A metabolomic analysis of adiposity measures and pre- and postmenopausal breast cancer risk in the Nurses’ Health Studies

Brantley, Kristen; Zeleznik, Oana A.; Dickerman, Barbra A.; Balasubramanian, Raji; Clish, Clary B.; Ávila-Pacheco, Julián; Rosner, Bernard; Tamimi, Rulla M.; Eliassen, A. Heather

doi:10.1038/s41416-022-01873-9

Cited by 6 publications

(6 citation statements)

References 52 publications

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“…It is often reported that metabolite levels change in diseased versus normal states. − This could be the result of one of two possibilities: , Metabolite levels could have changed as a consequence of the disease, or the change in metabolite levels could be a partial driver of the disease. , We suspect that, depending on the metabolite, both situations occur. However, if the change in metabolite levels is partly driving the disease (an example in cancer is found in refs and ), the question is how in reality does this contribute to cancer onset/progression?…”

Section: Discussionmentioning

confidence: 99%

“…It is often reported that metabolite levels change in diseased versus normal states. 115 − 120 This could be the result of one of two possibilities: 121 , 122 Metabolite levels could have changed as a consequence of the disease, or the change in metabolite levels could be a partial driver of the disease. 121 , 122 We suspect that, depending on the metabolite, both situations occur.…”

Section: Discussionmentioning

confidence: 99%

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Implications of the Essential Role of Small Molecule Ligand Binding Pockets in Protein–Protein Interactions

Skolnick

Zhou

2022

J. Phys. Chem. B

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Protein–protein interactions (PPIs) and protein–metabolite interactions play a key role in many biochemical processes, yet they are often viewed as being independent. However, the fact that small molecule drugs have been successful in inhibiting PPIs suggests a deeper relationship between protein pockets that bind small molecules and PPIs. We demonstrate that 2/3 of PPI interfaces, including antibody–epitope interfaces, contain at least one significant small molecule ligand binding pocket. In a representative library of 50 distinct protein–protein interactions involving hundreds of mutations, >75% of hot spot residues overlap with small molecule ligand binding pockets. Hence, ligand binding pockets play an essential role in PPIs. In representative cases, evolutionary unrelated monomers that are involved in different multimeric interactions yet share the same pocket are predicted to bind the same metabolites/drugs; these results are confirmed by examples in the PDB. Thus, the binding of a metabolite can shift the equilibrium between monomers and multimers. This implicit coupling of PPI equilibria, termed “metabolic entanglement”, was successfully employed to suggest novel functional relationships among protein multimers that do not directly interact. Thus, the current work provides an approach to unify metabolomics and protein interactomics.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Implications of the Essential Role of Small Molecule Ligand Binding Pockets in Protein–Protein Interactions

Skolnick

Zhou

2022

J. Phys. Chem. B

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“…This helps reduce data dimensionality and may lead to more powerful associations, but also assumes that associations stem from a general obesity metabolic phenotype rather than specific and/or sporadic metabolic states that only sometimes accompany obesity (such as when obesity leads to gallstones) 166 . In studies to date, adiposity signatures were not shown to substantially mediate the obesitycancer associations for advanced prostate cancer 167 or breast cancer 168 . There was 12% mediation for endometrial cancer 169 and results were mixed for colorectal cancer 169,170 .…”

Section: "Omics"-identified Biologic Factorsmentioning

confidence: 92%

Adiposity and cancer: meta-analysis, mechanisms, and future perspectives

Watts,

Moore,

Gunter

et al. 2024

Preprint

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Obesity is a recognised risk factor for many cancers and with rising global prevalence, has become a leading cause of cancer. Here we summarise the current evidence from both population-based epidemiologic investigations and experimental studies on the role of obesity in cancer development. This review presents a new meta-analysis using data from 40 million individuals and reports positive associations with 19 cancer types. Utilising major new data from East Asia, the meta-analysis also shows that the strength of obesity and cancer associations varies regionally, with stronger relative risks for several cancers in East Asia. This review also presents current evidence on the mechanisms linking obesity and cancer and identifies promising future research directions. These include the use of new imaging data to circumvent the methodological issues involved with body mass index and the use of omics technologies to resolve biologic mechanisms with greater precision and clarity.

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“…An alternative approach entails selecting metabolites on the basis of their associations with specific lifestyle factors, mainly diet, as performed in The Prostate, Lung, Colorectal, and Ovarian Cancer Screening (PLCO) trial 28 and in an additional study conducted in the SU.VI.MAX cohort, 26 or adiposity, such as in the PLCO trial 29 or the NHS. 20 Once the range of metabolites to be investigated is narrowed, associations of the metabolites with breast cancer risk can be evaluated.…”

Section: Linking Metabolites Breast Cancer and Lifestylementioning

confidence: 99%

Application of Metabolomics to Epidemiologic Studies of Breast Cancer: New Perspectives for Etiology and Prevention

His,

Gunter,

Keski-Rahkonen

et al. 2024

JCO

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PURPOSE To provide an overview on how the application of metabolomics (high-throughput characterization of metabolites from cells, organs, tissues, or biofluids) to population-based studies may inform our understanding of breast cancer etiology. METHODS We evaluated studies that applied metabolomic analyses to prediagnostic blood samples from prospective epidemiologic studies to identify circulating metabolites associated with breast cancer risk, overall and by breast cancer subtype and menopausal status. We provide some important considerations for the application and interpretation of metabolomics approaches in this context. RESULTS Overall, specific lipids and amino acids were indicated as the most common metabolite classes associated with breast cancer development. However, comparison of results across studies is challenging because of heterogeneity in laboratory techniques, analytical methods, sample size, and applied statistical methods. CONCLUSION Metabolomics is being increasingly applied to population-based studies for the identification of new etiologic hypotheses and/or mechanisms related to breast cancer development. Despite its success in applications to epidemiology, studies of larger sample size with detailed information on menopausal status, breast cancer subtypes, and repeated biologic samples collected over time are needed to improve comparison of results between studies and enhance validation of results, allowing potential clinical translation of findings.

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A metabolomic analysis of adiposity measures and pre- and postmenopausal breast cancer risk in the Nurses’ Health Studies

Cited by 6 publications

References 52 publications

Implications of the Essential Role of Small Molecule Ligand Binding Pockets in Protein–Protein Interactions

Implications of the Essential Role of Small Molecule Ligand Binding Pockets in Protein–Protein Interactions

Adiposity and cancer: meta-analysis, mechanisms, and future perspectives

Application of Metabolomics to Epidemiologic Studies of Breast Cancer: New Perspectives for Etiology and Prevention

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