Related Experiment Video
Updated: May 31, 2025

Testing Targeted Therapies in Cancer using Structural DNA Alteration Analysis and Patient-Derived Xenografts
Published on: July 25, 2020
Novel clinical trial designs emerging from the molecular reclassification of cancer
Mina Nikanjam1,2, Shumei Kato1,2, Teresa Allen3
1Division of Hematology-Oncology, University of California San Diego, La Jolla, California, USA.
Abstract:
Next-generation sequencing has revealed the disruptive reality that advanced/metastatic cancers have complex and individually distinct genomic landscapes, necessitating a rethinking of treatment strategies and clinical trial designs. Indeed, the molecular reclassification of cancer suggests that it is the molecular underpinnings of the disease, rather than the tissue of origin, that mostly drives outcomes. Consequently, oncology clinical trials have evolved from standard phase 1, 2, and 3 tissue-specific studies; to tissue-specific, biomarker-driven trials; to tissue-agnostic trials untethered from histology (all drug-centered designs); and, ultimately, to patient-centered, N-of-1 precision medicine studies in which each patient receives a personalized, biomarker-matched therapy/combination of drugs. Innovative technologies beyond genomics, including those that address transcriptomics, immunomics, proteomics, functional impact, epigenetic changes, and metabolomics, are enabling further refinement and customization of therapy. Decentralized studies have the potential to improve access to trials and precision medicine approaches for underserved minorities. Evaluation of real-world data, assessment of patient-reported outcomes, use of registry protocols, interrogation of exceptional responders, and exploitation of synthetic arms have all contributed to personalized therapeutic approaches. With greater than 1 × 1012 potential patterns of genomic alterations and greater than 4.5 million possible three-drug combinations, the deployment of artificial intelligence/machine learning may be necessary for the optimization of individual therapy and, in the near future, also may permit the discovery of new treatments in real time.
Insights
Advanced cancers have complex genomic landscapes, driving a shift towards personalized, biomarker-matched therapies. Precision medicine, utilizing diverse molecular data and AI, optimizes individual cancer treatment and drug discovery.
Area of Science:
- Oncology
- Genomics
- Precision Medicine
Background:
- Next-generation sequencing reveals complex, individual genomic landscapes in advanced cancers.
- Molecular characteristics, not tissue of origin, increasingly dictate cancer patient outcomes.
- This necessitates a paradigm shift in cancer treatment strategies and clinical trial design.
Purpose of the Study:
- To outline the evolution of oncology clinical trials towards precision medicine.
- To highlight the role of multi-omic technologies and data sources in personalizing cancer therapy.
- To discuss the potential of artificial intelligence in optimizing individualized treatment and discovering new therapies.
Main Methods:
- Review of evolving clinical trial designs from tissue-specific to patient-centered, N-of-1 studies.
- Integration of diverse molecular data (genomics, transcriptomics, proteomics, etc.).
- Leveraging real-world data, patient-reported outcomes, and advanced computational approaches like AI/machine learning.
Main Results:
- Oncology trials have progressed to biomarker-driven, tissue-agnostic, and N-of-1 precision medicine models.
- Multi-omic technologies enable refined and customized therapeutic strategies.
- AI/machine learning is crucial for navigating complex genomic data and optimizing personalized treatments.
Conclusions:
- Cancer treatment is increasingly personalized, moving beyond histology to molecular underpinnings.
- A multi-modal, data-driven approach, including AI, is essential for optimizing precision oncology.
- Future directions include real-time treatment discovery and improved trial accessibility through decentralized studies.
More Related Videos
Related Concept Videos
Combination Therapies and Personalized Medicine
The combination of the drug acetazolamide and sulforaphane is a good example of combination therapy to treat cancer. The cells in the interior of a large tumor often die due to the hypoxic and...
Targeted Cancer Therapies
There are several types of targeted therapies against...
Treatment Resistant Cancers
Mouse Models of Cancer Study
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...

