Evidence map›Paper›PMID 23706768›Full record

ArticleChinese journal of cancer2013

Investigating evolutionary perspective of carcinogenesis with single-cell transcriptome analysis.

Xi Zhang, Cheng Zhang, Zhongjun Li, Jiangjian Zhong, Leslie P Weiner, Jiang F Zhong

Open access · bronzeAbstract read
In one paragraph

Article in Chinese journal of cancer, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.6field-weighted citation impact, top 30% of its field
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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Article
  3. Single-cell Transcriptome Study as Big Data.Genomics, proteomics & bioinformatics · 2016
    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

6 authors at 3 institutions in 2 countries.

Xi ZhangDepartment of Pathology, University of Southern California, Keck School of Medicine, Los Angeles, CA 90033, USA; 2Z-Genetic Medicine LLC, Temple City, CA 91780, USA. jzhong@usc.edu.
Cheng Zhang
Zhongjun Li
Jiangjian Zhong
Leslie P Weiner
Jiang F Zhong
Army Medical University · CNUniversity of Southern California · USTemple University · US

Funding

Southern California Clinical and Translational Science InstituteUL1TR000130 · NCATS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI BUCHANAN, THOMAS A · 2012 to 2015
$36.0M
Multi-phase Microfluidic Devices for Characterization of Circulating Tumor CellsR01CA164509 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ZHONG, JOHN · 2012 to 2016
$2.0M
Microfluidic Devices for Molecular Characterization of Cancer Cells at the SingleR21CA134391 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ZHONG, JOHN · 2009 to 2010
$633k
NCATS NIH HHS UL1 TR000130NCI NIH HHS R01 CA164509NCI NIH HHS R01CA164509NCI NIH HHS R21 CA134391NCI NIH HHS R21CA134391
6 · The paper itself

Abstract

We developed phase-switch microfluidic devices for molecular profiling of a large number of single cells. Whole genome microarrays and RNA-sequencing are commonly used to determine the expression levels of genes in cell lysates (a physical mix of millions of cells) for inferring gene functions. However, cellular heterogeneity becomes an inherent noise in the measurement of gene expression. The unique molecular characteristics of individual cells, as well as the temporal and quantitative information of gene expression in cells, are lost when averaged among all cells in cell lysates. Our single-cell technology overcomes this limitation and enables us to obtain a large number of single-cell transcriptomes from a population of cells. A collection of single-cell molecular profiles allows us to study carcinogenesis from an evolutionary perspective by treating cancer as a diverse population of cells with abnormal molecular characteristics. Because a cancer cell population contains cells at various stages of development toward drug resistance, clustering similar single-cell molecular profiles could reveal how drug-resistant sub-clones evolve during cancer treatment. Here, we discuss how single-cell transcriptome analysis technology could enable the study of carcinogenesis from an evolutionary perspective and the development of drug-resistance in leukemia. The single-cell transcriptome analysis reported here could have a direct and significant impact on current cancer treatments and future personalized cancer therapies.

Indexed as

Gene Expression ProfilingTranscriptomeCarcinogenesisDrug Resistance, NeoplasmHematopoietic Stem CellsHumansLeukemia, Myelogenous, Chronic, BCR-ABL PositiveMicrofluidic Analytical TechniquesSingle-Cell Analysis

Identifiers

PMID23706768
PMCPMC3870846
OpenAlexW2026012491

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.