Biology subjects

Conway, K.

Publications and source records attributed to Conway, K..

3 recordsLinked to original sources

bioRxiv2026

Chromatin architecture and physical constriction cooperate in phenotype switching and cancer cell dissemination

Phenotypic plasticity is a prominent cancer feature that contributes to metastatic potential and resistance to therapy across multiple cancer types. Cancer cell state transitions have been attributed to transcriptional programs, such as the AP1/TEAD-regulated gene network driving the mesenchymal-like (MES) phenotype. In addition, during dissemination, tumor cells are subjected to variable loads of physical mechanical pressure and constriction across transited tissue, which are thought to impact nuclear molecular crowding. How the interplay between mechanical pressure, global 3D nuclear architecture and transcriptional programs contributes to MES identity and metastatic adaptation remains unclear. Using cutaneous melanoma as a model for early dissemination, we integrate in vitro and in vivo epigenomic profiling with nanoscale imaging of cell lines and patient samples to investigate chromatin organization features underlying the MES phenotype. We find that in MES cells, CTCF is relocated from domain boundaries to regulatory regions of EMT-like genes, leading to reduced insulation, extended topological associated domains (TADs) and increased inter-domain contacts, and de novo formation of chromatin hubs. This conformational rewiring, along with loss of heterochromatin, supports nuclear deformability during invasion and dissemination. Conversely, physical constriction of melanocytic cells induces MES-like chromatin features--including CTCF repositioning and heterochromatin loss-- and promotes metastasis in vivo. Similarly, pharmacological inhibition of the heterochromatin mark H3K9me3 triggers MES characteristics and increases invasiveness. These results demonstrate that metastatic competency involves both epigenetic and structural nuclear reprogramming, enabling shifts in gene networks and physical adaptability. Our findings reveal mechanistic links between nuclear architecture and aggressive tumor behavior, identifying potential biomarkers and therapeutic targets to intercept metastatic progression.

cancer biology↗

bioRxiv2026

Phylogenomics of Cypriniformes, the most diverse order of freshwater fishes: consensus, challenges and limitations

Cypriniformes, the most species-rich order of freshwater fishes ([~]5,000 species), represents a key lineage for understanding vertebrate diversification in freshwater ecosystems. This clade includes several highly miniaturized and understudied lineages whose phylogenetic placements have long remained contentious. Here, we present the first phylogenomic analysis of Cypriniformes with complete family-level representation and broad genus-level coverage, encompassing 316 species comprising approximately 30% of all described genera. Our dataset integrates 257 newly assembled genomes with publicly available resources and analyzes multiple sets of genome-wide markers using both concatenation-based and coalescent-aware approaches. The general concordance among analytical frameworks indicates that the backbone topology of Cypriniformes is now established, allowing clear identification between well-supported clades and regions of persistent conflict. Our results strengthen the evolutionary relationships of several miniaturized lineages, while identifying recalcitrant relationships shaped by both biological processes and model artefacts that can yield superficially similar patterns of phylogenetic conflict. Our study substantially expands genomic representation and establishes a phylogenomic foundation for future comparative, developmental, and evolutionary research in this freshwater radiation.

evolutionary biology↗

bioRxiv2024

Improving Accuracy of Somatic Mutation Profiling in Large Epidemiologic Studies: Addressing Cases without Matched Normal Samples

Ideally, detection of somatic mutations in a tumor is accomplished using a patient-matched sample of normal cells as the benchmark. In this way somatic mutations can be distinguished from rare germline mutations. In large retrospective studies, archival tissue collection can pose challenges in obtaining samples of normal DNA. In this article we propose a protocol that improves somatic mutation analysis in the absence of a matched normal sample. The method was motivated by the InterMEL study, a large-scale epidemiologic investigation involving multiomic, multi-institutional genomic profiling of 1000 primary melanoma samples. The key insight for accomplishing improved mutation calling is the fact that germline mutations should produce a variant allele frequency (VAF) of around 50%. While a similar VAF of 50% would also be expected for somatic mutations in pure tumor samples, typically the tumor purity is much less than 50%, resulting in a considerably lower VAF. Making use of a technique that can simultaneously estimate both tumor purity and VAF from tumor-only samples we have developed a method for better distinguishing somatic versus germline variants. Based on 137 melanomas from the InterMEL Study with matched normal tissue to provide a gold standard we show that the conventional pipeline using a panel of (unmatched) normal samples has a false positive rate of 15.6% and a false negative rate of 3.5%. Our new technique improves these error rates to 6.4% and 2.1%, respectively.

genomics↗