Background Despite significant advances in precision oncology, a large proportion of patients receiving genomically matched therapies fail to respond. Emerging evidence highlights that cancer outcomes are influenced by multiple non-genetic factors, including microbiome composition, metabolic environment, physiological parameters, and lifestyle habits. High-Definition Oncology (HDO) aims to integrate multi-dimensional, longitudinal patient data—spanning clinical, molecular, physiological, and behavioral domains—to enable truly individualized cancer care.

Methods We launched a prospective, multicenter observational study (HDO study; NCT0659050628) to longitudinally profile 300 female patients with newly diagnosed metastatic breast, lung, or colorectal cancer. Eleven data modalities are collected, including tumor and germline genomics, germline epigenomics, gut microbiome, blood and stool metabolome and proteome, exposome analysis, continuous wearable-based physiological monitoring, digital footprint, medical imaging, and patient-reported outcomes. This manuscript provides a comprehensive description of the study design, data acquisition workflows, sample processing pipelines, quality control procedures, and analytical strategies.

Results We report feasibility data from the first 10% of accrual (n=30). Patients completed 100% of scheduled clinical visits, 97.4% of planned plasma collections, 80.7% of stool samples, and 100% of tumor biopsies. Physiological monitoring captured activity, heart rate, sleep, and blood oxygen saturation data during 95.0%, 84.2%, 90.6%, and 70.7% of total patient-days, respectively. Biological samples met quality control criteria across all omic layers. Patient engagement with mobile apps for pain and emotion reporting exceeded 80%.

Conclusions The HDO study demonstrates the feasibility of deep, longitudinal, multi-modal patient profiling in metastatic cancer. This foundational protocol sets the stage for future analyses aiming to define disease trajectories, molecular taxonomies of outcomes, and patient digital twins.

The authors have declared no competing interest.

This study was performed at Centro Nacional de Investigaciones Oncologicas and funded by the Instituto de Salud Carlos III and the European Union (NextGenerationEU/PRTR), project number PMP22/00032. Leonardo Garma is beneficiary of a MSCA fellowship funded by the European Union (HORIZON-MSCA-2023-PF-01-01, grant agreement 101155328 HD-BRECA).

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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The protocol for this study was approved by the ethical committee of the Fuenlabrada Hospital (protocol HDM-21/11).

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All data produced in the present study are available upon reasonable request to the authors