---
title: "PACE: Hierarchical Framework to Quantify Proximity-Associated Changes in Gene Expression"
id: "biorxiv-17-pace-proximity-associated-changes-in-expression"
canonical_url: "https://medichelpline.com/clinical-feed/biorxiv-17-pace-proximity-associated-changes-in-expression"
content_type: "clinical_feed_article"
specialty: "Oncology"
source_name: "bioRxiv (Biomedical Preprints)"
source_url: "https://www.biorxiv.org/content/10.64898/2026.08.09.743800v1?rss=1"
published_at: "2026-08-14T12:00:00.000Z"
evidence_level: "Verified Feed"
license: "CC-BY-NC-4.0 / Informational Use"
---
# PACE: Hierarchical Framework to Quantify Proximity-Associated Changes in Gene Expression
## Provenance & Clinical Metadata
- **Canonical URL:** https://medichelpline.com/clinical-feed/biorxiv-17-pace-proximity-associated-changes-in-expression
- **Specialty:** [Oncology](https://medichelpline.com/clinical-feed/oncology.md)
- **Primary Source:** bioRxiv (Biomedical Preprints)
- **Source URL:** [Original Journal Publication](https://www.biorxiv.org/content/10.64898/2026.08.09.743800v1?rss=1)
- **Published At:** 2026-08-14T12:00:00.000Z
- **Evidence Rating:** Verified Feed
## Executive GIST (TL;DR)
- The authors introduce **PACE** (Proximity-Associated Changes in Expression), a hierarchical empirical Bayes framework to quantify how cell proximity influences gene expression in spatial transcriptomics data. - PACE addresses technical challenges of cell-resolved spatial assays, including data sparsity and contamination from neighboring cells due to diffusion, imperfect segmentation, and cell overlap. - The method uses **partial pooling** to stabilise inference across genes and cell types, improving robustness compared with gene-by-gene approaches. - PACE explicitly separates contamination artefacts from biologically meaningful spatial associations to avoid confounding technical effects with true proximity-driven expression changes. - The framework identifies coordinated transcriptional programs that underlie each proximity effect rather than treating genes independently. - PACE was applied to Xenium-profiled breast cancer tissue, revealing **tumour-associated reprogramming** of stromal cells and **macrophages** at tumour interfaces. - Applied to CosMx-profiled melanoma, PACE detected **fibroblast** responses to tumour proximity, including **extracellular matrix** programs that differed between tumours from patients with progressive versus stable disease after immunotherapy. - The authors position PACE as a robust and interpretable tool for quantifying how tissue organisation shapes cellular state using spatial molecular data. - Details on implementation, benchmarking, and exact quantitative results were not reported in the source abstract and would require consultation of the full preprint.
## Clinical Analysis & Structured Key Points
PACE, Proximity-Associated Changes in Expression | bioRxiv Skip to main content New Results PACE, Proximity-Associated Changes in Expression View ORCID Profile Elijah S Willie , Shreya Rajesh Rao , View ORCID Profile John Ormerod , View ORCID Profile Ellis Patrick doi: https://doi.org/10.64898/2026.08.09.743800 Elijah S Willie 1 University of Sydney; Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Elijah S Willie Shreya Rajesh Rao 1 University of Sydney; Find this author on Google Scholar Find this author on PubMed Search for this author on this site John Ormerod 2 Sydney University Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for John Ormerod Ellis Patrick 1 University of Sydney; Find this author on Google Scholar Find this author on PubMed Search for this author on this site ORCID record for Ellis Patrick For correspondence: ellis.patrick{at}sydney.edu.au Abstract Info/History Metrics Preview PDF Abstract Cellular transcriptional states are shaped by local tissue context, yet quantifying how cellular gene expression varies with proximity to different cell types remains challenging. Cell-resolved spatial transcriptomics data are typically sparse and susceptible to contamination from neighbouring cells through diffusion, imperfect segmentation and cell overlap, making it difficult to distinguish genuine cell-state changes from technical artefacts. We present PACE (Proximity-Associated Changes in Expression), a hierarchical empirical Bayes framework for quantifying cell-type-resolved proximity effects on gene expression. PACE uses partial pooling to stabilise inference across genes and cell types, separates contamination from biologically meaningful spatial associations, and identifies coordinated transcriptional programs underlying each proximity effect. Applied to Xenium-profiled breast cancer tissue, PACE reveals tumour-associated reprogramming of stromal cells and macrophages at tumour interfaces. In CosMx-profiled melanoma, it identifies fibroblast responses to tumour proximity, including extracellular matrix programs that differ between tumours from patients with progressive and stable disease following immunotherapy. PACE provides a robust and interpretable framework for quantifying how tissue organisation shapes cellular state in spatial molecular data. Competing Interest Statement The authors have declared no competing interest. Copyright The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license . Back to top Previous Posted August 14, 2026. Download PDF Email Thank you for your interest in spreading the word about bioRxiv. NOTE: Your email address is requested solely to identify you as the sender of this article. Your Email * Your Name * Send To * Enter multiple addresses on separate lines or separate them with commas. You are going to email the following PACE, Proximity-Associated Changes in Expression Message Subject (Your Name) has forwarded a page to you from bioRxiv Message Body (Your Name) thought you would like to see this page from the bioRxiv website. Your Personal Message CAPTCHA This question is for testing whether or not you are a human visitor and to prevent automated spam submissions. Share PACE, Proximity-Associated Changes in Expression Elijah S Willie , Shreya Rajesh Rao , John Ormerod , Ellis Patrick bioRxiv 2026.08.09.743800; doi: https://doi.org/10.64898/2026.08.09.743800 Share This Article: Copy Citation Tools PACE, Proximity-Associated Changes in Expression Elijah S Willie , Shreya Rajesh Rao , John Ormerod , Ellis Patrick bioRxiv 2026.08.09.743800; doi: https://doi.org/10.64898/2026.08.09.743800 Citation Manager Formats BibTeX Bookends EasyBib EndNote (tagged) EndNote 8 (xml) Medlars Mendeley Papers RefWorks Tagged Ref Manager RIS Zotero Tweet Widget Facebook Like Google Plus One Subject Areas All Articles Animal Behavior and Cognition (7888) Biochemistry (18459) Bioengineering (14615) Bioinformatics (43657) Biophysics (22221) Cancer Biology (19352) Cell Biology (26484) Clinical Trials (138) Developmental Biology (13784) Ecology (20657) Epidemiology (2067) Evolutionary Biology (25106) Genetics (15990) Genomics (23225) Immunology (18403) Microbiology (41855) Molecular Biology (17770) Neuroscience (91966) Paleontology (688) Pathology (2940) Pharmacology and Toxicology (5015) Physiology (7981) Plant Biology (15717) Scientific Communication and Education (2082) Synthetic Biology (4488) Systems Biology (10105) Zoology (2352)
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