Perioperative Progesterone for Obese Women with Breast Cancer May Improve Survival

Abstract

Keywords

BMI breast cancer obesity progesterone prognosis vascular invasion

“Overweight postmenopausal women have a worse prognosis, partly because nodal positivity is associated with obesity.”

Obesity is the blight of the western world being implicated in myriad diseases and premature deaths. Public Health England estimate that 58% of women have a BMI of >25 kg/m² with 33% overweight (BMI: 25 to <30) and 25% obese (BMI: >35). Overweight postmenopausal women have an increased risk of developing breast cancer and carry a worse prognosis [1,2]. Although the rationale for weight loss may appear self-evident, the likely benefits in breast cancer patients require closer examination. Obesity may worsen prognosis as a result of increased synthesis of estrogens in peripheral fat and one possible approach to this problem is to use progestins to counteract the estrogenic drive.

Obesity & prognosis of breast cancer

Overweight postmenopausal women have a worse prognosis, partly because nodal positivity is associated with obesity. Daniell examined the axillary lymph node status of 465 postmenopausal women with breast cancer and reported that nodal positivity was more frequently associated with obesity (p < 0.001) [3]. As is shown in Table 1, there was a significant increase in breast cancer mortality with increasing BMI [3]. Based on the hypothesis that large breast size in obese women might delay discovery of breast cancers Cui et al. investigated the relation between body mass and stage at diagnosis [4]. In 966 breast cancer cases from the Baltimore Metropolitan area, high body mass was significantly associated with late stage at diagnosis and this relationship was stronger among women <50 years compared with those ≥50 years. In the American Cancer Society's Cancer Prevention Study II (CPS-II), 2852 breast cancer deaths occurred among 424,168 postmenopausal women after 14 years of follow-up [5]. There was a substantial and sustained increase in breast cancer mortality rate with increasing BMI. For those with a BMI >40.0 compared with BMI <18.5 there was a trebling of risk, as shown in Table 1.

Table 1.

Breast cancer prognosis in relation to weight.

Study (year)	Design	Participants (n)	Result	Ref.
Petrelli et al. (2002)	Cohort	2852/424,168	BMI >40 vs <18.5; RR: 3.08	[3]
Calle et al. (2003)	Cohort	2755/495,477	BMI >40 vs <18.5; RR: 2.12	[4]
Whiteman et al. (2005)	Cohort	1347/3924	BMI >30 vs <22.99; HR: 1.34	[5]
Cleveland et al. (2007)	Cohort	1508	Gain of >12.7 kg after 50; HR: 2.95	[6]
Nichols et al. (2009)	Cohort	3993	Each 5 kg ↑ BC deaths by 13%	[7]
Ewertz et al. (2010)	Cohort	18,967	BMI ≥30 vs 25; 38% ↑ BC deaths	[8]
Hellmann et al. (2010)	Cohort	528	Obese 1.82 BC deaths	[11]
Conroy et al. (2011)	Cohort	3842/118,869	BMI >30 vs <25; HR: 1.45	[8]

BC: Breast cancer; HR: Hazard ratio; RR: Relative risk.

Another large population investigation of US adults participating in Cancer Prevention Study II reported that those with a BMI of >40 kg/m² had death rates from all cancers combined that were 62% than those of normal weight [6]. For breast cancer the relative risk in those with a BMI of >40kg/m² was 2.12. Whiteman et al. conducted a cohort analysis of 3924 women aged 20–54 years with breast cancer enrolled in the CASH study [7]. Obese women with a BMI of >30 were significantly more likely than lean women to die of breast cancer (hazard ratio [HR]: 1.34).

Cleveland et al. interviewed 1508 breast cancer patients soon after diagnosis regarding height and weight at each decade of life from age 20 years until 1 year before diagnosis [8]. Obese women had increased mortality due to breast cancer compared with ideal weight women among those premenopausal at diagnosis (HR: 2.85) and those postmenopausal at diagnosis (HR: 1.91). Women with postmenopausal breast cancer who gained >12.7 kg after age of 50 years up to the year before diagnosis had a two- to three-fold increased risk of death due to all-causes (HR: 2.69). In a cohort of 3993 breast cancer patients completing a structured telephone interview 1−2 years after diagnosis and a mailed follow-up questionnaire, each 5-kg gain was associated with a 12% increase in all-cause mortality and a 13% increase in breast cancer-specific mortality [9], In a Danish study of 18,967 women with early breast cancer those with a BMI of ≥30 kg/m² were older with more advanced disease at diagnosis compared with those having a BMI of <25 kg/m² [10]. After adjustment for disease stage, risk of developing distant metastases after 10 years was significantly increased by 46%, and the risk of dying from breast cancer after 30 years was significantly increased by 38% for women with a BMI of ≥30 kg/m². Additionally the heavier women were less likely to benefit from systemic adjuvant chemotherapy or endocrine therapy.

Expansion of adipocyte population

Postmenopausal breasts show irreversible lobular involution and at the same time, intralobular and interlobular stroma is replaced with dense connective tissue and fat, respectively [12]. Expansion of the numbers of the adipocyte population changes the endocrine milieu with elevated aromatase activity increasing estradiol conversion. In a study of 505 women with breast cancer, McTiernan et al. reported that a BMI >30 could lead to a tripling of free estradiol levels [13].

Invasion of macrophages secreting TNF-α, TGF-β, IL-1β and HGF may induce an insulin-resistant state with hyperinsulinemia stimulating mitosis in breast cancer cells [14]. Necrotic adipocytes surrounded by macrophages form crown-like structures (CLS) present in 47% of breast biopsies [15]. Severity of inflammation was significantly related to both BMI and adipocyte size with increased aromatase activity in the inflamed breast tissue of obese cases.

Higher fasting insulin levels in breast cancer patients increase risk of both recurrence and death [16,17]. Adipocyte-derived leptin may mediate obesity-associated mitogenesis and angiogenesis in vitro [18]. Insulin-related variables are prognostically significant only during the first 5 years whereas obesity-related variables (BMI, weight, leptin) have adverse associations constant over time [19]. High BMI was associated with increased mortality up to and beyond 10 years.

Widespread alterations in gene expression occur in obese patients with the obesity gene signature correlated with IGF signaling and reduced estrogen receptor (ER) levels expression [20]. Estrogens induce the obesity transcription program in vitro, while agents targeting neurotransmitter receptor pathways cause repression.

Adiponectin acts in a protective capacity against obesity-related disorders including Type 2 diabetes and cardiovascular disease [21]. Additionally it inhibits immune cells and downregulates vascular adhesion molecules in endothelium [22]. Adiponectin can inhibit leptin-stimulated invasion of breast cancer cells [23] and two case–control studies have found an inverse relationship between serum adiponectin levels and breast cancer risk, independent of known risk factors [24,25]. In vitro exposure of human adipocytes to hypoxia produces a rapid threefold reduction in adiponectin levels [26]. In contrast, hypoxia stimulates leptin and VEGF gene expression so that obesity can give rise to a potentially lethal combination of reduced protection and increased malignant proliferation and metastasis.

Aromatase

The majority of postmenopausal women with ER positive tumors receive aromatase inhibitors which achieve castrate levels of estrogen, irrespective of BMI [27]. In the ATAC study women with BMI of >35 kg/m² were more likely to relapse than those with a BMI of <23 kg/m² and had significantly more distant recurrences [28]. Similar results were recorded in the German BRENDA-cohort [29]. In the Japanese neoadjuvant study JFMC 34-0601, response rates to neoadjuvant exemestane were 22, 56 and 61% in tertiles of BMI, with low BMI emerging as an independent negative predictor of clinical response [30]. In a prospective Japanese study of 501 patients with ER-positive cancers, 102 were of normal weight (BMI <25 kg/m²) and 399 were overweight or obese and they all received an adjuvant aromatase inhibitor [31]. There were no significant clinicopathological differences according to BMI. At 3 years disease-free survival was 78% in the nonobese compared with 86% in the obese.

Lymphovascular invasion & obesity

Abe et al. reported that poorer prognosis in obese women was associated with increased lymphovascular invasion (LVI) present in 73% [32]. A study of 393 postmenopausal patients at Guy's Hospital (London, UK) showed a direct relationship between LVI and BMI [33]. In the specimens from those <50 kg, LVI was observed in 11% compared with 45% from women >80 kg (p = 0.02). 5-year survival of women with LVI was 74% compared with 91% when absent (p < 0.0001). This was confirmed in another study of 1312 breast cancer cases where on multivariate analysis, severe obesity was independently associated with the presence of LVI (odds ratio: 1.80; p = 0.03) [34].

Most studies have not distinguished (LVI) and blood vessel invasion (BVI). Using an endothelial subtype specific immunohistochemical stains, Lee et al. reported a significant correlation between D2–40 LVI positivity and lymph node metastasis and recurrence [35]. There was no correlation between BVI and recurrence. A large study from Nottingham showed clearly that LVI was strongly inversely associated with distant metastasis-free survival, similar to the effect of having one to two lymph nodes involved [36].

Weight loss & prognosis

De Waard et al. set up a feasibility study with weight reduction achieved by calorie restriction and this was maintained for another 2 years but no end results were published [37]. In a prospective observational study Holmes et al. examined regular exercise and risk of relapse [38]. Compared with women engaging in <3 metabolic equivalent task (MET) hours per week, RR of breast cancer death was 0.80 for 3–8.9 MET, as shown in Table 2.

Table 2.

Studies examining weight loss and outcome after breast cancer treatment.

Study (year)	n	Design	Result	Ref.
de Waard et al. (1993)	103	Calorie reduction. Feasibility study	No survival results	[37]
Holmes et al. (2005)	2987	Observational	MET <3; RR: 1 MET 3–8.9; RR: 0.8 MET 9–14; RR: 0.5	[38]
Chlebowski et al. (2006)	2437 RCT	Fat reduction	Relapse reduced by 24% in intervention	[39]
Caan et al. (2008)	1692	Observational	Those losing most weight had worst prognosis	[40]
Morey et al. (2009)	641 RCT	Tel counseling and weight loss pamphlets	No effect on survival	[41]

MET: Metabolic equivalent task hours; RCT: Randomized controlled trial; RR: Relative risk.

In a randomized multicenter clinical trial of 2437 women, after 5 years median follow-up (when funding ceased) fat intake was significantly lower in the intervention group with a hazard ratio for relapse events in the intervention group versus controls of 0.76 (95% CI: 0.60–0.98; p = 0.034) [39]. There was a significant reduction in mean bodyweight within the intervention group (6 pounds; 2.7 kg).

Against this, Caan et al. reported that weight gain up to 4 years after diagnosis did not increase risk of recurrence or death from any cause [40]. Women with weight losses (≥10%) had increased risk of death from to any cause versus those with unchanged weight. This risk was more pronounced among those obese before diagnosis.

The RENEW trial tested a mailed diet-exercise intervention and telephone counseling in cancer survivors either immediately or after a 1-year delay [41]. The immediate intervention group experienced significant improvements in diet, activity and BMI but no impact on survival was reported. Only 6% of invited patients actually participated in the study and the attrition rate at 2 years was 25% [42]. In a meta-analysis of body compositional changes after breast cancer diagnosis bodyweight did not consistently increase nor did it accurately reflect lean or adipose tissue changes [43]. Behavioral interventions produced inconsistent or insignificant effects on body composition.

Some patients are more likely to accept a drug rather than a life style change to enable weight loss. Veerman et al. constructed a multistate life-table based Markov model using Australian data on effectiveness, mortality and disease costs, evaluating 1-year interventions with the drugs sibutramine and orlistat [44]. With reductions in bodyweight related disease burdens of 0.2 and 0.1%, respectively, the disability-adjusted life year avoidance cost was almost three times that deemed good value for money.

A meta-analysis of 43 studies examining weight and prognosis, confirmed worse overall and breast cancer-specific survival in the obese [45]. Survival rates in treatment and control cohorts were not statistically different. The authors concluded there was no current evidence of weight loss improving survival.

Changing the perioperative endocrine milieu

The hyperestrogenisation associated with obesity stimulates VEGF and is associated with a higher risk of LVI [35,36]. Before and during surgical excision there may be an increased risk of tumor dissemination. Studies in premenopausal women with breast cancer had shown that surgery in the luteal phase of the cycle was associated with better outcome [46 –48]. Furthermore, higher blood levels of progesterone were also predictive of improved prognosis [49]. This being so, it was reasoned that progesterone treatment could be used in the postmenopausal to try and simulate the endocrine status in the luteal phase of the cycle of the premenopausal.

To investigate this prospectively Badwe et al. conducted a randomized trial of 1000 women with operable breast cancer treated by surgery alone or with a single intramuscular hydroxyprogesterone 500 mg injection between 5 and 14 days before surgery [50]. After a median follow-up of 65 months, there had been 273 recurrences and 202 deaths. 5-year overall survival rates for the intervention and control groups were 80 versus 78%, respectively. Among the 471 node-positive patients, the 5-year overall survival rates were 76 versus 67% (p = 0.04). There were no reported adverse events nor were there any postoperative deaths. This result was described by the authors as ‘hypothesis generating’ and warrants further investigation since it could represent a simple and effective adjuvant therapy with progesterone inhibiting shedding of viable tumor during surgery. This is a pragmatic approach to examine the impact on survival but biological effects of progesterone on proliferation and apoptosis could be determined as bolt-on projects.

Conclusion

In postmenopausal women with breast cancer, although weight loss may improve health and self-esteem there seems little evidence to support its use as a means of reducing risk of recurrence compared with that achieved by aromatase inhibitors. Additionally although this may be achieved by some motivated individuals it is unlikely to work on a population basis. The harm may already have been done in terms of tumor angiogenesis. An agent that can be simply administered and well tolerated is likely to be more acceptable to patients at a time of great stress. Perioperative progesterone does provide a nontoxic potentially effective intervention and it is important that this approach is investigated by further randomized controlled trials.

Future perspective

Until now, neoadjuvant treatments for breast cancer have been able to sometimes downsize the tumor but have not led to any improvement in survival compared with postsurgical adjuvant therapy. We need therapies which will stabilize the cancer possibly by reducing mitosis or increasing apoptosis and thereby prevent local or distant spread as a result of surgical interventions. Perioperative progesterone may offer such an approach which requires confirmation by further randomized trials since this could have an important impact on survival for postmenopausal women with operable breast cancer.

Footnotes

The author has no relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript. This includes employment, consultancies, honoraria, stock ownership or options, expert testimony, grants or patents received or pending, or royalties.

No writing assistance was utilized in the production of this manuscript.

References

Papers of special note have been highlighted as: • of interest; •• of considerable interest

Daniell

. Increased lymph node metastases at mastectomy for breast cancer. Cancer 62, 429–435 (1988).

Cui

Whiteman

Flaws

Langenberg

Tkaczuk

Bush

. Body mass and stage of breast cancer at diagnosis. Int. J. Cancer 98, 279–283 (2002).

Petrelli

Calle

Rodriguez

Thun

. Body mass index, height, and postmenopausal breast cancer mortality in a prospective cohort of US women. Cancer Causes Control 13, 325–332 (2002).

Calle

Rodriguez

Walker-Thurmond

Thun

. Overweight, obesity, and mortality from cancer in a prospectively studied cohort of U.S. adults. N. Engl. J. Med. 348, 1625–1638 (2003).

Whiteman

Hillis

Curtis

McDonald

Wingo

Marchbanks

. Body mass and mortality after breast cancer diagnosis. Cancer Epidemiol. Biomarkers Prev. 14, 2009–2014 (2005).

Cleveland

Eng

Abrahamson

Britton

Teitelbaum

Neugut

Gammon

. Weight gain prior to diagnosis and survival from breast cancer. Cancer Epidemiol. Biomarkers Prev. 16, 1803–1811 (2007).

Nichols

Trentham-Dietz

Egan

. Body mass index before and after breast cancer diagnosis: associations with all-cause, breast cancer, and cardiovascular disease mortality. Cancer Epidemiol. Biomarkers Prev. 18, 1403–1409 (2009).

Ewertz

Jensen

M-B

Gunnarsdottir

. Effect of obesity on prognosis after early-stage breast cancer. J. Clin. Oncol. 29, 25–31 (2010).

10.

Study of almost 19,000 breast cancer cases showing poor prognosis of the obese.

11.

Conroy

Maskarinec

Wilkens

White

Henderson

Kolonell

. Obesity and breast cancer survival in ethnically diverse postmenopausal women: the Multiethnic Cohort Study. Breast Cancer Res. Treat. 129, 565–574 (2011).

12.

Ligibel

Cirrincione

Liu

. Body mass index, PAM50 subtype, and outcomes in node-positive breast cancer: CALGB 9741 (Alliance). J. Natl Cancer Inst. 107(9), pii: djv179 (2015).

13.

Hellmann

Thygesen

Tolstrup

Grønbaek

. Modifiable risk factors and survival in women diagnosed with primary breast cancer: results from a prospective cohort study. Eur. J. Cancer Prev. 19, 366–373 (2010).

14.

Russo

Lynch

Russo

. Mammary gland architecture as a determining factor in the susceptibility of the human breast to cancer. Breast J. 7, 278–291 (2001).

15.

McTiernan

Rajan

Tworoger

. Adiposity and sex hormones in postmenopausal breast cancer survivors. J. Clin. Oncol. 21, 1961–1966 (2003).

16.

Obese women had 130% higher concentrations of estradiol compared with lighter-weight women.

17.

Bastard

Maachi

Lagathul

. Recent advances in the relationship between obesity, inflammation, and insulin. Eur. Cytokine Netw. 17, 4–12 (2006).

18.

Morris

Hudis

Giri

. Inflammation and increased aromatase expression occur in the breast tissue of obese women with breast cancer. Cancer Prev. Res. 4, 1021–1029 (2011).

19.

Goodwin

Ennis

Pritchard

. Fasting insulin and outcome in early-stage breast cancer: results of a prospective cohort study. J. Clin. Oncol. 20, 42–51 (2002).

20.

Borugian

Sheps

Kim-Sing

. Insulin, macronutrient intake, and physical activity: are potential indicators of insulin resistance associated with mortality from breast cancer? Cancer Epidemiol. Biomarkers Prev. 13, 1163–1172 (2004).

21.

Catalano

Marsico

Giordano

. Leptin enhances, via AP-1, expression of aromatase in the MCF-7 cell line. J. Biol. Chem. 278, 28668–28676 (2003).

22.

Goodwin

Ennis

Pritchard

. Insulin- and obesity-related variables in early-stage breast cancer: correlations and time course of prognostic associations. J. Clin. Oncol. 30, 164–171 (2012).

23.

Creighton

Sada

Zhang

. A gene transcription signature of obesity in breast cancer. Breast Cancer Res. Treat. 132, 993–1000 (2012).

24.

Yamauchi

Kamon

Waki

. The fat-derived hormone adiponectin reverses insulin resistance associated with both lipoatrophy and obesity. Nat. Med. 7, 941–946 (2001).

25.

Goldstein

Scalia

. Adiponectin: a novel adipokine linking adipocytes and vascular function. J. Clin. Endocrinol. Metab. 89, 2563–2568 (2004).

26.

Taliaferro-Smith

Nagalingam

Knight

B Brandon

Oberlick

Saxena

Sharma

. Integral role of PTP1B in adiponectin-mediated inhibition of oncogenic actions of leptin in breast carcinogenesis. Neoplasia 15, 23 (2013).

27.

Miyoshi

Funahashi

Kihara

. Association of serum adiponectin levels with breast cancer risk. Clin. Cancer Res. 9, 5699–5704 (2003).

28.

Mantzoros

Petridou

Dessypris

. Adiponectin and breast cancer risk. J. Clin. Endocrinol. Metab. 89, 1102–1107 (2004).

29.

Wang

Wood

Trayhurn

. Dysregulation of the expression and secretion of inflammation-related adipokines by hypoxia in human adipocytes. Eur. J. Physiol. 455, 479–492 (2007).

30.

Pfister

Martoni

Zamagni

. Effect of age and single versus multiple dose pharmacokinetics of letrozole (Femara) in breast cancer patients. Biopharm. Drug Dispos. 22, 191–197 (2001).

31.

Sestak

Distler

Forbes

Dowsett

Howell

Cuzick

. Effect of body mass index on recurrences in tamoxifen and anastrozole treated women: an exploratory analysis from the ATAC trial. J. Clin. Oncol. 28, 3411–3415 (2010).

32.

Obesity worsens prognosis in women who were given adjuvant anastrozole.

33.

Wolters

Schwentner

Regierer

Wischnewsky

Kreienberg

Wöckel

. Endocrine therapy in obese patients with primary breast cancer: another piece of evidence in an unfinished puzzle. Breast Cancer Res. Treat. 131, 925–931 (2012).

34.

Takada

Saji

Masuda

. Relationship between body mass index and preoperative treatment response to aromatase inhibitor exemestane in postmenopausal patients with primary breast cancer. Breast 21, 40–45 (2012).

35.

Sendur

MAN

Aksoy

Zengin

Altundag

. Efficacy of adjuvant aromatase inhibitor in hormone receptor-positive postmenopausal breast cancer patients according to the body mass index. Br. J. Cancer 107, 1815–1819 (2012).

36.

Abe

Kumagai

Kimura

Hirosaki

Nakamura

. Biological characteristics of breast cancer in obesity. Tohoku J. Exp. Med. 120, 351–359 (1976).

37.

Badwe

Fentiman

Millis

Gregory

. Body weight and vascular invasion in postmenopausal women with breast cancer. Br. J. Cancer 75, 910–913 (1997).

38.

Gillespie

Sorbero

Hanauer

. Obesity and angiolymphatic invasion in primary breast cancer. Ann. Surg. Oncol. 17, 752–759 (2010).

39.

Lee

Bae

Woo

Chul

Kim

. D2–40, Podoplanin, and CD31 as a prognostic predictor in invasive ductal carcinomas of the breast. J. Breast Cancer 14, 104–111 (2011).

40.

Rakha

Martin

Lee

. The prognostic significance of lymphovascular invasion in invasive breast carcinoma. Cancer 118, 3670–3680 (2012).

41.

de Waard

Ramlau

Mulders

de Vries

van Waveren

. A feasibility study on weight reduction in obese postmenopausal breast cancer patients. Eur. J. Cancer Prev. 2, 233–238 (1993).

42.

Holmes

Chen

Feskanich

Kroenke

Colditz

. Physical activity and survival after breast cancer diagnosis. JAMA 293, 2479–2486 (2005).

43.

Chlebowski

Blackburn

Thomson

. Dietary fat reduction and breast cancer outcome: interim efficacy results from the Women's Intervention Nutrition Study. J. Natl Cancer Inst. 98, 1767–1767 (2006).

44.

Caan

Kwan

Hartzell

. Pre-diagnosis body mass index, post-diagnosis weight change, and prognosis among women with early stage breast cancer. Cancer Causes Control. 19, 1319–1328 (2008).

45.

Morey

Snyder

Sloane

. Effects of home-based diet and exercise on functional outcomes among older, overweight long-term cancer survivors: the RENEW: randomized clinical trial. JAMA 301, 1883–1891 (2009).

46.

Ligibel

Goodwin

. NEW and RENEW: Building the case for weight loss in breast cancer. J. Clin. Oncol. 30, 2294–2296 (2012).

47.

Sheean

Hoskins

Stolley

. Body composition changes in females treated for breast cancer: a review of the evidence. Breast Cancer Res. Treat. 135, 663–680 (2012).

48.

Veerman

Barendregt

Forster

Vos

. Cost–effectiveness of pharmacotherapy to reduce obesity. PLoS ONE 6(10), e26051 (2011).

49.

Protani

Coory

Martin

. Effect of obesity on survival of women with breast cancer: systematic review and meta-analysis. Breast Cancer Res. Treat. 123, 627–635 (2010).

50.

Badwe

Gregory

Chaudary

. Timing of surgery during menstrual cycle and survival of premenopausal women with operable breast cancer. Lancet 337, 1261–1264 (1991).

51.

Senie

Rosen

Rhodes

Lesser

. Timing of breast cancer excision during the menstrual cycle influences duration of disease-free survival. Ann. Intern. Med. 115, 337–342 (1991).

52.

Veronesi

Luini

Mariani

. Effect of menstrual phase on surgical treatment of breast cancer. Lancet 343, 1545–1547 (1994).

53.

Mohr

Wang

Gregory

. Serum progesterone and prognosis in operable breast cancer. Br. J. Cancer 73, 1552–1555 (1996).

54.

Badwe

Hawalda

Parmar

. Single-injection depot progesterone before surgery and survival in women with operable breast cancer: a randomized controlled trial. J. Clin. Oncol. 29, 2845–2851 (2011).

55.

A single hydroxyprogesterone injection before surgery significantly improves in node-positive cases.