Breast Cancer Res Treat DOI 10.1007/s10549-016-3688-0

CLINICAL TRIAL

The effect of resistance training on markers of immune function and inflammation in previously sedentary women recovering from breast cancer: a randomized controlled trial Amanda D. Hagstrom1,2 • Paul W. M. Marshall2 • Chris Lonsdale3 • Shona Papalia2 • Birinder S. Cheema2,4 • Catherine Toben5 • Bernhard T. Baune5 Maria A. Fiatarone Singh6,7 • Simon Green2,8

•

Received: 11 November 2015 / Accepted: 20 January 2016 Ó Springer Science+Business Media New York 2016

Abstract The purpose of this randomized controlled trial was to determine the effects of resistance training (RT) on markers of inflammation and immune function in breast cancer survivors. Thirty-nine breast cancer survivors were randomly assigned to a RT (n = 20) or control (n = 19) group. RT performed supervized exercise three times per week. Natural killer cell (NK) and natural killer T-cell (NKT) function, and markers of inflammation (serum TNFa, IL-6, IL-10, and CRP) were measured before and after training. Changes in NK and NKT cell function were analyzed using ANCOVA, with the change score the Trial registration: Clinical Trials (ANZCTR #: 12612000346875). URL: http://www.anzctr.org.au/trial_view.aspx?id=362296. The University of Western Sydney Human Research Ethics Committee has approved all research procedures (Approval Number: H9427).

dependent variable, and the baseline value of the same variable the covariate. Effect sizes (ES) were calculated via partial eta-squared. We found a significant reduction, and large associated ESs, in the RT group compared to the control group for change in NK cell expression of TNF-a (p = 0.005, ES = 0.21) and NKT cell expression of TNFa (p = 0.04, ES = 0.12). No differences were observed in any serum marker. Significant improvements in all measurements of strength were found in RT compared to control (p \ 0.001; large ESs ranging from 0.32 to 0.51). These data demonstrate that RT has a beneficial effect on the NK and NKT cell expression of TNF-a indicating that RT may be beneficial in improving the inflammatory profile in breast cancer survivors.

1

School of Science and Technology, University New England, Armidale, NSW, Australia

Paul W. M. Marshall [email protected]

2

School of Science and Health, Western Sydney University, Campbelltown, Australia

Chris Lonsdale [email protected]

3

Institute for Positive Psychology and Education, Australian Catholic University, Strathfield, NSW, Australia

Shona Papalia [email protected]

4

The National Institute of Complementary Medicine (NICM), Western Sydney University, Campbelltown, NSW, Australia

Birinder S. Cheema [email protected]

5

School of Medicine, University of Adelaide, Adelaide, Australia

Catherine Toben [email protected]

6

Bernhard T. Baune [email protected]

Exercise, Health and Performance Research Group and Sydney Medical School, University of Sydney, Sydney, Australia

7

Maria A. Fiatarone Singh [email protected]

Hebrew Senior-Life and Jean Mayer USDA Human Nutrition Center on Aging at Tufts University, Boston, MA, USA

8

School of Medicine, Western Sydney University, Campbelltown, Australia

& Amanda D. Hagstrom [email protected]

Simon Green [email protected]

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Keywords Resistance training
Immune function
Inflammation
Breast cancer survivors

Introduction Breast cancer is the most commonly diagnosed invasive cancer in women [1], with over 1.3 million women worldwide diagnosed with the disease each year [1]. Cancer and its treatments are associated with detrimental alterations in the immunological and inflammatory profile [2–4]. Natural Killer (NK) cells serve as the first line of defence against cancerous and virus-infected cells and tumors [5, 6]; and play a critical role in the prevention of cancer recurrence [7, 8]. Signaling mechanisms, including interferons, cytokines, and inhibitory and activating cell receptors (e.g., CD158b and CD107a), tightly regulate natural killer cell activity (NKCA) [6, 9]. Activating signaling mechanisms trigger binding of the NK cell to the target cell, which upon activation allows the NK cell to destroy the target cell by directed exocytosis of secretory lysosomes, such as granzyme B (GB) and perforin. The perforin and granzyme-induced apoptotic pathways are the main pathways used by cytotoxic cells to eliminate tumor cells [10]. NK cells also trigger adaptive immune system responses via secretion of many cytokines and chemokines [11]. These cytokines, which include IL-6, IL-10, and TNF-a [12], mediate the immune and inflammatory responses [13] and establish the cancer microenvironment. Natural Killer T-cells (NKT) are a type of T-lymphocyte [14] that share many common characteristics of NK cells including the ability to produce large amounts of cytokines [15], highlighting their importance in the response to cancer. Individuals diagnosed with cancer exhibit lower systemic NKCA than the general population [2–5, 16–18], with the level of immunosuppression most severe in advanced cases [17–22]. Contributing factors include the tumor itself, and the use of invasive and cytotoxic therapies, including surgery [23, 24], chemotherapy [24–26], and radiotherapy [17]. Impairment of NKCA renders these individuals more susceptible to infections and contributes to longer disease durations [18]. Elevated levels of TNF-a are present in many pre-cancerous and malignant diseases, including breast cancer, when compared to serum and tissue of healthy controls [12, 27]. In addition high TNF-a levels are correlated with node involvement and larger tumor sizes in breast cancer patients [28]. Chronic production of TNF-a is responsible for sustaining many of the processes required for the successful growth of tumors [29] including increased invasive capacity [30]. Further, multiple animal models have demonstrated increased cancer

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development and spread when the microenvironment of TNF-a has been increased [12]. Hence, reduction of the expression of this marker may be of paramount importance for breast cancer survivors. Aerobic exercise has been shown to modulate markers of immune function and inflammation in breast cancer survivors [31–35], although not all research has found positive adaptations in response to aerobic or mixed modality training in this cohort [33, 36, 37]. Studies in which chronic RT has been combined with immunological measurements in cancer survivors are sparse, with only one observational intervention study of 10 prostate cancer patients [38]. This research demonstrated an upregulation of IL-8, with no change in the remainder of the inflammatory and immunological markers. As such, little is currently known regarding the efficacy of resistance training (RT) to modulate immune function in this group. Evidence from other populations, particularly aging individuals, who also suffer from chronic low-grade inflammation [39], demonstrates the anti-inflammatory and beneficial immunological effect of RT [40–43]. While the mechanism eliciting the change in the inflammatory profile is currently unknown, it has been hypothesized that IL-6, released from contracting skeletal muscle [44] may cause inhibition of key pro-inflammatory cytokines such as TNF-a [44, 45]. Resting serum concentrations of CRP, IL-6, and IL18 have been shown to decrease in response to aerobic exercise, with no change exhibited in response to RT [46]. Conversely, TNF-a concentration has been reduced in response to both aerobic [46] and RT [43, 46], highlighting a potentially different mechanism of change for TNF-a which may have some association with muscle mass [46]. Rodent research has demonstrated that exercise increases the expression of TNF-a and its receptor TNF (R1) in muscle [47], leading to the hypothesis that the muscular hypertrophy elicited in response to RT in humans may allow for a greater uptake of TNF-a by the increased TNF-a (R1) receptor [46], and hence a reduction in the serum concentration of TNF-a. Furthermore, higher levels of TNF-a have been linked with reduced protein synthesis, muscle mass, and muscular strength [41, 48] in both cross-sectional [44] and training [37] studies. These findings suggest two possibilities: (1) exercise-induced reductions in circulating TNF-a may contribute to greater strength gains following RT via facilitation of protein synthesis/muscle hypertrophy, or (2) greater adaptations in muscle hypertrophy and strength may result in greater contraction-related IL-6 release and down-regulation of TNF-a activity [43]. In addition to the proposed immunological and anti-inflammatory effects, RT can counteract the effects of aging and chronic disease by eliciting a distinct spectrum of physiological adaptations that may not be achieved with other modes of exercise training. Documented benefits

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from RT in women recovering from breast cancer treatment include the improvement of upper-body muscular strength and endurance, range of motion [49–51], reductions in exacerbations and symptoms of lymphedema [52], improvements in self-esteem [53], bone mineral density [54, 55], and body composition. These benefits, combined with the hypothesized alteration in the immunological and inflammatory profile, provide a solid rationale for examining the efficacy of RT in this population. Therefore, the primary objective of this study was to investigate the effect of RT on the functions of NK and NKT cells. We hypothesized that RT would improve markers of NK and NKT cell function. A secondary objective of this study was to examine the effect of RT on markers of inflammation, and thus we hypothesized that RT training would decrease the expression of inflammatory markers on NK and NKT cells along with a reduction in serum markers of inflammation. Lastly, the third objective of this study was to explore the relationship between changes in strength and changes in inflammation and immune functioning. We hypothesized that improvements in strength would be related to improvements in the immune/inflammatory profile.

Methods This parallel-arm randomized controlled clinical trial compared the immunological and inflammatory outcomes of breast cancer patients assigned to a 16-week experimental treatment group (RT) with those assigned to a non-exercise usual care control group (allocation ratio 1:1). Outcome measures were collected at weeks 0 and 17. All testing and exercise training took place at Western Sydney University (WSU) exercise science laboratories between July 2012 and December 2013. The study was approved by WSU Human Research Ethics (Approval Number: H9427). The trial was registered with the Australian and New Zealand clinical trials registry (ANZCTR#: 12612000346875). Recruitment of participants, eligibility, exclusion criteria, and randomization are described elsewhere [56]. Key inclusion criteria were a history of histologically confirmed stage I to IIIA breast cancer with no evidence of recurrent disease; age 18–70 years; completed surgery, radiotherapy, and/or chemotherapy; and sedentary (\30 min of structured, continuous moderate-intensity exercise, 3 times per week, and no current resistance training). Survivors were recruited from the local area. Survivors were stratified based on age (\50 or [50 years) and current use of hormone therapy (Yes; No) and then randomized to a control or RT group. An investigator not involved in testing or delivery of the intervention prepared the randomization assignments which were delivered to participants in sealed envelopes upon completion of baseline testing.

Resistance training intervention The RT intervention is described elsewhere [56]. Briefly, RT was conducted three times per week for 16 weeks, sessions lasted 60 min, and focused on machine-based movements for the first 8 weeks followed by progression to predominantly free weights for the final 8 weeks. Each exercise was performed for 3 sets of 8–10 repetitions at 8RM intensity, equivalent to approximately 80 % of the 1 repetition maximum [57]. Program one exercises included leg extension, leg curl or Romanian deadlift, lat pulldown, machine bench press, seated row, back extension, prone hold, or sit ups. In addition, a structured warm-up included skill development of the deadlift and barbell squat ensuring competency in movement patterns for the commencement of program two. Program two exercises included barbell squat, deadlift, free-weight barbell bench press, leg press, barbell bent-over row, and assisted chin up. Exercises were substituted when deemed necessary due to musculoskeletal limitations. Blood markers (NK and NKT activity) Individuals involved in the analyses of blood markers were blinded to the treatment time point (pre or post) and group assignment. Fluorescence-activated cell sorting (FACS) was applied for the detection of immune cells and their associated functionality by surface and intracellular marker staining. Venous blood was collected in an overnight-fasted state. Methods have been previously described [58, 59]. Multiparametric flow cytometry was employed to analyze markers of NKCA. To distinguish among T-cells, NK cells, and NKT cells peripheral blood treated with FACS lysis buffer (BD) with or without FACS perm (BD) was stained with appropriately diluted fluorescently conjugated monoclonal antibodies of CD3 PerCpCy5.5 (BD Biosciences, Sydney, Australia), (BD), CD56 PE (BD), and CD45 V450 (BD) and acquired on the FACSCanto II (BD). Expression of functional markers of NKCA on NK and NKT cells were determined by staining aliquots of unstimulated peripheral blood treated with FACS lysis buffer (BD) with monoclonal antibodies (mAbs) for granzyme B PE (BD) and perforin PE (BD). NK and NKT cell intracellular cytokine production was measured by staining PMA/Ionomycin/ Brefeldin A (P/I/BA) overnight stimulated aliquots of peripheral blood treated with FACS lysis buffer (BD) and FACS perm (BD) with TNFa V450 (BD) and IFNg FITC (BD). Samples were analyzed using the FACS Diva (BD) software and gated using forward scatter (FSC) versus side scatter (SSC) to exclude platelets and debris. Gated viable cells were then ascertained to be of lymphoid origin by gating on CD45-positive cells. NK cells were identified as being CD56? CD3- low side scatter events while NKT

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cells were identified as being CD56? CD3? high side scatter events. A minimum of 5000 CD56? low SSC events were acquired in list-mode format for further analyses. Secondary gating on NK and NKT cells allowed for functional marker analyses. Statistical analyses of functional NKCA on NK and NKT cells were determined using FACS Diva (BD) software. FSC and SSC gating initially identified viable cells. Secondary gating on CD45? cells then identified cells of lymphoid origin. Creating a dot plot for CD3 and CD56 then identified NK and NKT cells where NK cells were defined as being CD56? CD3- and NKT cells were defined as being CD56? CD3? cells. Further gating for a specific functional marker identified NK and NKT functional marker-positive cells. The percentage of NK or NKT specific marker-positive cells was then reported for each sample using FACSDiva (BD) software before being exported into Excel and entered into SPSS. Secondary outcomes Inflammatory markers A complete blood count including a differential white blood cell count via standard procedures was conducted with coefficients of variation (CV) ranging between 0.7 and 8.3 % (level 2). C-Reactive Protein (CRP) was analyzed via an immunoturbidimetric assay on an Abbott C16000 analyzer at a DHM lab with a combined level 2 CV of 4.0 %. Serum analysis was carried out using a BD Biosciences ES CBA kit protocol for determining IL-6, IL-10, and TNF-a. Serum was aliquoted on the same day approximately 7 h later at the Baune Psychiatric Neuroscience Laboratory, University of Adelaide. Serum aliquots were stored at -20° C and transferred to -80° C storage for approximately 12 months until analysis. Serum cytokines IL-6, IL-10, and TNF-a levels were quantified using the BD Biosciences human enhanced sensitivity (ES) cytokine bead array (CBA) kit. Fresh aliquots of serum samples were run in duplicate. The minimum theoretical detection limit of these kits is 0.0684 pg/mL for IL-6, 0.0137 pg/mL for IL-10 and 0.0673 pg/mL for TNF-a. Body composition An assessor blinded to the group assignment of participants collected anthropometric data. The International Society for the Advancement of Kinanthropometry (ISAK) level 1 restricted profile was utilized [60]. Outcome measurements consisted of percentage body fat, calculated by the Yuhasz formula [61], and body mass index (BMI).

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Muscular strength Lower body muscular strength was evaluated using a one repetition maximum (1-RM) leg press protocol, while upper-body strength was assessed by measuring the force output (N) during a unilateral isometric chest press protocol as previously described [56]. The participant sat on an incline bench with the shoulder joint placed in 45° of abduction and forearm in 45° of pronation. Force was measured using an AST-250 kg force transducer (PT Global, Baulkham hills, Australia) connected to a chain and grip handle. Average CV’s were 5.2 % for the treated arm and 6.7 % for the non-treated arm.

Statistical analysis Sample size estimates were driven by the hypothesized change in functional markers of NKCA following aerobic exercise training on NKCA, as measured by percent lysis, in breast cancer survivors [31]. Setting the alpha at 0.05 and beta at 0.20, approximately 34 participants (17 per group) were required per treatment group to detect a large effect (ES = 1.0) as seen in that study. Recruitment was inflated to 40 to allow for a 15 % attrition rate. Primary analysis was via intention-to-treat and included all participants regardless of dropout or level of adherence. Missing data at week 17 were imputed using the last observation carried forward method. Baseline characteristics were compared between groups using independent t tests for continuous variables and v2 tests for categorical variables. Primary analysis compared changes in NK and NKT function using ANCOVA where the change score was the dependent variable, and the baseline value of the same variable was the covariate. A p value of \0.05 was considered indicative of statistical significance. Partial eta-squared was used to measure effect size where 0.01, 0.06, and 0.14 were considered small, medium, and large, respectively [62]. All variables were visually checked for skewness and kurtosis. Due to the large amount of ‘zero’ values, serum TNF-a was transformed into a categorical variable (zero/nonzero) and assessed via Chi square. CRP values of C15 mg/L were excluded from analysis as levels of that value are thought to be indicative of acute illness or infection [63, 64]. This led to the exclusion of one participant’s data. Differences in CRP, IL-6, and IL-10 were assessed via Friedman’s test due to non-normal distributions. Associations between continuous variables were analyzed using Pearson correlation coefficients (r).

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Results

Baseline characteristics

Flow of participants through trial

There were no differences in baseline characteristics between control and RT at the start of the trial with the exception of aromatase inhibitor (AI) use (control, n = 8; RT, n = 4, p = 0.02) (Table 1).

Fifty-nine women expressed interest in the study. Thirtynine women enrolled and were randomized to either the RT (n = 20), or the control group (n = 19). The primary reason for exclusion was due to the participant presently undergoing chemotherapy or radiotherapy treatments. Please refer to Fig. 1 for diagrammatic representation of participant flow through the trial.

Adherence and adverse events Adherence and adverse events are described elsewhere [56]. There were no adverse events, nor were there any new

Fig. 1 Participant flow through trial

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Breast Cancer Res Treat Table 1 Baseline characteristics (mean or n)

Overall

Control

Exercise

p

Age (year)

51.9 ± 8.8

52.7 ± 9.4

51.2 ± 8.5

0.61

Weight (kg)

76.2 ± 13.8

80.2 ± 16.8

72.4 ± 9.2

0.08

BMI (kg/m2)

28.7 ± 5.5

29.9 ± 6.46

27.6 ± 4.2

0.20

Percentage BF (%)

34.94 ± 8.87

37.4 ± 9.98

32.61 ± 7.16

0.09

TST (m) (range)

11.5 ± 13.2 (1–44)

13 ± 14.8 (1–44)

10.3 ± 11.7 (1–44)

0.53

Radiotherapy (n)

33

16

18

0.60

Chemotherapy (n)

33

16

17

0.95

AI (n)

12

8

4

0.14

SERMs (n)

19

11

4

0.02*

Lymphedema

4

2

2

0.68

BMI body mass index, BF body fat, TST time since treatment, AI aromatase inhibitors, SERMs selective estrogen receptor modulators * p \ 0.05

cases of lymphedema documented in this study. Four women had current lymphedema diagnosis (2 per group). Adherence rates averaged 85 ± 15 % in the exercise group. Dropout rate was 12.8 %.

Body composition

Change in markers of natural killer cell and natural killer T-cell function

Muscular strength

RT had a significantly lower expression of TNF-a on their NK cells at the end of the intervention (p = 0.005; ES = 0.21) (Table 2), and a significantly lower expression of TNF-a on their NKT cells at the end of the intervention (p = 0.04, ES = 0.12). There were no other significant differences between groups (Table 3). Change in serum cytokines No significant changes between groups were observed for any serum marker of inflammation (CRP p = 0.84; IL-6, p = 0.16; IL-10, p = 0.48; TNF-a, p = 0.12) (Table 4). Table 2 Changes in markers of body composition and natural killer cell function over 16 weeks of RT

No significant differences were observed for percentage body fat or body mass index (Table 2).

All markers of strength significantly improved over the course of the intervention when compared to the control group (p \ 0.001). Large ESs were observed for all strength outcomes, ranging between 0.32 and 0.51. Strength data have been previously reported in more detail [56]. Relationships between variables Significant correlations were observed between changes in lower body strength and TNF-a expression on NK (r = -0.69, p \ 0.001) (Control, r = -0.56, p \ 0.05; RT, r = -0.60, p = \ 0.05, Fig. 2) and NKT cells (r = -0.36, p = 0.04). No significant relationships were

RT group

Control group

Variable

Baseline 2

Week 17 change

Baseline

Week 17 change

p

ES

BMI (kg/m )

27.6 ± 4.2

0.15 ± 0.90

29.9 ± 6.46

0.18 ± 0.95

0.85

0.00

Body fat (%)

32.61 ± 7.16

-1.21 ± 3.19

37.4 ± 9.98

0.74 ± 3.57

0.11

0.07

10.4 ± 4.9 4.6 ± 5.2

-1.0 ± 3.3 3.3 ± 8.2

9.5 ± 6.2 5.2 ± 4.4

1.1 ± 3.7 1.1 ± 4.3

0.94 0.37

0.08 0.02

NK (%) NKCD158 (%) NKGB (%)

49.0 ± 21.8

-6.5 ± 18.2

48.8 ± 12.4

0.45

0.02

NKPerf (%)

21.0 ± 13.9

-6.1 ± 15.9

33.3 ± 14.7

2.5 ± 14.9

0.41

0.02

NKCD107a (%)

73.1 ± 15.9

-5.5 ± 11.6

71.0 ± 22.0

-3.0 ± 22.5

0.78

0.00

NKTNF-a (%) NKIFN-y´ (%)

13.8 ± 4.7

-1.4 ± 5.1

26.7 ± 15.0

0.4 ± 10.7

-3.3 ± 8.1

13.5 ± 4.0

4.3 ± 6.2

0.005*

0.21

22.8 ± 11.8

3.5 ± 17.6

0.85

0.00

Data presented are mean ± standard deviation BMI body mass index, NK natural killer cell, CD158 cluster of differentiation, GB granzyme B, Perf perforin, TNF-a, tumor necrosis factor alpha, IFN- y´ interferon gamma, RT resistance training, ES effect size * p \ 0.05

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Breast Cancer Res Treat Table 3 Changes in markers of natural killer T-cell function over 16 weeks of RT

RT group Variable NKT (%) NKTCD158 (%)

Control group Baseline 6.9 ± 5.1

Week 17 change -1.5 ± 4.4

53.6 ± 19.8

1.0 ± 2.7

Baseline 5.5 ± 3.6

Week 17 change

p

ES

-0.1 ± 3.5

0.55

0.01

0.4 ± 2.4

0.45

0.02

53.6 ± 20.3

NKTGB (%)

49.0 ± 21.8

-4.3 ± 14.4

38.7 ± 15.7

1.6 ± 12.2

0.38

0.02

NKTPerf (%)

21.0 ± 13.9

-1.1 ± 18.1

23.2 ± 15.8

-1.8 ± 14.6

0.94

0.00

NKTCD107a (%)

53.6 ± 19.8

-5.6 ± 14.5

53.6 ± 20.3

-5.5 ± 24.0

0.99

0.00

NKTTNF-a (%) NKTIFN-y´ (%)

9.9 ± 5.9

-3.0 ± 5.0

13.6 ± 7.0

0.1 ± 8.5

0.038*

0.12

61.4 ± 19.4

3.0 ± 16.5

0.77

0.00

69.3 ± 15.3

0.9 ± 13.4

Data presented are mean ± standard deviation NKT natural killer T-cell, CD158 cluster of differentiation, GB granzyme B, Perf perforin, TNF-a tumor necrosis factor alpha, IFN- y´ interferon gamma, RT resistance training, ES effect size * p \ 0.05

Table 4 Changes in CRP and serum cytokines RT group Variable CRP (mg/L)

Control group Baseline 1.00 (0.80–3.75)

Week 17 change

Baseline

-0.50 (-0.35–0.08)

8.75 (4.88–10.75)

Serum IL-6 (fg/mL) Serum IL-10 (fg/mL)

954.50 (653.71–3172.14) 86.69 (20.30–169.26)

-236.26 (-610.94–34.15) 11.35 (-24.65–37.66)

1267.67 (584.41–3386.67) 103.97 (45.04–349.81)

Serum TNF-a (fg/mL)

0.00 (0.00–156.81)

0.00 (0.00–60.74)

0.00 (0.00–255.11)

Week 17 change 0.00 (-0.10–1.10) 0.00 (-390.00–413.12) 0.00 (-11.89–61.62) 0.00 (-26.46–0.00)

Data are presented as Median and IQR CRP C-reactive protein, IL interleukin, TNF-a tumor necrosis factor alpha, RT resistance training

observed between the muscular strength of the upper-body treated limb and NK (r = -0.32, p = 0.05) or NKT (r = -0.11, p = 0.50) expression of TNF-a, or with the non-treated limb (NK, r = -0.29, p = 0.07; NKT r = -0.04, p = 0.8). As change in strength was related to the change in TNF-a expression on NK and NKT cells, we added lower body strength change as an additional covariate to the ANCOVA model for these two variables to see whether it attenuated the effect of assignment to RT group. It diminished the RT group effect into non-significance (p = 0.946) suggesting that change in strength mediated the RT benefits on TNF expression.

Discussion This is the first study examining the effects of resistance training on markers of inflammation and immune function in a cohort of breast cancer survivors. In support of our hypothesis, RT significantly reduced the expression of TNF-a on NK and NKT cells, with these effects correlated with increases in lower body muscular strength. This is the first study to demonstrate the beneficial effects of resistance training on the inflammatory profile of breast cancer

survivors and suggests that the effect is linked to increases in muscular strength. These data are in support of previous research showing positive immunological effects following aerobic training in this population [31, 35, 63]. The mechanism eliciting the reduction of TNF-a expression on NK and NKT cells is currently unknown. A potential explanation regarding reduction of TNF-a expression on NK/NKT might relate to lactate. Lactate is increased in response to acute RT [65], with cAMP in turn upregulated by the production of lactate [66, 67]. Expression of TNF-a is suppressed by the upregulation of cAMP [68], therefore causing the subsequent reduction in the expression of TNF-a on NK and NKT cells. Additionally, higher levels of circulating cytokines are negatively related to the levels of protein synthesis in skeletal muscle in aging adults [41, 69], suggesting that inflammation can impair anabolic adaptations in muscle. The observed relationship between the reduction in TNF-a and improved strength in previous research in elderly populations [43], and the current study, provide support for this hypothesis. It is possible that increases in protein synthesis are also related to strength gains, even before alterations in muscle cross-sectional area have become apparent.

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Fig. 2 A comparison between groups of the relationship between changes in leg strength and changes in NK cell expression of TNF-a

This is the first study to measure markers of mononuclear cell cytotoxicity in breast cancer survivors in response to resistance training. We found no change in either GB or perforin expression on NK or NKT cells. This was surprising given that previous research has shown that individuals who engage in higher levels of exercise have an increased expression of GB [70] and perforin [70, 71]. Our study found that at baseline only 49 % of participant NK cells expressed GB and 40 % expressed perforin. Levels of expression in our study are markedly different from previous research demonstrating 76–98 % expression in pancreatic, gastric, and colorectal cancer patients [72], which were similar to levels found in healthy controls [71, 73– 75]. Differences in baseline results in our study compared to the previous research can possibly be explained by treatment differences. The sample of patients in the previous research were current sufferers of cancer who had not been through surgery, chemotherapy, or radiotherapy yet [72]. In comparison, the cohort of women presented in our study had completed treatment an average of 11.5 months prior to enrollment in this study. As stated previously, it is well documented that surgery, chemotherapy, and

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radiotherapy have negative effects on immune functioning [17, 23, 25, 26]. The lack of additional trials utilizing this methodology makes a definitive conclusion impossible. However, these findings suggest RT does not change expression of GB or perforin on NK or NKT cells in treated cancer patients. The findings do reaffirm the notion that cancer treatments have negative effects on immune system functioning as demonstrated by the markedly lower expression of perforin and GB when compared to previous data. The RT intervention in this study elicited significant strength gains. The average improvement in upper-body strength was approximately 20 % with lower body strength improving an average of 34 %. These results are comparable to previous randomized controlled trial RT interventions in this cohort that have elicited strength gains averaging 23 % in the upper body and 28 % in the lower body [54, 76–80]. While the strength gains observed in this study were of similar magnitude to those previously reported, they were achieved in a significantly lesser time period of 16 weeks compared to an average of just less than 12 months [54, 76–80]. Intensity is known to be a

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significant factor in muscular strength adaptation to RT, with multiple studies demonstrating superior strength gains when loads of approximately 80 % have been used in comparison to lighter loads [81]. As our results show that it seems the magnitude of strength gain is related to the magnitude of improvement in the inflammatory profile, if improved immunological and inflammatory profile is sought, then exercise prescription should ensure that adequate intensity is prescribed. Similar to most training studies, our study had both responders and non-responders in terms of the degree of muscular strength adaptation. Future research should attempt to elucidate the potential explanations for this variability, including the individual genetic profile and hormonal adaptations. An important consideration when interpreting the findings regarding the significant group difference in NK expression of TNF-a is that this effect was related to both a decrease in the RT group, and an increase in the control group. It must be acknowledged that there is the possibility that this increased inflammation was due to a factor unrelated to cancer or its treatments. However, there is a possibility that the delayed inflammatory response may have been a continued progression of low-level chronic inflation following treatment, and that perhaps RT prevented this rise in the experimental group. A limitation of the current study was the lack of measurement of muscle TNF-a, muscle mass/area, and muscle protein synthesis. However, due to the invasive measurement technique, and associated financial costs, we were unable to perform these measurements. Another limitation of this study was the measure of serum TNF-a. In the current study, over 50 % of the cohort had serum TNF-a levels that were undetectable, similar to findings in prostate cancer patients, where serum TNF-a could not be detected in 87 out of 110 samples [82]. Although the cohort in this study was not classified as a healthy population, it appears for this marker of inflammation they were similar to healthy populations [83, 84]. Serum TNF-a has an extremely short half-life in the blood [85, 86], compounding the difficulty in measurement suggesting that perhaps this marker is not an appropriate indicator of the levels of systemic inflammation in this cohort. Studies utilizing serum markers following exercise interventions in cancer survivors have frequently found no adaptation in these markers [38, 87, 88], in comparison, studies that have demonstrated a positive immunological adaptation following exercise [31, 34, 35] have utilized different methodologies such as the measurement of NKCA. This suggests that more sensitive measurement techniques may be required to overcome the present heterogeneity in the field of exercise immunology and cancer. In addition, we cannot rule out the possibility that the women who gained the most strength in our study had

differences in the intensity of contractions, anabolic adaptations to those contractions, anabolic hormone profiles, or neuromuscular recruitment compared to those exhibiting smaller strength gains. It is possible that these anabolic adaptations resulted in the down-regulation of TNF-a expression, rather than the other way around. Future research exploring the potential association between neural recruitment, muscle hypertrophy, protein synthesis and altered immune function, and the directionality of these relationships, is warranted. Studies utilizing skeletal muscle biopsies would be beneficial. Future research should also focus on NKT cell response to exercise interventions given the beneficial effect of exercise on this cell. Longterm studies would also help to clarify whether the alterations in inflammation correspond to any improvements in long-term health outcomes including cancer recurrence and survival, as at present, the clinical relevance of the reduction in mononuclear TNF-a expression is unknown. Although research measuring TNF-a concentration in its varying forms is still limited in this population, the link between RT and modulation of various forms of TNF-a appears promising. Findings from this study of reduced expression of TNF-a on NK and NKT cells, and the significant large correlation between reduced inflammation and improved lower body strength are consistent with the previously identified relationship between muscle mass and TNF-a. In summary, this randomized controlled trial demonstrated that a 16-week RT program reduced the NK and NKT cell expression of TNF-a, potentially improving the inflammatory profile in a cohort of breast cancer survivors. Acknowledgments This study was supported by a grant from Western Sydney University, Australia. Conflict of interest conflicts of interest.

All authors acknowledge that there are no

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