Evidence map›Paper›PMID 33563578›Full record

ReviewTrends in cancer2021

Leveraging Single-Cell Approaches in Cancer Precision Medicine.

Aritro Nath, Andrea H Bild

Open access · greenAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Trends in cancer, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing papers in PubMed
5.2field-weighted citation impact, top 3% 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

31 citing papers in PubMed, 52 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Aritro NathDepartment of Medical Oncology and Therapeutics Research, City of Hope, Monrovia, CA 91016, USA. Electronic address: anath@coh.org.
Andrea H BildDepartment of Medical Oncology and Therapeutics Research, City of Hope, Monrovia, CA 91016, USA.
City of Hope · US

Funding

Project 2: Targeting Cooperative Phenotypes Common in Spatial HeterogeneityU54CA209978 · NCI · UNIVERSITY OF UTAH · PI BILD, ANDREA HOPE · 2017 to 2021
$10.5M
NCI NIH HHS U54 CA209978
6 · The paper itself

Abstract

Cancer precision medicine aims to improve patient outcomes by tailoring treatment to the unique genomic background of a tumor. However, efforts to develop prognostic and drug response biomarkers largely rely on bulk 'omic' data, which fails to capture intratumor heterogeneity (ITH) and deconvolve signals from normal versus tumor cells. These shortcomings in measuring clinically relevant features are being addressed with single-cell technologies, which provide a fine-resolution map of the genetic and phenotypic heterogeneity in tumors and their microenvironment, as well as an improved understanding of the patterns of subclonal tumor populations. Here we present recent advances in the application of single-cell technologies, towards gaining a deeper understanding of ITH and evolution, and potential applications in developing personalized therapeutic strategies.

Indexed as

NeoplasmsPrecision MedicineSingle-Cell AnalysisDrug Resistance, NeoplasmGenetic HeterogeneityHumansTumor Microenvironmentbiomarkersclonal evolutionsingle-cell sequencingtumor heterogeneitytumor microenvironment

Identifiers

PMID33563578
PMCPMC7969443
OpenAlexW3126794667

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.