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Data Tools Designed for Genomics-Based Precision Cancer Care

Computational biology illustration

(Lawrence Livermore National Lab)

31 May 2018. A computerized system is available that analyzes the genomic composition of cancer patients and recommends personalized treatments that its designers say take into account a larger array of factors than comparable systems. The system known as PanDrugs, developed by a team at Spain’s National Cancer Research Centre, or CNIO, in Madrid, is described in today’s issue of the journal Genome Medicine.

PanDrugs seeks to offer computational tools for selecting cancer treatments personalized for patients based on documented evidence of those therapies addressing the molecular nature of the patients’ tumors. While many current precision medicine systems take into account the genomic profile of a patient’s tumors, the PanDrugs team says its system goes further by including evidenced-based data representing the signaling pathways corresponding to genomic alterations in the tumors, as well as biomarkers, or characteristic proteins, associated with those mutations.

The result says Fatima Al-Shahrour, director of CNIO’s bioinformatics unit that developed PanDrugs, is a richer resource for physicians in determining a treatment strategy for cancer patients. “The main novelty introduced in this methodology compared with current tools,” says  Al-Shahrour in a CNIO statement, “is the broadening of the search space to provide therapeutic options.” The addition of signaling pathway evidence from these biological circuits, adds Al-Shahrour, enriches “the therapeutic arsenal against tumors and opens new avenues for personalized medicine.”

The PanDrugs portal collects data from 24 cancer databases. Of those sources, 18 databases are curated by experts, while the other 6 databases represent gene-drug associations from experimental drug screenings. As of the publication date, PanDrugs includes data on 9,092 drugs, 4,804 unique genes, and 43,909 direct, and non-redundant gene-drug interactions. The system returns a Gene Score indicating the most relevant genetic alterations responsible for the cancer, and a Drug Score indicating the most responsive and suitable treatments for the patient.

The CNIO team tested PanDrugs’ recommendations against data in the Cancer Genome Atlas, a database of genomic mappings for 200 types of cancer, hosted by National Cancer Institute, part of National Institutes of Health in the U.S. The atlas includes data from cancerous and non-cancerous tissue samples donated by 11,000 patients, from which the researchers drew some 7,000 samples representing 20 types of tumors. The results, say the authors, show PanDrugs identified expanded treatment options for 93 percent of the patients sampled.

In addition, the researchers tested the findings from a PanDrugs analysis of a patient’s squamous cell lung cancer tumor tissue grafted on a mouse. The PanDrugs analysis identified a number of drugs for treating the human cancer in the mouse, with two of the recommended treatments showing measurable reduction in tumor growth.

The PanDrugs system and database are freely available from CNIO, also which offers an application program interface enabling connections with other analytical systems, and a docker image from GitHub for downloading containers with an all-in-one PanDrugs server. The following infographic describes the PanDrugs workflow; click on the image for a full-size view.

PanDrugs workflow

PanDrugs workflow, click on image for full-size view. (CNIO)

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