Loss of PTEN is associated with elevated EGFR and HER2 expression and worse prognosis in salivary gland cancer.

BACKGROUND: Activity of the tumour-suppressor gene PTEN is reduced in different types of cancer and implicates non-responsiveness to targeted therapy. This study evaluates the gene and protein status of PTEN in salivary gland carcinomas. METHODS: A total of 287 carcinomas of the major and minor salivary glands were investigated for phosphatase and tensin homologue located on chromosome 10 (PTEN) deletion and loss of PTEN expression using fluorescence in situ hybridisation (FISH) and immunohistochemistry (IHC), respectively. Results were correlated to clinicopathological parameters, long-term survival, epidermal growth factor receptor (EGFR) and human epidermal growth factor receptor 2 (HER2) (IHC and FISH) status of the tumours. RESULTS: Hemizygous deletions of PTEN were found in 35 out of 232 (15.1%) carcinomas, while homozygous deletions were observed in 17 out of 232 (7.3%) tumours. Phosphatase and tensin homologue located on chromosome 10 deletion was common in certain histological subtypes and especially homozygous deletion was associated with high-grade malignancy, lymph node metastases and unfavourable long-term prognosis (P<0.001). Loss of PTEN expression was present in 59 out of 273 (21.6%) carcinomas and was significantly correlated to genomic PTEN deletion, high-grade malignancy (P<0.001), increased tumour size (P=0.036), lymph node metastases (P=0.007) and worse disease-specific survival (P=0.002). Genomic PTEN deletion, in particular homogenous deletion (P<0.001) predominantly occurred in tumours with increased gene copy number of EGFR (60.0%) and/or amplification of HER2 (63.6%). Loss of PTEN expression was frequently found in tumours overexpressing EGFR (28.6%) and/or HER2 (52.6%). CONCLUSION: PTEN function is reduced in different types of salivary gland cancer indicating unfavourable prognosis. Its association with EGFR and HER2 signalling might affect targeted therapy.

Software implementation of statistical methods for the analysis of structure and patterns in neuroanatomical objects.

Neuroanatomical research has greatly benefited from the availability of a large number of cell-specific and region-specific molecular markers. In fact, the analysis of spatial patterns of gene expression in individual cells or patterns within cell populations often provides an inroad into understanding the functional significance of distinct structures. However, it can be difficult to discern whether the arrangement of different morphologically or biochemically defined structures represents a defined pattern. To address this issue, we adapted a series of established statistical procedures for the analysis of uni- and bivariate point patterns in histological specimens. We implemented these statistical procedures in an easy-to-use computer program. The methods are scale independent and easy to expand for various applications. The utility of this approach is demonstrated with examples from tissue sections and cultured cells at the light and electron microscopical levels.