Abstract Background: Recent evidence suggests that metabolic syndrome (MetS) may be a potential risk factor for obesity-related cancer (ORC) owing to shared risk factors like physical inactivity, hyperglycemia, insulin resistance, gut microbiome dysfunction, and inflammation. We conducted an umbrella review of systematic reviews with meta-analysis to synthesize the evidence on the association between MetS and ORC incidence and survival. Methods: The study protocol was registered with PROSPERO (CRD42021230899). Searches in five databases (Medline, Embase, CINAHL, Cochrane Library, and Scopus) retrieved 2,524 systematic reviews with meta-analyses (SRMA) after duplicates were removed. SRMA were eligible if they evaluated MetS with ORC incidence or survival, were conducted in an adult population (≥18 years), and included the pre-defined study-specific data. Using Covidence, two reviewers independently screened titles and abstracts (2,524) and then reviewed full text (41), selecting 23 SRMAs for inclusion. Data extraction was then completed independently by two reviewers. The outcomes were pooled using a random-effects model with the package “meta” in R. Sub-group analyses were conducted for a priori chosen factors, as outlined in the protocol. SRMA were appraised using the AMSTAR 2 criteria. Results: 23 SRMA published between 2001 and 2023 met our inclusion criteria, comprising a total of 112 studies, ~52,543,335 total individuals, and ~355,808 ORC cases. After pooled analyses, MetS was associated with a statistically significant 10% increased risk of ORC [RR(95% CI): 1.10(1.06-1.14)]. MetS was also statistically significantly associated with poorer ORC-specific survival [RR(95% CI): 1.10(1.02-1.18)], though there was no association between MetS and overall survival [RR(95% CI): 1.04(0.97-1.11)]. When stratified by sex, both male and female individuals with MetS had a statistically significant higher risk of ORC [RR(95% CI): 1.12(1.06-1.17), 1.10(1.01-1.19), respectively]. When stratified by cancer site, individuals with MetS demonstrated a higher risk of colorectal cancer [RR(95% CI): 1.12(1.06-1.18)]. We also observed suggestive associations between MetS and liver, pancreatic, and postmenopausal breast cancer risk, but these were not statistically significant [RR(95% CI): 1.20(1.00-1.45), 1.20(0.96-1.50), 1.12(0.99-1.27), respectively]. All associations were supported by “critically low” quality evidence according to the AMSTAR2 criteria. This was primarily because these SRMAs either did not follow a pre-specified written and published protocol, or did not provide a list of all potentially relevant studies that were read in full-text form but excluded from the review. Conclusions: These results emphasize the important role that MetS may play in the development of ORC as well as in the survival of patients with ORC. Conducting high-quality reviews is needed to increase the certainty of evidence, reduce potential bias, and improve knowledge in this field. Citation Format: Maci Winn, Prasoona Karra, Ryzen Benson, Svenja Pauleck, Nathorn Chaiyakunapruk, Win Khaing, Tallie Casucci, Mary M. McFarland, Siwen Hu-Lieskovan, Michelle Litchman, Yizhe Xu, Mary Playdon, Sheetal Hardikar. Metabolic syndrome and obesity-related cancer risk and survival: An umbrella review [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB149.
While diet and nutrition are modifiable risk factors for many chronic and infectious diseases, their role in cancer prevention and control remains under investigation. The lack of clarity of some diet–cancer relationships reflects the ongoing debate about the relative contribution of genetic factors, environmental exposures, and replicative errors in stem cell division as determinate drivers of cancer risk. In addition, dietary guidance has often been based upon research assuming that the effects of diet and nutrition on carcinogenesis would be uniform across populations and for various tumor types arising in a specific organ, i.e., that one size fits all. Herein, we present a paradigm for investigating precision dietary patterns that leverages the approaches that led to successful small-molecule inhibitors in cancer treatment, namely understanding the pharmacokinetics and pharmacodynamics of small molecules for targeting carcinogenic mechanisms. We challenge the scientific community to refine the paradigm presented and to conduct proof-in-concept experiments that integrate existing knowledge (drug development, natural products, and the food metabolome) with developments in artificial intelligence to design and then test dietary patterns predicted to elicit drug-like effects on target tissues for cancer prevention and control. We refer to this precision approach as dietary oncopharmacognosy and envision it as the crosswalk between the currently defined fields of precision oncology and precision nutrition with the goal of reducing cancer deaths.
Abstract Context Genome-wide association studies have identified associations between a common single nucleotide polymorphism (SNP; rs267738) in CERS2, a gene that encodes a (dihydro)ceramide synthase that is involved in the biosynthesis of very-long-chain sphingolipids (eg, C20-C26) and indices of metabolic dysfunction (eg, impaired glucose homeostasis). However, the biological consequences of this mutation on enzyme activity and its causal roles in metabolic disease are unresolved. Objective The studies described herein aimed to characterize the effects of rs267738 on CERS2 enzyme activity, sphingolipid profiles, and metabolic outcomes. Design We performed in-depth lipidomic and metabolic characterization of a novel CRISPR knock-in mouse modeling the rs267738 variant. In parallel, we conducted mass spectrometry-based, targeted lipidomics on 567 serum samples collected through the Utah Coronary Artery Disease study, which included 185 patients harboring 1 (n = 163) or both (n = 22) rs267738 alleles. Results In-silico analysis of the amino acid substitution within CERS2 caused by the rs267738 mutation suggested that rs267738 is deleterious for enzyme function. Homozygous knock-in mice had reduced liver CERS2 activity and enhanced diet-induced glucose intolerance and hepatic steatosis. However, human serum sphingolipids and a ceramide-based cardiac event risk test 1 score of cardiovascular disease were not significantly affected by rs267738 allele count. Conclusions The rs267738 SNP leads to a partial loss-of-function of CERS2, which worsened metabolic parameters in knock-in mice. However, rs267738 was insufficient to effect changes in serum sphingolipid profiles in subjects from the Utah Coronary Artery Disease Study.
Several meta-analyses have summarized evidence for the association between dietary factors and the incidence of colorectal cancer (CRC). However, to date, there has been little synthesis of the strength, precision, and quality of this evidence in aggregate.
Objective
To grade the evidence from published meta-analyses of prospective observational studies that assessed the association of dietary patterns, specific foods, food groups, beverages (including alcohol), macronutrients, and micronutrients with the incidence of CRC.
Data Sources
MEDLINE, Embase, and the Cochrane Library were searched from database inception to September 2019.
Evidence Review
Only meta-analyses of prospective observational studies with a cohort study design were eligible. Evidence of association was graded according to established criteria as follows: convincing, highly suggestive, suggestive, weak, or not significant.
Results
From 9954 publications, 222 full-text articles (2.2%) were evaluated for eligibility, and 45 meta-analyses (20.3%) that described 109 associations between dietary factors and CRC incidence were selected. Overall, 35 of the 109 associations (32.1%) were nominally statistically significant using random-effects meta-analysis models; 17 associations (15.6%) demonstrated large heterogeneity between studies (I2 > 50%), whereas small-study effects were found for 11 associations (10.1%). Excess significance bias was not detected for any association between diet and CRC. The primary analysis identified 5 (4.6%) convincing, 2 (1.8%) highly suggestive, 10 (9.2%) suggestive, and 18 (16.5%) weak associations between diet and CRC, while there was no evidence for 74 (67.9%) associations. There was convincing evidence of an association of intake of red meat (high vs low) and alcohol (≥4 drinks/d vs 0 or occasional drinks) with the incidence of CRC and an inverse association of higher vs lower intakes of dietary fiber, calcium, and yogurt with CRC risk. The evidence for convincing associations remained robust following sensitivity analyses.
Conclusions and Relevance
This umbrella review found convincing evidence of an association between lower CRC risk and higher intakes of dietary fiber, dietary calcium, and yogurt and lower intakes of alcohol and red meat. More research is needed on specific foods for which evidence remains suggestive, including other dairy products, whole grains, processed meat, and specific dietary patterns.
<div>Abstract<p>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 (<i>n</i> = 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.</p><p><b>Prevention Relevance:</b> Recognizing metabolic dysfunction as a significant risk factor for ORCs underscores the importance of preventive measures targeting metabolic health improvement across all BMI categories.</p></div>
174 Background: Because obesity portends a higher risk of breast cancer mortality, achieving a healthy weight is recommended for breast cancer survivors. The impact of weight history on the ability to lose weight is unclear. We previously reported a 6.2 + 0.7% vs. 2.1 + 0.9% weight loss (p = .0003) in 100 breast cancer survivors randomized to a 6-month weight loss intervention vs. usual care. We examined whether weight history modified the effect of the intervention on body weight changes. Methods: Breast cancer survivors with a BMI > 25 kg/m 2 were randomized to usual care or 6-month, 11-session diet and exercise-counseling intervention. Baseline and 6 month weight and height were measured; weight at ages 18 and 35, 5 years and 1 year before and at diagnosis were self-reported. We defined weight history as: 1) change in weight between each time point and baseline; and 2) duration of obesity (i.e., number of years of having a BMI > 30 between age 18 and baseline). Generalized linear models were used to evaluate mean changes at 6 months between the intervention and usual care groups, adjusted and stratified by weight history variables. Results: Mean age and time since diagnosis were 59 + 7 years and 2.9 + 2.1 years, respectively. BMI increased over time (age 18 BMI = 21.8 + 2.9; baseline BMI = 32.4 + 6.5). Number of years being obese was 5.3 + 8.2 years (range 0-40 years). BMI at baseline, change in BMI from various time points to baseline, and years of obesity did not modify weight loss results. After adjusting for weight history, women randomized to intervention vs. usual care lost 6.1 + 0.7% vs. 2.0 + 0.9%, p = .0006, respectively. Conclusions: Participants reported a history of steady weight gain over time. The duration of obesity did not modify weight loss results. Weight history did not hinder survivors’ ability to lose clinically meaningful weight via a structured intervention.
Abstract Introduction: Body mass index (BMI) may misclassify obesity-related cancer (ORC) risk since metabolic dysfunction can exist at any BMI. We measured the association of metabolic dysfunction, independent of BMI with risk of ORC. Methods: Study included 60% white and 34% black Women’s Health Initiative participants with available baseline cardiovascular disease biomarkers. Metabolic obesity phenotypes were classified as normal weight with no metabolic dysfunction (NWNMD), normal weight with metabolic dysfunction (NWMD), overweight/obese with no metabolic dysfunction (OONMD) and overweight/obese with metabolic dysfunction (OOMD) when defined by Wildman and ATP III criteria. We performed a Cox proportional hazards regression with death as a competing risk adjusting for confounders. Results: Defining by Wildman and ATP III criteria, 17.0%, 6.5%, 31.0%, 45.0%; and 22.2%, 2.4%, 41% and 35% were NWNMD, NWMD, OONMD and OOMD respectively. The risk of all ORC combined was elevated among NWMD (HR 1.12, 95% CI: 0.90-1.39), OONMD (HR 1.15, 95% CI: 1.00-1.32) and OOMD (HR 1.35, 95% CI: 1.18-1.54) when compared to NWNMD using Wildman criteria. Results were similar when defined by ATP III, hs-CRP and HOMA-IR. When stratified by cancer type, NWMD were at increased risk of colorectal cancer when compared to NWNMD (HR 1.70, 95% CI: 1.02-2.82). Individuals who were overweight/obese were at increased risk of cancer for all cancer types though the effect estimates were lower among OONMD phenotype. Conclusions: NWMD and OOMD individuals are at increased risk of all ORC combined, independent of BMI status when compared to individuals with NWNMD. Citation Format: Prasoona Karra, Maci Winn, Garnet Anderson, Benjamin Haaland, Aladdin H. Shadyab, Marian Neuhouser, Rebecca Seguin-Fowler, Cynthia A. Thomson, Mace Coday, Jean Wactawski-Wende, Marcia L. Stefanick, Xiaochen Zhang, Ting-Yuan David Cheng, Shama Karanth, Yangbo Sun, Nazmus Saquib, Margaret Pichado, Su Yon Jung, Fred Tabung, Scott A. Summers, William L. Holland, Thunder Jalili, Marc Gunter, Sheetal Hardikar, Mary C. Playdon. Metabolic obesity phenotype and risk of obesity-related cancers in the women's health initiative [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6454.
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