ABSTRACT Background Population-scale molecular profiling integrated into routine healthcare could accelerate biomarker discovery, validation, and implementation, but the feasibility and sustainability of such an approach have rarely been demonstrated prospectively. The Sweden Cancerome Analysis Network - Breast (SCAN-B) Initiative was established to integrate prospective molecular profiling with population-based breast cancer care and create an infrastructure for translating molecular discoveries into clinical practice ( ClinicalTrials.gov identifier NCT02306096 ). Methods We evaluated the first 10 full calendar years of SCAN-B, encompassing patients with primary invasive breast cancer enrolled between August 30, 2010 and December 31, 2020. Enrollment and biospecimen collection were compared with all eligible breast cancer diagnoses in participating hospitals to assess population coverage and representativeness. Clinicopathological characteristics, treatments, recurrence-free survival, overall survival, RNA-sequencing-based molecular subtypes and risk-of-recurrence, and somatic mutations were evaluated. We additionally report the translation of SCAN-B molecular profiling from the research setting into routine clinical diagnostics. Results Among 16,381 estimated eligible breast cancer diagnoses, 13,940 patients (85.1%) were prospectively enrolled across participating Swedish hospitals. Baseline blood samples were obtained from 98.4% of enrolled patients and tumor specimens from 71.1%; 9,323 tumors (94.0% of submitted tumor specimens) underwent RNA-sequencing. The enrolled cohort was broadly representative of the underlying breast cancer population across major clinicopathological characteristics. Integration of longitudinal clinical data with molecular profiling enabled characterization of real-world treatment patterns, long-term outcomes, molecular subtypes, risk-of-recurrence, and the somatic mutational landscape in this population-based cohort. Building on prospective real-time RNA-sequencing and subsequent development and validation of single-sample molecular subtype and risk-of-recurrence predictors, the SCAN-B workflow was transferred into routine clinical molecular diagnostics in Skåne and Blekinge in 2021. Through January 2026, more than 3,000 patients had received clinical RNA-sequencing-based molecular subtype and risk-of-recurrence reports, while prospective SCAN-B enrollment and transfer of samples and molecular data into the research infrastructure continued. Patient enrollment continues prospectively, with over 23,000 patients accrued as of January 2026. Conclusions A prospective, population-based molecular profiling program can be integrated into routine breast cancer care at scale while maintaining high population coverage and representativeness. Over more than a decade, SCAN-B progressed from prospective biosampling and molecular profiling through biomarker development and validation to implementation of RNA sequencing-based testing in routine healthcare. This model establishes a continuous framework linking population-based molecular research, biomarker discovery and validation, and clinical implementation, and provides a strategy for integrating precision oncology research with routine cancer care. Trial registration ClinicalTrials.gov identifier NCT02306096

PURPOSE:PORTOS is a 24-gene radiation response signature developed and validated in multiple randomized trials in prostate cancer. Given its basis in general radiation and DNA damage response pathways, we sought to evaluate whether PORTOS could also predict RT benefit in breast cancer. METHODS:PORTOS scores were calculated from gene expression profiles of 765 tumor samples from SweBCG91RT, a randomized trial of adjuvant whole-breast RT versus observation following breast-conserving surgery in node-negative stage I-IIA breast cancer. The primary endpoint was 10-year cumulative incidence (CI) of any recurrence, which closely mirrored the prostate cancer endpoints PORTOS was validated on. Patient-reported breast pain and tumor-infiltrating leukocytes (TILs) were also analyzed. RESULTS:A significant interaction (P = 0.049) between PORTOS and RT was observed for 10-year CI of any recurrence. Patients in the top 75% of PORTOS scores derived substantial benefit from RT (subdistribution hazard ratio (SHR) = 0.46, P < 0.001), compared to those in the bottom 25% (SHR = 0.73, P = 0.24). Higher PORTOS scores were also associated with increased risk of RT-related breast pain, though the interaction P-value was not significant (interaction P = 0.07). PORTOS was weakly anti-correlated with tumor size, histologic grade, and TILs, and provided orthogonal information to previously validated signatures ARTIC and POLAR. CONCLUSION:PORTOS predicts benefit from RT for any recurrence in early-stage breast cancer, mirroring its performance in prostate cancer. It is the first radiation response biomarker to demonstrate predictive value for both efficacy and toxicity across randomized trials in multiple tumor types.

Supplementary Figure 7 showing immune metagene rank scores for the IM classifier applied to 23 FUSCC_validation tumors with no IM consensus label from the online TNBCtype tool.

Supplementary Figure 6 showing immune cell fraction estimates for samples obtained pre- and post-treatment.

Supplementary Table 1 providing annotations for included samples.

Clinicopathologic and molecular characteristics of included TNBC cohorts.

Triple-negative breast cancer (TNBC) accounts for 10% to 20% of primary breast cancers and often has early relapses and aggressive progression. An activated tumor immune response can be prognostic in patients with treatment-naïve and chemotherapy-treated TNBC and may be assessed using gene expression data. We derived a stand-alone predictor for a proposed immunomodulatory transcriptional TNBC subtype in a training cohort of 235 patients with primary disease based on random forest modeling of RNA sequencing data. Validation in independent TNBC cohorts totaling more than 1,200 patients demonstrated that the classifier recapitulates the immunomodulatory mRNA subtype classification, is associated with elevated immune expression and diversity of T-cell receptor genes, is associated with response to neoadjuvant chemotherapy, and can separate patients into subgroups with better or worse prognosis after adjuvant chemotherapy. The availability of stand-alone classifiers for mRNA-based prediction may further enhance RNA sequencing’s usability in a more routine clinical context and for translational endpoints in clinical trials. Significance: Tumor immune response has prognostic and treatment predictive value in TNBC and can be estimated by, e.g., mRNA profiling. Translating this association into classifications for single patients requires stand-alone predictors. We have developed one such mRNA classifier that could be applied in future clinical contexts and clinical trials.

BackgroundSeveral cancer types have increased PFKFB3, a glycolytic enzyme for which potent inhibitors have been found. Inhibition of PFKFB3 impairs DNA repair after irradiation of cancer cells, making it a possible radiosensitization target. The SweBCG91RT trial, in which breast cancer patients were randomized to postoperative radiotherapy or not, was used to investigate PFKFB3 as a clinical marker of sensitivity to adjuvant radiotherapy.MethodsNuclear protein levels of PFKFB3 were assessed with immunohistochemistry in primary breast tumors (n = 970) and whole-cell RNA levels with microarray gene expression (n = 765). Multivariable competing risks regression analysis was employed for the effect of radiotherapy on incidence of ipsilateral breast tumor recurrence (IBTR), depending on PFKFB3 levels.ResultsTumors with high levels of nuclear protein and RNA had the largest effect on incidence of IBTR of adjuvant radiotherapy, however without evidence of an interaction. PFKFB3 RNA correlated with subtype, as high levels were more common among the human epidermal growth factor receptor 2 (HER2) positive and Luminal A subtypes than Luminal B and triple negative tumors.ConclusionHigh PFKFB3 is associated with a larger reduction of IBTR after radiotherapy but PFKFB3 cannot reliably be used as a predictive marker of sensitivity to adjuvant radiotherapy in breast cancer. PFKFB3 expression differed with subtype, indicating that it may be a better marker among Luminal A and HER2 positive tumors, but this is yet to be investigated.Trial registrationThe trial has been retrospectively registered at clinicaltrials.gov 2024-10-03 (NCT06637202).

Changes in TIME status in paired pre- and posttreatment NAC patients. A, Sankey plot of predicted IM status before treatment and after treatment at surgery (based on RNA-seq data from surgical tissue) for 36 patients with RD and matched tumor specimens from the SCAN-B_validationNAC cohort, followed by a later recorded distant metastasis event (asterisks). B, Rank scores for the immune response metagene for the 36 RD patients with paired pre- and posttreatment samples stratified by their combined pre- and posttreatment IM prediction. Left: immune rank scores based on RNA-seq data from pretreatment biopsies. Right: immune rank scores based on RNA-seq data from posttreatment surgical tissue. Numbers above boxplots correspond to sample sizes. C, Immune cell type scores imputed with CIBERSORTx for cell types that differed between pre- and posttreatment samples for IM-predicted positive tumors before treatment that were considered IM negative after treatment. Unadjusted P values reported from two-sided paired t tests. D, Strategy to identify differentially expressed genes between predicted IM-positive tumors before treatment that changed to IM negative after treatment (pos/neg) vs. those that remained IM positive (pos/pos). E, Importance scores for the 433 genes in the IM predictor with scores > 0. Scores for the eight genes from the set of 51 identified in (D) overlapping with the 433 are marked by points. F, FPKM gene expression (gex) data for the interferon signaling–associated genes CD38 (hallmark IFNγ response) and CXCL10 (hallmark IFNα response) from pretreatment and posttreatment samples stratified by their predicted IM status. Two-sided P values calculated using a Wilcoxon test. Gene expression of each gene in IM-predicted negative tumors both before and after treatment (neg/neg) included for reference. G, Same as (F) but for the immune-inhibitory genes PD-L1 (CD274) and LAG3. DEG, differentially expressed gene; GSEA, gene set enrichment analysis.

Protocol for original SweBCG91RT trial

PURPOSE:Identifying biomarkers of radiotherapy (RT) response is important for optimizing the treatment of early breast cancer. In this study, we tested the interaction between endothelial cell (EC) expression of phospho-Tyr397-FAK (pY397-FAK) and adjuvant-RT on clinical outcomes after breast-conserving surgery (BCS) within a randomized study. Preclinical data suggest an enhanced effect of RT on low EC_pY397-FAK expression. EXPERIMENTAL DESIGN:We analyzed tissue microarrays from the Swedish Breast Cancer Group 91 Radiotherapy (stage I-II, lymph node-negative) breast cancer cohort, consisting of 1,178 patients randomly assigned to receive either BCS alone or BCS plus adjuvant-RT. Tissue microarray sections were immunostained for pY397-FAK, CD31, α-smooth muscle actin, and pan-cytokeratin. HALO analysis scored mean pY397-FAK intensity in CD31+ ECs, pan-cytokeratin-positive tumor epithelial cells, and α-smooth muscle actin + mural/stromal cells per core. For 822 patients, multivariable Cox regression analysis was performed for the primary and secondary 5-year endpoints, locoregional recurrence and all recurrence, respectively, as dependent variables and RT and EC_pY397-FAK as independent variables. RESULTS:EC_pY397-FAK expression was not predictive for the primary endpoint locoregional recurrence (P = 0.098), but the direction of the RT effect was in line with preclinical findings. For the secondary endpoint all recurrence, there was a significant interaction (P = 0.026) between EC_pY397-FAK and RT. Without RT, higher EC_pY397-FAK expression resulted in a lower risk for all recurrence (HR = 0.74 per SD; 95% confidence interval = 0.57-0.96; P = 0.026). CONCLUSIONS:Within the first 5 years following BCS, patients with low EC_pY397-FAK expression derive greater benefit from RT than patients with high EC_pY397-FAK expression. However, without RT, low EC_pY397-FAK expression is associated with a higher risk of recurrence.

Supplementary Figure 4 showing IM predictor probabilities in independent validation cohorts.

Immunescore (A), developed in this manuscript, showed a stronger correlation with tumor-infiltrating lymphocytes than other developed methods (B and C) to quantify the degree of immune infiltration.

Supplementary Table 2 (RNAseq estimates)

Supplementary MethodsTable S5. Clinical characteristics of the Sjöström and Servant cohortsTable S6. Comparison of included versus excluded patientsTable S7. 10-year follow-up for local recurrence (IBTR). Flexible parametric survival analysis with Royston-Parmar (RP) regression models used in Figures 2 and 3Table S8. 10-year follow-up for local recurrence (IBTR). Flexible parametric survival analysis with Royston-Parmar (RP) regression models with adjustment for other covariatesTable S9. Absolute number of events within different tertiles of Immunescore and Proliferative Index and depending on RT treatmentTable S10. Unadjusted and adjusted analysis of the interaction between the Integrated model and RT in the SweBCG91RT cohortTable S11. Distribution of subtypes in the tertiles of the Integrated score among high-risk patients

Immunofluorescence staining for pY397-FAK, CD31, PanCK and αSMA. Representative immunofluorescence images of a patient in the highest and lowest quartiles of pY397-FAK intensity, in the CD31-positively stained endothelial cells (EC_ pY397-FAK) (A), panCK-positively stained epithelial tumour cells (TC_ pY397-FAK) (B) and ααSMA-positively stained mural and stromal cells (αSMA_ pY397-FAK) (C). Lowest panels represent high power regions of images in the row above denoted by the dotted boxes.

Supplementary Figure 2 showing IM predictor development and performance in the training cohort.

BACKGROUND:This prospective cohort study aimed to assess whether postoperative radiotherapy could safely be omitted in women aged 65 years and older with low-risk, estrogen receptor-positive T1N0 breast cancer treated with breast-conserving surgery and adjuvant endocrine therapy. METHODS:Eligible patients were women aged 65 years and older with unifocal, nonlobular, grade 1 or 2, estrogen receptor-positive, pT1N0 breast cancer treated with breast-conserving surgery and endocrine therapy for 5 years. Patients were followed up with mammography at least annually for 10 years. The primary endpoint was local recurrence. Secondary endpoints were contralateral breast cancer, recurrence-free survival, and overall survival. RESULTS:The final study cohort included 601 patients with a median age of 71 years (range = 65-90 years) and a median tumor size of 11 mm (range = 3-20 mm). Median follow-up time was 119 months (interquartile range = 103-121 months). The cumulative incidence of local recurrence was 1.5% (95% confidence interval [CI] = 0.8% to 2.8%) and 5.5% (95% CI = 3.8% to 7.6%) at 5 and 10 years, respectively. The cumulative incidence of contralateral breast cancer was 1.7% (95% CI = 0.9% to 3.0%) at 5 years and 4.5% (95% CI = 3.0% to 6.6%) at 10 years. The overall survival rate at 10 years was 83.1% (95% CI = 80.8% to 85.4%). In total, 3 (0.5%) patients died because of breast cancer. CONCLUSION:Our results support the possibility to omit radiotherapy after breast-conserving surgery in a well-defined subgroup of women aged 65 years and older with low-risk, estrogen receptor-positive, pT1N0 breast cancer receiving adjuvant endocrine therapy.

Gene sets from the molecular signatures database were used to create a model measuring immunological activity and immunomodulatory tumor-intrinsic factors. These were merged to create a model considering the interaction between the antitumoral immune response and tumor-intrinsic immunomodulatory factors.

Ki67 was evaluated by a board-certified pathologist on TMAs.