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Cancers
Special Issues
Novel Prognostic Biomarkers in Human Cancers: From Discovery to Application
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Novel Prognostic Biomarkers in Human Cancers: From Discovery to Application

A special issue of Cancers (ISSN 2072-6694). This special issue belongs to the section "Cancer Biomarkers".

Deadline for manuscript submissions: 31 October 2025 | Viewed by 9547

Special Issue Editor

Dr. Zakaria Y. Abd Elmageed

E-Mail Website
Guest Editor
Department of Pharmacology, Edward Via College of Osteopathic Medicine, University of Louisiana at Monroe, Monroe, LA 71203, USA
Interests: tumor biomarkers; investigational markers; prognosis; biochemical relapse; overall survival; clinical trials; advancement in biomarker discovery; bioinformatics and marker discovery; AI and biomarker discovery
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Cancer is the leading cause of death among men and women worldwide, with an estimated 19.3 million new cases and approximately 10 million cancer deaths each year. Reliable molecular biomarkers can serve as accurate tools for monitoring the clinical progression of the disease, the aggressiveness of the tumor, the drug response and the overall survival of cancer patients. Non-invasive biological materials such as DNA, coding and non-coding RNA, lipids and proteins could represent an abundant source of tumor markers. Because human tumor tissue is a biologically and clinically heterogeneous matter, the molecular biomarkers currently employed do not sufficiently address the wide variety of human specimens, the state of the disease, the reproducibility of results and patients’ clinical outcomes. Researchers should further endeavor to standardize biological biomarker sources, the various methodologies utilized, the interpretation of data, and the model of analysis and multicenter studies employed in order to ensure the reliability and specificity of tumor biomarkers. Unfortunately, the current application of some routine biomarkers is limited by the occurrence of false positive results, which can lead to the overtreatment of indolent disease and mislead treatment decisions at relapse. Therefore, the development of novel strategies for more specific and reliable prognostic tumor markers is needed.

In this Special Issue, we will highlight the most recent techniques used for investigational biomarker discovery, validation and clinical studies in order to promote next-generation human tumor biomarkers that can meet the clinical needs. This Special Issue particularly welcomes the submission of full manuscripts or review articles focusing on the development and evaluation of prognostic markers.

Dr. Zakaria Y. Abd Elmageed
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 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. Cancers 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 2900 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

  • tumor biomarkers
  • investigational markers
  • prognosis
  • biochemical relapse
  • overall survival
  • clinical trials
  • advancement in biomarker discovery
  • bioinformatics and marker discovery
  • AI and biomarker discovery

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Published Papers (4 papers)

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Research

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12 pages, 1137 KiB  
Article
Prognostic Value of Blood-Based Inflammatory Markers in Cancer Patients Receiving Immune Checkpoint Inhibitors
by Mustafa Murat Midik, Damla Gunenc, Pınar Fatma Acar and Burcak Saziye Karaca
Cancers 2025, 17(1), 37; https://doi.org/10.3390/cancers17010037 - 26 Dec 2024
Cited by 1 | Viewed by 1138
Abstract
Background: Although immune checkpoint inhibitors (ICIs) have significantly improved cancer treatment, a substantial proportion of patients do not benefit from these therapies, revealing the crucial need to identify reliable biomarkers. Inflammatory markers, such as the neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), pan-immune [...] Read more.
Background: Although immune checkpoint inhibitors (ICIs) have significantly improved cancer treatment, a substantial proportion of patients do not benefit from these therapies, revealing the crucial need to identify reliable biomarkers. Inflammatory markers, such as the neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), pan-immune inflammation value (PIV), systemic inflammation response index (SIRI), lactate dehydrogenase (LDH), and C-reactive protein (CRP), may provide insights into treatment outcomes. Objectives: This study aimed to evaluate the prognostic value of multiple inflammatory markers in patients with cancer receiving ICI-based therapies. Methods: A retrospective analysis was performed on 226 patients treated with ICI-based therapies at a single center between 2012 and 2023. The inflammatory markers NLR, PIV, SII, SIRI, LDH, CRP, and albumin were assessed. Cut-off values were determined using maximally selected rank statistics, and overall survival (OS) and progression-free survival (PFS) were evaluated using the Kaplan–Meier method and Cox regression analysis. Results: High NLR, PIV, SII, SIRI, LDH, and CRP, as well as low albumin levels, were associated with worse OS and PFS (p < 0.001). In the multivariate analysis, high CRP, LDH, NLR, PIV, and SII independently predicted worse OS. Conclusions: Our findings confirm the prognostic utility of several inflammatory biomarkers in patients with cancer receiving ICIs, highlighting their potential for treatment stratification. Further studies are necessary to standardize cut-off values and validate these findings across broader, more diverse populations. Full article
(This article belongs to the Special Issue Novel Prognostic Biomarkers in Human Cancers: From Discovery to Application)
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17 pages, 3998 KiB  
Article
Multi-Algorithm Analysis Reveals Pyroptosis-Linked Genes as Pancreatic Cancer Biomarkers
by Kangtao Wang, Shanshan Han, Li Liu, Lian Zhao and Ingrid Herr
Cancers 2024, 16(2), 372; https://doi.org/10.3390/cancers16020372 - 15 Jan 2024
Cited by 1 | Viewed by 2103
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is often diagnosed at late stages, limiting treatment options and survival rates. Pyroptosis-related gene signatures hold promise as PDAC prognostic markers, but limited gene pools and small sample sizes hinder their utility. We aimed to enhance PDAC prognosis with [...] Read more.
Pancreatic ductal adenocarcinoma (PDAC) is often diagnosed at late stages, limiting treatment options and survival rates. Pyroptosis-related gene signatures hold promise as PDAC prognostic markers, but limited gene pools and small sample sizes hinder their utility. We aimed to enhance PDAC prognosis with a comprehensive multi-algorithm analysis. Using R, we employed natural language processing and latent Dirichlet allocation on PubMed publications to identify pyroptosis-related genes. We collected PDAC transcriptome data (n = 1273) from various databases, conducted a meta-analysis, and performed differential gene expression analysis on tumour and non-cancerous tissues. Cox and LASSO algorithms were used for survival modelling, resulting in a pyroptosis-related gene expression-based prognostic index. Laboratory and external validations were conducted. Bibliometric analysis revealed that pyroptosis publications focus on signalling pathways, disease correlation, and prognosis. We identified 357 pyroptosis-related genes, validating the significance of BHLHE40, IL18, BIRC3, and APOL1. Elevated expression of these genes strongly correlated with poor PDAC prognosis and guided treatment strategies. Our accessible nomogram model aids in PDAC prognosis and treatment decisions. We established an improved gene signature for pyroptosis-related genes, offering a novel model and nomogram for enhanced PDAC prognosis. Full article
(This article belongs to the Special Issue Novel Prognostic Biomarkers in Human Cancers: From Discovery to Application)
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Review

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22 pages, 741 KiB  
Review
Tumor-Derived Extracellular Vesicles as Liquid Biopsy for Diagnosis and Prognosis of Solid Tumors: Their Clinical Utility and Reliability as Tumor Biomarkers
by Prerna Dabral, Nobel Bhasin, Manish Ranjan, Maysoon M. Makhlouf and Zakaria Y. Abd Elmageed
Cancers 2024, 16(13), 2462; https://doi.org/10.3390/cancers16132462 - 5 Jul 2024
Cited by 3 | Viewed by 2298
Abstract
Early cancer detection and accurate monitoring are crucial to ensure increased patient survival. Recent research has focused on developing non-invasive biomarkers to diagnose cancer early and monitor disease progression at low cost and risk. Extracellular vesicles (EVs), nanosized particles secreted into extracellular spaces [...] Read more.
Early cancer detection and accurate monitoring are crucial to ensure increased patient survival. Recent research has focused on developing non-invasive biomarkers to diagnose cancer early and monitor disease progression at low cost and risk. Extracellular vesicles (EVs), nanosized particles secreted into extracellular spaces by most cell types, are gaining immense popularity as novel biomarker candidates for liquid cancer biopsy, as they can transport bioactive cargo to distant sites and facilitate intercellular communications. A literature search was conducted to discuss the current approaches for EV isolation and the advances in using EV-associated proteins, miRNA, mRNA, DNA, and lipids as liquid biopsies. We discussed the advantages and challenges of using these vesicles in clinical applications. Moreover, recent advancements in machine learning as a novel tool for tumor marker discovery are also highlighted. Full article
(This article belongs to the Special Issue Novel Prognostic Biomarkers in Human Cancers: From Discovery to Application)
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Other

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12 pages, 1826 KiB  
Systematic Review
Prognostic Significance of the Royal Marsden Hospital (RMH) Score in Patients with Cancer: A Systematic Review and Meta-Analysis
by Taha Koray Sahin, Alessandro Rizzo, Sercan Aksoy and Deniz Can Guven
Cancers 2024, 16(10), 1835; https://doi.org/10.3390/cancers16101835 - 11 May 2024
Cited by 125 | Viewed by 3318
Abstract
Background: Cancer remains a leading cause of death globally, necessitating the identification of prognostic biomarkers to guide treatment decisions. The Royal Marsden Hospital (RMH) score, based on readily available blood tests and clinical features, has emerged as a prognostic tool, although its performance [...] Read more.
Background: Cancer remains a leading cause of death globally, necessitating the identification of prognostic biomarkers to guide treatment decisions. The Royal Marsden Hospital (RMH) score, based on readily available blood tests and clinical features, has emerged as a prognostic tool, although its performance across variable clinical scenarios is not thoroughly delineated. Therefore, we aimed to systematically assess the association between RMH score and survival in cancer patients. Methods: We conducted a systematic literature search across Pubmed, Scopus, and Web of Science databases for studies published up to 15 February 2024. We performed a meta-analysis with the generic inverse variance method with a random-effects model and reported hazard ratios (HR) with 95% confidence intervals (CI). Results: Nineteen studies encompassing 127,230 patients were included. A higher RMH score was significantly associated with worse overall survival (OS) (HR: 2.09, 95% CI: 1.87–2.33, p < 0.001) and progression-free survival (PFS) (HR: 1.80, 95% CI: 1.48–2.18, p < 0.001). This association was consistent across various subgroups, including study population (clinical trial vs. real-world cohort), geographic region, and tumor type. Conclusion: This meta-analysis, including over a hundred thousand patients, demonstrates a negative association between a higher RMH score and survival in cancer patients. The RMH score holds promise as a readily available prognostic tool across diverse cancer types and clinical settings. Future research should focus on validating and refining this score to aid clinical decision-making. Full article
(This article belongs to the Special Issue Novel Prognostic Biomarkers in Human Cancers: From Discovery to Application)
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