Evidence map›Paper›PMID 27608848›Full record

ReviewOncotarget2016

Addressing intra-tumoral heterogeneity and therapy resistance.

Brad Rybinski, Kyuson Yun

Open access · diamondAbstract readReview
In one paragraph

Review in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
53citing papers in PubMed, 1 pooled it
3.9field-weighted citation impact, top 5% 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

53 citing papers in PubMed, 1 synthesis or guideline pooled it, 86 citations in OpenAlex.

  1. Circulating Cell-Free DNA and Colorectal Cancer: A Systematic Review.International journal of molecular sciences · 2018
    Pooled it
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  15. Lactobacillus for ribosome peptide editing cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2023
    Review
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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 2 institutions in 1 country.

Brad RybinskiAlbert Einstein College of Medicine, Bronx, NY, USA.
Kyuson YunThe Jackson Laboratory, Bar Harbor, ME, USA.
Albert Einstein College of Medicine · USJackson Laboratory · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In the last several years, our appreciation of intra-tumoral heterogeneity has greatly increased due to accumulating evidence for the co-existence of genetically and epigenetically divergent cancer cells residing in different microenvironments within a tumor. Herein, we review recent literature discussing intra-tumoral heterogeneity in the context of therapy resistance mechanisms at the genetic, epigenetic and microenvironmental levels. We illustrate the influence of tumor microenvironment on therapy resistance and epigenetic states of cancer cells by highlighting the role of cancer stem cells in therapy resistance. We also summarize different strategies that have been employed to address various resistance mechanisms at genetic, epigenetic, and microenvironmental levels in preclinical and clinical studies. We propose that future personalized cancer therapy design needs to incorporate dynamic and comprehensive analyses of tumor heterogeneity landscape and multi-dimensional mechanisms of therapy resistance.

Indexed as

Genetic HeterogeneityAntineoplastic AgentsDrug Resistance, NeoplasmEpigenesis, GeneticHumansMolecular Targeted TherapyMutationNeoplasmsNeoplastic Stem CellsSignal TransductionTumor MicroenvironmentAntineoplastic Agentscancer stem cellsepigeneticheterogeneitymicroenvironmenttherapy resistance

Identifiers

PMID27608848
PMCPMC5342165
OpenAlexW2519072971

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.