Search bioRxiv⌕ Search

Biology subjects

Eze, A.

Publications and source records attributed to Eze, A..

2 recordsLinked to original sources
bioRxiv2025

Mapping Tumor Microenvironment and Treatment Response of Diffuse Midline Glioma Using Multiplexed Immunofluorescence and AI Models

BackgroundDespite its clinical promise in non-solid tumor, immunotherapy is yet to show significant clinical efficacy for brain tumors including pediatric diffuse midline glioma (DMG). This indicated the need to fully explore DMG immune tumor microenvironment (TME). MethodWhole brains (49 DMGs, 20 non-DMG, 10 non-malignant) from 79 pediatric patients were used to establish a tissue microarray (918 cores) representing primary, metastatic, and adjacent healthy sites. CellDIVE MxIF multiplex assay was used to probe for 33 immune and cell type markers. RNA sequencing (n=62 patients) defined additional immune signatures. Findings were validated using patient plasma and DMG PDX models. Our annotated single-cell atlas was used to train a spatial AI model to predict antigens from H&E staining. FindingsWe found enrichment of M1-activated microglia in primary versus adjacent healthy tissue. PD1 positive cells were significantly (p<0.01) higher in tumor compared to adjacent controls. This was validated by mRNA profiling, further indicating two distinct groups with top 35 significant (p<0.05) genes revealing synaptic signature in the metastatic cohort. We stratified the patient cohort by treatment. Imipridone cohort (n=5) showed decreased progenitor (Nestin+, Vimentin+, and SOX2+) and increased macrophages/microglia infiltration. Increased T and B cells was validated in patient plasma following imipridone therapy. Combination therapy of imipridone and immunotherapy (n=7) resulted in increased myeloid (Iba1, CD68, CD163) and lymphoid (CD3, CD8) cells. Enhanced immune engagement was validated in DMG PDX models. Machine learning resulted in a spatial AI model capable of predicting 22 antigens using H&E slides. InterpretationsDMG tumors maintain a cold immune microenvironment, which is nevertheless dynamic and responsive to therapy, indicating the need to explore combination therapies. AI-assisted antigen detection is suitable for rapid interpretation of clinical biospecimens. FundingThis work was supported by Rising Tide, SNF, LilaBean Foundation, Swifty Foundation, Swiss to Cure DIPG and Yuvaan Tiwari Foundation. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=45 SRC="FIGDIR/small/644698v1_ufig1.gif" ALT="Figure 1"> View larger version (24K): org.highwire.dtl.DTLVardef@198b382org.highwire.dtl.DTLVardef@312e0forg.highwire.dtl.DTLVardef@c71b82org.highwire.dtl.DTLVardef@1df1c35_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO C_FIG

cancer biology↗
bioRxiv2023

Single-molecule systems for detection and monitoring of plasma circulating nucleosomes and oncoproteins in Diffuse Midline Glioma

The analysis of cell-free tumor DNA (ctDNA) and proteins in the blood of cancer patients potentiates a new generation of non-invasive diagnostics and treatment monitoring approaches. However, confident detection of these tumor-originating markers is challenging, especially in the context of brain tumors, in which extremely low amounts of these analytes circulate in the patients plasma. Here, we applied a sensitive single-molecule technology to profile multiple histone modifications on millions of individual nucleosomes from the plasma of Diffuse Midline Glioma (DMG) patients. The system reveals epigenetic patterns that are unique to DMG, significantly differentiating this group of patients from healthy subjects or individuals diagnosed with other cancer types. We further develop a method to directly capture and quantify the tumor-originating oncoproteins, H3-K27M and mutant p53, from the plasma of children diagnosed with DMG. This single-molecule system allows for accurate molecular classification of patients, utilizing less than 1ml of liquid-biopsy material. Furthermore, we show that our simple and rapid detection strategy correlates with MRI measurements and droplet-digital PCR (ddPCR) measurements of ctDNA, highlighting the utility of this approach for non-invasive treatment monitoring of DMG patients. This work underscores the clinical potential of single-molecule-based, multi-parametric assays for DMG diagnosis and treatment monitoring.

cancer biology↗