Biology subjects

Gade, T. P.

Publications and source records attributed to Gade, T. P..

5 recordsLinked to original sources

bioRxiv2026

Enabling subcellular DESI-MSI for broad adoption: Acquisition, analysis, and application

Subcellular mass spectrometry imaging (MSI) has required specialized instrumentation and approaches. Additionally, data analysis has required expensive proprietary software, or code-based open-source tools. These barriers render spatial metabolomics less accessible than peer spatial omics techniques (transcriptomics, proteomics). Here we demonstrate subcellular MSI on standard commercial hardware, analyzed using code-free, open-source software. An inexpensive, fully reversible modification of a stock DESI source takes the platform past its typical 5-10 m pixels to routine 2x2 m pixels, and 1x1 m in proof-of-principle experiments. At a tissue-glass boundary imaged at 2x2 m, tissue-specific ions showed no measurable spillover onto the adjacent glass within the {+/-}4.4 m uncertainty of the edge position. To make these data interpretable, we extend MSI.EAGLE, an open-source, vendor-agnostic application with two new methods: i) Spatial UMAP preserves tissue architecture alongside subcellular detail, where conventional clustering breaks apart at high resolution; ii) Histology Fit performs landmark-free co-registration, and recovers synthetic misalignments of up to 8 m to within one pixel of a reference registration. Together, these enable previously high-burden spatial metabolomics experiments. In mouse brain tissue, we demonstrate genuine subcellular signal by resolving mitochondrial cardiolipin into perinuclear puncta, quantifying cytoplasmic enrichment across 6,073 cells. Cell identities are assigned to MSI pixels using histology-predicted transcriptomics, linking cell provenance to metabolism in 2D space directly. Finally, we recover cell-type-specific metabolomes consistent with the transcriptomic identities. This workflow allows cellular and subcellular spatial metabolomics linked to cell provenance, with only stock MSI hardware, open-source GUI-based software, and common histology techniques, putting it within reach of many researchers and laboratories.

molecular biology↗

bioRxiv2025

Optical genome mapping identifies a novel PSIP1::TBL1X fusion in metastatic pancreatic neuroendocrine tumors

Background and aimsEffective treatment of metastatic neuroendocrine tumors (NETs) is limited by a lack of targeted therapies and clinically useful predictive biomarkers. We applied complementary genomic profiling technologies to identify genomic alterations that could lead to actionable drug targets and biomarkers. MethodsOptical genome mapping (OGM) and whole exome sequencing (WES) were performed on 70 liver metastases of neuroendocrine tumors from multiple anatomical primary sites. PacBio Iso-Seq long read sequencing and western blotting was used to confirm fusion gene expression. Findings were validated by rtPCR and western blotting on a separate cohort of 17 resection specimens from 14 pancreatic NET cases. ResultsSomatic variant calling from OGM data detected recurrent fusions involving TBL1X (PSIP1::TBL1X) and BEND2 (CHD7::BEND2 and NEO1::BEND2) in pancreatic neuroendocrine tumors (pNETs). BEND2 fusions were associated with high grade tumors, as previously described. The novel PSIP1::TBL1X fusion was confirmed to result in fusion transcript expression by both long-read sequencing and nested rtPCR. Presence of the PSIP1::TBL1X fusion transcript was also confirmed in a second cohort of pNET resection specimens and fusion protein expression was established by western blotting. Both TBL1X and BEND2 fusions are mutually exclusive with ATRX/DAXX mutations. ConclusionThis study underscores the importance of structural variants, including fusion genes as both prognostic biomarkers and potential therapeutic targets, especially in ATRX/DAXX negative pNETs. BEND2 fusion positivity may be a clinically useful biomarker for aggressive disease. As all TBL1X fusion isoforms contain the entire TBL1X coding sequence, TBL1X inhibition could be explored as a novel treatment for TBL1X fusion positive pNETs.

cancer biology↗

bioRxiv2025

Drug-Eluting, Radiopaque, Tumor-Casting Hydrogels for Endovascular Locoregional Therapy of Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide. For patients with unresectable disease, locoregional therapies, such as transarterial chemoembolization (TACE), are the standard of care. However, even with this treatment, the average survival rate is only 27% at 5 years. Recent studies have demonstrated the potential of novel approaches to improve responses through more complete embolization and targeting ischemia-induced molecular dependencies. To build on these findings, we developed an injectable chitosan-based hydrogel system (AuNP-Lys05-gel) that we hypothesized might be a more effective embolic material by (i) enabling a more complete filling of tumor feeding blood vessels in a cast-like manner, (ii) encapsulating Lys05, a potent autophagy inhibitor, and (iii) providing X-ray contrast for direct visualization of the embolization. Chitosan hydrogels of varying composition were formed and characterized. We found that Lys05 could be loaded in this type of hydrogel and that it was released gradually over 7 days. We found that AuNP was better retained by the hydrogel than iopamidol, an FDA-approved contrast agent, indicating that AuNP would provide longer-lasting CT monitoring. In a rat model of HCC, AuNP-Lys05-gel reduced tumor growth and resulted in a 67% objective response rate vs 26% for a clinically used particle embolic. Histology indicated effective vascular occlusion by the gel. These findings indicate that AuNP-Lys05-gel merits further investigation as a treatment for HCC.

cancer biology↗

bioRxiv2025

MSI.EAGLE: An Open-Source GUI for Streamlined Mass Spectrometry Imaging Analysis

Mass Spectrometry Imaging (MSI) is an emergent tool for analyzing spatial molecular distributions, yet data complexity often hinders effective analysis. MSI.EAGLE, an open-source R-Shiny application, makes analysis accessible for non-specialists by integrating advanced tools in a user-friendly interface. The workflow leverages tools from the Cardinal MSI package, with enhanced phenotyping, segmentation, statistical analysis and visualization. The application addresses a gap in spatial biology research by empowering a broader scientific community.

pathology↗

bioRxiv2023

GM-CSF and IL-3 expression increases immune engraftment and tumor infiltration in a humanized patient-derived xenograft model of hepatocellular carcinoma

Background & AimsResponses to immunotherapies in hepatocellular carcinoma (HCC) are suboptimal with no biomarkers to guide patient selection. "Humanized" mice represent promising models to address this deficiency but are limited by variable chimerism and underdeveloped myeloid compartments. We hypothesized that expression of human GM-CSF and IL-3 increases tumor immune cell infiltration, especially myeloid-derived cells, in humanized HCC patient-derived xenografts (PDXs). Material and MethodsNOG (NOD/Shi-scid/IL-2R null) and NOG-EXL (huGM-CSF/huIL-3 NOG) mice conditioned with Busulfan underwent i.v. injection of human CD34+ cells. HCC PDX tumors were then implanted subcutaneously (SQ) or orthotopically (OT). Following serial blood sampling, mice were euthanized at defined tumor sizes. Tumor, blood, liver, and spleen were analyzed by flow cytometry and immunohistochemistry. ResultsHumanized NOG-EXL mice demonstrated earlier and increased human chimerism compared to humanized NOG mice (82.1% vs 43.8%, p<0.0001) with increased proportion of human monocytes (3.2% vs 1.1%, p=0.001) and neutrophils (0.8% vs 0.3%, p=0.02) in circulation. HCC tumors in humanized NOG-EXL mice had increased human immune cell infiltration (57.6% vs 30.2%, p=0.04), noting increased regulatory T cells (14.6% vs 6.8%, p=0.04), CD4+ PD-1 expression (84.7% vs 32.0%, p<0.01), macrophages (1.2% vs 0.6%, p=0.02), and neutrophils (0.5% vs 0.1%, p<0.0001). No differences were observed in tumor engraftment or growth latency in SQ tumors, but OT tumors required implantation at two rather than four weeks post-humanization for successful engraftment. Finally, utilizing adult bone marrow instead of fetal livers enabled partial HLA-matching to HCC tumors but required more CD34+ cells. ConclusionsHuman GM-CSF and IL-3 expression in humanized mice resulted in features more closely approximating the immune microenvironment of human disease, providing a promising model for investigating critical questions in immunotherapy for HCC. Impact and ImplicationsThis study introduces a unique mouse model at a critical point in the evolution of treatment paradigms for patients with hepatocellular carcinoma (HCC). Immunotherapies have become first line treatment for advanced HCC; however, response rates remain low with no clear predictors of response to guide patient selection. In this context, animal models that recapitulate human disease are greatly needed. Leveraging xenograft tumors derived from patients with advanced HCCs and a commercially available immunodeficient mouse strain that expresses human GM-CSF and IL-3, we demonstrate a novel but accessible approach for modeling the HCC tumor microenvironment.

cancer biology↗