ArticleCell systems2023
Uncovering the spatial landscape of molecular interactions within the tumor microenvironment through latent spaces.
Article in Cell systems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed, 36 citations in OpenAlex.
- Pan-tumor spatial transcriptomics reveals conserved properties of tumor organization.Cell reports. Medicine · 2026Article
- CODAvision: best practices and a user-friendly interface for rapid, customizable segmentation of medical images.Nature protocols · 2026Review
- Quantitative 3D histology reveals localized immune remodeling during early pancreatic cancer progression.Cell press blue · 2026Article
- Computational Modeling of Cellular Influence Delineates Functionally Relevant and Distinct Cellular Neighborhoods in Primary and Metastatic Pancreatic Ductal Adenocarcinoma.Cancer immunology research · 2026Article
- STAPLE: automating spatial transcriptomics analysis and AI interpretation.bioRxiv : the preprint server for biology · 2026Article
- FineST: contrastive learning integrates histology and spatial transcriptomics for nuclei-resolved ligand-receptor analysis.Nature communications · 2026Article
- Deep Learning Enabled 3D Multi-Omic Analysis Reveals Molecular Signatures of Heterogeneous Response to Chemotherapy in Pancreatic Cancer.bioRxiv : the preprint server for biology · 2026Article
- A lipid metabolism-based gene signature defines diagnosis and molecular heterogeneity in diabetic nephropathy.Iranian journal of basic medical sciences · 2026Article
- Addressing the mean-variance relationship in spatially resolved transcriptomics data with spoon.Biostatistics (Oxford, England) · 2025Article
- Whole-heart 3D reconstruction of mouse CVB3 myocarditis reveals spatial and transcriptomic heterogeneity of immune foci.Cardiovascular research · 2025Article
- A novel paradigm for single-cell annotation in stem cell research.Stem cell reports · 2025Review
- Integrative analysis of genomic and transcriptomic data informs precancer progression in the pancreas.bioRxiv : the preprint server for biology · 2025Article
- Neoadjuvant Immunotherapy Promotes the Formation of Mature Tertiary Lymphoid Structures in a Remodeled Pancreatic Tumor Microenvironment.Cancer immunology research · 2025Article
- Multiomic identification of senescent stem cell populations critical for osteoarthritis progression and therapy in subchondral bones.Science advances · 2025Article
- Tumor microenvironment: recent advances in understanding and its role in modulating cancer therapies.Medical oncology (Northwood, London, England) · 2025Review
- STimage-1K4M: A histopathology image-gene expression dataset for spatial transcriptomics.Advances in neural information processing systems · 2024Article
- Addressing the mean-variance relationship in spatially resolved transcriptomics data withbioRxiv : the preprint server for biology · 2024Article
- A phenotypic drug discovery approach by latent interaction in deep learning.Royal Society open science · 2024Article
- The MCIB Model: A Novel Theory for Describing the Spatial Heterogeneity of the Tumor Microenvironment.International journal of molecular sciences · 2024Review
- Image stitching algorithm for super-resolution localization microscopy combined with fluorescence noise prior.Biomedical optics express · 2024Article
Corrections and comments
- Erratum issued
Authors and funding
30 authors at 3 institutions in 1 country.
Funding
Abstract
Recent advances in spatial transcriptomics (STs) enable gene expression measurements from a tissue sample while retaining its spatial context. This technology enables unprecedented in situ resolution of the regulatory pathways that underlie the heterogeneity in the tumor as well as the tumor microenvironment (TME). The direct characterization of cellular co-localization with spatial technologies facilities quantification of the molecular changes resulting from direct cell-cell interaction, as it occurs in tumor-immune interactions. We present SpaceMarkers, a bioinformatics algorithm to infer molecular changes from cell-cell interactions from latent space analysis of ST data. We apply this approach to infer the molecular changes from tumor-immune interactions in Visium spatial transcriptomics data of metastasis, invasive and precursor lesions, and immunotherapy treatment. Further transfer learning in matched scRNA-seq data enabled further quantification of the specific cell types in which SpaceMarkers are enriched. Altogether, SpaceMarkers can identify the location and context-specific molecular interactions within the TME from ST data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.