DIPCAN, a multidimensional approach to precision oncology: Harnessing genomic, clinical, pathological and radiographic data to advance personalized cancer treatment.

TPS1656 Background: Advances in big data analytics and artificial intelligence (AI) are enabling novel approaches to patient classification in oncology. While existing studies often correlate only a few data types, the DIPCAN Study (Digitalisation and Integral Management of Personalised Medicine in CANcer) seeks a comprehensive, integrated analysis combining phenotypic, clinical, pathological, radiomic, and genomic data from patients with metastatic cancer in Spain. DIPCAN aims to deepen insights into cancer’s multifactorial nature, driving personalized care and more precise therapeutic strategies. Methods: DIPCAN was initiated through a consortium comprising five technology and healthcare SMEs—Genomcore, Quibim, Pangaea Oncology, Artelnics, and Atrys Health—alongside Eurofins Megalab and the non-profit MD Anderson International Foundation Spain. Funding was secured via the Spanish Ministry of Economic Affairs and Digital Transformation under the EU-funded Recovery, Transformation, and Resilience Plan (R&D Missions Program in Artificial Intelligence, File No. MIA.2021.M02.0006). DIPCAN’s primary objective is to characterize and map clinical, phenotypic, genomic, and radiomic profiles of metastatic cancer patients across Spain. Secondary goals involve developing Big Data, AI, and machine learning tools to enable multidimensional analysis of these patients. Eligible patients are 18 years or older, have histologically confirmed metastatic solid tumors, a life expectancy exceeding three months, and available tumor material for histological and molecular analyses. Participants consent to undergo a comprehensive set of diagnostic and imaging procedures outlined in the study protocol. If recent tumor tissue (<3 years) is unavailable, patients may opt for a current biopsy or liquid biopsy. At no cost, participants receive consultations with oncology and drug development specialists, who document baseline characteristics and compile structured medical histories. Additional diagnostics include bloodwork emphasizing lipid metabolism, digital pathology, extensive NGS sequencing on tissue or blood, and a full-body MRI. All participants receive digital access to their data and a clinical report with tailored recommendations for their physicians. With ethics approval in place, DIPCAN has enrolled 1,500 patients since June 14, 2022. Data collection is ongoing, with anticipated advancements in AI-driven analysis aimed at refining precision oncology approaches for metastatic cancer in Spain. Clinical trial information: 2021.M02.0006 .

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Publication Details

Journal
Journal of Clinical Oncology
Published
2025-05-28
DOI
https://doi.org/10.1200/jco.2025.43.16_suppl.tps1656
Primary Topic
Cancer Genomics and Diagnostics
Type
article
Field-Weighted Citation Impact
0.00

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article

DIPCAN, a multidimensional approach to precision oncology: Harnessing genomic, clinical, pathological and radiographic data to advance personalized cancer treatment.

Roberto López, Fernando Franco, Teresa Valdés‐Sánchez, E. Martín-Illana et al.
Journal of Clinical Oncology
Cancer Genomics and Diagnostics
article

DIPCAN, a multidimensional approach to precision oncology: Harnessing genomic, clinical, pathological and radiographic data to advance personalized cancer treatment.

Roberto López, Fernando Franco, Teresa Valdés‐Sánchez, E. Martín-Illana, Elena Báez, Enrique Grande, Alberto Orta, Víctor González‐Rumayor, Álvaro Huber dos Santos, Carlos Tarín, Carlota Costa, David G. Pisano, Mónica Díez-Fairén, Cristina Aguado, Marta Martín, Ruth Román, Anna Nogué Infante, Carmen Prieto-de-la-Lastra, Raquel Sáiz-Martínez, Xana Da Silva
article en

Abstract

TPS1656 Background: Advances in big data analytics and artificial intelligence (AI) are enabling novel approaches to patient classification in oncology. While existing studies often correlate only a few data types, the DIPCAN Study (Digitalisation and Integral Management of Personalised Medicine in CANcer) seeks a comprehensive, integrated analysis combining phenotypic, clinical, pathological, radiomic, and genomic data from patients with metastatic cancer in Spain. DIPCAN aims to deepen insights into cancer’s multifactorial nature, driving personalized care and more precise therapeutic strategies. Methods: DIPCAN was initiated through a consortium comprising five technology and healthcare SMEs—Genomcore, Quibim, Pangaea Oncology, Artelnics, and Atrys Health—alongside Eurofins Megalab and the non-profit MD Anderson International Foundation Spain. Funding was secured via the Spanish Ministry of Economic Affairs and Digital Transformation under the EU-funded Recovery, Transformation, and Resilience Plan (R&D Missions Program in Artificial Intelligence, File No. MIA.2021.M02.0006). DIPCAN’s primary objective is to characterize and map clinical, phenotypic, genomic, and radiomic profiles of metastatic cancer patients across Spain. Secondary goals involve developing Big Data, AI, and machine learning tools to enable multidimensional analysis of these patients. Eligible patients are 18 years or older, have histologically confirmed metastatic solid tumors, a life expectancy exceeding three months, and available tumor material for histological and molecular analyses. Participants consent to undergo a comprehensive set of diagnostic and imaging procedures outlined in the study protocol. If recent tumor tissue (<3 years) is unavailable, patients may opt for a current biopsy or liquid biopsy. At no cost, participants receive consultations with oncology and drug development specialists, who document baseline characteristics and compile structured medical histories. Additional diagnostics include bloodwork emphasizing lipid metabolism, digital pathology, extensive NGS sequencing on tissue or blood, and a full-body MRI. All participants receive digital access to their data and a clinical report with tailored recommendations for their physicians. With ethics approval in place, DIPCAN has enrolled 1,500 patients since June 14, 2022. Data collection is ongoing, with anticipated advancements in AI-driven analysis aimed at refining precision oncology approaches for metastatic cancer in Spain. Clinical trial information: 2021.M02.0006 .

Journal of Clinical OncologyVol. 43(16_suppl)
Universidad de Salamanca (ES), Hospital Universitario Dexeus (ES), Euroortodoncia (Spain) (ES), Madrid Health Service (ES), MD Anderson Cancer Center Madrid (ES)
European Commission
Openalex Percentile: Top 84%
Cancer Genomics and Diagnostics
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