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Updated: Mar 30, 2026

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
Precision medicine for cancer with next-generation functional diagnostics
Adam A Friedman1, Anthony Letai2, David E Fisher1,3
1Massachusetts General Hospital Cancer Center, Harvard Medical School, 55 Fruit Street, Boston, Massachusetts 02114, USA.
Precision medicine aims to match patients with the right cancer drugs. Functional testing of patient tumor cells offers a promising approach to overcome limitations of genomics alone for personalized cancer therapy.
Area of Science:
- Oncology
- Translational Medicine
- Cancer Diagnostics
Background:
- Precision medicine in oncology often relies heavily on genomics.
- Genomic approaches are limited by incomplete understanding of genotype-phenotype relationships in cancer.
- Current functional testing methods for chemosensitivity have limitations.
Purpose of the Study:
- To highlight the limitations of genomics-based precision oncology.
- To introduce next-generation functional diagnostic technologies for cancer.
- To propose an integrated diagnostic strategy for personalized cancer therapy.
Main Methods:
- Review of novel functional diagnostic technologies for tumor analysis.
- Comparison of new methods with older chemosensitivity tests.
- Discussion of integrating functional testing with genomic and immunoprofiling data.
Main Results:
- Next-generation functional diagnostics offer improved tumor manipulation and response assays.
- These advanced methods address limitations of traditional chemosensitivity testing.
- Emerging technologies enable more precise assessment of drug responses in patient tumors.
Conclusions:
- Functional testing of live patient tumor cells is crucial for precision medicine.
- Integrating functional tests with genomics and immunoprofiling can enhance treatment matching.
- This integrated approach promises more precise combination therapies for individual cancer patients.
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