Outcome and human epidermal growth factor receptor (HER) 1–4 status in invasive breast carcinomas with proliferation indices evaluated by bromodeoxyuridine labelling

BACKGROUND: We have shown previously that whereas overexpression of human epidermal growth factor receptor (HER)1, HER2 and HER3 is associated with poor prognosis in breast cancer, HER4 is associated with a good prognosis. Cell proliferation is a key component of aggressive cancers and is driven by growth factors. In this study, bromodeoxyuridine (BrdU)-derived proliferation indices are correlated with clinical outcome and HER1–4 status for further clarification of the differing roles for the HER family at a biological level. METHODS: Seventy-eight invasive breast cancers had BrdU labelling in vivo to determine the BrdU labelling index (BLI) and the potential tumour doubling time (T(pot)). Long-term clinical follow-up was available for these patients. We used immunohistochemistry to establish the HER1–4 status in 55 patients from the BrdU cohort. RESULTS: We demonstrate a significant correlation between high BLI values and breast cancer-specific death (P = 0.0174). Low T(pot )times were also significantly correlated with breast cancer-specific death (P = 0.0258). However, BLI did not independently predict survival in Cox's multiple regression analysis when combined with other prognostic factors such as size, grade and nodal status. Tumours found to be positive for HER1, HER2 or HER3 had significantly (P = 0.041) higher labelling indices, with HER1 also showing significantly higher indices when considered independently (P = 0.024). Conversely, HER4 positivity was significantly correlated (P = 0.013) with low BLI values, in line with previous data associating this receptor with good prognosis tumours. CONCLUSIONS: These results support the hypothesis that HER1–3 are associated with driving tumour proliferation, whereas HER4 is involved in a non-proliferative or even protective role

Genetic linkage analysis in the age of whole-genome sequencing

For many years, linkage analysis was the primary tool used for the genetic mapping of Mendelian and complex traits with familial aggregation. Linkage analysis was largely supplanted by the wide adoption of genome-wide association studies (GWASs). However, with the recent increased use of whole-genome sequencing (WGS), linkage analysis is again emerging as an important and powerful analysis method for the identification of genes involved in disease aetiology, often in conjunction with WGS filtering approaches. Here, we review the principles of linkage analysis and provide practical guidelines for carrying out linkage studies using WGS data