging. Despite the interest on the study of these diseases, the underlying biological mechanisms remain unknown and no treatment is available. Recent studies on HGPS (due to mutations of the LMNA gene encoding for the nucleoskeletal proteins lamin A/C) have reported disruptions in cellular and molecular mechanisms modulating genomic stability and stem cell populations, thus giving the nuclear lamina a relevant function in nuclear organization, epigenetic regulation and in the maintenance of the stem cell pool. In this context, modeling premature aging with induced pluripotent stem cells (iPSCs) offers the possibility to study these disorders during self-renewal and differentiation into relevant cell types. iPSCs generated by cellular reprogramming from adult somatic cells allows researchers to understand pathophysiological mechanisms and enables the performance of drug screenings. Moreover, the recent development of precision genome editing offers the possibility to study the complex mechanisms underlying senescence and the possibility to correct disease phenotypes, paving the way for future therapeutic interventions.

[18] Advancing the understanding of autism disease mechanisms through genetics

  • Authors: Luis de la Torre-Ubieta, H. Won, J. Stein, D. Geschwind
  • Year: 2016
  • Venue: Nature medicine
  • URL: https://www.semanticscholar.org/paper/a9f29d6ab53873fd50b1e65e64cd36d9447c1a9d
  • DOI: 10.1038/nm.4071
  • PMID: 27050589
  • PMCID: 5072455
  • Citations: 761
  • Influential citations: 8
  • Summary: Current understanding of the genetic architecture of ASD is reviewed and genetic evidence, neuropathology and studies in model systems with how they inform mechanistic models of ASD pathophysiology are integrated.
  • Evidence snippets:
  • Snippet 1 (score: 0.355) > stem cell models suggest that abnormalities in neurogenesis, cell fate, neuronal morphogenesis and synaptic function contribute to the pathogenesis of ASD ( Table 2 and Supplementary Table 3). Transcriptomic studies in these models point to dysregulation in specific molecular processes that may be driving pathogenesis, including chromatin modifications, RNA-splicing, Wnt signaling and Ca 2+ signaling [96][97][98][99] . A small number of drugs, including insulin-like growth factor 1 (IGF1) and roscovitine, have been used to reverse phenotypes associated with Rett syndrome, Timothy syndrome and Phelan-McDermid syndrome (PMDS) in hiPSC models [99][100][101][102] (Table 2). Although promising, human in vitro studies using neurons derived from stem cells have focused on syndromic ASD variants, and thus, modeling of idiopathic ASD 103 and ASD-associated de novo variants will be crucial to obtain a comprehensive picture of phenotypic overlap and potential, convergent disease mechanisms. A further challenge to in vitro studies is that it is not currently certain what the most relevant cellular and physiological ASD phenotypes are that need to be modeled in vitro. > Several molecular or cellular mechanisms of ASD pathophysiology have multiple lines of supporting evidence from studies in humans or model systems ( Table 3). Most of these mechanisms are individually quite broad and considerable work is needed to refine these models to targetable molecular pathways. Furthermore, these mechanisms are not entirely distinct. Indeed, the same genes or molecular pathways contribute to several of these processes at different points during development (Fig. 2), and it is not always clear how early developmental dysfunction relates to later events. An important caveat is that we only have a limited knowledge of the specific genetic contributions to autism susceptibility,

[19] Modeling psychiatric disorders: from genomic findings to cellular phenotypes

  • Authors: Anna Falk, Vivi M. Heine, A. Harwood, Patrick F. Sullivan, M. Peitz et al.
  • Year: 2016
  • Venue: Molecular Psychiatry
  • URL: https://www.semanticscholar.org/paper/235b41240d78140de7ab06a3ad8a7d0b1bdff1a5
  • DOI: 10.1038/mp.2016.89
  • PMID: 27240529
  • PMCID: 4995546
  • Citations: 83
  • Influential citations: 2
  • Summary: The challenges for modeling of psychiatric disorders, potential solutions and how iPSC technology can be used to develop an analytical framework for the evaluation and therapeutic manipulation of fundamental disease processes are critically reviewed.
  • Evidence snippets:
  • Snippet 1 (score: 0.353) > The key challenge for iPSC-based disease modeling is to identify one or more relevant cellular phenotypes that accurately represent the disease pathophysiology. Increasing numbers of reports have demonstrated that for many diseases specific pathophysiology can be captured in human iPSC-based disease models. These range from cardiovascular disease, 44,45 cancer, 46,47 ocular disease, 48,49 diabetes mellitus 50,51 and neurological disorders of the brain. 52,53 Can the same approach be applied to complex psychiatric disorders? > The problem is that almost all psychiatric disorders are characterized by clinical signs and symptoms, but lack independent verification from objective biomarkers. Thus, how might these clinical phenotypes manifest themselves in terms of cell behavior? The identity of robust cellular 'readouts', which typify any psychiatric disorder, is a crucial unsolved problem and an area of intense study 54 (Table 2). When satisfactorily answered, this will herald a new degree of biological objectivity and quantification for the study of psychiatric disorders. > The aim is to find a single or small number of cell phenotypes or parameters that strongly associate with psychiatric disorders, and establish a cellular profile characteristic of cells derived from the general patient population. Although a consensus set of cellular phenotypes for psychiatric disorder is yet to be established, we can define some of their desired characteristics. First, cellular phenotypes have to relate to the biological pathways identified by genetics. Second, although there are many risk genes in disparate biological pathways, at some level, phenotypes should converge onto a much smaller grouping. Third, phenotypes need to be quantifiable. Finally, to be useful for drug development cellular phenotypes should be reversed by pharmacological treatment, although not necessarily by drugs in current use. > Although human iPSC-based approaches underrepresent the complexity of the human central nervous system, cellular phenotypes are likely to lie more proximal to molecular disease mechanisms than phenotypes seen at the level of a tissue or organism, 55 and thus may bypass compensatory homeostatic (2) Gene expression profiles of SCZ human iPSC neurons identified altered expression of many components of the cyclic AMP and WNT signaling pathways.

[20] Mitochondrial Dysfunction in Diabetes: Shedding Light on a Widespread Oversight

  • Authors: F. Iheagwam, A. J. Joseph, E. D. Adedoyin, Olawumi Toyin Iheagwam, Samuel Akpoyowvare Ejoh
  • Year: 2025
  • Venue: Pathophysiology
  • URL: https://www.semanticscholar.org/paper/dbf8042761c1a5fc50f8cd894cc498505abac7cb
  • DOI: 10.3390/pathophysiology32010009
  • PMID: 39982365
  • PMCID: 12077258
  • Citations: 36
  • Summary: This review aims to elucidate the complex link between mitochondrial dysfunction and diabetes, covering the spectrum of diabetes types, the role of mitochondria in insulin resistance, highlighting pathophysiological mechanisms, mitochondrial DNA damage, and altered mitochondrial biogenesis and dynamics.
  • Evidence snippets:
  • Snippet 1 (score: 0.352) > The landscape of DM research is continuously evolving, with emerging technologies and approaches offering new insights into the pathophysiology of the disease and potential therapeutic targets. Advancements in omics technologies, encompassing genomes, transcriptomics, proteomics, and metabolomics, have transformed the molecular mechanisms underlying DM [134]. High-throughput sequencing techniques enable comprehensive analysis of genetic variants, gene expression profiles, protein abundance, and metabolite levels associated with DM and its complications [135]. Single-cell omics approaches provide unprecedented resolution and granularity, allowing researchers to dissect cellular heterogeneity and identify novel cell types, subpopulations, and signalling pathways involved in DM pathogenesis. Integrating multi-omics data sets offers a systems-level perspective of DM, unravelling complex networks of molecular interactions and regulatory circuits underlying disease progression [136]. > In addition to omics technologies, advances in imaging modalities, such as MRI, PET, and optical imaging, enable non-invasive visualisation and quantification of metabolic, functional, and structural changes. Molecular imaging probes targeting specific biomarkers and metabolic pathways provide valuable insights into disease mechanisms and treatment responses in preclinical and clinical settings [85]. Despite significant progress in DM research, numerous unanswered questions and knowledge gaps persist, hindering the ability to develop effective prevention and treatment strategies. Key areas requiring further investigation include the role of epigenetics, environmental factors, and the microbiome in DM susceptibility and progression. Moreover, the interaction between environmental cues and genetic predisposition remains incompletely understood, highlighting the need for comprehensive multi-omics studies and large-scale epidemiological analyses to identify gene-environment interactions and modifiable risk factors for DM [137]. Furthermore, the heterogeneity of DM phenotypes and clinical outcomes poses a challenge for personalised medicine approaches, necessitating robust biomarkers and predictive models to stratify patients based on disease subtypes, prognosis, and treatment response [138].

Notes

  • This provider combines search_papers_by_relevance with snippet_search.
  • No synthesis or second-stage model call is performed.