Effect of obesity on molecular characteristics of invasive breast tumors: gene expression analysis in a large cohort of female patients

Association of Computed Tomography Scan-Assessed Body Composition with Immune and PI3K/AKT Pathway Proteins in Distinct Breast Cancer Tumor Components

This hypothesis-generating study aims to examine the extent to which computed tomography-assessed body composition phenotypes are associated with immune and phosphoinositide 3-kinase (PI3K)/protein kinase B (AKT) signaling pathways in breast tumors. A total of 52 patients with newly diagnosed breast cancer were classified into four body composition types: adequate (lowest two tertiles of total adipose tissue [TAT]) and highest two tertiles of total skeletal muscle [TSM] areas); high adiposity (highest tertile of TAT and highest two tertiles of TSM); low muscle (lowest tertile of TSM and lowest two tertiles of TAT); and high adiposity with low muscle (highest tertile of TAT and lowest tertile of TSM). Immune and PI3K/AKT pathway proteins were profiled in tumor epithelium and the leukocyte-enriched stromal microenvironment using GeoMx (NanoString). Linear mixed models were used to compare log2-transformed protein levels. Compared with the normal type, the low muscle type was associated with higher expression of INPP4B (log2-fold change = 1.14, p = 0.0003, false discovery rate = 0.028). Other significant associations included low muscle type with increased CTLA4 and decreased pan-AKT expression in tumor epithelium, and high adiposity with increased CD3, CD8, CD20, and CD45RO expression in stroma (p < 0.05; false discovery rate > 0.2). With confirmation, body composition can be associated with signaling pathways in distinct components of breast tumors, highlighting the potential utility of body composition in informing tumor biology and therapy efficacies.

Impact of Obesity on Breast Cancer Clinicopathological Characteristics in Underserved US Community Safety-Net Hospital: A Retrospective Single-Center Study

BACKGROUND

Breast cancer continues to pose a significant public health challenge, with its incidence and disproportionate impact on underserved populations in the United States. The relationship between obesity and clinicopathological characteristics at presentation remains a critical area of investigation. Safety-net hospitals caring for underserved communities provide a unique setting to explore these associations. This study seeks to explore a critical gap in knowledge on obesity and breast cancer characteristics in underserved populations in the United States.

MATERIALS AND METHODS

In this retrospective study, 927 breast cancer patients were included. Analysis was conducted to assess the association between body mass index (BMI), age of diagnosis, tumor clinicopathologic characteristics, and molecular types stratified by menopausal status at diagnosis. Analysis was performed using the Statistical Package for Social Sciences version 29.

RESULTS

A significant association was found between BMI and menopausal status (P < .05). Disease stage at presentation was significantly associated with BMI (P < .05). Further investigation into BMI categories and tumor characteristics revealed a significant correlation in postmenopausal women, with obesity linked to tumor size and lymph node status (P < .05). No significant associations were observed between HER-2 status, ER/PR status, and obesity in either premenopausal or postmenopausal groups.

CONCLUSION

This observational retrospective hypothesis-generating study revealed the association between obesity and disease stage and menopause status at diagnosis. In postmenopausal patients, obesity correlated with larger tumor size and advanced lymph node disease involvement. Additionally, ethnic variations were observed, with a higher prevalence of obesity among African American patients.

Association of computed tomography scan-assessed body composition with immune and PI3K/AKT pathway proteins in distinct breast cancer tumor components

This hypothesis-generating study aims to examine the extent to which computed tomography-assessed body composition phenotypes are associated with immune and PI3K/AKT signaling pathways in breast tumors. A total of 52 patients with newly diagnosed breast cancer were classified into four body composition types: adequate (lowest two tertiles of total adipose tissue [TAT]) and highest two tertiles of total skeletal muscle [TSM] areas); high adiposity (highest tertile of TAT and highest two tertiles of TSM); low muscle (lowest tertile of TSM and lowest two tertiles of TAT); and high adiposity with low muscle (highest tertile of TAT and lowest tertile of TSM). Immune and PI3K/AKT pathway proteins were profiled in tumor epithelium and the leukocyte-enriched stromal microenvironment using GeoMx (NanoString). Linear mixed models were used to compare log2-transformed protein levels. Compared with the normal type, the low muscle type was associated with higher expression of INPP4B (log2-fold change = 1.14, p = 0.0003, false discovery rate = 0.028). Other significant associations included low muscle type with increased CTLA4 and decreased pan-AKT expression in tumor epithelium, and high adiposity with increased CD3, CD8, CD20, and CD45RO expression in stroma (P<0.05; false discovery rate >0.2). With confirmation, body composition can be associated with signaling pathways in distinct components of breast tumors, highlighting the potential utility of body composition in informing tumor biology and therapy efficacies.

MEIS2 suppresses breast cancer development by downregulating IL10

BACKGROUND

Breast cancer (BC) is the most commonly diagnosed female cancer. Homeobox protein MEIS2, a key transcription factor, is involved in the regulation of many developmental and cellular processes. However, the role of MEIS2 in the development of breast cancer is still unclear.

AIMS

We aimed to examine the role of myeloid ecotropic insertion site (MEIS2) in breast cancer and the association of MEIS2 with breast cancer clinical stages and pathological grades. We revealed the underlying mechanism by which MEIS2 affected breast cancer cell growth and tumor development.

METHODS AND RESULTS

Using human BC cell lines, clinical samples and animal xenograft model, we reveal that MEIS2 functions as a tumor suppressor in breast cancer. The expression of MEIS2 is inversely correlated with BC clinical stages and pathological grades. MEIS2 knockdown (MEIS2-KD) promotes while MEIS2 overexpression suppresses breast cancer cell proliferation and tumor development in vitro and in animal xenograft models, respectively. To determine the biological function of MEIS2, we screen the expression of a group of MEIS2 potential targeting genes in stable-established cell lines. Results show that the knockdown of MEIS2 in breast cancer cells up-regulates the IL10 expression, but MEIS2 overexpression opposed the effect on IL10 expression. Furthermore, the suppressive role of MEIS2 in breast cancer cell proliferation is associated with the IL10 expression and myeloid cells infiltration.

CONCLUSION

Our study demonstrates that the tumor suppressor of MEIS2 in breast cancer progression is partially via down regulating the expression of IL10 and promoting myeloid cells infiltration. Targeting MEIS2 would be a potentially therapeutic avenue for BC.

FGF1 supports glycolytic metabolism through the estrogen receptor in endocrine-resistant and obesity-associated breast cancer

BACKGROUND

Obesity increases breast cancer risk and breast cancer-specific mortality, particularly for people with estrogen receptor (ER)-positive tumors. Body mass index (BMI) is used to define obesity, but it may not be the best predictor of breast cancer risk or prognosis on an individual level. Adult weight gain is an independent indicator of breast cancer risk. Our previous work described a murine model of obesity, ER-positive breast cancer, and weight gain and identified fibroblast growth factor receptor (FGFR) as a potential driver of tumor progression. During adipose tissue expansion, the FGF1 ligand is produced by hypertrophic adipocytes as a stimulus to stromal preadipocytes that proliferate and differentiate to provide additional lipid storage capacity. In breast adipose tissue, FGF1 production may stimulate cancer cell proliferation and tumor progression.

METHODS

We explored the effects of FGF1 on ER-positive endocrine-sensitive and resistant breast cancer and compared that to the effects of the canonical ER ligand, estradiol. We used untargeted proteomics, specific immunoblot assays, gene expression profiling, and functional metabolic assessments of breast cancer cells. The results were validated in tumors from obese mice and breast cancer datasets from women with obesity.

RESULTS

FGF1 stimulated ER phosphorylation independently of estradiol in cells that grow in obese female mice after estrogen deprivation treatment. Phospho- and total proteomic, genomic, and functional analyses of endocrine-sensitive and resistant breast cancer cells show that FGF1 promoted a cellular phenotype characterized by glycolytic metabolism. In endocrine-sensitive but not endocrine-resistant breast cancer cells, mitochondrial metabolism was also regulated by FGF1. Comparison of gene expression profiles indicated that tumors from women with obesity shared hallmarks with endocrine-resistant breast cancer cells.

CONCLUSIONS

Collectively, our data suggest that one mechanism by which obesity and weight gain promote breast cancer progression is through estrogen-independent ER activation and cancer cell metabolic reprogramming, partly driven by FGF/FGFR. The first-line treatment for many patients with ER-positive breast cancer is inhibition of estrogen synthesis using aromatase inhibitors. In women with obesity who are experiencing weight gain, locally produced FGF1 may activate ER to promote cancer cell metabolic reprogramming and tumor progression independently of estrogen.

Obesity-associated changes in molecular biology of primary breast cancer

Obesity is associated with an increased risk of developing breast cancer (BC) and worse prognosis in BC patients, yet its impact on BC biology remains understudied in humans. This study investigates how the biology of untreated primary BC differs according to patients' body mass index (BMI) using data from >2,000 patients. We identify several genomic alterations that are differentially prevalent in overweight or obese patients compared to lean patients. We report evidence supporting an ageing accelerating effect of obesity at the genetic level. We show that BMI-associated differences in bulk transcriptomic profile are subtle, while single cell profiling allows detection of more pronounced changes in different cell compartments. These analyses further reveal an elevated and unresolved inflammation of the BC tumor microenvironment associated with obesity, with distinct characteristics contingent on the estrogen receptor status. Collectively, our analyses imply that obesity is associated with an inflammaging-like phenotype. We conclude that patient adiposity may play a significant role in the heterogeneity of BC and should be considered for BC treatment tailoring.

Metabolic Dysregulation Explains the Diverse Impacts of Obesity in Males and Females with Gastrointestinal Cancers

The prevalence of obesity, defined as the body mass index (BMI) ≥ 30 kg/m2, has reached epidemic levels. Obesity is associated with an increased risk of various cancers, including gastrointestinal ones. Recent evidence has suggested that obesity disproportionately impacts males and females with cancer, resulting in varied transcriptional and metabolic dysregulation. This study aimed to elucidate the differences in the metabolic milieu of adenocarcinomas of the gastrointestinal (GI) tract both related and unrelated to sex in obesity. To demonstrate these obesity and sex-related effects, we utilized three primary data sources: serum metabolomics from obese and non-obese patients assessed via the Biocrates MxP Quant 500 mass spectrometry-based kit, the ORIEN tumor RNA-sequencing data for all adenocarcinoma cases to assess the impacts of obesity, and publicly available TCGA transcriptional analysis to assess GI cancers and sex-related differences in GI cancers specifically. We applied and integrated our unique transcriptional metabolic pipeline in combination with our metabolomics data to reveal how obesity and sex can dictate differential metabolism in patients. Differentially expressed genes (DEG) analysis of ORIEN obese adenocarcinoma as compared to normal-weight adenocarcinoma patients resulted in large-scale transcriptional reprogramming (4029 DEGs, adj. p < 0.05 and |logFC| > 0.58). Gene Set Enrichment and metabolic pipeline analysis showed genes enriched for pathways relating to immunity (inflammation, and CD40 signaling, among others) and metabolism. Specifically, we found alterations to steroid metabolism and tryptophan/kynurenine metabolism in obese patients, both of which are highly associated with disease severity and immune cell dysfunction. These findings were further confirmed using the TCGA colorectal adenocarcinoma (CRC) and esophageal adenocarcinoma (ESCA) data, which showed similar patterns of increased tryptophan catabolism for kynurenine production in obese patients. These patients further showed disparate alterations between males and females when comparing obese to non-obese patient populations. Alterations to immune and metabolic pathways were validated in six patients (two obese and four normal weight) via CD8+/CD4+ peripheral blood mononuclear cell RNA-sequencing and paired serum metabolomics, which showed differential kynurenine and lipid metabolism, which corresponded with altered T-cell transcriptome in obese populations. Overall, obesity is associated with differential transcriptional and metabolic programs in various disease sites. Further, these alterations, such as kynurenine and tryptophan metabolism, which impact both metabolism and immune phenotype, vary with sex and obesity together. This study warrants further in-depth investigation into obesity and sex-related alterations in cancers that may better define biomarkers of response to immunotherapy.

Identification of Hub Genes and Biological Mechanisms Associated with Non-Alcoholic Fatty Liver Disease and Triple-Negative Breast Cancer

The relationship between non-alcoholic fatty liver disease (NAFLD) and triple-negative breast cancer (TNBC) has been widely recognized, but the underlying mechanisms are still unknown. The objective of this study was to identify the hub genes associated with NAFLD and TNBC, and to explore the potential co-pathogenesis and prognostic linkage of these two diseases. We used GEO, TCGA, STRING, ssGSEA, and Rstudio to investigate the common differentially expressed genes (DEGs), conduct functional and signaling pathway enrichment analyses, and determine prognostic value between TNBC and NAFLD. GO and KEGG enrichment analyses of the common DEGs showed that they were enriched in leukocyte aggregation, migration and adhesion, apoptosis regulation, and the PPAR signaling pathway. Fourteen candidate hub genes most likely to mediate NAFLD and TNBC occurrence were identified and validation results in a new cohort showed that ITGB2, RAC2, ITGAM, and CYBA were upregulated in both diseases. A univariate Cox analysis suggested that high expression levels of ITGB2, RAC2, ITGAM, and CXCL10 were associated with a good prognosis in TNBC. Immune infiltration analysis of TNBC samples showed that NCF2, ICAM1, and CXCL10 were significantly associated with activated CD8 T cells and activated CD4 T cells. NCF2, CXCL10, and CYBB were correlated with regulatory T cells and myeloid-derived suppressor cells. This study demonstrated that the redox reactions regulated by the NADPH oxidase (NOX) subunit genes and the transport and activation of immune cells regulated by integrins may play a central role in the co-occurrence trend of NAFLD and TNBC. Additionally, ITGB2, RAC2, and ITGAM were upregulated in both diseases and were prognostic protective factors of TNBC; they may be potential therapeutic targets for treatment of TNBC patients with NAFLD, but further experimental studies are still needed.

Shoulder function and health outcomes in newly diagnosed breast cancer patients receiving surgery: a prospective study

BACKGROUND

Breast cancer surgery is associated with upper-body morbidities that may last several years postsurgery. Research has not determined if the type of surgery leads to differential effects on shoulder function, activity levels, and QoL during the early rehabilitation period. The main objective of this study is to examine changes in shoulder function, health, and fitness outcomes from the day before to surgery to 6 months postsurgery.

PATIENTS AND METHODS

We recruited breast cancer patients (N = 70) scheduled to receive breast cancer surgery at Severance Hospital in Seoul to participate in this prospective study. Shoulder range of motion (ROM) and upper body strength, the disabilities of Arm, Shoulder, and Hand (quick-DASH), body composition, physical activity levels, and QoL were measured at baseline (presurgery) and then weekly for 4 weeks, and at 3 months and 6 months postsurgery.

RESULTS

During 6 months after surgery, shoulder ROM was reduced only affected arm while shoulder strength was significantly declined in both affected and unaffected arms. Within 4 weeks postsurgery, patients who underwent total mastectomy were significantly less recovered than patients with partial mastectomy in ROM of flexion (P < .05) and abduction (P < .05). However, shoulder strength of both arms observed no interaction between surgical type and time. We observed significant changes in body composition, quick-DASH score, physical activity levels, and QoL from presurgery to 6-months postsurgery.

CONCLUSIONS

Shoulder function, activity levels, and QoL improved significantly from surgery to 6-months postsurgery. Surgery type influenced changes in shoulder ROM.

Removing unwanted variation from large-scale RNA sequencing data with PRPS

Accurate identification and effective removal of unwanted variation is essential to derive meaningful biological results from RNA sequencing (RNA-seq) data, especially when the data come from large and complex studies. Using RNA-seq data from The Cancer Genome Atlas (TCGA), we examined several sources of unwanted variation and demonstrate here how these can significantly compromise various downstream analyses, including cancer subtype identification, association between gene expression and survival outcomes and gene co-expression analysis. We propose a strategy, called pseudo-replicates of pseudo-samples (PRPS), for deploying our recently developed normalization method, called removing unwanted variation III (RUV-III), to remove the variation caused by library size, tumor purity and batch effects in TCGA RNA-seq data. We illustrate the value of our approach by comparing it to the standard TCGA normalizations on several TCGA RNA-seq datasets. RUV-III with PRPS can be used to integrate and normalize other large transcriptomic datasets coming from multiple laboratories or platforms.

mTOR pathway gene expression in association with race and clinicopathological characteristics in Black and White breast cancer patients

BACKGROUND

Aberrant activation of the mammalian Target of Rapamycin (mTOR) pathway has been linked to obesity and endocrine therapy resistance, factors that may contribute to Black-White disparities in breast cancer outcomes. We evaluated associations of race and clinicopathological characteristics with mRNA expression of key mTOR pathway genes in breast tumors.

METHODS

Surgical tumor tissue blocks were collected from 367 newly diagnosed breast cancer patients (190 Black and 177 White). Gene expression of AKT1, EIF4EBP1, MTOR, RPS6KB2, and TSC1 were quantified by NanoString nCounter. Differential gene expression was assessed using linear regression on log2-transformed values. Gene expression and DNA methylation data from TCGA were used for validation and investigation of race-related differences.

RESULTS

Compared to White women, Black women had relative under-expression of AKT1 (log2 fold-change = - 0.31, 95% CI - 0.44, - 0.18) and RPS6KB2 (log2 fold-change = - 0.11, 95% CI - 0.19, - 0.03). Higher vs. lower tumor grade was associated with relative over-expression of EIF4EBP1 and RPS6KB2, but with lower expression of TSC1. Compared to luminal tumors, triple-negative tumors had relative under-expression of TSC1 (log2 fold-change = - 0.42, 95% CI - 0.22, - 0.01). The results were similar in the TCGA breast cancer dataset. Post-hoc analyses identified differential CpG methylation within the AKT1 and RPS6KB2 locus between Black and White women.

CONCLUSIONS

Over-expression of RPS6KB2 and EIF4EBP1 and under-expression of TSC1 might be indicators of more aggressive breast cancer phenotypes. Differential expression of AKT1 and RPS6KB2 by race warrants further investigation to elucidate their roles in racial disparities of treatment resistance and outcomes between Black and White women with breast cancer.

Development of a risk-stratification scoring system for predicting risk of breast cancer based on non-alcoholic fatty liver disease, non-alcoholic fatty pancreas disease, and uric acid

Many breast cancer patients have both non-alcoholic fatty liver disease (NAFLD) and non-alcoholic fatty pancreas disease (NAFPD). Consequently, we hypothesized that NAFPD and NAFLD were associated with breast cancer, and aimed to build a novel risk-stratification scoring system based on it. In this study, a total of 961 patients with breast cancer and 1,006 non-cancer patients were recruited. The clinical characteristics were collected and analyzed using logistic analysis. Risk factors were assessed by a risk rating system. Univariate analysis showed that body mass index, triglyceride, total cholesterol, NAFLD, NAFPD, low-density lipoprotein, and uric acid (UA) were significantly related to breast cancer. Among them, NAFLD, NAFPD, and UA were independent risk factors related to breast cancer identified by multivariate analysis. The risk assessment model was established based on these factors and demonstrated that the odds ratio sharply increased with the rising scores. Compared with the low-risk group, the odds ratio in the intermediate- and high-risk groups were 1.662 (1.380–2.001) and 3.185 (2.145–4.728), respectively. In conclusion, the risk-stratification scoring system combining NAFLD, NAFPD, and UA can accurately predict the occurrence of breast cancer.

Gender Differences in Obesity-Related Cancers

PURPOSE OF REVIEW

In this review, we summarize the role of obesity in carcinogenesis, providing details on specific cancer sites. Special emphasis is given to gender differences in obesity-related cancers and on the effect of bariatric surgery on cancer risk.

RECENT FINDINGS

Accumulating evidence has highlighted the detrimental role of overweight/obesity in cancer, with almost 55% of cancers diagnosed in women and 24% diagnosed in men considered overweight- and obesity-related cancers. Sufficient data have shown that higher BMI is associated with risk of gynecologic malignancies (mainly breast and endometrial cancers) as well as cancers in sites such as the esophagus (adenocarcinoma), gastric cardia, colon, rectum, liver, gallbladder, pancreas, kidney, thyroid gland, and multiple myeloma. The main mechanisms underlying this relationship include the insulin/IGF1 system, the effect of sex hormones, and adipocytokines. Marked differences may be seen in specific cancer sites when comparing men to women. There is a higher overall incidence of obesity-related cancers among females (endometrial, ovarian, and postmenopausal female breast cancers), whereas cancers that concern both sexes show a higher incidence in males, particularly esophageal adenocarcinoma (male to female ratio: 9: 1 in the USA). Additionally, bariatric surgery has provided evidence of lowering overall cancer risk in patients with morbid obesity. Interestingly, bariatric surgery may lower overall cancer risk in women within the first 5 years after surgery due to the reduced risk of breast and endometrial cancer, and non-Hodgkin lymphoma. Obesity constitutes the base for marked metabolic, hormonal, and inflammatory alterations, including increased cancer risk in both men and women. Implementation of early obesity prevention strategies could ameliorate the continuously increasing incidence of cancer attributed to obesity.

Cholesterol-Induced Metabolic Reprogramming in Breast Cancer Cells Is Mediated via the ERRα Pathway

Simple Summary

There is increasing evidence that obesity and high circulating cholesterol levels are associated with an increased risk of recurrence and a higher mortality rate in breast cancer patients via altering the metabolic programming in breast cancer cells. However, the underlying molecular mechanism by which high cholesterol levels reprogram the metabolic pathways in breast cancer cells is not well-understood. We have previously demonstrated that cholesterol acts as an endogenous agonist of estrogen-related receptor α (ERRα), a strong regulator of cellular metabolism. The aim of the current study is to demonstrate whether cholesterol/obesity mediates its pathogenic effect in breast cancer cells via altering metabolic pathways in an ERRα-dependent manner. The findings of this study provide mechanistic insights into the link between cholesterol/obesity and metabolic reprogramming in breast cancer patients and reveal the metabolic vulnerabilities in such breast cancer patients that could be therapeutically targeted.

Abstract

The molecular mechanism underlying the metabolic reprogramming associated with obesity and high blood cholesterol levels is poorly understood. We previously reported that cholesterol is an endogenous ligand of the estrogen-related receptor alpha (ERRα). Using functional assays, metabolomics, and genomics, here we show that exogenous cholesterol alters the metabolic pathways in estrogen receptor-positive (ER+) and triple-negative breast cancer (TNBC) cells, and that this involves increased oxidative phosphorylation (OXPHOS) and TCA cycle intermediate levels. In addition, cholesterol augments aerobic glycolysis in TNBC cells although it remains unaltered in ER+ cells. Interestingly, cholesterol does not alter the metabolite levels of glutaminolysis, one-carbon metabolism, or the pentose phosphate pathway, but increases the NADPH levels and cellular proliferation, in both cell types. Importantly, we show that the above cholesterol-induced modulations of the metabolic pathways in breast cancer cells are mediated via ERRα. Furthermore, analysis of the ERRα metabolic gene signature of basal-like breast tumours of overweight/obese versus lean patients, using the GEO database, shows that obesity may modulate ERRα gene signature in a manner consistent with our in vitro findings with exogenous cholesterol. Given the close link between high cholesterol levels and obesity, our findings provide a mechanistic explanation for the association between cholesterol/obesity and metabolic reprogramming in breast cancer patients.

Creatine-mediated crosstalk between adipocytes and cancer cells regulates obesity-driven breast cancer

Obesity is a major risk factor for adverse outcomes in breast cancer; however, the underlying molecular mechanisms have not been elucidated. To investigate the role of crosstalk between mammary adipocytes and neoplastic cells in the tumor microenvironment (TME), we performed transcriptomic analysis of cancer cells and adjacent adipose tissue in a murine model of obesity-accelerated breast cancer and identified glycine amidinotransferase (Gatm) in adipocytes and Acsbg1 in cancer cells as required for obesity-driven tumor progression. Gatm is the rate-limiting enzyme in creatine biosynthesis, and deletion in adipocytes attenuated obesity-driven tumor growth. Similarly, genetic inhibition of creatine import into cancer cells reduced tumor growth in obesity. In parallel, breast cancer cells in obese animals upregulated the fatty acyl-CoA synthetase Acsbg1 to promote creatine-dependent tumor progression. These findings reveal key nodes in the crosstalk between adipocytes and cancer cells in the TME necessary for obesity-driven breast cancer progression.

Identification of Aurora Kinase A as a Biomarker for Prognosis in Obesity Patients with Early Breast Cancer

BACKGROUND

Obesity is associated both with a higher risk of developing breast cancer, particularly in postmenopausal women, and with worse disease outcome for women of all ages. Previous investigation suggested Aurora A kinase was able to partially restore the functionalities of obese adipose-derived mesenchymal stem cells by stabilizing their primary cilia and reestablishing a balance of multiple stemness-associated genes. The association between Aurora A and obesity breast cancer is still unclear. We hypothesized that overexpression of Aurora A was associated with poor survival in obesity breast cancer and the related axis mechanism was involved.

METHODS

A total of 517 primary breast cancer specimens were collected from the First Affiliated Hospital of China Medical University between January 2011 and November 2016. Our independent variable was BMI at baseline, categorized as overweight (BMI ≥25 kg/m2, as obesity cohort), and normal (18.5 ≤ BMI <25 kg/m2, as non-obesity cohort). The immunohistochemical (IHC) staining was performed with Aurora A, Survivin, MMP11, Cyclin B1, and Cathepsin L. Kaplan-Meier curve was used to analyze overall survival in our cohorts and TCGA-BRCA data (GSE3494). Log rank test was used to calculate P values. Protein-protein interaction (PPI) network analysis and MCODE model were used to analyze the Aurora-altered signal pathway from GSE78958.

RESULTS

Among 517 breast patients, Aurora A-positive (staining scores ≥4) was significantly higher in obesity breast carcinoma compared with non-obesity cancer carcinoma (χ 2=9.79, P=0.002), with more frequency in hormone receptor-negative (68.4% vs 77.9%, P=0.015) and HER2-positive patients (28.7% vs 17.9%, P=0.003). High Aurora A expression was remarkably and significantly associated with overall survival (OS) (8-year OS ratio: 69.5% vs 81.1%, OR=1.76, 95% CI: 1.03~3.02, P=0.041) in obesity cohort. Interestingly, higher expression of Aurora A was not associated with a shorter overall survival time among the non-obesity breast cancer (8-year OS ratio: 81.4% vs 85.8%, OR=1.40, 95% CI: 0.79~2.45, P=0.229). As for RFS, the expression levels of Aurora A expression genes have no significance with RFS statistically in non-obesity and obesity patients. Aurora A and lymph node metastases were significantly poor prognostic factors for OS, and borderline significance was noted for high BMI. Kaplan-Meier survival analysis from TCGA database confirmed that the high Aurora A expression group had worse prognosis (HR=1.47, 95% CI: 1.14-1.90, P=0.003). The KEGG pathway enrichment results were consistent with GO biological process term analysis, in which CCNB1 was enriched for upregulated Aurora A. In our samples, Aurora A level on tumor cytoplasm had broad connections with Cyclin B1 by IHC correlation analysis (correlation coefficient = 0.227, P=0.001).

CONCLUSION

Our finding demonstrates here for the first time that high expression of Aurora A was notably correlated with early recurrence and poor overall survival in obesity patients with early breast cancer. The Aurora A-Cyclin B1 axis could be a potential promising therapeutic target for cancer intervention and therapy.

Weighing the Risk: effects of Obesity on the Mammary Gland and Breast Cancer Risk

Obesity is a preventable risk factor for breast cancer following menopause. Regardless of menopausal status, obese women who develop breast cancer have a worsened prognosis. Breast tissue is comprised of mammary epithelial cells organized into ducts and lobules and surrounded by adipose-rich connective tissue. Studies utilizing multiple in vivo models of obesity as well as human breast tissue have contributed to our understanding of how obesity alters mammary tissue. Localized changes in mammary epithelial cell populations, elevated secretion of adipokines and angiogenic mediators, inflammation within mammary adipose tissue, and remodeling of the extracellular matrix may result in an environment conducive to breast cancer growth. Despite these significant alterations caused by obesity within breast tissue, studies have suggested that some, but not all, obesity-induced changes may be mitigated with weight loss. Here, we review our current understanding regarding the impact of obesity on the breast microenvironment, how obesity-induced changes may contribute to breast tumor progression, and the impact of weight loss on the breast microenvironment.

Integration of transcriptomic data in a genome-scale metabolic model to investigate the link between obesity and breast cancer

BACKGROUND

Obesity is a complex disorder associated with an increased risk of developing several comorbid chronic diseases, including postmenopausal breast cancer. Although many studies have investigated this issue, the link between body weight and either risk or poor outcome of breast cancer is still to characterize. Systems biology approaches, based on the integration of multiscale models and data from a wide variety of sources, are particularly suitable for investigating the underlying molecular mechanisms of complex diseases. In this scenario, GEnome-scale metabolic Models (GEMs) are a valuable tool, since they represent the metabolic structure of cells and provide a functional scaffold for simulating and quantifying metabolic fluxes in living organisms through constraint-based mathematical methods. The integration of omics data into the structural information described by GEMs allows to build more accurate descriptions of metabolic states.

RESULTS

In this work, we exploited gene expression data of postmenopausal breast cancer obese and lean patients to simulate a curated GEM of the human adipocyte, available in the Human Metabolic Atlas database. To this aim, we used a published algorithm which exploits a data-driven approach to overcome the limitation of defining a single objective function to simulate the model. The flux solutions were used to build condition-specific graphs to visualise and investigate the reaction networks and their properties. In particular, we performed a network topology differential analysis to search for pattern differences and identify the principal reactions associated with significant changes across the two conditions under study.

CONCLUSIONS

Metabolic network models represent an important source to study the metabolic phenotype of an organism in different conditions. Here we demonstrate the importance of exploiting Next Generation Sequencing data to perform condition-specific GEM analyses. In particular, we show that the qualitative and quantitative assessment of metabolic fluxes modulated by gene expression data provides a valuable method for investigating the mechanisms associated with the phenotype under study, and can foster our interpretation of biological phenomena.

Impact of Obesity on Clinicopathologic Characteristics and Disease Prognosis in Pre- and Postmenopausal Breast Cancer Patients: A Retrospective Institutional Study

PURPOSE

To investigate the association between obesity and breast cancer clinicopathologic characteristics at presentation along with prognostic impact among Jordanian breast cancer patients. Such data are lacking in Arabian countries.

METHODS

In this retrospective study, 348 breast cancer patients were included. Analyses were conducted for associations between body mass index (BMI) and age at diagnosis, tumor clinicopathologic characteristics, and molecular subtypes. Eight prognostic factors were considered, and total prognostic scores were calculated. The analysis was stratified by menopausal status. Multivariate logistic stepwise regression analysis was conducted to identify predictors for breast cancer recurrence and death.

RESULTS

Mean age at diagnosis was 50.98 ± 10.96 years. Mean BMI at diagnosis was 29.52 ± 5.32 kg/m². Mean age at diagnosis was significantly higher for overweight and obese patients compared to underweight/normal patients (P < 0.001). A significant positive correlation was observed between patient age and BMI at diagnosis (r = 0.251, P < 0.001). Grade of carcinoma was significantly correlated with BMI in the whole population examined (P=0.003). Obese breast cancer patients had significantly higher prognostic scores compared to nonobese cases, indicating worse prognostic features at presentation (P=0.034). Stratification of data analysis based on menopausal status revealed significant associations between obesity and each of tumor stage and grade among postmenopausal but not premenopausal patients (P=0.019 and P=0.031, respectively). Similarly, postmenopausal obese patients had significantly higher prognostic scores compared to nonobese counterparts (P=0.007), indicating worse prognosis, a finding which was also absent among premenopausal breast cancer patients. No significant association between BMI with expression status of hormone receptors, HER2, lymphovascular invasion, and molecular subtypes was found among patients. BMI was a significant predictor for disease recurrence in which obese breast cancer patients had greater odds (2-fold) to develop locoregional and distant recurrence compared to nonobese cases (P=0.011).

CONCLUSIONS

Obesity was associated with advanced stage and grade of breast carcinoma at diagnosis. The impact of BMI on clinicopathologic characteristics and prognosis was confined to postmenopausal cases. Jordanian obese breast cancer patients are at greater risk of breast cancer recurrence and reduced survival compared to their nonobese counterparts.

Molecular mechanisms linking high body mass index to breast cancer etiology in post-menopausal breast tumor and tumor-adjacent tissues

PURPOSE

In post-menopausal women, high body mass index (BMI) is an established breast cancer risk factor and is associated with worse breast cancer prognosis. We assessed the associations between BMI and gene expression of both breast tumor and adjacent tissue in estrogen receptor-positive (ER+) and estrogen receptor-negative (ER-) diseases to help elucidate the mechanisms linking obesity with breast cancer biology in 519 post-menopausal women from the Nurses' Health Study (NHS) and NHSII.

METHODS

Differential gene expression was analyzed separately in ER+ and ER- disease both comparing overweight (BMI ≥ 25 to < 30) or obese (BMI ≥ 30) women to women with normal BMI (BMI < 25), and per 5 kg/m² increase in BMI. Analyses controlled for age and year of diagnosis, physical activity, alcohol consumption, and hormone therapy use. Gene set enrichment analyses were performed and validated among a subset of post-menopausal cases in The Cancer Genome Atlas (for tumor) and Polish Breast Cancer Study (for tumor-adjacent).

RESULTS

No gene was differentially expressed by BMI (FDR < 0.05). BMI was significantly associated with increased cellular proliferation pathways, particularly in ER+ tumors, and increased inflammation pathways in ER- tumor and ER- tumor-adjacent tissues (FDR < 0.05). High BMI was associated with upregulation of genes involved in epithelial-mesenchymal transition in ER+ tumor-adjacent tissues.

CONCLUSIONS

This study provides insights into molecular mechanisms of BMI influencing post-menopausal breast cancer biology. Tumor and tumor-adjacent tissues provide independent information about potential mechanisms.

Whole Genome Transcriptome Analysis of the Association between Obesity and Triple-Negative Breast Cancer in Caucasian Women

Background: Triple-negative breast cancer (TNBC) is the most aggressive form of breast cancer, with poor outcomes. The molecular basis of TNBC remains poorly understood. The objective of this exploratory study was to investigate the association between obesity and TNBC in premenopausal and postmenopausal Caucasian women using transcription profiling. Methods: We compared gene expression levels of tumor samples drawn from normal weight, overweight, and obese pre and postmenopausal women diagnosed with TNBC. We performed hierarchical clustering to assess similarity in patterns of gene expression profiles, and conducted network and pathway analysis to identify molecular networks and biological pathways. Results: We discovered gene signatures distinguishing normal weight from obese, normal weight from overweight, and overweight from obese individuals in both premenopausal and postmenopausal women. The analysis revealed molecular networks and biological pathways associating obesity with TNBC. The discovered pathways included the unfolded protein response, endoplasmic reticulum stress, B cell receptor, and autophagy signaling pathways in obese premenopausal women; and the integrin, axonal guidance, ERK/MAPK (extracellular-signal-regulated kinase/mitogen activated protein kinase) and glutathione biosynthesis signaling pathways in obese postmenopausal women. Conclusions: The results suggest that both overweight and obese status are associated with TNBC, highlighting the need for conformation of these results in independent studies.

Functional transcriptomic annotation and protein-protein interaction network analysis identify NEK2, BIRC5, and TOP2A as potential targets in obese patients with luminal A breast cancer

PURPOSE

Although obesity is a risk factor for breast cancer, little effort has been made in the identification of druggable molecular alterations in obese-breast cancer patients. Tumors are controlled by their surrounding microenvironment, in which the adipose tissue is a main component. In this work, we intended to describe molecular alterations at a transcriptomic and protein-protein interaction (PPI) level between obese and non-obese patients.

METHODS AND RESULTS

Gene expression data of 269 primary breast tumors were compared between normal-weight (BMI < 25, n = 130) and obese (IMC > 30, n = 139) patients. No significant differences were found for the global breast cancer population. However, within the luminal A subtype, upregulation of 81 genes was observed in the obese group (FC ≥ 1.4). Next, we explored the association of these genes with patient outcome, observing that 39 were linked with detrimental outcome. Their PPI map formed highly compact cluster and functional annotation analyses showed that cell cycle, cell proliferation, cell differentiation, and cellular response to extracellular stimuli were the more altered functions. Combined analyses of genes within the described functions are correlated with poor outcome. PPI network analyses for each function were to search for druggable opportunities. We identified 16 potentially druggable candidates. Among them, NEK2, BIRC5, and TOP2A were also found to be amplified in breast cancer, suggesting that they could act as strategic players in the obese-deregulated transcriptome.

CONCLUSION

In summary, our in silico analysis describes molecular alterations of luminal A tumors and proposes a druggable PPI network in obese patients with potential for translation to the clinical practice.

Literature review of data-based models for identification of factors associated with racial disparities in breast cancer mortality

In the United States, early detection methods have contributed to the reduction of overall breast cancer mortality but this pattern has not been observed uniformly across all racial groups. A vast body of research literature shows a set of health care, socio-economic, biological, physical, and behavioural factors influencing the mortality disparity. In this paper, we review the modelling frameworks, statistical tests, and databases used in understanding influential factors, and we discuss the factors documented in the modelling literature. Our findings suggest that disparities research relies on conventional modelling and statistical tools for quantitative analysis, and there exist opportunities to implement data-based modelling frameworks for (1) exploring mechanisms triggering disparities, (2) increasing the collection of behavioural data, and (3) monitoring factors associated with the mortality disparity across time.

Dietary oleuropein inhibits tumor angiogenesis and lymphangiogenesis in the B16F10 melanoma allograft model: a mechanism for the suppression of high-fat diet-induced solid tumor growth and lymph node metastasis

Previously, we reported that high-fat-diet (HFD)-induced obesity stimulates melanoma progression in the B16F10 allograft model. In this study, we examined whether oleuropein (OL), the most abundant phenolic compound in olives, inhibits HFD-induced melanoma progression. Four-week-old male C57BL/6N mice were fed a HFD-diet with or without OL. After 16 weeks of feeding, B16F10-luc cells were subcutaneously injected and the primary tumor was resected 3 weeks later. OL suppressed HFD-induced solid tumor growth. In the tumor tissues, OL reduced HFD-induced expression of angiogenesis (CD31, VE-cadherin, VEGF-A, and VEGFR2), lymphangiogenesis (LYVE-1, VEGF-C, VEGF-D, and VEGFR3), and hypoxia (HIF-1α and GLUT-1) markers as well as HFD-induced increases in lipid vacuoles and M2 macrophages (MΦs). All animals were euthanized 2.5 weeks after tumor resection. OL suppressed HFD-induced increases in lymph node (LN) metastasis; expression of VEGF-A, VEGF-C, and VEGF-D in the LN; and M2-MΦs and the size of adipocytes in adipose tissues surrounding LNs. Co-culture results revealed that the crosstalk between B16F10s, M2-MΦs, and differentiated 3T3-L1 cells under hypoxic conditions increased the secretion of VEGF-A and -D, which stimulated tube formation and migration of endothelial cells (HUVECs) and lymphatic endothelial cells (LEC), respectively. Additionally, OL directly inhibited the differentiation of 3T3-L1 preadipocytes and tube formation by HUVECs and LECs. The overall results indicated that dietary OL inhibits lipid and M2-MΦ accumulation in HFD-fed mice, which contributes to decreases in VEGF secretion, thereby leading to inhibition of angiogenesis and lymphangiogenesis.

Cancer-related risk factors and incidence of major cancers by race, gender and region; analysis of the NIH-AARP diet and health study

Background

Racial disparities in the incidence of major cancers may be attributed to differences in the prevalence of established, modifiable risk factors such as obesity, smoking, physical activity and diet.

Methods

Data from a prospective cohort of 566,398 adults aged 50–71 years, 19,677 African-American and 450,623 Whites, was analyzed. Baseline data on cancer-related risk factors such as smoking, alcohol, physical activity and dietary patterns were used to create an individual adherence score. Differences in adherence by race, gender and geographic region were assessed using descriptive statistics, and Cox proportional hazards models were used to determine the association between adherence and cancer incidence.

Results

Only 1.5% of study participants were adherent to all five cancer-related risk factor guidelines, with marked race-, gender- and regional differences in adherence overall. Compared with participants who were fully adherent to all five cancer risk factor criteria, those adherent to one or less had a 76% increased risk of any cancer incidence (HR: 1.76, 95% CI: 1.70 – 1.82), 38% increased risk of breast cancer (HR: 1.38, 95% CI: 1.25 – 1.52), and doubled the risk of colorectal cancer (HR: 2.06, 95% CI: 1.84 – 2.29). However, risk of prostate cancer was lower among participants adherent to one or less compared with those who were fully adherent (HR: 0.79, 95% CI: 0.75 – 0.85). The proportion of cancer incident cases attributable to low adherence was higher among African-Americans compared with Whites for all cancers (21% vs. 19%), and highest for colorectal cancer (25%) regardless of race.

Conclusion

Racial differences in the proportion of cancer incidence attributable to low adherence suggests unique opportunities for targeted cancer prevention strategies that may help eliminate racial disparities in cancer burden among older US adults.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-017-3557-1) contains supplementary material, which is available to authorized users.

Integrative analysis of pathway deregulation in obesity

Obesity is a pandemic disease, linked to the onset of type 2 diabetes and cancer. Transcriptomic data provides a picture of the alterations in regulatory and metabolic activities associated with obesity, but its interpretation is typically blurred by noise. Here, we solve this problem by collecting publicly available transcriptomic data from adipocytes and removing batch effects using singular value decomposition. In this way we obtain a gene expression signature of 38 genes associated to obesity and identify the main pathways involved. We then show that similar deregulation patterns can be detected in peripheral markers, in type 2 diabetes and in breast cancer. The integration of different data sets combined with the study of pathway deregulation allows us to obtain a more complete picture of gene-expression patterns associated with obesity, breast cancer, and diabetes.

The worldwide increase in obesity is extremely worrisome, especially because this condition is associated with a higher risk for diseases such as type 2 diabetes and cancer. Identifying alterations in regulatory and metabolic activities associated with obesity is complicated due to the presence of noise. A team lead by Caterina La Porta from the University of Milan addressed the question from the point of view of big data and extracted a signature of 38 genes associated to obesity from the combination of publicly available gene expression data from obese and lean subjects. The results revealed a similarity between the deregulation patterns observed in obesity and those found in breast cancer and diabetes, providing a clearer picture of the role of obesity in these diseases.

Diagnostic and prognostic values of contrast-enhanced ultrasound in breast cancer: a retrospective study

This study aimed to explore the diagnostic and prognostic values of contrast-enhanced ultrasound (CEUS) in breast cancer. Between September 2009 and October 2011, a total of 143 breast cancer patients and 161 healthy people were selected as case group and control group, respectively. After the identification of lesions by conventional ultrasound, all patients underwent CEUS. The CEUS images were analyzed, and time-intensity curves (TICs) were obtained. Hematoxylin-eosin and immunohistochemistry staining was performed on tissue specimens, according to which the expressions of estrogen receptor (ER), c-erb-B2, p53, and Ki-67 were measured. Multivariate logistic regression analysis was used to compare CEUS and TIC parameters between the two groups. Compared with the control group, cancer patients showed high enhancement, heterogeneous enhancement or defects in the central region, expansion of lesion diameter after enhancement and crab-like blur lesion edges. The peak intensity (PI), relative start time of enhancement, relative PI, and relative area under the curve in the case group were significantly higher than those in the control group. Logistic analysis showed that the uniformity of enhancement, expansion of lesion diameter, and relative PI were significant diagnostic parameters of breast cancer, with area under the curve being 0.798, 0.776, and 0.919, respectively. There were strong associations between CEUS characteristics and expressions of prognostic factors in breast cancer: the heterogeneous enhancement was common in c-erb-B2-positive tumors; the centripetal enhancement occurred more in ER-negative tumors; perforator vessels were often seen in tumors at high histological grade; perfusion defects were common in ER-negative, c-erb-B2-positive, and Ki-67-positive tumors. CEUS is a useful tool for the early diagnosis and prognosis of breast cancer.

Obesity and breast cancer - what's new?

Obesity rates are increasing in the developed and developing world; this has implications for breast cancer risk and outcome. Areas covered: Recent advances relating to the association of obesity with breast cancer are reviewed. Expert commentary: Obesity has been associated with increased risk of postmenopausal hormone receptor positive and premenopausal triple negative breast cancer and with poor prognosis of most types of breast cancer. Obese individuals may present with breast cancer at a more advanced stage and their breast cancer may differ biologically from cancers diagnosed in nonobese women. A picture of a complex, multifactorial biology underlying the obesity-cancer link is emerging, with the identification of obesity-associated tissue and systemic changes that are cancer promoting, enhancing proliferation, invasion and metastasis. Intervention research to ascertain effects of weight loss and of pharmacologic interventions that reverse the metabolic changes of obesity is needed.