Biology subjects

Gutschner, T.

Publications and source records attributed to Gutschner, T..

6 recordsLinked to original sources

bioRxiv2026

Multi-level Analysis of Codon Usage Patterns Reveals Systematic Optimization of Oncogenic Gene Expression in Pancreatic Cancer

BackgroundCodon usage bias, the non-random usage of synonymous codons in coding sequences, represents a fundamental feature of genomic organization that has been largely understudied in cancer biology. Pancreatic ductal adenocarcinoma (PDAC), the predominant subtype of pancreatic cancer, is characterized by aggressive disease progression and limited therapeutic options, necessitating novel approaches to understand its molecular pathogenesis. Leveraging publicly available single-cell RNA sequencing data, we performed comprehensive codon usage analyses across different cellular populations in PDAC. ResultsEmploying a variety of computational codon usage indices uncovered the connections between cancer-specific cellular state features and codon usage signatures. Our findings reveal that malignant pancreatic cells express genes with significantly higher GC content, demonstrate preferential usage of optimal codons through increased frequency of preferred synonymous codons, and exhibit a marked preference for more cost-effective amino acids. Analysis of transcript-level bulk RNA-seq data from PDAC tumors revealed that these codon optimization patterns extend to alternative isoform usage, with highly expressed isoforms displaying increased codon optimality and enhanced mRNA stability. ConclusionThese codon usage-dependent adaptations operating at both gene expression and transcript isoform levels may enable malignant cells to enhance gene expression rates, potentially leading to increased translational efficiency and protein production. These insights into the codon usage landscape of PDAC may provide potential biomarkers for disease monitoring and treatment response prediction.

cancer biology↗

bioRxiv2025

RNA-seq derived sequence variations are excellent features for cell line identification

1Cell lines are indispensable models for analyzing molecular mechanisms underlying human diseases. However, incorrect annotation and cross-contamination can introduce severe bias in respective studies. Accordingly, various publishers request authentication of cell lines before publication. Short tandem repeat profiling is commonly used to verify cell line identity and purity but does not guarantee that published results are based on the samples tested by this method. In this study, we demonstrate that RNA-seq-derived sequence variation information is eligible for unambiguous cell line-specific clustering. Based on this finding, we propose methods for reliable cell line identification from RNA-seq data using supervised machine learning methods. In addition, we demonstrate the ability to detect cross-contamination of human cell lines. The presented methods are insensitive to different data pre-processing steps and quality measures. The proposed TopFracCCLE algorithm for cell line identification and detection of cross-contamination is available as R-script at https://github.com/HuettelmaierLab/topFracCCLE.

genomics↗

bioRxiv2024

FOXM1 regulates platelet-induced anoikis resistance in pancreatic cancer cells

Anoikis resistance is a prerequisite for circulating tumor cells (CTC) to survive in the blood stream. Platelets can interact with these CTCs and protect them from cytokine and immune cell-mediated cell death. Whether platelets can regulate anoikis resistance by controlling tumor cell intrinsic gene expression changes has not been studied in pancreatic cancer cells in detail before. Here, we identified FOXM1 as a differentially regulated gene between attached and detached cells whose expression was controlled by platelets. Manipulating FOXM1 expression using FOXM1 knockdown and overexpression or by inhibiting its function using a small molecular inhibitor highlighted the role of FOXM1 in controlling platelet-mediated anoikis resistance in pancreatic cancer cells. Hence, targeting FOXM1 might be a novel therapeutic strategy in pancreatic cancer patients, especially in those with thrombocytosis.

cancer biology↗

bioRxiv2024

NEAT1 promotes genome stability via m6A methylation-dependent regulation of CHD4

Long non-coding (lnc)RNA emerge as regulators of genome stability. The nuclear enriched abundant transcript 1 (NEAT1) locus encodes two lncRNA isoforms that modulate gene expression, growth and proliferation in mammals. Interestingly, NEAT1 transcripts are overexpressed in many tumours and induced by DNA damage, suggesting a genome-protective function. However, the precise role of NEAT1 in the DNA damage response (DDR) is unclear. Here, we investigate the expression, modification levels, localization and structure of NEAT1 in response to DNA double-strand breaks (DSBs) induced by the topoisomerase-II inhibitor etoposide or the locus-specific endonuclease AsiSI. We find that induction of DSBs increases both the levels and N6-methyladenosine (m6A) marks on NEAT1, which promotes alterations in NEAT1 secondary structure and accumulation of hyper-methylated NEAT1 at a subset of promoter-associated DSBs to facilitate efficient DSB signalling. The depletion of NEAT1, in turn, delays the response to DSBs and triggers elevated DNA damage. The genome-protective role of NEAT1 is mediated by the RNA methyltransferase 3 (METTL3) and involves spreading of the chromodomain helicase DNA binding protein 4 (CHD4) upon release from NEAT1. Together, we describe a novel RNA-dependent DDR pathway that couples NEAT1 to the recognition and repair of DSBs.

molecular biology↗

bioRxiv2023

RAVER1 interconnects lethal EMT and miR/RISC activity by the control of alternative splicing

The RAVER1 protein was proposed to serve as a co-factor in guiding the PTBP-dependent control of alternative splicing (AS). Whether RAVER1 solely acts in concert with PTBPs and how it affects cancer cell fate remained elusive. Here we provide the first comprehensive investigation of RAVER1-controlled AS in cancer cell models and reveal a pro-oncogenic role of RAVER1 in tumor growth. This unravels that RAVER1 guides AS in synergy with PTBPs but more prominently serves PTBP1-independent roles in splicing. In cancer cells, one major function of RAVER1 is the control of proliferation and apoptosis, which involves the modulation of AS events within the miR/RISC pathway. Associated with this regulatory role, RAVER1 antagonizes lethal, TGFB-driven epithelial-mesenchymal-transition (EMT) by limiting TGFB signaling. RAVER1-modulated splicing events affect the insertion of protein interaction modules in factors guiding miR/RISC-dependent gene silencing. Most prominently, in all three human TNRC6 proteins, RAVER1 controls AS of GW-enriched motifs, which are essential for AGO2-binding. Disturbance of RAVER1-guided AS events in TNRC6 proteins and other facilitators of miR/RISC activity compromise miR/RISC activity which is essential to restrict TGFB signaling and lethal EMT.

molecular biology↗

bioRxiv2020

9p21 Loss Defines the Evolutionary Patterns of Aggressive Renal Cell Carcinomas

Dedifferentiation and acquisition of chromosomal instability in renal cell carcinoma portends dismal prognosis and aggressive clinical behavior. However, the absence of reliable experimental models dramatically impacts the understanding of mechanisms underlying malignant progression. Here we established an in vivo genetic platform to rapidly generate somatic mosaic genetically engineerd immune-competent mouse models of renal tumors, recapitulating the genomic and phenotypic features of these malignancies. Leveraging somatic chromosomal engineering, we demonstrated that ablation of the murine locus syntenic to human 9p21 drives the rapid expansion of aggressive mesenchymal clones with prominent metastatic behavior, characterized by early emergence of chromosomal instability, whole-genome duplication, and conserved patterns of aneuploidy. This model of punctuated equilibrium provides a remarkable example of cross-species convergent evolution. SignificanceTo better understand the role of 9p21 in malignant progression, we generated a somatic mosaic GEMM of renal cancer, capturing the histological, genomic and evolutionary features of human disease. With this technology we demonstrated a critica role of 9p21 loss in metastatic evolution of RCC and provide a unique tool for testing new therapeutic treatments.

cancer biology↗