RNA and protein are not interchangeable in single-cell spatial multi-omics
- 1Josep Carreras Research Institute, Spain; Barcelona Supercomputing Center (BSC), Spain
Abstract
Spatial transcriptomics is increasingly used to infer cellular phenotypes, molecular interactions, and functional tissue organization from RNA, although most of these biological processes are ultimately mediated by proteins. Here, we directly tested the interchangeability of spatial RNA and protein measurements using paired Xenium profiling of 21 matched targets across ~1.8 million cells from primary lung adenocarcinoma and metastatic castration-resistant prostate cancer. After accounting for marker- and dataset-specific protein background, we quantified concordance at multiple levels, including single-cell detection, expression magnitude, cell-type distribution, patient-level abundance, and spatial organization. Agreement at single-cell level was strongly marker-dependent. Canonical lineage markers generally showed concordant RNA and protein patterns, whereas several molecules, including in our study PD-1, PD-L1, and LAG-3, showed little concordance across modalities. Importantly, spatial organization remained substantially more discordant between modalities than overall abundance, indicating that spatial biomarkers are not directly transferable across modalities. Together, our results show that spatial RNA and protein measurements provide largely overlapping information for lineage markers and overall abundance, but can diverse for specific molecules and for higher-order spatial features, where the two layers provide complementary rather than equivalent readouts. These findings provide practical guidance on when spatial transcriptomic readouts can be interpreted as proxies for protein and when orthogonal protein validation is advisable.
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BibTeX
@misc{cervilla2026protein,
title = {{RNA and protein are not interchangeable in single-cell spatial multi-omics}},
author = {S. Cervilla and D. Grases and N. Montesdeoca and A. Font and M. Fernandez-Saorin and O. Etxaniz and J. C. Pardo and M. Ochoa-de-Olza and M. Figols and N. Sala-Gonzalez and C. Fina and M. Rodriguez and J. P. de Torres and M. D. Lozano and L. M. Montuenga and C. de Andrea and R. Pio and V. Ruiz de Porras and E. Porta-Pardo},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.05.756660},
url = {https://www.biorxiv.org/content/10.64898/2026.10.05.756660v1},
note = {CC BY-NC},
}
RIS
TY - UNPB
TI - RNA and protein are not interchangeable in single-cell spatial multi-omics
AU - S. Cervilla
AU - D. Grases
AU - N. Montesdeoca
AU - A. Font
AU - M. Fernandez-Saorin
AU - O. Etxaniz
AU - J. C. Pardo
AU - M. Ochoa-de-Olza
AU - M. Figols
AU - N. Sala-Gonzalez
AU - C. Fina
AU - M. Rodriguez
AU - J. P. de Torres
AU - M. D. Lozano
AU - L. M. Montuenga
AU - C. de Andrea
AU - R. Pio
AU - V. Ruiz de Porras
AU - E. Porta-Pardo
PY - 2026
DA - 2026/10/05
PB - bioRxiv
DO - 10.64898/2026.10.05.756660
UR - https://www.biorxiv.org/content/10.64898/2026.10.05.756660v1
AB - Spatial transcriptomics is increasingly used to infer cellular phenotypes, molecular interactions, and functional tissue organization from RNA, although most of these biological processes are ultimately mediated by proteins. Here, we directly tested the interchangeability of spatial RNA and protein measurements using paired Xenium profiling of 21 matched targets across ~1.8 million cells from primary lung adenocarcinoma and metastatic castration-resistant prostate cancer. After accounting for marker- and dataset-specific protein background, we quantified concordance at multiple levels, including single-cell detection, expression magnitude, cell-type distribution, patient-level abundance, and spatial organization. Agreement at single-cell level was strongly marker-dependent. Canonical lineage markers generally showed concordant RNA and protein patterns, whereas several molecules, including in our study PD-1, PD-L1, and LAG-3, showed little concordance across modalities. Importantly, spatial organization remained substantially more discordant between modalities than overall abundance, indicating that spatial biomarkers are not directly transferable across modalities. Together, our results show that spatial RNA and protein measurements provide largely overlapping information for lineage markers and overall abundance, but can diverse for specific molecules and for higher-order spatial features, where the two layers provide complementary rather than equivalent readouts. These findings provide practical guidance on when spatial transcriptomic readouts can be interpreted as proxies for protein and when orthogonal protein validation is advisable.
ER -