Metabolic Syndrome and Risk of Breast Cancer by Molecular Subtype: Analysis of the MEND Study

J-shaped association between uric acid and breast cancer risk: a prospective case-control study

BACKGROUND/AIM

In terms of breast cancer risk, there is no consensus on the effect of uric acid (UA) levels. The aim of our study was to clarify the link between UA and breast cancer risk in a prospective case-control study and to find the UA threshold point.

METHODS

We designed a case-control study with 1050 females (525 newly diagnosed breast cancer patients and 525 controls). We measured the UA levels at baseline and confirmed the incidence of breast cancer through postoperative pathology. We used binary logistic regression to study the association between breast cancer and UA. In addition, we performed restricted cubic splines to evaluate the potential nonlinear links between UA and breast cancer risk. We used threshold effect analysis to identify the UA cut-off point.

RESULTS

After adjusting for multiple confounding factors, we found that compared with the referential level (3.5-4.4 mg/dl), the odds ratio (OR) of breast cancer was 1.946 (95% CI 1.140-3.321) (P < 0.05) in the lowest UA level and 2.245 (95% CI 0.946-5.326) (P > 0.05) in the highest level. Using the restricted cubic bar diagram, we disclosed a J-shaped association between UA and breast cancer risk (P-nonlinear < 0.05) after adjusting for all confounders. In our study, 3.6 mg/dl was found to be the UA threshold which acted as the optimal turning point of the curve. The OR for breast cancer was 0.170 (95% CI 0.056-0.512) to the left and 1.283 (95% CI 1.074-1.532) to the right of 3.6 mg/dl UA (P for log likelihood ratio test < 0.05).

CONCLUSION

We found a J-shaped association between UA and breast cancer risk. Controlling the UA level around the threshold point of 3.6 mg/dl provides a novel insight into breast cancer prevention.

Prevalence of the metabolic syndrome in African populations: A systematic review and meta-analysis

BACKGROUND

The metabolic syndrome (MS) is a leading cause of death worldwide. Several studies have found MS to be prevalent in various African regions. However, no specific estimates of MS prevalence in African populations exist. The aim of this study was to estimate the overall prevalence of MS in the African populations.

METHODS

A systematic review was conducted in PubMed, Web of Science, Africa Index Medicus, and African Journal Online Scopus to find studies published up to the 15th of August 2022. Pooled prevalence was calculated based on six diagnostic methods. The pooled prevalence of MS was estimated using a random-effects model. Our risk of bias analysis was based on the Hoy et al. tool. A Heterogeneity (I2) assessment was performed, as well as an Egger test for publication bias. PROSPERO number CRD42021275176 was assigned to this study.

RESULTS

In total, 297 studies corresponding to 345 prevalence data from 29 African countries and involving 156 464 participants were included. The overall prevalence of MS in Africa was 32.4% (95% CI: 30.2-34.7) with significant heterogeneity (I2 = 98.9%; P<0.001). We obtained prevalence rates of 44.8% (95% CI: 24.8-65.7), 39.7% (95% CI: 31.7-48.1), 33.1% (95% CI: 28.5-37.8), 31.6% (95% CI: 27.8-35.6) and 29.3% (95% CI: 25.7-33) using the WHO, revised NCEP-ATP III, JIS, NCEP/ATP III and IDF definition criteria, respectively. The prevalence of MS was significantly higher in adults >18 years with 33.1% (95%CI: 30.8-35.5) compared to children <18 years with 13.3% (95%CI: 7.3-20.6) (P<0.001). MS prevalence was significantly higher in females with 36.9% (95%CI: 33.2-40.7) compared to males with 26.7% (95%CI: 23.1-30.5) (P<0.001). The prevalence of MS was highest among Type 2 diabetes patients with 66.9% (95%CI: 60.3-73.1), followed by patients with coronary artery disease with 55.2% (95%CI: 50.8-59.6) and cardiovascular diseases with 48.3% (95%CI: 33.5-63.3) (P<0.001). With 33.6% (95% CI: 28.3-39.1), the southern African region was the most affected, followed by upper-middle income economies with 35% (95% CI: 29.5-40.6).

CONCLUSION

This study, regardless of the definition used, reveals a high prevalence of MS in Africa, confirming the ongoing epidemiological transition in African countries. Early prevention and treatment strategies are urgently needed to reverse this trend.

Updates on Triple-Negative Breast Cancer in Type 2 Diabetes Mellitus Patients: From Risk Factors to Diagnosis, Biomarkers and Therapy

Triple-negative breast cancer (TNBC) is usually the most malignant and aggressive mammary epithelial tumor characterized by the lack of expression for estrogen receptors and progesterone receptors, and the absence of epidermal growth factor receptor (HER)2 amplification. Corresponding to 15-20% of all breast cancers and well-known by its poor clinical outcome, this negative receptor expression deprives TNBC from targeted therapy and makes its management therapeutically challenging. Type 2 diabetes mellitus (T2DM) is the most common ageing metabolic disorder due to insulin deficiency or resistance resulting in hyperglycemia, hyperinsulinemia, and hyperlipidemia. Due to metabolic and hormonal imbalances, there are many interplays between both chronic disorders leading to increased risk of breast cancer, especially TNBC, diagnosed in T2DM patients. The purpose of this review is to provide up-to-date information related to epidemiology and clinicopathological features, risk factors, diagnosis, biomarkers, and current therapy/clinical trials for TNBC patients with T2DM compared to non-diabetic counterparts. Thus, in-depth investigation of the diabetic complications on TNBC onset, development, and progression and the discovery of biomarkers would improve TNBC management through early diagnosis, tailoring therapy for a better outcome of T2DM patients diagnosed with TNBC.

Identification of Hub Genes and Biological Mechanisms Associated with Non-Alcoholic Fatty Liver Disease and Triple-Negative Breast Cancer

The relationship between non-alcoholic fatty liver disease (NAFLD) and triple-negative breast cancer (TNBC) has been widely recognized, but the underlying mechanisms are still unknown. The objective of this study was to identify the hub genes associated with NAFLD and TNBC, and to explore the potential co-pathogenesis and prognostic linkage of these two diseases. We used GEO, TCGA, STRING, ssGSEA, and Rstudio to investigate the common differentially expressed genes (DEGs), conduct functional and signaling pathway enrichment analyses, and determine prognostic value between TNBC and NAFLD. GO and KEGG enrichment analyses of the common DEGs showed that they were enriched in leukocyte aggregation, migration and adhesion, apoptosis regulation, and the PPAR signaling pathway. Fourteen candidate hub genes most likely to mediate NAFLD and TNBC occurrence were identified and validation results in a new cohort showed that ITGB2, RAC2, ITGAM, and CYBA were upregulated in both diseases. A univariate Cox analysis suggested that high expression levels of ITGB2, RAC2, ITGAM, and CXCL10 were associated with a good prognosis in TNBC. Immune infiltration analysis of TNBC samples showed that NCF2, ICAM1, and CXCL10 were significantly associated with activated CD8 T cells and activated CD4 T cells. NCF2, CXCL10, and CYBB were correlated with regulatory T cells and myeloid-derived suppressor cells. This study demonstrated that the redox reactions regulated by the NADPH oxidase (NOX) subunit genes and the transport and activation of immune cells regulated by integrins may play a central role in the co-occurrence trend of NAFLD and TNBC. Additionally, ITGB2, RAC2, and ITGAM were upregulated in both diseases and were prognostic protective factors of TNBC; they may be potential therapeutic targets for treatment of TNBC patients with NAFLD, but further experimental studies are still needed.

Characterization of Immune-Based Molecular Subtypes and Prognostic Model in Prostate Adenocarcinoma

Prostate adenocarcinoma (PRAD), also named prostate cancer, the most common visceral malignancy, is diagnosed in male individuals. Herein, in order to obtain immune-based subtypes, we performed an integrative analysis to characterize molecular subtypes based on immune-related genes, and further discuss the potential features and differences between identified subtypes. Simultaneously, we also construct an immune-based risk model to assess cancer prognosis. Our findings showed that the two subtypes, C1 and C2, could be characterized, and the two subtypes showed different characteristics that could clearly describe the heterogeneity of immune microenvironments. The C2 subtype presented a better survival rate than that in the C1 subtype. Further, we constructed an immune-based prognostic model based on four screened abnormally expressed genes, and they were selected as predictors of the robust prognostic model (AUC = 0.968). Our studies provide reference for characterization of molecular subtypes and immunotherapeutic agents against prostate cancer, and the developed robust and useful immune-based prognostic model can contribute to cancer prognosis and provide reference for the individualized treatment plan and health resource utilization. These findings further promote the development and application of precision medicine in prostate cancer.