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Cells
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Molecular Pathways in Medicine and Cell Models of Disease
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Molecular Pathways in Medicine and Cell Models of Disease

A special issue of Cells (ISSN 2073-4409). This special issue belongs to the section "Cellular Pathology".

Deadline for manuscript submissions: closed (15 December 2023) | Viewed by 5773

Special Issue Editor

Prof. Dr. Anton Buzdin

E-Mail Website
Guest Editor
1. Subgroup of Bioinformatics and Biostatistics, European Organization for Research and Treatment of Cancer, Brussels, Belgium
2. Group for Genomic Analysis of Cell Signaling Systems, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, 117997 Moscow, Russia
3. Institute of Personalized Medicine, I.M. Sechenov First Moscow State Medical University, 119991 Moscow, Russia
4. Omicsway Corp., Walnut, CA 91789, USA
Interests: systems biology; omics molecular medicine; personalized oncology; molecular diagnostics of cancer; targeted therapy
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Molecular pathways are currently the next level of omics data analysis. Interrogation of molecular pathways using gene expression data has become almost a one-click instrument such as in the Oncobox Pathway Databank open resource (https://open.oncobox.com/auth/sign-in). In addition to transcriptomics and proteomics, epigenomics and emerging fields like advanced metabolomics have many valuable options to offer to an overall concept of omics-based science. Thus, it is important to link recent developments in this domain with medicine and cell-based disease models to improve diagnosis, prognosis, and treatment options. In this research collection, submission of manuscripts strongly encouraged that deal with (especially invited, but not limited to):

  • New methods of molecular pathway analysis with applications to clinical or cell-based disease model research
  • Emerging sources of data for the assessment of molecular pathways with links to medicine and cell-based disease models
  • Applications of Big data and Machine Learning/AI to molecular pathway analysis with link to clinical oncology
  • Advantages of using molecular pathways as the actionable alternative to single-gene approach in medicine and cell-based disease models
  • Building complex multi-omics in silico models of disease development and drug resistance.

Both research and review articles are welcome. For bioinformatic papers, effort should be made not to restrict the analysis to a single source of data such as the TCGA database, and to include as many independent validation cohorts as possible. In all manuscripts, special attention must be given to statistical assessment such as adjustment to false-discovery rate and tests for randomness of intersections, when applicable.

Prof. Dr. Anton Buzdin
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Cells is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • systems biology
  • omics molecular medicine
  • molecular and cellular biology
  • molecular pathways analysis
  • targeted therapy

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Published Papers (2 papers)

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Research

19 pages, 9421 KiB  
Article
Pre-Infection Innate Immunity Attenuates SARS-CoV-2 Infection and Viral Load in iPSC-Derived Alveolar Epithelial Type 2 Cells
by Satish Kumar, Jose Granados, Miriam Aceves, Juan Peralta, Ana C. Leandro, John Thomas, Sarah Williams-Blangero, Joanne E. Curran and John Blangero
Cells 2024, 13(5), 369; https://doi.org/10.3390/cells13050369 - 21 Feb 2024
Cited by 3 | Viewed by 2145
Abstract
A large portion of the heterogeneity in coronavirus disease 2019 (COVID-19) susceptibility and severity of illness (SOI) remains poorly understood. Recent evidence suggests that SARS-CoV-2 infection-associated damage to alveolar epithelial type 2 cells (AT2s) in the distal lung may directly contribute to disease [...] Read more.
A large portion of the heterogeneity in coronavirus disease 2019 (COVID-19) susceptibility and severity of illness (SOI) remains poorly understood. Recent evidence suggests that SARS-CoV-2 infection-associated damage to alveolar epithelial type 2 cells (AT2s) in the distal lung may directly contribute to disease severity and poor prognosis in COVID-19 patients. Our in vitro modeling of SARS-CoV-2 infection in induced pluripotent stem cell (iPSC)-derived AT2s from 10 different individuals showed interindividual variability in infection susceptibility and the postinfection cellular viral load. To understand the underlying mechanism of the AT2′s capacity to regulate SARS-CoV-2 infection and cellular viral load, a genome-wide differential gene expression analysis between the mock and SARS-CoV-2 infection-challenged AT2s was performed. The 1393 genes, which were significantly (one-way ANOVA FDR-corrected p ≤ 0.05; FC abs ≥ 2.0) differentially expressed (DE), suggest significant upregulation of viral infection-related cellular innate immune response pathways (p-value ≤ 0.05; activation z-score ≥ 3.5), and significant downregulation of the cholesterol- and xenobiotic-related metabolic pathways (p-value ≤ 0.05; activation z-score ≤ −3.5). Whilst the effect of post-SARS-CoV-2 infection response on the infection susceptibility and postinfection viral load in AT2s is not clear, interestingly, pre-infection (mock-challenged) expression of 238 DE genes showed a high correlation with the postinfection SARS-CoV-2 viral load (FDR-corrected p-value ≤ 0.05 and r2-absolute ≥ 0.57). The 85 genes whose expression was negatively correlated with the viral load showed significant enrichment in viral recognition and cytokine-mediated innate immune GO biological processes (p-value range: 4.65 × 10−10 to 2.24 × 10−6). The 153 genes whose expression was positively correlated with the viral load showed significant enrichment in cholesterol homeostasis, extracellular matrix, and MAPK/ERK pathway-related GO biological processes (p-value range: 5.06 × 10−5 to 6.53 × 10−4). Overall, our results strongly suggest that AT2s’ pre-infection innate immunity and metabolic state affect their susceptibility to SARS-CoV-2 infection and viral load. Full article
(This article belongs to the Special Issue Molecular Pathways in Medicine and Cell Models of Disease)
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24 pages, 4601 KiB  
Article
Distinct Traits of Structural and Regulatory Evolutional Conservation of Human Genes with Specific Focus on Major Cancer Molecular Pathways
by Galina Zakharova, Alexander Modestov, Polina Pugacheva, Rijalda Mekic, Ekaterina Savina, Anastasia Guryanova, Anastasia Rachkova, Semyon Yakushov, Andrei Alimov, Elizaveta Kulaeva, Elena Fedoseeva, Artem Kleyman, Kirill Vasin, Victor Tkachev, Andrew Garazha, Marina Sekacheva, Maria Suntsova, Maksim Sorokin, Anton Buzdin and Marianna A. Zolotovskaia
Cells 2023, 12(9), 1299; https://doi.org/10.3390/cells12091299 - 2 May 2023
Cited by 4 | Viewed by 3045
Abstract
The evolution of protein-coding genes has both structural and regulatory components. The first can be assessed by measuring the ratio of non-synonymous to synonymous nucleotide substitutions. The second component can be measured as the normalized proportion of transposable elements that are used as [...] Read more.
The evolution of protein-coding genes has both structural and regulatory components. The first can be assessed by measuring the ratio of non-synonymous to synonymous nucleotide substitutions. The second component can be measured as the normalized proportion of transposable elements that are used as regulatory elements. For the first time, we characterized in parallel the regulatory and structural evolutionary profiles for 10,890 human genes and 2972 molecular pathways. We observed a ~0.1 correlation between the structural and regulatory metrics at the gene level, which appeared much higher (~0.4) at the pathway level. We deposited the data in the publicly available database RetroSpect. We also analyzed the evolutionary dynamics of six cancer pathways of two major axes: Notch/WNT/Hedgehog and AKT/mTOR/EGFR. The Hedgehog pathway had both components slower, whereas the Akt pathway had clearly accelerated structural evolution. In particular, the major hub nodes Akt and beta-catenin showed both components strongly decreased, whereas two major regulators of Akt TCL1 and CTMP had outstandingly high evolutionary rates. We also noticed structural conservation of serine/threonine kinases and the genes related to guanosine metabolism in cancer signaling: GPCRs, G proteins, and small regulatory GTPases (Src, Rac, Ras); however, this was compensated by the accelerated regulatory evolution. Full article
(This article belongs to the Special Issue Molecular Pathways in Medicine and Cell Models of Disease)
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