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Biomedicines
Special Issues
Multiomics Approaches for Translational Medicine
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Multiomics Approaches for Translational Medicine

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Molecular and Translational Medicine".

Deadline for manuscript submissions: closed (31 July 2023) | Viewed by 3739

Special Issue Editor

Dr. Maxim Sorokin

E-Mail Website
Guest Editor
1. Laboratory for Clinical and Genomic Bioinformatics, Institute for Personalized Oncology, Sechenov University, Moscow, Russia
2. Laboratory for Translational Genomic Bioinformatics, Moscow Institute of Physics and Technology, Dolgoprudny, Moscow, Russia
3. Department of Bioinformatics and Molecular Networks, OmicsWay Corp., Walnut, CA, USA
Interests: translational oncology; cancer bioinformatics; RNA sequencing; transcriptomics; pathway analysis; gene expression analysis

Special Issue Information

Dear Colleagues,

Multiple high-throughput methods for molecular profiling of biological samples have been developed during the last two decades, including various sequencing, microarray, proteomic, and proteogenomic assays. However, so far, only a few have been implemented into clinical practice and guidelines, e.g., exome and target panel sequencing for cancer diagnostics. At the same time, other high-throughput methods, such as RNA sequencing for gene expression profiling and fusion detection, as well as various proteomic assays, provide relevant information on pathological biosamples, allowing discovery and implementation of novel prognostic, diagnostic, and predictive biomarkers. This Special Issue will cover a broad range of experimental and analytical high-throughput tools to be applied to human disease.

We invite researchers to contribute original research articles as well as review articles on the use of mics approaches to study human disease with a special focus on oncology. We welcome manuscripts from, but not limited to, the following subtopics: discovery of novel biomarkers; development of bioinformatic tools for the analysis of multidimensional omics datasets; pathway and whole-interactome analysis; novel methodologies for high-throughput molecular profiling of human biosamples; functional analysis of multiomics datasets.

Dr. Maxim Sorokin
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. 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

  • translational medicine
  • high-throughput molecular profiling
  • biomarkers
  • omics datasets
  • bioinformatics
  • precision medicine
  • interactome analysis
  • pathway analysis
  • sequencing
  • proteomics

Published Papers (2 papers)

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Research

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25 pages, 23246 KiB  
Article
Cyclin Dependent Kinase Inhibitor 2A Genetic and Epigenetic Alterations Interfere with Several Immune Components and Predict Poor Clinical Outcome
by Mohamed A. Soltan, Ahmad A. Alhanshani, Ayed A. Shati, Youssef A. Alqahtani, Dalal Sulaiman Alshaya, Jawaher Alharthi, Sarah Awwadh Altalhi, Eman Fayad, Mohamed Samir A. Zaki and Refaat A. Eid
Biomedicines 2023, 11(8), 2254; https://doi.org/10.3390/biomedicines11082254 - 11 Aug 2023
Cited by 1 | Viewed by 1056
Abstract
Cyclin dependent kinase inhibitor 2A (CDKN2A) is a well-known tumor suppressor gene as it functions as a cell cycle regulator. While several reports correlate the malfunction of CDKN2A with the initiation and progression of several types of human tumors, there is a lack [...] Read more.
Cyclin dependent kinase inhibitor 2A (CDKN2A) is a well-known tumor suppressor gene as it functions as a cell cycle regulator. While several reports correlate the malfunction of CDKN2A with the initiation and progression of several types of human tumors, there is a lack of a comprehensive study that analyzes the potential effect of CDKN2A genetic alterations on the human immune components and the consequences of that effect on tumor progression and patient survival in a pan-cancer model. The first stage of the current study was the analysis of CDKN2A differential expression in tumor tissues and the corresponding normal ones and correlating that with tumor stage, grade, metastasis, and clinical outcome. Next, a detailed profile of CDKN2A genetic alteration under tumor conditions was described and assessed for its effect on the status of different human immune components. CDKN2A was found to be upregulated in cancerous tissues versus normal ones and that predicted the progression of tumor stage, grade, and metastasis in addition to poor prognosis under different forms of tumors. Additionally, CDKN2A experienced different forms of genetic alteration under tumor conditions, a characteristic that influenced the infiltration and the status of CD8, the chemokine CCL4, and the chemokine receptor CCR6. Collectively, the current study demonstrates the potential employment of CDKN2A genetic alteration as a prognostic and immunological biomarker under several types of human cancers. Full article
(This article belongs to the Special Issue Multiomics Approaches for Translational Medicine)
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Review

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14 pages, 322 KiB  
Review
Transcriptomic Harmonization as the Way for Suppressing Cross-Platform Bias and Batch Effect
by Nicolas Borisov and Anton Buzdin
Biomedicines 2022, 10(9), 2318; https://doi.org/10.3390/biomedicines10092318 - 18 Sep 2022
Cited by 6 | Viewed by 2356
Abstract
(1) Background: Emergence of methods interrogating gene expression at high throughput gave birth to quantitative transcriptomics, but also posed a question of inter-comparison of expression profiles obtained using different equipment and protocols and/or in different series of experiments. Addressing this issue is challenging, [...] Read more.
(1) Background: Emergence of methods interrogating gene expression at high throughput gave birth to quantitative transcriptomics, but also posed a question of inter-comparison of expression profiles obtained using different equipment and protocols and/or in different series of experiments. Addressing this issue is challenging, because all of the above variables can dramatically influence gene expression signals and, therefore, cause a plethora of peculiar features in the transcriptomic profiles. Millions of transcriptomic profiles were obtained and deposited in public databases of which the usefulness is however strongly limited due to the inter-comparison issues; (2) Methods: Dozens of methods and software packages that can be generally classified as either flexible or predefined format harmonizers have been proposed, but none has become to the date the gold standard for unification of this type of Big Data; (3) Results: However, recent developments evidence that platform/protocol/batch bias can be efficiently reduced not only for the comparisons of limited transcriptomic datasets. Instead, instruments were proposed for transforming gene expression profiles into the universal, uniformly shaped format that can support multiple inter-comparisons for reasonable calculation costs. This forms a basement for universal indexing of all or most of all types of RNA sequencing and microarray hybridization profiles; (4) Conclusions: In this paper, we attempted to overview the landscape of modern approaches and methods in transcriptomic harmonization and focused on the practical aspects of their application. Full article
(This article belongs to the Special Issue Multiomics Approaches for Translational Medicine)
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