Cristina Tebar

PURPOSE: A substantial proportion of patients receiving genomically matched therapies do not achieve clinical benefit, underscoring the influence of nongenetic factors on cancer outcomes. High-Definition Oncology (HDO) proposes integrating longitudinal, multimodal patient data—spanning clinical, molecular, physiological, and behavioral domains—to enable truly individualized cancer care. This manuscript describes the HDO study design, framework, and feasibility results in women with metastatic cancer. METHODS: We initiated a prospective, multicenter observational study (HDO study; ClinicalTrials.gov identifier: NCT06590506 ) enrolling 300 female patients with newly diagnosed metastatic breast, lung, or colorectal cancer. Here, we report the study design, standardized workflows, prespecified feasibility criteria, and early internal pilot results. Eleven data modalities are collected longitudinally, including tumor and germline genomics, germline epigenomics, gut microbiome, blood and stool metabolomics and proteomics, exposome characterization, wearable-derived physiological monitoring, digital footprint assessment, medical imaging, and patient-reported outcomes. Standardized workflows govern clinical procedures, data acquisition, biospecimen processing, and quality control across all participating sites. RESULTS: Feasibility was evaluated in the first 30 participants (10% of planned accrual). Patients completed 100% of scheduled clinical visits, 97.4% of planned plasma collections, 80.7% of stool samples, and all tumor biopsies. Wearable devices 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. Biospecimens met predefined quality control metrics across all molecular modalities. Engagement with mobile applications for pain and emotion reporting exceeded 80%. CONCLUSION: The HDO study demonstrates the feasibility of comprehensive, longitudinal, multimodal data collection in women with metastatic cancer. This internal pilot establishes an integrated framework for future analyses aimed at characterizing disease trajectories, defining molecular and physiological determinants of outcomes, and developing patient-specific computational models.

Associations between HER2DX ERBB2 score and pathologic variables. Distribution of HER2DX ERBB2 score groups (low, medium, and high; A); HER2DX ERBB2 score by tumor grade (B), HR status (C), HER2 IHC status (D), TLS status (E), and spatial immune distribution (F). All scores are shown on a continuous scale from 1 to 99. Boxplots show IQR with medians indicated and display score distributions across groups. Statistical comparisons were performed using appropriate parametric tests.

Associations between HER2DX risk score and pathologic variables. Distribution of HER2DX risk groups (low vs. high; A); HER2DX risk score by tumor grade (B), HR status (C), HER2 IHC status (D), TLS status (E), and spatial immune distribution (F). All scores are shown on a continuous scale from 1 to 99. Boxplots show IQR with medians indicated and display score distributions across groups. Statistical comparisons were performed using appropriate parametric tests.

Correlations between HER2DX molecular modules and pathology features. Heatmap of Pearson correlation coefficients between HER2DX scores/modules (pCR score, risk score, ERBB2 score, IGG, proliferation, and luminal) and pathologic features (TIL%, Ki67, HR status, TLS, HER2 IHC, tumor grade, and spatial pattern; A); scatter plots showing IGG score vs. TIL% (B), proliferation score vs. Ki67% (C), luminal score vs. binary HR status (D), and luminal score vs. ER % levels (E). Correlation values and P values are shown; positive correlations reflect biological concordance between genomic and pathologic features. Statistical comparisons were performed using appropriate parametric tests.

Purpose:HER2DX is a validated genomic assay used to support treatment decisions in early-stage HER2-positive (HER2+) breast cancer. It provides three scores: relapse risk, likelihood of pathologic complete response (pCR), and ERBB2 mRNA expression. This study aimed to evaluate the association between HER2DX and histopathologic features and assess its relationship with pCR after neoadjuvant therapy.Experimental Design:Patients with newly diagnosed stage I to III HER2+ breast cancer were analyzed based on available HER2DX results during routine care in Spain (January 2022–June 2025). Centralized HER2DX testing was performed on formalin-fixed, paraffin-embedded tumor samples. Histopathologic analysis included tumor grade, hormone receptor status, histologic subtype, Ki67 index, HER2 IHC score, stromal tumor-infiltrating lymphocytes (TIL), tertiary lymphoid structures, and spatial immune distribution. Univariate and multivariable logistic regression analyses were conducted to identify factors associated with pCR after neoadjuvant trastuzumab-based therapy.Results:A total of 410 HER2+ tumors were analyzed, and 250 patients received neoadjuvant trastuzumab-based therapy with available surgical outcomes (36% achieved a pCR). HER2DX pCR scores were significantly associated with all eight histopathologic features, whereas relapse risk and ERBB2 scores were associated with five and two, respectively. TIL correlated with the immune/immunoglobulin signature (r = 0.59), and Ki67 with the proliferation signature (r = 0.50). The HER2DX pCR score remained the only independent predictor of pCR in multivariable analysis (OR, 1.77; 95% confidence interval, 1.08–2.97; P = 0.030).Conclusions:HER2DX reflects key biological and pathologic features of HER2+ breast cancer and independently predicts pCR, supporting its utility for individualized treatment decision-making.

Associations between HER2DX pCR score and standard pathologic features. Distribution of HER2DX pCR score groups (low, medium, and high; A); HER2DX pCR score by tumor grade (B), HR status (C), HER2 IHC status (D), TLS status (E), and spatial immune distribution (F). All scores are shown on a continuous scale from 1 to 99. Boxplots show IQR with medians indicated and display score distributions across groups. Statistical comparisons were performed using appropriate parametric tests.

Overview of patient and tumor characteristics. Patient distribution across the top 10 hospitals by enrollment (A), tumor grade (B), HR status (C), HER2 IHC status (D), Ki67 expression (E), stromal TIL percentage (F), TIL grouped as <20% vs. ≥20% (G), TLS status (H), spatial immune distribution (I), and histologic subtype (J). Each panel summarizes the distribution of clinical and pathologic variables across the full study cohort (N = 410).

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Associations between HER2DX scores and histopathologic variables.

Purpose: HER2DX is a validated genomic assay used to support treatment decisions in early-stage HER2-positive (HER2+) breast cancer. It provides three scores: relapse risk, likelihood of pathologic complete response (pCR), and ERBB2 mRNA expression. This study aimed to evaluate the association between HER2DX and histopathologic features and assess its relationship with pCR after neoadjuvant therapy. Experimental Design: Patients with newly diagnosed stage I to III HER2+ breast cancer were analyzed based on available HER2DX results during routine care in Spain (January 2022–June 2025). Centralized HER2DX testing was performed on formalin-fixed, paraffin-embedded tumor samples. Histopathologic analysis included tumor grade, hormone receptor status, histologic subtype, Ki67 index, HER2 IHC score, stromal tumor-infiltrating lymphocytes (TIL), tertiary lymphoid structures, and spatial immune distribution. Univariate and multivariable logistic regression analyses were conducted to identify factors associated with pCR after neoadjuvant trastuzumab-based therapy. Results: A total of 410 HER2+ tumors were analyzed, and 250 patients received neoadjuvant trastuzumab-based therapy with available surgical outcomes (36% achieved a pCR). HER2DX pCR scores were significantly associated with all eight histopathologic features, whereas relapse risk and ERBB2 scores were associated with five and two, respectively. TIL correlated with the immune/immunoglobulin signature (r = 0.59), and Ki67 with the proliferation signature (r = 0.50). The HER2DX pCR score remained the only independent predictor of pCR in multivariable analysis (OR, 1.77; 95% confidence interval, 1.08–2.97; P = 0.030). Conclusions: HER2DX reflects key biological and pathologic features of HER2+ breast cancer and independently predicts pCR, supporting its utility for individualized treatment decision-making.