ArticleBriefings in bioinformatics2023
SpaRx: elucidate single-cell spatial heterogeneity of drug responses for personalized treatment.
Article in Briefings in bioinformatics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.
- Deep learning in single-cell and spatial transcriptomics data analysis: advances and challenges from a data science perspective.Briefings in bioinformatics · 2025Pooled it
- From descriptive to generative: foundation-model approaches for spatial transcriptomics.Briefings in bioinformatics · 2026Review
- Condition-Associated Pattern Extraction and Recovery From Multi-Condition Single-Cell RNA-seq Data With CAPER.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- SP-printer: reconstruction of tumor stage-specific microenvironments via phenotype-integrated spatial transcriptomics.Journal of translational medicine · 2026Article
- GraphTME: graph-based framework for predicting immunotherapy response by interpreting tumour microenvironment interactions using spatial transcriptomics.NPJ systems biology and applications · 2026Article
- DeepSGE: predicting spatial gene expression using residual network with efficient channel attention and dynamic graph attention network.BMC genomics · 2026Article
- Spatial confinement of the AREG-SOX9 signaling circuit: rethinking tumor-stroma interactions in gastric cancer.Annals of medicine and surgery (2012) · 2026Article
- Spatial omics: applications and utility in profiling the tumor microenvironment.Cancer metastasis reviews · 2025Review
- Cracking PRMT5: Mechanistic insights, clinical advances, and AI-driven strategies.Cancer letters · 2025Review
- Integration of eQTL and GEO Datasets to Identify Genes Associated with Breast Ductal Carcinoma In Situ.Current issues in molecular biology · 2025Article
- Mitochondria-related gene-based molecular subtypes of lung adenocarcinoma and their prognostic implications.Scientific reports · 2025Article
- Drug resistance and tumor heterogeneity: cells and ensembles.Biophysical reviews · 2025Review
- Galectin-1 Inhibition as a Strategy for Malignant Peripheral Nerve Sheath Tumor Treatment.Cells · 2025Article
- The Impact of Klotho in Cancer: From Development and Progression to Therapeutic Potential.Genes · 2025Review
- Hepatic Metabolic Signature and Its Association with the Response to Immunotherapy in Hepatocellular Carcinoma.ImmunoTargets and therapy · 2025Article
- Prognostic model construction and immune microenvironment analysis of pyroptosis-related genes in hepatocellular carcinoma based on single-cell RNA sequencing.Frontiers in immunology · 2025Article
- High-throughput gene expression analysis with TempO-LINC sensitively resolves complex brain, lung and kidney heterogeneity at single-cell resolution.Scientific reports · 2024Article
- Single cell spatial profiling of FFPE splenic tissue from a humanized mouse model of HIV infection.Biomarker research · 2024Article
- AntiFormer: graph enhanced large language model for binding affinity prediction.Briefings in bioinformatics · 2024Article
- Advances in spatial transcriptomics and its applications in cancer research.Molecular cancer · 2024Review
Corrections and comments
- Update of
Authors and funding
7 authors at 3 institutions in 1 country.
Funding
Abstract
Spatial cellular authors heterogeneity contributes to differential drug responses in a tumor lesion and potential therapeutic resistance. Recent emerging spatial technologies such as CosMx, MERSCOPE and Xenium delineate the spatial gene expression patterns at the single cell resolution. This provides unprecedented opportunities to identify spatially localized cellular resistance and to optimize the treatment for individual patients. In this work, we present a graph-based domain adaptation model, SpaRx, to reveal the heterogeneity of spatial cellular response to drugs. SpaRx transfers the knowledge from pharmacogenomics profiles to single-cell spatial transcriptomics data, through hybrid learning with dynamic adversarial adaption. Comprehensive benchmarking demonstrates the superior and robust performance of SpaRx at different dropout rates, noise levels and transcriptomics coverage. Further application of SpaRx to the state-of-the-art single-cell spatial transcriptomics data reveals that tumor cells in different locations of a tumor lesion present heterogenous sensitivity or resistance to drugs. Moreover, resistant tumor cells interact with themselves or the surrounding constituents to form an ecosystem for drug resistance. Collectively, SpaRx characterizes the spatial therapeutic variability, unveils the molecular mechanisms underpinning drug resistance and identifies personalized drug targets and effective drug combinations.
Indexed as
Identifiers
What OpenQuestion holds
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.