Biology subjects

Godfrey, B.

Publications and source records attributed to Godfrey, B..

7 recordsLinked to original sources

bioRxiv2026

CSF-Seq enables transcriptome-wide profiling of cerebrospinal fluid and identifies prognostic signature of leptomeningeal disease

Leptomeningeal disease (LMD) is a rapidly fatal complication of systemic cancer for which sensitive diagnostic tools and informative biomarkers remain limited. Here, we introduce CSF-Seq, a method for whole-transcriptome sequencing of cell-free RNA (cfRNA) from human cerebrospinal fluid (CSF), designed to enable molecular profiling of LMD and other central nervous system (CNS) conditions. Using a prospectively collected CSF biobank, we analyzed 125 samples spanning multiple pathologies, including breast and lung LMD, glioblastoma, traumatic brain injury, and non-cancer neurological controls. Through optimized RNA extraction, library preparation, and deep sequencing, CSF-Seq generated robust and reproducible transcriptome-wide profiles despite the low abundance and fragmentation of cfRNA in CSF. CSF transcriptomes exhibited disease-specific expression, separating LMD from non-cancer controls and from non-LMD cancers, independent of CSF collection modality. Tumor-associated epithelial transcripts, including CEACAM6 and MUC1, were consistently enriched in LMD samples, whereas immune and CNS-associated transcripts were broadly detected across disease states, consistent with contributions from both tumor and non-tumor sources. Cross-site processing of matched samples demonstrated high concordance, indicating preservation of sample-specific transcriptional signatures across independent workflows. Importantly, we identified a collection method- independent LMD gene expression signature that was significantly associated with overall survival, supporting its potential prognostic relevance. Together, these findings establish CSF-Seq as a technically robust and clinically informative platform for transcriptomic biomarker discovery in CNS metastatic disease, offering a minimally invasive approach for disease characterization, risk stratification, and longitudinal monitoring in patients with LMD.

cancer biology↗

bioRxiv2026

Dissecting polycomb complexes for enhanced fetal hemoglobin production

Polycomb repressive complexes PRC1 and PRC2 regulate diverse developmental processes, including the fetal-to-adult switch in hemoglobin production, a process whose reversal is a goal for the treatment of sickle cell disease and {beta}-thalassemia. PRC inhibitors show promise for various disorders, but use is limited because of pleiotropic PRC activities. We explored whether fetal hemoglobin (HbF) can be reactivated in adult erythroid cells by selective perturbations of PRC1 or PRC2 components without complete loss of PRC function. A high-density CRISPR-Cas9 mutagenesis screen identified a region in the EZH2 subunit where Cas9 induced exon 14 skipping (EZH2{Delta}14). EZH2{Delta}14, which lacks a portion of the CXC domain, relieves HbF repression while largely maintaining cellular fitness. EZH2{Delta}14 retains H3K27 methylation and repression of a PRC target gene subset. Experiments in cells derived from mice bearing human {beta}-globin genes confirm that pathways mediating EZH2 control of HbF expression can function in a mouse model of HBG switching. These findings demonstrate that partial disruption of PRC can yield selective phenotypes, highlighting the therapeutic potential of targeting non-enzymatic domains within chromatin-modifying complexes. Key PointsO_LICRISPR-Cas9 screen across PRC1 and a saturating mutagenesis screen of PRC2 found the EZH2 CXC domain a desirable target for HbF induction C_LIO_LIthe EZH2-CXC domain leads to exon 14 exclusion, resulting in de-repression of HbF but maintenance of cell fitness. C_LI

molecular biology↗

bioRxiv2025

Dapagliflozin mitigates hypoxia-induced metabolic stress, kidney tubular cell death and fibrosis

Sodium-glucose co-transporter 2 inhibitors (SGLT2-i) slow progression of kidney disease but therapeutic mechanisms remain elusive. Here we report the beneficial effect of dapagliflozin on hypoxia-mediated kidney tubular epithelial cell injury, a contributing factor to kidney disease progression, using a human pluripotent stem cell (hPSC)-derived hypoxic kidney organoid model. Hypoxic organoids showed increased expression of Hypoxia Inducible Factor (HIF)-associated transcriptional targets, decreased tricarboxylic acid (TCA) cycle metabolites and mitochondrial {beta}-oxidation protein expression, and activated unfolded protein response. A transcriptional signature derived from hypoxic organoids 1) identified a subgroup of individuals whose kidney disease subsequently progressed, and 2) correlated with worse tubular injury. Dapagliflozin enhanced mitochondrial stress response resulting in reversed hypoxia-induced tubular epithelial cell apoptosis, reactive oxygen species (ROS) accumulation, and organoid fibrosis. These results indicate that dapagliflozin may contribute to improved kidney disease outcomes by attenuating hypoxia-induced metabolic stress-mediated tubular epithelial cell injury.

cell biology↗

bioRxiv2025

Spatial Profiling Reveals Equivalence-Derived Molecular Signatures of Brain Mimicry and Adaptation in Breast Cancer Brain Metastases

Brain metastases (BrMets), common for advanced-stage breast cancer patients, are associated with poor median survival and accompanied by severe neurologic decline. Halting the progression of breast cancer brain metastases (BCBMs) may require modulation of the tumor microenvironment (TME), yet little is known about the impact of the primary breast TME on brain tropism, or how, once there, metastatic breast cancer cells coexist with brain-resident cells (e.g., neurons and glia). Traditionally, studies in this space have focused on differential expression analysis, overlooking potential insights gained from investigating genes with equivalent expression between groups. This is particularly crucial in distant metastasis, where tumor cells may co-opt the transcriptional programs of the host organ (e.g., brain) to facilitate successful seeding and outgrowth. Prior to our work, no computational framework existed to determine biologically-relevant equivalent gene expression. To resolve molecular mechanisms of BCBM enabled by metastatic cancer cells and/or resident brain cells, we leveraged Nanostring GeoMx to perform spatially-resolved transcriptomic profiling on 235 patient-derived tissue cores from BCBM (including adjacent normal brain), primary invasive breast cancers, and normal (non-cancer) brain; analyzing 18,677 RNAs in 450 areas of interest (AOIs). We introduce the "Equivalent Expression Index" a highly specific and accurate algorithm that identifies statistically significant "Equivalently-Expressed Genes". This method facilitated the identification of molecular remodeling and mimicry genes within tissue-specific TMEs. By integrating differential expression analysis with the Equivalent Expression Index, we discovered multiple novel gene signatures associated with BCBM and primary tumor brain-metastatic potential. We demonstrate that the Equivalent Expression Index is a powerful tool to uncover shared gene expression programs representing the adaptation of metastatic cells and brain-resident cells to the BCBM microenvironment.

cancer biology↗

bioRxiv2021

Micro-dissection and integration of long and short reads to create a robust catalog of kidney compartment-specific isoforms

Studying isoform expression at the microscopic level has always been a challenging task. A classical example is kidney, where glomerular and tubulo-insterstitial compartments carry out drastically different physiological functions and thus presumably their isoform expression also differs. We aim at developing an experimental and computational pipeline for identifying isoforms at microscopic structure-level. We microdissed glomerular and tubulo-interstitial compartments from healthy human kidney tissues from two cohorts. The two compartments were separately sequenced with the PacBio RS II platform. These transcripts were then validated using transcripts of the same samples by the traditional Illumina RNA-Seq protocol, distinct Illumina RNA-Seq short reads from European Renal cDNA Bank (ERCB) samples, and annotated GENCODE transcript list, thus identifying novel transcripts. We identified 14,739 and 14,259 annotated transcripts, and 17,268 and 13,118 potentially novel transcripts in the glomerular and tubulo-interstitial compartments, respectively. Of note, relying solely on either short or long reads would have resulted in many erroneous identifications. We identified distinct pathways involved in glomerular and tubulointerstitial compartments at the isoform level.We demonstrated the possibility of micro-dissecting a tissue, incorporating both long- and short-read sequencing to identify isoforms for each compartment.

bioinformatics↗

bioRxiv2018

Redefining Nephrotic Syndrome in Molecular Terms: Outcome-associated molecular clusters and patient stratification with noninvasive surrogate biomarkers

A tissue transcriptome driven classification of nephrotic syndrome patients identified a high risk group of patients with TNF activation and established a non-invasive marker panel for pathway activity assessment paving the way towards precision medicine trials in NS.\n\nAbstractNephrotic syndrome from primary glomerular diseases can lead to chronic kidney disease (CKD) and/or end-stage renal disease (ESRD). Conventional diagnoses using a combination of clinical presentation and descriptive biopsy information do not accurately predict risk for progression in patients with nephrotic syndrome, which complicates disease management. To address this challenge, a transcriptome-driven approach was used to classify patients with minimal change disease and focal segmental glomerulosclerosis in the Nephrotic Syndrome Study Network (NEPTUNE). Transcriptome-based classification revealed a group of patients at risk for disease progression. High risk patients had a transcriptome profile consistent with TNF activation. Non-invasive urine biomarkers TIMP1 and CCL2 (MCP1), which are causally downstream of TNF, accurately predicted TNF activation in the NEPTUNE cohort setting the stage for patient stratification approaches and precision medicine in kidney disease.

systems biology↗

bioRxiv2018

Inflammatory and JAK-STAT Pathways as Shared Molecular Targets for ANCA-Associated Vasculitis and Nephrotic Syndrome

BackgroundGlomerular diseases of the kidney are presently differentiated, diagnosed and treated according to conventional clinical or structural features. While etiologically diverse, these diseases share common clinical features including but not limited to reduced glomerular filtration rate, increased serum creatinine and proteinuria suggesting shared pathogenic mechanisms across diseases. Renal biopsies from patients with nephrotic syndrome (NS) or ANCA-associated vasculitis (AAV) were evaluated for molecular signals cutting across conventional disease categories as candidates for therapeutic targets.\n\nMethodsRenal biopsies were obtained from patients with NS (minimal change disease, focal segmental glomerulosclerosis, or membranous nephropathy) (n=187) or AAV (granulomatosis with polyangiitis or microscopic polyangiitis) (n=80) from the Nephrotic Syndrome Study Network (NEPTUNE) and the European Renal cDNA Bank. Transcriptional profiles were assessed for shared disease mechanisms.\n\nResultsIn the discovery cohort, 10-25% transcripts were differentially regulated versus healthy controls in both NS and AAV, >500 transcripts were shared across diseases. The majority of shared transcripts (60-77%) were validated in independent samples. Therapeutically targetable networks were identified, including inflammatory JAK-STAT signaling. STAT1 eQTLs were identified and STAT1 expression associated with GFR-based outcome. A transcriptional STAT1 activity score was generated from STAT1-regulated target genes which correlated with CXCL10 (p<0.001), a JAK-STAT biomarker, predictors of CKD progression, interstitial fibrosis (r=0.41, p<0.001), and urinary EGF (r=-0.51, p<0.001).\n\nConclusionAAV and NS caused from histopathologically distinct disease categories share common intra-renal molecular pathways cutting across conventional disease classifications. This approach provides a starting point for de novo drug development, and repurposing efforts in rare kidney diseases.

systems biology↗