Novel immunohistochemistry-based signatures to predict metastatic site of triple-negative breast cancers

Background: Although distant metastasis (DM) in breast cancer (BC) is the most lethal form of recurrence and the most commonunderlying cause of cancer related deaths, the outcome following the development of DM is related to the site of metastasis.Triple negative BC (TNBC) is an aggressive form of BC characterised by early recurrences and high mortality. Athough multiplevariables can be used to predict the risk of metastasis, few markers can predict the specific site of metastasis. This study aimed atidentifying a biomarker signature to predict particular sites of DM in TNBC.Methods: A clinically annotated series of 322 TNBC were immunohistochemically stained with 133 biomarkers relevant to BC, todevelop multibiomarker models for predicting metastasis to the bone, liver, lung and brain. Patients who experienced metastasisto each site were compared with those who did not, by gradually filtering the biomarker set via a two-tailed t-test and Coxunivariate analyses. Biomarker combinations were finally ranked based on statistical significance, and evaluated in multivariableanalyses.Results: Our final models were able to stratify TNBC patients into high risk groups that showed over 5, 6, 7 and 8 times higher riskof developing metastasis to the bone, liver, lung and brain, respectively, than low-risk subgroups. These models for predictingsite-specific metastasis retained significance following adjustment for tumour size, patient age and chemotherapy status.Conclusions: Our novel IHC-based biomarkers signatures, when assessed in primary TNBC tumours, enable prediction of specificsites of metastasis, and potentially unravel biomarkers previously unknown in site tropism