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Updated: Feb 9, 2026

Assessing Specificity of Anticancer Drugs In Vitro
Published on: March 23, 2016
PanDrugs: a novel method to prioritize anticancer drug treatments according to individual genomic data
Elena Piñeiro-Yáñez1, Miguel Reboiro-Jato2,3, Gonzalo Gómez-López1
1Spanish National Cancer Research Centre (CNIO), 3rd Melchor Fernandez Almagro st., E-28029, Madrid, Spain.
Background:
Large-sequencing cancer genome projects have shown that tumors have thousands of molecular alterations and their frequency is highly heterogeneous. In such scenarios, physicians and oncologists routinely face lists of cancer genomic alterations where only a minority of them are relevant biomarkers to drive clinical decision-making. For this reason, the medical community agrees on the urgent need of methodologies to establish the relevance of tumor alterations, assisting in genomic profile interpretation, and, more importantly, to prioritize those that could be clinically actionable for cancer therapy.
Results:
We present PanDrugs, a new computational methodology to guide the selection of personalized treatments in cancer patients using the variant lists provided by genome-wide sequencing analyses. PanDrugs offers the largest database of drug-target associations available from well-known targeted therapies to preclinical drugs. Scoring data-driven gene cancer relevance and drug feasibility PanDrugs interprets genomic alterations and provides a prioritized evidence-based list of anticancer therapies. Our tool represents the first drug prescription strategy applying a rational based on pathway context, multi-gene markers impact and information provided by functional experiments. Our approach has been systematically applied to TCGA patients and successfully validated in a cancer case study with a xenograft mouse model demonstrating its utility.
Conclusions:
PanDrugs is a feasible method to identify potentially druggable molecular alterations and prioritize drugs to facilitate the interpretation of genomic landscape and clinical decision-making in cancer patients. Our approach expands the search of druggable genomic alterations from the concept of cancer driver genes to the druggable pathway context extending anticancer therapeutic options beyond already known cancer genes. The methodology is public and easily integratable with custom pipelines through its programmatic API or its docker image. The PanDrugs webtool is freely accessible at http://www.pandrugs.org .
Insights
PanDrugs is a new computational method that interprets cancer genomic alterations to prioritize clinically actionable therapies. This tool aids oncologists in selecting personalized cancer treatments by analyzing variant lists and drug-target associations.
Area of Science:
- Oncology
- Genomics
- Bioinformatics
Background:
- Cancer genome projects reveal numerous heterogeneous molecular alterations in tumors.
- Identifying clinically relevant biomarkers from extensive genomic data is challenging for oncologists.
- There is a critical need for methodologies to assess tumor alteration relevance and prioritize actionable cancer therapies.
Purpose of the Study:
- To present PanDrugs, a novel computational methodology for personalized cancer treatment selection.
- To provide the largest available database of drug-target associations, from approved to preclinical drugs.
- To interpret genomic alterations and prioritize anticancer therapies based on evidence.
Main Methods:
- Utilizing variant lists from genome-wide sequencing analyses.
- Developing a scoring system for data-driven gene cancer relevance and drug feasibility.
- Integrating pathway context, multi-gene marker impact, and functional experimental data.
- Applying the methodology to TCGA (The Cancer Genome Atlas) patient data.
Main Results:
- PanDrugs identifies potentially druggable molecular alterations and prioritizes anticancer drugs.
- The tool facilitates the interpretation of genomic landscapes for clinical decision-making.
- The approach was validated in a cancer case study using a xenograft mouse model.
Conclusions:
- PanDrugs offers a feasible method for identifying druggable alterations and prioritizing cancer therapies.
- The methodology expands therapeutic options by considering druggable pathways beyond known cancer genes.
- PanDrugs is publicly accessible via a web tool and API for integration into custom pipelines.
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