As demonstrated by the EBCTCG meta-analyses, 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 de-escalation of the overall treatment burden. 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- 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 aspect of breast cancer treatment calls 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 score as determined by the genomic profile 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-specific, cytotoxic T-lymphocytes might contribute to the efficacy of RT. However, high tumour infiltrating lymphocytes (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. Also the Profile for the Omission of Local Adjuvant Radiotherapy “POLAR”, 16-gene molecular signature that was developed based on gene expression differences between patients with and without local recurrence after breast-conserving surgery carries significant promises, as it may predict which patients may and may not benefit from radiation therapy after breast-conserving surgery.
Concluding, 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 de-escalating of treatments based on beliefs and assumptions rather than on solid evidence.