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Biomarkers in Hematological and Oncological Malignancies: Identification, Validation and Involvement in Molecular Pathways

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Oncology".

Deadline for manuscript submissions: closed (31 March 2021) | Viewed by 11994

Special Issue Editor

Dr. Peppino Mirabelli

E-Mail Website
Guest Editor
SYNLAB IRCCS SDN, via E. Gianturco n. 113, 80143 Napoli, Italy
Interests: flow cytometry; experimental hematology; cellular therapy; hemopoiesis; leukemia diagnosis
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear colleagues,

The identification and validation of biomarkers in hematological and oncological research are an intensely active field of medical research. Indeed, biomarkers have a number of applications in clinical practice, including risk assessment, screening, differential diagnosis, determination of prognosis, prediction of response to treatment, and monitoring of progression of the disease. In recent years, an increasing number of novel biomarkers were identified thanks to the advent of high-throughput technologies for genomics, proteomics, transcriptomics analyses. However, much work is still needed for their validation as well as identification of the altered molecular pathways in which they are involved. In this context, research biobanks will have a critical role in supporting the identification and validation of biomarkers as well as for accelerating their translation into clinical practice, other than supporting the reproducibility of data thanks to the harmonization of the procedures applied in sample processing. The aim of this special issue is to present scientific contributions including but not limited to the following arguments: biobanks for supporting translational research; identification and validation of biomarkers involved in leukemogenesis and oncogenesis; prospective evaluation of biomarkers for precision medicine and personalized medicine; biomarkers identification and validation for possible theranostic strategies. Finally, articles regarding the novel class of non-invasive imaging biomarkers, obtained from advanced imaging technologies (high field magnetic resonance, dual source computed tomography, positron emission tomography) will be also welcome.

Dr. Peppino Mirabelli
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. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. 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

  • Diagnostic marker
  • Prognostic marker
  • Molecular pathway
  • Leukemia
  • Epithelial cancers
  • Melanoma
  • Lymphoma
  • Biobanking
  • Immunology
  • Flow cytometry
  • Imaging parameters

Published Papers (3 papers)

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Research

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17 pages, 2917 KiB  
Article
Construction and Validation of a Prognostic Gene-Based Model for Overall Survival Prediction in Hepatocellular Carcinoma Using an Integrated Statistical and Bioinformatic Approach
by Eskezeia Yihunie Dessie, Siang-Jyun Tu, Hui-Shan Chiang, Jeffrey J.P. Tsai, Ya-Sian Chang, Jan-Gowth Chang and Ka-Lok Ng
Int. J. Mol. Sci. 2021, 22(4), 1632; https://doi.org/10.3390/ijms22041632 - 05 Feb 2021
Cited by 8 | Viewed by 3421
Abstract
Hepatocellular carcinoma (HCC) is one of the most common lethal cancers worldwide and is often related to late diagnosis and poor survival outcome. More evidence is demonstrating that gene-based prognostic models can be used to predict high-risk HCC patients. Therefore, our study aimed [...] Read more.
Hepatocellular carcinoma (HCC) is one of the most common lethal cancers worldwide and is often related to late diagnosis and poor survival outcome. More evidence is demonstrating that gene-based prognostic models can be used to predict high-risk HCC patients. Therefore, our study aimed to construct a novel prognostic model for predicting the prognosis of HCC patients. We used multivariate Cox regression model with three hybrid penalties approach including least absolute shrinkage and selection operator (Lasso), adaptive lasso and elastic net algorithms for informative prognostic-related genes selection. Then, the best subset regression was used to identify the best prognostic gene signature. The prognostic gene-based risk score was constructed using the Cox coefficient of the prognostic gene signature. The model was evaluated by Kaplan–Meier (KM) and receiver operating characteristic curve (ROC) analyses. A novel four-gene signature associated with prognosis was identified and the risk score was constructed based on the four-gene signature. The risk score efficiently distinguished the patients into a high-risk group with poor prognosis. The time-dependent ROC analysis revealed that the risk model had a good performance with an area under the curve (AUC) of 0.780, 0.732, 0.733 in 1-, 2- and 3-year prognosis prediction in The Cancer Genome Atlas (TCGA) dataset. Moreover, the risk score revealed a high diagnostic performance to classify HCC from normal samples. The prognosis and diagnosis prediction performances of risk scores were verified in external validation datasets. Functional enrichment analysis of the four-gene signature and its co-expressed genes involved in the metabolic and cell cycle pathways was constructed. Overall, we developed a novel-gene-based prognostic model to predict high-risk HCC patients and we hope that our findings can provide promising insight to explore the role of the four-gene signature in HCC patients and aid risk classification. Full article
(This article belongs to the Special Issue Biomarkers in Hematological and Oncological Malignancies: Identification, Validation and Involvement in Molecular Pathways)
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Review

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28 pages, 774 KiB  
Review
Immunological Prognostic Factors in Multiple Myeloma
by Dominika Bębnowska, Rafał Hrynkiewicz, Ewelina Grywalska, Marcin Pasiarski, Barbara Sosnowska-Pasiarska, Iwona Smarz-Widelska, Stanisław Góźdź, Jacek Roliński and Paulina Niedźwiedzka-Rystwej
Int. J. Mol. Sci. 2021, 22(7), 3587; https://doi.org/10.3390/ijms22073587 - 30 Mar 2021
Cited by 15 | Viewed by 3938
Abstract
Multiple myeloma (MM) is a plasma cell neoplasm characterized by an abnormal proliferation of clonal, terminally differentiated B lymphocytes. Current approaches for the treatment of MM focus on developing new diagnostic techniques; however, the search for prognostic markers is also crucial. This enables [...] Read more.
Multiple myeloma (MM) is a plasma cell neoplasm characterized by an abnormal proliferation of clonal, terminally differentiated B lymphocytes. Current approaches for the treatment of MM focus on developing new diagnostic techniques; however, the search for prognostic markers is also crucial. This enables the classification of patients into risk groups and, thus, the selection of the most optimal treatment method. Particular attention should be paid to the possible use of immune factors, as the immune system plays a key role in the formation and course of MM. In this review, we focus on characterizing the components of the immune system that are of prognostic value in MM patients, in order to facilitate the development of new diagnostic and therapeutic directions. Full article
(This article belongs to the Special Issue Biomarkers in Hematological and Oncological Malignancies: Identification, Validation and Involvement in Molecular Pathways)
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24 pages, 1830 KiB  
Review
Estrogen Receptor Beta: The Promising Biomarker and Potential Target in Metastases
by Ana Božović, Vesna Mandušić, Lidija Todorović and Milena Krajnović
Int. J. Mol. Sci. 2021, 22(4), 1656; https://doi.org/10.3390/ijms22041656 - 06 Feb 2021
Cited by 40 | Viewed by 4188
Abstract
The discovery of the Estrogen Receptor Beta (ERβ) in 1996 opened new perspectives in the diagnostics and therapy of different types of cancer. Here, we present a review of the present research knowledge about its role in endocrine-related cancers: breast, prostate, and thyroid, [...] Read more.
The discovery of the Estrogen Receptor Beta (ERβ) in 1996 opened new perspectives in the diagnostics and therapy of different types of cancer. Here, we present a review of the present research knowledge about its role in endocrine-related cancers: breast, prostate, and thyroid, and colorectal cancers. We also discuss the reasons for the controversy of its role in carcinogenesis and why it is still not in use as a biomarker in clinical practice. Given that the diagnostics and therapy would benefit from the introduction of new biomarkers, we suggest ways to overcome the contradictions in elucidating the role of ERβ. Full article
(This article belongs to the Special Issue Biomarkers in Hematological and Oncological Malignancies: Identification, Validation and Involvement in Molecular Pathways)
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