Biology subjects

Dumanski, J. P.

Publications and source records attributed to Dumanski, J. P..

5 recordsLinked to original sources

bioRxiv2025

The effect of cold ischemia time on hypoxia, EMT, and apoptosis pathways in normal colon mucosa

Cold ischemia time (CIT), the interval between tissue excision and preservation, is a critical preanalytical variable that profoundly impacts gene expression profiles. Variability in CIT can lead to inconsistent transcriptomic results, making study interpretation challenging and undermining reproducibility in biomedical research. Our study aimed to evaluate the impact of CIT on the expression of cancer-related genes, particularly these involved in hypoxia, apoptosis, and epithelial-to-mesenchymal transition (EMT). We performed RNA sequencing on 54 normal colon mucosa samples from nine patients undergoing colorectal cancer surgeries, freezing samples at predefined intervals ranging from 0 to 60 minutes. A total of 44 differentially expressed genes (DEGs) (p < 0.05) were identified when comparing samples frozen immediately (T0) with those frozen after 60 minutes (T5). These DEGs were further analyzed through functional and pathway enrichment analyses and weighted gene coexpression network analysis (WGCNA). The enrichment analysis revealed significant alterations in pathways associated with apoptosis, hypoxia, EMT, and cancer progression, including p53 and HIF-1 signaling. WGCNA highlighted two co-expressed gene modules: ME2, which showed downregulation of apoptosis-related genes, and ME4, linked to apoptosis and cellular metabolism. Our findings highlight CIT as a critical preanalytical variable, showing that prolonged ischemia can induce transcriptomic changes that may mimic malignancy, and potentially confound research outcomes. To minimize such effects, we recommend keeping CIT under 45-60 minutes.

cancer biology↗

bioRxiv2024

Prelude to Malignancy: A Gene Expression Signature in Normal Mammary Gland from Breast Cancer Patients Suggests Pre-tumorous Alterations and Is Associated with Adverse Outcomes

Despite advances in early detection and treatment strategies, breast cancer recurrence and mortality remain a significant health issue. Recent insights suggest the prognostic potential of microscopically healthy mammary gland, in the vicinity of the breast lesion. Nonetheless, a comprehensive understanding of the gene expression profiles in these tissues and their relationship to patient outcomes is still missing. Furthermore, the increasing trend towards breast-conserving surgery may inadvertently lead to the retention of existing cancer-predisposing mutations within the normal mammary gland. This study assessed the transcriptomic profiles of 242 samples from 83 breast cancer patients with unfavorable outcomes, including paired uninvolved mammary gland samples collected at varying distances from primary lesions. As a reference, control samples from 53 mammoplasty individuals without cancer history were studied. A custom panel of 634 genes linked to breast cancer progression and metastasis was employed for expression profiling, followed by whole-transcriptome verification experiments and statistical analyses to discern molecular signatures and their clinical relevance. A distinct gene expression signature was identified in uninvolved mammary gland samples, featuring key cellular components encoding keratins, CDH1, CDH3, EPCAM cell adhesion proteins, matrix metallopeptidases, oncogenes, tumor suppressors, along with crucial genes (FOXA1, RAB25, NRG1, SPDEF, TRIM29, and GABRP) having dual roles in cancer. Enrichment analyses revealed disruptions in epithelial integrity, cell adhesion, and estrogen signaling. This signature, named KAOS for Keratin-Adhesion-Oncogenes-Suppressors, was significantly associated with reduced tumor size but increased mortality rates. Integrating molecular assessment of non-malignant mammary tissue into disease management could enhance survival prediction and facilitate personalized patient care.

genomics↗

bioRxiv2022

Size matters - the impact of nucleus size on results from spatial transcriptomics

Visium Spatial Gene Expression (ST) is a method combining histological spatial information with transcriptomics profiles directly from tissue sections. The use of spatial information has made it possible to discover novel modes of gene expression regulations. However, in the ST experiment, the nucleus size of cells may exceed the thickness of a tissue slice. This may, in turn, negatively affect comprehensive capturing the transcriptomics profile in a single slice, especially for tissues having large differences in the size of nuclei. Here, we defined the effect of Consecutive Slices Data Integration (CSDI) on results from spatial transcriptomic study of human postmortem brains. CSDI can be applied to investigate consecutive sections studied with ST in the human cerebral cortex, avoiding misinterpretation of spot clustering and annotation, increasing accuracy of cell recognition as well as improvement in uncovering the layers of grey matter in the human brain.

bioinformatics↗

bioRxiv2019

Loss of Y in leukocytes, dysregulation of autosomal immune genes and disease risks

Mosaic loss of chromosome Y (LOY) in leukocytes has been associated with many diseases, yet it remains unclear whether this form of clonal mosaicism exerts a direct physiological effect. Here we perform single-cell and bulk RNA sequencing in leukocytes, observing considerable variation in the rate of LOY across individuals, cell types and disease state. Cells with LOY demonstrated a profound degree of transcriptional dysregulation impacting [~]500 autosomal genes. These genes are preferentially involved in immune functions but also encode proteins with roles in other diverse biological processes. Our findings highlight a surprisingly broad role for chromosome Y challenging the view of it as a "genetic wasteland". Furthermore, they support the hypothesis that altered immune function in leukocytes is a mechanism directly linking LOY to disease.

immunology↗

bioRxiv2019

Intra-individual changes in the frequency of mosaic loss of chromosome Y over time estimated with a new method

BackgroundMosaic loss of chromosome Y (LOY) is the most common somatic mutation and is associated with all-cause mortality, non-haematological cancers and Alzheimers disease among other outcomes. The predominant method used for estimating LOY is the intensity data generated by SNP-arrays, which is difficult to interpret due to its logarithmic scale. Here we describe a new way to convert the LOY mosaicism into a non-logarithmic scale, which instead represents the percentage of affected cells.\n\nMethodsWe compared three independent LOY readouts from matched samples, generated by SNP-array, whole genome sequencing and droplet digital PCR. The SNP-array standardization was derived from this comparison and was applied in analyses of serially collected samples from a large cohort of aging men. The sampling was performed up to five times, spanning up to 22 years.\n\nResultsWe observed a higher correlation between the LOY measurements from SNP-array and the two other readouts when using the standardized, instead of the logarithmic, SNP-array data. We also observed a pronounced intra-individual variation of changes in the frequency of LOY within individual males over time.\n\nConclusionsDescribing LOY measurements generated from SNP-arrays in percentage of cells without the Y chromosome makes comparisons to WGS and ddPCR measurements more precise and easier to interpret. This standardization could be applied to the vast amount of SNP-array data already generated in the scientific community, allowing further discoveries of LOY associated disease and outcomes. Additionally, the frequency of LOY in this study changed profoundly within men over time, likely as a result of aberrant clonal expansions.

genetics↗