Evidence map›Paper›PMID 23341571›Full record

ReviewCancer prevention research (Philadelphia, Pa.)2013

Personalized immune-interception of cancer and the battle of two adaptive systems--when is the time right?

Madhav V Dhodapkar

Abstract readReview
In one paragraph

Review in Cancer prevention research (Philadelphia, Pa.), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Article
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

1 author.

Madhav V DhodapkarYale University School of Medicine, 333 Cedar Street, Box 208028, New Haven, CT 06510, USA. madhav.dhodapkar@yale.edu

Funding

Anti-Tumor immunity in myelomaR01CA106802 · NCI · YALE UNIVERSITY · PI DHODAPKAR, MADHAV V · 2004 to 2016
$3.3M
Targeting myeloma via dendritic cellsR01CA109465 · NCI · YALE UNIVERSITY · PI DHODAPKAR, MADHAV V · 2005 to 2009
$1.6M
Immunity to stem cell antigens in preneoplastic gammopathyR01CA135110 · NCI · YALE UNIVERSITY · PI DHODAPKAR, MADHAV V · 2008 to 2013
$1.6M
NCI NIH HHS R01 CA106802NCI NIH HHS R01 CA109465NCI NIH HHS R01 CA135110
6 · The paper itself

Abstract

A growing body of evidence points to a coevolutionary model of cancer, wherein the cross-talk between tumor cells (or their subclones) and the host determine the malignant potential of individual tumors. Most of this natural history is clinically invisible and includes preneoplastic states. The capacity of the immune system to recognize these incipient lesions provides the basis for targeting them immunologically to arrest the development of preneoplasia toward clinical cancer. Kimura and colleagues provide evidence of immunogenicity of a potential cancer vaccine in patients with a history of advanced colon adenomas. These studies provide proof-of-principle or feasibility of such an approach in the clinic. Here, we discuss emerging opportunities and challenges in harnessing the immune system to "intercept" the precursor or preneoplastic lesions. Both cancer cells as well as the immune system represent independent and complex systems with plasticity and adaptive potential. It is therefore likely that specific aspects of the cross-talk between tumor cells and host may differ between individual tumors and determine the evolution of both tumors and the host response. We try to make the case to consider individualized approaches based on the genetic make-up of tumor cells and properties of the host response. Such strategies may be needed to optimally position the immune system to prevent cancers.

Indexed as

Precision MedicineAnimalsHumansImmune SystemNeoplasms

Identifiers

PMID23341571
PMCPMC3593788

What OpenQuestion holds

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Registered trials

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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.