Cancer Risk in Normal Weight Individuals with Metabolic Obesity: A Narrative Review

Change in Metabolic Markers and the Risk of Skin Cancer: Results from the Lifelines Cohort Study in the Netherlands

BACKGROUND

Skin cancers are the most common cancers in Caucasians, and their incidence is rising. Although metabolic and anthropometric markers play a role in cancer development, the relationship between metabolic and anthropometric changes in skin cancer remains unclear. This study aimed to examine possible associations between these changes and the risk of skin cancer.

METHODS

Participants without prior skin cancer history from the Northern Netherlands representative of the general population were included. Histopathology data were obtained from the Dutch Nationwide Pathology Database. Adjusted Cox regression analyzed associations between metabolic changes and time to pathology-confirmed skin cancer incidence over a 7-year follow-up, assessing overall skin cancer risk and subtypes, including melanoma and nonmelanoma skin cancer.

RESULTS

Out of 97,106 participants, 4,195 (4.3%) developed skin cancer. Decrease and increase in body mass index (BMI) were both associated with lower skin cancer risk: adjusted HRs (aHR) of 0.88 (0.80-0.98) and 0.78 (0.72-0.86), respectively. Triglyceride and waist-to-hip ratio decreases were also associated with lower risk: aHR: 0.89 (0.80-0.98) and 0.89 (0.83-0.98), respectively. Increase in Hemoglobin A1c (HbA1c) was associated with a higher risk in individuals below the age of 45 years at baseline: aHR: 1.21 (1.01-1.45). Subtype analysis showed an increase in BMI was associated with lower melanoma risk: aHR: 0.72 (0.58-0.91).

CONCLUSIONS

Changes in BMI and decrease in triglycerides and waist-to-hip ratio are related to lower skin cancer risk, whereas an increase in HbA1c may elevate risk in individuals younger than 45 at baseline. These findings highlight the importance of non-sunlight-related risk factors for skin cancer prevention and the need for further research into underlying mechanisms.

IMPACT

This study contributes to the broader understanding of how metabolic health impacts skin cancer development, offering potential avenues for targeted prevention strategies.

Metabolic Phenotype and Risk of Obesity-Related Cancers in the Women's Health Initiative

Body mass index (BMI) may misclassify obesity-related cancer (ORC) risk, as metabolic dysfunction can occur across BMI levels. We hypothesized that metabolic dysfunction at any BMI increases ORC risk compared with normal BMI without metabolic dysfunction. Postmenopausal women (n = 20,593) in the Women's Health Initiative with baseline metabolic dysfunction biomarkers [blood pressure, fasting triglycerides, high-density lipoprotein cholesterol, fasting glucose, homeostatic model assessment for insulin resistance (HOMA-IR), and high-sensitive C-reactive protein (hs-CRP)] were included. Metabolic phenotype (metabolically healthy normal weight, metabolically unhealthy normal weight, metabolically healthy overweight/obese, and metabolically unhealthy overweight/obese) was classified using four definitions of metabolic dysfunction: (i) Wildman criteria, (ii) National Cholesterol Education Program Adult Treatment Panel III, (iii) HOMA-IR, and (iv) hs-CRP. Multivariable Cox proportional hazards regression, with death as a competing risk, was used to assess the association between metabolic phenotype and ORC risk. After a median (IQR) follow-up duration of 21 (IQR, 15-22) years, 2,367 women developed an ORC. The risk of any ORC was elevated among metabolically unhealthy normal weight (HR = 1.12, 95% CI, 0.90-1.39), metabolically healthy overweight/obese (HR = 1.15, 95% CI, 1.00-1.32), and metabolically unhealthy overweight/obese (HR = 1.35, 95% CI, 1.18-1.54) individuals compared with metabolically healthy normal weight individuals using Wildman criteria. The results were similar using Adult Treatment Panel III criteria, hs-CRP alone, or HOMA-IR alone to define metabolic phenotype. Individuals with overweight or obesity with or without metabolic dysfunction were at higher risk of ORCs compared with metabolically healthy normal weight individuals. The magnitude of risk was greater among those with metabolic dysfunction, although the CIs of each category overlapped. Prevention Relevance: Recognizing metabolic dysfunction as a significant risk factor for ORCs underscores the importance of preventive measures targeting metabolic health improvement across all BMI categories.

Predicting Postoperative Lung Cancer Recurrence and Survival Using Cox Proportional Hazards Regression and Machine Learning

BACKGROUND

Surgical resection remains the standard treatment for early-stage lung cancer. However, the recurrence rate after surgery is unacceptably high, ranging from 30% to 50%. Despite extensive efforts, accurately predicting the likelihood and timing of recurrence remains a significant challenge. This study aims to predict postoperative recurrence by identifying novel image biomarkers from preoperative chest CT scans.

METHODS

A cohort of 309 patients was selected from 512 non-small-cell lung cancer patients who underwent lung resection. Cox proportional hazards regression analysis was employed to identify risk factors associated with recurrence and was compared with machine learning (ML) methods for predictive performance. The goal is to improve the ability to predict the risk and time of recurrence in seemingly "cured" patients, enabling personalized surveillance strategies to minimize lung cancer recurrence.

RESULTS

The Cox hazards analyses identified surgical procedure, TNM staging, lymph node involvement, body composition, and tumor characteristics as significant determinants of recurrence risk, both for local/regional and distant recurrence, as well as recurrence-free survival (RFS) and overall survival (OS) (p < 0.05). ML models and Cox models exhibited comparable predictive performance, with an area under the receiver operative characteristic (ROC) curve (AUC) ranging from 0.75 to 0.77.

CONCLUSIONS

These promising findings demonstrate the feasibility of predicting postoperative lung cancer recurrence and survival time using preoperative chest CT scans. However, further validation using larger, multisite cohort is necessary to ensure robustness and facilitate integration into clinical practice for improved cancer management.

Nutrition, GH/IGF-1 signaling, and cancer

Cancer is the second leading cause of death in the United States and among the most prevalent diseases globally, with an incidence expected to grow because of smoking, pollution, poor dietary habits, obesity, and the rise in the older population. Given their ability to reduce risk factors, albeit with varying efficacy, nutrition and fasting could help prevent cancer and other age-related disorders. Calorie restriction (CR), various forms of intermittent fasting (IF) or periodic fasting (PF), and fasting-mimicking diets (FMDs) have been shown to improve health span, increase lifespan, and prevent or postpone cancer in rodents. The effects of specific diets and fasting regimens on aging and cancer appear to be mediated in part by the reduction in the activity of the growth hormone (GH)/insulin-like-growth-factor-I (IGF-1) axis. Nevertheless, recent data indicate that the alternation of low and normal levels of these hormones and factors may be ideal for optimizing longevity and function. Here, we review the role of nutrition, CR, and fasting/FMD on cancer, focusing on the hypothesis that the modulation of GH, IGF-1, and insulin signaling partly mediates the effect of these dietary interventions on cancer prevention.

Genetics, diet, microbiota, and metabolome: partners in crime for colon carcinogenesis

Colorectal cancer (CRC) ranks among the most prevalent malignant tumors worldwide, with a multifactorial etiology encompassing genetic, environmental, and life-style factors, as well as the intestinal microbiota and its metabolome. These risk factors often work together in specific groups of patients, influencing how CRC develops and progresses. Importantly, alterations in the gut microbiota act as a critical nexus in this interplay, significantly affecting susceptibility to CRC. This review highlights recent insights into unmodifiable and modifiable risk factors for CRC and how they might interact with the gut microbiota and its metabolome. Understanding the mechanisms of these interactions will help us develop targeted, precision-medicine strategies that can adjust the composition of the gut microbiota to meet individual health needs, preventing or treating CRC more effectively.

Mechanistic Association of Hepatoblastoma with Cerebral Palsy: A Narrative Review

Hepatoblastoma is a rare liver cancer that occurs most often in children who present with lower birth weight. Cerebral palsy (CP) is a neurodevelopmental disorder distinguished by irregularities in muscle tone, movement, and motor skills. CP is caused by damage to the developing brain and is often associated with secondary complications such as severe constipation. Clinicians must be aware of sudden worsening constipation occurring in CP children because it can also be a sign of hepatoblastoma. The aim of this review is to summarize the current understanding of the risks for hepatoblastoma development in children with CP. Cancer risks likely include dysfunction of the immune system surveillance in CP children. Elevated C-reactive protein and tumor necrosis factor-alpha levels may be higher in children with CP, which weakens their innate immune system. Metabolic disruption increases the risk of some cancers, and poor nutrition and reduced growth that occur in CP patients may have an impact on cancer development through a loss in immune function. Increased mobility and physical activity can increase the T-cell, natural killer cell, and neutrophil population. Children with CP tend to engage poorly in physical activity, and consequently, their immune system is affected. There are multiple factors associated with CP that increase the risk of childhood cancers such as hepatoblastoma.

Dietary intervention for adult survivors of cancers other than breast cancer: A systematic review

INTRODUCTION

Healthy eating and weight control are recommended for cancer survivors; however, dietary interventions are not routinely offered to them. This study aimed to assess the effects of dietary interventions on survival, nutritional status, morbidity, dietary changes, health-related quality of life (QOL), and clinical measures in cancer survivors.

METHODS

Searches were conducted from October 1, 2018 to November 21, 2011 in the Medline, EMBASE, CENTRAL, Emcare, and DARE electronic databases. We included randomized controlled trials (RCTs) that involved individuals diagnosed with cancer, excluding conference abstracts, case studies, other reviews, and meta-analyses, and screened the articles.

RESULTS

Eight studies were included in this meta-analysis. We observed significant improvements in QOL and clinical data in 3 of 6 studies and in one study, respectively, significant weight loss on anthropometry in 2 of 5 studies, and dietary improvement in 4 of 5 studies of adult cancer survivors. However, we did not observe any benefits of dietary intervention for cancer survivors with undernutrition.

DISCUSSION

Dietary interventions for adult cancer survivors might contribute to improving their nutritional status; however, further clarification requires a study that standardizes the intervention method. Furthermore, RCTs are required to determine the effects on cancer survivors with undernutrition.

Prevalence of health behaviors among cancer survivors in the United States

PURPOSE

We determined the proportion of cancer survivors who met each of five health behavior guidelines recommended by the American Cancer Society (ACS), including consuming fruits and vegetables at least five times/day, maintaining a body mass index (BMI) < 30 kg/m2, engaging in 150 min or more of physical activity weekly, not currently smoking, and not excessively drinking alcohol.

METHODS

Using data from the 2019 Behavioral Risk Factor Surveillance System (BRFSS), 42,727 survey respondents who reported a previous diagnosis of cancer (excluding skin cancer) were included. Weighted percentages with 95% confidence intervals (95% CI) were estimated for the five health behaviors accounting for BRFSS' complex survey design.

RESULTS

The weighted percentage of cancer survivors who met ACS guidelines was 15.1% (95%CI: 14.3%, 15.9%) for fruit and vegetable intake; 66.8% (95%CI: 65.9%, 67.7%) for BMI < 30 kg/m2; 51.1% (95%CI: 50.1%, 52.1%) for physical activity; 84.9% (95%CI: 84.1%, 85.7%) for not currently smoking; and 89.5% (95%CI: 88.8%, 90.3%) for not drinking excessive alcohol. Adherence to ACS guidelines among cancer survivors generally increased with increasing age, income, and education.

CONCLUSIONS

While the majority of cancer survivors met the guidelines for not smoking and limiting alcohol drinking, one-third had elevated BMI, almost half did not meet recommended physical activity levels, and the majority had inadequate fruit and vegetable intake.

IMPLICATIONS FOR CANCER SURVIVORS

Adherence to guidelines was lowest among younger cancer survivors and those with lower income and education, suggesting these may be populations where resources could be targeted to have the greatest impact.

Automatic deep learning method for third lumbar selection and body composition evaluation on CT scans of cancer patients

Introduction

The importance of body composition and sarcopenia is well-recognized in cancer patient outcomes and treatment tolerance, yet routine evaluations are rare due to their time-intensive nature. While CT scans provide accurate measurements, they depend on manual processes. We developed and validated a deep learning algorithm to automatically select and segment abdominal muscles [SM], visceral fat [VAT], and subcutaneous fat [SAT] on CT scans.

Materials and Methods

A total of 352 CT scans were collected from two cancer centers. The detection of the third lumbar vertebra and three different body tissues (SM, VAT, and SAT) were annotated manually. The 5-fold cross-validation method was used to develop the algorithm and validate its performance on the training cohort. The results were validated on an external, independent group of CT scans.

Results

The algorithm for automatic L3 slice selection had a mean absolute error of 4 mm for the internal validation dataset and 5.5 mm for the external validation dataset. The median DICE similarity coefficient for body composition was 0.94 for SM, 0.93 for VAT, and 0.86 for SAT in the internal validation dataset, whereas it was 0.93 for SM, 0.93 for VAT, and 0.85 for SAT in the external validation dataset. There were high correlation scores with sarcopenia metrics in both internal and external validation datasets.

Conclusions

Our deep learning algorithm facilitates routine research use and could be integrated into electronic patient records, enhancing care through better monitoring and the incorporation of targeted supportive measures like exercise and nutrition.

Normal-Weight Obesity and Metabolic Syndrome in Korean Adults: A Population-Based Cross-Sectional Study

BACKGROUND

The disadvantage of using body mass index (BMI) as an obesity diagnostic tool is that it cannot distinguish between fat mass and lean mass, which may understate the impact of obesity on metabolic complications. This population-based cross-sectional study aimed to investigate the relationship between normal-weight obesity (NWO) and metabolic syndrome in Korean adults aged 20 years (5962 males and 6558 females) who took part in the Korea National Health and Nutrition Examination Surveys from 2008 to 2011.

METHODS

NWO was defined as having a BMI of 18.5 to 24.9 kg/m2 and a body fat percentage of 26.0% in males or 36.0% in females. Metabolic syndrome (MetS) was defined using the revised National Cholesterol Education Program definition, with a Korean-specific waist circumference threshold of >90 cm for males and >85 cm for females.

RESULTS

NWO males and females were 2.7 times (p < 0.001) and 1.9 times (p < 0.001) more likely to develop metabolic syndrome than normal-weight non-obese males and females, respectively. Additionally, NWO females were 1.3 times (p = 0.027) more likely to develop MetS even after adjustments for all measured covariates.

CONCLUSIONS

The current findings of the study show that NWO is a proxy biomarker of MetS to be considered for early intervention.

CT-derived body composition associated with lung cancer recurrence after surgery

OBJECTIVES

To evaluate the impact of body composition derived from computed tomography (CT) scans on postoperative lung cancer recurrence.

METHODS

We created a retrospective cohort of 363 lung cancer patients who underwent lung resections and had verified recurrence, death, or at least 5-year follow-up without either event. Five key body tissues and ten tumor features were automatically segmented and quantified based on preoperative whole-body CT scans (acquired as part of a PET-CT scan) and chest CT scans, respectively. Time-to-event analysis accounting for the competing event of death was performed to analyze the impact of body composition, tumor features, clinical information, and pathological features on lung cancer recurrence after surgery. The hazard ratio (HR) of normalized factors was used to assess individual significance univariately and in the combined models. The 5-fold cross-validated time-dependent receiver operating characteristics analysis, with an emphasis on the area under the 3-year ROC curve (AUC), was used to characterize the ability to predict lung cancer recurrence.

RESULTS

Body tissues that showed a standalone potential to predict lung cancer recurrence include visceral adipose tissue (VAT) volume (HR = 0.88, p = 0.047), subcutaneous adipose tissue (SAT) density (HR = 1.14, p = 0.034), inter-muscle adipose tissue (IMAT) volume (HR = 0.83, p = 0.002), muscle density (HR = 1.27, p < 0.001), and total fat volume (HR = 0.89, p = 0.050). The CT-derived muscular and tumor features significantly contributed to a model including clinicopathological factors, resulting in an AUC of 0.78 (95% CI: 0.75-0.83) to predict recurrence at 3 years.

CONCLUSIONS

Body composition features (e.g., muscle density, or muscle and inter-muscle adipose tissue volumes) can improve the prediction of recurrence when combined with clinicopathological factors.

The Role of Selected Adipocytokines in Ovarian Cancer and Endometrial Cancer

Due to their multidirectional influence, adipocytokines are currently the subject of numerous intensive studies. Significant impact applies to many processes, both physiological and pathological. Moreover, the role of adipocytokines in carcinogenesis seems particularly interesting and not fully understood. For this reason, ongoing research focuses on the role of these compounds in the network of interactions in the tumor microenvironment. Particular attention should be drawn to cancers that remain challenging for modern gynecological oncology-ovarian and endometrial cancer. This paper presents the role of selected adipocytokines, including leptin, adiponectin, visfatin, resistin, apelin, chemerin, omentin and vaspin in cancer, with a particular focus on ovarian and endometrial cancer, and their potential clinical relevance.

Metabolic Health, Obesity, and Intraocular Pressure

Obesity has been associated with increased intraocular pressure (IOP), but the results are inconsistent. Recently, a subgroup of obese individuals with good metabolic profiles were suggested to have better clinical outcomes than normal-weight individuals with metabolic diseases. The relationships between IOP and different combinations of obesity and metabolic health status have not been investigated. Therefore, we investigated the IOP among groups with different combinations of obesity status and metabolic health status. We examined 20,385 adults aged 19 to 85 years at the Health Promotion Center of Seoul St. Mary's Hospital between May 2015 and April 2016. Individuals were categorized into four groups according to obesity (body mass index (BMI) ≥ 25 kg/m²) and metabolic health status (defined based on prior medical history or abdominal obesity, dyslipidemia, low high-density lipoprotein cholesterol, high blood pressure, or high fasting blood glucose levels upon medical examination). ANOVA and ANCOVA were performed to compare the IOP among the subgroups. The IOP of the metabolically unhealthy obese group (14.38 ± 0.06 mmHg) was the highest, followed by that of the metabolically unhealthy normal-weight group (MUNW, 14.22 ± 0.08 mmHg), then, the metabolically healthy groups (p < 0.001; 13.50 ± 0.05 mmHg and 13.06 ± 0.03 mmHg in the metabolically healthy obese (MHO) and metabolically healthy normal-weight groups, respectively). Subjects who were metabolically unhealthy showed higher IOP compared to their counterparts who were metabolically healthy at all BMI levels, and there was a linear increase in IOP as the number of metabolic disease components increased, but no difference between normal-weight vs. obese individuals. While obesity, metabolic health status, and each component of metabolic disease were associated with higher IOP, those who were MUNW showed higher IOP than those who were MHO, which indicates that metabolic status has a greater impact than obesity on IOP.

The crosstalk within the breast tumor microenvironment in type II diabetes: Implications for cancer disparities

Obesity-driven (type 2) diabetes (T2D), the most common metabolic disorder, both increases the incidence of all molecular subtypes of breast cancer and decreases survival in postmenopausal women. Despite this clear link, T2D and the associated dysfunction of diverse tissues is often not considered during the standard of care practices in oncology and, moreover, is treated as exclusion criteria for many emerging clinical trials. These guidelines have caused the biological mechanisms that associate T2D and breast cancer to be understudied. Recently, it has been illustrated that the breast tumor microenvironment (TME) composition and architecture, specifically the surrounding cellular and extracellular structures, dictate tumor progression and are directly relevant for clinical outcomes. In addition to the epithelial cancer cell fraction, the breast TME is predominantly made up of cancer-associated fibroblasts, adipocytes, and is often infiltrated by immune cells. During T2D, signal transduction among these cell types is aberrant, resulting in a dysfunctional breast TME that communicates with nearby cancer cells to promote oncogenic processes, cancer stem-like cell formation, pro-metastatic behavior and increase the risk of recurrence. As these cells are non-malignant, despite their signaling abnormalities, data concerning their function is never captured in DNA mutational databases, thus we have limited insight into mechanism from publicly available datasets. We suggest that abnormal adipocyte and immune cell exhaustion within the breast TME in patients with obesity and metabolic disease may elicit greater transcriptional plasticity and cellular heterogeneity within the expanding population of malignant epithelial cells, compared to the breast TME of a non-obese, metabolically normal patient. These challenges are particularly relevant to cancer disparities settings where the fraction of patients seen within the breast medical oncology practice also present with co-morbid obesity and metabolic disease. Within this review, we characterize the changes to the breast TME during T2D and raise urgent molecular, cellular and translational questions that warrant further study, considering the growing prevalence of T2D worldwide.

Estimating 3-D whole-body composition from a chest CT scan

BACKGROUND

Estimating whole-body composition from limited region-computed tomography (CT) scans has many potential applications in clinical medicine; however, it is challenging.

PURPOSE

To investigate if whole-body composition based on several tissue types (visceral adipose tissue [VAT], subcutaneous adipose tissue [SAT], intermuscular adipose tissue [IMAT], skeletal muscle [SM], and bone) can be reliably estimated from a chest CT scan only.

METHODS

A cohort of 97 lung cancer subjects who underwent both chest CT scans and whole-body positron emission tomography-CT scans at our institution were collected. We used our in-house software to automatically segment and quantify VAT, SAT, IMAT, SM, and bone on the CT images. The field-of-views of the chest CT scans and the whole-body CT scans were standardized, namely, from vertebra T1 to L1 and from C1 to the bottom of the pelvis, respectively. Multivariate linear regression was used to develop the computer models for estimating the volumes of whole-body tissues from chest CT scans. Subject demographics (e.g., gender and age) and lung volume were included in the modeling analysis. Ten-fold cross-validation was used to validate the performance of the prediction models. Mean absolute difference (MAD) and R-squared (R2 ) were used as the performance metrics to assess the model performance.

RESULTS

The R2 values when estimating volumes of whole-body SAT, VAT, IMAT, total fat, SM, and bone from the regular chest CT scans were 0.901, 0.929, 0.900, 0.933, 0.928, and 0.918, respectively. The corresponding MADs (percentage difference) were 1.44 ± 1.21 L (12.21% ± 11.70%), 0.63 ± 0.49 L (29.68% ± 61.99%), 0.12 ± 0.09 L (16.20% ± 18.42%), 1.65 ± 1.40 L (10.43% ± 10.79%), 0.71 ± 0.68 L (5.14% ± 4.75%), and 0.17 ± 0.15 L (4.32% ± 3.38%), respectively.

CONCLUSION

Our algorithm shows promise in its ability to estimate whole-body compositions from chest CT scans. Body composition measures based on chest CT scans are more accurate than those based on vertebra third lumbar.

Inflammatory biomarkers and risk of breast cancer among young women in Latin America: a case-control study

BACKGROUND

Breast cancer incidence is increasing rapidly in Latin America, with a higher proportion of cases among young women than in developed countries. Studies have linked inflammation to breast cancer development, but data is limited in premenopausal women, especially in Latin America.

METHODS

We investigated the associations between serum biomarkers of chronic inflammation (interleukin (IL)-6, IL-8, IL-10, tumor necrosis factor-α (TNF-α), interferon-γ (IFN-γ), leptin, adiponectin) and risk of premenopausal breast cancer among 453 cases and 453 matched, population-based controls from Chile, Colombia, Costa Rica, and Mexico. Odds ratios (OR) were estimated using conditional logistic regression models. Analyses were stratified by size and hormonal receptor status of the tumors.

RESULTS

IL-6 (ORper standard deviation (SD) = 1.33 (1.11-1.60)) and TNF-α (ORper SD = 1.32 (1.11-1.58)) were positively associated with breast cancer risk in fully adjusted models. Evidence of heterogeneity by estrogen receptor (ER) status was observed for IL-8 (P-homogeneity = 0.05), with a positive association in ER-negative tumors only. IL-8 (P-homogeneity = 0.06) and TNF-α (P-homogeneity = 0.003) were positively associated with risk in the largest tumors, while for leptin (P-homogeneity = 0.003) a positive association was observed for the smallest tumors only.

CONCLUSIONS

The results of this study support the implication of chronic inflammation in breast cancer risk in young women in Latin America. Largest studies of prospective design are needed to confirm these findings in premenopausal women.

Metabolic dysfunction and obesity-related cancer: Beyond obesity and metabolic syndrome

OBJECTIVES

The metabolic dysfunction driven by obesity, including hyperglycemia and dyslipidemia, increases risk for developing at least 13 cancer types. The concept of "metabolic dysfunction" is often defined by meeting various combinations of criteria for metabolic syndrome. However, the lack of a unified definition of metabolic dysfunction makes it difficult to compare findings across studies. This review summarizes 129 studies that evaluated variable definitions of metabolic dysfunction in relation to obesity-related cancer risk and mortality after a cancer diagnosis. Strategies for metabolic dysfunction management are also discussed.

METHODS

A comprehensive search of relevant publications in MEDLINE (PubMed) and Google Scholar with review of references was conducted.

RESULTS

Metabolic dysfunction, defined as metabolic syndrome diagnosis or any number of metabolic syndrome criteria out of clinical range, inflammatory biomarkers, or markers of metabolic organ function, has been associated with risk for, and mortality from, colorectal, pancreatic, postmenopausal breast, and bladder cancers. Metabolic dysfunction associations with breast and colorectal cancer risk have been observed independently of BMI, with increased risk in individuals with metabolically unhealthy normal weight or overweight/obesity compared with metabolically healthy normal weight.

CONCLUSION

Metabolic dysfunction is a key risk factor for obesity-related cancer, regardless of obesity status. Nonetheless, a harmonized definition of metabolic dysfunction will further clarify the magnitude of the relationship across cancer types, enable better comparisons across studies, and further guide criteria for obesity-related cancer risk stratification.

Role of Obesity, Physical Exercise, Adipose Tissue-Skeletal Muscle Crosstalk and Molecular Advances in Barrett's Esophagus and Esophageal Adenocarcinoma

Both obesity and esophageal adenocarcinoma (EAC) rates have increased sharply in the United States and Western Europe in recent years. EAC is a classic example of obesity-related cancer where the risk of EAC increases with increasing body mass index. Pathologically altered visceral fat in obesity appears to play a key role in this process. Visceral obesity may promote EAC by directly affecting gastroesophageal reflux disease and Barrett’s esophagus (BE), as well as a less reflux-dependent effect, including the release of pro-inflammatory adipokines and insulin resistance. Deregulation of adipokine production, such as the shift to an increased amount of leptin relative to “protective” adiponectin, has been implicated in the pathogenesis of BE and EAC. This review discusses not only the epidemiology and pathophysiology of obesity in BE and EAC, but also molecular alterations at the level of mRNA and proteins associated with these esophageal pathologies and the potential role of adipokines and myokines in these disorders. Particular attention is given to discussing the possible crosstalk of adipokines and myokines during exercise. It is concluded that lifestyle interventions to increase regular physical activity could be helpful as a promising strategy for preventing the development of BE and EAC.

Association of a Healthy Lifestyle Index with Risk of Breast Cancer among Women with Normal Body Mass Index in the UK Biobank

BACKGROUND

A high healthy lifestyle index (HLI), a composite score based on good diet quality, low alcohol consumption, no smoking, moderate to high physical activity, and waist circumference <80 cm, has been consistently associated with a reduced risk of breast cancer. Recently, high levels of body fat were found to be associated with an elevated risk of breast cancer in postmenopausal women with a normal body mass index (BMI; 18.5-<25 kg/m2). Whether the HLI is associated with breast cancer risk in women with normal BMI is unknown.

METHODS

We studied 102,572 women aged 40 to 69 years with a normal BMI at enrollment into the UK Biobank cohort study. The HLI was created by assigning to each component higher scores for healthier behaviors and then summing the scores. The HLI was categorized by tertiles and age- and multivariable-adjusted HRs for the association of the HLI with breast cancer risk by menopausal status were estimated using Cox proportional hazards models.

RESULTS

In postmenopausal women, compared with a low HLI, higher scores were associated with a reduced risk of breast cancer [HRHLI-3rd tertile = 0.76; 95% confidence interval (CI), 0.64-0.91]. Findings were similar for premenopausal women, although they did not reach statistical significance, except when smoking status was excluded from the HLI score (HLIwithout smoking: HR3rd tertile = 0.71; 95% CI, 0.56-0.90).

CONCLUSIONS

In normal BMI postmenopausal women, a high HLI score was associated with a reduced risk of breast cancer.

IMPACT

Following a healthy lifestyle may reduce the risk of breast cancer among normal weight postmenopausal women.

Increased trunk fat is associated with altered gene expression in breast tissue of normal weight women

Increased trunk fat is associated with an elevated risk of breast cancer in normal-weight postmenopausal women. The main objective of this study was to determine whether levels of trunk fat are associated with changes in breast gene expression in normal-weight women. Non-tumorous breast tissue was collected from 32 normal BMI women who underwent mastectomy for breast cancer risk reduction or treatment. Body composition was measured by dual-energy x-ray absorptiometry. High levels of trunk fat were associated with a large number of differentially expressed genes and changes in multiple pathways and processes potentially linked to breast cancer pathogenesis. High levels of trunk fat were also associated with an elevated immune score and increased levels of leptin, CCL2, VEGF-C, IL6, and aromatase. Collectively, these results help to explain why high levels of trunk fat are associated with an increased risk of breast cancer in normal BMI women.

The Troubling Link Between Non-alcoholic Fatty Liver Disease (NAFLD) and Extrahepatic Cancers (EHC)

Non-alcoholic fatty liver disease (NAFLD) is a fast-spreading epidemic across the globe and has serious implications far beyond that of a "benign" liver condition. It is usually an outcome of ectopic fat storage due to chronic positive energy balance leading to obesity and is associated with multiple health problems. While association with cardiovascular disease and hepatocellular cancer is well recognized, it is becoming clear the NAFLD carries with it an increased risk of cancers of extrahepatic tissues. Studies have reported a higher risk for cancers of the colon, breast, prostate, lung, and pancreas. Fatty liver is associated with increased mortality; there is an urgent need to understand that fatty liver is not always benign, and not always associated with obesity. It is, however, a reversible condition and early recognition and intervention can alter its natural history and associated complications.