| Literature DB >> 18371194 |
Alastair Thompson1, Keith Brennan, Angela Cox, Julia Gee, Diana Harcourt, Adrian Harris, Michelle Harvie, Ingunn Holen, Anthony Howell, Robert Nicholson, Michael Steel, Charles Streuli.
Abstract
BACKGROUND: A gap analysis was conducted to determine which areas of breast cancer research, if targeted by researchers and funding bodies, could produce the greatest impact on patients.Entities:
Mesh:
Substances:
Year: 2008 PMID: 18371194 PMCID: PMC2397525 DOI: 10.1186/bcr1983
Source DB: PubMed Journal: Breast Cancer Res ISSN: 1465-5411 Impact factor: 6.466
Summary of the gap analysis for the genetics of breast cancer
| What do we know? | Multiple genes of different penetrance are involved in the predisposition to breast cancer. |
| Genome wide screens and somatic genetic approaches are identifying further genes involved in breast cancer. | |
| What are the gaps? | Detailed understanding of the actions of BRCA1 and BRCA2. |
| Knowledge of large-scale genetic rearrangements in tumour cells. | |
| The important variants, effects and interactions of low-penetrance genes. | |
| Further identification of point mutations and epigenetic changes. | |
| Problems | The quality, quantity and accessibility of materials. |
| Funding for large-scale experiments (such as sequencing) using expensive equipment. | |
| Bioinformatic analysis skills. | |
| Translational implications | Classifying breast tumours according to the signalling pathways that are disrupted to predict prognosis and response to therapy. |
| Determining the relevance of somatic events to prognosis and response to therapy. | |
| Generate new, targeted therapies based on target discovery. | |
| Better genetic risk estimation. | |
| Recommendations | Encourage development of research techniques to allow integrated analysis of sequence level, epigenetic and large-scale somatic changes. |
| Engage in national initiatives for activities such as high-throughput re-sequencing and UK controls. | |
| Encourage research involving intermediate phenotypes. |
Summary of the gap analysis for the initiation of breast cancer
| What do we know? | Animal models have given us great insight into the molecular pathways involved in breast development and dysregulation in cancer. |
| What are the gaps? | The relationship of signalling pathways to ductal and acinar breast architecture. |
| The need for widespread use of more appropriate | |
| The importance of stroma and other cell types, cell adhesion and the extracellular matrix. | |
| Understanding stem cells. | |
| Understanding mechanisms of epithelial apoptosis. | |
| Understanding how pregnancy and functional differentiation in the breast protect against breast cancer. | |
| Problems | The breast cell lines used and their culture conditions. |
| A wider variety of promoters with spatial, temporal and differentiation control of gene expression is needed. | |
| The need for mouse models of specific breast cancer types, for example, triple negative breast cancer. | |
| The implantation methods for single cells | |
| Translational implications | Understanding the complex interactions between cell types should provide new opportunities for intervention. |
| Identifying pre-invasive changes has implications for patient-tailored approaches. | |
| Recommendations | Develop three-dimensional cell culture models, containing multiple cell types, which reflect the tissue architecture of the normal and diseased breast. |
| Generate better animal models, in which gene expression can be manipulated in each cell type of the mammary gland and will not be altered by transdifferentiation or dedifferentiation. | |
| Gain a greater understanding of the genetic changes that occur within atypias and DCIS. |
Summary of the gap analysis for the progression of breast cancer
| What do we know? | Oestrogen receptor, receptor tyrosine kinase (RTK) and DNA repair pathways have been researched extensively. |
| Around 50% of DCIS will progress to invasive disease if untreated, with 12% to 20% recurring at 10 years despite appropriate treatment. | |
| What are the gaps? | Understanding the complexities of breast cancer intracellular signal transduction pathways, paracrine pathways, invasion, angiogenesis and metastasis including relevance of these mechanisms to clinical progression. |
| Whether there are inherently migratory stem cells or is metastatic capacity acquired. | |
| Understanding time-dependent progression events, notably dormancy and reactivation of micrometastasis, at particular secondary sites. | |
| Understanding the emerging relationship between therapeutic resistance and metastasis. | |
| Causative factors underlying recurrence of DCIS or progression to invasive disease | |
| Understanding the interplay between stroma, myoepithelial and epithelial components during early progression and interplay between tumour cells, stroma and the immune system in metastasis. | |
| The need for improved preclinical models of the influences of the microenvironment, site-specific metastasis and dormancy. | |
| Problems | Appropriate clinical samples to evaluate biomarkers and cellular endpoints. |
| Appropriate preclinical models and improved research reagents. | |
| Increasingly complex and multidisciplinary research infrastructure. | |
| Translational implications | Identifying patients at increased risk of dissemination. |
| Effectively predict therapeutic response with growth inhibitors. | |
| Improve selection of patients with DCIS for adjuvant radiotherapy or endocrine therapies. | |
| Identify cellular targets for developing new agents to target breast cancer progression effectively and selectively. | |
| Recommendations | Improve preclinical models, research reagents and technologies (including imaging). |
| Enhance access to appropriate clinical material, notably matched samples during progression and sequential samples obtained during treatments including new agents. | |
| Consider the genetic signature/specific genetic lesions when exploring progression biology and designing clinical trials. |
Summary of the gap analysis for the therapies and targets in breast cancer
| What do we know? | The selective use of combinations of surgery, radiotherapy, chemotherapy, and biological therapies has improved patient survival in recent years. |
| Not all therapies used are effective on all patients. | |
| What are the gaps? | There is an incomplete understanding of the biology of breast cancer including the effects of compensatory signalling pathways responsible for drug resistance. |
| We cannot determine who goes on to develop metastatic disease or drug-resistant cancers. | |
| Individualisation of therapies could be improved. | |
| The optimal duration of therapy is unclear for many drugs. | |
| Problems | There are insufficient model systems for the complexity and diversity of breast cancer. |
| The need to understand not only the cancer, but the tumour microenvironment and patient characteristics (including drug metabolism and immune mechanisms). | |
| Availability of clinical material is scarce, particularly from metastatic disease tissues. | |
| The neoadjuvant model could be used more effectively. | |
| Translational implications | Patients could be selected for appropriate therapy more effectively. |
| Enhanced understanding of the sequencing, combinations and duration of treatments. | |
| Recommendations | Build resources through high-quality, uniform, multicentre collection of clinical material from breast cancer patients before and during treatment (including neoadjuvant studies), including samples of primary tumours as well as metastatic deposits. |
| Develop methods for easy, reproducible monitoring of response to and development of resistance to therapy, as well as early disease progression. | |
| Increase research efforts into the role of the tumour microenvironment and the immune system in the development and treatment of breast cancer. |
Summary of the gap analysis for disease markers in breast cancer
| What do we know? | Patient groups can be successfully stratified in clinical trials using biomarkers. |
| What are the gaps? | Optimum protocols for pathological assessment of DCIS and sentinel lymph nodes. |
| Combining clinical, radiological, pathological and genomic data in trial populations. | |
| No robust validated markers have yet been developed for predicting response to chemotherapy or radiotherapy. | |
| There is no consensus for markers indicative of resistance to therapy. | |
| There is a need for improved prognostic indices based on disease markers. | |
| Problems | New assays must be robust and reproducible. |
| There is a need for standardisation of tissue handling. | |
| The impact of legislation, industrial involvement and academic pressures. | |
| Networks of collaboration employing systems biology are required. | |
| Translational implications | Accurate recognition of the diversity of breast cancer. |
| Identification of patients most likely to benefit. | |
| Identification of patients least likely to benefit from therapy and hence able to avoid toxicity. | |
| Recommendations | Design innovative trials and translational studies to develop and evaluate predictive and prognostic markers. |
| Develop close multidisciplinary collaboration with high-quality histopathology and rigorous scientific assessments to validate new markers important for patient outcome. | |
| Identify robust markers of resistance or sensitivity to therapy that can be applied across the spectrum of breast disease from screen-detected to metastatic breast cancer. |
Summary of the gap analysis for the prevention of breast cancer
| What do we know? | Endocrine chemoprevention for oestrogen-responsive tumours works. |
| Key risk factors include mammographic density, post-menopausal weight gain, high-calorie, high-fat diets and lack of exercise. | |
| Breast screening is effective. MRI screening is more sensitive than mammography for high-risk women | |
| Epidemiological data suggest weight control, low-fat diet and exercise after diagnosis improves outcome of early breast cancer patients. | |
| What are the gaps? | The long-term effects of chemoprevention of ER positive cancers are unknown. |
| Prevention of ER-negative cancers remains a challenge. | |
| There is a need to understand the target cell for breast cancer prevention. | |
| Need to improve current risk prediction models by including modifiable risk factors. | |
| The health beliefs of high-risk and population risk women require exploration. | |
| The effects of breast screening out with currently targeted groups is not known. | |
| To define deliverable diet and exercise interventions for the primary and secondary prevention of breast cancer. | |
| To elucidate the mechanism for breast cancer prevention with energy restriction. | |
| Problems | Accrual and retention of women in prevention trials. |
| Better models to research new chemoprevention agents. | |
| Breast screening lags behind advances in imaging technology. | |
| Poor uptake to diet and exercise trials after diagnosis. | |
| Translational implications | Better identification of high-risk women would allow chemoprevention to be targeted more effectively. |
| Defining optimum screening methods will ensure more effective use of limited NHS resources. | |
| The development of energy-restriction mimetics for breast cancer prevention. | |
| Optimal diet and exercise interventions could improve quality of life and outcome for women with breast cancer. | |
| Recommendations | Improve breast cancer risk prediction models. |
| Encourage transdisciplinary input to prevention trials (for example, geneticists, epidemiologists, nutritionists, psychologists and clinicians) to study the psychosocial, compliance and genetic aspects of prevention. | |
| Establish the potential benefits of diet and exercise post-diagnosis on outcome and quality of life for breast cancer patients. |
Summary of the gap analysis for the psychosocial aspects of breast cancer
| What do we know? | There are psychosocial effects of genetic testing, prophylactic mastectomy and breast screening. |
| Descriptive studies of the experiences of breast cancer patients using quantitative and qualitative methods show women still experience psychosocial distress despite improvements in treatment and prognosis. | |
| Psychosocial interventions have been shown to benefit women, including those identified as experiencing high levels of distress. | |
| What are the gaps? | Evaluation of decision aids for risk management and the choice of preventative surgery amongst high-risk women. |
| Ways of effectively communicating information and aiding patient treatment decision-making. | |
| Defining patient experiences in early, chronic and end stage breast cancer. | |
| Limited research into co-morbidities amongst breast cancer patients. | |
| Experiences of ethnic minority populations and older women. | |
| The need to develop and evaluate appropriate psychosocial interventions for high-risk women and those diagnosed as having breast cancer. | |
| Use of psychological theories in behaviour change that could enhance compliance to lifestyle and chemoprevention trials. | |
| Problems | The need for the long-term follow-up in psychosocial research. |
| Barriers to the uptake of research findings. | |
| Translational implications | Direct improvement in the experience of patients, their families and those at increased risk. |
| Recommendations | Develop and rigorously evaluate appropriate psychosocial interventions. |
| Encourage cross-speciality collaboration to incorporate psychosocial issues and psychological theory (for example, psychological theories in relation to behaviour change are relevant to those researching prevention with diet and exercise or chemoprevention). | |
| Ensure research gives greater attention to all stages of breast cancer and that the needs of older women and those from a range of ethnic groups are included. |
Gap analysis recommendations and future directions
| Generic needs | Improved preclinical models. |
| Access to appropriate and annotated clinical material. | |
| Cross-disciplinary working. | |
| 1. Genetics of breast cancer | Encourage development of research techniques to allow integrated analysis of sequence-level, epigenetic and large-scale somatic changes. |
| Engage in national initiatives for activities such as high-throughput re-sequencing and UK controls. | |
| Encourage research involving intermediate phenotypes. | |
| 2. Initiation of breast cancer | Develop three-dimensional cell culture models, containing multiple cell types, which reflect the tissue architecture of the normal and diseased breast. |
| Generate better animal models, particularly for ER-positive tumours, in which gene expression can be manipulated in all cell types of the mammary gland and will not be altered by transdifferentiation or dedifferentiation. | |
| Gain a greater understanding of the genetic changes that occur within atypias and DCIS. | |
| 3. Progression of breast cancer | Improve preclinical models, research reagents and technologies (including imaging). |
| Enhance access to appropriate clinical material, including sequential samples obtained during treatments extending to new agents. | |
| Consider genetic signature/specific genetic lesions when exploring progression biology and designing clinical trials. | |
| 4. Therapies and targets in breast cancer | Build resources through the high-quality, uniform, multicentre collection of clinical material from breast cancer patients before and during treatment (including neoadjuvant studies), including samples of primary tumours as well as metastatic deposits. |
| Develop methods for easy, reproducible monitoring of response to and development of resistance to therapy, as well as early disease progression. | |
| Increase research efforts into the role of the tumour microenvironment and the immune system in the development and treatment of breast cancer. | |
| 5. Disease markers in breast cancer | Design innovative trials and translational studies to develop and evaluate predictive and prognostic markers. |
| Develop close multidisciplinary collaboration with high-quality histopathology and rigorous scientific assessments to validate new markers important for patient outcome. | |
| Identify robust markers of resistance or sensitivity to therapy that can be applied across the spectrum of breast disease from screen-detected to metastatic breast cancer. | |
| 6. Prevention of breast cancer | Improve breast cancer risk prediction models. |
| Encourage transdisciplinary input to prevention trials (for example, geneticists, epidemiologists, nutritionists, psychologists and clinicians) to study the psychosocial, compliance and genetic aspects of prevention. | |
| Establish the potential benefits of diet and exercise post-diagnosis on outcome and quality of life for breast cancer patients. | |
| 7. Psychosocial aspects of breast cancer | Develop and rigorously evaluate appropriate psychosocial interventions. |
| Encourage cross-speciality collaboration to incorporate psychosocial issues and psychological theory (for example, psychological theories in relation to behaviour change are relevant to those researching preventative lifestyles including diet and exercise). | |
| Ensure research gives greater attention to all stages of breast cancer and that the needs of older women and those from a range of ethnic groups are included. |