ArticleJournal of clinical medicine2020
Integrative Analysis and Machine Learning based Characterization of Single Circulating Tumor Cells.
Article in Journal of clinical medicine, 2020. 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 22 papers.
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
22 citing papers in PubMed, 39 citations in OpenAlex.
- Chromatin unwinding state for in situ identification and lineage tracing of circulating tumor cells.iMeta · 2026Article
- Microfluidic approaches for liquid biopsy in glioblastoma: Insights into diagnostic and follow-up strategies.Bioengineering & translational medicine · 2026Review
- Single-cell RNA-sequencing of circulating tumour cells: A practical guide to workflow and translational applications.Cancer metastasis reviews · 2025Review
- Liquid biopsy into the clinics: Current evidence and future perspectives.The journal of liquid biopsy · 2024Review
- Detection of circulating tumor cells by means of machine learning using Smart-Seq2 sequencing.Scientific reports · 2024Article
- A combined experimental-computational approach uncovers a role for the Golgi matrix protein Giantin in breast cancer progression.PLoS computational biology · 2023Article
- Marker-free characterization of full-length transcriptomes of single live circulating tumor cells.Genome research · 2023Article
- Recent advances in microfluidic-based cancer immunotherapy-on-a-chip strategies.Biomicrofluidics · 2023Review
- Accelerating the Development and Validation of Liquid Biopsy for Early Cancer Screening and Treatment Tailoring.Healthcare (Basel, Switzerland) · 2022Article
- Microfluidics applications for high-throughput single cell sequencing.Journal of nanobiotechnology · 2021Review
- Article
- Single-cell RNA sequencing in cancer: Applications, advances, and emerging challenges.Molecular therapy oncolytics · 2021Review
- Circulating Tumor Cells from Enumeration to Analysis: Current Challenges and Future Opportunities.Cancers · 2021Review
- Modeling expression ranks for noise-tolerant differential expression analysis of scRNA-seq data.Genome research · 2021Article
- DIscBIO: A User-Friendly Pipeline for Biomarker Discovery in Single-Cell Transcriptomics.International journal of molecular sciences · 2021Article
- Erratum: Iyer, A., et al. Integrative Analysis and Machine Learning Based Characterization of Single Circulating Tumor Cells.Journal of clinical medicine · 2021Article
- Single-Cell RNA-Seq Analysis Reveals Macrophage Involved in the Progression of Human Intervertebral Disc Degeneration.Frontiers in cell and developmental biology · 2021Article
- Complementary Sequential Circulating Tumor Cell (CTC) and Cell-Free Tumor DNA (ctDNA) Profiling Reveals Metastatic Heterogeneity and Genomic Changes in Lung Cancer and Breast Cancer.Frontiers in oncology · 2021Article
- Hypoxia, partial EMT and collective migration: Emerging culprits in metastasis.Translational oncology · 2020Review
- Scalable Signature-Based Molecular Diagnostics Through On-chip Biomarker Profiling Coupled with Machine Learning.Annals of biomedical engineering · 2020Review
Corrections and comments
- Erratum issued
Authors and funding
16 authors at 9 institutions in 4 countries.
Funding
Abstract
We collated publicly available single-cell expression profiles of circulating tumor cells (CTCs) and showed that CTCs across cancers lie on a near-perfect continuum of epithelial to mesenchymal (EMT) transition. Integrative analysis of CTC transcriptomes also highlighted the inverse gene expression pattern between PD-L1 and MHC, which is implicated in cancer immunotherapy. We used the CTCs expression profiles in tandem with publicly available peripheral blood mononuclear cell (PBMC) transcriptomes to train a classifier that accurately recognizes CTCs of diverse phenotype. Further, we used this classifier to validate circulating breast tumor cells captured using a newly developed microfluidic system for label-free enrichment of CTCs.
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.