Biology subjects

Buchner, A.

Publications and source records attributed to Buchner, A..

4 recordsLinked to original sources

bioRxiv2025

Exploration of oncogenic cooperation between germline variation and somatic mutation in prostate cancer progression

Prostate carcinoma (PCa) is the most common cancer of men, associated with a still unresolved issue of accurate risk-stratification. While recent advances in omics technologies have provided clues as to how molecular changes shape the onset and progression of PCa, it remains largely unclear whether germline variants and somatic mutations cooperate to contribute to PCa progression and outcome. Thus, we explored whether oncogenic cooperation between regulatory germline variants and somatic driver mutations can help explain why some PCa patients develop a more aggressive phenotype, which may have implications for risk-adapted medical treatment. Here, by employing an integrative functional genomics approach, we identified receptor-type protein-tyrosine phosphatase kappa (PTPRK) as a TMPRSS2::ERG (TE)-modulated gene associated with PCa progression whose expression is controlled by cooperation of the TE-fusion with a regulatory single nucleotide polymorphism (SNP). Analysis of available clinically annotated patient cohorts demonstrated that PTPRK is overexpressed in TE-positive PCa tumors and associated with higher Gleason scores and metastatic disease. TE knockdown in PCa cell lines reduced PTPRK expression, while ectopic overexpression of the fusion in TE-negative PCa cell lines and prostatic epithelium cells induced its expression. Functionally, PTPRK silencing inhibited cellular proliferation, cell cycle progression, and clonogenic growth of PCa cells, which was mirrored by dysregulation of corresponding gene and protein signatures in global transcriptomic and phospho-proteomic analyses after PTPRK knockdown. Analysis of TE ChIP-Seq and Hi-C data from PCa cells highlighted a proximal TE-bound DNA element whose TE-dependent enhancer activity was validated in reporter assays and which could be abrogated by a regulatory SNP. Collectively, our results provide evidence of how exploration of oncogenic cooperation may help to identify novel biomarkers and potentially druggable pathways and highlight the role of the regulatory genome in PCa progression.

cancer biology↗

bioRxiv2022

Single molecule long-read real-time amplicon-based sequencing of CYP2D6: a proof-of-concept with hybrid haplotypes

CYP2D6 is a widely expressed human xenobiotic metabolizing enzyme, best known for its role in the hepatic phase I cytochrome P450 enzyme system, where it metabolizes [~]20% of medications. It is also expressed in other organs including the brain, where its potential role in physiology and mental health traits and disorders is under further investigation. Owing to the presence of homologous pseudogenes in the CYP2D locus and transposable repeat elements in the intergenic regions, the gene encoding the CYP2D6 enzyme, CYP2D6, is one of the most hypervariable known human genes - with more than 165 core haplotypes. Haplotypes include structural variants, with a subtype of these known as hybrid haplotypes or fusion genes comprising part of CYP2D6 and part of its adjacent pseudogene, CYP2D7. The fusion genes are particularly challenging to identify. High fidelity (HiFi) single molecule real-time (SMRT) long-read sequencing can cover whole CYP2D6 haplotypes in a single continuous sequence, and is therefore ideal for structural variant detection. In addition, it is highly accurate and suitable for novel haplotype identification, which is necessary as new CYP2D6 haplotypes are continuously being discovered, and many more likely remain to be identified in relatively understudied populations such as Indigenous Peoples. The aim of the present work was to develop an efficient and accurate HiFi SMRT amplicon-based method capable of detecting the full range of CYP2D6 haplotypes including fusion genes. We report proof-of-concept for 24 amplicons including three positive controls, aligned to fusion gene haplotypes, with prior cross-validation data. Amplicons with CYP2D7-D6 fusion genes, including positive controls, aligned to the *13 subhaplotypes predicted (*13F, *13A2) with 100% accuracy, with the exception of one that aligned at 99.9%. Alignment of the *68 was 100% and above 99.9% to the CYP2D6*68 partial sequences EU5300606 and JF307779, respectively. The best alignments for the remaining CYP2D6-2D7 fusion genes were [≥]99.7% (to 3 significant figures). Lower percentage alignment for CYP2D6-2D7 fusion genes may reflect imperfect PCR optimization and/or the possibility that we may have haplotypes not yet in public databases. Further work on these is in progress. Moreover, we have adapted this method for non-hybrid haplotypes. This technique could therefore suffice for the characterization of the full range of CYP2D6 haplotypes. The method that we have developed could be extended to other complex loci and to other species in a multiplexed high throughput assay.

genomics↗

bioRxiv2020

Trade-offs and design principles in the spatial organization of catalytic particles

Spatial organization of catalytic particles is ubiquitous in biological systems across different length scales, from enzyme complexes to metabolically coupled cells. Despite the different scales, these systems share common features of localized reactions with partially hindered diffusive transport, determined by the collective arrangement of the catalysts. Yet it remains largely unexplored how different arrangements affect the interplay between the reaction and transport dynamics, which ultimately determines the flux through the reaction pathway. Here we show that two fundamental trade-offs arise, the first between efficient inter-catalyst transport and depletion of substrate, and the second between steric confinement of intermediate products and accessibility of catalysts to substrate. We use a model reaction pathway to characterize the general design principles for the arrangement of catalysts that emerge from the interplay of these trade-offs. We find that the question of optimal catalyst arrangements generalizes the famous Thomson problem of electrostatics.

biophysics↗

bioRxiv2019

Biomarker-based outcome prediction in prostate adenocarcinoma depends on the TMPRSS2-ERG status

BackgroundProstate adenocarcinoma (PCa) with/without the TMPRSS2-ERG (T2E)-fusion represent distinct molecular subtypes. ObjectiveTo investigate gene-signatures associated with metastasis in T2E-positive and -negative PCa, and to identify and validate subtype-specific prognostic biomarkers. Design, setting and participantsGene expression and clinicopathological data of two discovery PCa cohorts (total n=783) were separately analyzed regarding the T2E-status. Selected subtype-specific biomarkers were validated in two additional cohorts (total n=405). Outcome measurements and statistical analysisFrom both discovery cohorts, we generated two gene lists ranked by their differential intratumoral expression in patients with/without metastases stratified by T2E-status, which were subjected to gene set enrichment and leading-edge analyses. The resulting top 20 gene-signatures of both gene lists associated with metastasis were analyzed for overlaps between T2E-positive and -negative cases. Genes shared by several functional gene-signatures were tested for their association with event-free survival using the Kaplan-Meier method in a validation cohort. Immunohistochemistry was performed in another validation cohort. Results and limitationsMetastatic T2E-positive and -negative PCa are characterized by different gene-signatures. Five genes (ASPN, BGN, COL1A1, RRM2 and TYMS) were identified whose high expression was significantly associated with worse outcome exclusively in T2E-negative PCa. This was validated in an independent cohort for all genes and additionally for RRM2 by immunohistochemistry in a separate validation cohort. No prognostic biomarkers were identified exclusively for T2E-positive tumors. ConclusionsOur study demonstrates that the prognostic value of biomarkers critically depends on the molecular subtype, i.e. the T2E-status, which should be considered when screening for and applying novel prognostic biomarkers for outcome prediction in PCa. Patient summaryOutcome prediction for PCa is complex. The results of this study highlight that the validity of prognostic biomarkers depends on the molecular subtype, specifically the presence/absence of T2E. The reported new subtype-specific biomarkers exemplify that biomarker-based outcome prediction in PCa should consider the T2E-status.

cancer biology↗