👤 Malgorzata Kowalska

Preclinical atherosclerosis and prediabetes are key targets of preventive medicine as their prevalence rises. Therefore, it is crucial to identify early processes and limit confounders such as lipid-lowering or antidiabetic therapy and advanced atherosclerosis. Proteomics enables the identification of biomarkers and molecular pathways related to atherogenesis in prediabetes. To investigate the relationship between prediabetes and preclinical atherosclerosis in apparently healthy individuals using a comprehensive proteomic approach. This cross-sectional, population-based study included 389 participants (mean age 49 ± 10 years; 47% males) from the Białystok PLUS cohort in Poland. Individuals with known diabetes, major cardiovascular, inflammatory, or malignant diseases, or those receiving steroidal or lipid-lowering therapy were excluded. Carotid ultrasound was used to assess preclinical atherosclerosis, and prediabetes was defined as impaired fasting glucose, impaired glucose tolerance, or HbA1c 5.7–6.4%. Proteomic profiling was performed using the Olink® Reveal platform, enabling deep profiling of 1050 proteins with the Proximity Extension Assay and next-generation sequencing readout, yielding log2-scaled NPX (Normalized Protein eXpression) values. In preliminary analyses, we identified proteins associated with prediabetes and then linked them to early atherosclerotic lesions. A block-sPLS-DA model integrating clinical and proteomic data revealed clear separation between participants with and without prediabetes. The clinical block comprised eight variables reflecting cardiometabolic status, whereas the proteomic block retained 45 proteins across two components. The heatmap shows pairwise Pearson correlations between selected serum proteins and clinical variables (Fig. 1). Vascular and age measures cluster together and share correlation patterns distinct from those of BMI and glycaemic parameters. A protein module including the ectodysplasin A2 receptor (EDA2R) and leiomodin 1 (LMOD1) correlates positively with age and vascular parameters, and inversely with GFR and HDL-C. Multivariable linear regression analyses were performed with selected vascular parameters as dependent variables and clinical covariates, together with proteins identified in Component 2, which are weakly related to clinical parameters and thus may represent novel biomarkers associated with prediabetes (Fig. 2). Expression of EDA2R (B = 0.05; An integrative block-sPLS-DA approach separated individuals with prediabetes from those without and revealed a proteomic signature independent of clinical covariates. Within this signature, the expression of LMOD1, EDA2R, and C16orf89 showed robust associations with atherosclerosis-related vascular traits. Enrichment analyses highlighted proteins involved in neuronal processes as candidate pathways linking early glucose disturbances with preclinical atherosclerosis. The online version contains supplementary material available at 10.1186/s12933-026-03128-w. Show less

In the present work, the 3T3-L preadipocytes were utilized to explore the impact of Obtained results showed the ability of RCE to reduce lipid overloads in hypertrophic adipocytes associated with the down-regulation of mRNA expressions of adipogenic transcription factors such as Show less

Transcriptome of papillary thyroid cancer (PTC) is well characterized and correlates with some prognostic and genotypic factors, but data addressing the interaction between PTC and tumor microenvironment (TME) are scarce. Therefore, in the present study, we aimed to assess the impact of TME on gene expression profile in PTC. We evaluated the gene expression profile in PTC and normal thyroid cells isolated by laser capture microdissection and in whole tissue slides corresponding to the entire tumor. We included 26 microdissected samples for gene expression analysis (HG-U133 PLUS 2.0, Affymetrix, currently Thermo Fisher Scientific USA): 15 PTC samples, 11 samples of normal thyrocytes, and 30 whole slides (15 PTC and 15 normal thyroid). Transcripts were divided into three groups: differentially expressed both in microdissected and whole slides, transcripts differently expressed in microdissected samples and not changed in whole slides, and transcripts differentially expressed in whole slides and not changed in microdissected samples. Eleven genes were selected for validation in an independent set of samples; among them, four genes differentiated only microdissected PTC and normal cells. Two genes (PTCSC and CTGF) were confirmed. One gene (FOS) was not confirmed by the validation, whereas EGR1 was also significant in whole slide analysis. The other seven genes (TFF3, FN1, MPPED2, MET, KCNJ2, TACSTD2, and GALE) showed differentiated expression in microdissected thyrocytes and in whole tumor slides. Most of identified genes were related to the tumor-microenvironment interaction and confirmed the crosstalk between TME and cancer cells. Show less

Several studies have shown the prognostic and predictive potential of molecular markers in combined therapy for lung cancer. Most of them referred, however, to operable early stage NSCLC. The aim of the present study is to correlate the expression of multiple mRNA markers in bronchoscopy obtained cancer specimens with clinical outcome of advanced lung cancer. Bronchoscopy cancer specimens were taken from 123 patients with radiological diagnosis of advanced lung tumor. Out of 123 patients 50 were diagnosed with squamous cell cancer, 17 with adenocarcinoma, 12 with NOS, 32 with SCLC and one with large cell neuroendocrinal cancer. In 11 patients other tumours were diagnosed. The group was heterogeneous with respect to clinical stage, performance of the patients and treatment. Quantitative real time PCR was carried out by ABI 7900 HT machine, with Universal Probe Library (Roche) fluorescent probes. The genes selected for the analysis were ERCC1, EGFR, BRCA1, CSF1, CA9, DUSP6, STAT1, ERBB3, MMD, FN1, and CDKN1B. More than 50 ng of RNA (the amount considered sufficient for the analysis) was isolated in 82 out of 112 lung cancer specimens (73%), including 60/80 (75.0%) of NSCLC specimens and 22/32 (68,7%) of SCLC samples. The highest Cohen's κ coefficient for discrimination between small cell, squamous cell and adenocarcinoma was found for CDKN1B, CSF and EGFR1 (κ = 0.177, p = 0.0041). A multivariate Cox regression model has shown a significant impact of clinical stage (p<0.001, RR = 4.19), ERCC1 (p = 0.01, RR = 0.43) and CA9 (p = 0.03, RR = 2.11) expression on overall survival in a group of 60 patients with NSCLC. These results show the feasibility of multiple gene expression analysis in bronchoscopy obtained cancer specimens as prognostic markers in radiotherapy and chemotherapy for advanced lung cancer. A limiting factor was relatively high proportion of samples from which sufficient amount of RNA could not be isolated. Show less

The aim of the study was to evaluate smoking prevalence and exposure to environmental tobacco smoke among school administrators. The study population consisted of 320 administrative workers in schools from Lodz district. Among the study participants self-administrative questionnaire was conducted. The questionnaire focused on socio-demographic characteristics, detail information about active smoking and environmental tobacco smoke exposure. Current tobacco smoking was indicated by 19% of women and 28% of men (p = 0.06). Only 35% of the study subjects declared willingness to give up the habit. Significantly less men than women felt that they should quit smoking (36% vs. 11.4%, p < 0.05). Only small part of the study population expected the help in quitting smoking from specialists, physicians or school. It is crucial to increase awareness among the school administrators about negative effects of smoking and to motivate them to give up the habit. About 7% of study subjects (5% of women and 11% of men, p < 0.05) declared that smoking is allowed in school building and 13% of them indicated that there are no regulations on it or did not know such regulations. Show less