Biology subjects

Ranjan, D.

Publications and source records attributed to Ranjan, D..

2 recordsLinked to original sources

bioRxiv2026

Synchrotron diffraction reveals distinct collagen-associated distributions of EGFR-targeted antibody and affibody in pancreatic tumors

Significance: Tumor extracellular matrix may influence the distribution of targeted agents differently across molecular formats. We compared how an antibody and an affibody targeting the same receptor distribute relative to collagen associated tissue structure in pancreatic tumors. Methods: Cetuximab IRDye700DX, an epidermal growth factor receptor (EGFR) targeted fluorescent antibody, and ABY029, an EGFR targeted fluorescent affibody, were coadministered intravenously to 12 athymic nude mice bearing orthotopic pancreatic tumors: eight AsPC1 and four PANC1. Tumors were harvested at 3 or 24 h after injection, with four AsPC1 and two PANC1 mice at each time. Fluorescence images from 21 tissue slices were registered to scanning synchrotron X ray diffraction (XRD) maps to compare the distribution of each agent with local collagen associated diffraction intensity. Results: Cetuximab XRD correlations were negative in all 12 mice at every evaluated binning scale (100 to 400 microns, all adjusted P = 0.0039). Cohort average correlations were more negative for cetuximab than ABY029 at all four scales (paired adjusted P = 0.0137 to 0.0381). Conclusions: Cetuximab exhibited consistent inverse spatial associations with collagen-associated diffraction and stronger cohort-average associations than ABY029. These findings show that agents targeting the same receptor can differ in their relationships with local tissue structure and support spatially resolved assessment of tissue access when selecting molecular formats for imaging and therapy.

bioengineering↗

bioRxiv2025

A complete diploid human genome benchmark for personalized genomics

Human genome resequencing typically involves mapping reads to a reference genome to call variants; however, this approach suffers from both technical and reference biases, leaving many duplicated and structurally polymorphic regions of the genome unmapped. Consequently, existing variant benchmarks, generated by the same methods, fail to assess these complex regions. To address this limitation, we present a telomere-to-telomere genome benchmark that achieves near-perfect accuracy (i.e. no detectable errors) across 99.4% of the complete, diploid HG002 genome. This benchmark adds 701.4 Mb of autosomal sequence and both sex chromosomes (216.8 Mb), totaling 15.3% of the genome that was absent from prior benchmarks. We also provide a diploid annotation of genes, transposable elements, segmental duplications, and satellite repeats, including 39,144 protein-coding genes across both haplotypes. To facilitate application of the benchmark, we developed tools for measuring the accuracy of sequencing reads, phased variant call sets, and genome assemblies against a diploid reference. Genome-wide analyses show that state-of-the-art de novo assembly methods resolve 2-7% more sequence and outperform variant calling accuracy by an order of magnitude, yielding just one error per 100 kb across 99.9% of the benchmark regions. Adoption of genome-based benchmarking is expected to accelerate the development of cost-effective methods for complete genome sequencing, expanding the reach of genomic medicine to the entire genome and enabling a new era of personalized genomics.

genomics↗