Background: We tested the effect of weight loss on circulating levels of the angiogenic factors VEGF and pigment epithelium-derived factor (PEDF) in postmenopausal overweight/obese women, 18 months after completing a year-long 4-arm randomized controlled trial of behavioral weight loss and/or exercise versus control (i.e., 30 months postrandomization).

Methods: The 439 overweight/obese, postmenopausal women, ages 50 to 75 years, were randomized to: diet (goal: 10% weight loss, N = 118), exercise (225 min/wk moderate-to-vigorous activity, N = 117), diet + exercise (N = 117), or control (N = 87). At 12 months, 399 women gave a blood sample; 156 returned at 30 months. Biomarkers were measured by immunoassay. Changes were compared using generalized estimating equations, adjusting for baseline BMI, age, and race/ethnicity.

Results: Participants randomized to diet, exercise, and diet + exercise arms had greater reductions in VEGF at 30 months (−14.1% P = 0.02; −19.7% P = 0.003; −14.5% P = 0.002, respectively) versus controls (−4.5%). There were no statistically significant changes in PEDF in any intervention arm. Participants maintaining ≥10% of baseline weight loss at 30 months had greater reductions in VEGF versus those who gained weight/had no weight change (−22.3% vs. −10.2% respectively, P = 0.002). Participants maintaining any weight loss had significantly lower levels of PEDF at 30 months versus those who gained weight/no weight change.

Conclusions: Sustained weight loss via diet and/or exercise results in reductions in angiogenic factors, and can be maintained up to 30-month follow-up. Limitations include relatively small numbers, and possible bias toward more successful weight loss among women who returned at 30 months.

Impact: Maintaining weight loss can achieve long-term reductions in biomarkers of angiogenesis that can persist up to 18 months after completion of a weight loss intervention. Cancer Epidemiol Biomarkers Prev; 26(12); 1788–94. ©2017 AACR.

Excess body fat is associated with increased risk of a variety of cancers (1–3). The exact mechanisms linking adiposity and excess cancer risk are unknown but may include altered sex hormone metabolism, increased insulin levels, and adipokine pathophysiology combined with systemic elevated inflammation (4, 5). These candidate mechanisms have a variety of effects on downstream processes, including on angiogenesis, a process where new blood vessels are formed. Angiogenesis is tightly regulated by a number of pro- and antiangiogenic factors in healthy tissue, but during tumorigenesis these pathways are dysregulated, and new blood vessels form, allowing dormant avascular tumors to form new blood vessels and to proliferate (6). Adipose tissue expansion also requires angiogenesis, and many of the angiogenic factors upregulated during adipogenesis are involved in the “angiogenic switch” (7–9).

We have previously reported that women who lost at least 1.85% of baseline fat mass in a 12-month exercise intervention experienced significant reductions in some biomarkers of angiogenesis (10) compared with sedentary controls. Subsequently, in a completed randomized control trial—the Nutrition and Exercise in Women (NEW) study—of 439 overweight/obese, postmenopausal women, we investigated the independent and combined effects of a behavioral dietary weight loss intervention and an exercise intervention on circulating levels of pro- and antiangiogenic factors, compared with controls. VEGF and plasminogen activator inhibitor type-1 (PAI-1), proangiogenic factors, and pigment epithelium-derived factor (PEDF), a potent inhibitor of angiogenesis (11), were measured in participants at baseline and 12 months post-randomization. Participants randomized to the diet + exercise arms had statistically significantly greater reductions in PAI-1, VEGF, and PEDF at 12 months compared with controls (all P < 0.0001). Increasing weight loss was statistically significantly associated with linear trends of greater reductions in PAI-1, PEDF, and VEGF (12). However, it is currently unknown whether beneficial changes in these and other cancer-related biomarkers persist long-term. Some studies on diabetes prevention indicate that, despite weight regain, risk of developing diabetes is reduced on average for several years (13). If biomarker changes associated with decreased cancer risk can be maintained, with or without sustained weight loss, it would support weight loss interventions for cancer prevention in overweight or obese individuals.

In this study, we investigate the effects of weight loss on long-term circulating levels of VEGF and PEDF in 156 women who were enrolled in the NEW study, and who returned at 30 months post-randomization; that is, 18 months after discontinuing the yearlong intervention, to give a blood sample. To our knowledge, this study will be the first to investigate the long-term effects of dietary weight loss on circulating levels of these angiogenic factors.

This study is ancillary to the NEW (www.clinicaltrials.gov NCT00470119) study, a 12-month randomized controlled trial that tested the effects of caloric restriction and/or exercise on circulating sex steroid hormones in healthy overweight, postmenopausal women. The parent and ancillary studies were carried out in the Fred Hutchinson Cancer Research Center (FHCRC; Seattle, Washington), and performed with the approval of the FHCRC Institutional Review Board, in accordance with an assurance filed with and approved by the U.S. Department of Health and Human Services. Written informed consent was obtained from each participant. The parent trial is described in detail elsewhere (14). Briefly, 439 postmenopausal, healthy, overweight (BMI ≥ 25 kg/m2), sedentary women, ages 50 to 75 years, not taking hormonal therapy, were recruited through media and mass mailings and were enrolled in the study between 2005 and 2008; 12-month follow-up for all participants was completed in 2009. Eligible participants were randomly assigned to a (i) reduced-calorie dietary modification intervention (N = 118); (ii) moderate-to-vigorous intensity aerobic exercise intervention (N = 117); (iii) combined diet and exercise intervention (N = 117); or (iv) control (no intervention; N = 87). Exclusion criteria included > 100 min/wk of moderate physical activity; diagnosed diabetes or other serious medical condition(s); postmenopausal hormone use; consumption of >2 alcoholic drinks/d; current smoking; participation in another structured weight loss program; contraindication to participation (e.g., abnormal exercise tolerance test, inability to attend sessions). Permuted block randomization was used to achieve a proportionally smaller control arm, stratified according to BMI (≥/<30 kg/m2) and race/ethnicity. The random assignment was generated by a computerized program, written by the study statistician, and run by the study manager to assign eligible participants to study arms. Investigators and laboratory staff were blinded to randomization arm.

At 12 months, 399 of 439 participants from the NEW study completed physical exams and provided a blood sample (Fig. 1). For the ancillary study, women were identified from study records as they approached their 30-month anniversary of randomization. Seventy-five women had already passed the 30-month anniversary at the time recruitment began, and were thus ineligible. To assess interest, women were contacted by study staff, and invited to be part of the follow-up study. Of the 324 eligible (i.e., those who were still within the 30-month time frame) women contacted from the parent trial, 221 women agreed to provide questionnaire-based follow-up data and, of these, 156 provided fasting blood samples.

Figure 1.

CONSORT diagram. It illustrates the participant progress through the phases of the NEW study, a four-arm randomized control trial, including enrollment, intervention allocation and follow-up at 12 and 30 months postrandomization.

Figure 1.

CONSORT diagram. It illustrates the participant progress through the phases of the NEW study, a four-arm randomized control trial, including enrollment, intervention allocation and follow-up at 12 and 30 months postrandomization.

Close modal

Blood specimen collection and processing

Fasting (12 hours) venous blood samples (50 mL) were collected during clinic visits at baseline (prerandomization), 12 months, when the study was completed and at 30months post-randomization. Participants refrained from alcohol (48 hours), vigorous exercise or NSAID use (24 hours) before fasting venous blood collection (50 mL) at baseline and 12 months. Blood was processed within one hour and stored at −70°C.

Assays

VEGF and PEDF were assayed from 30-month blood samples at the Clinical and Epidemiologic Research Laboratory, at the Department of Laboratory Medicine, Boston Children's Hospital (Boston, MA), using Enzyme Linked Immunosorbent Assays from R&D Systems (Minneapolis, MN). Duplicate pooled blood samples were included for quality assurance (QA) purposes and to assess inter- and intra-assay coefficient of variation (CV). Laboratory personnel were blinded with regard to subject and QA sample identity. Inter- and intra-assay CVs for each assay were VEGF 3.5% and 3.5%; PEDF 7.5% and 5.8%, respectively. To correct for assay drift over time and to incorporate these data into the baseline and 12-month data, we included a series of baseline and 12-month samples that matched samples that had been previously assayed in each batch of 30-month samples (12). We compared the results from these samples with previously measured results, and used mean of the difference to normalize the newly assayed 30-month data.

Covariates

All study measures were obtained at baseline, 12-month, and 30-month time points by trained personnel blinded to participants' randomization status. Height and weight were measured and body mass index (BMI, kg/m2) calculated. Body composition (fat mass and percent body fat) was measured by DXA (Dual-energy X-ray absorptiometry) whole-body scanner (GE Lunar, Madison, WI). Cardiorespiratory fitness (VO2max) was assessed using a maximal graded treadmill test according to a modified branching protocol (15). Questionnaires collected information on demographics, medical history, dietary intake, supplement use, and physical activity patterns.

Statistical analyses

The Kolmogorov-Smirnov test was used for the baseline comparisons between participants versus nonparticipants because the assumption of homogeneous variances between the two samples may not hold for all variables. Descriptive data are presented as geometric means [95% confidence intervals (CI)].

We compared average changes in outcomes from baseline to 30 months by randomization arm, using the generalized estimating equations (GEE) modification of linear regression to account for the correlation within individuals over time. The main analyses were performed according to the intention-to-treat principle, where outcome for patients are analyzed by treatment assignment, regardless of adherence.

For secondary, preplanned analyses, we combined data from participants who had been randomized to the control and exercise arms to the “No Diet” group (N = 56), and data from participants randomized to the diet and diet + exercise arms to the “Diet” group (N = 87). Participants were divided into four categories based on change from baseline to 30 months: (i) gained weight or remained weight stable; (ii) lost < 5% of baseline weight; (iii) lost 5–< 10% of baseline weight; and (iv) lost ≥ 10% of baseline weight. These four weight-loss categories were used to stratify observed changes in analytes between the Diet and No Diet groups at 30 months. We then compared 30-month analyte changes by these 30-month weight loss groups. We next combined data for all women regardless of randomization group, and compared analytes changes from baseline to 30 months stratified by weight-loss categories.

All models were adjusted for age, baseline BMI (<30 kg/m2, ≥30 kg/m2) and race/ethnicity. All statistical tests were two sided. Statistical analyses were performed using SAS software (version 8.2, SAS Institute Inc.).

Participants

At 30 months, 156 (39.1%) of 399 women who had completed the 12-month assessment provided a blood sample and completed questionnaires. At baseline, participants were on average 58.0 years, with an average BMI of 30.1 kg/m2, and were predominantly non-Hispanic whites. Compared with nonparticipants, women who agreed to take part in the ancillary study had lower baseline BMIs (30.1 vs. 31.3 kg/m2, P = 0.007), and a smaller waist circumference (P < 0.001), but did not differ by baseline VEGF or PEDF levels, or percent weight lost during the 12-month intervention period (Table 1).

Table 1.

Baseline covariates by the study group

No diet (Control and Exercise), N = 69Diet (Diet, and Diet + Exercise), N = 87Study participants, N = 156Study nonparticipants, N = 282
Mean (SD)Mean (SD)Mean (SD)Mean (SD)Pa
Age 58.54 (5.22) 58.10 (5.75) 58.3 (5.5) 57.74 (4.74) 0.48 
BMI kg/m2 29.63 (3.64) 30.39 (3.85) 30.06 (3.77) 31.31 (4.0) 0.007 
Waist circumference (cm) 91.47 (8.51) 92.29 (8.82) 91.93 (8.66) 95.97 (10.53) <0.001 
Physical activity 38.32 (46.90) 35.99 (48.46) 37.02 (47.64) 29.90 (41.12) 0.16 
% calories intake from fat 33.45 (6.66) 33.97 (6.22) N=85 33.74 (6.41) N=154 34.63 (7.19)N=272 0.57 
VO2max 22.78 (4.11) 22.70 (4.38) 22.74 (4.25) 23.05 (3.90) 0.92 
Total calories intake 2,108 (668.6) 1,886 (563.2)N=85 1,985 (620.5)N=154 1,907 (647)N=272 0.32 
Weight loss at 12 months (%) −0.92 (4.21) −12.60 (6.33) −7.43 (7.99) −6.02 (7.34) 0.19 
VEGF 347.6 (220.6) 383.2 (228.9) 367.4 (225.2) 390.8 (262.3) 0.74 
PEDF 10.62 (2.03) 10.81 (2.16) 10.73 (2.10) 10.80 (2.07) 0.73 
 N(%) N(%) N(%) N(%) Pb 
Race/ethnicity 
 Non-Hispanic white 61 (88.4) 76 (87.4) 137 (87.8) 235 (83.3) 0.09 
 African American 4 (5.8) 2 (2.3) 6 (3.8) 29 (10.3)  
 Hispanic/Latino 2 (2.9) 4 (4.6) 6 (3.8) 6 (2.1)  
Other 2 (2.9) 5 (5.7) 7 (4.6) 12 (4.3)  
Education 46 (66.67) 60 (68.97) 106 (67.95) 180 (63.83) 0.39 
No diet (Control and Exercise), N = 69Diet (Diet, and Diet + Exercise), N = 87Study participants, N = 156Study nonparticipants, N = 282
Mean (SD)Mean (SD)Mean (SD)Mean (SD)Pa
Age 58.54 (5.22) 58.10 (5.75) 58.3 (5.5) 57.74 (4.74) 0.48 
BMI kg/m2 29.63 (3.64) 30.39 (3.85) 30.06 (3.77) 31.31 (4.0) 0.007 
Waist circumference (cm) 91.47 (8.51) 92.29 (8.82) 91.93 (8.66) 95.97 (10.53) <0.001 
Physical activity 38.32 (46.90) 35.99 (48.46) 37.02 (47.64) 29.90 (41.12) 0.16 
% calories intake from fat 33.45 (6.66) 33.97 (6.22) N=85 33.74 (6.41) N=154 34.63 (7.19)N=272 0.57 
VO2max 22.78 (4.11) 22.70 (4.38) 22.74 (4.25) 23.05 (3.90) 0.92 
Total calories intake 2,108 (668.6) 1,886 (563.2)N=85 1,985 (620.5)N=154 1,907 (647)N=272 0.32 
Weight loss at 12 months (%) −0.92 (4.21) −12.60 (6.33) −7.43 (7.99) −6.02 (7.34) 0.19 
VEGF 347.6 (220.6) 383.2 (228.9) 367.4 (225.2) 390.8 (262.3) 0.74 
PEDF 10.62 (2.03) 10.81 (2.16) 10.73 (2.10) 10.80 (2.07) 0.73 
 N(%) N(%) N(%) N(%) Pb 
Race/ethnicity 
 Non-Hispanic white 61 (88.4) 76 (87.4) 137 (87.8) 235 (83.3) 0.09 
 African American 4 (5.8) 2 (2.3) 6 (3.8) 29 (10.3)  
 Hispanic/Latino 2 (2.9) 4 (4.6) 6 (3.8) 6 (2.1)  
Other 2 (2.9) 5 (5.7) 7 (4.6) 12 (4.3)  
Education 46 (66.67) 60 (68.97) 106 (67.95) 180 (63.83) 0.39 

aA P value from a nonparametric Kolmogorov-Smirnov two-sample test for difference between study participants versus nonparticipants.

bA P value from a χ2 test for a difference in proportions between study participants versus nonparticipants.

Although a pattern of weight regain is seen, at 30 months the mean reduction in BMI in the diet + exercise arm was −7.92% at 30 months versus −13.7% loss at 12 months. Weight loss at 30 months and 12 months in the control, diet, and exercise arms, were −2.88% and +0.62% (control); −6.64% and −12.0% (diet) and −2.11% and −1.93% (exercise), respectively.

Intervention and weight-loss effects on angiogenic factors in the parent study (NEW study)

Briefly, in the parent trial (the NEW study), participants randomized to the diet and diet + exercise arms only had statistically significantly greater reductions in both VEGF and PEDF at 12 months compared with those randomized to the control arm (all P ≤ 0.0005). There was a statistically significant linear trend of reductions in PEDF and VEGF with increasing weight loss among participants randomized to both the diet and diet + exercise arm (all Ptrend<0.0001). Participants randomized to the exercise arm also had statistically significant linear trend of reductions in PEDF with increasing levels of weight loss (12)

Intervention effects on angiogenic factors at 30-month follow-up (NOW study)

At the 30-month follow-up, participants randomized to any of the three intervention arms had statistically significant reductions in levels of VEGF between baseline and 30 months compared to controls (controls −4.54%; diet −14.1%, P = 0.02; exercise −19.7%, P = 0.003; diet + exercise −14.5%, P = 0.002; Table 2). In contrast, there were no statistically significant changes in levels of PEDF between baseline and 30 months in any randomization arm, compared with controls.

Table 2.

Twelve- and 30-month changes in BMI and in angiogenesis biomarkers by randomization arm

Time pointP
Baseline12 Months30 Months
Randomization armNGM (95% CI)NGM (95% CI)NGM (95% CI)0–12 Months change (%)0–30 Months change (%)P12unadjP12adjP30unadjP30adj
BMI 
 Control 25 30.42 (28.99–31.93) 25 30.61 (29.03–32.28) 24 29.55 (27.77–31.43) 0.19 (0.62) −0.88 (−2.88) 
 Diet 45 29.88 (28.85–30.94) 45 26.30 (25.14–27.51) 45 27.89 (26.69–29.15) −3.58 (−12.0) −1.98 (−6.64) <0.001 <0.001 0.05 0.05 
 Exercise 44 28.87 (27.95–29.83) 44 28.32 (27.35–29.32) 44 28.27 (27.24–29.33) −0.56 (−1.93) −0.61 (−2.11) 0.02 0.02 0.47 0.45 
 Diet+Ex 42 30.46 (29.28–31.69) 42 26.28 (25.13–27.47) 42 28.05 (26.86–29.29) −4.19 (−13.7) −2.41 (−7.92) <0.001 <0.001 0.005 0.005 
VEGF 
 Control 25 304.4 (236.7–391.4) 25 318.0 (243.2–415.9) 23 290.6 (221.1–381.8) 13.63 (4.48) −13.8 (−4.54) 
 Diet 45 321.3 (268.6–384.3) 45 289.1 (241.4–346.3) 43 276.1 (224.0–340.2) −32.1 (−10.0) −45.2 (−14.1) <0.001 <0.001 0.02 0.02 
 Exercise 44 269.4 (218.5–332.2) 44 267.1 (215.3–331.4) 39 216.5 (171.3–273.5) −2.29 (−0.85) −52.9 (−19.7) 0.13 0.126 0.002 0.003 
 Diet+Ex 42 312.2 (252.1–386.6) 42 284.2 (230.2–350.8) 39 267.0 (210.5–338.7) −28.0 (−8.97) −45.2 (−14.5) <0.001 <0.001 0.002 0.002 
PEDF 
 Control 25 11.37 (10.60–12.20 25 11.24 (10.50–12.04 23 11.79 (10.75–12.93 −0.13 (-1.16) 0.42 (3.68) 
 Diet 45 10.68 (10.06–11.34 45 9.19 (8.66–9.77 43 10.59 (9.92–11.32 −1.49 (−13.9) −0.09 (−0.84) <0.001 <0.001 0.41 0.42 
 Exercise 44 9.95 (9.46–10.46 44 9.94 (9.46–10.45) 39 10.98 (10.32–11.68) −0.01 (−0.08) 1.03 (10.35) 0.72 0.72 0.21 0.19 
 Diet+Ex 42 10.50 (9.88–11.16) 42 9.25 (8.77–9.75) 39 10.53 (10.02–11.07) −1.25 (−11.9) 0.03 (0.29) <0.001 <0.001 0.46 0.48 
Time pointP
Baseline12 Months30 Months
Randomization armNGM (95% CI)NGM (95% CI)NGM (95% CI)0–12 Months change (%)0–30 Months change (%)P12unadjP12adjP30unadjP30adj
BMI 
 Control 25 30.42 (28.99–31.93) 25 30.61 (29.03–32.28) 24 29.55 (27.77–31.43) 0.19 (0.62) −0.88 (−2.88) 
 Diet 45 29.88 (28.85–30.94) 45 26.30 (25.14–27.51) 45 27.89 (26.69–29.15) −3.58 (−12.0) −1.98 (−6.64) <0.001 <0.001 0.05 0.05 
 Exercise 44 28.87 (27.95–29.83) 44 28.32 (27.35–29.32) 44 28.27 (27.24–29.33) −0.56 (−1.93) −0.61 (−2.11) 0.02 0.02 0.47 0.45 
 Diet+Ex 42 30.46 (29.28–31.69) 42 26.28 (25.13–27.47) 42 28.05 (26.86–29.29) −4.19 (−13.7) −2.41 (−7.92) <0.001 <0.001 0.005 0.005 
VEGF 
 Control 25 304.4 (236.7–391.4) 25 318.0 (243.2–415.9) 23 290.6 (221.1–381.8) 13.63 (4.48) −13.8 (−4.54) 
 Diet 45 321.3 (268.6–384.3) 45 289.1 (241.4–346.3) 43 276.1 (224.0–340.2) −32.1 (−10.0) −45.2 (−14.1) <0.001 <0.001 0.02 0.02 
 Exercise 44 269.4 (218.5–332.2) 44 267.1 (215.3–331.4) 39 216.5 (171.3–273.5) −2.29 (−0.85) −52.9 (−19.7) 0.13 0.126 0.002 0.003 
 Diet+Ex 42 312.2 (252.1–386.6) 42 284.2 (230.2–350.8) 39 267.0 (210.5–338.7) −28.0 (−8.97) −45.2 (−14.5) <0.001 <0.001 0.002 0.002 
PEDF 
 Control 25 11.37 (10.60–12.20 25 11.24 (10.50–12.04 23 11.79 (10.75–12.93 −0.13 (-1.16) 0.42 (3.68) 
 Diet 45 10.68 (10.06–11.34 45 9.19 (8.66–9.77 43 10.59 (9.92–11.32 −1.49 (−13.9) −0.09 (−0.84) <0.001 <0.001 0.41 0.42 
 Exercise 44 9.95 (9.46–10.46 44 9.94 (9.46–10.45) 39 10.98 (10.32–11.68) −0.01 (−0.08) 1.03 (10.35) 0.72 0.72 0.21 0.19 
 Diet+Ex 42 10.50 (9.88–11.16) 42 9.25 (8.77–9.75) 39 10.53 (10.02–11.07) −1.25 (−11.9) 0.03 (0.29) <0.001 <0.001 0.46 0.48 

NOTE:P12unadj was obtained from a GEE model comparing changes in the biomarkers from baseline with 12 months between intervention versus control arm, unadjusted. P12adj was obtained from a GEE model comparing changes in the biomarkers from baseline with 12 months between intervention versus control arm, adjusted for baseline age, baseline BMI (<30 kg/m2, ≥30 kg/m2), and race/ethnicity. P30unadj was obtained from a GEE model comparing changes in the biomarkers from baseline with 30 months between intervention versus control arm, unadjusted. P30adj was obtained from a GEE model comparing changes in the biomarkers from baseline with 30 months between intervention vs control arm, adjusted for baseline age, baseline BMI (<30 kg/m2, ≥30 kg/m2), and race/ethnicity.

Weight loss effects on angiogenic factors at 30-month follow-up

In the parent study, weight loss appeared to account for the majority of the reductions in both PEDF and VEGF, with increasing weight loss associated with statistically significant linear decreases in all analytes. Because of the relatively small numbers, we were unable to stratify randomization arm by weight-loss categories. However, when we combined the diet and diet + exercise arms into a “Diet” group, and control and exercise arms into a “No Diet” group, and stratified by weight loss, there were no associations between changes in analytes from baseline to 30-months by intervention grouping. This lack of association may be due to the greater increase in percent weight loss in the control and exercise arms at 30 months (−2.88% and −2.11% respectively), compared with 12 months (0.62% and −1.93%, respectively; Supplementary Table S1).

When we combined all participants' data regardless of intervention arm, and stratified by four categories of percentage of weight loss, only women who maintained ≥10% of baseline weight at 30 months had significantly greater reductions in VEGF levels compared to those who lost no weight or gained weight (−22.3% vs. −10.2% respectively, P = 0.002; Table 3). Participants who maintained any level of weight loss at 30 months had significantly lower levels of PEDF compared with those who had either gained weight or had no weight change. However, for participants who lost 0% to 5% and 5% to 10% of weight, these differences were represented by comparatively smaller increases in PEDF levels (+3.67%, 3.26%, respectively) compared with no weight loss/weight gain (+15.76%). Participants who lost ≥10% of baseline weight reduced PEDF levels by −7.73% (P < 0.001).

Table 3.

Change from baseline to 30 months in the log-transformed (normalized) biomarkers by category of weight loss (all participants combined)

Baseline30 Months
Weight change Baseline to 30 monthsNGM (95% CI)9NGM (95% CI)Absolute change (%)Pa
VEGF 
 Lost ≤0% 33 286.7 (233.1–352.7) 30 257.4 (202.2–327.7) −29.3 (−10.2) 
 Lost 0–5% 53 312.0 (266.6–365.1) 51 279.1 (233.0–334.3) −32.9 (−10.5) 0.84 
 Lost 5–10% 37 302.1 (239.4–381.2) 31 266.3 (201.5–351.9) −35.8 (−11.9) 0.13 
 Lost ≥10% 32 291.1 (219.6–385.9) 32 226.1 (169.5–301.6) −65.0 (−22.3) 0.002 
PEDF 
 Lost ≤0% 33 10.32 (9.59–11.11) 30 11.95 (11.04–12.94) 1.63 (15.76) 
 Lost 0–5% 53 10.93 (10.37–11.51) 51 11.33 (10.79–11.89) 0.40 (3.67) 0.02 
 Lost 5–10% 37 10.30 (9.73–10.91) 31 10.64 (10.02–11.29) 0.34 (3.26) 0.01 
 Lost ≥10% 32 10.34 (9.68–11.05) 32 9.54 (8.94–10.19) −0.80 (−7.73) <0.001 
Baseline30 Months
Weight change Baseline to 30 monthsNGM (95% CI)9NGM (95% CI)Absolute change (%)Pa
VEGF 
 Lost ≤0% 33 286.7 (233.1–352.7) 30 257.4 (202.2–327.7) −29.3 (−10.2) 
 Lost 0–5% 53 312.0 (266.6–365.1) 51 279.1 (233.0–334.3) −32.9 (−10.5) 0.84 
 Lost 5–10% 37 302.1 (239.4–381.2) 31 266.3 (201.5–351.9) −35.8 (−11.9) 0.13 
 Lost ≥10% 32 291.1 (219.6–385.9) 32 226.1 (169.5–301.6) −65.0 (−22.3) 0.002 
PEDF 
 Lost ≤0% 33 10.32 (9.59–11.11) 30 11.95 (11.04–12.94) 1.63 (15.76) 
 Lost 0–5% 53 10.93 (10.37–11.51) 51 11.33 (10.79–11.89) 0.40 (3.67) 0.02 
 Lost 5–10% 37 10.30 (9.73–10.91) 31 10.64 (10.02–11.29) 0.34 (3.26) 0.01 
 Lost ≥10% 32 10.34 (9.68–11.05) 32 9.54 (8.94–10.19) −0.80 (−7.73) <0.001 

aA P value obtained from a GEE model comparing the change from baseline to 30 months in the (log-transformed) biomarkers between higher levels of weight loss percentage to lowest level (Loss ≤ 0%).

This is the first study to examine the associations between maintaining long-term weight loss in participants 18 months after completing a structured randomized controlled dietary weight loss and/or exercise intervention, on circulating levels of biomarkers of angiogenesis—VEGF and PEDF. At 30 months, participants randomized to any of the three intervention arms had statistically significant reductions in levels of VEGF between baseline and 30 months compared with controls. In contrast, there were no statistically significant changes in levels of PEDF between baseline-30 months in any randomization arm, compared with controls.

Like the parent study, weight loss appeared to account for the majority of the reductions in both PEDF and VEGF: only women who maintained ≥10% of baseline weight at 30 months had significantly greater reductions in VEGF levels compared with those who lost no weight or gained weight. Participants who maintained any level of weight loss at 30 months had significantly lower levels of PEDF compared with those who had either gained weight or had no weight change.

Studies such as the Diabetes Prevention Program, which examined long-term weight maintenance, have primarily focused on diabetes prevention and have reported that participants who undertook lifestyle changes to reduce caloric intake and increase physical activity maintained some weight loss for a number of years after participants completed the intervention. These long-term benefits also included a reduction in the cumulative incidence of diabetes, and lower fasting glucose levels, among others (13, 16–18).

Randomized controlled studies have demonstrated that weight loss is associated with beneficial changes in cancer-associated biomarkers including adipokines (19), sex-steroid hormones (20), and markers of inflammation (21), among others. However, to our knowledge, few studies have examined long-term weight loss maintenance and its association with changes in cancer-related biomarkers. In the present study, the long-term reduction in levels of VEGF and PEDF appears to be related to the extent to which weight loss persisted, with the greatest reductions seen in participants who maintained a ≥10% reduction of baseline weight.

VEGF and its receptors have been identified as one of the main molecular drivers of tumor angiogenesis (22), and the VEGF pathway is a primary target for antiangiogenic drugs due to its “ubiquitous and increased expression in most human cancers” (23, 24). Adipogenesis is dependent upon angiogenesis (25–27), and VEGF is elevated in the obese state (28, 29). Expansion of fat mass induces hypoxia, a driver of VEGF expression, via HIF-1 stabilization (30).

Weight loss in our studies is consistently associated with reductions in the anti-angiogenic PEDF. In mouse models, PEDF is a key inhibitor of stromal vasculature and epithelial tissue growth in mouse prostate and pancreas, and exogenous PEDF induced tumor epithelial apoptosis in vitro and limited in vivo tumor xenograft growth, triggering endothelial apoptosis (31). However, it also has a significant role as an adipokine that induces insulin resistance and inflammatory signaling in muscle and fat cells (32), is associated with obesity (33) and with increased risk of developing the metabolic syndrome (34).

In our prior studies of the impact of weight loss on reducing levels of circulating biomarkers of angiogenesis (10, 12), we discussed the potential utility of weight loss as a chemopreventive approach targeting both angiogenesis and inflammation in healthy individuals (35). Again, although it is currently impossible to ascertain whether reductions in circulating levels of angiogenic factors might inhibit tumor cell growth and progression by blocking the vascularization of indolent tumors, the long-term maintenance of reduced levels of VEGF and PEDF can only reflect a more beneficial angiogenic profile. A structured weight loss program may thus represent a safe and effective method of improving the long-term angiogenic profile in overweight individuals.

Limitations of our study include the relatively small numbers of women that returned for the 30-month follow-up visit, which limit the power to investigate effects in subgroups of data. However, these numbers are broadly similar to other studies where participants returned for follow-up approximately 2-years post enrollment, after the intervention was completed (17). In addition, there may have been bias in women who returned—women who were more successful at maintaining their weight might have been more likely to return to the clinic. We also investigated only two angiogenic biomarkers.

Strengths of our study include the well-characterized study population, a focus on postmenopausal women, a group at high risk for obesity-related breast cancer, and excellent participant adherence to interventions. In addition, our focus on long-term effects of weight loss and exercise biomarkers of angiogenesis, builds on our prior work in the parent trial.

In conclusion, our findings support that post-intervention, maintaining weight loss can achieve statistically significant reductions in biomarkers of angiogenesis, that can be maintained up to 18 months after a diet and/or exercise intervention was completed. These findings should be investigated further in other RCTs of weight loss with extended follow-up.

No potential conflicts of interest were disclosed.

Conception and design: C. Duggan, C.-Y. Wang, K.E.F. Schubert, A. McTiernan

Development of methodology: C. Duggan, K.E.F. Schubert

Acquisition of data (provided animals, acquired and managed patients, provided facilities, etc.): K.E.F. Schubert, A. McTiernan

Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): C. Duggan, J.de D. Tapsoba, C.-Y. Wang

Writing, review, and/or revision of the manuscript: C. Duggan, J.de D. Tapsoba, C.-Y. Wang, A. McTiernan

Study supervision: K.E.F. Schubert, A. McTiernan

This work was supported by grants from the National Cancer Institute at the National Institutes of Health (R01 CA105204 and U54 CA116847, to A. McTiernan), and grants from the Breast Cancer Research Foundation (BCRF-16-106 and BCRF-17-105, to A. McTiernan).

The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

1.
Lauby-Secretan
B
,
Scoccianti
C
,
Loomis
D
,
Grosse
Y
,
Bianchini
F
,
Straif
K
. 
Body fatness and cancer — viewpoint of the IARC working group
.
N Eng J Med
2016
;
375
:
794
8
.
2.
Renehan
AG
,
Tyson
M
,
Egger
M
,
Heller
RF
,
Zwahlen
M
. 
Body-mass index and incidence of cancer: a systematic review and meta-analysis of prospective observational studies
.
Lancet
2008
;
371
:
569
78
.
3.
Kyrgiou
M
,
Kalliala
I
,
Markozannes
G
,
Gunter
MJ
,
Paraskevaidis
E
,
Gabra
H
, et al
Adiposity and cancer at major anatomical sites: umbrella review of the literature
.
BMJ
2017
;
356
.
4.
Saltiel
AR
,
Olefsky
JM
. 
Inflammatory mechanisms linking obesity and metabolic disease
.
J Clin Invest
2017
;
127
:
1
4
.
5.
Lohmann
AE
,
Goodwin
PJ
,
Chlebowski
RT
,
Pan
K
,
Stambolic
V
,
Dowling
RJ
. 
Association of obesity-related metabolic disruptions with cancer risk and outcome
.
J Clin Oncol
2016
;
34
:
4249
55
.
6.
Bergers
G
,
Benjamin
LE
. 
Tumorigenesis and the angiogenic switch
.
Nat Rev Cancer
2003
;
3
:
401
10
.
7.
Lemoine
AY
,
Ledoux
S
,
Larger
E
. 
Adipose tissue angiogenesis in obesity
.
Thromb Haemost
2013
;
110
:
661
8
.
8.
Cao
Y
. 
Angiogenesis and vascular functions in modulation of obesity, adipose metabolism, and insulin sensitivity
.
Cell Metab
2013
;
18
:
478
89
.
9.
Rupnick
MA
,
Panigrahy
D
,
Zhang
CY
,
Dallabrida
SM
,
Lowell
BB
,
Langer
R
, et al
Adipose tissue mass can be regulated through the vasculature
.
Proc Natl Acad Sci USA
2002
;
99
:
10730
5
.
10.
Duggan
C
,
Xiao
L
,
Wang
CY
,
McTiernan
A
. 
Effect of a 12-month exercise intervention on serum biomarkers of angiogenesis in postmenopausal women: a randomized controlled trial
.
CEBP
2014
;
23
:
648
57
.
11.
Dawson
DW
,
Volpert
OV
,
Gillis
P
,
Crawford
SE
,
Xu
HJ
,
Benedict
W
, et al
Pigment epithelium-derived factor: a potent inhibitor of angiogenesis
.
Science
1999
;
285
:
245
8
.
12.
Duggan
C
,
Tapsoba Jde
D
,
Wang
CY
,
McTiernan
A
. 
Dietary weight loss and exercise effects on serum biomarkers of angiogenesis in overweight postmenopausal women: a randomized controlled trial
.
Cancer Res
2016
;
76
:
4226
35
.
13.
Knowler
WC
,
Fowler
SE
,
Hamman
RF
,
Christophi
CA
,
Hoffman
HJ
,
Brenneman
AT
, et al
10-year follow-up of diabetes incidence and weight loss in the Diabetes Prevention Program Outcomes Study
.
Lancet
2009
;
374
:
1677
86
.
14.
Foster-Schubert
KE
,
Alfano
CM
,
Duggan
CR
,
Xiao
L
,
Campbell
KL
,
Kong
A
, et al
Effect of diet and exercise, alone or combined, on weight and body composition in overweight-to-obese postmenopausal women
.
Obesity (Silver Spring)
2012
;
20
:
1628
38
.
15.
Pate
RR
,
Blair
SN
,
Durstine
JL
,
Eddy
DL
,
Hanson
P
,
Painter
P
, et al
Guidelines for exercise testing and prescription
.
Philadelphia, PA
:
Lea & Febiger
; 
1991
. p.
70
2
.
16.
Lindstrom
J
,
Ilanne-Parikka
P
,
Peltonen
M
,
Aunola
S
,
Eriksson
JG
,
Hemio
K
, et al
Sustained reduction in the incidence of type 2 diabetes by lifestyle intervention: follow-up of the finnish diabetes prevention study
.
Lancet
2006
;
368
:
1673
9
.
17.
Gilis-Januszewska
A
,
Lindstrom
J
,
Tuomilehto
J
,
Piwonska-Solska
B
,
Topor-Madry
R
,
Szybinski
Z
, et al
Sustained diabetes risk reduction after real life and primary health care setting implementation of the diabetes in Europe prevention using lifestyle, physical activity and nutritional intervention (DE-PLAN) project
.
BMC Public Health
2017
;
17
:
198
.
18.
Wing
RR
. 
Long-term effects of a lifestyle intervention on weight and cardiovascular risk factors in individuals with type 2 diabetes mellitus: four-year results of the Look AHEAD trial
.
Arch Intern Med
2010
;
170
:
1566
75
.
19.
Abbenhardt
C
,
McTiernan
A
,
Alfano
CM
,
Wener
MH
,
Campbell
KL
,
Duggan
C
, et al
Effects on adiponectin and leptin after individual and combined diet and exercise interventions in postmenopausal women
.
J Intern Med
2013
;
274
:
163
75
.
20.
Campbell
KL
,
Foster-Schubert
KE
,
Alfano
CM
,
Wang
CC
,
Wang
CY
,
Duggan
CR
, et al
Reduced-calorie dietary weight loss, exercise, and sex hormones in postmenopausal women: randomized controlled trial
.
J Clin Oncol
2012
;
30
:
2314
26
.
21.
Imayama
I
,
Ulrich
CM
,
Alfano
CM
,
Wang
C
,
Xiao
L
,
Wener
MH
, et al
Effects of a caloric restriction weight loss diet and exercise on inflammatory biomarkers in overweight/obese postmenopausal women: a randomized controlled trial
.
Cancer Research
2012
;
72
:
2314
26
.
22.
Kerbel
RS
. 
Tumor angiogenesis
.
N Eng J Med
2008
;
358
:
2039
49
.
23.
Jayson
GC
,
Kerbel
R
,
Ellis
LM
,
Harris
AL
. 
Antiangiogenic therapy in oncology: current status and future directions
.
Lancet
2016
;
388
:
518
29
.
24.
Ferrara
N
,
Kerbel
RS
. 
Angiogenesis as a therapeutic target
.
Nature
2005
;
438
:
967
74
.
25.
Christiaens
V
,
Lijnen
HR
. 
Angiogenesis and development of adipose tissue
.
Mol Cell Endocrinol
2010
;
318
:
2
9
.
26.
Voros
G
,
Maquoi
E
,
Demeulemeester
D
,
Clerx
N
,
Collen
D
,
Lijnen
HR
. 
Modulation of angiogenesis during adipose tissue development in murine models of obesity
.
Endocrinology
2005
;
146
:
4545
54
.
27.
Corvera
S
,
Gealekman
O
. 
Adipose tissue angiogenesis: impact on obesity and type-2 diabetes
.
Biochim Biophys Acta
2014
;
1842
:
463
72
.
28.
Doupis
J
,
Rahangdale
S
,
Gnardellis
C
,
Pena
SE
,
Malhotra
A
,
Veves
A
. 
Effects of diabetes and obesity on vascular reactivity, inflammatory cytokines, and growth factors
.
Obesity
2011
;
19
:
729
35
.
29.
Silha
JV
,
Krsek
M
,
Sucharda
P
,
Murphy
LJ
. 
Angiogenic factors are elevated in overweight and obese individuals
.
Int J Obes
2005
;
29
:
1308
14
.
30.
Early Breast Cancer Trialists' Collaborative Group Tamoxifen for early breast cancer: an overview of the randomised trials. Early Breast Cancer Trialists' Collaborative Group
.
Lancet
1998
;
351
:
1451
67
.
31.
Doll
JA
,
Stellmach
VM
,
Bouck
NP
,
Bergh
AR
,
Lee
C
,
Abramson
LP
, et al
Pigment epithelium-derived factor regulates the vasculature and mass of the prostate and pancreas
.
Nat Med
2003
;
9
:
774
80
.
32.
Famulla
S
,
Lamers
D
,
Hartwig
S
,
Passlack
W
,
Horrighs
A
,
Cramer
A
, et al
Pigment epithelium-derived factor (PEDF) is one of the most abundant proteins secreted by human adipocytes and induces insulin resistance and inflammatory signaling in muscle and fat cells
.
Int J Obes
2011
;
35
:
762
72
.
33.
Wang
P
,
Smit
E
,
Brouwers
MC
,
Goossens
GH
,
van der Kallen
CJ
,
van Greevenbroek
MM
, et al
Plasma pigment epithelium-derived factor is positively associated with obesity in Caucasian subjects, in particular with the visceral fat depot
.
Eur J Endocrinol
2008
;
159
:
713
71
.
34.
Chen
C
,
Tso
AW
,
Law
LS
,
Cheung
BM
,
Ong
KL
,
Wat
NM
, et al
Plasma level of pigment epithelium-derived factor is independently associated with the development of the metabolic syndrome in Chinese men: a 10-year prospective study
.
J Clin Endocrinol Metab
2010
;
95
:
5074
81
.
35.
Albini
A
,
Tosetti
F
,
Li
VW
,
Noonan
DM
,
Li
WW
. 
Cancer prevention by targeting angiogenesis
.
Nat Rev Clin Oncol
2012
;
9
:
498
509
.