Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.1101/2025.10.23.684213

ROSIE-Enabled Spatial Mapping Reveals Architectural Fragmentation and Immune Reprogramming in Lung Adenocarcinoma Evolution

Huang, B.·Zhu, B.
View original source ↗Export metadata ↓

Abstract

The earliest steps of lung adenocarcinoma (LUAD) evolution remain poorly resolved because existing spatial-omics technologies cannot scale to the large archival cohorts required to capture rare transitional states. Here, we reconstructed a stage-resolved spatial atlas of LUAD progression using ROSIE, a deep-learning framework inferring 50-plex protein expression from routine H&E slides (114 specimens; 3.8 million cells). Using a pathology-defined precursor continuum (Normal[->]AAH[->]AIS[->]MIA[->]IAC) as a pseudotemporal axis, this scalable virtual multiplexing approach reveals a previously unrecognized two-phase immune reprogramming cascade tightly coupled to a measurable structural transition we term architectural fragmentation. During the AAH[->]AIS transition, transient adaptive immune engagement collapses, marked by a 48.4% loss of CD8 + T cells and the emergence of microfragmented epithelial-stromal interfaces. Subsequent AIS[->]MIA[->]IAC transitions are dominated by myeloid-driven immunosuppression, expansion of CD163 + macrophage niches, and the establishment of an immune-excluded architecture. Fragmentation severity in AIS strongly predicts downstream invasive potential, positioning it as an early, quantifiable hallmark of malignant transition. These findings define a mechanistic sequence linking structural disintegration, immune collapse, and invasive outgrowth and demonstrate that H&E-based virtual multiplexing enables cohort-scale dissection of early cancer evolution and identification of actionable windows for immunoprevention. The ROSIE predictions were validated against imaging mass cytometry (IMC) across 25 precursor samples, achieving concordance up to r [≥] 0.90 (93% of marker-cell-type pairs at r [≥] 0.80). A complementary comparison against MIPHEI-ViT, an independent virtual multiplexing framework, corroborated the structural and pan-immune components of this signature across all stages, while highlighting fine-grained immune-lineage resolution as a shared open challenge for H&E-based virtual multiplexing.

Explore related subjects

cancer biologyPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Huang, B., Zhu, B.. 2025-10-27. ROSIE-Enabled Spatial Mapping Reveals Architectural Fragmentation and Immune Reprogramming in Lung Adenocarcinoma Evolution. https://doi.org/10.1101/2025.10.23.684213

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

TROP2 and immune gene expression by African ancestry in triple-negative breast cancer

Purpose: TROP2 is a treatment target in triple-negative breast cancer (TNBC). TACSTD2 encodes TROP2, while PDCD1 encodes the immune protein PD-1. We investigated whether these genes differ by race or African genetic ancestry and whether the reported link between higher TACSTD2 and lower immune-gene expression partly reflects the mixture of cells in tumor samples. Methods: We analyzed TNBC tumors from TCGA (n = 107) and GSE268851 (n = 253; ancestry data for 229), together with spatial, normal-breast, and protein datasets. Regression models adjusted for age, tumor stage, and a score based on epithelial gene expression. We compared TACSTD2 with other epithelial markers using paired bootstrap analysis. Results: TACSTD2 was detected in nearly all tumors, with no significant differences by race or ancestry. Higher African ancestry was linked to higher PDCD1 expression in TCGA (P = 0.00039), but not in GSE268851. In GSE268851, higher TACSTD2 remained associated with lower CD8A, GZMB, and cytotoxic score after epithelial adjustment (all q < 0.003). These associations were stronger than those for EPCAM; the CD8A association was also stronger than that for KRT8. TACSTD2 was 1.55-fold higher in TNBC than in normal breast and correlated with TROP2 protein (Spearman rho = 0.74). Conclusion: TACSTD2 was widely expressed in the TNBC groups studied, while the ancestry-PDCD1 association differed between cohorts. Epithelial gene expression did not fully explain some negative TACSTD2-immune associations, and some were stronger than those for other epithelial markers such as EPCAM.

cancer biology↗
bioRxiv2026

Quantifying subcellular organization from localization to co-occurrence with InSpace

Cell identity and function depend not only on molecular abundance, but also on how molecules are organized within cells. Although spatial transcriptomics now resolves individual RNA molecules within cells, routine computational workflows reduce these measurements to cell-by-gene count matrices, retaining abundance while discarding information about intracellular localization and molecular co-occurrence. This loss of spatial information creates a need for scalable methods that preserve subcellular detail and enable comparisons across diverse cellular morphologies. Therefore, we present InSpace, a scalable framework for quantifying these complementary dimensions of subcellular organization. InSpace-R maps transcripts onto a continuous radial coordinate anchored to nuclear and cell boundaries, while InSpace-C measures distance-dependent co-occurrence or depletion of molecular pairs. Simulations and orthogonal biochemical references support accurate measurements, with scalability demonstrated on datasets containing 275 million transcripts. RNA-RNA and RNA-DNA analyses recover organelle-linked neighbourhoods and associations between nascent transcripts and their genomic origins. Analysis of B and plasma cells across 58 tumour datasets spanning 12 cancer types reveals that reduced MHC-II transcript abundance accompanies more peripheral localization and stronger mutual co-occurrence, separating these transcripts from a program enriched for ER-targeted proteins. InSpace makes intracellular organization accessible alongside abundance, enabling discovery of spatial programs that distinguish cellular states and generate hypotheses about their functional specialization.

cancer biology↗
bioRxiv2026

Age-based shifts in multicellular community organization and abundance in HPV-Negative Head and Neck Cancer

Aging represents a fundamental driver of cancer risk and progression, yet the mechanisms by which aging reshapes the tumor microenvironment remain incompletely understood. To interrogate how aging alters cellular and microenvironmental organization in cancer, we developed an integrated single-cell atlas of HPV-negative head and neck squamous cell carcinoma (HNSCC) encompassing 73 patients aged 18-91 years. Using a multi-layered computational framework combining NMF-based module discovery and partial correlation network analysis, we reveal that age-associated differences in tumor composition are driven primarily by selective shifts in cell type abundance and organization rather than widespread age-dependent transcriptional rewiring. We identify an age-enriched cellular community centered on basal-like squamous epithelial states linked to epithelial-mesenchymal transition, matrix-associated myofibroblast-like CAFs, and FOLR2+ macrophages, which secrete immunosuppressive and ECM-remodeling factors. Cross-dataset in-silico validation via TCGA transcriptomes, spatial transcriptomics, and mouse tumor models confirms the correlation of these cell types across patients, specific ligand-receptor usage, and increased proportions of epithelial and stromal cells in aged mouse models. Among epithelial cell-intrinsic age-associated transcriptional changes, midkine (MDK) emerges as a rare but robust tumor-derived signal linked to stromal remodeling, immunosuppression, and invasive epithelial programs. These findings reveal conserved mechanisms of age-dependent cellular reorganization in the tumor microenvironment and identify MDK and associated stromal-remodeling pathways as potential intervention points for age-stratified cancer therapy.

cancer biology↗