Biology subjects

Huettelmaier, S.

Publications and source records attributed to Huettelmaier, S..

11 recordsLinked to original sources

bioRxiv2026

Local fractal dimension as an indicator of functional reorganization in molecular interaction networks

Changes in protein abundance incompletely describe how molecular perturbations reshape cellular organization. Here we introduce DIFFRACT, a framework that integrates quantitative proteomics with protein-protein interaction networks to identify reorganization through changes in local fractal dimension. Molecular associations define effective distances between connected proteins, allowing the geometry of their surrounding network neighborhoods to be compared across conditions. Analyses across four organisms (E. coli, A. thaliana, C. elegans, and H. sapiens) and three interaction resources (STRING, BioGRID, and IntAct) establish heterogeneous local scaling, while controlled perturbations demonstrate sensitivity to regional changes and invariance to uniform distance rescaling. Applied to RAVER1-deficient A549 cells, DIFFRACT identifies components associated with established RNA-regulatory functions and candidate roles in tRNA biology, mitochondrial organization and ciliogenesis. Selected RNA-regulatory and ciliary themes are not significantly enriched by abundance-ranked gene set analysis, supporting complementary information from network geometry. Selected functional annotations also recur in HEK293T cells. Guided by the ciliary predictions, we show that RAVER1 depletion increases the proportion of ciliated A549 cells 2.57-fold and increases cilium length. DIFFRACT thus connects changes in molecular network geometry to experimentally testable biological responses, extending the interpretation of proteomic perturbations beyond differential abundance.

bioinformatics↗

bioRxiv2026

Targeting IGF2BP1 Creates a Mitotic Vulnerability in Colorectal Carcinoma

Background Mitotic dysregulation is a common feature of colorectal cancer (CRC), yet the contribution of post-transcriptional mechanisms remain incompletely understood. We investigated how the oncofetal RNA-binding protein IGF2BP1 supports mitotic integrity and exposes therapeutic vulnerabilities in CRC. Methods We integrated patient cohort analyses with genetic and pharmacological perturbation of IGF2BP1, transcriptomics, proteomics, RNA-binding assays and functional studies. Xenografts assessed tumor formation, while BTYNB-paclitaxel responses were examined in CRC cell lines and patient-derived organoids. Results IGF2BP1 expression was elevated in CRC, increased with tumor stage, and associated with poor survival and proliferative gene signatures. Genetic depletion or pharmacological inhibition of IGF2BP1 impaired cell viability, induced mitotic abnormalities, and promoted apoptosis, whereas its re-expression enhanced tumor formation in vivo. Integrated molecular analyses identified the chromosomal passenger complex (CPC) as a previously unrecognized downstream target of IGF2BP1. IGF2BP1 bound transcripts encoding CPC components and its depletion consistently reduced their expression across multiple cancer cell models. BTYNB disrupted IGF2BP1 association with INCENP, CDCA8, and BIRC5 transcripts and accelerated INCENP mRNA decay. Functionally, INCENP depletion recapitulated the mitotic defects and impaired viability observed upon IGF2BP1 inhibition. Exploiting this mitotic vulnerability, BTYNB synergized with paclitaxel in CRC cell lines and across four independent IGF2BP1-positive patient-derived organoid models. Conclusions Our findings uncover an IGF2BP1-dependent post-transcriptional regulatory mechanism sustaining CPC expression and mitotic integrity in CRC. Targeting this mechanism exposes a therapeutically exploitable mitotic vulnerability and provides a rationale for combining IGF2BP1 inhibition with microtubule-targeting agents.

cancer biology↗

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↗

bioRxiv2026

Hyperbolic stratification of protein intrinsic disorder and structure-mediated interactions in the human protein interactome

Classical models of protein-protein interactions (PPIs) focus on stable, structure-driven interfaces between folded domains, yet recent work highlights the central role of intrinsic disorder and phase separation in shaping dynamic, multivalent associations. How these interaction modes are reflected in the large-scale organization of PPI networks remains unclear. Here, we map the human interactome onto a hyperbolic representation, integrating sequence- and structure-derived features to test whether network organization reflects distinct molecular interaction strategies. Radial position defines a continuum: central proteins are enriched in folded domains, structural complexity, and post-translational modifications, whereas peripheral proteins show increased intrinsic disorder and liquid-liquid phase separation (LLPS) propensity. Angular organization further reveals communities structured by characteristic domain architectures or disorder-linked motifs. Combined analysis of intrinsic disorder, LLPS propensity, and binding-mode diversity uncovers interaction patterns associated with distinct molecular functions and motif repertoires. Condensate-associated proteins span multiple communities while retaining shared short linear motif signatures. Together, these results show that the hyperbolic map links sequence composition, structural organization, and network topology, providing a framework to interpret protein interaction behavior and to guide functional analysis within the human interactome.

systems biology↗

bioRxiv2026

Lineage-restricted dependency on an oncofetal SNHG29-IGF2BP1 RNA axis in acute megakaryoblastic leukemia

Acute megakaryoblastic leukemia (AMKL) is a rare, aggressive subtype of acute myeloid leukemia with developmental origins in early childhood. To uncover long noncoding RNAs (lncRNAs) sustaining this high-risk malignancy, we conducted CRISPR interference screens targeting lncRNAs overexpressed in primary AMKL samples. This analysis identified SNHG29 as a previously unrecognized lineage-specific dependency, whose silencing profoundly impaired leukemic proliferation and clonogenic growth in vitro and reduced leukemic burden in vivo. RNA pulldown coupled with proteomic analysis revealed that SNHG29 interacts with the oncofetal RNA-binding protein IGF2BP1, which is aberrantly expressed in AMKL. SNHG29 was required to maintain expression of IGF2BP1 target transcripts, including MYC- and E2F-driven proliferative programs, thereby reinforcing fetal transcriptional programs essential for leukemic maintenance. Pharmacologic inhibition of IGF2BP1-RNA interactions with the small-molecule BTYNB induced potent and selective cytotoxicity in patient-derived AMKL models. Together, these findings uncover a developmental co-dependency between SNHG29 and IGF2BP1 that defines a lineage-restricted oncogenic circuit and an actionable therapeutic vulnerability in AMKL.

cancer biology↗

bioRxiv2025

CENTRA: Knowledge-Based Gene Contexuality Graphs Reveal Functional Master Regulators by Centrality and Fractality

Deciphering gene function via context-aware approaches is limited by various means. Especially static gene sets used in enrichment analyses and the lack of single-gene resolution in such analyses restrains the flexible association of genes with specific context. Here, we introduce CENTRA (Centrality-based Exploration of Network Topologies from Regulatory Assemblies), a framework that models gene contextuality through topic-specific gene co-occurrence networks derived from curated gene sets and associated literature. Using Latent Dirichlet Allocation on 12,045 abstracts linked to MSigDB C2 gene sets, we uncovered 27 biological topics and constructed corresponding topic-specific networks that reflect distinct biological states, perturbation conditions, and disease-related regulatory programs. Graph-topological metrics, including centrality, local fractality, and perturbation sensitivity, were computed for each gene to capture structural relevance within these topic-specific contexts. We demonstrate that topological profiles distinguish well-characterized regulators, identify emerging functional candidates, and reveal context-specific roles. Thereby, our framework enables the prioritization of understudied genes by assessing the robustness of their topological signatures across topic-specific networks. To support exploration of these results, we developed a publicly accessible interactive browser application, CENTRA, which enables dynamic navigation of networks and their functional annotations. CENTRA provides an interpretable, scalable framework for investigating context-dependent gene function and hypothesis generation, offering a novel entry point beyond traditional enrichment approaches. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/662180v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@10e4eeorg.highwire.dtl.DTLVardef@125d5b4org.highwire.dtl.DTLVardef@f137aeorg.highwire.dtl.DTLVardef@7ea4e5_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

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↗

bioRxiv2023

IGF2BP1 induces high-risk neuroblastoma and forms a druggable feedforward loop with MYCN promoting 17q oncogene expression

BackgroundNeuroblastoma is the most common solid tumor in infants accounting for approximately 15% of all cancer-related deaths. Over 50% of high-risk neuroblastoma relapse, emphasizing the need of novel drug targets and therapeutic strategies. In neuroblastoma, chromosomal gains at chromosome 17q, including IGF2BP1, and MYCN amplification at chromosome 2p are associated with adverse outcome. Recent, pre-clinical evidence indicates the feasibility of direct and indirect targeting of IGF2BP1 and MYCN in cancer treatment. MethodsCandidate oncogenes on 17q were identified by profiling the transcriptomic/genomic landscape of 100 human neuroblastoma samples and public gene essentiality data. Molecular mechanisms and gene expression profiles underlying the oncogenic and therapeutic target potential of the 17q oncogene IGF2BP1 and its cross-talk with MYCN were characterized and validated in human neuroblastoma cells, xenografts and PDX as well as novel IGF2BP1/MYCN transgene mouse models. ResultsWe reveal a novel, druggable feedforward loop of IGF2BP1 (17q) and MYCN (2p) in high-risk neuroblastoma. This promotes 2p/17q chromosomal gains and unleashes an oncogene storm resulting in fostered expression of 17q oncogenes like BIRC5 (survivin). Conditional, sympatho- adrenal transgene expression of IGF2BP1 induces neuroblastoma at a 100% incidence. IGF2BP1- driven malignancies are reminiscent to human high-risk neuroblastoma, including 2p/17q-syntenic chromosomal gains and upregulation of Mycn, Birc5, as well as key neuroblastoma circuit factors like Phox2b. Co-expression of IGF2BP1/MYCN reduces disease latency and survival probability by fostering oncogene expression. Combined inhibition of IGF2BP1 by BTYNB, MYCN by BRD inhibitors or BIRC5 by YM-155 is beneficial in vitro and, for BTYNB, also in vivo. ConclusionWe reveal a novel, druggable neuroblastoma oncogene circuit settling on strong, transcriptional/post-transcriptional synergy of MYCN and IGF2BP1. MYCN/IGF2BP1 feed-forward regulation promotes an oncogene storm harboring high therapeutic potential for combined, targeted inhibition of IGF2BP1, MYCN expression and MYCN/IGF2BP1-effectors like BIRC5.

cancer biology↗

bioRxiv2020

Deep and accurate detection of m6A RNA modifications using miCLIP2 and m6Aboost machine learning

N6-methyladenosine (m6A) is the most abundant internal RNA modification in eukaryotic mRNAs and influences many aspects of RNA processing. miCLIP (m6A individual-nucleotide resolution UV crosslinking and immunoprecipitation) is an antibody-based approach to map m6A sites with single-nucleotide resolution. However, due to broad antibody reactivity, reliable identification of m6A sites from miCLIP data remains challenging. Here, we present miCLIP2 in combination with machine learning to significantly improve m6A detection. The optimised miCLIP2 results in high-complexity libraries from less input material. Importantly, we established a robust computational pipeline to tackle the inherent issue of false positives in antibody-based m6A detection. The analyses are calibrated with Mettl3 knockout cells to learn the characteristics of m6A deposition, including m6A sites outside of DRACH motifs. To make our results universally applicable, we trained a machine learning model, m6Aboost, based on the experimental and RNA sequence features. Importantly, m6Aboost allows prediction of genuine m6A sites in miCLIP2 data without filtering for DRACH motifs or the need for Mettl3 depletion. Using m6Aboost, we identify thousands of high-confidence m6A sites in different murine and human cell lines, which provide a rich resource for future analysis. Collectively, our combined experimental and computational methodology greatly improves m6A identification. HighlightsO_LImiCLIP2 produces complex libraries to map m6A RNA modifications C_LIO_LIMettl3 KO miCLIP2 allows to identify Mettl3-dependent RNA modification sites C_LIO_LIMachine learning predicts genuine m6A sites from human and mouse miCLIP2 data without Mettl3 KO C_LIO_LIm6A modifications occur outside of DRACH motifs and associate with alternative splicing C_LI

genomics↗

bioRxiv2020

IGF2BP1 is a targetable SRC/MAPK-dependent driver of invasive growth in ovarian cancer

Epithelial-to-mesenchymal transition (EMT) is a hallmark of aggressive, mesenchymal-like high-grade serous ovarian carcinoma (HG-SOC). The SRC kinase is a key driver of cancer-associated EMT promoting adherens junction (AJ) disassembly by phosphorylation-driven internalization and degradation of AJ proteins. Here we show, that the IGF2 mRNA binding protein 1 (IGF2BP1) is up-regulated in mesenchymal-like HG-SOC and promotes SRC activation by a previously unknown protein-ligand-induced, but RNA-independent mechanism. IGF2BP1-driven invasive growth of ovarian cancer cells essentially relies on the SRC-dependent disassembly of AJs. Concomitantly, IGF2BP1 enhances ERK2 expression in a RNA-binding dependent manner. Together this reveals a post-transcriptional mechanism of interconnected stimulation of SRC/ERK signaling in ovarian cancer cells. The IGF2BP1-SRC/ERK2 axis is targetable by the SRC-inhibitor saracatinib and MEK-inhibitor selumetinib. However, due to IGF2BP1-directed stimulation only combinatorial treatment effectively overcomes the IGF2BP1-promoted invasive growth in 3D culture conditions as well as intraperitoneal mouse models. In conclusion, we reveal an unexpected role of IGF2BP1 in enhancing SRC/MAPK-driven invasive growth of ovarian cancer cells. This provides a rational for the therapeutic benefit of combinatorial SRC/MEK inhibition in mesenchymal-like HG-SOC. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

cancer biology↗

bioRxiv2020

Mass Spectrometric Identification of SARS-CoV-2 Proteins from Gargle Solution Samples of COVID-19 Patients

Mass spectrometry (MS) can deliver valuable diagnostic data that complements genomic information and allows us to increase our current knowledge of the COVID-19 disease caused by the SARS-CoV-2 virus. We developed a simple, MS-based method to specifically detect SARS-CoV-2 proteins from gargle solution samples of COVID-19 patients. Our protocol consists of an acetone precipitation and tryptic digestion of proteins contained within the gargle solution, followed by a targeted MS analysis. Our methodology identifies unique peptides originating from SARS-CoV-2 nucleoprotein. Building on these promising initial results, faster MS protocols can now be developed as routine diagnostic tools for COVID-19 patients. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY Image credit (left): Gerd Altmann, Pixabay License, https://pixabay.com/illustrations/corona-coronavirus-virus-covid-19-4959447 C_FIG_DISPLAY

biochemistry↗