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Updated: Jul 4, 2025
Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
Published on: April 11, 2016
Omics-based molecular classifications empowering in precision oncology
Zhaokai Zhou1,2, Ting Lin1, Shuang Chen3
1Department of Interventional Radiology, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, 450052, China.
Background:
In the past decades, cancer enigmatical heterogeneity at distinct expression levels could interpret disparities in therapeutic response and prognosis. It built hindrances to precision medicine, a tactic to tailor customized treatment informed by the tumors' molecular profile. Single-omics analysis dissected the biological features associated with carcinogenesis to some extent but still failed to revolutionize cancer treatment as expected. Integrated omics analysis incorporated tumor biological networks from diverse layers and deciphered a holistic overview of cancer behaviors, yielding precise molecular classification to facilitate the evolution and refinement of precision medicine.
Conclusion:
This review outlined the biomarkers at multiple expression layers to tutor molecular classification and pinpoint tumor diagnosis, and explored the paradigm shift in precision therapy: from single- to multi-omics-based subtyping to optimize therapeutic regimens. Ultimately, we firmly believe that by parsing molecular characteristics, omics-based typing will be a powerful assistant for precision oncology.
Insights
Cancer
Area of Science:
- Oncology
- Genomics
- Molecular Biology
Background:
- Cancer's complex heterogeneity complicates personalized medicine.
- Single-omics approaches offer limited insights into tumor biology.
- Integrated omics analysis provides a comprehensive view of cancer.
Purpose of the Study:
- To review biomarkers for molecular classification and tumor diagnosis.
- To explore the shift towards multi-omics-based precision therapy.
- To highlight the role of omics-based typing in oncology.
Main Methods:
- Review of multi-omics data integration strategies.
- Analysis of biomarkers across different molecular layers.
- Exploration of precision medicine advancements.
Main Results:
- Multi-omics analysis enables precise molecular classification of tumors.
- Biomarkers from diverse expression layers aid diagnosis.
- Integrated omics refines therapeutic strategies.
Conclusions:
- Omics-based typing is crucial for advancing precision oncology.
- Multi-omics subtyping optimizes cancer treatment regimens.
- This approach enhances diagnostic accuracy and therapeutic efficacy.
