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Biomolecules
Special Issues
Deciphering Disease Progression Through Multi-Omics Integration
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Deciphering Disease Progression Through Multi-Omics Integration

A Special Issue of Biomolecules (ISSN 2218-273X) belonging to the section "Molecular Biology".

Deadline for manuscript submissions: 30 September 2026 | Viewed by 5270

Editor

Dr. Cinzia Franchin

E-Mail Website
Guest Editor
Department of Pharmaceutical and Pharmacological Sciences, University of Padova, Via Marzolo 5, 35131 Padova, Italy
Interests: proteomics; mass spectrometry; cancer proteomics; protein identification; peptidomics; phosphoproteomics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Recent advances in high-throughput omics technologies are providing unprecedented opportunities to unravel the molecular mechanisms underlying disease onset and progression. Integrating multi-omics data—including genomics, transcriptomics, proteomics, metabolomics, and lipidomics—enables a comprehensive and system-level view of biological regulation, offering new routes for the discovery of diagnostic and prognostic biomarkers as well as potential therapeutic targets.

This Special Issue, “Deciphering Disease Progression through Multi-Omics Integration”, aims to collect cutting-edge studies and reviews that explore the power of multi-omics approaches in understanding complex diseases. We welcome contributions that apply or develop integrative methodologies across omics layers, address challenges in data harmonization and computational modelling, or demonstrate translational relevance in clinical and pre-clinical contexts. Studies focusing on molecular mechanisms, network-based approaches, or advances in technological approaches are also encouraged.

By bringing together experimental and computational perspectives, this Special Issue seeks to highlight how integrative omics can bridge molecular alterations to phenotypic outcomes, ultimately contributing to precision medicine and the identification of new biomarkers for human health and disease.

Dr. Cinzia Franchin
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomolecules is an international peer-reviewed open access monthly 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

  • multi-omics integration
  • systems biology
  • biomarkers
  • disease progression
  • precision medicine
  • computational modelling

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Related Special Issue

Published Papers (2 papers)

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30 pages, 3170 KB  
Article
Establishment of the H8T-MG Meningioma Cell Line and Integrated Transcriptomics Reveal a Metabolic–Immune Signature in Diploid Transitional WHO Grade 1 Tumours
by Esther Mancheño-Maciá, Marina Leal-Clavel and Vanesa Escudero-Ortiz
Biomolecules 2026, 16(5), 744; https://doi.org/10.3390/biom16050744 - 19 May 2026
Viewed by 1465
Abstract
Meningiomas are the most common intracranial tumours, yet the molecular programs underlying WHO grade 1 subtypes—particularly transitional diploid tumours—remain insufficiently defined, partly due to the scarcity of biologically faithful in vitro models. Here, we report the establishment of a long-term, genetically unmanipulated grade [...] Read more.
Meningiomas are the most common intracranial tumours, yet the molecular programs underlying WHO grade 1 subtypes—particularly transitional diploid tumours—remain insufficiently defined, partly due to the scarcity of biologically faithful in vitro models. Here, we report the establishment of a long-term, genetically unmanipulated grade 1 meningioma cell line (H8T-MG) maintained under normoxic conditions in serum-containing, growth-factor-supplemented medium, together with a complementary long-term primary culture (H16T-MG), and provide an integrated descriptive and functional characterization of these models, combined with a subtype-restricted transcriptomic analysis of diploid transitional grade 1 tumours versus normal meninges. Both cultures preserved the dual meso-neuroectodermal identity characteristic of meningothelial cells, exhibiting stable adherent growth, preserved contact inhibition and a coherent immunocytochemical profile, expressing vimentin, α-SMA, nestin, connexin-43 and cannabinoid receptors—reported here for the first time in grade 1 meningioma cultures—highlighting cannabinoid-related pathways as potential targets for exploration. Transcriptomic analysis identified 51 differentially expressed genes, revealing a coherent inflammatory–metabolic programme characterised by downregulation of IL-17 and TNF signalling, cytokines and chemokines (IL6, CCL2, SELE, S100A8), together with reduced extracellular-matrix and cytoskeletal activity. In parallel, the enrichment of arachidonic acid metabolism, cytochrome-P450/xenobiotic pathways, retinol metabolism and oxidative/epoxygenase activity indicated a lipid/xenobiotic-oriented metabolic shift distinctive of this subtype. Protein–protein interaction analysis identified four hub genes—ASPN, SELE, ACKR1 and ABCB1—integrating ECM remodelling, endothelial–immune modulation and xenobiotic transport, reinforcing an immune-attenuated, metabolically adapted tumour landscape. Collectively, these findings provide the first integrated in vitro and transcriptomic characterisation of diploid transitional meningiomas, underscore the value of biologically stable models for early-stage meningioma research, and support the value of histological and ploidy stratification in grade 1 meningioma biology. Full article
(This article belongs to the Special Issue Deciphering Disease Progression Through Multi-Omics Integration)
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19 pages, 3351 KB  
Perspective
Challenges and Opportunities in Multi-Omics Data Acquisition and Analysis: Toward Integrative Solutions
by Christopher L. Hemme, Janet Atoyan, Ang Cai and Chang Liu
Biomolecules 2026, 16(2), 271; https://doi.org/10.3390/biom16020271 - 9 Feb 2026
Cited by 20 | Viewed by 3237
Abstract
In this perspective, we discuss the current challenges and opportunities in multi-omics, a rapidly evolving approach that integrates multiple molecular layers to advance our understanding of complex biological systems. As biomedical research moves toward precision medicine, the ability to correlate genotype, phenotype, and [...] Read more.
In this perspective, we discuss the current challenges and opportunities in multi-omics, a rapidly evolving approach that integrates multiple molecular layers to advance our understanding of complex biological systems. As biomedical research moves toward precision medicine, the ability to correlate genotype, phenotype, and environmental contexts has never been more critical. Multi-omics enhances biomarker discovery and elucidates regulatory networks underlying health and disease. The dominant scientific paradigm for over a century was to take a reductionist approach, studying individual molecular components in isolation or as simplified systems. The advent of omics technologies in the 1990s enabled a systems paradigm, allowing holistic analyses of molecular networks. These early systems studies were constrained by technology and methodology to bulk tissue measurements and single-omics analyses. Recent advances in single-cell and spatial omics, high-throughput proteomics and metabolomics, cloud computing, and artificial intelligence now allow high-resolution, spatially contextualized multi-omics analyses. Despite these gains, challenges in data analysis and interpretation remain, including high dimensionality, missing or incomplete data, multiple batch effects, and method-specific variability. Emerging strategies—such as paired data collection, staged or joint integration, and latent factor or quasi-mediation frameworks—offer promising solutions, positioning multi-omics as a transformative tool for elucidating complex mechanisms and guiding personalized medicine. Continued refinement of these approaches may further enhance the utility of multi-omics for understanding complex biological systems. Full article
(This article belongs to the Special Issue Deciphering Disease Progression Through Multi-Omics Integration)
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