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Published on: June 20, 2015
Cancer Heterogeneity and Cancer Cell Plasticity: Molecular Mechanisms and Precision Therapy.
Hanwen Hu1,2, Zhixing Hao3,4, Lili Li2,5
1Department of Breast Surgery Second Affiliated Hospital Zhejiang University School of Medicine Hangzhou China.
Tumor heterogeneity and cancer cell plasticity drive cancer progression and treatment resistance. Overcoming these challenges requires a new precision oncology approach integrating advanced diagnostics and adaptive therapies.
Area of Science:
- Oncology
- Cancer Biology
- Genomics
Background:
- Tumor heterogeneity and cancer cell plasticity are key drivers of cancer progression, therapeutic resistance, and recurrence.
- These processes limit the effectiveness and durability of current precision oncology strategies.
- Understanding the interplay between heterogeneity and plasticity is crucial for developing more effective cancer treatments.
Purpose of the Study:
- To synthesize recent advances in understanding tumor heterogeneity and cancer cell plasticity.
- To discuss the role of the tumor microenvironment in regulating cancer cell plasticity.
- To propose a next-generation precision oncology paradigm to overcome treatment resistance.
Main Methods:
- Review of current literature on tumor heterogeneity, cancer cell plasticity, and the tumor microenvironment.
- Analysis of challenges in precision therapy, including target loss, bypass pathway activation, and adaptive cell-state transitions.
- Discussion of emerging technologies like single-cell and spatial multiomics and artificial intelligence.
Main Results:
- Tumor heterogeneity and plasticity are intrinsically linked, driving tumor progression and therapeutic resistance.
- The tumor microenvironment significantly influences cancer cell plasticity through various cues.
- Cancer cell plasticity is a major contributor to heterogeneous therapeutic efficacy and drug resistance.
Conclusions:
- A next-generation precision oncology paradigm integrating stratified diagnosis, combination interventions, and adaptive monitoring is proposed.
- The development of "digital twin" tumor models using multiomics and AI can guide individualized treatment decisions.
- Addressing tumor heterogeneity and plasticity is essential for improving long-term cancer patient outcomes.
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