Grade of recurrent in situ and invasive carcinoma following treatment of pure ductal carcinoma in situ of the breast

Grade of recurrent in situ and invasive carcinoma following treatment of pure ductal carcinoma in situ of the breast The grade of recurrent in situ and invasive carcinoma occurring after treatment of pure ductal carcinoma in situ (DCIS) has been compared with the grade of the original DCIS in 122 patients from four different centres (The Royal Marsden Hospitals, London and Sutton, 57 patients; Guy's Hospital, London, 19 patients; Nottingham City Hospital, 31 patients and The Royal Liverpool Hospital, 15 patients). The recurrent carcinoma was pure DCIS in 70 women (57%) and in 52 women (43%) invasive carcinoma was present, which was associated with an in situ element in 43. In all, 19 patients developed a second recurrence (pure DCIS in 11 and invasive with or without an in situ element in eight). The majority of invasive carcinomas followed high-grade DCIS. There was strong agreement between the grade of the original DCIS and that of the recurrent DCIS (k = 0.679), which was the same in 95 of 113 patients (84%). The grade of the original DCIS showed only fair agreement with the grade of recurrent invasive carcinoma (k = 0.241), although agreement was stronger with the pleomorphism score of the recurrent carcinoma (k = 0.396). There was moderate agreement, in recurrent invasive lesions, between the grade of the DCIS and that of the associated invasive element (k = 0.515). Other features that showed moderate or strong agreement between the original and recurrent DCIS were necrosis and periductal inflammation. The similarity between the histological findings of the original and subsequent DCIS is consistent with the concept that recurrent lesions represent regrowth of residual carcinoma. In addition, although agreement between the grade of the original DCIS and that of any subsequent invasive carcinoma was only fair, there is no suggestion that low-grade DCIS lesions progress to higher grade lesions or to the development of higher grade invasive carcinoma. This is in agreement with immunohistochemical and molecular data indicating that low- grade and high-grade mammary carcinomas are quite different lesions

Adenomyoepithelial tumours and myoepithelial carcinomas of the breast – a spectrum of monophasic and biphasic tumours dominated by immature myoepithelial cells

BACKGROUND: Adenomyoepithelial tumours and myoepithelial carcinomas of the breast are primarily defined by the presence of neoplastic cells with a myoepithelial immunophenotype. Current classification schemes are based on purely descriptive features and an assessment of individual prognosis is still problematic. METHODS: A series of 27 adenomyoepithelial tumours of the breast was analysed immunohistochemically with antibodies directed against various cytokeratins, p63, smooth muscle alpha-actin (SMA) and vimentin. Additionally, double immunofluorescence and comparative genomic hybridisation (CGH) was performed. RESULTS: Immunohistochemically, all the tumours showed a constant expression of high molecular weight cytokeratins (Ck) Ck5 and Ck14, p63, SMA and vimentin. With exception of one case diagnosed as myoepithelial carcinoma, all tested tumours expressed low molecular weight cytokeratin Ck18 in variable proportions of cells. Even in monophasic tumours lacking obvious glandular differentiation in conventional staining, a number of neoplastic cells still expressed those cytokeratins. Double immunofluorescence revealed tumour cells exclusively staining for Ck5/Ck14 in the presence of other cell populations that co-expressed high molecular weight Ck5/Ck14 as well as either low molecular weight Ck8/18 or SMA. Based on morphology, we assigned the series to three categories, benign, borderline and malignant. This classification was supported by a stepwise increase in cytogenetic alterations on CGH. CONCLUSION: Adenomyoepithelial tumours comprise a spectrum of neoplasms consisting of an admixture of glandular and myoepithelial differentiation patterns. As a key component SMA-positive cells co-expressing cytokeratins could be identified. Although categorisation of adenomyoepithelial tumours in benign, borderline and malignant was supported by results of CGH, any assessment of prognosis requires to be firmly based on morphological grounds. At present it is not yet clear, if and to what extent proposed Ck5-positive progenitor cells contribute to the immunohistochemical and morphological heterogeneity of these neoplasms of the breast

Transcriptomic landscape of breast cancers through mRNA sequencing

Breast cancer is a heterogeneous disease with a poorly defined genetic landscape, which poses a major challenge in diagnosis and treatment. By massively parallel mRNA sequencing, we obtained 1.2 billion reads from 17 individual human tissues belonging to TNBC, Non-TNBC, and HER2-positive breast cancers and defined their comprehensive digital transcriptome for the first time. Surprisingly, we identified a high number of novel and unannotated transcripts, revealing the global breast cancer transcriptomic adaptations. Comparative transcriptomic analyses elucidated differentially expressed transcripts between the three breast cancer groups, identifying several new modulators of breast cancer. Our study also identified common transcriptional regulatory elements, such as highly abundant primary transcripts, including osteonectin, RACK1, calnexin, calreticulin, FTL, and B2M, and “genomic hotspots” enriched in primary transcripts between the three groups. Thus, our study opens previously unexplored niches that could enable a better understanding of the disease and the development of potential intervention strategies

Classification of ductal carcinoma in situ by gene expression profiling

INTRODUCTION: Ductal carcinoma in situ (DCIS) is characterised by the intraductal proliferation of malignant epithelial cells. Several histological classification systems have been developed, but assessing the histological type/grade of DCIS lesions is still challenging, making treatment decisions based on these features difficult. To obtain insight in the molecular basis of the development of different types of DCIS and its progression to invasive breast cancer, we have studied differences in gene expression between different types of DCIS and between DCIS and invasive breast carcinomas. METHODS: Gene expression profiling using microarray analysis has been performed on 40 in situ and 40 invasive breast cancer cases. RESULTS: DCIS cases were classified as well- (n = 6), intermediately (n = 18), and poorly (n = 14) differentiated type. Of the 40 invasive breast cancer samples, five samples were grade I, 11 samples were grade II, and 24 samples were grade III. Using two-dimensional hierarchical clustering, the basal-like type, ERB-B2 type, and the luminal-type tumours originally described for invasive breast cancer could also be identified in DCIS. CONCLUSION: Using supervised classification, we identified a gene expression classifier of 35 genes, which differed between DCIS and invasive breast cancer; a classifier of 43 genes could be identified separating between well- and poorly differentiated DCIS samples

Syndromics: A Bioinformatics Approach for Neurotrauma Research

Substantial scientific progress has been made in the past 50 years in delineating many of the biological mechanisms involved in the primary and secondary injuries following trauma to the spinal cord and brain. These advances have highlighted numerous potential therapeutic approaches that may help restore function after injury. Despite these advances, bench-to-bedside translation has remained elusive. Translational testing of novel therapies requires standardized measures of function for comparison across different laboratories, paradigms, and species. Although numerous functional assessments have been developed in animal models, it remains unclear how to best integrate this information to describe the complete translational “syndrome” produced by neurotrauma. The present paper describes a multivariate statistical framework for integrating diverse neurotrauma data and reviews the few papers to date that have taken an information-intensive approach for basic neurotrauma research. We argue that these papers can be described as the seminal works of a new field that we call “syndromics”, which aim to apply informatics tools to disease models to characterize the full set of mechanistic inter-relationships from multi-scale data. In the future, centralized databases of raw neurotrauma data will enable better syndromic approaches and aid future translational research, leading to more efficient testing regimens and more clinically relevant findings