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Rapid Communication

ANTHROPOMETRIC, METABOLIC AND MOLECULAR DETERMINANTS OF HUMAN EPIDERMAL

GROWTH FACTOR RECEPTOR 2 EXPRESSION IN LUMINAL B BREAST CANCER†

Patrizia Vici1, Anna Crispo

2, *Antonio Giordano

3-4, Luigi Di Lauro

1, Francesca Sperati

5, Irene

Terrenato5, Laura Pizzuti

1, Domenico Sergi

1, Marcella Mottolese

6, Claudio Botti

7, Maria Grimaldi

2,

Immacolata Capasso8, Giuseppe D’Aiuto

8, Maurizio Di Bonito

9, Flaviano Di Paola

10, Marcello

Maugeri-Saccà11

, Maurizio Montella2

and *Maddalena Barba

11*

1 Division of Medical Oncology B, Regina Elena National Cancer Institute, Rome, Italy

2 Epidemiology Unit, G. Pascale Foundation National Cancer Institute, Naples,  Italy

3 Sbarro Institute for Cancer Research and Molecular Medicine and Center of Biotechnology, College of Science and

Technology Temple University, Philadelphia, USA 4 Department of Human Pathology and Oncology, University of Siena, Siena, Italy

5 Biostatistics-Scientific Direction, Regina Elena National Cancer Institute, Rome, Italy

6 Department of Pathology, Regina Elena National Cancer Institute, Rome, Italy

7 Department of Surgery, Regina Elena National Cancer Institute, Rome, Italy

8 Breast Unit, G. Pascale Foundation National Cancer Institute, Naples,  Italy

9 Department of Pathology, G. Pascale Foundation National Cancer Institute, Naples,  Italy

10 Department of Diagnostics and Clinical Pathology, G. Pascale Foundation National Cancer Institute, Naples,  Italy

11 Division of Medical Oncology B-Scientific Direction, Regina Elena National Cancer Institute, Rome, Italy

*Correspondence to:

Maddalena Barba, MD, PhD

Division of Medical Oncology B, Regina Elena National Cancer Institute

Via Elio Chianesi, 53 00144 Rome, Italy

Landline +39 06 5266 5419, fax +39 06 5266 5075

email: maddalena.barba@shro.org; maddalena.barba@gmail.com

Antonio Giordano, MD, PhD, Director

Sbarro Institute for Cancer Research and Molecular Medicine and Center of Biotechnology

College of Science and Technology, Temple University BioLife Science Bldg. Suite 431 1900 N 12th

Street

Philadelphia PA 19122 USA

Landline +1215-2049520, fax +1 215-2049522

email: giordano@temple.edu; president@shro.org

†This article has been accepted for publication and undergone full peer review but has not

been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as doi: [10.1002/jcp.24891] Additional Supporting Information may be found in the online version of this article.

Received 10 November 2014; Revised 10 December 2014; Accepted 12 December 2014 Journal of Cellular Physiology

This article is protected by copyright. All rights reserved DOI 10.1002/jcp.24891

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Running title: Expression of HER2 in luminal B breast cancer

Key words:

Luminal B breast cancer

HER2 expression

Body mass index

Fasting glucose

Hormone receptors.

Funding: not funded

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ABSTRACT

Genomic and trascriptomic profiling has recently contributed details to the characterization of

luminal B breast cancer. We explored the contribution of anthropometric, metabolic and molecular

determinants to the multifaceted heterogeneity of this breast cancer subtype, with a specific focus

on the association between body mass index (BMI), pre-treatment fasting glucose, hormone

receptors and expression of human epidermal growth factor receptor 2 (HER2). Extensively

annotated specimens were obtained from 154 women with luminal B breast cancer diagnosed at two

Italian comprehensive cancer centres. Participants’ characteristics were descriptively analyzed

overall and by HER2 status (positive vs negative). BMI (˂25 vs ≥25), pre-treatment fasting glucose

(˂median value of 94 mg/dl vs ≥94) and percentage of hormone receptors were tested for

association with HER2 expression in regression models. In univariate models, BMI, fasting glucose

and, at a lesser extent, percentage of estrogen receptors (ER) were significantly and inversely

associated with HER2 expression (OR: 0.32, 95%CI: 0.16-0.66; 0.43, 0.23-0.0.82; 0.96, 0.94-0.97,

respectively). The multivariate models confirmed the protective role of BMI and ER on HER2

expression, with luminal B HER2 positive patients being significantly less frequent among women

within the highest category of BMI and percentage expression of ER compared with their

counterparts (OR: 0.22, 95%CI: 0.09-0.53; 0.95, 0.93-0.97). In conclusions, BMI and percentage of

ER representation are inversely associated with HER2 expression in luminal B breast cancers. Upon

confirmatory findings, this might help identify patient subgroups who may best benefit from the use

of interventions targeting insulin resistance in well depicted breast cancer scenarios. This article is

protected by copyright. All rights reserved

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BACKGROUND

In recent years, the key dowels contributed by high throughput technologies to breast cancer

profiling have added molecular hints to the pre-existing knowledge on standard clinical-

pathological features. This has led to an increasingly more precise definition of four distinct entities,

namely, basal-like, human epidermal growth factor receptor 2 (HER2)–enriched, and luminal A and

B subtypes (Perou et al. 2000).

Subsequently, next generation sequencing (NGS) studies have highlighted significant differences

between luminal A and luminal B breast cancers and have strengthened the notion of luminal B

subtype as a distinct entity (Weinstein et al. 2013; The Cancer Genome Atlas Network 2012; Ellis

et al. 2012; Banerji et al. 2012; Stender et al. 2010). A further relevant gain in knowledge has been

recently substantiated by the data on the extremely heterogeneous nature of luminal B breast cancer

emerged by genomic and trascriptomic profiling studies (Curtis et al. 2012). So far, the attempts of

transferring results from the gene expression profiling studies of luminal B breast cancers to the

clinical setting have been poorly remunerative, with the clinical decisions concerning treatment

being still largely driven by the traditional immunohistochemical (IHC) approach. Within this

context, the expression of human epidermal growth factor receptor 2 (HER2) is a widely recognized

factor in treatment assignment and patients’ clinical management (Ades et al. 2014; Goldhirsch et

al. 2013). This makes the evaluation of factors associated with HER2 expression particularly

appealing to a research agenda.

Insulin resistance (IR) stems from the inadequate ability of insulin to increase cellular glucose

uptake and utilization, thereby leading to the compensatory and chronically elevation of insulin

levels known as hyperinsulinemia. IR provides a common backdrop to several cancers and has been

consistently associated with breast cancer risk and treatment outcome in non diabetic patients

(Lebovitz 2001; Meyerhardt et al. 2010; Goodwin and Stambolic 2011; Goodwin et al. 2002;

Duggan et al. 2011; Emaus et al 2010). Obesity is increasingly conceived as a continuum of

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resistance to insulin action, with IR being by definition tethered to hyperinsulinemia. In addition,

obesity has been recently shown to accelerate the development and progression of estrogen receptor

(ER) positive breast cancer through adipokines and phosphatidylinositol 3-kinase/Akt/mammalian

target of rapamycin signaling in mouse models (Garca-Estévez et al. 2004; Shanik et al. 2008;

Fuentes-Mattei et al. 2014; Garofalo C and Surmacz 2006).

Within our research pipeline centered on the binomious “breast cancer and glucose metabolism”,

we have repeatedly focused on the metabolic determinants of breast cancer patients’ important

outcomes (Barba et al. 2012; Vici et al. 2014). We have now hypothesized that such determinants,

i.e., factors related to glucose metabolism, along with anthropometric and molecular features, may

have a role in conditioning the multifaceted heterogeneity of luminal B breast cancers, with a

specific focus on HER2 expression. To test our hypothesis, we explored BMI, fasting glucose and

percentage expression of hormone receptors in association with HER2 expression in a historic

cohort including 154 women diagnosed with luminal B breast cancer.

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METHODS

The present analysis includes data on 154 clinically annotated luminal B breast cancers diagnosed at

two Italian comprehensive cancer centers, namely, the Regina Elena National Cancer Institute of

Rome and the G. Pascale Foundation National Cancer Institute of Naples.

The study protocol was reviewed and approved by the Ethical Boards of the Institutions involved

and a written informed consent was secured from each participating woman. On study entrance, a

trained research assistant collected data on demographics and anthropometrics including weight in

kilograms (Kg), height in meters (m). Body Mass Index (BMI) was calculated from weight and

height (kg/m2). Twenty milliliters of venous blood were collected on study entrance and prior to

any therapeutic procedures according to highly standardized conditions calling for overnight fasting

and blood drawing between 7.00 and 10.00 AM. Fasting plasma glucose was measured by

hexokinase reagent using a Cobas analyzer (Roche Diagnostics). The assessment was centralized at

the institutional laboratories. Abnormalities in glucose metabolisms were identified based on the

reported use of antidiabetic medications and/or fasting plasma glucose levels greater than 126 mg/dl

(American Diabetes Association 2008).

IMMUNOHISTOCHEMISTRY

At the participating centres, antigen expression was evaluated by an experienced pathologist using

light microscopy. For each sample, at least five fields (inside the tumour and in the area exhibiting

tumour invasion) and >500 cells were analysed. Using a semiquantitative scoring system, the

intensity, extent and subcellular distribution of ER, progesterone receptor (PR), c-erb B2, Ki67, CK

5/6, CK 14 and CK8/18 were evaluated.

The cutoff used to distinguish “positive” from “negative” cases was ≥1% ER/PR positive tumour

cells. Immunohistochemical analyses of HER2 expression describe the intensity and staining pattern

of tumour cells evaluated using the 0 to 3+ score in agreement with the ASCO-CAP guidelines.

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which distinguish four categories: no staining, or faint/barely perceptible membrane staining in

≤10% of the tumour cells (0); incomplete faint/barely perceptible membrane within >10% of the

tumour cells (1+); circumferential weak/moderate membrane staining within >10% of tumour cells

or intense complete and circumferential membrane within ≤10% of tumour cells (2+); and

circumferential complete membrane staining within >10% of tumour cells strong (3+). Scores of 0

or 1+ were considered negative for HER2 expression, 2+ was defined as equivocal and a reflex test

using ISH must be performed, and 3+ was positive (Wolff et al. 2010).

The proliferative index Ki67 was defined as the percentage of immunoreactive tumour cells out of

the total number of cells. The percentage of positive cells per case was scored according to 2

different groups: group 1: <20% (low proliferative activity) and group 2: ≥20% (high proliferative

activity). CKs stains were considered positive if any (weak or strong) cytoplasmic invasive

carcinoma cell staining was observed.

Molecular subtype classification

Luminal B breast cancers were identified and categorized based on the St Gallen

International Expert Consensus on the Primary Therapy of Early Breast Cancer 2013 [9]. In brief,

cases were distinguished into:1. Luminal B HER2 negative if ER positive, HER2 negative and with

Ki-67 ‘high’, i.e., ≥20%, and/or PR ‘negative or low’, i.e., ˂20% and 2. ‘Luminal B HER2 positive

if ER positive and HER2 over-expressed or amplified, independently on Ki-67 percentage and PR

status.

Statistical analyses

We examined distributions and computed descriptive statistics for all the variables of interest. The

characteristics of the study participants were reported overall and by HER2 status, i.e., negative vs

positive. BMI was categorized into two groups (˂25 vs ≥25), while categories of pre-treatment

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fasting glucose were defined upon the median value for this study population (˂ 94 mg/dl vs≥94)

and percentage of hormone receptors was addressed as a continuous variable. Means and standard

deviations were used for continuous data while frequencies and percentage values for categorical

data. Existing differences between mean values were evaluated using the T- Student or One Way

Anova test according to the number (2 or more) of groups compared. We used the Pearson’s Chi-

squared test of independence (2-tailed) to assess the relationship between categorical variables. We

tested several variables for association with HER2 status using univariate logistic regression

analysis. Multivariate models were then built by exclusively including those factors testing

significant at the univariate analysis. Analyses were further stratified by menopausal status.

We considered p values less than 0.05 statistically significant. All statistical analyses were

performed with the SPSS statistical software version 21 (SPSS inc., Chicago IL, USA).

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RESULTS

The characteristics of the 154 study participants included in our analysis are illustrated in table 1.

The variables shown are related to baseline demographics and anthropometrics as well as clinical-

molecular features assessed at baseline.

In table 2, our study participants were compared by HER2 status. Patients with Luminal B HER2

negative breast cancer were significantly older and more often postmenopausal compared to their

counterparts (63.7±9.1 vs 50.6±12.4, p=0.0001 and 60% vs 40%, p=0.0001, respectively). In

addition, luminal B HER2 negative cases tended to exhibit a significantly greater BMI than HER2

positive patients (28.8±5.0 vs 24.8±4.1, p=0.0001).

In table 3, we report on the results from univariate regression models testing variables associated

with HER2 positivity in luminal B breast cancer. Our data showed that BMI, fasting glucose and, at

a minor extent, percentage expression of ER were inversely and significantly associated with HER2

expression (OR: 0.32 95%CI: 0.16-0.66, p= 0.002; 0.43 0.23-0.82, p=0.011 and 0.96 0.94-0.97,

p˂0.0001). In multivariate analysis including variables testing significant at the univariate

regression (table 4), BMI and percentage expression of ER confirmed their association with HER2

expression (OR: 0.22 95%CI:0.09-0.53, p=0.001 and 0.95 0.93-0.97, p˂0.0001, respectively).

When stratifying analysis by menopause, results from the multivariate models were confirmed in

postmenopausal women (supplementary table 5).

Given the well documented prevalence of insulin resistance in conditions characterized by

abnormalities of glucose metabolism and their tights with cancer (Gallagher et al. 2013; Reiss et al.

2012), we also considered the potential impact of such disturbances on HER2 positivity in our

cohort. Among the patients included in the present analysis, 17 self-reported on the current use of

anti-diabetic drugs and/or exhibited fasting glucose levels ˃126 mg/dl on study entry. However, the

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exclusion of these patients from the analysis did not affect our study results at any extent (data

available upon request).

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DISCUSSION

In this study, results from a set of analyses performed on 154 women with luminal B breast cancer

showed a significant, inverse association between BMI, percentage of ER and HER2 expression.

This seemed to indicate that HER2 expression was significantly less common among luminal B

breast cancer patients whose BMI and ER expression were in the highest categories compared to

their respective counterparts. Results were fully confirmed in postmenopausal women in models

stratified by menopausal status.

The link between obesity, exemplified in our cohort by BMI, and IR is solidly established (Garca-

Estévez et al. 2004). IR has been repeatedly assessed in relation to breast cancer risk with fairly

consistent results. In a recent systematic review from Hernandez and colleagues, among the studies

judged eligible for inclusion, two cross sectional and three case-control studies contributed data to

address the association between the Homeostasis Model Assessment of IR (HOMA-IR), a surrogate

of proven validity for the assessment of IR, and risk of breast cancer (Sieri et al. 2012; Gonullu et al

2005; Garmendia et al. 2007; Lawlor et al. 2004; Abbasi et al. 2010). Women with and without

breast cancer were compared by HOMA-IR. According to the results reported, HOMA-IR values

were significantly and slightly higher in breast cancer patients than in women without breast cancer

[Mean difference (MD) 0.22, 95% Confidence Interval (95% CI): 0.13 to 0.31, p<0.00001

(Hernandez et al. 2014). Results from the case-control study carried out by Cordero-Franco and

colleagues were not available at the time the work from Hernandez and co-authors was conducted.

Data from this study do not provide support to the association between HOMA-IR and breast cancer

risk. However, when testing the association with glycated hemoglobin (HbA1c), a parameter

reflecting average pre- and postprandial glucose levels over the past 6–8 weeks, the authors

observed an increased breast cancer risk in pre- and post-menopausal women with HbA1c ≥5.7%

(Cordero-Franco et al. 2014).

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The critical appraisal of the literature cited above provides several hints for discussion. First, the

available evidence is quite consistent, though not conclusive, in supporting the association between

insulin resistance and risk of breast cancer. Second, this same evidence is barely, if ever, referred to

specific patient- and/or disease-related features and thus difficult to be translated into the clinical

context. Such difficulty might be partly exemplified by Hernandez and colleagues, who cite the lack

of data on menopausal status when outlining the limitations of their work. In these respects, it may

be worth further mentioning the absence of referrals to the standard clinical and molecular features

of breast cancer cases in at least three studies out of the five included in the meta-regression (Sieri

et al. 2012; Garmendia et al. 2007; Lawlor et al. 2004). Conversely, limited information on the

lesions’ nature (i.e., benign versus malignant) and basic histological features of the breast masses

characterized (i.e., in situ vs invasive breast cancer and lobular vs ductal carcinoma) were reported

by Abbasi and co-authors and a quick referral to the specific setting, i.e., adjuvant setting, and

therapeutic management for some of the patients included appear in the latest paragraph of the

results in the manuscript from Gonullu and colleagues (Sieri S et al. 2012; Lawlor et al. 2004).

Again, no hints on standard disease-related clinical and molecular features were reported for cancer

cases in the work from Cordero-Franco (Cordero-et al. 2014).

In such scenario, we posed a precisely framed research question and focused on luminal B breast

cancers only. These tumours represent an extremely heterogeneous fraction of ER-expressing

disease with generally poorer treatment outcome in the early setting when compared to luminal A

breast cancers. Approximately 30% of luminal B-like tumors are HER2 positive and require a

distinct treatment approach involving HER2-targeted therapy (Cheang et al. 2009). The first time

evidence emerged from our study on the existence of a significant, inverse association between

BMI, a factor tightly linked to insulin resistance, ER and HER2 expression in luminal B-like breast

cancer might suggest a contributing role of these factors in explaining the heterogeneous nature of

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luminal B tumours. To our knowledge, no prior studies have addressed the role these determinants

in affecting breast cancer risk at such a specifically defined level, i.e., in exclusive referral to

luminal B breast cancer. For the historic cohort included in this analysis, updated follow up data

will be shortly available and the eventual predictive role of BMI and ER status on treatment

outcome will be soon assessable across categories defined upon HER2 status. If in key with our

previous findings (Barba et al. 2012; Vici et al. 2014) and with the evidence from this study, results

from future investigations along this same research pipeline might indicate a role for the assessment

of relatively cheap serum biomarkers of insulin resistance (e.g., fasting glucose and insulin) and

anthropometric data collection in informing therapeutic decisions regarding the use of

pharmaceutical and/or lifestyle-related co-interventions acting on insulin resistance in luminal B

breast cancer patients. Assessment of the patient-and disease-related features might thus contribute

key “dowels” to the intricate puzzle of luminal-B like breast cancer, particularly if evaluated jointly

with a limited number of easy measurable parameters accounting for general and visceral adiposity

(e.g. BMI and waist circumference).

From a biological standpoint, our results are supported by preclinical findings on the role of insulin-

like growth factor-1 receptor (IGF-1R)/insulin receptor substrate-1 (IRS-1) IGF-1R/IRS-1 signaling

axis in breast carcinogenesis (Pollak 2008). In addition, increased signaling from IGF-1R has been

consistently described among the molecular mechanisms driving resistance to the humanized anti-

HER2 antibody trastuzumab (Nahta 2012; Gallardo et al. 2012; Ye et al. 2014) and IGR-1

expression has been evaluated in association with trastuzumab response (K¨ostler et al. 2006; Smith

et al. 2004). This has led to the clinical testing of several IGF-IR antibodies and kinase inhibitors in

clinical trials of solid tumours including breast cancer (Tap et al. 2012; Weickhardt et al. 2012;

Robertson et al. 2013; Baserga 2013)). A similar substrate of pre-clinical and clinical findings has

converged into the wave of studies centred on the use of metformin in breast cancer (Leone et al.

2014). Independently on the intervention tested, a choral voice invites to the use of biomarkers for

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patients’ population selection, with the identification of subgroups which might particularly benefit

from a given treatment remaining one of the greatest challenges. In this view, assessment of

anthropometric, metabolic and molecular determinant might efficiently integrate data for patients’

selection.

Our study has some limitations. We analyzed data from a relatively numerically limited historic

cohort. This is mainly due to the restricted focus of our investigation which led us to exclusively

consider one specific molecular subtype rather than referring risk assessment to the broadly defined

category of “histologically-confirmed invasive breast cancer”. We are aware of the need of

exploring our hypothesis in larger studies and eventually pooling data from several studies

following careful evaluation of heterogeneity based on ad hoc indicators (e.g., Cochrane x2 and the

I2 statistic). The limitations stemming from the restricted size of the study sample might be partly

attenuated by the in-depth molecular characterization available for all the study participants along

with the high reliability of the data provided by the pathologists due to the availability of protocols

for quality control of HER2 characterization at the involved Institutions.

Among our study strengths, we may cite its novelty, since to the best of our knowledge no evidence

of association between anthropometric, metabolic and molecular determinants and HER2

expression has been previously produced. Standardized operative procedures were applied to data

collection, including anthropometric measurements, biological sample collection and handling.

Biomarkers’ assessment was performed at the central laboratories of the Institutions involved. The

study procedures were perfectly integrated in the clinical routine and the costs related to the study

conduct were extremely low.

In summary, we conducted an observational study framed within the normal course of clinical care

in both the early and advanced breast cancer setting. This allowed us to gather data on the

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association between anthropometric, metabolic, molecular factors and HER2 expression in a case

series including 154 women with luminal B breast cancer. Our assessment may contribute key

“dowels” to the intricate puzzle of luminal-B like breast cancer, particularly if evaluated jointly

with a bunch of easily measurable parameters accounting for visceral adiposity (e.g. waist

circumference). Such an approach might help better define the host profile and disease features in

view of an increasingly targeted therapeutic approach. The identification of patient subgroups who

may best benefit from the use of co-interventions targeting insulin resistance in well depicted breast

cancer scenarios may ultimately translate into improved patients’ important outcome.

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Acknowledgements

We thank Dr Tania Merlino for language revisions. We further thank Dr Anamaria Edlisca for

editorial assistance and data managing. We are grateful to the Sbarro Institute for Cancer Research

and Molecular Medicine for the support provided.

Conflict of Interest: The authors declare that they have no conflict of interest.

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Table 1 Study Participants’ Characteristics (N=154)

Age* (mean, ±SD)

56.8 (12.7)

Menopausal status (N, %) Pre 33 (21)

Post 121 (79)

BMI§ (N, %) <25 51 (33)

≥25 103 (67)

Fasting Glucose° (N, %) <94 78 (51)

≥ 94 76 (49)

1Stage at Diagnosis (N, %) Early 109 (73)

Advanced 40 (27)

HER2 expression (N, %) aNegative 73 (47)

bPositive 81 (53)

* in years, § Body Mass Index in m

2/Kg

a Luminal B-like (HER2 negative) breast cancer,

b Luminal B-like (HER2 positive) breast cancer

1 Sums do not add up to 100 because of missing values

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Table 2 Study Participants’ Characteristics by HER2 status (N=154)

HER2 (-)

N=73

HER2(+)

N=81 p-value

Age* (mean ± SD) 63.7 (9.1) 50.6(12.4) 0.0001

Menopausal status (N, %) Pre 0 33 (100) 0.0001

Post 73(60) 48 (40)

BMI§ (N, %) <25 15(29) 36(71) 0.002

≥25 58(56) 45(44)

Fasting Glucose (N, %) <94 29(37) 49(63) 0.010

≥94 44(58) 32(42)

Stage at Cancer Diagnosis (N, %) Early 54 (49) 55 (51) ns

Advanced 14 (65) 26(65)

* in years, § Body Mass Index in m

2/Kg

a Luminal B-like (HER2 negative) breast cancer,

b Luminal B-like (HER2 positive) breast cancer

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Table3 : Univariate logistic regression models testing variables associated with HER2 positivity in luminal

B breast cancer (N=154)

Factors Univariate analysis

*OR (95% CI)* P- value

BMI§(<25 vs ≥25) 0.32 (0.16-0.66) 0.002 Fasting glucose 1 (<94 vs ≥94) 0.43 (0.23-0.82) 0.011 ER2 (%) 0.96 (0.94-0.97) <0.0001 PgR3(%) 0.99 (0.98-1.00) ns

*Odds Ratio and 95% Confident Interval

§ Body Mass Index in m

2/Kg

1 mg/dl

2 ER Estrogen Receptor

3 Progesterone Receptor

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Table4 : Multivariate logistic regression models testing variables associated with HER2 positivity in luminal B breast cancer (N=154)

Factors Multivariate analysis

*OR (95% CI) P- value

BMI§(<25 vs ≥25) 0.22 (0.09-0.53) 0.001

Fasting glucose1 (94 vs ≥94) 0.67 (0.30-1.47) ns

ER2 (%) 0.95 (0.93-0.97) <0.0001

§ Body Mass Index in m

2/Kg. *Odds Ratio and 95% Confident Interval

1 mg/dl

2 Estrogen receptor