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Abstract Background BReast CAncer gene 1 (BRCA1) and BReast CAncer gene 2 (BRCA2) encode for tumor suppressor proteins which are critical regulators of the Homologous Recombination (HR) pathway, the most precise and important DNA damage response mechanism. Dysfunctional HR proteins cannot repair double-stranded DNA breaks in mammalian cells, a situation called HR deficiency. Since their identification, pathogenic variants and other alterations of BRCA1 and BRCA2 genes have been associated with an increased risk of developing mainly breast and ovarian cancer. Interestingly, HR deficiency is also detected in tumors not carrying BRCA1/2 mutations, a condition termed “BRCAness”. Main text One of the main mechanisms causing the BRCAness phenotype is the methylation of the BRCA1/2 promoters, and this epigenetic modification is associated with carcinogenesis and poor prognosis mainly among patients with breast and ovarian cancer. BRCA1 promoter methylation has been suggested as an emerging biomarker of great predictive significance, especially concerning Poly (ADP-ribose) Polymerase inhibitors (PARP inhibitor-PARPi) responsiveness, along with or beyond BRCA1/2 mutations. However, as its clinical exploitation is still insufficient, the impact of BRCA1/2 promoter methylation status needs to be further evaluated. The current review aims to gather the latest findings about the mechanisms that underline BRCA1/2 function as well as the molecular characteristics of tumors associated with BRCA1/2 defects, by focusing on DNA methylation. Furthermore, we critically analyze their translational meaning and the validity of BRCA methylation biomarkers in predicting treatment response. Conclusions We believe that BRCA1/2 methylation alone or combined with other biomarkers in a clinical setting is expected to change the scenery in prognosis and predicting treatment response in multiple cancer types and is worthy of further attention. The quantitative BRCA1 promoter methylation assessment might predict treatment response in PARPi and analysis of BRCA1/2 methylation in liquid biopsy might define patient subgroups at different time points that may benefit from PARPi. Finally, we suggest a pipeline that could be implemented in liquid biopsy to aid precision pharmacotherapy in BRCA-associated tumors.

In total, 3274 adults (65.2% females) from six European countries were included in this cross-sectional analysis using data from the baseline assessment of the Feel4Diabetes study. Anthropometric, sociodemographic, dietary and behavioral data were assessed, and the existence of metabolic syndrome (MetS) was recorded. Beverage consumption patterns (BCPs) were derived via principal component analysis. Three BCPs were derived explaining 39.5% of the total variation. BCP1 was labeled as “Alcoholic beverage pattern”, which loaded heavily on high consumption of beer/cider, wine and other spirits; BCP2 was labeled as “High in sugars beverage pattern” that was mainly characterized by high consumption of soft drinks with sugar, juice containing sugar and low consumption of water; and BCP3 was labeled as “Healthy beverage pattern” that was mainly characterized by high consumption of water, tea, fruit juice freshly squeezed or prepacked without sugar and low consumption of soft drinks without sugar. After adjusting for various confounders, BCP2 was positively associated with elevated triglycerides (p = 0.001), elevated blood pressure (p = 0.001) elevated fasting glucose (p = 0.008) and the existence of MetS (p = 0.006), while BCP1 was inversely associated with reduced HDL-C (p = 0.005) and BCP3 was inversely associated with elevated blood pressure (p = 0.047). The establishment of policy actions as well as public health nutritional education can contribute to the promotion of a healthy beverage consumption.

Abstract Schizophrenia (SCZ) is a chronic, severe, and complex psychiatric disorder that affects all aspects of personal functioning. While SCZ has a very strong biological component, there are still no objective diagnostic tests. Lately, special attention has been given to epigenetic biomarkers in SCZ. In this study, we introduce a three-step, automated machine learning (AutoML)-based, data-driven, biomarker discovery pipeline approach, using genome-wide DNA methylation datasets and laboratory validation, to deliver a highly performing, blood-based epigenetic biosignature of diagnostic clinical value in SCZ. Publicly available blood methylomes from SCZ patients and healthy individuals were analyzed via AutoML, to identify SCZ-specific biomarkers. The methylation of the identified genes was then analyzed by targeted qMSP assays in blood gDNA of 30 first-episode drug-naïve SCZ patients and 30 healthy controls (CTRL). Finally, AutoML was used to produce an optimized disease-specific biosignature based on patient methylation data combined with demographics. AutoML identified a SCZ-specific set of novel gene methylation biomarkers including IGF2BP1, CENPI, and PSME4. Functional analysis investigated correlations with SCZ pathology. Methylation levels of IGF2BP1 and PSME4, but not CENPI were found to differ, IGF2BP1 being higher and PSME4 lower in the SCZ group as compared to the CTRL group. Additional AutoML classification analysis of our experimental patient data led to a five-feature biosignature including all three genes, as well as age and sex, that discriminated SCZ patients from healthy individuals [AUC 0.755 (0.636, 0.862) and average precision 0.758 (0.690, 0.825)]. In conclusion, this three-step pipeline enabled the discovery of three novel genes and an epigenetic biosignature bearing potential value as promising SCZ blood-based diagnostics.

The role of the microbiome in cancer and its crosstalk with the tumor microenvironment (TME) has been extensively studied and characterized. An emerging field in the cancer microbiome research is the concept of the intratumoral microbiome, which refers to the microbiome residing within the tumor. This microbiome primarily originates from the local microbiome of the tumor-bearing tissue or from translocating microbiome from distant sites, such as the gut. Despite the increasing number of studies on intratumoral microbiome, it remains unclear whether it is a driver or a bystander of oncogenesis and tumor progression. This review aims to elucidate the intricate role of the intratumoral microbiome in tumor development by exploring its effects on reshaping the multileveled ecosystem in which tumors thrive, the TME. To dissect the complexity and the multitude of layers within the TME, we distinguish six specialized tumor microenvironments, namely, the immune, metabolic, hypoxic, acidic, mechanical and innervated microenvironments. Accordingly, we attempt to decipher the effects of the intratumoral microbiome on each specialized microenvironment and ultimately decode its tumor-promoting or tumor-suppressive impact. Additionally, we portray the intratumoral microbiome as an orchestrator in the tumor milieu, fine-tuning the responses in distinct, specialized microenvironments and remodeling the TME in a multileveled and multifaceted manner.

Introduction: Determining the effect of body composition on chronic low back pain seems to have the potential to improve our understanding of its mechanism and to develop novel preventive and therapeutic approaches. Aim: The purpose of the present study was to assess by electrical impedance the composition of lower extremities of individuals with chronic low back pain.Materials and methods: One hundred and twenty-one adult participants with diagnosed chronic low back pain were recruited in this study. The study activities were divided into three phases: phase 1 – self-administered questionnaires, phase 2 – biomedical examination (including anthropometric measurements and physical function performance tests), and phase 3 – bioimpedance analysis.Results: Our results showed that chronic low back pain differentiates the circumference of thigh and calf of the symptomatic leg. Besides, patients experience pain also in hip, thigh, and calf, which act as a barrier to patient’s personal, professional, social, and recreational activities. Furthermore, patients appear with ‘unstable’ walking, reduced balance, and reduced general physical condition that affect all of the neuromuscular structures of the locomotor system. Interestingly, patients seem to be characterized by a tendency to deposit fat and to decrease muscle mass in the symptomatic limb regardless of the gender.Conclusions: In the present study, we determine the profile of a patient with chronic low back pain through a variety of measurements. Chronic low back pain causes several structural changes to the symptomatic leg of the patients leading to ‘unstable’ walking, reduced balance, and reduced general physical condition. It is clear that further studies using bioimpedance analysis are needed to address the concerns raised by investigating a multifactorial condition such as chronic low back pain.

Abstract COVID-19 outbreak brings intense pressure on healthcare systems, with an urgent demand for effective diagnostic, prognostic and therapeutic procedures. Here, we employed Automated Machine Learning (AutoML) to analyze three publicly available high throughput COVID-19 datasets, including proteomic, metabolomic and transcriptomic measurements. Pathway analysis of the selected features was also performed. Analysis of a combined proteomic and metabolomic dataset led to 10 equivalent signatures of two features each, with AUC 0.840 (CI 0.723–0.941) in discriminating severe from non-severe COVID-19 patients. A transcriptomic dataset led to two equivalent signatures of eight features each, with AUC 0.914 (CI 0.865–0.955) in identifying COVID-19 patients from those with a different acute respiratory illness. Another transcriptomic dataset led to two equivalent signatures of nine features each, with AUC 0.967 (CI 0.899–0.996) in identifying COVID-19 patients from virus-free individuals. Signature predictive performance remained high upon validation. Multiple new features emerged and pathway analysis revealed biological relevance by implication in Viral mRNA Translation, Interferon gamma signaling and Innate Immune System pathways. In conclusion, AutoML analysis led to multiple biosignatures of high predictive performance, with reduced features and large choice of alternative predictors. These favorable characteristics are eminent for development of cost-effective assays to contribute to better disease management.

Cervical cancer is strongly related to certain high-risk types of human papilloma virus infection. Breast cancer metastasis suppressor 1 (BRMS1) is a tumor suppressor gene, its expression being regulated by DNA promoter methylation in several types of cancers. This study aims to evaluate the methylation status of BRMS1 promoter in relation to high-risk types of human papilloma virus infection and the development of pre-cancerous lesions and describe the pattern of BRMS1 protein expression in normal, high-risk types of human papilloma virus–infected pre-cancerous and malignant cervical epithelium. We compared the methylation status of BRMS1 in cervical smears of 64 women with no infection by high-risk types of human papilloma virus to 70 women with proven high-risk types of human papilloma virus infection, using real-time methylation-specific polymerase chain reaction. The expression of BRMS1 protein was described by immunohistochemistry in biopsies from cervical cancer, pre-cancerous lesions, and normal cervices. Methylation of BRMS1 promoter was detected in 37.5% of women with no high-risk types of human papilloma virus infection and was less frequent in smears with high-risk types of human papilloma virus (11.4%) and in women with pathological histology (cervical intraepithelial neoplasia) (11.9%). Methylation was detected also in HeLa cervical cancer cells. Immunohistochemistry revealed nuclear BRMS1 protein staining in normal high-risk types of human papilloma virus–free cervix, in cervical intraepithelial neoplasias, and in malignant tissues, where staining was occasionally also cytoplasmic. In cancer, expression was stronger in the more differentiated cancer blasts. In conclusion, BRMS1 promoter methylation and aberrant protein expression seem to be related to high-risk types of human papilloma virus–induced carcinogenesis in uterine cervix and is worthy of further investigation.