ArticleCell reports methods2023
scCURE identifies cell types responding to immunotherapy and enables outcome prediction.
Article in Cell reports methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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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.
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Who cites it
8 citing papers in PubMed, 8 citations in OpenAlex.
- Multi-omics-driven precision medicine.iMeta · 2026Review
- scResponse: A Rank-Based Method for Identifying Cell States That Contribute to Immunotherapy Response by Single-Cell Data.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Understanding the immune microenvironment of ovarian cancer.Frontiers in oncology · 2026Review
- Toward a better pan-tumor predictive signature for unleashing precision immuno-oncology.Journal for immunotherapy of cancer · 2025Review
- Paired-Sample and Pathway-Anchored MLOps Framework for Robust Transcriptomic Machine Learning in Small Cohorts: Model Classification Study.JMIR bioinformatics and biotechnology · 2025Article
- Revolutionizing breast cancer immunotherapy by integrating AI and nanotechnology approaches: review of current applications and future directions.Bioelectronic medicine · 2025Review
- Deep scSTAR: leveraging deep learning for the extraction and enhancement of phenotype-associated features from single-cell RNA sequencing and spatial transcriptomics data.Briefings in bioinformatics · 2025Article
- Protocol for using scCURE to construct an immunotherapy outcome prediction model.STAR protocols · 2024Article
Corrections and comments
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Authors and funding
11 authors at 6 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A deep understanding of immunotherapy response/resistance mechanisms and a highly reliable therapy response prediction are vital for cancer treatment. Here, we developed scCURE (single-cell RNA sequencing [scRNA-seq] data-based Changed and Unchanged cell Recognition during immunotherapy). Based on Gaussian mixture modeling, Kullback-Leibler (KL) divergence, and mutual nearest-neighbors criteria, scCURE can faithfully discriminate between cells affected or unaffected by immunotherapy intervention. By conducting scCURE analyses in melanoma and breast cancer immunotherapy scRNA-seq data, we found that the baseline profiles of specific CD8
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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.