Guest Editor(s)
Prof. Dr. Hung-Yu Lin
Email: linhungyu700218@gmail.com
Affiliation: Department of Post-Baccalaureate Medicine, National Chung Hsing University, Taichung, Taiwan
Homepage:
Research Interests: cancer biology, biomarker, metabolism, mitochondria, immuno-oncology, non-coding RNAs, single-cell omics, targeted therapy, machine learning
Prof. Hsing-Ju Wu
Email: hildawu09@gmail.com
Affiliation: 1. Research Assistant Center, Show Chwan Memorial Hospital, Changhua, Taiwan
2. Department of Nursing, Nursing and Management, Jenteh Junior College of Medicine, Miaoli, Taiwan
Homepage:
Research Interests: cancer biology, molecular biology, medical microbiology
Summary
This Special Issue is the second edition of a previous Special Issue entitled "Tumor Biomarkers for Diagnosis, Prognosis and Targeted Therapy" (https://www.techscience.com/or/special_detail/tumor_biomarkers).
The second edition of this Special Issue in Oncology Research centers on expanding the horizons of translational oncology by bridging high-throughput technological innovations with advanced clinical applications. In the era of precision oncology, understanding the complex cellular architecture and molecular interactions within the dynamic tumor microenvironment is critical. This edition aims to showcase high-impact research dedicated to the identification, validation, and clinical implementation of robust prognostic biomarkers and predictive biomarkers to optimize patient stratification and guide diverse personalized therapies.
A primary focus of this updated edition is the integration of cutting-edge methodologies, such as artificial intelligence (AI), single-cell RNA sequencing (scRNA-seq), and spatial transcriptomics, when applied to the discovery of therapeutic targets, drug response biomarkers, and mechanisms of treatment resistance in cancer therapy. We highly welcome submissions exploring novel tissue-based biomarkers that map spatial cellular landscapes, as well as minimally invasive circulating biomarkers for real-time, longitudinal monitoring, particularly those associated with treatment response, drug sensitivity, or emergence of resistance.
Key areas of interest include the discovery of novel immune biomarkers, expression profiling of immune checkpoint molecules, and the systemic or local signaling networks of biomarkers that modulate anti-tumor immunity and therapeutic efficacy. Special emphasis will be placed on using state-of-the-art computational and experimental tools to identify markers that correlate with personalized therapy response, including targeted therapies, immunotherapies, and novel combination regimens.
By merging advanced data-driven approaches with diverse clinical specimen analysis, this Special Issue seeks to accelerate the translation of next-generation biomarkers into routine oncology practice. Studies focusing primarily on algorithm development, descriptive multi-omics profiling, or technological optimization without clear therapeutic relevance or experimental validation will not be considered within the scope of this Special Issue.
Keywords
translational oncology, artificial intelligence, single-cell RNA sequencing, spatial transcriptomics, tumor microenvironment, prognostic biomarkers, predictive biomarkers, immune biomarkers, tissue-based biomarkers, circulating biomarkers, personalized therapy response, targeted therapy,
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