Cancer Biology & Therapy

The evolving proteome plays a pivotal role in therapy across various medical disciplines. In precision medicine, the dynamic nature of the proteome enables tailored treatment strategies based on individual patients' molecular profiles. By analyzing proteomics data, clinicians can identify specific protein alterations driving disease progression, facilitating the development of targeted therapies. Monitoring changes in the proteome over time can help predict treatment responses and drug resistance, guiding adjustments to therapy for optimal outcomes. By integrating proteomics information into therapeutic decision-making, clinicians can enhance treatment efficacy and improve patient outcomes in a wide range of medical contexts. For instance, in cancer treatment, drugs can be designed to selectively inhibit overexpressed or mutated proteins identified in the patient's proteome, leading to more effective and personalized interventions. Proteomics-based strategies aim to understand the complex interplay of proteins within cancer cells and exploit this knowledge for therapeutic benefit. This personalized approach enables the development of tailored treatment regimens that can more effectively target the underlying mechanisms driving tumor growth and progression and minimize adverse effects on normal tissues.

While targeting the proteome holds immense potential for advancing mechanism-based therapy in cancer, and facilitating the discovery of novel therapeutic targets, biomarkers, etc., several formidable challenges must be addressed to realize its full therapeutic benefits. It poses critical complications in light of the complexity and heterogeneity of the cancer proteome, which can vary widely between different tumor types and even within individual tumors. Identifying key driver proteins or pathways amidst this complexity is essential but can be challenging due to the dynamic nature of the proteome and the interplay between various signaling networks. The development of drugs targeting specific proteins or protein interactions may face obstacles such as off-target effects, drug resistance, and limited bioavailability, necessitating innovative drug design, delivery strategies, and so on. It's paramount to develop innovative proteomics technologies and insights into cancer biology for refining targeted therapies that exploit vulnerabilities in the cancer proteome, ultimately improving patient outcomes in the fight against cancer.

This special section illustrates how advances in targeting the proteome for mechanism-based therapy represent a paradigm shift in cancer treatment, offering the potential for more precise, personalized, and effective therapeutic strategies. Original research and review articles related to intricate network of proteins that drive cancer progression, proteomics-based approaches for improving patient outcomes and ultimately transforming the landscape of cancer therapy are welcome.

• Trends in the integration of proteomics and genomics data for developing cancer mechanisms and novel therapeutic targets
• Multi-omics technological approaches for the advancement of personalized therapies in cancer
• Recent advances in high-throughput mass spectrometry-based proteomics and bioinformatics tools for targeted cancer therapy
• Evolving proteome analysis of the diagnosis and targeted treatment in advanced thyroid cancer
• Novel proteome mapping strategies in the analysis of targeted protein-protein interactions for therapeutic intervention in cancer
• Proteome mechanisms of glioma cells and analysis for efficient immunotherapy
• Proteome expression and stability in tumorigenicity testing of human breast cancer cells and therapeutics
• Evaluating proteomic biomarkers technologies and their challenges in real-time cancer liquid biopsies
• Next generation targeted proteomics: cancer diagnosis, prognosis, and treatment response prediction
• Evolving network pharmacology for minimizing off-target effects of cancer therapy
• Advancing targeted proteome-based mechanisms and applications of therapeutic resistance in cancer patients
• Emerging trends in post-translational modifications (PTMs) analysis of signaling pathways for disrupting cancer cells and proliferation

Cancer Biology & Therapy accepts the following types of article:

• Review
• Meeting Reports
• Perspectives
• Bedside-to-Bench Reports
• Research Papers

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Dr. Sandip K Mishra, Scientist-F, Cancer Biology Lab, Institute of Life Sciences, Bhubaneswar has been appointed as an Associate Editor of the esteemed Journal, BMC Cancer. BMC Cancer is a very prestigious journal in the field of Cancer, being a subsidiary of Springer Nature. It is one of premiere cancer journal, that publishes all aspects of cancer research, including the pathophysiology, prevention, diagnosis and treatment of cancers. His research interest includes Cellular Oncology; Molecular Oncology; Breast Cancer; Cancer Biology.

Additional Emails: [email protected]; [email protected]

Institute of Life Sciences | Sandip Mishra

Google Scholar | Sandip Mishra

Prof. Himangshu Bose has received his PhD in Biophysical Chemistry from the North Bengal University during the period of 1982-1988. Currently he is working as a professor of Biochemistry in Memorial University Medical Center and Mercer University School of Medicine. He serves numerous administrative responsibilities at the hospital and also for the University. He also participates teaching in Biochemistry and Endocrinology to the medical students and fellows and residents for Endocrine training. He has authored forty research articles. Dr. Bose’s areas of interest include: reproductive endocrine cell biology and breast cancer. Most of his publications are highly cited in textbooks of endocrinology and biochemistry. Dr. Bose’s earliest discovery is a mandatory test (LCAH/LStAR) for all pregnant women after the first trimester and recently his laboratory has cloned a 22 kDa protein, SAM, which is likely to be a biomarker for breast cancer patients with high estradiol.

Mercer University | Himangshu Bose

Google Scholar | Himangshu Bose

Dr. Abir J. Hussain received the Ph.D. degree from The University of Manchester (UMIST), U.K., in 2000., Her Ph.D. thesis title Polynomial Neural Networks for Image and Signal Processing. She is currently a professor in machine learning with the University of Sharjah, United Arab Emirates. She has published numerous refereed research papers in conferences and journals in the research areas of neural networks, signal prediction, telecommunication fraud detection, and image compression. Her research has been published in a number of high esteemed and high impact journals. She is also a Ph.D. Supervisor and an External Examiner for research degrees, including Ph.D. and M.Phil. She is one of the initiators and chairs of the Development in e-Systems Engineering (DeSE) series, most notably illustrated by the IEEE technically sponsored DeSE International Conference Series. Her research interests include machine learning algorithms and their applications to medical, image and signal processing, and data analysis.

Google Scholar | Abir Hussain

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Disclosure Statement: Dr. Mishra, Prof. Bose and Dr. Hussain declare no conflicts of interest regarding this work.

The deadline for submitting manuscripts is September 30th, 2024.

When submitting your article, please select the Special Issue, 'Targeting the Proteome for Mechanism-based Therapy in Cancer' from the drop-down menu on the submission system.

All manuscripts submitted to this Article Collection will undergo a full peer-review; the Guest Advisor for this collection will not be handling the manuscripts (unless they are an Editorial Board member). Please review the journal scope and author submission instructions prior to submitting a manuscript.

The deadline for submitting manuscripts is September 30th, 2024.

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