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Biomolecules
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Omics Data Integration: Focusing on Molecular Biomarkers for Cancers and...
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Omics Data Integration: Focusing on Molecular Biomarkers for Cancers and Diseases

A special issue of Biomolecules (ISSN 2218-273X). This special issue belongs to the section "Bioinformatics and Systems Biology".

Deadline for manuscript submissions: 31 July 2025 | Viewed by 3663

Special Issue 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 Issue Information

Dear Colleagues,

The multi-omics approach has become essential in understanding cancer biology and other severe diseases, offering unprecedented insights into the molecular mechanisms underlying their genesis, progression, and therapeutic responses.

The proteome reflects cellular processes and alterations, identifying biomarkers for early detection and explaining the complex interplay of proteins within cancer cells and their microenvironment. Despite the relatively small number of human genes, alternative splicing and post-translational modifications generate diverse protein isoforms. High-throughput analysis explores protein expression, structures, variants, and functional effects to elucidate pathological mechanisms.

Evaluating the genome and transcriptome is crucial in identifying genetic mutations and variations linked to hereditary and complex diseases, providing insights into the genetic basis of pathologies and revealing how gene regulation alterations contribute to disease development. This analysis aids in early diagnosis, prognosis, and the development of targeted therapies.

Examining the cellular metabolome offers comprehensive insights into biochemical processes and metabolic pathways, identifying biomarkers for early diagnosis and monitoring disease progression. Changes in the metabolite profile can be detected before clinical symptoms become evident.

Integrating genomic, transcriptomic, proteomic, and metabolomic information accelerates translational research, fostering innovation in disease diagnosis, treatment, and prevention. Personalized medicine benefits from omics profiling, tailoring treatments to individuals, enhancing efficacy, and reducing side-effects.

This Special Issue of Biomolecules is dedicated to biomarker discovery based on omics data, with special attention to studies involving multiple high-throughput methods. Interdisciplinary research contributions, including original articles and reviews, are encouraged. Submissions may encompass, but are not limited to, the following areas:

  • Biomarker discovery and clinical implications in diagnosis and prognosis;
  • Proteomic profiling of tumour heterogeneity and personalized medicine;
  • Integration of multi-omics data to unravel complex signalling networks;
  • Advancements in mass spectrometry and computational tools;
  • Functional proteomics to decipher the roles of specific proteins in disease development;
  • Structural proteomics to elucidate new therapeutic approaches;
  • Future directions and emerging technologies in omics;
  • Single-cell multi-omics approaches;
  • Application of multi-omics approaches for personalized medicine.

Join us in advancing knowledge in "Omics Data Integration: Focusing on Molecular Biomarkers for Cancers and Diseases." Your contributions will enhance our understanding of disease biology and pave the way for innovative strategies in diagnosis and treatment.

Sincerely,

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 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. 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

  • omics data analysis
  • omics data integration
  • biomarker discovery
  • bioinformatics
  • cancers

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Published Papers (3 papers)

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Research

24 pages, 13179 KiB  
Article
Omics Investigations of Prostate Cancer Cells Exposed to Simulated Microgravity Conditions
by Herbert Schulz, Fatima Abdelfattah, Anna Heinrich, Daniela Melnik, Viviann Sandt, Marcus Krüger, Markus Wehland, Per Hoffmann, José Luis Cortés-Sánchez, Matthias Evert, Katja Evert and Daniela Grimm
Biomolecules 2025, 15(2), 303; https://doi.org/10.3390/biom15020303 - 18 Feb 2025
Viewed by 547
Abstract
Prostate cancer (PC) is the most diagnosed cancer in males across the globe. Following the formation of metastasis, PC is linked to a notable decline in both prognosis and survival rates. Three-dimensional multicellular spheroids (MCSs) of a prostate adenocarcinoma cell line were generated [...] Read more.
Prostate cancer (PC) is the most diagnosed cancer in males across the globe. Following the formation of metastasis, PC is linked to a notable decline in both prognosis and survival rates. Three-dimensional multicellular spheroids (MCSs) of a prostate adenocarcinoma cell line were generated in a three-day simulated microgravity environment (s-µg) to serve as a model for metastasis and to derive transcriptional and epigenetic PC candidates from molecular biological changes. With an FDR of 10−3, we detected the most differentially expressed genes in the two comparisons’ adherent cells (AD) to MCSs (N = 751 genes) and 1g control cells to MCSs (N = 662 genes). In these two comparisons, genes related to cell cycle, angiogenesis, cell adhesion, and extracellular space were consistently found to be significantly enriched in GO annotations. Furthermore, at a 5% FDR significance level, we were able to identify 11,090 genome-wide differentially methylated positions (DMPs) and one differentially methylated region in the SRMS gene in the 1g vs. AD comparison, as well as an additional 10,797 DMPs in the 1g vs. MCSs comparison. Finally, we identified five s-µg-related positive enrichments of transcription factor binding sites for AR, IRF1, IRF2, STAT1, STAT2, and FOXJ3 close to the DMPs. Full article
(This article belongs to the Special Issue Omics Data Integration: Focusing on Molecular Biomarkers for Cancers and Diseases)
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16 pages, 2234 KiB  
Article
Integrated Clinomics and Molecular Dynamics Simulation Approaches Reveal the SAA1.1 Allele as a Biomarker in Alkaptonuria Disease Severity
by Alfonso Trezza, Bianca Roncaglia, Anna Visibelli, Roberta Barletta, Luana Peruzzi, Barbara Marzocchi, Daniela Braconi, Ottavia Spiga and Annalisa Santucci
Biomolecules 2025, 15(2), 194; https://doi.org/10.3390/biom15020194 - 29 Jan 2025
Viewed by 595
Abstract
Alkaptonuria (AKU) is a rare metabolic disorder characterized by the accumulation of homogentisic acid (HGA), leading to progressive ochronosis and joint degeneration. While much is known about HGA’s role in tissue damage, the molecular mechanisms underlying acute inflammation in AKU remain poorly understood. [...] Read more.
Alkaptonuria (AKU) is a rare metabolic disorder characterized by the accumulation of homogentisic acid (HGA), leading to progressive ochronosis and joint degeneration. While much is known about HGA’s role in tissue damage, the molecular mechanisms underlying acute inflammation in AKU remain poorly understood. Serum amyloid A (SAA) proteins are key mediators of the inflammatory response, yet their potential as biomarkers for inflammation in AKU has not been explored. This study investigated the role of the SAA1.1 allele as a biomarker for the severity of acute inflammation in AKU. Data from the ApreciseKUre Precision Medicine Ecosystem were analyzed to assess the relationship between SAA1 allelic variants and inflammatory markers. Molecular dynamics simulations compared the structural dynamics of SAA1.1 and SAA1.2 isoforms, with standard modeling and analysis pipelines employed. Using a clinomics approach, we showed that AKU patients expressing the SAA1.1 allele have significantly higher acute inflammation-related markers. Extensive molecular dynamics simulations revealed that the SAA1.1 isoform lent high structural instability of the C-terminal domain, accelerating the formation of amyloid fibrils and exacerbating the inflammatory condition. These findings would identify the SAA1.1 allele as a novel genetic biomarker for the progression of secondary amyloidosis in AKU and its severity. Furthermore, new molecular insights into the inflammatory mechanisms of AKU were provided, suggesting potential therapeutic approaches aimed at stabilizing SAA1.1 protein and preventing amyloid fibril formation, with significant implications in AKU and precision medicine strategies for SAA-related diseases. Full article
(This article belongs to the Special Issue Omics Data Integration: Focusing on Molecular Biomarkers for Cancers and Diseases)
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10 pages, 240 KiB  
Article
Serum Biomarker Signatures of Choroid Plexus Volume Changes in Multiple Sclerosis
by Dejan Jakimovski, Robert Zivadinov, Ferhan Qureshi, Murali Ramanathan, Bianca Weinstock-Guttman, Eleonora Tavazzi, Michael G. Dwyer and Niels Bergsland
Biomolecules 2024, 14(7), 824; https://doi.org/10.3390/biom14070824 - 10 Jul 2024
Cited by 2 | Viewed by 1832
Abstract
Increased choroid plexus (CP) volume has been recently implicated as a potential predictor of worse multiple sclerosis (MS) outcomes. The biomarker signature of CP changes in MS are currently unknown. To determine the blood-based biomarker characteristics of the cross-sectional and longitudinal MRI-based CP [...] Read more.
Increased choroid plexus (CP) volume has been recently implicated as a potential predictor of worse multiple sclerosis (MS) outcomes. The biomarker signature of CP changes in MS are currently unknown. To determine the blood-based biomarker characteristics of the cross-sectional and longitudinal MRI-based CP changes in a heterogeneous group of people with MS (pwMS), a total of 202 pwMS (148 pwRRMS and 54 pwPMS) underwent MRI examination at baseline and at a 5-year follow-up. The CP was automatically segmented and subsequently refined manually in order to obtain a normalized CP volume. Serum samples were collected at both timepoints, and the concentration of 21 protein measures relevant to MS pathophysiology were determined using the Olink™ platform. Age-, sex-, and BMI-adjusted linear regression models explored the cross-sectional and longitudinal relationships between MRI CP outcomes and blood-based biomarkers. At baseline, there were no significant proteomic predictors of CP volume, while at follow-up, greater CP volume was significantly associated with higher neurofilament light chain levels, NfL (standardized β = 0.373, p = 0.001), and lower osteopontin levels (standardized β = −0.23, p = 0.02). Higher baseline GFAP and lower FLRT2 levels were associated with future 5-year CP % volume expansion (standardized β = 0.277, p = 0.004 and standardized β = −0.226, p = 0.014, respectively). The CP volume in pwMS is associated with inflammatory blood-based biomarkers of neuronal injury (neurofilament light chain; NfL) and glial activation such as GFAP, osteopontin, and FLRT2. The expansion of the CP may play a central role in chronic and compartmentalized inflammation and may be driven by glial changes. Full article
(This article belongs to the Special Issue Omics Data Integration: Focusing on Molecular Biomarkers for Cancers and Diseases)
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