Biology subjects

Perry, K.

Publications and source records attributed to Perry, K..

7 recordsLinked to original sources

bioRxiv2026

Reversibility of Nuclear and 3D Genomic Changes in Non-Cancerous Fibroblasts After Constricted Migration

Metastatic cancer cells and healthy fibroblasts must traverse constrictive spaces to reach secondary sites. After passing through multiple constrictions, cancer cells often experience stable changes to their nucleus morphology, 3D genome structure, and migratory phenotype. Here, we investigate whether fibroblasts (BJ-5ta), which are non-cancerous and have an inherent ability to migrate to fulfill roles in wound repair, likewise experience nuclear and 3D genomic changes with constricted migration. We find that BJ-5ta cells do not get progressively better at migrating with sequential attempts but do experience nuclear deformations and 3D genome alterations at the compartment level after constricted migration. Transient compartment shifts spatially rearranged genes associated with preparation for and response to migration. Unlike the stable changes associated with long term phenotype changes in cancer cells, however, the nucleus deformations recovered back to unmigrated levels following proliferation and cell movement. Some compartment changes persist and might influence responses to future stimuli, but most 3D genome changes revert to the unmigrated state after cell proliferation. Our study shows that non-cancerous migratory cells are not more robust against alterations caused by constricted migration but can recover from the ones that do arise more readily than cancer cells. Significance StatementO_LICancer cells experience stable phenotype shifts and 3D genome changes after constricted migration, but it is unknown whether these changes would occur in innately migratory non-cancerous fibroblasts. C_LIO_LIFibroblasts (BJ-5ta) show reversible nuclear morphology and 3D genome alterations after constricted migration. C_LIO_LIOur results reveal the connection between basic nucleus mechanobiology and genome structure in fibroblasts, showing how these cells adapt and respond to the forces of constriction during processes such as wound healing. C_LI

cell biology↗

bioRxiv2026

dgiLIT: A Method for Prioritization and AI Curation of Drug-Gene Interactions

IMPORTANCEThe Drug-Gene Interaction Database (DGIdb) has a long history of driving hypothesis generation for biomedical research through the careful curation of drug-gene interaction data from primary and secondary sources with supporting literature. Recent advances in large-language model (LLM) and artificial intelligence (AI) technologies have enabled new paradigms for knowledge extraction and biocuration. The accelerating growth of biomedical literature presents a significant challenge for maintaining up-to-date interaction data. With more than 38 million citations indexed in PubMed alone, new strategies must evolve to identify and incorporate new interaction data into DGIdb. OBJECTIVEIdentify new cost-effective AI curation strategies for incorporating new drug-gene interactions into DGIdb. METHODSWe present a methodology that leverages deterministic natural language processing techniques, existing harmonization frameworks, and AI-assisted curation to systematically narrow the literature space and identify new drug-gene interactions from published studies for inclusion in DGIdb. RESULTSWe demonstrate the use of lemmatization to prioritize a set of 100 abstracts containing high amounts of interaction words for downstream AI curation. From our set of abstracts, we were then able to identify 137 drug-gene interactions via an AI curation task, with 121 (88.3%) of these interactions being completely novel to DGIdb. A human expert evaluator reviewed this interaction set and was able to validate 134 of 137 (97.8%) interactions as being valid based on the text provided. CONCLUSIONTaken together, our results highlight a promising, cost-effective method of ingesting new interactions into DGIdb.

bioinformatics↗

bioRxiv2024

Cell and Transcriptomic Diversity of Infrapatellar Fat Pad during Knee Osteoarthritis

ObjectivesIn this study, we employ a multi-omic approach to identify major cell types and subsets, and their transcriptomic profiles within the infrapatellar fat pad (IFP), and to determine differences in the IFP based on knee osteoarthritis (KOA), sex, and obesity status. MethodsSingle-nucleus RNA sequencing of 82,924 nuclei from 21 IFPs (n=6 healthy control and n=15 KOA donors), spatial transcriptomics and bioinformatic analysis were used to identify contributions of the IFP to KOA. We mapped cell subclusters from other white adipose tissues using publicly available literature. The diversity of fibroblasts within the IFP was investigated by bioinformatic analyses, comparing by KOA, sex, and obesity status. Metabolomics was used to further explore differences in fibroblasts by obesity status. ResultsWe identified multiple subclusters of fibroblasts, macrophages, adipocytes, and endothelial cells with unique transcriptomic profiles. Using spatial transcriptomics, we resolved distributions of cell types and their transcriptomic profiles, and computationally identified putative cell-cell communication networks. Furthermore, we identified transcriptomic differences in fibroblasts from KOA versus healthy control donor IFPs, female versus male KOA-IFPs, and obese versus normal body mass index (BMI) KOA-IFPs. Finally, using metabolomics, we defined differences in metabolite levels in supernatants of naive, profibrotic- and proinflammatory stimuli-treated fibroblasts from obese compared to normal BMI KOA-IFP. ConclusionsOverall, by employing a multi-omic approach, this study provides the first comprehensive map of cellular and transcriptomic diversity of human IFP and identifies IFP fibroblasts as a key cell type contributing to transcriptomic and metabolic differences related to KOA disease, sex, or obesity.

cell biology↗

bioRxiv2023

Reinstatement of CDX2 as a differentiation therapy for colorectal cancers

Despite advances in artificial intelligence (AI) within cancer research, its application toward realizing differentiation therapy in solid tumors remains limited. Using colorectal cancer (CRC) as a model, we developed a machine learning (ML) framework, CANDiT (Cancer Associated Nodes for Differentiation Targeting), to selectively induce differentiation and death of cancer stem cells (CSCs)--a key obstacle to durable response. Centering on one node, CDX2, a master differentiation factor lost in high-risk, poorly differentiated CRCs, we built a transcriptomic network to identify therapeutic strategies for CDX2 restoration. Network-based prioritization identified PRKAB1, a stress polarity sensor, as a top target. A clinical-grade PRKAB1 agonist reprogrammed transcriptional networks, induced crypt differentiation, and selectively eliminated CDX2-low CSCs in CRC cell lines, xenografts and patient-derived organoids (PDOs). Multivariate analyses in PDOs revealed a strong therapeutic index, linking efficacy (IC) to the biomarker-defined CDX2-low state. A 50-gene response signature--derived from an integrated analyses of all three models and trained across multiple datasets--revealed that CDX2 restoration therapy may translate into a [~]50% reduction in recurrence and mortality risk. Mechanistically, treatment activated a differentiation-associated stress polarity signaling axis while dismantling Wnt and YAP-driven stemness programs essential to CSC survival. Thus, CANDiT offers a scalable path to CSC-directed therapy in solid tumors by translating transcriptomic vulnerabilities into precision treatments. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=174 SRC="FIGDIR/small/557628v4_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@16eeb1eorg.highwire.dtl.DTLVardef@10e308borg.highwire.dtl.DTLVardef@9512f0org.highwire.dtl.DTLVardef@10e74eb_HPS_FORMAT_FIGEXP M_FIG C_FIG One sentence summaryIn this work, Sinha et al. introduce a machine learning-guided framework to identify and target transcriptomic vulnerabilities in colorectal cancer, demonstrating that differentiation therapy selectively eliminates cancer stem cells and reduces recurrence risk. HighlightsO_LIAn ML framework (CANDiT) identifies target for differentiation therapy for CRCs C_LIO_LITherapy induces crypt differentiation and CSC-specific cytotoxicity C_LIO_LICDX2-low state predicts therapeutic response; restoration improves prognosis C_LIO_LITherapy dismantles stemness via reactivation of stress polarity signaling C_LI

cancer biology↗

bioRxiv2023

A Living Organoid Biobank of Crohn's Disease Patients Reveals Molecular Subtypes for Personalized Therapeutics

ABSTRACT (Structured)Crohns disease (CD) is a complex, clinically heterogeneous disease of multifactorial origin; there is no perfect pre-clinical model, little insight into the basis for such heterogeneity, and still no cure. To address these unmet needs, we sought to explore the translational potential of adult stem cell-derived organoids that not only retain their tissue identity, but also their genetic and epigenetic disease-driving traits. We prospectively created a biobank of CD patient-derived organoid cultures (PDOs) using biopsied tissues from colons of 34 consecutive subjects representing all clinical subtypes (Montreal Classification B1-B3 and perianal disease). PDOs were generated also from healthy subjects. Comparative gene expression analyses enabled benchmarking of PDOs as tools for modeling the colonic epithelium in active disease and revealed that despite the clinical heterogeneity there are two major molecular subtypes: immune-deficient infectious-CD [IDICD] and stress and senescence-induced fibrostenotic-CD [S2FCD]. The transcriptome, genome and phenome show a surprising degree of internal consistency within each molecular subtype. The spectrum of morphometric, phenotypic, and functional changes within the "living biobank" reveals distinct differences between the molecular subtypes. These insights enabled drug screens that reversed subtype-specific phenotypes, e.g., impaired microbial clearance in IDICD was reversed using agonists for nuclear receptors, and senescence in S2FCD was rectified using senotherapeutics, but not vice versa. Phenotyped-genotyped CD-PDOs may fill the gap between basic biology and patient trials by enabling pre-clinical Phase 0 human trials for personalized therapeutics. GRAPHIC ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/532245v1_ufig1.gif" ALT="Figure 1"> View larger version (58K): org.highwire.dtl.DTLVardef@1edcea0org.highwire.dtl.DTLVardef@198a3c8org.highwire.dtl.DTLVardef@28d394org.highwire.dtl.DTLVardef@5a9dbb_HPS_FORMAT_FIGEXP M_FIG C_FIG In BriefThis work creates a prospectively biobanked phenotyped-genotyped Crohns disease patient-derived organoids (CD-PDOs) as platforms for molecular subtyping of disease and for ushering personalized therapeutics. HIGHLIGHTSO_LIProspectively biobanked CD-organoids recapitulate the disease epithelium in patients C_LIO_LIThe phenome-transcriptome-genome of CD-organoids converge on two molecular subtypes C_LIO_LIOne subtype shows impaired microbial clearance, another increased cellular senescence C_LIO_LIPhenotyped-genotyped PDOs are then used for integrative and personalized therapeutics C_LI

immunology↗

bioRxiv2022

Increased core body temperature exacerbates defective protein prenylation in mouse avatars of mevalonate kinase deficiency

Mevalonate kinase deficiency (MKD) is caused by biallelic loss-of-function mutations in MVK, leading to recurrent fevers and systemic inflammation. We describe new mouse avatars of MKD bearing p.Val377Ile (the commonest variant) or deletions in Mvk. Compound heterozygous mice recapitulated the biochemical phenotype of MKD, with build-up of unprenylated GTPases and increased plasma mevalonic acid. Mice with different deficiencies in mevalonate kinase revealed new insights into the genotype-phenotype relationship and mirrored the variability in the prenylation defect in human MKD, with p.V377I homozygous mice having a milder phenotype than compound heterozygous animals. The inflammatory response to LPS was enhanced in compound heterozygous mice in vivo and elevated serum interleukin-1{beta} was abrogated by NLRP3 inflammasome inhibition. Increased temperature dramatically but reversibly exacerbated the deficit in the mevalonate pathway and defective prenylation in vitro and in vivo, highlighting increased body temperature as a likely trigger of inflammatory flares and an additional potential target for future therapeutic approaches.

physiology↗

bioRxiv2021

ROR and RYK extracellular region structures suggest that receptor tyrosine kinases have distinct WNT-recognition modes

SUMMARYWNTs play key roles in development and disease, by binding both Frizzled (FZD) seven-pass transmembrane receptors and numerous co-receptors that include the ROR and RYK receptor tyrosine kinases (RTKs). We describe crystal structures and WNT-binding characteristics of extracellular regions from the Drosophila ROR and RYK orthologs Nrk (neurospecific receptor tyrosine kinase) and Derailed-2 (Drl-2). RORs bind WNTs though a FZD-related cysteine-rich domain (CRD), and RYKs through a WNT-inhibitory factor (WIF) domain. Our structures suggest that neither the Nrk CRD nor the Drl-2 WIF domain can accommodate the acyl chain typically attached to WNTs. The Nrk CRD contains a deeply buried bound fatty acid, unlikely to be exchangeable with a WNT acyl chain. The Drl-2 WIF domain lacks the lipid-binding site seen in WIF-1. We also show that DWnt-5, which regulates Drosophila ROR and RYK orthologs, lacks an acyl chain. Together with analysis of WNT/receptor interaction sites, these structures provide new insight into how WNTs recruit their RTK co-receptors into signaling complexes.

biochemistry↗