Predictive gene lists for breast cancer prognosis: a topographic visualisation study

Background: The controversy surrounding the non-uniqueness of predictive gene lists (PGL) of small selected subsets of genes from very large potential candidates as available in DNA microarray experiments is now widely acknowledged 1. Many of these studies have focused on constructing discriminative semi-parametric models and as such are also subject to the issue of random correlations of sparse model selection in high dimensional spaces. In this work we outline a different approach based around an unsupervised patient-specific nonlinear topographic projection in predictive gene lists. Methods: We construct nonlinear topographic projection maps based on inter-patient gene-list relative dissimilarities. The Neuroscale, the Stochastic Neighbor Embedding(SNE) and the Locally Linear Embedding(LLE) techniques have been used to construct two-dimensional projective visualisation plots of 70 dimensional PGLs per patient, classifiers are also constructed to identify the prognosis indicator of each patient using the resulting projections from those visualisation techniques and investigate whether a-posteriori two prognosis groups are separable on the evidence of the gene lists. A literature-proposed predictive gene list for breast cancer is benchmarked against a separate gene list using the above methods. Generalisation ability is investigated by using the mapping capability of Neuroscale to visualise the follow-up study, but based on the projections derived from the original dataset. Results: The results indicate that small subsets of patient-specific PGLs have insufficient prognostic dissimilarity to permit a distinction between two prognosis patients. Uncertainty and diversity across multiple gene expressions prevents unambiguous or even confident patient grouping. Comparative projections across different PGLs provide similar results. Conclusion: The random correlation effect to an arbitrary outcome induced by small subset selection from very high dimensional interrelated gene expression profiles leads to an outcome with associated uncertainty. This continuum and uncertainty precludes any attempts at constructing discriminative classifiers. However a patient's gene expression profile could possibly be used in treatment planning, based on knowledge of other patients' responses. We conclude that many of the patients involved in such medical studies are intrinsically unclassifiable on the basis of provided PGL evidence. This additional category of 'unclassifiable' should be accommodated within medical decision support systems if serious errors and unnecessary adjuvant therapy are to be avoided.

Breast clinic and life style study BLLISS

Background: Independent, strong and unequivocal evidence suggests that life style factors such as obesity and lack of physical activity along with certain reproductive choices can increase the risk of breast cancer. There are no studies measuring the effectiveness of guidelines from the Department of Health regarding life style choices made by women presenting to breast clinics. The aim of this audit was to study the prevalence of obesity, physical activity and reproductive factors in women referred to breast clinic. Patients and methods: All patients attending the Breast clinic as new referrals were invited to complete a life style questionnaire. The data was analysed for prevalence of various risk factors for breast cancer. Three hundred and 73 patients completed the questionnaire. Results: Final analyses of 373 patients demonstrated that 42% of women performed no exercise and only 24% of patients met Department of Health guideline of 30 minutes of exercise for 5 days a week. Overall 50% of patients were either obese or overweight and 22% of patients had BMI of > 30 kg/m. The median age of menarche was 13 and 18% of women started their period below the age 12. Twenty one percent of women were nulliparous and 14% had their first live birth after the age of 30. Fourteen percent of patients were on the hormone replacement therapy of which 57% have used hormones for more than 5 years. Twenty two percent of women smoked and 9% of women consumed alcohol 5 days a week of which 13% had more than 4 glasses of alcohol in a day. Conclusion: There is preponderance of high risk life style choices in women attending breast clinic. If these life style options are not modified, there could potentially be a significant rise in the number of breast cancer in West Midlands.

Chronic preoperative pain and psychological robustness predict acute postoperative pain outcomes after surgery for breast cancer

Background - Few epidemiological studies have prospectively investigated preoperative and surgical risk factors for acute postoperative pain after surgery for breast cancer. We investigated demographic, psychological, pain-related and surgical risk factors in women undergoing resectional surgery for breast cancer. Methods - Primary outcomes were pain severity, at rest (PAR) and movement-evoked pain (MEP), in the first postoperative week. Results - In 338 women undergoing surgery, those with chronic preoperative pain were three times more likely to report moderate to severe MEP after breast cancer surgery (OR 3.18, 95% CI 1.45–6.99). Increased psychological ‘robustness’, a composite variable representing positive affect and dispositional optimism, was associated with lower intensity acute postoperative PAR (OR 0.63, 95% CI 0.48–0.82) and MEP (OR 0.71, 95% CI 0.54–0.93). Sentinel lymph node biopsy (SLNB) and intraoperative nerve division were associated with reduced postoperative pain. No relationship was found between preoperative neuropathic pain and acute pain outcomes; altered sensations and numbness postoperatively were more common after axillary sample or clearance compared with SLNB. Conclusion - Chronic preoperative pain, axillary surgery and psychological robustness significantly predicted acute pain outcomes after surgery for breast cancer. Preoperative identification and targeted intervention of subgroups at risk could enhance the recovery trajectory in cancer survivors.