Submit to Special Issue Submit Abstract to Special Issue Review for Biology Propose a Special Issue

Journal Menu

Journal Browser

► Journal Browser

New Sight in Cancer Genetics

Special Issue Editors
Special Issue Information
Keywords
Benefits of Publishing in a Special Issue
Published Papers

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

Deadline for manuscript submissions: 31 January 2025 | Viewed by 13674

Share This Special Issue

Special Issue Editors

Prof. Dr. Ilda Patrícia Ribeiro

E-Mail Website
Guest Editor

1. Cytogenetics and Genomics Laboratory, Institute of Cellular and Molecular Biology, Faculty of Medicine, University of Coimbra, 3000-548 Coimbra, Portugal
2. Institute for Clinical and Biomedical Research (iCBR), Center of Investigation on Environment Genetics and Oncobiology (CIMAGO), Faculty of Medicine (FMUC), University of Coimbra, 3004-531 Coimbra, Portugal
Interests: genomic; omics in cancer; head and neck cancer; methylation and genetic mechanisms; oncobiology; copy number alterations; prognosis biomarkers

Prof. Dr. Isabel Marques Carreira

E-Mail Website
Guest Editor

1. Cytogenetics and Genomics Laboratory, Institute of Cellular and Molecular Biology, Faculty of Medicine, University of Coimbra, 3000-548 Coimbra, Portugal
2. Institute for Clinical and Biomedical Research (iCBR), Center of Investigation on Environment Genetics and Oncobiology (CIMAGO), Faculty of Medicine (FMUC), University of Coimbra, 3004-531 Coimbra, Portugal
Interests: cytogenetics; human genetics, cancer genetics, oncobiology

Prof. Dr. Alberto Orfao

E-Mail Website1 Website2
Guest Editor

Department of Medicine, Cancer Research Center (IBMCC-CSIC/USAL), CIBERONC and Institute for Biomedical Research of Salamanca (IBSAL), University of Salamanca (USAL), Salamanca, Spain
Interests: leukemia; lymphoma; early cancer diagnosis; immunophenotyping; genetics; diagnosis; prognosis; minimal residual disease; immune monitoring; CART; EuroFlow
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In general, it has remained challenging to treat cancer despite the innovative and revolutionary research taking place worldwide. The remarkable advances over the last decade in multi-omics technologies, especially next-generation sequencing (NGS) and genome analysis, have led to significant improvements in our knowledge of the molecular mechanisms of cancer. Together with bioinformatic tools and Artificial Intelligence, it is possible to use computer programming to improve cancer diagnosis, drug development, and precision medicine.

This Special Issue aims to present robust molecular signatures and biomarkers of unmet clinical problems in cancer field, mostly focusing on predicting treatment response, making early diagnosis and assessing disease prognosis through the use of different omics approaches, such as genomic, epigenomic, transcriptomis, proteomic, metabolomic methods. We welcome original research articles and reviews to this Special Issue. Research areas may include (but are not limited to) the following topics: new developments in cancer research in order to identify biomarkers and molecular signatures with high possibility of clinical application and therapeutic development.

We look forward to receiving your contributions.

Prof. Dr. Ilda Patrícia Ribeiro
Prof. Dr. Isabel Marques Carreira
Prof. Dr. Alberto Orfao
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. 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

genomic and epigenetic characterization
diagnosis and prognosis biomarkers
omics profiles
genetic and genomic signature
molecular heterogeneity
molecular targeted therapy
oncogenic signaling pathways
copy number alterations and mutational landscape
chromosome abnormalities

Benefits of Publishing in a Special Issue

Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.

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

Published Papers (7 papers)

Download All Papers

Order results

Result details

Show export options Show export options

Select all

Export citation of selected articles as:

Research

Jump to: Review

15 pages, 1265 KiB

Open AccessArticle

Polygenic Risk Score Improves Melanoma Risk Assessment in a Patient Cohort from the Veneto Region of Italy

by Stefania Pellegrini, Thomas P. Potjer, Paola Del Bianco, Antonella Vecchiato, Alessio Fabozzi, Luisa Piccin, Debora Tonello, Nienke van der Stoep, Emily Tinsley, Maria Teresa Landi, Mark M. Iles and Chiara Menin

Biology 2024, 13(11), 954; https://doi.org/10.3390/biology13110954 - 20 Nov 2024

Viewed by 688

Abstract

Recent genome-wide association studies (GWASs) have identified many single nucleotide polymorphisms (SNPs) that alone weakly affect melanoma risk, but their combined effect on a polygenic risk score (PRS) can have a far bigger impact on estimating risk. However, the PRS is not yet at the stage of being utilized in clinical practice, and further evidence is needed. In this study, 270 melanoma patients fulfilling the criteria for a suspected genetic predisposition but with a negative genetic test for high/medium-penetrance genes were genotyped for 57 SNPs selected in previous GWASs to construct a PRS model. We found a significantly higher mean PRS₅₇ in all melanoma cases than in controls (0.58 vs. 0.00, p < 0.001), and the mean PRS₅₇ in multiple primary melanoma cases was twice that in single melanoma cases (0.689 vs. 0.362, p = 0.025). Interestingly, our results confirm the association of the PRS₅₇ not only with other melanoma risk factors but also with a younger age at diagnosis. This evidence supports the potentially powerful discriminative role of PRS in the selection of high-risk patients who should undergo stricter surveillance protocols. Full article

(This article belongs to the Special Issue New Sight in Cancer Genetics)

► Show Figures

Figure 1

18 pages, 3069 KiB

Open AccessArticle

Paired Primary and Recurrent Rhabdoid Meningiomas: Cytogenetic Alterations, BAP1 Gene Expression Profile and Patient Outcome

by Patricia Alejandra Garrido Ruiz, Álvaro Otero Rodriguez, Luis Antonio Corchete, Victoria Zelaya Huerta, Alejandro Pasco Peña, Cristina Caballero Martínez, Joaquín González-Carreró Fojón, Inmaculada Catalina Fernández, Juan Carlos López Duque, Laura Zaldumbide Dueñas, Lorena Mosteiro González, María Aurora Astudillo, Aurelio Hernández-Laín, Emma Natalia Camacho Urkaray, María Amparo Viguri Diaz, Alberto Orfao and María Dolores Tabernero

Biology 2024, 13(5), 350; https://doi.org/10.3390/biology13050350 - 16 May 2024

Viewed by 1172

Abstract

Rhabdoid meningiomas (RM) are a rare meningioma subtype with a heterogeneous clinical course which is more frequently associated with recurrence, even among tumors undergoing-complete surgical removal. Here, we retrospectively analyzed the clinical-histopathological and cytogenetic features of 29 tumors, from patients with recurrent (seven primary and 14 recurrent tumors) vs. non-recurrent RM (n = 8). Recurrent RM showed one (29%), two (29%) or three (42%) recurrences. BAP1 loss of expression was found in one third of all RM at diagnosis and increased to 100% in subsequent tumor recurrences. Despite both recurrent and non-recurrent RM shared chromosome 22 losses, non-recurrent tumors more frequently displayed extensive losses of chromosome 19p (62%) and/or 19q (50%), together with gains of chromosomes 20 and 21 (38%, respectively), whereas recurrent RM (at diagnosis) displayed more complex genotypic profiles with extensive losses of chromosomes 1p, 14q, 18p, 18q (67% each) and 21p (50%), together with focal gains at chromosome 17q22 (67%). Compared to paired primary tumors, recurrent RM samples revealed additional losses at chromosomes 16q and 19p (50% each), together with gains at chromosomes 1q and 17q in most recurrent tumors (67%, each). All deceased recurrent RM patients corresponded to women with chromosome 17q gains, although no statistical significant differences were found vs. the other RM patients. Full article

(This article belongs to the Special Issue New Sight in Cancer Genetics)

► Show Figures

Graphical abstract

23 pages, 7697 KiB

Open AccessArticle

An Exploration of Small Molecules That Bind Human Single-Stranded DNA Binding Protein 1

by Zachariah P. Schuurs, Alexander P. Martyn, Carl P. Soltau, Sam Beard, Esha T. Shah, Mark N. Adams, Laura V. Croft, Kenneth J. O’Byrne, Derek J. Richard and Neha S. Gandhi

Biology 2023, 12(11), 1405; https://doi.org/10.3390/biology12111405 - 6 Nov 2023

Cited by 3 | Viewed by 2446

Abstract

Human single-stranded DNA binding protein 1 (hSSB1) is critical to preserving genome stability, interacting with single-stranded DNA (ssDNA) through an oligonucleotide/oligosaccharide binding-fold. The depletion of hSSB1 in cell-line models leads to aberrant DNA repair and increased sensitivity to irradiation. hSSB1 is over-expressed in several types of cancers, suggesting that hSSB1 could be a novel therapeutic target in malignant disease. hSSB1 binding studies have focused on DNA; however, despite the availability of 3D structures, small molecules targeting hSSB1 have not been explored. Quinoline derivatives targeting hSSB1 were designed through a virtual fragment-based screening process, synthesizing them using AlphaLISA and EMSA to determine their affinity for hSSB1. In parallel, we further screened a structurally diverse compound library against hSSB1 using the same biochemical assays. Three compounds with nanomolar affinity for hSSB1 were identified, exhibiting cytotoxicity in an osteosarcoma cell line. To our knowledge, this is the first study to identify small molecules that modulate hSSB1 activity. Molecular dynamics simulations indicated that three of the compounds that were tested bound to the ssDNA-binding site of hSSB1, providing a framework for the further elucidation of inhibition mechanisms. These data suggest that small molecules can disrupt the interaction between hSSB1 and ssDNA, and may also affect the ability of cells to repair DNA damage. This test study of small molecules holds the potential to provide insights into fundamental biochemical questions regarding the OB-fold. Full article

(This article belongs to the Special Issue New Sight in Cancer Genetics)

► Show Figures

Graphical abstract

13 pages, 1753 KiB

Open AccessArticle

3D Chromatin Architecture Re-Wiring at the CDH3/CDH1 Loci Contributes to E-Cadherin to P-Cadherin Expression Switch in Gastric Cancer

by Celina São José, Carla Pereira, Marta Ferreira, Ana André, Hugo Osório, Irene Gullo, Fátima Carneiro and Carla Oliveira

Biology 2023, 12(6), 803; https://doi.org/10.3390/biology12060803 - 31 May 2023

Cited by 2 | Viewed by 2016

Abstract

Cadherins are cell–cell adhesion molecules, fundamental for cell architecture and polarity. E-cadherin to P-cadherin switch can rescue adherens junctions in epithelial tumours. Herein, we disclose a mechanism for E-cadherin to P-cadherin switch in gastric cancers. CDH1 and CDH3 mRNA expression was obtained from 42 gastric tumours’ RNA-seq data. CRISPR-Cas9 was used to knock out CDH1 and a putative regulatory element. CDH1-depleted and parental cells were submitted to proteomics and enrichment GO terms analysis; ATAC-seq/4C-seq with a CDH1 promoter viewpoint to assess chromatin accessibility and conformation; and RT-PCR/flow cytometry to assess CDH1/E-cadherin and CDH3/P-cadherin expression. In 42% of gastric tumours analysed, CDH1 to CDH3 switch was observed. CDH1 knockout triggered CDH1/E-cadherin complete loss and CDH3/P-cadherin expression increase at plasma membrane. This switch, likely rescuing adherens junctions, increased cell migration/proliferation, commonly observed in aggressive tumours. E- to P-cadherin switch accompanied increased CDH1 promoter interactions with CDH3–eQTL, absent in normal stomach and parental cells. CDH3–eQTL deletion promotes CDH3/CDH1 reduced expression. These data provide evidence that loss of CDH1/E-cadherin expression alters the CDH3 locus chromatin conformation, allowing a CDH1 promoter interaction with a CDH3-eQTL, and promoting CDH3/P-cadherin expression. These data highlight a novel mechanism triggering E- to P-cadherin switch in gastric cancer. Full article

(This article belongs to the Special Issue New Sight in Cancer Genetics)

► Show Figures

Figure 1

Review

Jump to: Research

19 pages, 1316 KiB

Open AccessReview

The Protein Corona on Nanoparticles for Tumor Targeting in Prostate Cancer—A Review of the Literature and Experimental Trial Protocol

by Giulio Bevilacqua, Roberta Corvino, Anna Laura Capriotti, Carmela Maria Montone, Martina Moriconi, Stefano Salciccia, Valentina Brunelli, Valerio Santarelli, Beatrice Sciarra, Aldo Laganà, Daniele Santini, Alessandro Sciarra and Alessandro Gentilucci

Biology 2024, 13(12), 1024; https://doi.org/10.3390/biology13121024 - 7 Dec 2024

Viewed by 579

Abstract

The National Cancer Institute (NCI) recognizes the potential of technologies based on the use of nanoparticles (NPs) in revolutionizing clinical approaches to the diagnosis and prognosis of cancer. Recent research suggests that once NPs come into contact with the biological fluid of cancer patients, they are covered by proteins, forming a “protein corona” composed of hundreds of plasma proteins. The concept of a personalized, disease-specific protein corona, demonstrating substantial differences in NP corona profiles between patients with and without cancer, has been introduced. We developed the design of an experimental prospective single-center study with patients allocated in a 1:1:1 ratio of one of three arms: untreated patients with benign prostatic hyperplasia (BPH), untreated patients with non-metastatic prostate cancer (PCa), and metastatic prostate cancer patients starting systemic therapies with new androgen-targeted agents or taxanes. The protocol aims to develop and implement sensitive nanotools with two distinct objectives: First, to design NPs capable of selectively binding and detecting biomarkers in order to build a predictive diagnostic model to effectively discriminate between patient sera affected by BPH and PCa. Secondly, within the population with PCa, in the case of initial advanced metastatic diagnosis, the objective is to find biomarkers capable of predicting the response to systemic treatments to improve the precision and efficiency of monitoring treatment outcomes. For protein and metabolite corona experiments, we developed a cross-reactive sensor array platform with cancer detection capacity made of three liposomal formulations with different surface charges. For proteomic-NP studies, proteins were identified and quantified using nano-high-performance LC (nanoHPLC) coupled with MS/MS (nanoHPLC−MS/MS). Metabolites were instead analyzed using an untargeted metabolomic approach. Compared with previous review articles, the novelty of this review is represented by the analysis of the possible clinical applications of protein corona NPs focused on PCa and the presentation of a new clinical protocol in the metastatic phase of PCa. Full article

(This article belongs to the Special Issue New Sight in Cancer Genetics)

► Show Figures

Figure 1

33 pages, 1407 KiB

Open AccessReview

Proteomic Profile of Endometrial Cancer: A Scoping Review

by Beatriz Serambeque, Catarina Mestre, Kristina Hundarova, Carlos Miguel Marto, Bárbara Oliveiros, Ana Rita Gomes, Ricardo Teixo, Ana Sofia Carvalho, Maria Filomena Botelho, Rune Matthiesen, Maria João Carvalho and Mafalda Laranjo

Biology 2024, 13(8), 584; https://doi.org/10.3390/biology13080584 - 1 Aug 2024

Viewed by 1975

Abstract

Proteomics can be a robust tool in protein identification and regulation, allowing the discovery of potential biomarkers. In clinical practice, the management of endometrial cancer can be challenging. Thus, identifying promising markers could be beneficial, helping both in diagnosis and prognostic stratification, even predicting the response to therapy. Therefore, this manuscript systematically reviews the existing evidence of the proteomic profile of human endometrial cancer. The literature search was conducted via Medline (through PubMed) and the Web of Science. The inclusion criteria were clinical, in vitro, and in vivo original studies reporting proteomic analysis using all types of samples to map the human endometrial cancer proteome. A total of 55 publications were included in this review. Most of the articles carried out a proteomic analysis on endometrial tissue, serum and plasma samples, which enabled the identification of several potential diagnostic and prognostic biomarkers. In addition, eight articles were analyzed regarding the identified proteins, where three studies showed a strong correlation, sharing forty-five proteins. This analysis also allowed the identification of the 10 most frequently reported proteins in these studies: EGFR, PGRMC1, CSE1L, MYDGF, STMN1, CASP3 ANXA2, YBX1, ANXA1, and MYH11. Proteomics-based approaches pointed out potential diagnostic and prognostic candidates for endometrial cancer. However, there is a lack of studies exploring novel therapeutic targets. Full article

(This article belongs to the Special Issue New Sight in Cancer Genetics)

► Show Figures

Figure 1

15 pages, 816 KiB

Open AccessReview

Current Applications and Challenges of Next-Generation Sequencing in Plasma Circulating Tumour DNA of Ovarian Cancer

by Ricardo Roque, Ilda Patrícia Ribeiro, Margarida Figueiredo-Dias, Charlie Gourley and Isabel Marques Carreira

Biology 2024, 13(2), 88; https://doi.org/10.3390/biology13020088 - 31 Jan 2024

Cited by 1 | Viewed by 3494

Abstract

Circulating tumour DNA (ctDNA) facilitates longitudinal study of the tumour genome, which, unlike tumour tissue biopsies, globally reflects intratumor and intermetastatis heterogeneity. Despite its costs, next-generation sequencing (NGS) has revolutionised the study of ctDNA, ensuring a more comprehensive and multimodal approach, increasing data collection, and introducing new variables that can be correlated with clinical outcomes. Current NGS strategies can comprise a tumour-informed set of genes or the entire genome and detect a tumour fraction as low as 10⁻⁵. Despite some conflicting studies, there is evidence that ctDNA levels can predict the worse outcomes of ovarian cancer (OC) in both early and advanced disease. Changes in those levels can also be informative regarding treatment efficacy and tumour recurrence, capable of outperforming CA-125, currently the only universally utilised plasma biomarker in high-grade serous OC (HGSOC). Qualitative evaluation of sequencing shows that increasing copy number alterations and gene variants during treatment may correlate with a worse prognosis in HGSOC. However, following tumour clonality and emerging variants during treatment poses a more unique opportunity to define treatment response, select patients based on their emerging resistance mechanisms, like BRCA secondary mutations, and discover potential targetable variants. Sequencing of tumour biopsies and ctDNA is not always concordant, likely as a result of clonal heterogeneity, which is better captured in the plasma samples than it is in a large number of biopsies. These incoherences may reflect tumour clonality and reveal the acquired alterations that cause treatment resistance. Cell-free DNA methylation profiles can be used to distinguish OC from healthy individuals, and NGS methylation panels have been shown to have excellent diagnostic capabilities. Also, methylation signatures showed promise in explaining treatment responses, including BRCA dysfunction. ctDNA is evolving as a promising new biomarker to track tumour evolution and clonality through the treatment of early and advanced ovarian cancer, with potential applicability in prognostic prediction and treatment selection. While its role in HGSOC paves the way to clinical applicability, its potential interest in other histological subtypes of OC remains unknown. Full article

(This article belongs to the Special Issue New Sight in Cancer Genetics)

► Show Figures

Journal Menu

Journal Browser

New Sight in Cancer Genetics

Share This Special Issue

Special Issue Editors

Special Issue Information

Keywords

Benefits of Publishing in a Special Issue

Published Papers (7 papers)

Research

Review

Further Information

Guidelines

MDPI Initiatives

Follow MDPI