Biology subjects

Gonen, M.

Publications and source records attributed to Gonen, M..

9 recordsLinked to original sources

bioRxiv2026

GLproxScape reconstructs spatial chromatin occupancy landscapes from tiled genomic locus proteomics

Genomic locus proteomics combines proximity labeling with mass spectrometry to identify the proteins associated with user-defined genomic loci. However, per-region enrichment values from tiled guide designs are typically pooled before hit calling, collapsing the latent spatial structure encoded by overlapping measurements. Here, we describe GLproxScape, an R package that treats per-region enrichments as indirect spatial measurements and reconstructs latent chromatin occupancy landscapes through a Gaussian labeling-kernel forward model. Sequence-specific transcription factors are resolved by motif-anchored non-negative least-squares deconvolution against JASPAR or HOCOMOCO position weight matrices, while chromatin regulators which lack defined DNA-binding motifs are inferred as broad occupancy zones, enabling recovery of overlapping members of multi-subunit complexes. Applied to published genomic locus proteomics datasets at the human TERT, MYC, FOXP2, and FOXQ1 loci and the mouse Ripk3 locus, GLproxScape recovered known regulators with predicted positions independently supported by ChIP-Atlas peaks, reconstructed candidate co-binding relationships, and identified chromatin complexes inaccessible to pooled analyses. Systematic sgRNA-ablation experiments further showed that densely tiled designs improve event recovery and positional stability, providing concrete experimental guidance for future genomic locus proteomics studies.

bioinformatics↗

bioRxiv2026

CCDC66 couples actin-microtubule crosslinking to KANK1-associated microtubule targeting and focal adhesion turnover

Cell migration requires actin-based protrusion to be coordinated with microtubule (MT)-dependent focal adhesion (FA) remodeling. Although KANK proteins link talin-containing FAs to cortical MT-capture machinery, how this machinery couples to force-bearing actin networks remains unclear. Here, we identify the ciliopathy-associated protein CCDC66 as an actin-MT crosslinker required for FA turnover and migration. CCDC66 depletion impaired collective, Transwell, and random migration, whereas CCDC66 overexpression enhanced wound closure and Matrigel invasion. Mechanistically, CCDC66 loss reduced MT targeting to peripheral FAs and shifted cells into a ROCK-dependent contractile state marked by impaired lamellipodial protrusion, stress fiber accumulation, enlarged long-lived adhesions, and increased RhoA-ROCK signaling. ROCK or formin inhibition suppressed this state, whereas Rac1 activation failed to restore productive protrusion, indicating that CCDC66 maintains the balance between protrusive and contractile actin organization. In vitro TIRF reconstitution demonstrated that purified CCDC66 directly crosslinks actin filaments and MTs. In cells, CCDC66 associated with KANK1, supported its peri-adhesion organization, and functioned with KANK1 in an overlapping migration pathway. TCGA analyses further revealed that a coordinated CCDC66/KANK/ROCK-associated module, but not CCDC66 expression alone, stratified outcome in chromophobe renal cell carcinoma. These findings reveal a non-ciliary role for CCDC66 in coupling actin-MT integration to FA turnover and contractile-state control, with relevance to developmental disease and cancer-associated motility.

cell biology↗

bioRxiv2025

Transfer learning framework via Bayesian group factor analysis incorporating feature-wise dependencies

Transfer learning considers distinct but related tasks defined over heterogeneous domains and aims to improve generalization and performance through knowledge transfer between tasks. This approach can be especially advantageous in biomedical contexts with insufficient labeled training data, where joint learning across domains can enable inference in otherwise underpowered datasets. High-dimensional biomedical data is characterized with redundancy, rendering non-linear dependencies among features. Existing models often fail to leverage such feature dependencies during inference, limiting their ability to model complex biological systems. We present a Bayesian group factor analysis transfer learning framework that supports multitask, multi-modal learning. Our approach learns a shared latent space within each domain, simultaneously across multiple domains, and uses a feature-wise prior to model complex relationships. We evaluate our framework using controlled synthetic data experiments and four disjoint patient cancer datasets from acute myeloid leukemia and neuroblastoma. We show that our method improves drug response prediction and more readily recapitulates consensus biomarkers of drug response. Similarly, our approach improves tumor purity prediction and identifies a robust gene signature associated with it. Our framework is scalable, interpretable, and adaptable across target phenotypes, offering a robust solution for a wide range of heterogeneous multi-omics problems.

bioinformatics↗

bioRxiv2023

Less is More: Nek2A Unclusters Extra Centrosomes and Induces Cell Death in Cancer Cells via KIF2C Interaction

Unlike normal cells, cancer cells frequently exhibit extra centrosomes, leading to formation of multipolar spindles that can trigger cell death. Nevertheless, they manage to divide successfully and escape the deadly consequences of unequal segregation of genomic material by coalescing their extra centrosomes into two poles. This unique trait of cancer cells presents a promising target for cancer therapy, focusing on selectively attacking cells with supernumerary centrosomes. Nek2A is a kinase involved in mitotic regulation, including the centrosome cycle, where it phosphorylates linker proteins to separate centrosomes. In this study, we investigated if Nek2A also unclusters extra centrosomes, akin to its separation function. Reduction of Nek2A activity, achieved through knockout, silencing, or inhibition, promotes centrosome clustering, whereas its overexpression results in unclustering. Significantly, this unclustering activity induces cell death, but only in cancer cells with extra centrosomes, both in vitro and in vivo. Notably, none of the known centrosomal (e.g., CNAP1, Rootletin, Gas2L1) or non-centrosomal (e.g., TRF1, HEC1) Nek2A targets were implicated in this unclustering activity. Additionally, Nek2A operated via a mechanism distinct from other unclustering factors like HSET and NuMA. Through TurboID proximity labeling analysis, we identified novel proteins associated with the centrosome or microtubules, expanding the known interaction partners of Nek2A. KIF2C, in particular, emerged as a novel interactor, confirmed through coimmunoprecipitation and localization analysis. The silencing of KIF2C diminished the impact of Nek2A on centrosome unclustering and rescued cell viability. Additionally, elevated Nek2A levels were indicative of better patient outcomes, specifically in those predicted to have excess centrosomes. Therefore, while Nek2A is a proposed target, its use must be specifically adapted to the broader cellular context, especially considering centrosome amplification. Discovering partners such as KIF2C offers fresh insights into cancer biology and new possibilities for targeted treatment.

cancer biology↗

bioRxiv2023

Interferon response and epigenetic modulation by SMARCA4 mutations drive ovarian tumor immunogenicity

Cell-intrinsic mechanisms of immunogenicity in ovarian cancer (OC) are not well understood. The presence of damaging mutations in the SWI/SNF chromatin remodeling complex, such as the SMARCA4 (BRG1) catalytic subunit, has been associated with improved response to ICB, however the mechanism by which this occurs is unclear. The aim of this current study was to examine the alterations in tumor cell-intrinsic and extrinsic immune signaling caused by SMARCA4 loss. Using OC models with loss-of-function mutations in SMARCA4, we found that SMARCA4 loss resulted in increased cancer cell-intrinsic immunogenicity, characterized by upregulation of long-terminal RNA repeats such as endogenous retroviruses, increased expression of interferon-stimulated genes, and upregulation of antigen presentation machinery. Notably, this response was dependent on IRF3 signaling, but was independent of the type I interferon receptor. Mice inoculated with cancer cells bearing SMARCA4 loss demonstrated increased activation of cytotoxic T cells and NK cells in the tumor microenvironment as well as increased infiltration with activated dendritic cells. These results were recapitulated when animals bearing SMARCA4-proficient tumors were treated with a BRG1 inhibitor, suggesting that modulation of chromatin remodeling through targeting SMARCA4 may serve as a strategy to reverse immune evasion in OC.

cancer biology↗

bioRxiv2022

Epigenetic-focused CRISPR/Cas9 screen identifies ASH2L as a regulator of glioblastoma cell survival

Glioblastoma is the most common and aggressive primary brain tumor with poor prognosis, highlighting an urgent need for novel treatment strategies. In this study, we investigated epigenetic regulators of glioblastoma cell survival through CRISPR/Cas9 based genetic ablation screens using a customized sgRNA library EpiDoKOL, which targets critical functional domains of chromatin modifiers. Screens conducted in multiple cell lines revealed ASH2L, a histone lysine methyltransferase complex subunit, as a major regulator of glioblastoma cell viability. ASH2L depletion led to cell cycle arrest and apoptosis. RNA sequencing and greenCUT&RUN together identified a set of cell cycle regulatory genes, such as TRA2B, BARD1, KIF20B, ARID4A and SMARCC1 that were downregulated upon ASH2L depletion. Mass spectrometry analysis revealed the interaction partners of ASH2L in glioblastoma cell lines as SET1/MLL family members including SETD1A, SETD1B, MLL1 and MLL2. We further showed that glioblastoma cells had a differential dependency on expression of SET1/MLL family members for survival. The growth of ASH2L-depleted glioblastoma cells was markedly slower than controls in orthotopic in vivo models. TCGA analysis showed high ASH2L expression in glioblastoma compared to low grade gliomas and immunohistochemical analysis revealed significant ASH2L expression in glioblastoma tissues, attesting to its clinical relevance. Therefore, high throughput, robust and affordable screens with focused libraries, such as EpiDoKOL, holds great promise to enable rapid discovery of novel epigenetic regulators of cancer cell survival, such as ASH2L. Together, we suggest that targeting ASH2L could serve as a new therapeutic opportunity for glioblastoma.

cancer biology↗

bioRxiv2019

Spectroscopy and Machine Learning Based Rapid Point-of-Care Assessment of Core Needle Cancer Biopsies

Solid tumor needle biopsies are essential to confirm malignancy and assess for actionable characteristics or genetic alterations to guide treatment selection. Ensuring that sufficient and suitable material is acquired for tumor profiling, while minimizing patient risk, remains a critical unmet need. Here, we evaluated the performance characteristics of transmission optical spectroscopy for rapid identification of malignant tissue in core needle biopsies (CNB). Human kidney biopsy specimens (545 CNB from 102 patients, 5583 spectra for analysis) were analyzed directly on core biopsy needles with a custom-built optical spectroscopy instrument. Machine learning classifiers were trained to differentiate malignant from normal tissue spectra. Classifiers were compared using receiver operating characteristics analysis and sensitivity and specificity were calculated relative to a histopathologic gold standard. The best performing algorithm was the random forest (sensitivity 96% and 93%, specificity 90% and 93% at the level of individual spectra and full CNB, respectively). Ex-vivo spectroscopy paired with machine learning paves the way towards rapid and accurate characterization of CNB at the time of tissue acquisition and improving tumor biopsy quality.

bioinformatics↗

bioRxiv2019

PARP1 as a biomarker for early detection and intraoperative tumor delineation in epithelial cancers - first-in-human results

Major determining factors for survival of patients with oral, oropharyngeal, and esophageal cancer are early detection, the quality of surgical margins, and the contemporaneous detection of residual tumor. Intuitively, the exposed location at the epithelial surface qualifies these tumor types for utilization of visual aids to assist in discriminating tumor from healthy surrounding tissue. Here, we explored the DNA repair enzyme PARP1 as imaging biomarker and conducted optical imaging in animal models, human tissues and as part of a first-in-human clinical trial. Our data suggests that PARP1 is a quantitative biomarker for oral, oropharyngeal, and esophageal cancer and can be visualized with PARPi-FL, a fluorescently labeled small molecule contrast agent for topical or intravenous delivery. We show feasibility of PARPi-FL-assisted tumor detection in esophageal cancer, oropharyngeal and oral cancer. We developed a contemporaneous PARPi-FL topical staining protocol for human biospecimens. Using fresh oral cancer tissues within 25 min of biopsy, tumor and margin samples were correctly identified with >95% sensitivity and specificity without terminal processing. PARPi-FL imaging can be integrated into clinical workflows, potentially providing instantaneous assessment of the presence or absence of microscopic disease at the surgical margin. Additionally, we showed first-in-human PARPi-FL imaging in oral cancer. In aggregate, our preclinical and clinical studies have the unifying goal of verifying the clinical value of PARPi-FL-based optical imaging for early detection and intraoperative margin assignment.

clinical trials↗

bioRxiv2017

Human PGBD5 DNA transposase promotes site-specific oncogenic mutations in rhabdoid tumors

Genomic rearrangements are a hallmark of childhood solid tumors, but their mutational causes remain poorly understood. Here, we identify the piggyBac transposable element derived 5 (PGBD5) gene as an enzymatically active human DNA transposase expressed in the majority of rhabdoid tumors, a lethal childhood cancer. Using assembly-based whole-genome DNA sequencing, we observed previously unknown somatic genomic rearrangements in primary human rhabdoid tumors. These rearrangements were characterized by deletions and inversions involving PGBD5-specific signal (PSS) sequences at their breakpoints, with some recurrently targeting tumor suppressor genes, leading to their inactivation. PGBD5 was found to be physically associated with human genomic PSS sequences that were also sufficient to mediate PGBD5-induced DNA rearrangements in rhabdoid tumor cells. We found that ectopic expression of PGBD5 in primary immortalized human cells was sufficient to promote penetrant cell transformation in vitro and in immunodeficient mice in vivo. This activity required specific catalytic residues in the PGBD5 transposase domain, as well as end-joining DNA repair, and induced distinct structural rearrangements, involving PSS-associated breakpoints, similar to those found in primary human rhabdoid tumors. This defines PGBD5 as an oncogenic mutator and provides a plausible mechanism for site-specific DNA rearrangements in childhood and adult solid tumors.

cancer biology↗