Influence of pre-operative oral carbohydrate loading vs. standard fasting procedure on tumor proliferation and clinical outcome in breast cancer patients — a randomized trial

The influence of carbohydrates in breast cancer is conflicting. Objective To determine whether preoperative per-oral carbohydrate load influences proliferation in breast tumors. mIE/L to 33.27 mIE/L), insulin c-peptide (+ 1.39 nM, 95% CI, 1.03 nM to 1.77 nM), but reduced IGFBP3 levels (– 0.26 nM; 95% CI, – 0.46 nM to – 0.051 nM). CH-Intervention ER-positive patients had poorer relapse free survival (73%) than the fasting group (100%) (p=0.012; HR= 9.3 (95%CI, 1.1 to 77.7)). In the ER-positive patients, only tumor size (p=0.021; HR=6.07, 95%CI=1.31 to 28.03) and CH-or-fasting grouping (p=0.040; HR=9.30, 95% CI=1.11 to 77.82) had independent prognostic value. The adverse clinical outcome of carbohydrate loading occurred only in T2 patients with Relapse Free Survival of 100% in the fasting group vs. 33% in the CH-group (p=0.015; HR= inf). The CH-group reported less pain on day 5 and 6 compared to the control group (p<0.001) but showed otherwise no factors related to well-being. Only applicable to ER-positive breast cancer patients with T2-tumors.


Limitation
Only applicable to ER-positive breast cancer patients with T2-tumors.

Conclusions
Preoperative carbohydrate load increases proliferation and PR-negativity in ER-positive patients and worsens clinical outcome in ER-positive T2-patients.
Keywords: breast cancer, carbohydrate load, proliferation, insulin, insulin c-peptide, IGF-1, IGFBP3, tumor size, relapse free survival, breast cancer specific survival Background Breast cancer is the most frequent malignancy among women worldwide [1] representing 12% of all new cancer cases, and 25 % of all cancers in women [2,3]. In Norway, its incidence has doubled during the last 50 years. Lifetime risk for a Norwegian woman of getting the disease is 10-12 % [4]. Worldwide, 570,000 women died of breast cancer in 2015, which is 15% of all cancer deaths among women [3]. Approximately 75% of all new breast cancers comprise the luminal breast cancer subtypes which express estrogen receptor (ER) and/or progesterone receptor (PR) [5]. The etiological factors of breast cancer comprise genetic, hormonal, environmental and lifestyle related elements [6].
Western lifestyle aspects risk factors including lack of physical exercise, overweight, certain hormonal and dietary factors, and diabetes mellitus type 2 have recently gained increased attention [2].
The effect of carbohydrates consumption on breast cancer incidence and outcome is probably mediated through three parallel routes. Firstly, through stimulation of the Insulin involved [11]. Thirdly, alimentary glucose may also affect the cancer cells directly through the Warburg effect, which is an expedient switch that changes cellular energy metabolism from oxidative mitochondrial ATP-production to cytoplasmic aerobic glycolysis [12]. This transition enables the proliferative cancer cells to produce both ATP for energy and ribose for DNA synthesis [13].
In human breast cancer patients, there is a lack of studies on the relationship between carbohydrate/glucose content in food and quantitative insulin characteristics. Insulin is a growth factor which increases proliferation and decreases apoptosis, and elevated levels of insulin are associated with different cancers, including breast cancer [14]. Also, in breast cancer patients without diabetes, high insulin levels are associated with a poor prognosis [15]. Insulin receptors have been detected on breast cancer cells [16] although there is conflicting evidence on whether insulin directly regulates cancer proliferation, and how fast such an effect will occur. Also, there is a research deficit on the influence of carbohydrates on clinical outcome or prognostic endpoint biomarkers such as proliferation. Proliferation is often measured by the Mitotic Activity Index (MAI), Phosphohistone -H3 (PPH3) and Ki-67. [17,18] MAI and PPH3 estimate the number of cells in the mitosis phase (M-phase) and G 2 M-phase respectively, while Ki-67 detects all cells outside the G 0 -phase. Notably, insulin influences the cell cycle kinetics by more rapid transit through the G 1 -phase in ER -positive cells [7].
A meta-analysis has shown that in patients with abdominal surgery, administration of two per-oral carbohydrates loads administered 12 -18 hours and 2-4 hours before elective surgery reduces postoperative insulin resistance and leads to enhanced recovery after surgery (ERAS) [19]. During surgery, however, breast cancer cells are known to be massively pushed into the circulation [20]. Moreover, due to the pre-operative oral carbohydrate load used in ERAS-protocols, these cells may have a much better chance of survival and of forming viable metastatic foci [21,22]. Pre-operative oral hyperglycemic loading might bring breast cancer cells into a favorable state to escape, divide, thrive and survive during surgery, which may in turn lead to an inferior long-term prognosis for breast cancer patients [23]. It is therefore of great importance to gain more insight into the effects of administration in breast cancer regarding insulin-related characteristics, proliferation and clinical outcome.
The cell cycle in breast cancer is regarded as fast enough to be influenced by the two abovementioned ERAS-protocolled pre-operative oral carbohydrate loads [24,25]. We chose to use MAI as our primary endpoint for proliferation. Our hypotheses were: 1. An ERAS-protocol comprising two oral carbohydrate loads will improve the post-surgical recovery of breast cancer patients; 2. The oral carbohydrate load will stimulate cellular signal systems and increase proliferation as measured by MAI; 3. A Pre-operative carbohydrate load will lead to an adverse prognosis in breast cancer patients. A subgroup analysis of ER-positive patients was planned before the study was started.
Thus, the aim of this study was to investigate whether a pre-operative carbohydrate load according to a standard ERAS-protocol influences tumor proliferation, postsurgical recovery and/or clinical outcome.

Methods
This population-based cohort of operable breast cancer patients was randomized into an intervention group receiving preoperative per-oral carbohydrate loading or to a control group comprising the standard fasting preoperative protocol with unlimited drink of water.
The investigation was an open labelled study for the patient and the breast surgeon.
However, all researchers at the department of pathology and the hormone laboratory were blinded for the intervention. to participate in the study and were randomized (Fig.1). The last follow up date was 28.06.2017. A larger proportion of drop outs in the intervention group for various random reasons created an imbalance in numbers of patients between the allocation groups ( Fig.  1).

Randomization and intervention
The randomization took place after the patients had signed the written consent to participate in the study. The randomization procedure was organized as an in-house procedure with concealed envelopes generated and distributed in two boxes by the study nurse. The allocation sequence was performed by the trial administration committee. The sequence was balanced according to age, which was performed by choosing between two boxes; one for age <55 (i.e. possible and certain premenopausal) and one for age ≥ 55 (i.e. most probably postmenopausal), each with a 1:1 block randomization regarding the carbohydrate (intervention) and fasting (control) groups in each box. The surgeon in the out-patient clinic enrolled consecutively operable breast cancer patients, who agreed to participate in the trial.

Intervention
Patients who were randomized to preoperative carbohydrates drank 200 ml pre-Op TM (Nutricia, Netherlands) containing 12 % carbohydrates, 2 % glucose, and 10 % polysaccharides the evening before (i.e. 18 hours before surgery) and in the morning on the day of operation (i.e. 2-4 hours before surgery). Each patient was asked before surgery if they had been able to finish the carbohydrate drink or if they were fasting according to the randomization. The control group received standard fasting procedure with free intake of tap water.

Blinding
The investigation was an open labelled randomized study for the patient and the breast surgeon as carbohydrates are very sweet compared to tap water and thus impossible to blind. However, all laboratory measurements and assessments performed at the department of pathology and the Hormone laboratory were performed blinded to intervention status.

Primary treatment
The primary surgery was performed according to the recommendations of the Norwegian Breast Cancer Group (NBCG) [4] with either breast conserving treatment (BCT) or mastectomy, and sentinel node (SN) diagnostic or axillary lymph node clearance of level I and II. Adjuvant chemotherapy given was also based on the national NBCG guidelines. [4] Notably, there were no differences between the two allocation groups regarding the type of primary treatment received (Table 1).

Safety issues
The patients were hospitalized for 1-2 days after surgery. Any complications, such as hemorrhage, infection and others were recorded in the Case Report Forms. No patients died or experienced any serious complications from the received pre-operative treatment.

Blood sampling for serum analyses
Five blood samples were obtained from the participants; 1. At the time of diagnosis, 2. On admission (the day before surgery), 3. Pre-operatively before surgery, after the second pre-Op™ carbohydrate dose, 4. The day after surgery and 5. Four weeks post-surgery.
Immediately after being drawn, the blood samples were put in ice water for transport to the in-house medical laboratory. The samples were spun, and the serum frozen for transport to the Hormone Laboratory, Haukeland University Hospital, Bergen, Norway.

Histology
The tumor size was macroscopically measured in the fresh specimens following excision and cut in slices of 0.5 cm. The axillary lymph nodes from sentinel node biopsy or axillary fat from axillary dissection were first examined macroscopically by a pathologist. Then, all detectable lymph nodes were prepared for histological examination. The median number of identified lymph nodes was 3 (range 1-21, no lymph nodes detected in 2 patients). All tissues were fixed in buffered 4 % formaldehyde and embedded in paraffin. Histological sections (4 µm) were made and stained with hematoxylin-eosin-saffron (HES). Histological type and grade were assessed by two pathologists (EG and JPAB) according to the World Health Organization criteria [26].
Antigen retrieval and IHC techniques were based on DAKO technology as described previously [27]. Formalin fixed paraffin-embedded (FFPE) sections, 4 µm thick, serially sectioned following HES sections, were mounted onto siliconized slides (#S3002, DAKO, Glostrup, Denmark). Antigen retrieval was performed with a highly stabilized retrieval system (ImmunoPrep; Instrumec, Oslo, Norway) using 10 mM Tris/1 mM EDTA (pH 9.0) as the retrieval buffer. Sections were heated for 3 min at 110 o C followed by 10 min at 95 o C then cooled to 20 o C. ER (clone SP1, Neomarkers/LabVision, Fremont, CA, USA) was used at a dilution 1:400. PR (clone SP2, Neomarkers/LabVision) was used at a dilution of 1:1,000. Areas with necrosis or inflammation were avoided. This procedure was done as a routine diagnostic procedure, but in addition controlled by EJ as described elsewhere. [28] The PPH3 index was assessed as described elsewhere [29]. PPH3 expression was evaluated using the fully automated VIS analysis system (Visiopharm, Hørsholm, Denmark), using the same image processing principles described previously [27]. ER was scored as positive when nuclear staining was present in >1 % of the cancer cells and scored negative when <1 % of the cells were stained. PR was scored as positive when nuclear staining was present in >10 %, borderline between 1-10 % and negative when <1 % of the epithelial breast cancer cells showed nuclear staining. HER2 was scored according to the DAKO Hercep-Test scoring protocol. All 2+ and 3+ cases were regarded as positive. All sections were independently scored by two of the authors (BH and EJ).

Main outcome measures
The main primary outcome measure was the difference in proliferation (measured by MAI) in the primary tumor between the study groups. The secondary outcome measures were differences in insulin related characteristics i.e. Insulin/c-peptide, IGF1 and IGFBP3 between the intervention group and control group. Moreover, Patient Reported Outcome Measures (PROM) on the following complaints and symptoms: nausea, pain, mobilization, dizziness, insecureness and bleeding were also regarded as secondary outcomes. We applied an 'in-house' questionnaire where the patients were asked to score the six variables above on a 4-step Likert scale where 1= 'no', 2='little', 3= 'moderate' and 4 ='very much' on the 1 st ,2 nd ,3 rd ,4 th ,5 th ,6 th and the 7 th day after the operation.
For long term outcome measures we looked at relapse free survival (RFS) defined as the time from surgery until the time the patient was diagnosed with a relapse in any location i.e. locoregional, systemic and contralateral. Breast cancer specific survival (BCSS) was defined as the time from surgery until death due to breast cancer. For both the primary and secondary outcomes a subgroup analysis in the ER-positive (luminal) breast cancer subtype was planned.

Statistical Analysis
Power calculation was performed on the basis of the primary endpoint. We anticipated a 20% increment in MAI in the intervention group compared to the control group. Based on the mean value of MAI in patients belonging to the catchment area of Stavanger University Hospital, [33, 34] and the reproducibility of the method to assess MAI, a total of 30 patients in each study group (i.e. 60 patients) was necessary to achieve 80% power.
We decided to randomize 80 patients to allow for a 10-15 % drop-out rate.
As ER-positive breast cancer patients comprise approximately 75% of all breast cancers, there should be a reasonable number of patients to perform a subgroup analysis of the luminal breast cancers. Statistical analysis was performed with SPSS statistical software v.22 (SPSS, inc., Chicago, II, USA). T-tests or Fishers exact test or chi square tests, as appropriate, were used to test for differences in the clinical variables between the intervention groups. Kaplan-Meier survival curves were constructed and survival differences between groups were tested by the log-rank test. The relative importance of potential prognostic variables was tested using Cox-proportional hazard analysis. In multivariable Cox regression a backward stepwise model selection procedure was used, where all covariates deemed clinically relevant were included in the initial model. The proportion of patients reporting at least mild problems on each of the items on the PROM questionnaire (pain, nausea, mobilization, dizziness, insecureness and bleeding) on each day during the first seven postoperative days were analyzed using a mixed effects logistic regression model. Using this model, we tested for differences between the intervention and control groups. If a significant difference was found, a post hoc analysis was done by chi square tests for each of the days. We did not apply any correction for multiple testing due to the pilot and exploratory nature of the study. A two-tailed P value of 0.05 was considered as cut-off value to define the statistical significance.

Manuscript reporting
We ensure that the manuscript reporting adheres to CONSORT guidelines for reporting clinical trials, including sticking to the CONSORT check list.

Results
The various characteristics of the two allocation groups are shown in Table 1. There were 50 patients with ER-positive tumors and 11 patients with ER-negative tumors. Of the latter, 8 were HER2 negative (ER-, HER2-) and 4 were triple negative (ER-, PR-, HER2-) based on IHC-profiling. Notably, there were no differences in the distribution of the basic covariates between the carbohydrate-intervention group and the fasting group (Table 1).

Proliferation markers
In the total study cohort, none of the continuous variables of MAI, Ki67 and PPH3 were different between the carbohydrate and fasting groups. However, when applying the robust and well-established prognostic threshold for MAI (<10/≥10), among the ERpositive patients (n=50) there were significantly more patients with high proliferation (MAI ≥ 10) in the carbohydrate intervention (70%) than in the fasting group (30%) (p=0.038).
The same trend (58% in carbohydrate intervention) compared to the control group (42%, fasting group) was found (p=0.083) when all tumors were considered.

Progesterone Receptor
In the carbohydrate group, there were significantly more patients with PR-negative tumors (50%) than PR-positive tumors (20%) compared to the fasting group. (p=0.014), independent of Luminal A/B status.

Serum glucose and insulin responses.
Response to the preoperative carbohydrate loading was assessed by the difference between the pre-operative serum values and the values taken at admission (i.e. serum levels after carbohydrate loading minus fasting baseline values in both groups) ( Table 4).
As expected, the intervention group had a significant increment in both S-Insulin  Table 4). There were no changes in S-glucose and S-IGF-1 values within or between the two study groups (Table 4).

Quality of Life data
In the carbohydrate intervention group, fewer patients reported mild and moderate pain during the first seven postoperative days than in the fasting group (p<0.001) which in post hoc analysis was significant on postoperative day 5 (28% vs 47%; p=0.038) and day 6 (28% vs 50%; p < 0.001). Otherwise, there were no significant differences between the two groups regarding the other items from the PROM-questionnaire (nausea, mobilization, dizziness, insecureness and bleeding) (data not shown).

Long term clinical outcome
Median follow-up time for RFS was 88 months (range 33 to 97) and for BCSS the median was 88 months (range 45 to 97). There were 8 patients who experienced a relapse; locoregional (n=1), systemic (n=6) and contralateral (n=1) and 5 patients died of breast cancer.

Relapse free survival
Randomization to intervention with preoperative carbohydrates was found to have a weak and borderline influence on RFS when analyzed in the whole study cohort (Table 2).
However, in the ER positive patients who received carbohydrates preoperatively a reduced RFS of 71% compared to 97% in the control group (p= 0.012, HR=9.3, CI=1.1 to 77.7; Table 2 and Fig.2A) was observed. The covariates tumor diameter between 2 and 5 cm (T2), and the proliferation marker Ki67 (both ≥15% and ≥ 30%) had a significant negative influence on RFS in both the whole group and in the ER-positive cohort (

Breast Cancer Specific Survival
In the unadjusted analysis of BCSS, intervention with carbohydrates showed a significantly inferior BCSS in ER-positive patients compared to the control group (Table 3; Fig. 3A). In ER-positive T2 tumors the carbohydrate intervention group had the worst BCSS of 30 % compared to 100% in the control fasting group (p=0.031, HR=infinite, due to zero relapses in one of the two groups) (Fig. 3B).
In addition, tumor size, nodal status and Ki67-30% provided significant prognostic information in the unadjusted analysis (Table 3.) In the multivariable analysis, only Ki67-30 remained in the final model. In general, the small number of patients and endpoints hampered a robust multivariable analysis.

Adverse events
No adverse events were seen in neither of the two study arms. Especially, no signs of pathologic elevated fasting blood sugar levels (i.e. > 6 mmol/L) was seen in the two groups. Furthermore, in the carbohydrate arm no signs of occult diabetes mellitus was seen, i.e. blood sugar levels > 10 mmol/L after carbohydrate loading.

Discussion
Glucose has been correlated with cancer for nearly one century. Warburg (1925)  Luminal cancers have, on average, a lower proliferation rate than ER-negative and triple negative cancers [37]. As such, the proliferation increasing effect of carbohydrate loading in luminal cancers understandably leads to a higher percental increase of patients crossing the prognostically essential MAI-10 threshold. Most ER-/triple negative breast cancer patients already have a MAI greatly exceeding 10. Therefore, carbohydrate loading will probably not increase proliferation clinically significantly as they have an 'a priori' high risk for distant metastases [38]. In addition, the Luminal A patients exposed to  [54].
The observed inferior prognosis of patients who received carbohydrate load and comprise T2 tumors calls for some reflection. Patients with higher levels of insulin c-peptide may be more responsive not only to the carbohydrate loading they received in the present study, but also to carbohydrates in every meal they consume during the period of adjuvant therapies, and hereafter. These patients may comprise a subclinical insulin resistant state, which is known to be a risk factor for relapsing from breast cancer in non-diabetic women [55]. Thus, it may be that tumor size combined with insulin c-peptide status may predict an increased effect of adjuvant metformin or other insulin lowering drugs in the adjuvant treatment of breast cancer patients. Metformin attenuates the systemic biological effect of IR /IGF on tumor promoting signaling by improving insulin sensitivity and suppressing liver glucose output, which leads to reduced levels of systemic circulating insulin [14].
This will further mitigate paracrine signaling, overcome endocrine resistance [51, 56] and improve prognosis in breast cancer [57][58][59][60]. The present study supports the hypothesis that adjuvant metformin or other insulin-lowering therapeutic interactions may have their largest effect in breast cancer patients with ER-positive T2 tumors. In addition, the greatly increased glucose consumption of cancer cells measured by positron emission tomography (PET) with 18 F-deoxy-glucose (FDG) as tracer [61] identifies patients with an inferior clinical outcome [62]. This may also serve as a promising proxy for becoming an insulin / metformin responder.
The effect of the carbohydrate loading on well-being in the present study had a very limite clinical subjective effect (i.e., only reduced pain on the 5 th and 6 th day after surgery). Of note, no difference in mobilization and hospitalization was found. This is most probably due to the short duration of the operation and the extraperitoneal nature of the surgical procedure in breast cancer patients. Recently, the health authorities in Norway have introduced new national guidelines for a more standardized trajectory in breast cancer [63]. Also, day-care surgery comprising anesthesiologic medication with a short half-life leading to less side effects for the patients and optimization of pain relief regimen has been introduced since this trial was performed. Thus, the present study does not support introducing carbohydrate loading in this patient group, especially due to the worrying inferior relapse free survival observed in the carbohydrate intervention group.
The strengths of the above described biological model are, that it allows for assessing changes in the breast tumor after manipulating the metabolic environment preoperatively, and thus combines assessment of primary tumor characteristics in concert with systemic metabolic changes. Also, the stable nature of insulin c-peptide has compensated for the more short-lived insulin and IGF. This may explain the more robust nature of insulin cpeptide in the various analyses.

Ethics approval and consent to participate
The randomized trial was approved by the Regional Ethics Committee (Accession number 2015/1445), NSD (Norwegian Centre for Research data) (# 20984) and "The Norwegian Biobank registry (# 2239). An informed consent form was signed by each patient. The trial was retrospectively registered in Clinicaltrials.gov (NCT03886389). The reason for delayed registration was that we were not aware of the obligation to register prospectively at the time.

Consent for publication
Not applicable

Availability of data and material
The data that support the findings of this study are available from Stavanger Breast Cancer Research Group, but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are however available from the authors upon reasonable request and with permission from Stavanger Breast Cancer Research Group.

Manuscript reporting
We ensure that the manuscript reporting adheres to CONSORT guidelines for reporting clinical trials, including filling out the CONSORT check list.

Competing interests
The authors declare that they have no competing interests