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Biology
Special Issues
Disease Biomarker Discovery and Validation
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Disease Biomarker Discovery and Validation

A special issue of Biology (ISSN 2079-7737). This special issue belongs to the section "Biochemistry and Molecular Biology".

Deadline for manuscript submissions: closed (31 August 2025) | Viewed by 1676

Special Issue Editor

Dr. Matthew James Jennings

E-Mail Website
Guest Editor
Clinical Laboratory Sciences, Upper Michigan Brain Tumor Center (UMBTC), Northern Michigan University, Marquette, MI 49855, USA
Interests: molecular diagnostics; assay development; cancer biology

Special Issue Information

Dear Colleagues,

The journal Biology is pleased to invite you to participate in a Special Issue titled, “Disease Biomarker Discovery and Validation”. This Special Issue intends to collect publications that relate to biomarkers defining human conditions. Disease biomarkers define characteristics that are used as indicators of abnormal biological processes, pathogenic processes, or responses to a therapeutic intervention. Each biomarker possesses either chemical, physical, or biological characteristics that can be measured along functional, physiological, biochemical, cellular, or molecular aspects.  Biomarkers are classified into the seven following categories: diagnostic, prognostic, predictive, susceptible, monitored, safe, and pharmacodynamic. Biological markers include molecules, enzymes, genes, gene products, hormones, or specific cells that assist our understanding of disease states.

Biology is an international, peer-reviewed, open-access journal of biological sciences published online monthly by MDPI. Biology publishes reviews, research papers, and communications in all areas of biology and at the interface of related disciplines. In this Special Issue, original research articles and reviews are welcome. In addition to research articles, publications focusing on the analytical validations of candidate biomarkers are also encouraged for submission. We look forward to receiving your contributions.

Dr. Matthew James Jennings
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. Biology 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

  • biomarkers
  • prognostic validation
  • predictive validation
  • analytical validation

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Further information on MDPI's Special Issue policies can be found here.

Published Papers (2 papers)

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Research

21 pages, 7855 KB  
Article
Development and Validation of a 7-eRNA Prognostic Signature for Lung Adenocarcinoma
by Yiwen Sun, Keng Chen, Jingkai Zhang, Zhijie Hu, Mingmei Xiong, Zhigang Fang, Guanmei Chen, Xiaomei Meng, Baolin Liao, Yuanyan Xiong and Luping Lin
Biology 2025, 14(10), 1431; https://doi.org/10.3390/biology14101431 - 17 Oct 2025
Viewed by 221
Abstract
Enhancer RNAs (eRNAs) are abundant in most human cells and tissues, and quantifying eRNAs has become a robust approach for biomarker discovery. While eRNAs play crucial roles in regulating biological processes and cancer progression, their functions in lung adenocarcinoma (LUAD) remain poorly understood. [...] Read more.
Enhancer RNAs (eRNAs) are abundant in most human cells and tissues, and quantifying eRNAs has become a robust approach for biomarker discovery. While eRNAs play crucial roles in regulating biological processes and cancer progression, their functions in lung adenocarcinoma (LUAD) remain poorly understood. Here, we developed a LUAD prognostic model based on eRNA expression data from The Cancer Genome Atlas (TCGA). Through rigorous validation, a 7-eRNA signature was identified, which robustly stratified LUAD patients into high-risk and low-risk groups in both training and testing sets. Functional analyses revealed distinct enrichment of pathways related to amino acid biosynthesis, ribosome biogenesis, and proteasome activity in high-risk patients. Somatic mutation profiling highlighted TP53 and TTN as frequently mutated genes, while drug sensitivity prediction identified four potential therapeutic agents (including AZD4547 and Nutlin-3a) for high-risk individuals. Collectively, this study constructed a 7-eRNA prognostic model for LUAD, providing a powerful tool for clinical risk assessment and uncovering eRNA-mediated regulatory mechanisms. Full article
(This article belongs to the Special Issue Disease Biomarker Discovery and Validation)
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33 pages, 16266 KB  
Article
Integrated Bioinformatics Analysis and Cellular Experimental Validation Identify Lipoprotein Lipase Gene as a Novel Biomarker for Tumorigenesis and Prognosis in Lung Adenocarcinoma
by Wanwan He, Meilian Wei, Yan Huang, Junsen Qin, Meng Liu, Na Liu, Yanli He, Chuanbing Chen, Yali Huang, Heng Yin and Ren Zhang
Biology 2025, 14(5), 566; https://doi.org/10.3390/biology14050566 - 19 May 2025
Viewed by 1088
Abstract
Lung adenocarcinoma (LUAD) is one of the leading causes of death worldwide, and thus, more biomarker and therapeutic targets need to be explored. Herein, we aimed to explore new biomarkers of LUAD by integrating bioinformatics analysis with cell experiments. We firstly identified 266 [...] Read more.
Lung adenocarcinoma (LUAD) is one of the leading causes of death worldwide, and thus, more biomarker and therapeutic targets need to be explored. Herein, we aimed to explore new biomarkers of LUAD by integrating bioinformatics analysis with cell experiments. We firstly identified 266 druggable genes that were significantly differentially expressed between LUAD tissues and adjacent normal lung tissues. Among these genes, SMR analysis with p-value correction suggested that declining lipoprotein lipase (LPL) levels may be causally associated with an elevated risk of LUAD, which was corroborated by co-localization analysis. Analyses of clinical data showed that LPL in lung cancer tissues has considerable diagnostic value for LUAD, and elevated LPL levels were positively associated with improved patient survival outcomes. Cell experiments with an LPL activator proved these findings; the activator inhibited the proliferation and migration of lung cancer cells. Next, we found that LPL promoted the infiltration of immune cells such as DCs, IDCs, and macrophages in LUAD by mononuclear sequencing analysis and TIMER2.0. Meanwhile, patients with low levels of LPL expression demonstrated superior immunotherapeutic responses to anti-PD-1 therapy. We conclude that LPL acts as a diagnostic and prognostic marker for LUAD. Full article
(This article belongs to the Special Issue Disease Biomarker Discovery and Validation)
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