Branched-Chain Amino Acids and Risk of Breast Cancer

Branched-chain amino acids and risk of lung cancer: insights from mendelian randomization and NHANES III

Background

Recent studies have observed the relationships of circulatory and dietary intake of branched-chain amino acids (BCAAs) with long-term risk of certain cancers. However, the exact causality of BCAA with lung cancer (LUCA) and its pathological subtypes remains obscure. The aim of this study is to investigate the association between BCAA metabolism and risk of LUCA.

Methods

Here we conducted Mendelian randomization (MR) and observational epidemiological analyses to investigate the association between BCAA and risk of LUCA. With single nucleotide polymorphism (SNP)-phenotype association data extracted from genome-wide association studies (GWAS), we performed univariate and multivariate MR analyses to infer the causal effect of circulatory BCAA concentrations on LUCA. We further investigated the effects of several potential mediators and quantified the mediation effects. Population-level analyses were performed in the National Health and Nutrition Examination Survey (NHANES) III.

Results

Our results demonstrated that genetically predicted circulatory valine concentrations causally increased the risk of overall LUCA [odds ratio (OR) =1.324, 95% confidence interval (CI): 1.058-1.658, P=0.01]. For pathological subgroups, elevated levels of leucine, isoleucine, valine, and total BCAA were founded to be significantly associated with a higher risk of squamous cell lung cancer (LUSC); however, they did not significantly affect lung adenocarcinoma (LUAD). Moreover, body mass index (BMI) mediated approximately 3.91% (95% CI: 1.22-7.18%) of the total effect of leucine on LUSC. In the NHANES III population, dietary total BCAA intake was significantly associated with BMI ≥30 kg/m2, while no non-linear relationships were observed.

Conclusions

This study provides genetic evidence for the histology-specific causality of BCAA on LUCA and implies the mediation role of BMI in this relationship. Further studies are needed to confirm these findings and elucidate the underlying mechanisms.

Global untargeted and individual targeted plasma metabolomics of breast cancer recurrence modified by hormone receptors

BACKGROUND

Breast cancer is a heterogeneous and complex etiological disease. Understanding perturbations of circulating metabolites could improve prognosis.

METHODS

We recruited breast cancer patients from Kaohsiung Medical University (KMU) to perform untargeted (case-control design) and targeted (patient cohort) metabolomics analyses in the discovery and validation phases to evaluate interaction effects between clinical factors and plasma metabolites using multivariable Cox proportional hazards model.

RESULTS

In the discovery phase, partial least squares-discriminant analysis (PLS-DA) showed that plasma metabolites were significantly different between recurrent and non-recurrent breast cancer patients. Metabolite set enrichment analysis (MSEA) and metabolomic pathway analysis (MetPA) showed that valine, leucine, and isoleucine degradation was the significant pathway, and volcano plot showed significant ten upregulated and two downregulated metabolites between recurrent and non-recurrent cases. Combined with receiver operating characteristic (ROC) curve and biological significance, creatine, valine, methionine, and mannose were selected for the validation phase. In this patient cohort with 41 new-recurrent vs. 248 non-recurrent breast cancer cases, followed for 720.49 person-years, compared with low level of valine, high valine level was significantly negatively associated with recurrent breast cancer (aHR: 0.36, 95% CI: 0.18-0.72, P = 0.004), especially in ER-negative and PR-negative status. There were interaction effects between valine and ER (Pinteraction = 0.006) as well as PR (Pinteraction = 0.002) on recurrent breast cancer. After Bonferroni correction, stratification effects between valine and hormone receptors were still significant.

CONCLUSION

Our study revealed that plasma metabolites were significantly different between recurrent and non-recurrent patients, proposing therapeutic insights for breast cancer prognosis.

Depression promotes breast cancer progression by regulating amino acid neurotransmitter metabolism and gut microbial disturbance

INTRODUCTION

Breast cancer (BC) is the most prevalent type of cancer and has the highest mortality among women worldwide. BC patients have a high risk of depression, which has been recognized as an independent factor in the progression of BC. However, the potential mechanism has not been clearly demonstrated.

METHODS

To explore the correlation and mechanism between depression and BC progression, we induced depression and tumor in BC mouse models. Depression was induced via chronic unpredictable mild stress (CUMS) and chronic restraint stress (CRS). Amino acid (AA) neurotransmitter-targeted metabonomics and gut microbiota 16S rDNA gene sequencing were employed in the mouse model after evaluation with behavioral tests and pathological analysis.

RESULTS

The tumors in cancer-depression (CD) mice grew faster than those in cancer (CA) mice, and lung metastasis was observed in CD mice. Metabonomics revealed that the neurotransmitters and plasma AAs in CD mice were dysregulated, namely the tyrosine and tryptophan pathways and monoamine neurotransmitters in the brain. Gut microbiota analysis displayed an increased ratio of Firmicutes/Bacteroides. In detail, the abundance of f_Lachnospiraceae and s_Lachnospiraceae increased, whereas the abundance of o_Bacteroidales and s_Bacteroides_caecimuris decreased. Moreover, the gut microbiota was more closely associated with AA neurotransmitters than with plasma AA.

CONCLUSION

Depression promoted the progression of BC by modulating the abundance of s_Lachnospiraceae and s_Bacteroides_caecimuris, which affected the metabolism of monoamine neurotransmitters in the brain and AA in the blood.

Unravelling genetic architecture of circulatory amino acid levels, and their effect on risk of complex disorders

Variations in serum amino acid levels are linked to a multitude of complex disorders. We report the largest genome-wide association study (GWAS) on nine serum amino acids in the UK Biobank participants (117 944, European descent). We identified 34 genomic loci for circulatory levels of alanine, 48 loci for glutamine, 44 loci for glycine, 16 loci for histidine, 11 loci for isoleucine, 19 loci for leucine, 9 loci for phenylalanine, 32 loci for tyrosine and 20 loci for valine. Our gene-based analysis mapped 46-293 genes associated with serum amino acids, including MIP, GLS2, SLC gene family, GCKR, LMO1, CPS1 and COBLL1.The gene-property analysis across 30 tissues highlighted enriched expression of the identified genes in liver tissues for all studied amino acids, except for isoleucine and valine, in muscle tissues for serum alanine and glycine, in adrenal gland tissues for serum isoleucine and leucine, and in pancreatic tissues for serum phenylalanine. Mendelian randomization (MR) phenome-wide association study analysis and subsequent two-sample MR analysis provided evidence that every standard deviation increase in valine is associated with 35% higher risk of type 2 diabetes and elevated levels of serum alanine and branched-chain amino acids with higher levels of total cholesterol, triglyceride and low-density lipoprotein, and lower levels of high-density lipoprotein. In contrast to reports by observational studies, MR analysis did not support a causal association between studied amino acids and coronary artery disease, Alzheimer's disease, breast cancer or prostate cancer. In conclusion, we explored the genetic architecture of serum amino acids and provided evidence supporting a causal role of amino acids in cardiometabolic health.

The causal association between serum metabolites and lung cancer based on multivariate Mendelian randomization

This study seeks to understand the causal association between serum metabolites and different lung cancer types, an area yet to be extensively studied. We Used a two-sample Mendelian randomization (TSMR) approach, utilizing 486 blood metabolites as exposures and 3 distinct lung cancer types genome-wide association studies datasets as outcomes. We employed inverse variance weighting, MR-Egger, weighted median, simple mode, and weighted mode to estimate causal effects. We performed sensitivity analyses using Cochran Q test, MR-Egger intercept test, and MR-pleiotropy residual sum and outlier (MR-PRESSO). Linkage disequilibrium score (LDSC) analysis was conducted on the selected metabolites, and common confounding single nucleotide polymorphisms were eliminated using the human genotype-phenotype association Database. Metabolic pathway analysis was performed with MetaboAnalyst 5.0 software. Subsequently, a multivariate Mendelian randomization analysis was conducted to ascertain independent risk exposures. Our findings suggest independent risk factors for specific types of lung cancer: 7-methylxanthine and isoleucine for lung adenocarcinoma, cysteine and 1-arachidonoylglycerophosphocholine are identified as independent protective and risk factors for squamous lung cancer. Undecanoate (11:0) with Linoleate (18:2n6) showed a protective effect for small cell lung cancer. Additionally, 11 metabolic pathways were associated with lung cancer. This novel perspective offers a multidimensional understanding of lung cancer phenotypes, providing valuable guidance for identifying and screening of diverse lung cancer phenotypes.

Dietary Branched Chain Amino Acids Association with Cancer and Mortality: A Systematic Review and Meta-Analysis of Observational Studies

The present study aimed to investigate the association of dietary branched-chain amino acids (BCAAs) and its components with cancer, cancer mortality, and all-cause mortality in a meta-analysis of observational studies. A comprehensive search was conducted between electronic databases (PubMed, Scopus, and Web of Science) until September 2022. Odds ratios (OR), hazard ratios (HR), and relative risks (RR) were extracted. Eight articles (six studies on breast cancer (BC) and digestive cancers risk, and three studies on both BC and digestive cancers mortality, and all-cause mortality) were included. The present study showed no statistically significant association between dietary BCAAs and its components with BC and digestive cancers (RRBCAA: 0.87, 95% CI: 0.68-1.10, RRLeucine: 0.74, 95% CI: 0.52-1.04, RRIsoleucine: 0.98, 95% CI: 0.93-1.04, RRValine: 0.76, 95% CI: 0.55-1.05). Also, no statistically significant relationship between dietary BCAAs and its components with both BC and digestive cancers mortality (RRBCAA: 0.95, 95% CI: 0.68-1.33, RRLeucine: 0.95, 95% CI: 0.79-1.15, RRIsoleucine: 0.95, 95% CI: 0.79-1.14, RRValine: 1.01, 95% CI: 0.84-1.21) and all-cause mortality (RRBCAA: 0.98, 95% CI: 0.73-1.32, RRLeucine: 1.02, 95% CI: 0.81-1.29, RRIsoleucine: 0.96, 95% CI: 0.73-1.27, RRValine: 1.02, 95% CI: 0.79-1.32) were observed. Our findings showed no significant association between dietary BCAAs and its components with BC and digestive cancers, BC and digestive cancers mortality, and all-cause mortality.

The Role of Amino Acids in the Diagnosis, Risk Assessment, and Treatment of Breast Cancer: A Review

This review summarizes the role of amino acids in the diagnosis, risk assessment, imaging, and treatment of breast cancer. It was shown that the content of individual amino acids changes in breast cancer by an average of 10-15% compared with healthy controls. For some amino acids (Thr, Arg, Met, and Ser), an increase in concentration is more often observed in breast cancer, and for others, a decrease is observed (Asp, Pro, Trp, and His). The accuracy of diagnostics using individual amino acids is low and increases when a number of amino acids are combined with each other or with other metabolites. Gln/Glu, Asp, Arg, Leu/Ile, Lys, and Orn have the greatest significance in assessing the risk of breast cancer. The variability in the amino acid composition of biological fluids was shown to depend on the breast cancer phenotype, as well as the age, race, and menopausal status of patients. In general, the analysis of changes in the amino acid metabolism in breast cancer is a promising strategy not only for diagnosis, but also for developing new therapeutic agents, monitoring the treatment process, correcting complications after treatment, and evaluating survival rates.

The Influence of Adipocyte Secretome on Selected Metabolic Fingerprints of Breast Cancer Cell Lines Representing the Four Major Breast Cancer Subtypes

Molecular subtype (MS) is one of the most used classifications of breast cancer (BC). Four MSs are widely accepted according to receptor expression of estrogen, progesterone, and HER2. The impact of adipose tissue on BC MS metabolic impairment is still unclear. The present work aims to elucidate the metabolic alterations in breast cancer cell lines representing different MSs subjected to adipocyte associated factors. Preadipocytes isolated from human subcutaneous adipose tissue were differentiated into mature adipocytes. MS representative cell lines were exposed to mature adipocyte secretome. Extracellular medium was collected for metabolomics and RNA was extracted to evaluate enzymatic expression by RT-PCR. Adipocyte secretome exposure resulted in a decrease in the Warburg effect rate and an increase in cholesterol release. HER2+ cell lines (BT-474 and SK-BR-3) exhibited a similar metabolic pattern, in contrast to luminal A (MCF-7) and triple negative (TN) (MDA-MB-231), both presenting identical metabolisms. Anaplerosis was found in luminal A and TN representative cells, whereas cataplerotic reactions were likely to occur in HER2+ cell lines. Our results indicate that adipocyte secretome affects the central metabolism distinctly in each BC MS representative cell line.

Inhibition of branched-chain alpha-keto acid dehydrogenase kinase augments the sensitivity of ovarian and breast cancer cells to paclitaxel

CONTEXT

Many cancer patients who initially respond to chemotherapy eventually develop chemoresistance, and to address this, we previously conducted a RNAi screen to identify genes contributing to resistance. One of the hits from the screen was branched-chain α-keto acid dehydrogenase kinase (BCKDK). BCKDK controls the metabolism of branched-chain amino acids (BCAAs) through phosphorylation and inactivation of the branched-chain α-keto acid dehydrogenase complex (BCKDH), thereby inhibiting catabolism of BCAAs.

METHODS

We measured the impact on paclitaxel sensitivity of inhibiting BCKDK in ovarian and breast cancer cell lines.

RESULTS

Inhibition of BCKDK using siRNA or two chemical inhibitors (BCKDKi) was synergistic with paclitaxel in both breast and ovarian cancer cells. BCKDKi reduced levels of BCAA and the addition of exogenous BCAA suppressed this synergy. BCKDKi inactivated the mTORC1-Aurora pathway, allowing cells to overcame M-phase arrest induced by paclitaxel. In some cases, cells almost completed cytokinesis, then reverted to a single cell, resulting in multinucleate cells.

CONCLUSION

BCKDK is an attractive target to augment the sensitivity of cancer cells to paclitaxel.

A prospective case-cohort analysis of plasma metabolites and breast cancer risk

BACKGROUND

Breast cancer incidence rates have not declined despite an improvement in risk prediction and the identification of modifiable risk factors, suggesting the need to identify novel risk factors and etiological pathways involved in this cancer. Metabolomics has emerged as a promising tool to find circulating metabolites associated with breast cancer risk.

METHODS

Untargeted metabolomic analysis was done on prediagnostic plasma samples from a case-cohort study of 1695 incident breast cancer cases and a 1983 women subcohort drawn from Cancer Prevention Study 3. The associations of 868 named metabolites (per one standard deviation increase) with breast cancer were determined using Prentice-weighted Cox proportional hazards regression modeling.

RESULTS

A total of 11 metabolites were associated with breast cancer at false discovery rate (FDR) < 0.05 with the majority having inverse association [ranging from RR = 0.85 (95% CI 0.80-0.92) to RR = 0.88 (95% CI 0.82-0.94)] and one having a positive association [RR = 1.14 (95% CI 1.06-1.23)]. An additional 50 metabolites were associated at FDR < 0.20 with inverse associations ranging from RR = 0.88 (95% CI 0.81-0.94) to RR = 0.91 (95% CI 0.85-0.98) and positive associations ranging from RR = 1.13 (95% CI 1.05-1.22) to RR = 1.11 (95% CI 1.02-1.20). Several of these associations validated the findings of previous metabolomic studies. These included findings that several progestogen and androgen steroids were associated with increased risk of breast cancer in postmenopausal women and four phospholipids, and the amino acids glutamine and asparagine were associated with decreased risk of this cancer in pre- and postmenopausal women. Several novel associations were also identified, including a positive association for syringol sulfate, a biomarker for smoked meat, and 3-methylcatechol sulfate and 3-hydroxypyridine glucuronide, which are metabolites of xenobiotics used for the production of pesticides and other products.

CONCLUSIONS

Our study validated previous metabolite findings and identified novel metabolites associated with breast cancer risk, demonstrating the utility of large metabolomic studies to provide new leads for understanding breast cancer etiology. Our novel findings suggest that consumption of smoked meats and exposure to catechol and pyridine should be investigated as potential risk factors for breast cancer.

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

BACKGROUND

Adiposity is consistently positively associated with postmenopausal breast cancer and inversely associated with premenopausal breast cancer risk, though the reasons for this difference remain unclear.

METHODS

In this nested case-control study of 1649 breast cancer cases and 1649 matched controls from the Nurses' Health Study (NHS) and the NHSII, we selected lipid and polar metabolites correlated with BMI, waist circumference, weight change since age 18, or derived fat mass, and developed a metabolomic score for each measure using LASSO regression. Logistic regression was used to investigate the association between this score and breast cancer risk, adjusted for risk factors and stratified by menopausal status at blood draw and diagnosis.

RESULTS

Metabolite scores developed among only premenopausal or postmenopausal women were highly correlated with scores developed in all women (r = 0.93-0.96). Higher metabolomic adiposity scores were generally inversely related to breast cancer risk among premenopausal women. Among postmenopausal women, significant positive trends with risk were observed (e.g., metabolomic waist circumference score OR Q4 vs. Q1 = 1.47, 95% CI = 1.03-2.08, P-trend = 0.01).

CONCLUSIONS

Though the same metabolites represented adiposity in pre- and postmenopausal women, breast cancer risk associations differed suggesting that metabolic dysregulation may have a differential association with pre- vs. postmenopausal breast cancer.

Prediagnostic Plasma Metabolomics and the Risk of Exfoliation Glaucoma

Purpose

The etiology of exfoliation glaucoma (XFG) is poorly understood. We aimed to identify a prediagnostic plasma metabolomic signature associated with XFG.

Methods

We conducted a 1:1 matched case-control study nested within the Nurses' Health Study and Health Professionals Follow-up Study. We collected blood samples in 1989-1990 (Nurses' Health Study) and 1993-1995 (Health Professionals Follow-up Study). We identified 205 incident XFG cases through 2016 (average time to diagnosis from blood draw = 11.8 years) who self-reported glaucoma and were confirmed as XFG cases with medical records. We profiled plasma metabolites using liquid chromatography-mass spectrometry. We evaluated 379 known metabolites (transformed for normality using probit scores) using multiple conditional logistic models. Metabolite set enrichment analysis was used to identify metabolite classes associated with XFG. To adjust for multiple comparisons, we used number of effective tests (NEF) and the false discovery rate (FDR).

Results

Mean age of cases (n = 205) at diagnosis was 71 years; 85% were women and more than 99% were Caucasian; controls (n = 205) reported eye examinations as of the matched cases' index date. Thirty-three metabolites were nominally significantly associated with XFG (P < 0.05), and 4 metabolite classes were FDR-significantly associated. We observed positive associations for lysophosphatidylcholines (FDR = 0.02) and phosphatidylethanolamine plasmalogens (FDR = 0.004) and inverse associations for triacylglycerols (FDR < 0.0001) and steroids (FDR = 0.03). In particular, the multivariable-adjusted odds ratio with each 1 standard deviation higher plasma cortisone levels was 0.49 (95% confidence interval, 0.32-0.74; NEF = 0.05).

Conclusions

In plasma from a decade before diagnosis, lysophosphatidylcholines and phosphatidylethanolamine plasmalogens were positively associated and triacylglycerols and steroids (e.g., cortisone) were inversely associated with XFG risk.

Dietary intake of branched-chain amino acids in relation to the risk of breast cancer

BACKGROUND

Given that, studies on the association of dietary intake of branched-chain amino acids (BCAAs) with risk of cancers, especially breast cancer, are limited, we aimed to examine the association between dietary intake of BCAAs and risk of breast cancer.

METHODS

This case-control study was performed on Iranian women aged ≥ 30 years from July 2013 to July 2015. Overall 1050 women including 350 patients and 700 controls were included. Breast cancer was diagnosed by physical examination, mammography and pathological confirmation. We assessed dietary intakes using the validated 106-item Willett-format semi-quantitative dish-based food frequency questionnaire. The total intake of valine, leucine, and isoleucine from all food items in the questionnaire was used to calculate BCAAs intake. To estimate odds ratios (ORs) and 95% confidence intervals (95% CI), we used logistic regression analysis.

RESULTS

After controlling for potential confounders, we found that women in the highest quartile of BCAAs had lower odds of breast cancer compared with the first quartile (OR: 0.50; 95% CI 0.34-0.72). When we stratified the analysis based on menopausal status, a significant inverse association between BCAAs intake and odds of postmenopausal breast cancer was observed (OR: 0.22; 95% CI 0.13-0.39), although this significant relationship was not found in premenopausal breast cancer (OR: 2.57; 95% CI 0.51-12.73). Also, this significant association was also observed for valine, leucine, and isoleucine separately.

CONCLUSION

We found that higher dietary intake of BCAAs was significantly associated with a reduced risk of postmenopausal breast cancer.

Intrapersonal Stability of Plasma Metabolomic Profiles over 10 Years among Women

In epidemiological studies, samples are often collected long before disease onset or outcome assessment. Understanding the long-term stability of biomarkers measured in these samples is crucial. We estimated within-person stability over 10 years of metabolites and metabolite features (n = 5938) in the Nurses’ Health Study (NHS): the primary dataset included 1880 women with 1184 repeated samples donated 10 years apart while the secondary dataset included 1456 women with 488 repeated samples donated 10 years apart. We quantified plasma metabolomics using two liquid chromatography mass spectrometry platforms (lipids and polar metabolites) at the Broad Institute (Cambridge, MA, USA). Intra-class correlations (ICC) were used to estimate long-term (10 years) within-person stability of metabolites and were calculated as the proportion of the total variability (within-person + between-person) attributable to between-person variability. Within-person variability was estimated among participants who donated two blood samples approximately 10 years apart while between-person variability was estimated among all participants. In the primary dataset, the median ICC was 0.43 (1st quartile (Q1): 0.36; 3rd quartile (Q3): 0.50) among known metabolites and 0.41 (Q1: 0.34; Q3: 0.48) among unknown metabolite features. The three most stable metabolites were N6,N6-dimethyllysine (ICC = 0.82), dimethylguanidino valerate (ICC = 0.72), and N-acetylornithine (ICC = 0.72). The three least stable metabolites were palmitoylethanolamide (ICC = 0.05), ectoine (ICC = 0.09), and trimethylamine-N-oxide (ICC = 0.16). Results in the secondary dataset were similar (Spearman correlation = 0.87) to corresponding results in the primary dataset. Within-person stability over 10 years is reasonable for lipid, lipid-related, and polar metabolites, and varies by metabolite class. Additional studies are required to estimate within-person stability over 10 years of other metabolites groups.

Role of Branched-chain Amino Acid Metabolism in Tumor Development and Progression

Branched-chain amino acids (BCAAs), isoleucine, leucine and valine, are essential amino acids with vital roles in protein synthesis and energy production. We reviewed the fundamentals of BCAA metabolism in advanced cancer patients. BCAAs and various catabolic products act as signalling molecules, which activate mechanisms ranging from protein synthesis to insulin secretion. Recently, BCAA metabolism has been suggested to contribute to cancer progression. Of particular interest is the modulation of the mTOR activity by BCAAs. There are likely multiple pathways involved in BCAA metabolism implicated in carcinogenesis. Understanding the mechanism(s) underlying altered BCAAs metabolism will significantly advance the current understanding of nutrient involvement in carcinogenesis and direct future studies to unravel the significance of BCCA metabolites in tumor development and progression.