Abstract MS2-2: Can genomic risk be used to tailor radiation therapy?

Abstract

Abstract Radiation therapy (RT) reduces any-recurrence risks and breast cancer related mortality after mastectomy for node positive disease and after breast conserving surgery. The relative risk reduction is partially independent from patient, tumour and treatment related factors, while the absolute benefit depends to a large extent on the absolute risks without RT. Of note is an important interaction between systemic and locoregional treatments. The continuous improvements in outcomes after breast cancer diagnosis led to a quest for treatment de-escalation. In this, the decreased extent of axillary surgery led to an increased proportion of patients eligible for nodal RT. While most data concerning prognostic and predictive value of genomic data is related to metastatic disease and to systemic treatments, more recently also RT evolves from the “one-size fits all” to a much more “tailor-made approach”. Optimally, current tailoring of locoregional treatments involves decreasing volumes and extensiveness, maintaining treatment focus mainly at high-risk areas, while de-escalating treatment to low-risk areas. The multidisciplinary aspects call for integration of predictive and prognostic tools and looking into optimally combining less of both systemic and locoregional treatments to optimise tumour control while sparing normal tissues.Not only distant but also locoregional recurrences risks depend on the intrinsic tumour phenotype, which can be expressed by the genomic profile. Several post-hoc evaluations of datasets derived from prospective studies showed that the genomic profile score can assist in predicting locoregional recurrence risks (and thereby indirectly the possible benefits of RT) or, with more scarce data, the interaction between the genomically predicted risk and the risk reduction obtained by RT. Currently, several trials are evaluating further de-escalation of locoregional treatments in patients with favourable intrinsic tumour types. Of interest in patients with intrinsic high-risk tumour types is the response to primary systemic therapy, with trials ongoing to de-escalate both axillary and local management after a favourable tumour response. Preclinical data suggests that immunogenic cell death, mediated through activation of tumour infiltrating lymphocytes (TIL’s) might contribute to the efficacy of RT. However, high TIL’s levels are seen in only 10% of breast cancers, more commonly in basal-like- and Her2-enriched subtypes. The mechanism behind this association with TIL’s remain unclear. Of particular interest seems the recently validated genomic adjusted radiation dose (GARD), aimed to personalise RT dose prescription based on the biological effect rather than merely on physical dose. GARD combines a gene expression assay, assuming pan-tissue biological networks of radiosensitivity and radioresistance, with a linear quadratic model for estimation of total radiation dose in tissues. Up to now, clinical utility remains to be confirmed, preferably by integrating GARD in prospective clinical research. Summary: at present no validated biomarkers can reliably predict the benefit derived from RT at the individual patient’s level, with current evidence not yet robust enough to guide decision making. Available data are mainly based on retrospective analyses of older trials, necessitating prospective validation in contemporary cohorts. Research is ongoing to personalise RT using biological factors including gene expression profiles. Projects to identify genetic variants associated with susceptibility to radiotoxicity are required to proceed to a more personalised indication/target volume/dose approach for our patients. In the meantime, we should avoid jeopardising the impressive improvements obtained in the outcomes after breast cancer diagnosis by precipitated treatment de-escalating based on beliefs and assumptions. Citation Format: PMP Poortmans. Can genomic risk be used to tailor radiation therapy? [abstract]. In: Proceedings of the 2021 San Antonio Breast Cancer Symposium; 2021 Dec 7-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2022;82(4 Suppl):Abstract nr MS2-2.