Biology subjects

Hannan, R.

Publications and source records attributed to Hannan, R..

6 recordsLinked to original sources

bioRxiv2026

Integrated analysis of ribosomal DNA copy number and methylation using nanopore long-read sequencing

Ribosomal RNA (rRNA) provides the structural and catalytic core of ribosomes and is encoded by ribosomal RNA genes (rDNA) arranged in tandem repeat arrays. rDNA copy number (CN) is highly dynamic, representing a clinically relevant form of structural variation, but its accurate quantification has been challenging due to its highly repetitive and GC-rich nature. Here, we present RICO (Ribosomal DNA Integrated Copy Number and Methylation Analysis), a novel computational pipeline for integrated estimation of rDNA CN and methylation using nanopore long-read sequencing. RICO leverages long sequencing reads that span entire rDNA repeats, mapped to an rDNA-augmented reference genome, and normalizes coverage using an array of single-copy genes. We show that RICO provides accurate rDNA CN estimates in simulated datasets and reproducible measurements across human samples, with strong agreement to short-read sequencing and PCR-based methods. As biological validation, RICO detects a [~]40% reduction in rDNA CN in Atrx-knockout mouse cells, consistent with established effects of ATRX loss on rDNA CN, and captures detected increased total and active rDNA CN in malignant cells from a MYC-driven B-cell lymphoma mouse model, in line with prior psoralen-based chromatin studies. Applying RICO to independent human cohorts, we uncover that individuals with higher total rDNA CN consistently exhibited higher fractions of high-methylated rDNA copies, suggesting a dosage compensation mechanism that potentially maintains a similar number of active rDNA copies across individuals. Together, RICO enables integrated analysis of rDNA CN and methylation state, providing a scalable framework for investigating rDNA regulation across population and disease studies.

bioinformatics↗

bioRxiv2026

Microporous annealed particle scaffolds avoid foreign body response by down regulating complement-fibroblast-macrophage signaling loop

Biomaterial implantation can trigger a foreign body response (FBR) that impedes tissue-implant integration. To investigate how implant porosity influences this response, we compared the immune response to subcutaneous implants of microporous annealed particle (MAP) scaffolds and nanoporous hydrogels using mass cytometry, single-cell RNA sequencing, and multiplex cytokine assays. MAP scaffolds promoted vascularization and tissue integration, marked by increased endothelial and regulatory T cells, and reduced proinflammatory immune cells and cytokines. In contrast, nanoporous hydrogels demonstrated enrichment of basophils, natural killer cells, and macrophage populations associated with fibrosis. Transcriptomic and proteomic analyses revealed that MAP scaffolds suppressed activation of the complement-fibroblast-macrophage signaling loop, particularly the C5a signaling crosstalk pathway. This was confirmed using C5-deficient mice, where complement-driven cytokine production was significantly reduced only in nanoporous implants. These findings demonstrate that scaffold porosity modulates immune and complement responses, identifying a key mechanism by which MAP scaffolds reduce FBR and improve biomaterial integration.

bioengineering↗

bioRxiv2025

Immune stromal components impede biological effectiveness of carbon ion therapy in a preclinical model of pancreatic ductal adenocarcinoma

The tumor landscape of pancreatic ductal adenocarcinoma (PDAC) is refractory to conventional photon radiotherapy (RT) due to a fibrotic tumor microenvironment (TME) that promotes chronic hypoxia and reduced immune surveillance. The radiobiological factors unique to carbon ion radiotherapy (CIRT), such as high linear energy transfer (LET) and less dependence on oxygen, make it well-suited to overcome the PDAC TME. Here, we utilized clonal syngeneic KPC pancreatic tumor cell lines and tumors to examine this postulate and to identify underlying factors that impact the response of PDAC to CIRT. While KPC cell lines exhibited radiobiologic effectiveness (RBE) greater than 3, subcutaneous tumors in the mouse hind leg showed lower RBEs - 1.3 based on quintupling time - at a LET of 75 keV/m. Four days after CIRT, we observed widespread transcriptomic changes in the tumor immune microenvironment (TME), suggesting increased infiltration of anti-tumor immune cells, elevated expression of anti-tumor T cell cytokines, MHC class I molecules, and co-stimulatory signals. Fewer immunologic changes were observed following photon irradiation. By seven days after CIRT, tumor-supportive transcriptomic programs characterized by pro-tumor cytokines, M2 macrophages, and cancer-associated fibroblasts (CAFs) emerged, promoting resistance and limiting the durability of tumor growth delay. These findings suggest that CIRT may offer a favorable platform compared to conventional photon radiation therapy for combining with immunotherapies. Furthermore, these data highlight the risk of using in vitro survival data alone in treatment planning and indicate that underlying TME factors impact the response of PDAC in vivo.

cancer biology↗

bioRxiv2023

Mapping Cell-to-cell Interactions from Spatially Resolved Transcriptomics Data

Cell-cell communication (CCC) is essential to how life forms and functions. However, accurate, high-throughput mapping of how expression of all genes in one cell affects expression of all genes in another cell is made possible only recently, through the introduction of spatially resolved transcriptomics technologies (SRTs), especially those that achieve single cell resolution. However, significant challenges remain to analyze such highly complex data properly. Here, we introduce a Bayesian multi-instance learning framework, spacia, to detect CCCs from data generated by SRTs, by uniquely exploiting their spatial modality. We highlight spacias power to overcome fundamental limitations of popular analytical tools for inference of CCCs, including losing single-cell resolution, limited to ligand-receptor relationships and prior interaction databases, high false positive rates, and most importantly the lack of consideration of the multiple-sender-to-one-receiver paradigm. We evaluated the fitness of spacia for all three commercialized single cell resolution ST technologies: MERSCOPE/Vizgen, CosMx/Nanostring, and Xenium/10X. Spacia unveiled how endothelial cells, fibroblasts and B cells in the tumor microenvironment contribute to Epithelial-Mesenchymal Transition and lineage plasticity in prostate cancer cells. We deployed spacia in a set of pan-cancer datasets and showed that B cells also participate in PDL1/PD1 signaling in tumors. We demonstrated that a CD8+ T cell/PDL1 effectiveness signature derived from spacia analyses is associated with patient survival and response to immune checkpoint inhibitor treatments in 3,354 patients. We revealed differential spatial interaction patterns between {gamma}{delta} T cells and liver hepatocytes in healthy and cancerous contexts. Overall, spacia represents a notable step in advancing quantitative theories of cellular communications.

bioinformatics↗

bioRxiv2020

Tumor Neoantigenicity Assessment with CSiN Score Incorporates Clonality and Immunogenicity to Predict Immunotherapy Outcomes

Lack of responsiveness to checkpoint inhibitors is a central problem in the modern era of cancer immunotherapy. Tumor neoantigens are critical mediators of host immune response and immunotherapy treatment efficacy. Current studies of neoantigens almost entirely focus on total neoantigen load, which simplistically treats all neoantigens equally. Besides, neoantigen loads have been linked with treatment response and prognosis only in some studies, but not others. We developed a Cauchy-Schwarz index of Neoantigens (CSiN) score to characterize the degree of concentration of immunogenic neoantigens in truncal mutations. Unlike simple neoantigen loads, CSiN incorporates the effect of both clonality and MHC-binding affinity of neoantigens when characterizing patient neoantigen profiles. By exploiting the clinical responses in 501 treated patients (mostly by checkpoint inhibitors) and the overall survival of 1,978 baseline patients, we showed that CSiN scores predict treatment response to checkpoint inhibitors and prognosis in melanoma, lung cancer, and kidney cancer patients. CSiN substantially outperforms prior genetics-based prediction methods of responsiveness. Overall, our work fulfilled an important gap in current research involving neoantigens. One Sentence SummaryThe quality of tumor neoantigens predicts response to immunotherapy

bioinformatics↗

bioRxiv2019

Selective Translation Complex Profiling Reveals Staged Initiation and Co-translational Assembly of Initiation Factor Complexes

Translational control targeting mainly the initiation phase is central to the regulation of gene expression. Understanding all of its aspects requires substantial technological advancements. Here we modified yeast Translational Complex Profile sequencing (TCP-seq), related to ribosome profiling, and adopted it for mammalian cells. Human TCP-seq, capable of capturing footprints of 40S subunits (40Ses) in addition to 80S ribosomes (80Ses), revealed that mammalian and yeast 40Ses distribute similarly across 5UTRs indicating considerable evolutionary conservation. We further developed a variation called Selective TCP-seq (Sel-TCP-seq) enabling selection for 40Ses and 80Ses associated with an immuno-targeted factor in yeast and human. Sel-TCP-seq demonstrated that eIF2 and eIF3 travel along 5UTRs with scanning 40Ses to successively dissociate upon start codon recognition. Manifesting the Sel-TCP-seq versatility for gene expression studies, we also identified four initiating 48S conformational intermediates, provided novel insights into ATF4 and GCN4 mRNA translational control, and demonstrated co-translational assembly of initiation factor complexes.

molecular biology↗