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Gene-expression profiling in differentiated thyroid cancer--a viable strategy for the practice of genomic medicine?
1The Ohio State University, Human Cancer Genetics Program, 420 West 12th Avenue, Ste 690 TMRF, Columbus, OH 43210, USA.
Abstract:
Thyroid neoplasias have been largely ignored as an active field of investigation due to the overall favorable prognosis of differentiated nonmedullary thyroid cancers. However, differentiated thyroid cancers have the highest estimated annual percentage increase in incidence amongst all cancer sites. Furthermore, no significant progress has been made to improve survival, especially for advanced disease. Compounding the problem, there remains a lack of highly accurate preoperative markers or molecular-based predictive models to differentiate benign from malignant follicular neoplasias, thus we continue to rely upon surgery for diagnostic purposes in this subset of patients. Therefore, new approaches are necessary to identify potential novel diagnostic, prognostic and therapeutic algorithms, which would not only allow accurate early diagnosis but also personalized patient management, with clinical management and surveillance tailored according to the genetic signature of the patient. The advent of modern genomic technologies, such as global gene-expression profiling, may begin to provide the data required for the evidence-based practice of genomic medicine as it relates to thyroid neoplasia. However, it is already clear that genomic technology alone is insufficient to fully achieve this vision.
Insights
Thyroid cancer incidence is rising, yet survival for advanced cases remains poor. New genomic approaches are needed for accurate diagnosis and personalized treatment of thyroid neoplasias.
Area of Science:
- Oncology
- Genomics
- Molecular Biology
Background:
- Differentiated nonmedullary thyroid cancers have a generally favorable prognosis but show the highest incidence increase.
- Significant advancements in survival for advanced thyroid cancer are lacking.
- Accurate preoperative markers to distinguish benign from malignant follicular neoplasias are needed, often requiring surgery for diagnosis.
Purpose of the Study:
- To highlight the need for novel diagnostic, prognostic, and therapeutic strategies for thyroid neoplasia.
- To emphasize the potential of genomic technologies for personalized patient management and early diagnosis.
- To underscore the limitations of current genomic approaches alone in achieving these goals.
Main Methods:
- Review of current challenges in thyroid neoplasia diagnosis and treatment.
- Exploration of the role of modern genomic technologies, such as gene-expression profiling.
- Discussion of the necessity for integrated approaches combining genomic data with clinical insights.
Main Results:
- Thyroid cancer incidence is increasing significantly across all cancer sites.
- Current methods lack accuracy in preoperative differentiation of follicular neoplasias.
- Genomic technologies offer promise but are insufficient on their own for comprehensive management.
Conclusions:
- New diagnostic and therapeutic algorithms are essential for thyroid neoplasia.
- Personalized patient management based on genetic signatures is a future goal.
- Genomic medicine requires further development and integration for effective thyroid cancer care.
