ArticleNucleic acids research2024
SORC: an integrated spatial omics resource in cancer.
Article in Nucleic acids research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Deep learning in single-cell and spatial transcriptomics data analysis: advances and challenges from a data science perspective.Briefings in bioinformatics · 2025Pooled it
- Computational analysis in spatial transcriptomics: methods and perspectives.Briefings in bioinformatics · 2026Review
- STGBench: sequencing-level spatial DNA-RNA simulation for multimodal and virtual cell-oriented benchmarking of genomic alterations.Briefings in bioinformatics · 2026Article
- Catalase inhibits tumor growth by alleviating oxidative stress and promoting the polarization of tumor-associated macrophage from M2 to M1 phenotype in non-small cell lung cancer.Biology direct · 2026Article
- So3D: a comprehensive three-dimensional spatial omics resource for decoding tissue architecture in physiology and disease.Nucleic acids research · 2026Article
- DeepSpaceDB: a spatial transcriptomics atlas for interactive in-depth analysis of tissues and tissue microenvironments.Nucleic acids research · 2026Article
- SDMap: a comprehensive database of spatial drug perturbation maps.Nucleic acids research · 2026Article
- Article
- SMTdb: A Comprehensive Spatial Meta-Transcriptome Resource in Cancer.Molecular biology and evolution · 2025Article
- Tumor-intrinsic MHC-II activation in pancreatic ductal adenocarcinoma enhances immune response and treatment efficacy.bioRxiv : the preprint server for biology · 2025Article
- Cell-cell interactions as predictive and prognostic markers for drug responses in cancer.Genome medicine · 2025Review
- PLIN2 promotes colorectal cancer progression through CD36-mediated epithelial-mesenchymal transition.Cell death & disease · 2025Article
- Cancer therapy resistance from a spatial-omics perspective.Clinical and translational medicine · 2025Review
- SOAR elucidates biological insights and empowers drug discovery through spatial transcriptomics.Science advances · 2025Article
- HISSTA: a human in situ single-cell transcriptome atlas.Bioinformatics (Oxford, England) · 2025Article
- Pairpot: a database with real-time lasso-based analysis tailored for paired single-cell and spatial transcriptomics.Nucleic acids research · 2025Article
- Applications and advances of multi-omics technologies in gastrointestinal tumors.Frontiers in medicine · 2025Review
- STimage-1K4M: A histopathology image-gene expression dataset for spatial transcriptomics.Advances in neural information processing systems · 2024Article
- The 2024 Nucleic Acids Research database issue and the online molecular biology database collection.Nucleic acids research · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
The interactions between tumor cells and the microenvironment play pivotal roles in the initiation, progression and metastasis of cancer. The advent of spatial transcriptomics data offers an opportunity to unravel the intricate dynamics of cellular states and cell-cell interactions in cancer. Herein, we have developed an integrated spatial omics resource in cancer (SORC, http://bio-bigdata.hrbmu.edu.cn/SORC), which interactively visualizes and analyzes the spatial transcriptomics data in cancer. We manually curated currently available spatial transcriptomics datasets for 17 types of cancer, comprising 722 899 spots across 269 slices. Furthermore, we matched reference single-cell RNA sequencing data in the majority of spatial transcriptomics datasets, involving 334 379 cells and 46 distinct cell types. SORC offers five major analytical modules that address the primary requirements of spatial transcriptomics analysis, including slice annotation, identification of spatially variable genes, co-occurrence of immune cells and tumor cells, functional analysis and cell-cell communications. All these spatial transcriptomics data and in-depth analyses have been integrated into easy-to-browse and explore pages, visualized through intuitive tables and various image formats. In summary, SORC serves as a valuable resource for providing an unprecedented spatially resolved cellular map of cancer and identifying specific genes and functional pathways to enhance our understanding of the tumor microenvironment.
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.