IntroductionBreast cancer remains a significant scientific, clinical and societal challenge. This gap analysis has reviewed and critically assessed enduring issues and new challenges emerging from recent research, and proposes strategies for translating solutions into practice.MethodsMore than 100 internationally recognised specialist breast cancer scientists, clinicians and healthcare professionals collaborated to address nine thematic areas: genetics, epigenetics and epidemiology; molecular pathology and cell biology; hormonal influences and endocrine therapy; imaging, detection and screening; current/novel therapies and biomarkers; drug resistance; metastasis, angiogenesis, circulating tumour cells, cancer ‘stem’ cells; risk and prevention; living with and managing breast cancer and its treatment. The groups developed summary papers through an iterative process which, following further appraisal from experts and patients, were melded into this summary account.ResultsThe 10 major gaps identified were: (1) understanding the functions and contextual interactions of genetic and epigenetic changes in normal breast development and during malignant transformation; (2) how to implement sustainable lifestyle changes (diet, exercise and weight) and chemopreventive strategies; (3) the need for tailored screening approaches including clinically actionable tests; (4) enhancing knowledge of molecular drivers behind breast cancer subtypes, progression and metastasis; (5) understanding the molecular mechanisms of tumour heterogeneity, dormancy, de novo or acquired resistance and how to target key nodes in these dynamic processes; (6) developing validated markers for chemosensitivity and radiosensitivity; (7) understanding the optimal duration, sequencing and rational combinations of treatment for improved personalised therapy; (8) validating multimodality imaging biomarkers for minimally invasive diagnosis and monitoring of responses in primary and metastatic disease; (9) developing interventions and support to improve the survivorship experience; (10) a continuing need for clinical material for translational research derived from normal breast, blood, primary, relapsed, metastatic and drug-resistant cancers with expert bioinformatics support to maximise its utility. The proposed infrastructural enablers include enhanced resources to support clinically relevant in vitro and in vivo tumour models; improved access to appropriate, fully annotated clinical samples; extended biomarker discovery, validation and standardisation; and facilitated cross-discipline working.ConclusionsWith resources to conduct further high-quality targeted research focusing on the gaps identified, increased knowledge translating into improved clinical care should be achievable within five years.

Immunohistochemistry is no longer a technique used only for research but is employed increasingly for diagnosis and for the assessment of therapeutic biomarkers. The latter, in particular, often require a semiquantitative evaluation of the extent of their presence. There are many factors that can affect this that relate to the method: fixation of tissue, duration and type of antigen retrieval, antibody specificity, antibody dilution and detection systems. Other complexities relate to assessment. Different scoring systems are used for either the same or different antigens. Cut-off levels for assessing whether a tissue is 'positive' or 'negative' can vary for the same antigen. Whilst there are quality assurance schemes for the methodology that have improved standards of staining, there are no similar schemes that relate to interpretation, although errors here can create as many problems. There have been improvements in automated analysis but availability is limited and it is still predominantly a research tool. In order for quantification of immunohistochemistry to be a reliable and reputable tool, there must be easy to use, reproducible, standardized protocols for assessment which are international. Improvements in automated analysis with wider applicability could lead to standardization.

Previously we analysed overlapping homozygous deletions in lung and breast tumours/tumour lines and de®ned a small region of 120 kb (part of LCTSGR1) at 3p21.3 that contained putative lung and breast cancer tumour suppressor gene(s) (TSG). Eight genes including RASSF1 were isolated from the minimal region. However, extensive mutation analysis in lung tumours and tumour lines revealed only rare inactivating mutations. Recently, de novo methylation at a CpG island associated with isoform A of RASSF1 (RASS-F1A) was reported in lung tumours and tumour lines. To investigate RASSF1A as a candidate TSG for various cancers, we investigated: (a) RASSF1A methylation status in a large series of primary tumour and tumour lines; (b) chromosome 3p allele loss in lung tumours and (c) RASSF1 mutation analysis in breast tumours. RASSF1A promoter region CpG island methylation was detected in 72% of SCLC, 34% of NSCLC, 9% of breast, 10% of ovarian and 0% of primary cervical tumours and in 72% SCLC, 36% NSCLC, 80% of breast and 40% of ovarian tumour lines. In view of the lower frequency of RASSF1 methylation in primary breast cancers we proceeded to RASSF1 mutation analysis in 40 breast cancers. No mutations were detected, but six single nucleotide polymorphisms were identi®ed. Twenty of 26 SCLC tumours with 3p21.3 allelic loss had RASSF1A methylation, while only six out of 22 NSCLC with 3p21.3 allele loss had RASSF1A methylation (P=0.0012), one out of ®ve ovarian and none out of six cervical tumours with 3p21.3 loss had RASSF1A methylation. These results suggest that (a) RASSF1A inactivation by two hits (methylation and loss) is a critical step in SCLC tumourigenesis and (b) RASSF1A inactivation is of lesser importance in NSCLC, breast, ovarian and cervical cancers in which other genes within LCTSGR1 are likely to be implicated. Oncogene (2001) 20, 1509 ± 1518.

The distribution of astrocytic gliosis in Alzheimer's disease (AD) and aging cerebrum, as marked by immunoperoxidase staining for glial fibrillary acidic protein (GFAP), was examined in whole-hemisphere coronal sections. Cortical gliosis in AD had an obvious laminar pattern. There were two heavy bands of staining, one in layers II-III and another in layer V. Normal aging cases sometimes displayed considerable cortical gliosis, but no specific patterns were apparent. Most AD cases, and some normal aging cases, displayed hypertrophy of immunoreactive astrocytes at grey matter-white matter interfaces, especially the cortico-medullary junction. Subcortical grey matter gliosis was common in both normal aging and AD, but there was no consistent pattern in either group. The deep cerebral white matter, which is stained evenly and heavily in young, healthy individuals, showed uneven staining in both normal elderly and AD brains. In both AD and aging, perivascular gliosis was prominent throughout the cerebrum and especially in the putamen. In conclusion, both AD and aging cerebri show extensive gliosis: AD cortical gliosis has a specific laminar pattern, but there does not appear to be an AD-specific pattern of subcortical gliosis.