BMI change and abdominal circumference are risk factors for breast cancer, even in Asian women

The impact of lipid metabolism on breast cancer: a review about its role in tumorigenesis and immune escape

BACKGROUND

Breast cancer (BC) is the second most frequent type of cancer in the world and most common among women, configuring a major challenge to global health. BC is a complex and heterogeneous disease that can be subdivided into distinct tumor types based on the expression of molecular markers predicting patient outcomes and response to therapy. A growing number of studies have tried to expand the known markers by investigating the association of altered lipid metabolism with BC immune escape, progression, and metastasis. In this review, we describe the metabolic peculiarities of each BC subtype, understanding how this influences its aggressiveness and identifying whether these intrinsic vulnerabilities of each subtype can play a role in therapeutic management and may affect immune system cells in the tumor microenvironment.

CONCLUSION

The evidence suggests so far that when changes occur in lipid pathways, it can affect the availability of structural lipids for membrane synthesis, lipid synthesis, and degradation that contribute to energy homeostasis and cell signaling functions. These findings will guide the next steps on the path to understanding the mechanisms underlying how lipids alterations are related to disparities in chemotherapeutic response and immune escape in BC. Video Abstract.

Using machine learning to identify gene interaction networks associated with breast cancer

BACKGROUND

Breast cancer (BC) is one of the most prevalent cancers worldwide but its etiology remains unclear. Obesity is recognized as a risk factor for BC, and many obesity-related genes may be involved in its occurrence and development. Research assessing the complex genetic mechanisms of BC should not only consider the effect of a single gene on the disease, but also focus on the interaction between genes. This study sought to construct a gene interaction network to identify potential pathogenic BC genes.

METHODS

The study included 953 BC patients and 963 control individuals. Chi-square analysis was used to assess the correlation between demographic characteristics and BC. The joint density-based non-parametric differential interaction network analysis and classification (JDINAC) was used to build a BC gene interaction network using single nucleotide polymorphisms (SNP). The odds ratio (OR) and 95% confidence interval (95% CI) of hub gene SNPs were evaluated using a logistic regression model. To assess reliability, the hub genes were quantified by edgeR program using BC RNA-seq data from The Cancer Genome Atlas (TCGA) and identical edges were verified by logistic regression using UK Biobank datasets. Go and KEGG enrichment analysis were used to explore the biological functions of interactive genes.

RESULTS

Body mass index (BMI) and menopause are important risk factors for BC. After adjusting for potential confounding factors, the BC gene interaction network was identified using JDINAC. LEP, LEPR, XRCC6, and RETN were identified as hub genes and both hub genes and edges were verified. LEPR genetic polymorphisms (rs1137101 and rs4655555) were also significantly associated with BC. Enrichment analysis showed that the identified genes were mainly involved in energy regulation and fat-related signaling pathways.

CONCLUSION

We explored the interaction network of genes derived from SNP data in BC progression. Gene interaction networks provide new insight into the underlying mechanisms of BC.

Obesity and Breast Cancer Risk: The Oncogenic Implications of Metabolic Dysregulation

CONTEXT

Breast cancer is increasing in prevalence in parallel with rising rates of obesity worldwide. Obesity is recognized as a leading modifiable risk factor for the development of breast cancer; however, this association varies considerably by clinicopathologic features, and the underlying mechanisms are complex.

EVIDENCE ACQUISITION

Pubmed literature search using combinations of "obesity," "breast cancer risk," "diet," "exercise," "weight gain," "weight loss," "adipose tissue inflammation," "crown-like structure," "immune markers," "metformin," "gliflozins," "SGLT-2i," "GLP1-RA," and related terms.

EVIDENCE SYNTHESIS

Elevated body mass index and weight gain are associated with increased risk of postmenopausal, hormone receptor-positive breast cancer. Emerging evidence suggests that adverse measures of body composition in individuals of any weight can also confer increased breast cancer risk. Mechanistically, various factors including altered adipokine balance, dysfunctional adipose tissue, dysregulated insulin signaling, and chronic inflammation contribute to tumorigenesis. Weight loss and more specifically fat mass loss through lifestyle and pharmacologic interventions improve serum metabolic and inflammatory markers, sex hormone levels, and measures of breast density, suggesting a link to decreased breast cancer risk.

CONCLUSION

Incorporating markers of metabolic health and body composition measures with body mass index can capture breast cancer risk more comprehensively. Further studies of interventions targeting body fat levels are needed to curb the growing prevalence of obesity-related cancer.

Global Increase in Breast Cancer Incidence: Risk Factors and Preventive Measures

Breast cancer is a global cause for concern owing to its high incidence around the world. The alarming increase in breast cancer cases emphasizes the management of disease at multiple levels. The management should start from the beginning that includes stringent cancer screening or cancer registry to effective diagnostic and treatment strategies. Breast cancer is highly heterogeneous at morphology as well as molecular levels and needs different therapeutic regimens based on the molecular subtype. Breast cancer patients with respective subtype have different clinical outcome prognoses. Breast cancer heterogeneity emphasizes the advanced molecular testing that will help on-time diagnosis and improved survival. Emerging fields such as liquid biopsy and artificial intelligence would help to under the complexity of breast cancer disease and decide the therapeutic regimen that helps in breast cancer management. In this review, we have discussed various risk factors and advanced technology available for breast cancer diagnosis to combat the worst breast cancer status and areas that need to be focused for the better management of breast cancer.

Breast Cancer Mortality Trends and Predictions to 2030 and Its Attributable Risk Factors in East and South Asian Countries

Background

Amidst the rising breast cancer burden in Asia, we aim to predict the future mortality risk due to breast cancer and identify the risk-attributable deaths for breast cancer among East and South Asian countries.

Methods

We used country-level data to predict the trends in the next decade relating to female breast cancer mortality by employing data from 1990 to 2019 from the Global Burden of Disease 2019 study. We used the stochastic mortality modeling and prediction techniques to forecast the age-specific and risk-attributable breast cancer mortality trends at the regional and national levels of East and South Asia.

Results

The number of deaths caused by the breast cancer is predicted to increase in East and South Asian countries in the next decade (2020–2030). Age-standardized death rate (ASDR) of breast cancer is predicted to increase by 7.0% from 9.20/100,000 (95% CI: 6.04–12.12) in 1990 to 9.88/100,000 (95% CI: 7.12–11.4) in 2030 in East Asia, and about 35% increase from 13.4/100,000 (95% CI: 9.21–16.02) in 1990 to 18.1/100,000 (95% CI: 13.23–21.10) in 2030 in South Asia. At the national level, the highest percent change in ASDR between 1990 and 2030 was reported in Pakistan (a 62% increase) and Nepal (a 47% increase). The highest percent change in breast cancer mortality between 2020 and 2030 for females of age group 80–84 years was observed in Pakistan [21.6, (95% CI, 20.6–94.7)], followed by Afghanistan [13.3 (4.0–80.8)], and Nepal [36.6 (11.1–125.7)] as compared to the other countries. In the females of aged 50–80 years, the predicted death rates were associated with high body mass index, high-fasting plasma glucose, and diet high in red meat, across the majority of countries under study. Furthermore, reductions in percent change in mortality rates occurred in several countries with increases in sociodemographic index (SDI), notably across high SDI countries.

Conclusion

Breast cancer mortality risk varies substantially across East and South Asian countries with higher mortality risk in low/middle SDI countries. Early detection using screening, awareness among females and health workers, and cost-effective and timely treatment of patients with breast cancer is vital in stemming the tide of breast cancer in the next decade.

Could Self-Reported Body Sizes be An Alternative Tool for Assessing Breast Cancer Risk in Postmenopausal Women?

Background: The use of self-reported body size as an alternative tool to estimate body weight for health risk assessment is not widely reported, especially in relation to breast cancer. Therefore, we examined the association between breast cancer and body-mass index (BMI) and the usefulness of pictograms. Methods: The case–control study was conducted among postmenopausal women from 2015 to 2019. The study involved 151 women with breast cancer and 67 control subjects. Data were collected by a self-reported detailed questionnaire. Results: An increased, 4.13-fold risk of breast cancer (OR = 4.13; 95% CI [1.69, 10.28]) was observed for women with BMI 25.0–29.9 kg/m² compared to women with normal BMI (18.5–24.9 kg/m²), whereas the association in the case of obese women was not statistically significant. An increased risk of breast cancer was observed for pictogram scores 3–4 (OR = 8.95; 95% CI [3.22, 24.88]) and for the highest level of self-reported body size, pictograms ≥ 5 (OR = 3.20; 95% CI [1.13, 9.09]). Conclusions: The risk of breast cancer is associated with an increased BMI and visual overweigh and obesity. The results suggest that a self-reporting alternative tool can be used to assess the prevalence of overweight/obesity, particularly in situations where no other tools are available.

Associations between ADIPOQ rs2241766 SNP and breast cancer risk: a systematic review and a meta-analysis

Purpose

We aimed to conduct a meta-analysis to accurately evaluate the potential association between ADIPOQ rs2241766 gene SNP and breast cancer risk.

Methods

A systematic literature search on Cochrane Library, PubMed, Embase, Web of Science and China National Knowledge Infrastructure (CNKI) identified 8 articles with 1692 cases and 1890 controls. Strength of association was evaluated by pooled odds ratio (OR), 95 % confidence interval (CI) and p value. Funnel plots and Begger’s regression test were applied for testing the publication bias. Statistical analysis of all data was performed by Stata 12.0.

Results

The meta-analysis results indicated that the ADIPOQ rs2241766 gene polymorphism did not significantly associated with the risk of breast cancer for these genetic models (TT vs. TG + GG: OR = 1.20, 95 % CI = 0.77–1.89, p=0.417; TT + TG vs. GG: OR = 1.05, 95 % CI = 0.71–1.56, p=0.805; T vs. G: OR =1.17, 95 % CI = 0.79–1.74, p=0.437).

Conclusions

This study indicated that no significant relationship between the ADIPOQ rs2241766 SNP and breast cancer. Further large-scale and well-designed studies will be indispensable to confirm our result.

Association of body composition with odds of breast cancer by molecular subtype: analysis of the Mechanisms for Established and Novel Risk Factors for Breast Cancer in Nigerian Women (MEND) study

BACKGROUND

The association between obesity and breast cancer (BC) has been extensively studied among US, European and Asian study populations, with often conflicting evidence. However, despite the increasing prevalence of obesity and associated conditions in Africa, the continent with the highest age-standardized BC mortality rate globally, few studies have evaluated this association, and none has examined in relation to molecular subtypes among African women. The current analysis examines the association between body composition, defined by body mass index (BMI), height, and weight, and BC by molecular subtype among African women.

METHODS

We estimated odds ratios (ORs) and 95% confidence intervals (95% CI) for the association between measures of body composition and BC and molecular subtypes among 419 histologically confirmed cases of BC and 286 healthy controls from the Mechanisms for Established and Novel Risk Factors for Breast Cancer in Women of Nigerian Descent (MEND) case-control study.

RESULTS

Higher BMI (aOR: 0.79; 95% CI: 0.67, 0.95) and weight (aOR: 0.83; 95% CI: 0.69, 0.98) were associated with reduced odds of BC in adjusted models, while height was associated with non-statistically significant increased odds of BC (aOR: 1.07, 95% CI: 0.90, 1.28). In pre/peri-menopausal, but not post-menopausal women, both higher BMI and weight were significantly associated with reduced odds of BC. Further, higher BMI was associated with reduced odds of Luminal A, Luminal B, and HER2-enriched BC among pre/peri-menopausal women, and reduced odds of triple-negative BC among post-menopausal women.

CONCLUSIONS

Higher BMI and weight were associated with reduced odds of BC overall and by molecular subtype among West African women. Larger studies of women of African descent are needed to definitively characterize these associations and inform cancer prevention strategies.

Evaluation of the eating habits of breast cancer patients

Objective:

To determine the relationship between the dietary characteristics of breast cancer patients.

Methods:

Patients with breast cancer whose treatments have finished and are in remission formed the study group and healthy people formed the control group. Demographic, anthropometric characteristics, food consumption frequency form and exercise status were recorded with all groups. Data analysis was done by SPSS 22.

Results:

In the study group, mean carbohydrate percentage was lower, while fat, fat percentage, monosaccharide, glucose, fructose, omega3(n3), saturated fatty acids(SFA), monounsaturated fatty acids (MUFA), vitamin A, C, E, B6, biotin and copper values were significantly higher (p<0.05). Recurrence was observed in seven patients (7.1%) during the follow-up period, hormone receptor levels (ER) and vitamin B2 intake (accuracy 93.9%) were inversely related to the recurrence of the disease (p=0.02).

Conclusions:

While the percentage of carbohydrate taken was lower in study group; total fat, n3, SFA, MUFA, monosaccharide, glucose, fructose, water-soluble fiber, B6, biotin and copper values were higher. Further studies are needed for vitamin B2 deficiency in patients with recurrence

High-sensitivity C-reactive protein, hemoglobin A1c and breast cancer risk: a nested case-control study from Alberta's Tomorrow Project cohort

PURPOSE

Our aim is to examine the associations between high-sensitivity C-reactive protein (hsCRP) and hemoglobin A1c (HbA1c), common biomarkers of inflammation and insulin resistance, respectively, with breast cancer risk, while adjusting for measures of excess body size.

METHODS

We conducted a nested case-control study within the Alberta's Tomorrow Project cohort (Alberta, Canada) including 197 incident breast cancer cases and 394 matched controls. The sample population included both pre- and postmenopausal women. Serum concentrations of hsCRP and HbA1c were measured from blood samples collected at baseline, along with anthropometric measurements, general health and lifestyle data. Conditional logistic regression was used to evaluate associations between hsCRP, HbA1c, and breast cancer risk adjusted for excess body size (body fat percentage) and other risk factors for breast cancer.

RESULTS

Higher concentrations of hsCRP were associated with elevated breast cancer risk (odds ratio [OR] 1.27; 95% confidence interval [95% CI] 1.03-1.55). The observed associations were unchanged with adjustment for body fat percentage. Higher HbA1c concentrations were not significantly associated with an increased breast cancer risk (OR 1.22; 95% CI 0.17-8.75).

CONCLUSION

These data suggest that hsCRP may be associated with elevated breast cancer risk, independent of excess body size. However, elevated concentrations of HbA1c did not appear to increase breast cancer risk in apparently healthy women.

Breast cancer

Breast cancer is the most frequent malignancy in women worldwide and is curable in ~70-80% of patients with early-stage, non-metastatic disease. Advanced breast cancer with distant organ metastases is considered incurable with currently available therapies. On the molecular level, breast cancer is a heterogeneous disease; molecular features include activation of human epidermal growth factor receptor 2 (HER2, encoded by ERBB2), activation of hormone receptors (oestrogen receptor and progesterone receptor) and/or BRCA mutations. Treatment strategies differ according to molecular subtype. Management of breast cancer is multidisciplinary; it includes locoregional (surgery and radiation therapy) and systemic therapy approaches. Systemic therapies include endocrine therapy for hormone receptor-positive disease, chemotherapy, anti-HER2 therapy for HER2-positive disease, bone stabilizing agents, poly(ADP-ribose) polymerase inhibitors for BRCA mutation carriers and, quite recently, immunotherapy. Future therapeutic concepts in breast cancer aim at individualization of therapy as well as at treatment de-escalation and escalation based on tumour biology and early therapy response. Next to further treatment innovations, equal worldwide access to therapeutic advances remains the global challenge in breast cancer care for the future.

Negative prognostic value of intra-ductal fat infiltrate in breast cancer

BACKGROUND

Recent studies showed a correlation between Body Mass Index and both breast cancer occurrence and progression. Nevertheless, no study reported an accurate evaluation of intra-ductal fat infiltrate. Therefore, the main aim of this study was to evaluate the putative association between intra-ductal fat infiltrate (IDFi) and breast cancer subtypes by using digital pathology.

METHODS

We retrospectively collected 220 breast biopsies. Paraffin serial sections were used for haematoxylin and eosin staining and immunohistochemical evaluation of the following markers: estrogen receptor (ER), progesterone receptor (PR), Ki67 and c-erb2. Three haematoxylin and eosin sections for each paraffin block were digitalized. Digital slides were used to evaluate the areas of IDFi. Five randomized areas were evaluated for each slide. By using GraphPad software IDFi areas was correlated with a) breast cancer histotype, b) presence of microcalcifications and c) biomarkers expression.

RESULTS

Breast biopsies were classified as follow: 20 normal breast, 50 benign lesions, and 150 malignant lesions (85 ductal in situ carcinomas; 65 ductal infiltrating carcinomas). Statistical analysis showed a significant increase of IDFi in malignant lesions as compared to both normal breast and benign lesions. We noted higher IDFi in breast ductal carcinomas as compared to lobular lesions. Significant differences were observed between breast lesions with microcalcifications respect to lesions without calcifications. Noteworthy, we also found a positive association between IDFi and the expression of both ER and Ki67.

CONCLUSION

Results of our study highlighted the possible role of fat in breast cancer progression suggesting a negative prognostic value of IDFi.

Switching from a high-fat cellulose diet to a high-fat pectin diet reverses certain obesity-related morbidities

Background

Reducing caloric intake is a proven intervention for mitigating and modulating morbidities associated with overnutrition. Caloric restriction is difficult to affect clinically, therefore, dietary interventions that ameliorate the adverse consequences of overnutrition in the presence of a high-calorie diet would be of value.

Methods

Mice were fed an obesogenic diet containing 60% fat + 10% cellulose (HFC), or a control diet containing 10% fat + 10% cellulose (LFC) for 12 wks. Subgroups of mice were then switched from HFC to each of the following diets for an additional 5 wks: 1) 60% fat + 10% pectin (HFP), 2) LFC or 3) 10% fat + 10% pectin (LFP). To test for statistical differences, one-way or two-way ANOVAs were used with or without repeated measurements as needed.

Results

In comparison to HFC, HFP prevented additional weight gain while LFC and LFP triggered weight loss of 22.2 and 25.4%, respectively. Mice continued on HFC experienced a weight increase of 26% during the same 5 wk. interval. After 12 wks, HFC decreased mouse locomotion by 18% when compared to control diet, but a diet switch to LFC or LFP restored mouse movement. Importantly, HFP, LFC, and LFP reduced fasting blood glucose when compared to HFC. Likewise, HFP, LFC and LFP improved glucose tolerance and decreased fatty liver by 37.9, 49.8, 53.6 and 20.2%, 37.2, 43.7%, respectively.

Conclusions

Taken together, the results indicate that the dietary fiber pectin can mitigate some adverse consequences of overnutrition even in the presence of high-fat.

Assessment of potential risk factors for breast cancer in a population in Southern Brazil

PURPOSE

The aim of this study is to assess potential risk factors for breast cancer in a population in Southern Brazil and build a multivariate logistic model using these factors for breast cancer risk prediction.

METHODS

A total of 4242 women between 40 and 69 years of age without a history of breast cancer were selected at primary healthcare facilities in Porto Alegre and submitted to mammographic screening. They were evaluated for potential risk factors.

RESULTS

In all, 73 participants among the 4242 women had a breast cancer diagnosis during the follow-up of the project (10 years). The multivariate analysis considering all the patients aged 40-69 years showed that older age (OR 1.08, 95% CI 1.04-1.12), higher height (OR 1.04, 95% CI 1.01-1.09), and history of previous breast biopsy (OR 2.66, 95% CI 1.38-5.13) were associated with the development of breast cancer. Conversely, the number of pregnancies (OR 0.87, 95% CI 0.78-0.98) and use of hormone replacement therapy (OR 0.39, 95% CI 0.20-0.75) were considered a protective factor. Additionally, we performed an analysis separating the participants into groups of 40-49 and 50-69 years old, since a risk factor could have a specific behavior in these age groups. No additional risk factors were identified within these age brackets, and some factors lost statistical significance.

CONCLUSION

The risk prediction model indicates that the following variables should be assessed in this specific population: age, height, having had previous breast biopsies, number of pregnancies, and use of hormone replacement therapy. These findings may help to better understand the causal model of breast cancer in Southern Brazil.