Biology subjects

Craig, D.

Publications and source records attributed to Craig, D..

4 recordsLinked to original sources

bioRxiv2026

Graph-based modeling of multiparametric MRI deciphers molecular states of high-grade glioma invasion with prognostic implications

AbstractThe infiltrative, non-enhancing margin of IDH wildtype high grade glioma (IDHwt HGG) harbors distinct molecular programs that drive invasion and therapeutic resistance, yet remains largely unevaluable by conventional tissue sampling approaches and by conventional imaging. Here we show that this invasive architecture is encoded within multiparametric MRI (mpMRI) feature relationships and can be decoded using a graph-based framework trained on multiregional image-localized biopsies. Across 134 spatially matched biopsy-imaging pairs from 35 patients with primary IDHwt HGG (29 glioblastomas (GBM) and 6 non-glioblastoma HGGs), unsupervised graph community detection identifies two imaging-defined clusters that localize to invasive tumor regions without molecular supervision. Transcriptomic profiling associates these clusters with neuronal (NEU) and glycolytic-plurimetabolic (GPM) molecular programs. Building on this framework, a graph convolutional network (GCN) accurately predicts NEU and GPM transcriptional states in independent training and validation cohorts and significantly outperforms conventional convolutional neural networks. Applied to whole-tumor mpMRI volumes, the trained GCN generates spatially resolved probability maps that quantify the distribution and relative burden of NEU and GPM programs across both MRI contrast-enhancing and non-enhancing invasive regions. These imaging-derived molecular maps stratify patients by overall survival. Increased GPM burden is associated with poorer survival, consistent with the aggressive behavior associated with mesenchymal-like transcriptional programs in IDHwt HGG. In contrast, increased NEU burden is associated with improved survival, identifying a previously unrecognized imaging-derived prognostic biomarker that was not detected by biopsy-based molecular classification alone. Together, these findings establish a graph-based imaging framework for spatially resolved molecular classification of invasive IDHwt HGG and demonstrate that whole-tumor molecular state architecture carries prognostic information beyond conventional tissue sampling.

cancer biology↗

bioRxiv2026

Scalable Production of a De Novo SARS-CoV-2 Antiviral miniprotein in Escherichia coli

The rapid emergence of SARS-CoV-2 variants that evade neutralizing antibodies underscores the need for next-generation antiviral biologics that combine molecular precision with scalable, cost-effective manufacturing. Computationally designed miniproteins targeting the receptor-binding domain (RBD) of the spike protein offer a compelling alternative to monoclonal antibodies due to their small size, high thermal stability, and compatibility with microbial expression systems. Here we report the end-to-end development and cGMP production of IPD-52520, a de novo antiviral miniprotein, using an optimized E. coli platform. Two miniprotein candidates, a homotrimeric construct (Trimer is referred to as IPD-52520, 17 kDa) and a tandem fusion (Daisy is referred to as IPD-52521, 25 kDa), were evaluated in parallel through systematic optimization of strain selection, media composition, fed-batch fermentation, inclusion-body solubilization, refolding, and chromatographic purification. The Trimer was downselected as the lead molecule based on superior preclinical efficacy, favorable pharmacokinetic properties, and higher volumetric manufacturing yields. The optimized process delivers approximately 2 g/L of purified protein at greater than 90% purity. Scale-up from 5 L to 50 L under cGMP conditions demonstrated excellent batch-to-batch reproducibility across six independent batches, supporting nonclinical and Phase 1 clinical supply. Comprehensive biophysical characterization confirmed a well-folded, predominantly alpha-helical trimer (Tm = 73.4 {degrees}C; polydispersity = 1.005) with an intact primary structure and strong target-binding affinity (KD < 1 pM). Real-time stability studies indicate that the drug substance is stable at 2-8 {degrees}C for at least 12 months, with ongoing stability studies. These results demonstrate the feasibility of translating computationally designed antiviral miniproteins into manufacturable biologics and provide a platform applicable to rapid-response therapeutics against current and future pandemic threats.

bioengineering↗

bioRxiv2026

Translating Innovation to Clinic: End-to-End Bioprocess Development and cGMP Manufacturing of N332-GT5 HIV Vaccine Candidate for First-in-Human Trials HVTN144

The successful translation of rationally designed HIV-1 immunogens into effective vaccines requires manufacturing platforms that maintain structural conformity while meeting clinical-grade quality standards. We developed and scaled a robust, cGMP-compliant process for N332-GT5 gp140, a germline-targeting envelope trimer designed to initiate broadly neutralizing antibody responses, which is now undergoing first-in-human evaluation in HVTN144. Starting with a stable CHO cell line developed using Leap-In(R) transposon technology, we established a production clone exhibiting high-titer expression (>200 mg/L) and genetic stability through 60 population doublings. The manufacturing process scaled efficiently from Ambr(R) 250 miniature bioreactors to 200-L single-use systems, delivering consistent product quality across multiple cGMP batches. A streamlined three-step purification strategy--affinity capture, multimodal polishing, and viral clearance- yielded >99% trimeric purity with preserved quaternary structure and native-like antigenicity. Orthogonal LC-MS analyses confirmed site-specific glycan occupancy matching design specifications, while robust viral clearance exceeded 18-log and 11-log reductions for model retroviruses. Clinical material manufactured through this platform has been successfully administered in HVTN144. This work establishes a scalable, reproducible manufacturing paradigm for structurally complex HIV-1 envelope immunogens, advancing the field toward rational vaccine design based on germline-targeting principles.

bioengineering↗

bioRxiv2023

The relationships between genetic ancestry, somatic mutation frequency, and histologic subtypes in high-grade endometrial cancer

High-grade endometrial cancer, like numerous other cancer types, exhibits clear racial disparities in the United States for both the incidence and outcomes of the disease. While institutional factors are likely the primary contributor to these disparities, other underlying causes cannot be ignored (i.e., molecular, genetic, and histopathologic factors). This study seeks to interrogate the role that germline genetic influences, specifically genetic ancestry, may play in contributing to characteristics of high-grade endometrial cancer. This is mainly accomplished by examining the relationship between local ancestry inferences and somatic mutation frequency as well as histologic subtypes. An association between clinical characteristics and patient survival was also interrogated, and while global ancestry was seen to have no significant effect, tumor mutation burden (TMB) did impact patient survival. Here, we identify associations between local ancestry segments on chromosomes 1 and 14 and an increased TMB in self-described (SD) Black patients. We also highlight a complex relationship between heterozygous ancestry combinations within genomic regions (i.e., [European/African] vs. [African/African]) and an increase in local somatic mutation frequency. Furthermore, we explore the relationship between local ancestry and histologic subtype. We identify one region (chr9q32) wherein the African/European local ancestry diplotype was associated with a higher incidence of serous carcinoma. We also underline a difference in somatic mutation frequency between endometrioid and serous carcinoma. While highly exploratory, these findings begin to characterize the complex relationship between genetic ancestry and characteristics of high-grade endometrial cancer, which may impact patient survival.

genomics↗