Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
6.8
3.9
Journals
Biomedicines
Special Issues
Genomic Insights and Translational Opportunities for Human Cancers
share announcement

Genomic Insights and Translational Opportunities for Human Cancers

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Cancer Biology and Oncology".

Deadline for manuscript submissions: closed (31 May 2025) | Viewed by 5802

Special Issue Editors

Prof. Dr. Apostolos Zaravinos

E-Mail Website
Guest Editor
Cancer Genetics, Genomics and Systems Biology Laboratory, Basic and Translational Cancer Research Center (BTCRC), Nicosia 1516, Cyprus
Interests: cancer genomics; precision medicine; data science in genomics; next-generation sequencing; translational oncology; tumor immunology
Special Issues, Collections and Topics in MDPI journals
Dr. Ilias Georgakopoulos-Soares

E-Mail Website
Guest Editor
Department of Biochemistry and Molecular Biology, Penn State College of Medicine, Hershey, PA 17033-0850, USA
Interests: bioinformatics; genomics; machine learning

Special Issue Information

Dear Colleagues,

The field of cancer genomics has undergone a revolution in recent years with the advent of next-generation sequencing technologies and the development of new algorithms that can analyze large amounts of genomic information. These advances have enabled researchers to sequence cancer genomes with unprecedented accuracy, leading to new insights into the genetic basis of cancer, and opening up new avenues for cancer diagnosis, treatment, and prevention. By understanding the specific genetic mutations and transcriptomic changes that are present in a particular cancer, scientists can also develop more targeted and effective therapies. Additionally, liquid biopsies have gathered excitement for their potential utility in cancer detection, monitoring, and patient stratification. This Special Issue on genomic insights into human cancer focuses on the latest advances in cancer genomics, with an emphasis on the translational potential of these findings. The articles in this Special Issue will cover recent advances in cancer genomics, including: (i) advances in bioinformatics algorithms, such as machine learning and artificial intelligence, and their application in cancer research; (ii) novel cancer biomarkers, particularly those pertaining to liquid biopsies; and (iii) other translational research relating to cancer.

Dr. Apostolos Zaravinos
Dr. Ilias Georgakopoulos-Soares
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. Biomedicines 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

  • genomics
  • cancer genomics
  • biomarkers
  • machine learning
  • bioinformatics
  • liquid biopsies
  • cell-free DNA
  • cell-free RNA

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.
  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

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

Published Papers (3 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

23 pages, 8434 KiB  
Article
Duodenal Adenocarcinoma Is Characterized by Acidity, High Infiltration of Macrophage, and Activated Linc01559–GRSF1 Axis
by Xinxin Huang, Ying Shi, Zekun Liu, Yihang Wu, Xiaotong Luo, Dongwen Chen, Zhengyu Wei, Chong Chen, Huaiqiang Ju, Xiaojian Wu, Xuanhui Liu, Zhanhong Chen and Peishan Hu
Biomedicines 2025, 13(7), 1611; https://doi.org/10.3390/biomedicines13071611 - 30 Jun 2025
Viewed by 335
Abstract
Background: Duodenal adenocarcinoma (DA) is often insidious due to the low rate of early diagnosis and because the mechanisms that underlie its malignant progression are poorly understood. The tumor microenvironment (TME) plays a crucial regulatory role in promoting tumor malignancy. Hence, this [...] Read more.
Background: Duodenal adenocarcinoma (DA) is often insidious due to the low rate of early diagnosis and because the mechanisms that underlie its malignant progression are poorly understood. The tumor microenvironment (TME) plays a crucial regulatory role in promoting tumor malignancy. Hence, this study aimed to identify novel biomarkers for early diagnosis and potential therapeutic targets for DA. Methods: Surgical resection samples and normal tissues from DA patients were collected for RNA sequencing (RNA-seq). The characteristics of TME in DA patients were analyzed, and the differentially expressed long non-coding RNAs (lncRNA) were screened. Functional experiments were performed to verify the relationship between Linc01559, G-rich sequence binding factor 1 (GRSF1), and tumor malignant phenotype. Results: The present study revealed that DA exhibits a significantly upregulated expression of acidic environment markers and a high degree of macrophage infiltration. Further investigation revealed that macrophages upregulate the expression of the long noncoding RNA, Linc01559, in DA through the STAT3/c-MYC signaling pathway, thereby promoting malignant phenotypes such as invasion, metastasis, tumor stemness, and apoptosis. The interaction between GRSF1 and Linc01559 was subsequently confirmed using RNA pulldown-mass spectrometry. It was further revealed that Linc01559 promotes the malignant phenotype of duodenal cancer cells through its interaction with GRSF1. Conclusions: These findings demonstrate that the acidic microenvironment influences the phenotype of DA by regulating the Linc01559–GRSF1 axis. Therefore, these findings provide potential targets for the early detection and treatment of DA. Full article
(This article belongs to the Special Issue Genomic Insights and Translational Opportunities for Human Cancers)
►▼ Show Figures

Figure 1

32 pages, 16475 KiB  
Article
Comprehensive Analysis of Granzymes and Perforin Family Genes in Multiple Cancers
by Manvita Mareboina, Katrina Bakhl, Stephanie Agioti, Nelson S. Yee, Ilias Georgakopoulos-Soares and Apostolos Zaravinos
Biomedicines 2025, 13(2), 408; https://doi.org/10.3390/biomedicines13020408 - 7 Feb 2025
Viewed by 1535
Abstract
Background/Objectives: Cancer remains a significant global health concern, with immunotherapies emerging as promising treatments. This study explored the role of perforin-1 (PRF1) and granzymes A, B and K (GZMA, GZMB and GZMK) in cancer biology, focusing on their [...] Read more.
Background/Objectives: Cancer remains a significant global health concern, with immunotherapies emerging as promising treatments. This study explored the role of perforin-1 (PRF1) and granzymes A, B and K (GZMA, GZMB and GZMK) in cancer biology, focusing on their impact on tumor cell death and immune response modulation. Methods: Through a comprehensive genomic analysis across various cancer types, we explored the differential expression, mutation profiles and methylation patterns of these genes, providing insights into their potential as therapeutic targets. Furthermore, we investigated their association with immune cell infiltration and pathway activation within the tumor microenvironment in each tumor type. Results: Our findings revealed distinct expression patterns and prognostic implications for PRF1, GZMA, GZMB and GZMK across different cancers, highlighting their multifaceted roles in tumor immunity. We found increased immune infiltration across all tumor types and significant correlations between the genes of interest and cytotoxic T cells, as well as the most significant survival outcomes in breast cancer. We also show that granzymes and perforin-1 are significantly associated with indicators of immunosuppression and T cell dysfunction within patient cohorts. In skin melanoma, glioblastoma, kidney and bladder cancers, we found significant correlations between the genes of interest and patient survival after receiving immune-checkpoint inhibition therapy. Additionally, we identified potential associations between the mRNA expression levels of these genes and drug sensitivity. Conclusions: Overall, this study enhances our understanding of the molecular mechanisms underlying tumor immunity and provides valuable insights into the potential therapeutic implications of PRF1, GZMA, GZMB and GZMK in cancer treatment. Full article
(This article belongs to the Special Issue Genomic Insights and Translational Opportunities for Human Cancers)
►▼ Show Figures

Figure 1

19 pages, 1868 KiB  
Article
A Comparison of Tools That Identify Tumor Cells by Inferring Copy Number Variations from Single-Cell Experiments in Pancreatic Ductal Adenocarcinoma
by Daisy J. A. Oketch, Matteo Giulietti and Francesco Piva
Biomedicines 2024, 12(8), 1759; https://doi.org/10.3390/biomedicines12081759 - 5 Aug 2024
Cited by 1 | Viewed by 2879
Abstract
Single-cell RNA sequencing (scRNA-seq) technique has enabled detailed analysis of gene expression at the single cell level, enhancing the understanding of subtle mechanisms that underly pathologies and drug resistance. To derive such biological meaning from sequencing data in oncology, some critical processing must [...] Read more.
Single-cell RNA sequencing (scRNA-seq) technique has enabled detailed analysis of gene expression at the single cell level, enhancing the understanding of subtle mechanisms that underly pathologies and drug resistance. To derive such biological meaning from sequencing data in oncology, some critical processing must be performed, including identification of the tumor cells by markers and algorithms that infer copy number variations (CNVs). We compared the performance of sciCNV, InferCNV, CopyKAT and SCEVAN tools that identify tumor cells by inferring CNVs from scRNA-seq data. Sequencing data from Pancreatic Ductal Adenocarcinoma (PDAC) patients, adjacent and healthy tissues were analyzed, and the predicted tumor cells were compared to those identified by well-assessed PDAC markers. Results from InferCNV, CopyKAT and SCEVAN overlapped by less than 30% with InferCNV showing the highest sensitivity (0.72) and SCEVAN the highest specificity (0.75). We show that the predictions are highly dependent on the sample and the software used, and that they return so many false positives hence are of little use in verifying or filtering predictions made via tumor biomarkers. We highlight how critical this processing can be, warn against the blind use of these software and point out the great need for more reliable algorithms. Full article
(This article belongs to the Special Issue Genomic Insights and Translational Opportunities for Human Cancers)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop