Erythrocyte membrane fatty acids and breast cancer risk by tumor tissue expression of immuno-inflammatory markers and fatty acid synthase: a nested case-control study

Fatty Acid Profile and Genetic Variants of Proteins Involved in Fatty Acid Metabolism Could Be Considered as Disease Predictor

Circulating fatty acids (FA) have an endogenous or exogenous origin and are metabolized under the effect of many enzymes. They play crucial roles in many mechanisms: cell signaling, modulation of gene expression, etc., which leads to the hypothesis that their perturbation could be the cause of disease development. FA in erythrocytes and plasma rather than dietary FA could be used as a biomarker for many diseases. Cardiovascular disease was associated with elevated trans FA and decreased DHA and EPA. Increased arachidonic acid and decreased Docosahexaenoic Acids (DHA) were associated with Alzheimer's disease. Low Arachidonic acid and DHA are associated with neonatal morbidities and mortality. Decreased saturated fatty acids (SFA), increased monounsaturated FA (MUFA) and polyunsaturated FA (PUFA) (C18:2 n-6 and C20:3 n-6) are associated with cancer. Additionally, genetic polymorphisms in genes coding for enzymes implicated in FA metabolism are associated with disease development. FA desaturase (FADS1 and FADS2) polymorphisms are associated with Alzheimer's disease, Acute Coronary Syndrome, Autism spectrum disorder and obesity. Polymorphisms in FA elongase (ELOVL2) are associated with Alzheimer's disease, Autism spectrum disorder and obesity. FA-binding protein polymorphism is associated with dyslipidemia, type 2 diabetes, metabolic syndrome, obesity, hypertension, non-alcoholic fatty liver disease, peripheral atherosclerosis combined with type 2 diabetes and polycystic ovary syndrome. Acetyl-coenzyme A carboxylase polymorphisms are associated with diabetes, obesity and diabetic nephropathy. FA profile and genetic variants of proteins implicated in FA metabolism could be considered as disease biomarkers and may help with the prevention and management of diseases.

Circulating plasma phospholipid fatty acid levels and breast cancer risk in the Cancer Prevention Study-II Nutrition Cohort

Prospective studies that objectively measure circulating levels of fatty acids are needed to clarify their role in the etiology of breast cancer. Thirty-eight phospholipid fatty acids were measured using gas chromatograph in the plasma fraction of blood samples collected prospectively from 2718 postmenopausal women (905 breast cancer cases) enrolled in the Cancer Prevention Study II Nutrition Cohort. Associations of 28 fatty acids that passed quality control metrics (modeled as per 1-SD increase) with breast cancer risk were assessed using multiple variable conditional logistic regression models to compute odds ratios (OR) and 95% confidence intervals (CI). The false discovery rate (q value) was computed to account for multiple comparisons. Myristic acid levels were positively associated with breast cancer risk (OR, 1.17, 95% CI: 1.07-1.28; q value = 0.03). Borderline associations were also found for palmitoleic acid (OR, 1.14, 95% CI: 1.04-1.24) and desaturation index16 (OR, 1.10, 95% CI: 1.01-1.20) at nominal P values (<.03) (q values>0.05). These findings suggest that higher circulating levels of myristic acid, sourced from dietary intake of palm kernel oils along with increased de novo synthesis of fatty acids, may increase breast cancer risk. Additional studies are needed to investigate de novo synthesis of fatty acid in breast cancer tissues.

Development and Clinical Validation of a Novel 5 Gene Signature Based on Fatty Acid Metabolism-Related Genes in Oral Squamous Cell Carcinoma

Background/Aim

Lipid metabolism disorders play a crucial role in tumor development and progression. The aim of the study focused on constructing a novel prognostic model of oral squamous cell carcinoma (OSCC) patients using fatty acid metabolism-related genes.

Methods

Microarray test and data from The Cancer Genome Atlas (TCGA) were used to identify differentially expressed genes related to fatty acid metabolism. The quantitative real-time polymerase chain reaction (qRT-PCR) was then used to validate the expression of targeted fatty acid metabolism genes. A risk predictive scoring model of fatty acid metabolism-related genes was generated using a multivariate Cox model. The efficacy of this model was assessed by time-dependent receiver operating characteristic curve (ROC).

Results

14 fatty acid metabolism-related genes were identified by microarray test and TCGA database analysis and then confirmed by PCR. Finally, a 5 gene signature (ACACB, FABP3, PDK4, PPARG, and PLIN5) was constructed and a RiskScore was calculated for each patient. Compared to the high RiskScore group, the low RiskScore group had better overall survival (OS) (p = 0.02). The RiskScore derived from a 5 gene signature was a prognostic factor (HR: 3.73, 95% CI: 1.38, 10.09) for OSCC patients. The predictive classification efficiencies of RiskScore were evaluated and the area under the curve (AUC) values for 1, 3, and 5 years were 0.613, 0.652, and 0.681, respectively. Then we compared the predictive performance of the prognostic model with or without the RiskScore. The 5 gene-derived RiskScore can improve the predictive performance with AUC values of 0.760, 0.803, and 0.830 for 1, 3, and 5 years OS in prognostic model including the RiskScore. While the predicted AUC values of the model without RiskScore for 1, 3, and 5 years OS were 0.699, 0.715, and 0.714, respectively.

Conclusion

We developed a predictive score model using 5 fatty acid metabolism-related genes, which could be a potential prognostic indicator in OSCC.

Association of body mass index and inflammatory dietary pattern with breast cancer pathologic and genomic immunophenotype in the nurses' health study

BACKGROUND

Breast tumor immune infiltration is clearly associated with improved treatment response and outcomes in breast cancer. However, modifiable patient factors associated with breast cancer immune infiltrates are poorly understood. The Nurses' Health Study (NHS) offers a unique cohort to study immune gene expression in tumor and adjacent normal breast tissue, immune cell-specific immunohistochemistry (IHC), and patient exposures. We evaluated the association of body mass index (BMI) change since age 18, physical activity, and the empirical dietary inflammatory pattern (EDIP) score, all implicated in systemic inflammation, with immune cell-specific expression scores.

METHODS

This population-based, prospective observational study evaluated 882 NHS and NHSII participants diagnosed with invasive breast cancer with detailed exposure and gene expression data. Of these, 262 women (training cohort) had breast tumor IHC for four classic immune cell markers (CD8, CD4, CD20, and CD163). Four immune cell-specific scores were derived via lasso regression using 105 published immune expression signatures' association with IHC. In the remaining 620 patient evaluation cohort, we evaluated association of each immune cell-specific score as outcomes, with BMI change since age 18, physical activity, and EDIP score as predictors, using multivariable-adjusted linear regression.

RESULTS

Among women with paired expression/IHC data from breast tumor tissue, we identified robust correlation between novel immune cell-specific expression scores and IHC. BMI change since age 18 was positively associated with CD4+ (β = 0.16; p = 0.009), and CD163 novel immune scores (β = 0.14; p = 0.04) in multivariable analyses. In other words, for each 10 unit (kg/m2) increase in BMI, the percentage of cells positive for CD4 and CD163 increased 1.6% and 1.4%, respectively. Neither physical activity nor EDIP was significantly associated with any immune cell-specific expression score in multivariable analyses.

CONCLUSIONS

BMI change since age 18 was positively associated with novel CD4+ and CD163+ cell scores in breast cancer, supporting further study of the effect of modifiable factors like weight gain on the immune microenvironment.

Mediation analysis of erythrocyte lipophilic index on the association between BMI and risk of oral cancer

Aims

To explore the relationship between the fatty acid lipophilic index (LI) of the erythrocyte membrane and oral cancer risk, as well as to evaluate the possibility of LI acting as a mediator of the association between body mass index (BMI) and oral cancer.

Method

Twenty-three fatty acids (FAs) of the erythrocyte membrane were measured using gas chromatography in 380 patients with oral cancer and 387 control subjects. The LI was calculated based on the FA proportion and FA melting points. The association of BMI and erythrocyte LI with oral cancer risk was analysed using logistic regression. The mediation effect of LI on the association between BMI and oral cancer risk was evaluated using mediation analysis.

Results

Among the control group, 46.0% were overweight or obese, which was significantly higher than that of oral cancer patients (29.5%). Significant differences in erythrocyte membrane saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs), and polyunsaturated fatty acids (PUFAs) were observed between the patient and control groups. The proportion of C18:1 n-9 from the MUFA family increased in oral cancer patients (12.67%) compared with controls (12.21%). While the total proportion of n-3 PUFAs decreased in oral cancer patients compared with controls, with C20:5 n-3 decreasing from 0.66 to 0.47%, and C22:6 n-3 decreasing from 5.82 to 4.86%. The LI was lower in the control participants (M = 27.6, IQR: 27.3–27.9) than in the oral cancer patients (M = 28.2, IQR: 27.9–28.5). BMI was inversely associated with oral cancer risk with a fully adjusted OR of 0.59 (95% CI: 0.43–0.83), while LI was positively associated with oral cancer risk with a fully adjusted OR of 1.99 (95% CI:1.36–2.94). LI explained 7% of the variance in the relationship between BMI and oral cancer risk.

Conclusions

The distribution of the FA profile in erythrocyte membranes differed between the oral cancer patients and the control group. The LI derived from the profile of FAs was positively associated with the risk of oral cancer, and the associations between BMI and oral cancer risk can be explained, at least in part, by LI.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12944-022-01704-z.

Contribution of n-3 Long-Chain Polyunsaturated Fatty Acids to the Prevention of Breast Cancer Risk Factors

Nowadays, diet and breast cancer are studied at different levels, particularly in tumor prevention and progression. Thus, the molecular mechanisms leading to better knowledge are deciphered with a higher precision. Among the molecules implicated in a preventive and anti-progressive way, n-3 long chain polyunsaturated fatty acids (n-3 LC-PUFAs) are good candidates. These molecules, like docosahexaenoic (DHA) and eicosapentaenoic (EPA) acids, are generally found in marine material, such as fat fishes or microalgae. EPA and DHA act as anti-proliferative, anti-invasive, and anti-angiogenic molecules in breast cancer cell lines, as well as in in vivo studies. A better characterization of the cellular and molecular pathways involving the action of these fatty acids is essential to have a realistic image of the therapeutic avenues envisaged behind their use. This need is reinforced by the increase in the number of clinical trials involving more and more n-3 LC-PUFAs, and this, in various pathologies ranging from obesity to a multitude of cancers. The objective of this review is, therefore, to highlight the new elements showing the preventive and beneficial effects of n-3 LC-PUFAs against the development and progression of breast cancer.

Immunohistochemistry scoring of breast tumor tissue microarrays: A comparison study across three software applications

Digital pathology can efficiently assess immunohistochemistry (IHC) data on tissue microarrays (TMAs). Yet, it remains important to evaluate the comparability of the data acquired by different software applications and validate it against pathologist manual interpretation. In this study, we compared the IHC quantification of 5 clinical breast cancer biomarkers-estrogen receptor (ER), progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), epidermal growth factor receptor (EGFR), and cytokeratin 5/6 (CK5/6)-across 3 software applications (Definiens Tissue Studio, inForm, and QuPath) and benchmarked the results to pathologist manual scores. IHC expression for each marker was evaluated across 4 TMAs consisting of 935 breast tumor tissue cores from 367 women within the Nurses' Health Studies; each women contributing three 0.6-mm cores. The correlation and agreement between manual and software-derived results were primarily assessed using Spearman's ρ, percentage agreement, and area under the curve (AUC). At the TMA core-level, the correlations between manual and software-derived scores were the highest for HER2 (ρ ranging from 0.75 to 0.79), followed by ER (0.69-0.71), PR (0.67-0.72), CK5/6 (0.43-0.47), and EGFR (0.38-0.45). At the case-level, there were good correlations between manual and software-derived scores for all 5 markers (ρ ranging from 0.43 to 0.82), where QuPath had the highest correlations. Software-derived scores were highly comparable to each other (ρ ranging from 0.80 to 0.99). The average percentage agreements between manual and software-derived scores were excellent for ER (90.8%-94.5%) and PR (78.2%-85.2%), moderate for HER2 (65.4%-77.0%), highly variable for EGFR (48.2%-82.8%), and poor for CK5/6 (22.4%-45.0%). All AUCs across markers and software applications were ≥0.83. The 3 software applications were highly comparable to each other and to manual scores in quantifying these 5 markers. QuPath consistently produced the best performance, indicating this open-source software is an excellent alternative for future use.