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Novel Biomarkers in the Diagnostics of Cancer
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Novel Biomarkers in the Diagnostics of Cancer

A special issue of Journal of Personalized Medicine (ISSN 2075-4426). This special issue belongs to the section "Disease Biomarker".

Deadline for manuscript submissions: 15 June 2025 | Viewed by 3791

Special Issue Editors

Prof. Dr. Daniela Calina

E-Mail Website
Guest Editor
Department of Clinical Pharmacy, University of Medicine and Pharmacy of Craiova, 200349 Craiova, Romania
Interests: clinical pharmacy; oncology; biomarkers; experimental pharmacology
Special Issues, Collections and Topics in MDPI journals
Dr. Luca Falzone

E-Mail Website
Guest Editor
Department of Biomedical and Biotechnological Sciences, University of Catania, Catania, Italy
Interests: molecular oncology; oncogenetics; epigenetics; biomarker discovery; drug resistance; microRNAs
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Background and History of This Topic: The quest to understand cancer has driven scientific endeavors for over a century. Since the inception of the molecular era of medicine, there has been a fervent push to identify and characterize biomarkers specific to various forms of the disease. Early biomarkers, such as the prostate-specific antigen (PSA) for prostate cancer, revolutionized early detection, and became integral in guiding treatment decisions. Over the years, advancements in genomics, proteomics, metabolomics, and bioinformatics have led to the discovery of a plethora of potential biomarkers, offering finer diagnostic precision, prognosis prediction, and therapeutic response evaluation.

Aim and Scope of the Special Issue: This Special Issue, titled "Novel Biomarkers in the Diagnostics of Cancer", aims to serve as a comprehensive platform for the dissemination of the latest research and advancements in the identification and validation of novel cancer biomarkers. We aim to explore not only the molecular intricacies of these markers but also their clinical applications and potential to shape personalized therapeutic strategies.

Specific areas of focus include, but are not limited to:

  • Novel genetic, epigenetic, proteomic, and metabolic markers.
  • Technological advancements in biomarker discovery.
  • Bioinformatics approaches in data mining for potential biomarkers.
  • Clinical utility and validation studies.
  • Implications for personalized medicine and therapy adjustments based on biomarker profiles.

Cutting-Edge Research: Emerging research has elucidated the potential of liquid biopsies, capturing circulating tumor DNA, exosomes, and circulating tumor cells as non-invasive diagnostic tools; advanced computational methodologies are being employed to analyze massive datasets to identify potential biomarkers with unprecedented accuracy.

We welcome:

  • Original research papers detailing novel findings in the realm of cancer biomarkers.
  • Review articles offering comprehensive overviews of specific subfields within cancer biomarker discovery.
  • Methodological papers detailing novel techniques or improvements on existing methodologies for biomarker detection or validation.
  • Case studies or case series that provide clinical insights into the application of new biomarkers.
  • Perspective or opinion pieces discussing challenges, future directions, and ethical considerations in the field.

We intend for this Special Issue to bring together a multidisciplinary cohort of researchers, clinicians, and scholars, shedding light on the future of personalized oncology through the lens of biomarker discovery.

Prof. Dr. Daniela Calina
Dr. Luca Falzone
Guest Editors

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. Journal of Personalized Medicine 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 2600 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

  • cancer biomarkers
  • liquid biopsy
  • circulating tumor DNA
  • exosomes
  • cancer personalized medicine
  • biomarker validation
  • genomic biomarkers
  • epigenetic markers
  • proteomic signatures
  • metabolomic profiling

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

Published Papers (3 papers)

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Research

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14 pages, 1161 KiB  
Article
Novel Somay’s GLUCAR Index Efficiently Predicts Survival Outcomes in Locally Advanced Pancreas Cancer Patients Receiving Definitive Chemoradiotherapy: A Propensity-Score-Matched Cohort Analysis
by Erkan Topkan, Sukran Senyurek, Nulifer Kılic Durankus, Duriye Ozturk and Ugur Selek
J. Pers. Med. 2024, 14(7), 746; https://doi.org/10.3390/jpm14070746 - 13 Jul 2024
Viewed by 707
Abstract
Background: Propensity score matching (PSM) was used to investigate the prognostic value of a novel GLUCAR index [Glucose × (C-reactive protein ÷ albumin)] in unresectable locally advanced pancreatic cancer (LA-NPC) patients who received definitive concurrent chemoradiotherapy (CCRT). Methods: The PSM analysis comprised 142 [...] Read more.
Background: Propensity score matching (PSM) was used to investigate the prognostic value of a novel GLUCAR index [Glucose × (C-reactive protein ÷ albumin)] in unresectable locally advanced pancreatic cancer (LA-NPC) patients who received definitive concurrent chemoradiotherapy (CCRT). Methods: The PSM analysis comprised 142 LA-PAC patients subjected to definitive CCRT. Receiver operating characteristic (ROC) curve analysis was utilized to identify relevant pre-CCRT cutoffs that could effectively stratify survival results. The primary and secondary objectives were the correlations between the pre-CCRT GLUCAR measures and overall survival (OS) and progression-free survival (PFS). Results: The ROC analysis revealed significance at 43.3 for PFS [area under the curve (AUC): 85.1%; sensitivity: 76.8%; specificity: 74.2%; J-index: 0.510)] and 42.8 for OS (AUC: 81.8%; sensitivity: 74.2%; specificity: 71.7%; J-index: 0.459). Given that these cutoff points were close, the standard cutoff point, 42.8, was selected for further analysis. Comparative survival analyses showed that pre-CCRT GLUCAR ≥ 42.8 (n = 71) measures were associated with significantly shorter median PFS (4.7 vs. 15.8 months; p < 0.001) and OS (10.1 vs. 25.4 months; p < 0.001) durations compared to GLUCAR < 42.8 measures (n = 71). The multivariate analysis results confirmed the independent significance of the GLUCAR index on PFS (p < 0.001) and OS (p < 0.001) outcomes. Conclusions: Elevated pre-CCRT GLUCAR levels are robustly and independently linked to significantly poorer PFS and OS outcomes in unresectable LA-PAC patients treated with definitive CCRT. Full article
(This article belongs to the Special Issue Novel Biomarkers in the Diagnostics of Cancer)
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Review

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28 pages, 6016 KiB  
Review
Intratumoral Microbiota: Insights from Anatomical, Molecular, and Clinical Perspectives
by Claudia Lombardo, Rosanna Fazio, Marta Sinagra, Giuseppe Gattuso, Federica Longo, Cinzia Lombardo, Mario Salmeri, Guido Nicola Zanghì and Carla Agata Erika Loreto
J. Pers. Med. 2024, 14(11), 1083; https://doi.org/10.3390/jpm14111083 - 31 Oct 2024
Viewed by 681
Abstract
The human microbiota represents a heterogeneous microbial community composed of several commensal, symbiotic, and even pathogenic microorganisms colonizing both the external and internal body surfaces. Despite the term “microbiota” being commonly used to identify microorganisms inhabiting the gut, several pieces of evidence suggest [...] Read more.
The human microbiota represents a heterogeneous microbial community composed of several commensal, symbiotic, and even pathogenic microorganisms colonizing both the external and internal body surfaces. Despite the term “microbiota” being commonly used to identify microorganisms inhabiting the gut, several pieces of evidence suggest the presence of different microbiota physiologically colonizing other organs. In this context, several studies have also confirmed that microbes are integral components of tumor tissue in different types of cancer, constituting the so-called “intratumoral microbiota”. The intratumoral microbiota is closely related to the occurrence and development of cancer as well as to the efficacy of anticancer treatments. Indeed, intratumoral microbiota can contribute to carcinogenesis and metastasis formation as some microbes can directly cause DNA damage, while others can induce the activation of proinflammatory responses or oncogenic pathways and alter the tumor microenvironment (TME). All these characteristics make the intratumoral microbiota an interesting topic to investigate for both diagnostic and prognostic purposes in order to improve the management of cancer patients. This review aims to gather the most recent data on the role of the intratumoral microbiota in cancer development, progression, and response to treatment, as well as its potential diagnostic and prognostic value. Full article
(This article belongs to the Special Issue Novel Biomarkers in the Diagnostics of Cancer)
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17 pages, 922 KiB  
Review
Role of Oral Microbiota Dysbiosis in the Development and Progression of Oral Lichen Planus
by Alessandro Lavoro, Giovanni Cultrera, Giuseppe Gattuso, Cinzia Lombardo, Luca Falzone, Candido Saverio, Massimo Libra and Mario Salmeri
J. Pers. Med. 2024, 14(4), 386; https://doi.org/10.3390/jpm14040386 - 3 Apr 2024
Cited by 2 | Viewed by 1785
Abstract
Oral lichen planus (OLP) is a chronic inflammatory autoimmune disease of the oral cavity with malignant potential affecting 1.01% of the worldwide population. The clinical patterns of this oral disorder, characterized by relapses and remissions of the lesions, appear on buccal, lingual, gingival, [...] Read more.
Oral lichen planus (OLP) is a chronic inflammatory autoimmune disease of the oral cavity with malignant potential affecting 1.01% of the worldwide population. The clinical patterns of this oral disorder, characterized by relapses and remissions of the lesions, appear on buccal, lingual, gingival, and labial mucosa causing a significant reduction in the quality of life. Currently, there are no specific treatments for this disease, and the available therapies with topical and systemic corticosteroids only reduce symptoms. Although the etiopathogenesis of this pathological condition has not been completely understood yet, several exogenous and endogenous risk factors have been proposed over the years. The present review article summarized the underlying mechanisms of action involved in the onset of OLP and the most well-known triggering factors. According to the current data, oral microbiota dysbiosis could represent a potential diagnostic biomarker for OLP. However, further studies should be undertaken to validate their use in clinical practice, as well as to provide a better understanding of mechanisms of action and develop novel effective intervention strategies against OLP. Full article
(This article belongs to the Special Issue Novel Biomarkers in the Diagnostics of Cancer)
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