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bioRxiv · 10.64898/2026.10.18.759958

Enabling Spatially Resolved Gene Expression Analysis in a Multilayer Paper-Based In Vitro Tumor Model

Kumar, A.·Toley, B. J.
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Abstract

Spatial heterogeneity is a defining feature of solid tumors, yet molecular analysis of three-dimensional (3D) in vitro tumor models is often performed as a bulk measurement, potentially obscuring position-dependent cellular responses. Here, we establish an analytical workflow for spatially resolved gene-expression analysis in a multilayer paper-based 3D tumor model by addressing the challenge of RNA recovery from cell-laden paper-Matrigel scaffolds. Using MDA-MB-231 breast cancer cells, multiple RNA extraction strategies were systematically evaluated across conventional culture, Matrigel, paper, and composite paper-Matrigel environments. Conventional silica-column extraction yielded only 3.39 {+/-} 0.93 ng/L RNA from the composite scaffold, whereas TRIzol-chloroform extraction increased recovery to 201.13 {+/-} 38.32 ng/L. The optimized workflow subsequently enabled independent RNA recovery from all eight layers of a multi-layer paper-based in vitro tumor, with concentrations ranging from 113.06 {+/-} 5.00 to 245.26 {+/-} 15.76 ng/L and purity suitable for downstream qRT-PCR analysis. Layer-resolved profiling of untreated cultures revealed distinct spatial patterns in HIF1A, HIF2A, VEGFA, and GLUT4 expression across the multilayer construct. To evaluate the workflow under pharmacological perturbation, cultures were exposed to 5 M doxorubicin (DOX) for 48 h. Relative cell viability exhibited a non-monotonic spatial profile, whereas DOX-induced HIF1A and VEGFA expression generally became more pronounced toward the deeper layers when each treated layer was compared with its corresponding untreated control. Collectively, these results establish a workflow for converting individually addressable regions of a multilayer 3D tumor model into spatially resolved transcriptional measurements, enabling analysis of both baseline spatial heterogeneity and position-dependent molecular responses to pharmacological perturbation.

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Kumar, A., Toley, B. J.. 2026-10-20. Enabling Spatially Resolved Gene Expression Analysis in a Multilayer Paper-Based In Vitro Tumor Model. https://doi.org/10.64898/2026.10.18.759958

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