Biology subjects

Bujko, M.

Publications and source records attributed to Bujko, M..

5 recordsLinked to original sources

bioRxiv2026

The Copy-Number Events in Skull Base Chordoma Stratify Tumours into Four Biologically Coherent Groups

Chordoma, a rare sarcoma of notochordal origin, exhibits slow growth and local aggressiveness. While copy-number (CN) events are recognized as key chordoma drivers, no comprehensive classification, based on CN, has yet been developed. Here, we establish a robust, reproducible genomic subtyping of chordoma, based on CN events. Two independent skull base chordoma cohorts (N=32,N=71) were analyzed, utilizing distinct analytical platforms, DNA methylation microarrays and whole-genome sequencing, both controlled for B-allele frequencies. Samples were clustered using unsupervised hierarchical methods. The CN events defined four consistent molecular clusters across both cohorts: C1 (CN-stable), C9 (chromosomal losses, especially of chr9/CDKN2A), C7 (chr7 gain), and C2 (gains of chr2 and chr7). The findings were validated in fluorescence in situ hybridization (FISH) with concordance of 84-89%. The CN clusters explain 31-33% of the RNA-sequencing transcriptional variance. Moreover, the C2 cluster showed up-regulation of Sonic Hedgehog signaling and clusters C2 and C9 were enriched in cell-cycle-related genes. The proposed CN clusters correlate with existing chordoma classificators e.g. chromosomal instability (CIN), mutation burden, immune score, and methylation clusters. Furthermore, comparison with over 2,000 sarcomas highlighted CN patterns more common in chordoma (i.e. chr1q, chr2, chr7 gains and chr1p, chr3, chr9, chr10, chr13, chr14, chr18 losses) but also revealed shared aberrations, e.g. chr22 loss shared with Gastrointestinal Stromal Tumours (GISTs). This study provides a unifying classification for skull base chordoma, linking distinct genomic architectures to specific transcriptional programs and potential therapeutic vulnerabilities.

cancer biology↗

bioRxiv2025

Transcriptomic perspective on acromegaly-related PIT-1/SF-1 positive pituitary tumors

Neuroendocrine pituitary tumors (PitNETs) are classified based on clinical manifestation and expression of pituitary cell lineage-specific transcription factors (TFs) and hormones. A subtype of acromegaly-related tumors was found to express PIT-1 and SF-1 TFs, two markers of distinct pituitary cells. They were considered as multilineage or "somatogonadotoph" tumors. The aim of our study was to determine their identity and cell type origin by extensive transcriptomic analysis. For this purpose, we analyzed the RNA sequencing (RNAseq) data from 546 PitNETs (including 193 acromegaly-related tumors) and single cell RNAseq data from somatotroph and gonadotroph tumors and normal pituitary. Somatrotroph PitNETs co-expressing PIT-1 and SF-1 TFs were found in each included RNAseq dataset. Their transcriptomic profile and activity of pituitary TFs closely resembles other somatotroph tumors, but they substantially differ from gonadotroph PitNETs yet retain activity of NR5A1 (SF-1) and expression of some of SF-1-regulated genes (LHB and GNHRH). SF-1 apparently regulates slightly different set of genes in double positive somatotroph PitNETs and gonadotroph tumors. Based on scRNAseq data a subcluster of normal gonadotroph cells with POU1F1 (PIT-1) expression was identified, but tumor cells of PIT-1/SF-1 PitNETs were not similar to this subtype of normal gonadotrophs. A difference in genes expression profiles between 3 subtypes of somatotroph tumors was determined by analysis of both bulk- and scRNAseq data. From transcriptomic perspective of genes-coregulation and the activity of pituitary transcription factors, acromegaly-related PitNETs co-expressing PIT-1 and SF-1 are subtype of PIT-1 lineage tumors and molecular data do not support considering them as multilineage.

molecular biology↗

bioRxiv2024

Pivotal role of biallelic frequency analysis in identifying copy number alterations using genome-wide methods in tumors with a high level of aneuploidy

Chromosome number abnormalities is one of the hallmarks of cancer. DNA copy number alterations (CNA) are studied using various genome-wide methods. In our study we investigated CNA in human pituitary tumors using three platforms CytoSNP-850K microarrays, low-pass whole-genome sequencing (average x7 coverage, LPWGS), and Infinium Methylation EPIC array. Virtual karyotypes based on each dataset were generated using open-source software packages for each sample. Concordant CNA profiles were found for most of tumor. Surprisingly, substantial discrepancies between results from SNP arrays and LPWGS/EPIC arrays were identified in 20% of tumors, for which discrimination of true karyotype was required. B-allelic frequency data from SNP arrays was crucial to adjust normal ploidy level as ultimately verified with FISH. The discrepancy between virtual karyotypes was more pronounced the more CNAs were found. When CNAs covered more than half of genome the level of normal/diploid copy number was incorrectly set with methods, based solely on signal intensity/read-counts coverage. To conclude, CNA analysis with methods such as LPWGS and methylation arrays in highly aneuploid tumors are prone to a bias from improper normal ploidy level setting. These methods are commonly used therefore we aimed to aware the scientific community about this underestimated methodological problem.

genomics↗

bioRxiv2022

Transcriptomic classification of pituitary neuroendocrine tumors causing acromegaly

Acromegaly results from growth hormone hypersecretion caused by somatotroph pituitary neuroendocrine tumor (PitNET). Our molecular profiling revealed that acromegaly-causing tumors form three distinct transcriptomic subgroups with different histological/clinical features. Transcriptomic subtypes of somatotroph tumors differ in the expression levels of numerous genes including those involved in hormone secretion and genes with known prognostic value. They can be distinguished by determining the expression of marker genes. Transcriptomic group 1 includes [~]20% of acromegaly patients with GNAS mutations-negative, mainly densely granulated tumors with NR5A1 (SF-1) and GIPR co-expression. Group 2 tumors are the most common (46%) and include mainly GNAS-mutated, densely granulated somatotroph and mixed PitNETs. They have significantly smaller size and express favorable prognosis-related genes. Group 3 includes predominantly sparsely granulated somatotroph PitNETs with low GNAS mutations frequency causing [~]35% of acromegaly cases. Ghrelin signaling is implied in their pathogenic mechanism, they have unfavorable gene expression profile, and invasive growth rate. Since a subgroup of somatotroph tumors have high NR5A1 expression, using SF-1 as classification marker specific to gonadotroph PitNETs could be reconsidered.

cancer biology↗

bioRxiv2020

TOP2A substitution enhances topoisomerase activity and causes transcriptional dysfunction in glioblastoma patients

BackgroundHigh grade gliomas (HGGs) are aggressive, primary brain tumors with poor clinical outcomes. We aim to better understand glioma pathobiology and find potential therapeutic susceptibilities. MethodsWe designed a custom panel of 664 cancer- and epigenetics-related genes, and employed targeted next generation sequencing to study the genomic landscape of somatic and germline variants in 182 gliomas of different malignancy grades. mRNA sequencing was performed to detect transcriptomic abnormalities. ResultsIn addition to known alterations in TP53, IDH1, ATRX, EGFR genes found in this cohort, we identified a novel, recurrent mutation in the TOP2A gene coding for Topoisomerase 2A occurring only in glioblastomas (GBM, WHO grade IV gliomas). Biochemical assays with recombinant proteins demonstrated stronger DNA binding and DNA supercoil relaxation activities of the variant proteins. GBM patients carrying the mutated TOP2A had shorter overall survival than those with the wild type TOP2A. Computational analyses of transcriptomic data showed that GBMs with the mutated TOP2A have different transcriptomic patterns suggesting higher transcriptomic activity. ConclusionWe identified a novel TOP2A E948Q variant that strongly binds to DNA and is more active than the wild type protein. Our findings suggest that the discovered TOP2A variant is gain-of-function mutation. Key pointsO_LIThe most frequent genetic alterations in high grade gliomas are reported. C_LIO_LIA new mutation in the TOP2A gene was found in 4 patients from Polish population. C_LIO_LIA E948Q substitution changes TOP2A activities towards DNA. C_LIO_LIThe recurrent TOP2A variant is a gain-of-function mutation. C_LI Importance of the studyGlioblastoma is a deadly disease. Despite recent advancements in genomics and innovative targeted therapies, glioblastoma therapy has not shown improvements. Insights into glioblastoma biology may improve diagnosis, prognosis, and treatment prediction, directing to a better outcome. We performed targeted sequencing of 664 cancer genes, and identified a new variant of the TOP2A gene encoding topoisomerase 2A in glioblastomas. The TOP2A protein variant shows a higher affinity towards DNA and causes transcriptional alterations, suggesting a higher de novo transcription rate.

cancer biology↗