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Updated: May 18, 2026

Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts
Published on: July 25, 2020
Personalized medicine in a phase I clinical trials program: the MD Anderson Cancer Center initiative
Apostolia-Maria Tsimberidou1, Nancy G Iskander, David S Hong
1Department of Investigational Cancer Therapeutics, Phase I Clinical Trials Program, The University of Texas MD Anderson Cancer Center, Houston, Texas 77030, USA. atsimber@mdanderson.org
Purpose:
We initiated a personalized medicine program in the context of early clinical trials, using targeted agents matched with tumor molecular aberrations. Herein, we report our observations.
Patient And Methods:
Patients with advanced cancer were treated in the Clinical Center for Targeted Therapy. Molecular analysis was conducted in the MD Anderson Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory. Patients whose tumors had an aberration were treated with matched targeted therapy, when available. Treatment assignment was not randomized. The clinical outcomes of patients with molecular aberrations treated with matched targeted therapy were compared with those of consecutive patients who were not treated with matched targeted therapy.
Results:
Of 1,144 patients analyzed, 460 (40.2%) had 1 or more aberration. In patients with 1 molecular aberration, matched therapy (n = 175) compared with treatment without matching (n = 116) was associated with a higher overall response rate (27% vs. 5%; P < 0.0001), longer time-to-treatment failure (TTF; median, 5.2 vs. 2.2 months; P < 0.0001), and longer survival (median, 13.4 vs. 9.0 months; P = 0.017). Matched targeted therapy was associated with longer TTF compared with their prior systemic therapy in patients with 1 mutation (5.2 vs. 3.1 months, respectively; P < 0.0001). In multivariate analysis in patients with 1 molecular aberration, matched therapy was an independent factor predicting response (P = 0.001) and TTF (P = 0.0001).
Conclusion:
Keeping in mind that the study was not randomized and patients had diverse tumor types and a median of 5 prior therapies, our results suggest that identifying specific molecular abnormalities and choosing therapy based on these abnormalities is relevant in phase I clinical trials.
Insights
Personalized medicine using targeted therapies matched to tumor molecular aberrations improved outcomes in early clinical trials. Identifying genetic abnormalities and tailoring treatment significantly enhances response rates and survival for advanced cancer patients.
Area of Science:
- Oncology
- Genomics
- Clinical Trials
Background:
- Personalized medicine aims to tailor treatments based on individual patient and tumor characteristics.
- Targeted therapies offer a promising approach by focusing on specific molecular aberrations in cancer cells.
Purpose of the Study:
- To evaluate the efficacy of a personalized medicine program using targeted agents matched to tumor molecular aberrations in early clinical trials.
- To compare clinical outcomes of patients treated with matched targeted therapy versus those without matching.
Main Methods:
- Patients with advanced cancer underwent molecular analysis of their tumors.
- Tumors with identified aberrations were treated with matched targeted therapy when available.
- Clinical outcomes were compared between matched and unmatched treatment groups.
Main Results:
- Of 1,144 patients, 460 (40.2%) had molecular aberrations.
- Matched therapy in patients with one aberration showed higher overall response rates (27% vs. 5%) and longer time-to-treatment failure (median 5.2 vs. 2.2 months) compared to unmatched therapy.
- Matched therapy was an independent predictor of response and time-to-treatment failure in multivariate analysis.
Conclusions:
- Identifying molecular abnormalities and matching therapy is relevant in phase I clinical trials.
- Despite diverse tumor types and prior therapies, matched targeted therapy demonstrated significant clinical benefit.
- Further research in non-randomized settings supports the value of molecular-guided treatment selection.
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