X-CODE: a dual RNA barcoding system for multi-platform clonal tracking and spatial phenotyping

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Authors: Roberto Rota, Elizabeth Flittner, Matteo Tartagni, Marwane Bourdim, Emma Westlund, James S. McKenzie, Anthony J. Devlin, Archana P. Thankamony, Nicole Pandell, Florian Gabel, Misha Siddiqui, Dalia Rosano
+8 more Alexander Wilkes, Ivan Andrew, Ka Lok Choi, Laurence Gamé, Chiara Gorrini, Luca Magnani, Zoltán Takáts, Marco Bezzi
Cited by: 0
References: 55

Abstract

ABSTRACT Experimental dissection of clonal dynamics in complex tissues requires barcoding systems that are scalable, compatible with different analytical platforms, providing phenotypic and spatial resolution. Here we introduce X-CODE, a dual-expressed RNA barcoding system designed to enable high-complexity clonal tracking across sequencing-based, cytometric, and spatial imaging modalities within a unified experimental framework. X-CODE combines a combinatorial, probe-detectable long RNA barcode with a matched short sequencing barcode, enabling seamless integration of probe-based readouts with sequencing and barcode-guided clonal retrieval. We demonstrate robust X-CODE detection by mass cytometry and imaging-based platforms, including spatial RNA barcode readout using via a repurposed Akoya PhenoCycler-Fusion protocol. In addition, we show compatibility with MALDI mass spectrometry imaging for co-registration of clonal and metabolic information. We further demonstrate the feasibility of X-CODE detection within probe-based spatial transcriptomics using the 10x Genomics Xenium platform. Applied to an in vivo model of androgen deprivation in prostate cancer, X-CODE reveals clonal architecture, selection and clone-specific phenotypic and metabolic plasticity underlying castration resistance. Together, X-CODE provides a flexible and broadly accessible platform for integrated clonal analysis across spatial, phenotypic, and molecular dimensions.

Fields of Study & Subjects

Single-cell and spatial transcriptomics Cancer Genomics and Diagnostics Genomics and Phylogenetic Studies

Publication details

Journal / source
bioRxiv (Cold Spring Harbor Laboratory)
Publication date
11 February 2026
Language
EN
Document type
Preprint