Pamela J. Goodwin

Insulin and related factors in premenopausal breast cancer risk.

Background: Insulin and insulin-like growth factor I (IGF-I) are important mitogens in vitro and in vivo. It has been hypothesized that these factors may play an important role in the development of breast cancer. Methods: A case-control study comparing plasma insulin levels in 99 premenopausal women with newly diagnosed node-negative invasive carcinoma of the breast and 99 age-matched controls with incident biopsied non-proliferative breast disease (NP) was conducted. Women with known diabetes were excluded. Results: For the entire study group, mean age was 42.6 ± 5.1 years and mean weight was 62.9 ± 10.3 kg. After adjustment for age and weight, elevated insulin levels were significantly associated with breast cancer, Odds Ratio (OR) for women in the highest insulin quintile versus the lowest quintile=2.83 (95% Confidence Interval [CI] 1.22–6.58). There were no statistically significant differences between cases and controls for IGF-I and IGFBP-1 levels. However, after adjustment for age, the association between plasma levels of insulin-like growth factor binding protein 3 (IGFBP-3) and breast cancer approached statistical significance; OR for highest quintile versus lowest quintile of IGFBP-3 being 2.05 (95% CI, 0.93–4.53). All results were independent of diet and other known risk factors for breast cancer. Conclusion: Circulating insulin levels and possibly IGFBP-3 levels are elevated in women with premenopausal breast cancer. This association may reflect an underlying syndrome of insulin resistance that is independent of obesity.

Body size and breast cancer prognosis: A critical review of the evidence

There is currently controversy about the effect of body size on the prognosis of patients with breast cancer. In order to clarify the prognostic importance of body size, and to determine whether the effect varies across subgroups of patients, a critical appraisal of the published literature was undertaken. Thirteen cohort studies and one case-control study were identified that examined the prognostic effect of body size. Methodologic standards were developed that reflected those features of study design considered most important in studies of prognosis in breast cancer, and were independently applied to each report by each of the authors.When the effects of methodologic differences among the studies were controlled, a modest prognostic effect of body size was identified. This effect appeared to be greatest in postmenopausal women, in those with little or no involvement of axillary nodes, and to be independent of other prognostic factors.Additional investigation is recommended to determine the prognostic effects of body size in postmenopausal women with axillary node negative breast cancer and in women receiving systemic adjuvant therapy, and to determine the pathophysiological basis for these effects. Intervention studies to determine the effects of altering body size may also be indicated.

Evidence for biological effects of metformin in operable breast cancer: biomarker analysis in a pre-operative window of opportunity randomized trial

Metformin has therapeutic potential against breast cancer, but the mechanisms of action in vivo remain uncertain. This study examined biomarker effects of metformin in primary breast cancer in a preoperative window of opportunity trial. Non-diabetic women with operable invasive breast cancer were randomized to receive open label pre-operative metformin (500xa0mg daily for 1xa0week then 1xa0g twice daily for a further week) or as controls, not receiving metformin. Patients in both arms had a core biopsy pre-randomisation and again at the time of surgery. Immunohistochemistry for phospho-AMPK (pAMPK), phospho-Akt (pAkt), insulin receptor, cleaved caspase-3, and Ki67 was performed on formalin-fixed paraffin-embedded cores, scored blinded to treatment and analysed by paired t test. In metformin-treated patients, significant up-regulation of pAMPK (paired t test, pxa0=xa00.04) and down-regulation of pAkt (paired t test, pxa0=xa00.043) were demonstrated compared to the control group. Insulin receptor and serum insulin remained similar following metformin treatment compared with a rise in insulin receptor and insulin in controls. Significant falls in Ki67 and cleaved caspase-3 (paired t test, pxa0=xa00.044) were seen in the metformin-treated patients but not in the control group. Changes were independent of body mass index. These biomarker data suggest mechanisms for metformin action in vivo in breast cancer patients via up-regulation of tumor pAMPK, down-regulation of pAkt, and suppression of insulin responses reflecting cytostatic rather than cytotoxic mechanisms.

Utility of metformin in breast cancer treatment, is neoangiogenesis a risk factor?

To the Editor There is growing evidence that metformin (a biguanide derivative used to treat type 2 diabetes) may impede the growth of human tumors, including breast cancers. A recent report in this journal raises a potentially important issue regarding the utility and safety of metformin as a therapy for breast cancer. While metformin was found to be effective in suppressing the growth of several breast cancer cell lines in vitro, in a xenograft model using certain breast cancer cells metformin appeared to increase the production of VEGF, a neo-angiogenic signal, leading to augmented angiogenesis [1]. The potential utility of metformin as an anti-breast cancer agent is founded on two biologic mechanisms. First, metformin acts systemically to indirectly lower insulin levels, as demonstrated by a 22% reduction with standard clinical doses in non-diabetic breast cancer patients (a noncell-autonomous effect) [2]. Clinical studies have shown that higher than average insulin levels have been associated with a 2–3-fold increased risk of recurrence and death [3–5]. It is biologically plausible that physiological levels of insulin may influence the proliferation of breast cancer cells because of the almost uniform expression of the insulin receptor on sporadic breast cancers [6]. Second, metformin can directly activate AMP-dependent protein kinase (AMPK) and in so doing, suppress global protein synthesis and proliferation in target cells (a cell-autonomous effect) [7–9]. Epidemiological studies which demonstrated lower cancer mortality in patients treated with metformin in comparison to other anti-diabetic drugs [10] and a dose-dependent decrease in cancer incidence in metformin-treated diabetics [11] lend further support to the importance of conducting prospective clinical trials examining the effect of metformin in breast and other cancers. For these reasons, the laboratory data presented by Phoenix et al. need to be carefully considered to understand their relevance to the potential use of metformin in the clinical management of breast cancer. Our first concern relates to the doses used in this report which led to concentrations that far exceed the standard therapeutic plasma levels of metformin in humans (0.465–2.5 mg/l). For cells in culture, metformin was used at levels of 1–20 mM (165–3,300 mg/l, a minimum of 300-fold excess over the recommended therapeutic levels), whereas in mice the estimated dose was 750 mg/kg/day (a 45-fold excess over recommended therapeutic doses based on a human daily dose of 1,000–2,550 mg and an average patient body weight of 60 kg). Extremely high plasma metformin levels (4–8 mg/l, still at least 20-fold lower than doses used by Phoenix et al.) are rarely seen in the clinical setting and only found in very ill patients with renal dysfunction and lactic acidosis who experience metformin accumulation [12]. Thus, the results obtained from the model system implemented in this study cannot be considered an approximation of the clinical use of metformin; nor can the V. Stambolic (&) Division of Signaling Biology, Ontario Cancer Institute, University Health Network, Toronto, Canada e-mail: vuks@uhnres.utoronto.ca

Metformin Pharmacokinetics in Mouse Tumors: Implications for Human Therapy

Metformin exhibits anticancer properties and is currently being explored as a therapeutic option for a variety of cancer types. Epidemiological studies demonstrate associations between metformin use in patients with type 2 diabetes and decreased cancer incidence and cancer-related mortality (Evans et al., 2005). Metformin also exhibits inhibitory effects on cancer cells in vitro and in mouse models (Anisimov et al., 2005; Zakikhani et al., 2006). Its mechanism of action is believed to involve both indirect (insulin-dependent) and direct (insulin-independent) effects.

Association of Obesity-Related Metabolic Disruptions With Cancer Risk and Outcome.

Over the past 40 years, the prevalence of obesity has increased epidemically worldwide, which raises significant concerns regarding public health and the associated economic burden. Obesity is a major risk factor for several conditions including cardiovascular disease and type 2 diabetes, and recent evidence suggests that obesity negatively affects cancer risk and outcome. The relationship between obesity and cancer is complex and involves multiple factors both at the systemic and cellular level. Indeed, disruptions in insulin metabolism, adipokines, inflammation, and sex hormones all contribute to the adverse effects of obesity in cancer development and progression. The focus of this review will be the impact of these systemic obesity-related factors on cancer biology, incidence, and outcome. Potential therapeutic interventions and current clinical trials targeting obesity and its associated factors will also be discussed.

The Importance of a Family History of Breast Cancer in Predicting the Presence of a BRCA Mutation

To the Editor:Hartge et al. (1999xThe prevalence of common BRCA1 and BRCA2 mutations among Ashkenazi Jews. Hartge, P, Struewing, JP, Wacholder, S, Brody, LC, and Tucker, MA. Am J Hum Genet. 1999; 64: 963–970Abstract | Full Text | Full Text PDF | PubMed | Scopus (122)See all References1999) describe the prevalence of the three founder Ashkenazi Jewish (AJ) mutations in BRCA1 (MIM 113705) and BRCA2 (MIM 600185) in 5,290 AJ volunteers from the Washington, DC, area. They report an overall mutation frequency of 2.3%, ranging from 1.2%, in those with no personal or first-degree-relative history of breast or ovarian cancer, to 50%, in women diagnosed with breast or ovarian cancer at age <40 years who had at least one first-degree relative with breast cancer diagnosed at age <50 years. The authors demonstrate, as we and others (Karp et al. 1997xInfluence of BRCA1 mutations on nuclear grade and estrogen receptor status on breast carcinoma in Ashkenazi Jewish women. Karp, SE, Tonin, PN, Begin, LR, Martinez, JJ, Zhang, JC, Pollak, MN, and Foulkes, WD. Cancer. 1997; 80: 435–441Crossref | PubMed | Scopus (142)See all References1997; Shattuck-Eidens et al. 1997xBRCA1 sequence analysis in women at high risk for susceptibility mutations: risk factor analysis and implications for genetic testing. Shattuck-Eidens, D, Oliphant, A, McClure, M, McBride, C, Gupte, J, Rubano, T, Pruss, D et al. JAMA. 1997; 278: 1242–1250Crossref | PubMedSee all References1997; Fodor et al. 1998xFrequency and carrier risk associated with common BRCA1 and BRCA2 mutations in Ashkenazi Jewish breast cancer patients. Fodor, FH, Weston, A, Bleiweiss, IJ, McCurdy, LD, Walsh, MM, Tartter, PI, Brower, ST et al. Am J Hum Genet. 1998; 63: 45–51Abstract | Full Text | Full Text PDF | PubMed | Scopus (154)See all References1998) have done, that, for the 297 women in their study with breast or ovarian cancer, the probability of carrying a BRCA1 or BRCA2 (BRCA) mutation decreases as age at diagnosis increases. Hartge et al. (1999xThe prevalence of common BRCA1 and BRCA2 mutations among Ashkenazi Jews. Hartge, P, Struewing, JP, Wacholder, S, Brody, LC, and Tucker, MA. Am J Hum Genet. 1999; 64: 963–970Abstract | Full Text | Full Text PDF | PubMed | Scopus (122)See all References1999, p. 965) state that, given age-at-onset information, “family history discriminated relatively little if the participant herself developed breast cancer, whereas, among other participants, family history best discriminated carriers from non-carriers.” The age of the proband is clearly a powerful predictor of carrier probability, but our experience is that family history is an important determinant of the probability of a mutation, in both unaffected and affected women. Therefore, we reanalyzed Hartge et al.s data, estimating relative risks of carrying a BRCA mutation for each age-at-diagnosis group (stratified by decade), in association with a first-degree-relative family history of breast cancer at any age (“positive family history”) and in association with a first-degree-relative family history of at least one case of breast cancer diagnosed at age <50 years (“positive early-onset family history”). We analyzed affected and unaffected women separately. In affected women, the Mantel-Haenszel (M-H) odds ratio (OR), stratified by age at onset, for the association between a positive family history and the presence of a founder BRCA mutation, compared with a negative family history, was 2.6 (95% confidence interval [CI] 1.2–6.0, P=.022; table 1table 1, first “OR” column). For unaffected women, the M-H OR for the presence of a mutation in women with a positive family history was 3.1 (95% CI 1.9–5.1, P<.001; table 1table 1, second “OR” column). For affected women, the M-H OR for the presence of a BRCA mutation in association with a positive early-onset family history was 4.4 (95% CI 1.7–11.4, P=.003; table 2table 2, first column). This OR is greater than that observed in unaffected women with a positive early-onset family history (M-H OR 3.6, P<.001; table 2table 2, second “OR” column). Thus, a family history of breast cancer is as predictive of the presence of a BRCA mutation in affected women as it is in unaffected women. The M-H OR for the unaffected and affected subgroups is similar and has overlapping CIs. The significance levels do differ, but this reflects the much larger size of the subgroup of unaffected women (n=4,993; 94.4%) compared with those with breast or ovarian cancer (n=297; 5.6%). In addition, a comparison of the strata-specific ORs in unaffected and affected women does not reveal a consistent pattern: none of the within-strata ORs differ statistically—the smallest P value is .38 (table 1table 1, “OR” column 1 vs. column 2; table 2table 2, “OR” column 1 vs. column 2).Table 1M-H OR for the Presence of a BRCA Mutation in Association with a Positive Family History of Breast Cancer, Stratified by Age or Age at OnsetHartge et al. (1999)Warner et al. (1999): Affected WomenAffected WomenUnaffected WomenNo. ofNo. ofNo. ofNoncarriersCarriersbbOR [95%CI]ccNoncarriersCarriersbbOR [95%CI]ccNoncarriersCarriersbbOR [95%CI]ccAgeaa <40 years FH× −2161.0557 91.014 71.0 FH× + 432.6 [.5–15.0]114105.4 [2.4–12.5] 3 64.0 [.8–20.6] 40–49 years FH× −7161.0874141.080131.0 FH× +2752.2 [.6–7.6]215 92.6 [1.2–5.9]31102.0 [.8–5.0] 50–59 years FH× −5721.0628 81.081 41.0 FH× +1946.0 [1.2–30.2]169 62.8 [.9–7.8]21 54.8 [1.3–17.8] ≥60 years FH× −4611.0611 41.095 21.0 FH× +250.6 [.0–15.5]189 21.6 [.3–8.8]39 11.2 [.1–13.9]M-H2.6 [1.2–6.0]3.1 [1.9–5.1]2.6 [1.4–5.0]PPPHomogeneity.50.53.63Unity.022<.001.004aFH×= family history of breast cancer in any first-degree relative. The minus sign (−) indicates negative; the plus sign (+) indicates positive.bOf a founder AJ BRCA1 or BRCA2 mutation.cThe logit estimate of the odds ratio was used when there was a zero cell.Table 2M-H OR for the Presence of a BRCA Mutation in Association with a Positive Family History of Early-Onset Breast Cancer, Stratified by Age or Age at OnsetHartge et al. (1999)Warner et al. (1999): Affected WomenAffected WomenUnaffected WomenNo. ofNo. ofNo. ofNoncarriersCarriersbbOR [95%CI]ccNoncarriersCarriersbbOR [95%CI]ccNoncarriersCarriersbbOR [95%CI]ccAgeaa <40 years FH×50 −2371.0 614141.0 17111.0 FH×50 + 223.3 [.4–26.4] 57 53.9 [1.4–10.3] 0 27.6 [.3–173] 40–49 years FH×50 −9281.01014171.0 97171.0 FH×50 + 635.8 [1.4–23.9] 75 64.8 [2.0–11.4] 14 62.5 [.8–7.1] 50–59 years FH×50 −7041.0 743121.0 90 41.0 FH×50 + 625.8 [1.0–32.6] 54 22.3 [.5–10.1] 12 59.4 [2.7–33.1] ≥60 years FH×50 −6111.0 73451.0122 21.0 FH×50 +1002.0 [.1–51.2] 6612.2 [.3–18.3] 12 15.1 [.548.0]M-H4.4 [1.7–11.4]3.6 [2.0–6.4]4.4 [2.1–9.2]PPPHomogeneity.81.83.40Unity.003<.001<.001aFH×50 = family history of breast cancer at age <50 years in any first-degree relative. The minus sign (−) indicates negative; the plus sign (+) indicates positive.bOf a founder AJ BRCA1 or BRCA2 mutation.cThe logit estimate of the odds ratio was used when there was a zero cell.To assess whether our reinterpretation of the Washington, DC, data set is valid, we performed the same analysis in 412 prevalent cases of breast cancer diagnosed in AJ women, ascertained between November 1, 1996, and May 31, 1998, in Toronto and Montreal (Warner et al. 1999xPrevalence and penetrance of BRCA1 and BRCA2 mutations in unselected Ashkenazi Jewish women with breast cancer. Warner, E, Foulkes, W, Goodwin, P, Meschino, W, Blondal, J, Patterson, C, Ozcelik, H et al. J Natl Cancer Inst. 1999; 91: 1241–1247Crossref | PubMedSee all References1999). To compare exactly with the Washington, DC, study, we included only first-degree relatives with breast cancer in the analyses here. The definition of early-onset breast cancer was age at diagnosis of <50 years. The results are shown in tables 11 and 22, “OR” column 3. Notably, the M-H ORs seen in the Canadian study are identical to that observed in affected women in the Washington, DC, study: M-H OR 2.6 for the presence of a BRCA mutation in association with any first-degree-relative history of breast cancer and 4.4 for a positive early-onset family history. Thus, the findings from the Canadian study support our interpretation of the data published by Hartge et al. (1999xThe prevalence of common BRCA1 and BRCA2 mutations among Ashkenazi Jews. Hartge, P, Struewing, JP, Wacholder, S, Brody, LC, and Tucker, MA. Am J Hum Genet. 1999; 64: 963–970Abstract | Full Text | Full Text PDF | PubMed | Scopus (122)See all References1999) and lead us to question those authors conclusion that the knowledge gained from knowing the family history of an affected person is “relatively small.” The weight of evidence from clinical experience, from previously published work, and from their own study supports the conclusion that family history and age at diagnosis of breast cancer are both important factors in indicating the likely presence of a mutation in BRCA1 or BRCA2.

Economic factors in cancer palliation—methodologic considerations

The role of economic factors in the care of cancer patients has been receiving increasing attention in recent years (l-3) as it has become increasingly apparent in most health care systems that health care resources are not unlimited. There is greater demand for health care personnel, time, facilities, equipment and money than there is supply. Because of this imbalance decisions must be made regarding allocation of available resources and it is important that health care professionals understand how economic factors are evaluated, the role they play in health care decision making and the limitations of their contributions to the health care decisionmaking process. Decisions about resource allocation may either be made explicitly, after consideration of all relevant factors, including cost, or they may be made on an ad hoc basis. When the latter approach is taken, those most able to pay are more likely to receive care in user-pay systems whereas a first-come, first-served approach is likely to be taken in publically funded systems. In either situation, scarce health care resources will probably be allocated to marginally useful procedures for some patients at the same time that highly effective (and affordable) treatment is denied to others, It is only when resource allocation decisions are made explicitly, and economic factors considered directly, that the most equitable distribution of resources possible can be achieved. Even when there is agreement that economic factors should be incorporated into health care decisions, these factors should never be taken in isolation. Other factors that should be considered include treatment efficacy/effectiveness, treatment toxicity and effect on quality of life, availability of resources for treatment administration, acceptability of treatment (and non-treatment) to patients, health care professionals and society, societal and political preferences (e.g. that children should receive more than their ‘share’ of health care resources) and individual physician and patient preferences (4). The latter are most relevant when treatment decisions are being made for individual patients and they may lead to conflicfs between clinicians and policy makers. Health care professionals are often uncomfortable when asked to examine the

Association of young age and chemotherapy with psychosocial distress and health-related quality of life (HRQOL) during the first year after breast cancer (BC)

8014 Background: Psychosocial distress and HRQOL after BC diagnosis may be related to a variety of factors, including age and treatment.nnnMETHODSnWe investigated these attributes in 397 women with newly diagnosed T1-3, N0-1, M0 BC. Women completed the Profile of Mood States (POMS), Impact of Event Scale (IES), Psychosocial Adjustment to Illness Scale (PAIS), Mental Adjustment to Cancer Scale (MAC) and EORTC QLQ-C30 questionnaires shortly after diagnosis (9.7±5.2 weeks) and one year post diagnosis (57.4±7.7 weeks). The impact of age and adjuvant chemotherapy was analysed with t-tests and regression analysis. Mean age was 52.0±9.9 years. 47.6% were postmenopausal, 68.0% had ER/PgR positive tumors, 39.8% received CXT, 44.0% tamoxifen.nnnRESULTSnAt baseline, young age was significantly associated with greater distress (POMS all scales, total score), greater adverse impact on adjustment (PAIS 4 subscales, total), greater anxious-preoccupied and reduced fatalistic coping (MAC), and reduced emotional and cognitive functioning (EORTC QLQ-C30) (all p≤0.05); most of these effects were attenuated at one year, reflecting improvement over time. At 1 year, anxiety, anger and total mood disturbance (POMS), psychological distress and total score (PAIS), poor emotional functioning (EORTC QLQ-C30), and greater anxious-preoccupied coping and fatalistic coping (MAC) remained significantly associated with young age (p≤0.05). Physical functioning (EORTC QLQ-C30) was worse in older women at both timepoints. Adjusting for age, women who received chemotherapy reported greater adverse impact on vocational and social functioning (PAIS); role, social functioning and QOL (EORTC QLQ-C30) at baseline (p≤0.05). At one year, greater adverse impact of chemotherapy was seen for most PAIS scales and for physical, role and social functioning (EORTC QLQ-C30) (p≤0.05).nnnCONCLUSIONSnAge is an important determinant of psychosocial distress and HRQOL in newly diagnosed BC; women who receive CXT report greater adverse impact on adjustment, role, social and vocational functioning which persisted at one year. No significant financial relationships to disclose.

Multilayer bandaging plus compression hosiery was better than hosiery alone for unilateral lymphedema of a limb

Source Citation Badger CM, Peacock JL, Mortimer PS. A randomized, controlled, parallel-group clinical trial comparing multilayer bandaging followed by hosiery versus hosiery alone in the treatment ...