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Bioengineering
Special Issues
Targeted Therapy for Cancer
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Targeted Therapy for Cancer

A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Regenerative Engineering".

Deadline for manuscript submissions: closed (30 September 2022) | Viewed by 12252

Special Issue Editor

Prof. Dr. Liang Xu

E-Mail Website
Guest Editor
College of Life Sciences, Zhejiang University, Hangzhou 310000, China
Interests: molecular medicine; cancer biology; epigenetics; experimental therapeutics; proteolysis-targeting chimera

Special Issue Information

Dear Colleagues,

Targeted therapy has significantly advanced cancer treatment over the past few decades. However, a series of new questions and challenges have emerge from the fields of target discovery, drug design, patient selection, therapy resistance, and clinical management. To fulfill the unmet needs, many innovative approaches and solutions have been developed. Breakthroughs in chemical biology, disease model, immunotherapy, and artificial intelligence have the potential to further transform personalized medicine, tailoring cancer treatment for an individual patient’s tumor.

This Special Issue on the “Targeted Therapy for Cancer” aims to gather insightful thoughts and impactful findings in a wide variety of aspects of targeted therapy including basic cancer research, translational oncology, and clinical studies. Both original research articles and comprehensive review papers are welcome. Your contributions will be valuable to advance the current understanding of cancer biology and intervention, and to stimulate the next breakthroughs in cancer therapeutics and precision medicine.

Prof. Dr. Liang Xu
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. Bioengineering 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

  • drug development
  • cancer target
  • molecular mechanism
  • biomarker
  • drug resistance
  • translational research
  • precision medicine

Published Papers (4 papers)

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Research

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14 pages, 2721 KiB  
Article
Pheno-SELEX: Engineering Anti-Metastatic Aptamers through Targeting the Invasive Phenotype Using Systemic Evolution of Ligands by Exponential Enrichment
by Greg Shelley, Jinlu Dai, Jill M. Keller and Evan T. Keller
Bioengineering 2021, 8(12), 212; https://0-doi-org.brum.beds.ac.uk/10.3390/bioengineering8120212 - 13 Dec 2021
Cited by 3 | Viewed by 2262
Abstract
Multiple methods (e.g., small molecules and antibodies) have been engineered to target specific proteins and signaling pathways in cancer. However, many mediators of the cancer phenotype are unknown and the ability to target these phenotypes would help mitigate cancer. Aptamers are small DNA [...] Read more.
Multiple methods (e.g., small molecules and antibodies) have been engineered to target specific proteins and signaling pathways in cancer. However, many mediators of the cancer phenotype are unknown and the ability to target these phenotypes would help mitigate cancer. Aptamers are small DNA or RNA molecules that are designed for therapeutic use. The design of aptamers to target cancers can be challenging. Accordingly, to engineer functionally anti-metastatic aptamers we used a modification of systemic evolution of ligands by exponential enrichment (SELEX) we call Pheno-SELEX to target a known phenotype of cancer metastasis, i.e., invasion. A highly invasive prostate cancer (PCa) cell line was established and used to identify aptamers that bound to it with high affinity as opposed to a less invasive variant to the cell line. The anti-invasive aptamer (AIA1) was found to inhibit in vitro invasion of the original highly invasive PCa cell line, as well as an additional PCa cell line and an osteosarcoma cell line. AIA1 also inhibited in vivo development of metastasis in both a PCa and osteosarcoma model of metastasis. These results indicate that Pheno-SELEX can be successfully used to identify aptamers without knowledge of underlying molecular targets. This study establishes a new paradigm for the identification of functional aptamers. Full article
(This article belongs to the Special Issue Targeted Therapy for Cancer)
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Review

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16 pages, 1351 KiB  
Review
Anti-Tumor Effect of Parasitic Protozoans
by Haojie Ding, Songrui Wu, Zi Jin, Bin Zheng, Yuan Hu, Ke He, Shaohong Lu and Xunhui Zhuo
Bioengineering 2022, 9(8), 395; https://0-doi-org.brum.beds.ac.uk/10.3390/bioengineering9080395 - 16 Aug 2022
Cited by 4 | Viewed by 2285
Abstract
The immune system may aberrantly silence when against “altered self”, which consequently may develop into malignancies. With the development of tumor immunology and molecular biology, the deepened understanding of the relationship between parasites and tumors shifts the attitude towards parasitic pathogens from elimination [...] Read more.
The immune system may aberrantly silence when against “altered self”, which consequently may develop into malignancies. With the development of tumor immunology and molecular biology, the deepened understanding of the relationship between parasites and tumors shifts the attitude towards parasitic pathogens from elimination to utilization. In recent years, the antitumor impact implemented by protozoan parasites and the derived products has been confirmed. The immune system is activated and enhanced by some protozoan parasites, thereby inhibiting tumor growth, angiogenesis, and metastasis in many animal models. In this work, we reviewed the available information on the antitumor effect of parasitic infection or induced by parasitic antigen, as well as the involved immune mechanisms that modulate cancer progression. Despite the fact that clinical trials of the protozoan parasites against tumors are limited and the specific mechanisms of the effect on tumors are not totally clear, the use of genetically modified protozoan parasites and derived molecules combined with chemotherapy could be an important element for promoting antitumor treatment in the future. Full article
(This article belongs to the Special Issue Targeted Therapy for Cancer)
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24 pages, 881 KiB  
Review
Emerging Promise of Computational Techniques in Anti-Cancer Research: At a Glance
by Md. Mominur Rahman, Md. Rezaul Islam, Firoza Rahman, Md. Saidur Rahaman, Md. Shajib Khan, Sayedul Abrar, Tanmay Kumar Ray, Mohammad Borhan Uddin, Most. Sumaiya Khatun Kali, Kamal Dua, Mohammad Amjad Kamal and Dinesh Kumar Chellappan
Bioengineering 2022, 9(8), 335; https://0-doi-org.brum.beds.ac.uk/10.3390/bioengineering9080335 - 25 Jul 2022
Cited by 15 | Viewed by 5035
Abstract
Research on the immune system and cancer has led to the development of new medicines that enable the former to attack cancer cells. Drugs that specifically target and destroy cancer cells are on the horizon; there are also drugs that use specific signals [...] Read more.
Research on the immune system and cancer has led to the development of new medicines that enable the former to attack cancer cells. Drugs that specifically target and destroy cancer cells are on the horizon; there are also drugs that use specific signals to stop cancer cells multiplying. Machine learning algorithms can significantly support and increase the rate of research on complicated diseases to help find new remedies. One area of medical study that could greatly benefit from machine learning algorithms is the exploration of cancer genomes and the discovery of the best treatment protocols for different subtypes of the disease. However, developing a new drug is time-consuming, complicated, dangerous, and costly. Traditional drug production can take up to 15 years, costing over USD 1 billion. Therefore, computer-aided drug design (CADD) has emerged as a powerful and promising technology to develop quicker, cheaper, and more efficient designs. Many new technologies and methods have been introduced to enhance drug development productivity and analytical methodologies, and they have become a crucial part of many drug discovery programs; many scanning programs, for example, use ligand screening and structural virtual screening techniques from hit detection to optimization. In this review, we examined various types of computational methods focusing on anticancer drugs. Machine-based learning in basic and translational cancer research that could reach new levels of personalized medicine marked by speedy and advanced data analysis is still beyond reach. Ending cancer as we know it means ensuring that every patient has access to safe and effective therapies. Recent developments in computational drug discovery technologies have had a large and remarkable impact on the design of anticancer drugs and have also yielded useful insights into the field of cancer therapy. With an emphasis on anticancer medications, we covered the various components of computer-aided drug development in this paper. Transcriptomics, toxicogenomics, functional genomics, and biological networks are only a few examples of the bioinformatics techniques used to forecast anticancer medications and treatment combinations based on multi-omics data. We believe that a general review of the databases that are now available and the computational techniques used today will be beneficial for the creation of new cancer treatment approaches. Full article
(This article belongs to the Special Issue Targeted Therapy for Cancer)
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12 pages, 598 KiB  
Review
Fusobacterium nucleatum and Malignant Tumors of the Digestive Tract: A Mechanistic Overview
by Yue Lai, Jun Mi and Qiang Feng
Bioengineering 2022, 9(7), 285; https://0-doi-org.brum.beds.ac.uk/10.3390/bioengineering9070285 - 28 Jun 2022
Cited by 2 | Viewed by 2072
Abstract
Fusobacterium nucleatum (F. nucleatum) is an oral anaerobe that plays a role in several oral diseases. However, F. nucleatum is also found in other tissues of the digestive tract, and several studies have recently reported that the level of F. nucleatum [...] Read more.
Fusobacterium nucleatum (F. nucleatum) is an oral anaerobe that plays a role in several oral diseases. However, F. nucleatum is also found in other tissues of the digestive tract, and several studies have recently reported that the level of F. nucleatum is significantly elevated in malignant tumors of the digestive tract. F. nucleatum is proposed as one of the risk factors in the initiation and progression of digestive tract malignant tumors. In this review, we summarize recent reports on F. nucleatum and its role in digestive tract cancers and evaluate the mechanisms underlying the action of F. nucleatum in digestive tract cancers. Full article
(This article belongs to the Special Issue Targeted Therapy for Cancer)
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