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Karthaus, W.

Publications and source records attributed to Karthaus, W..

6 recordsLinked to original sources

Generative modeling reveals the connection between cellular morphology and gene expression

The understanding of how transcriptional programs give rise to cellular morphology, and how morphological features reflect and influence cell identity and function remains limited. This is due in part to the lack of large-scale datasets pairing the two modalities as well as the absence of computational frameworks capable of modeling their cross-modal structure. Here, we introduce COSMIC, a bidirectional generative framework that enables quantitative decomposition of transcriptional variance reflected in morphology and morphological variance explained by gene expression. COSMIC builds on a foundation model trained on over 21 million segmented nuclei and couples it with existing transcriptomic embeddings. To enable cross-modal learning, we leveraged a newly generated multimodal dataset acquired using IRIS, a technology that captures high-resolution images and transcriptomes from the same single cells at scale. COSMIC accurately modeled cell type identity, as well as continuous dynamics such as cell-cycle progression, establishing a quantitative link between morphological phenotypes and underlying gene expression. In prostate cancer cells, COSMIC identified morphological and transcriptomic differences between chemotherapy drug treatment-responsive and -resistant cells, and revealed morphology-associated genes linked to tumor state. Together, these results demonstrate that generative modeling powered by paired single-cell measurements can capture the bidirectional flow of information between cellular form and gene expression, opening new avenues for mechanistic discovery and predictive modeling in both basic and translational cell biology.

bioinformatics↗

Single-cell phenomics through integrated imaging and molecular profiling

Single-cell technologies such as transcriptomics, microscopy, and flow cytometry have revolutionized the study of cellular identity and function. While each of these technologies is powerful on its own, their full potential lies in their integration, enabling multimodal profiling of the same cell and revealing how distinct modalities influence one another. Here, we introduce IRIS (Interconnected Robotic Imaging and Single cell transcriptomics), a deterministic single-cell platform technology that seamlessly couples high-resolution microscopy with droplet-based single-cell RNA sequencing. IRIS enables precise cell positioning, multimode imaging across brightfield and fluorescent channels, and subsequent molecular capture from the same cell, directly linking high-resolution morphological features to matched transcriptomes. We validate IRIS by recovering cell cycle progression states and transcriptional programmes associated with canonical morphologies and demonstrate its discovery power by molecularly resolving two nuclear-ER architectures within naive CD8+ T cells, each defined by distinct gene expression profiles and functional markers. IRIS establishes an integrative single-cell phenomics framework, opening new avenues for dissecting how cellular form relates to molecular state and function.

immunology↗

BRCA2 reversion mutation-independent resistance to PARP inhibition in prostate cancer through loss of function perturbations in the DNA pre-replication complex

Recent approvals of PARP inhibitors (PARPi) for BRCA-mutant metastatic castration resistant prostate cancer (mCRPC) necessitate an understanding of the factors that shape sensitivity and resistance. Reversion mutations that restore homologous recombination (HR) repair are detected in [~]50-80% of BRCA-mutant patients who respond but subsequently relapse, but there is currently little insight into why only [~]50% of BRCA-mutant patients display upfront resistance. To address this question, we performed a genome-wide CRISPR screen to identify genomic determinants of PARPi resistance in murine Brca2{Delta}/{Delta} prostate organoids genetically engineered in a manner that precludes the development of reversion mutations. Remarkably, we recovered multiple independent sgRNAs targeting three different members (Cdt1, Cdc6, Dbf4) of the DNA pre-replication complex (pre-RC), each of which independently conferred resistance to olaparib and the next generation PARP-1 selective inhibitor AZD5305. Moreover, sensitivity to PARP inhibition was restored in Brca2{Delta}/{Delta}, Cdc6-depleted prostate cells by knockdown of geminin, a negative regulator of Cdt1, further implicating the critical role of a functional pre-RC complex in PARPi sensitivity. Furthermore, [~]50% of CRPC tumors have copy number loss of pre-RC complex genes, particularly CDT1. Mechanistically, prostate cells with impaired pre-RC activity displayed rapid resolution of olaparib-induced DNA damage as well as protection from replication fork degradation caused by Brca2 loss, providing insight into how Brca2-mutant cancer cells can escape cell death from replication stress induced by PARP inhibition in the absence of HR repair. Of note, a pharmacologic inhibitor that targets the CDT1/geminin complex (AF615) restored sensitivity to AZD5305, providing a potential translational avenue to enhance sensitivity to PARP inhibition in BRCA-mutant cancers. SignificanceHere, we address a major limitation in the effectiveness of PARP inhibitors in BRCA-mutant prostate cancer treatment: only [~]50% of patients respond despite clear genomic evidence of defective homologous recombination. Prior efforts to study PARP inhibitor resistance in prostate cancer have been plagued by the lack of suitable cell lines. We overcame this challenge using primary prostate organoids coupled with genome-wide CRISPR screening. The key finding is that loss of function mutations in the DNA pre-replication complex confer PARP inhibitor resistance. These genes map to chromosomal regions frequently lost in prostate cancer and could therefore serve as potential biomarkers of treatment response. Pharmacologic inhibition of geminin, a negative regulator of the pre-replication complex, can restore PARP inhibitor sensitivity.

cancer biology↗

CocycleHunter: cohomology-based circular gene setenrichment and genetic phase estimation in single-cell RNA-seq data.

Standard single-cell RNA-seq analysis frameworks aggregate over-lapping biological processes and impose a single parametrization, conflating distinct programs. Here, we introduce a topological framework that detects and disentangles multiple cyclic processes directly from single-cell transcriptomic data. We validate this approach on synthetic datasets and scRNA-seq profiles of human dermal fibroblasts under control conditions and following androgen receptor (AR) silencing, as well as in vivo mouse prostate regeneration under androgen receptor add-back. We show robust cell cycle structure across conditions, identify an unbiased AR-linked stress signature related to the senescence and proliferation across organisms, and uncover cholesterol homeostasis as an AR-linked program in tissue regeneration. This framework enables identification and separation of concurrent cyclic processes from snapshot single-cell data, revealing complex multi-dimensional regulatory dynamics inaccessible to standard clustering analysis.

bioinformatics↗

Allosteric interactions prime androgen receptor dimerization and activation

The androgen receptor (AR) is a steroid receptor and master transcription factor that governs gene expression programs required for luminal development of prostate epithelium, formation of muscle tissue and maintenance of the male phenotype. AR misregulation is a hallmark of multiple malignancies, including prostate cancer, where AR hyperactivation and expansion of its transcriptome occur in part through AR gene amplification and interaction with oncoprotein cofactors. Despite its biological importance, how ARs individual domains and its protein cofactors cooperate to bind DNA have remained elusive. Using a combination of reconstitution biochemistry and single particle cryo-electron microscopy (EM), we have isolated three conformational states of AR bound to DNA. We observe that AR forms a non-obligate dimer, with the buried dimer interface utilized by related ancestral nuclear receptors repurposed to facilitate cooperative DNA binding. We identify surfaces bridging ARs domains responsible for allosteric communication, that are compromised in partial androgen insensitivity syndrome (PAIS), and are reinforced by ARs oncoprotein cofactor, ERG, and DNA binding site motifs. Finally, we present evidence that this plastic dimer interface for transcriptional activation may have been adopted by AR at the expense of DNA binding. Our work highlights how fine-tuning of ARs cooperative interactions translate to consequences in development and disease.

biochemistry↗

Reversal of lineage plasticity in RB1/TP53-deleted prostate cancer through FGFR and Janus kinase inhibition

The inherent plasticity of tumor cells provides a mechanism of resistance to many molecularly targeted therapies, exemplified by adeno-to-neuroendocrine lineage transitions seen in prostate and lung cancer. Here we investigate the root cause of this lineage plasticity in a primary murine prostate organoid model that mirrors the lineage transition seen in patients. These cells lose luminal identity within weeks following deletion of Trp53 and Rb1, ultimately acquiring an Ar-negative, Syp+ phenotype after orthotopic in vivo transplantation. Single-cell transcriptomic analysis revealed progressive mixing of luminal-basal lineage features after tumor suppressor gene deletion, accompanied by activation of Jak/Stat and Fgfr pathway signaling and interferon-a and -g gene expression programs prior to any morphologic changes. Genetic or pharmacologic inhibition of Jak1/2 in combination with FGFR blockade restored luminal differentiation and sensitivity to antiandrogen therapy in models with residual AR expression. Collectively, we show lineage plasticity initiates quickly as a largely cell-autonomous process and, through newly developed computational approaches, identify a pharmacological strategy that restores lineage identity using clinical grade inhibitors.

cancer biology↗