Evidence map›Paper›PMID 39156821›Full record

ArticleCancer heterogeneity and plasticity2024

Advances in Single-Cell Techniques for Linking Phenotypes to Genotypes.

Hsiao-Chun Chen, Yushu Ma, Jinxiong Cheng, Yu-Chih Chen

Abstract read
In one paragraph

Article in Cancer heterogeneity and plasticity, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Hsiao-Chun ChenUPMC Hillman Cancer Center, University of Pittsburgh, 5115 Centre Ave, Pittsburgh, PA 15232, USA.
Yushu MaUPMC Hillman Cancer Center, University of Pittsburgh, 5115 Centre Ave, Pittsburgh, PA 15232, USA.
Jinxiong ChengUPMC Hillman Cancer Center, University of Pittsburgh, 5115 Centre Ave, Pittsburgh, PA 15232, USA.
Yu-Chih ChenUPMC Hillman Cancer Center, University of Pittsburgh, 5115 Centre Ave, Pittsburgh, PA 15232, USA.

Funding

VECTOR CORE FACILITYP30CA047904 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI CHRISTOPHER J. BAKKENIST · 1988 to 2026
$158.0M
University of Pittsburgh Clinical and Translational Science InstituteUL1TR001857 · NCATS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI REIS, STEVEN E · 2016 to 2025
$129.3M
Project 3: Hedgehog Inhibition to Enhance Response to ICI TherapyP50CA272218 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI FRANCESMARY MODUGNO · 2023 to 2026
$11.0M
Deciphering Cellular Heterogeneity and Inheritability in MigrationR35GM150509 · NIGMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI Yu-Chih Chen · 2023 to 2026
$1.5M
NCATS NIH HHS UL1 TR001857NCI NIH HHS P30 CA047904NCI NIH HHS P50 CA272218NIGMS NIH HHS R35 GM150509
6 · The paper itself

Abstract

Single-cell analysis has become an essential tool in modern biological research, providing unprecedented insights into cellular behavior and heterogeneity. By examining individual cells, this approach surpasses conventional population-based methods, revealing critical variations in cellular states, responses to environmental cues, and molecular signatures. In the context of cancer, with its diverse cell populations, single-cell analysis is critical for investigating tumor evolution, metastasis, and therapy resistance. Understanding the phenotype-genotype relationship at the single-cell level is crucial for deciphering the molecular mechanisms driving tumor development and progression. This review highlights innovative strategies for selective cell isolation based on desired phenotypes, including robotic aspiration, laser detachment, microraft arrays, optical traps, and droplet-based microfluidic systems. These advanced tools facilitate high-throughput single-cell phenotypic analysis and sorting, enabling the identification and characterization of specific cell subsets, thereby advancing therapeutic innovations in cancer and other diseases.

Indexed as

cellular heterogeneitydropletsgenotypemicrofluidicsphenotypeselective cell retrievalsingle-cell analysis

Identifiers

PMID39156821
PMCPMC11328949

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.