TY - JOUR
T1 - Biomarker-Directed Radiotherapy in Breast Cancer
T2 - A Narrative Review
AU - Meattini, Icro
AU - Coles, Charlotte E.
AU - Tramm, Trine
AU - Borghesi, Simona
AU - Krug, David
AU - Montero, Angel
AU - Nardone, Valerio
AU - Salvestrini, Viola
AU - Valzano, Marianna
AU - Valentini, Vincenzo
AU - Aristei, Cynthia
AU - Poortmans, Philip
AU - Arenas, Meritxell
AU - Boersma, Liesbeth J.
AU - Bolukbasi, Yasemin
AU - Ciabattoni, Antonella
AU - Franco, Pierfrancesco
AU - Genovesi, Domenico
AU - Person, Orit Kaidar
AU - Kouloulias, Vassilis
AU - Krengli, Marco
AU - Leonardi, Maria Cristina
AU - Lozza, Laura
AU - Marazzi, Fabio
AU - Masiello, Valeria
AU - Morganti, Alessio G.
AU - Offersen, Birgitte
AU - Palumbo, Isabella
AU - Pedretti, Sara
AU - Perrucci, Elisabetta
AU - Ratosa, Ivica
AU - Rivera, Sofia
AU - Trigo, Maria de Lurdes Garcia
AU - Assisi Think Tank Meeting Investigators
N1 - Funding Information:
Dr Coles is funded by the National Institute of Health and Care Research (NIHR) and supported by the NIHR Cambridge Biomedical Research Centre. The views expressed are those of the author and not necessarily those of the NIHR or the Department of Health and Social Care.
Publisher Copyright:
© 2025 American Medical Association. All rights reserved.
PY - 2025/3/20
Y1 - 2025/3/20
N2 - Importance: Integration of molecular biomarker information into systemic therapy has become standard practice in breast cancer care. However, its implementation in guiding radiotherapy (RT) is slower. Although postoperative RT is recommended for most patients after breast-conserving surgery and, depending on risk factors, following mastectomy, emerging evidence has indicated that patients with low scores on gene expression signatures or selected clinical-pathological features may have very low local recurrence rates. This narrative review explored the potential of biomarker-directed personalized RT approaches, which may optimize treatment strategies and be associated with improved patient outcomes and experiences. Observations: Distinctions between prognostic and predictive biomarkers were highlighted, emphasizing the importance of analytical and clinical validity in biomarker-based studies. Findings from studies investigating the prognostic and predictive value of various genomic signatures and immunohistochemical markers for guiding breast RT were presented. These included the Adjuvant Radiotherapy Intensification Classifier and the Profile for the Omission of Local Adjuvant Radiation, which have shown potential in predicting RT benefits. The genomic-adjusted radiation dose and role of tumor-infiltrating lymphocytes were also discussed. Ongoing clinical trials exploring the use of biomarkers in ductal carcinoma in situ and invasive breast cancer to refine RT decision-making were illustrated. Conclusions and Relevance: The results of this narrative review suggest that evidence-based shared decision-making is crucial to optimize treatment according to the individual's predicted benefits and risks along with their personal preferences. Incorporation of biomarker-directed approaches in RT for breast cancer may hold promise for personalized treatment, potentially facilitating omission of RT for patients at low risk of recurrence, while identifying those who may benefit from intensified therapy. This personalized RT approach may be associated with improved clinical outcomes and quality of life and facilitate decision-making for people with breast cancer. However, there remains a need for robust clinical and analytical validation of biomarkers to ensure reliability and clinical utility for RT optimization.
AB - Importance: Integration of molecular biomarker information into systemic therapy has become standard practice in breast cancer care. However, its implementation in guiding radiotherapy (RT) is slower. Although postoperative RT is recommended for most patients after breast-conserving surgery and, depending on risk factors, following mastectomy, emerging evidence has indicated that patients with low scores on gene expression signatures or selected clinical-pathological features may have very low local recurrence rates. This narrative review explored the potential of biomarker-directed personalized RT approaches, which may optimize treatment strategies and be associated with improved patient outcomes and experiences. Observations: Distinctions between prognostic and predictive biomarkers were highlighted, emphasizing the importance of analytical and clinical validity in biomarker-based studies. Findings from studies investigating the prognostic and predictive value of various genomic signatures and immunohistochemical markers for guiding breast RT were presented. These included the Adjuvant Radiotherapy Intensification Classifier and the Profile for the Omission of Local Adjuvant Radiation, which have shown potential in predicting RT benefits. The genomic-adjusted radiation dose and role of tumor-infiltrating lymphocytes were also discussed. Ongoing clinical trials exploring the use of biomarkers in ductal carcinoma in situ and invasive breast cancer to refine RT decision-making were illustrated. Conclusions and Relevance: The results of this narrative review suggest that evidence-based shared decision-making is crucial to optimize treatment according to the individual's predicted benefits and risks along with their personal preferences. Incorporation of biomarker-directed approaches in RT for breast cancer may hold promise for personalized treatment, potentially facilitating omission of RT for patients at low risk of recurrence, while identifying those who may benefit from intensified therapy. This personalized RT approach may be associated with improved clinical outcomes and quality of life and facilitate decision-making for people with breast cancer. However, there remains a need for robust clinical and analytical validation of biomarkers to ensure reliability and clinical utility for RT optimization.
U2 - 10.1001/jamaoncol.2024.5780
DO - 10.1001/jamaoncol.2024.5780
M3 - (Systematic) Review article
SN - 2374-2437
VL - 11
SP - 329
EP - 339
JO - JAMA Oncology
JF - JAMA Oncology
IS - 3
M1 - 5780
ER -