Discover Oncology
Scope & Guideline
Empowering collaboration for groundbreaking therapeutic discoveries.
Introduction
Aims and Scopes
- Molecular Mechanisms and Pathways:
Research focusing on the molecular and cellular mechanisms underlying cancer development and progression, including studies on signaling pathways, gene expression, and tumor microenvironment interactions. - Biomarker Discovery and Validation:
Studies aimed at identifying and validating biomarkers for cancer diagnosis, prognosis, and treatment response, utilizing techniques such as genomics, proteomics, and bioinformatics. - Therapeutic Strategies:
Investigations into novel therapeutic approaches, including pharmacological treatments, immunotherapy, and combination therapies, as well as the mechanisms of resistance to existing therapies. - Clinical Trials and Translational Research:
Research that bridges laboratory findings with clinical applications, focusing on the design, execution, and outcomes of clinical trials in oncology. - Patient-Centered Outcomes:
Studies assessing the impact of cancer treatments on patient quality of life, survivorship, and psychosocial factors, emphasizing the importance of holistic care in oncology. - Emerging Technologies in Cancer Research:
Exploration of advanced technologies such as artificial intelligence, machine learning, and novel imaging techniques in the context of cancer diagnosis, treatment, and research.
Trending and Emerging
- Immunotherapy and Immune Microenvironment:
There is a growing emphasis on immunotherapy, including the exploration of immune checkpoint inhibitors and their efficacy across various cancer types, as well as the role of the immune microenvironment in tumor progression. - Genomic and Proteomic Profiling:
Increasing focus on genomic and proteomic analyses to identify novel biomarkers and therapeutic targets, utilizing high-throughput sequencing and bioinformatics to drive precision oncology. - Liquid Biopsies and Circulating Tumor Cells:
Research on liquid biopsies and circulating tumor cells is gaining traction, providing non-invasive methods for early cancer detection, monitoring treatment response, and understanding metastasis. - Machine Learning and AI in Cancer Research:
The integration of machine learning and artificial intelligence in cancer research is emerging, particularly for predictive modeling, diagnostic accuracy, and personalized treatment strategies. - Microbiome and Cancer Interactions:
An increasing number of studies are exploring the relationship between gut microbiota and cancer, investigating how microbial communities influence tumor development and response to therapies. - Metabolic Reprogramming in Cancer:
Research is increasingly focusing on the metabolic pathways in cancer cells, examining how metabolic alterations contribute to tumor growth and therapy resistance.
Declining or Waning
- Traditional Chemotherapy Approaches:
There is a noticeable decrease in papers focused solely on traditional chemotherapeutic agents without the incorporation of novel strategies or combination therapies, reflecting a shift towards more targeted and personalized treatment modalities. - Basic Science without Clinical Relevance:
Research that is strictly basic science with minimal implications for clinical practice is becoming less common, as the journal increasingly prioritizes studies that have clear translational potential. - Single-Cancer Focus Studies:
The trend is moving away from studies that focus exclusively on a single type of cancer, with more publications emphasizing pan-cancer analyses or comparative studies across multiple cancer types.
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