ReviewNature biotechnology2012
From single cells to deep phenotypes in cancer.
Review in Nature biotechnology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 114 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
114 citing papers in PubMed.
- Anti-α4β7 therapy targets lymphoid aggregates in the gastrointestinal tract of HIV-1-infected individuals.Science translational medicine · 2018Trial
- In-air microfluidic sorting of single cells on multiple paths.Microsystems & nanoengineering · 2025Article
- Hypersonic levitation and spinning: paving the way for enhanced single-cell analysis via contactless tissue dissociation.Communications engineering · 2025Article
- Polymer-Based Mass Cytometry Reagents: Synthesis and Biomedical Applications.Molecules (Basel, Switzerland) · 2025Review
- Review
- Profiling signaling mediators for cell-cell interactions and communications with microfluidics-based single-cell analysis tools.iScience · 2025Review
- Single-cell proteomics delineates murine systemic immune response to blast lung injury.Communications biology · 2024Article
- Single-cell mass cytometry in immunological skin diseases.Frontiers in immunology · 2024Review
- Aneuploidy in human cancer: new tools and perspectives.Trends in genetics : TIG · 2023Review
- COSMOS: a platform for real-time morphology-based, label-free cell sorting using deep learning.Communications biology · 2023Article
- Single-cell profiling reveals a memory B cell-like subtype of follicular lymphoma with increased transformation risk.Nature communications · 2022Article
- Mass cytometry reveals immune atlas of urothelial carcinoma.BMC cancer · 2022Article
- Immunophenotyping: Analytical approaches and role in preclinical development of nanomedicines.Advanced drug delivery reviews · 2022Review
- Microfluidic Device Technologies for Digestion, Disaggregation, and Filtration of Tissue Samples for Single Cell Applications.Methods in molecular biology (Clifton, N.J.) · 2022Article
- The Interleukin-1 (IL-1) Superfamily Cytokines and Their Single Nucleotide Polymorphisms (SNPs).Journal of immunology research · 2022Review
- Mass Cytometry for the Characterization of Individual Cell Types in Ovarian Solid Tumors.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Knowledge transfer to enhance the performance of deep learning models for automated classification of B cell neoplasms.Patterns (New York, N.Y.) · 2021Article
- Single-cell analysis defines a pancreatic fibroblast lineage that supports anti-tumor immunity.Cancer cell · 2021Article
- Single-cell analysis at the protein level delineates intracellular signaling dynamic during hematopoiesis.BMC biology · 2021Article
- Multiplexed live-cell profiling with Raman probes.Nature communications · 2021Article
54 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
In recent years, major advances in single-cell measurement systems have included the introduction of high-throughput versions of traditional flow cytometry that are now capable of measuring intracellular network activity, the emergence of isotope labels that can enable the tracking of a greater variety of cell markers and the development of super-resolution microscopy techniques that allow measurement of RNA expression in single living cells. These technologies will facilitate our capacity to catalog and bring order to the inherent diversity present in cancer cell populations. Alongside these developments, new computational approaches that mine deep data sets are facilitating the visualization of the shape of the data and enabling the extraction of meaningful outputs. These applications have the potential to reveal new insights into cancer biology at the intersections of stem cell function, tumor-initiating cells and multilineage tumor development. In the clinic, they may also prove important not only in the development of new diagnostic modalities but also in understanding how the emergence of tumor cell clones harboring different sets of mutations predispose patients to relapse or disease progression.
Indexed as
Identifiers
22781693What 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.