Evidence map›Paper›PMID 22484193›Full record

ReviewSeminars in oncology2012

Advances in the treatment of metastatic melanoma: adoptive T-cell therapy.

Chantale Bernatchez, Laszlo G Radvanyi, Patrick Hwu

Open access · greenAbstract readReview
In one paragraph

Review in Seminars in oncology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
2.3field-weighted citation impact, top 11% 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

15 citing papers in PubMed, 39 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

3 authors at 2 institutions in 2 countries.

Chantale BernatchezDepartment of Melanoma Medical Oncology, The University of Texas, M.D. Anderson Cancer Center, Houston, TX 77054, USA. cbernatc@mdanderson.org
Laszlo G Radvanyi
Patrick Hwu
Melanoma Institute Australia · AUThe University of Texas MD Anderson Cancer Center · US

Funding

Transduction of T-cells to improve migration to tumorR01CA116206 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI HWU, PATRICK · 2005 to 2014
$3.2M
DC Vaccination to Enhance Adoptive T Cell TransferR01CA111999 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI HWU, PATRICK · 2006 to 2010
$1.8M
NCI NIH HHS R01 CA111999NCI NIH HHS R01 CA116206
6 · The paper itself

Abstract

Metastatic melanoma is notoriously resistant to chemotherapy and radiotherapy regimens. The prospect for newly diagnosed metastatic melanoma patients is grim, with a median survival of less than 1 year. Currently, the only therapies resulting in long-term disease-free intervals, high-dose interleukin-2 (IL-2) and more recently anti-CTLA-4, work through activation of the immune system. However, with both therapies the response rate is low. Advances in our knowledge of how the immune system interacts with cancer have led to a number of strategies to manipulate anti-tumor immune responses through immunotherapy. This review will focus on one avenue of immunotherapy using the transfer of T cells referred to as "adoptive cell therapy" (ACT), which involves the ex vivo expansion of autologous tumor-specific T cells to large numbers that are ultimately transferred back to the patient to boost anti-tumor immunity. This approach has been shown to be effective in the treatment of virally induced cancers, as well as metastatic melanoma. Recent successes with ACT hold promise and further emphasize the tremendous potential benefit of harnessing the immune system in the fight against cancer.

Indexed as

AnimalsClinical Trials as TopicHumansImmunotherapy, AdoptiveMelanomaRandomized Controlled Trials as TopicT-Lymphocytes

Identifiers

PMID22484193
PMCPMC3500663
OpenAlexW2135701120

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.