Evidence map›Paper›PMID 25164877›Full record

ReviewCancer immunology, immunotherapy : CII2015

Somatically mutated tumor antigens in the quest for a more efficacious patient-oriented immunotherapy of cancer.

Zlatko Trajanoski, Cristina Maccalli, Daniele Mennonna, Giulia Casorati, Giorgio Parmiani, Paolo Dellabona

Open access · greenAbstract readReview
In one paragraph

Review in Cancer immunology, immunotherapy : CII, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.1field-weighted citation impact, top 8% 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

19 citing papers in PubMed, 32 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

6 authors at 4 institutions in 2 countries.

Zlatko TrajanoskiBiocenter, Division for Bioinformatics, Innsbruck Medical University, Innrain 80, 6020, Innsbruck, Austria.
Cristina Maccalli
Daniele Mennonna
Giulia Casorati
Giorgio Parmiani
Paolo Dellabona
Vita-Salute San Raffaele University · ITInnsbruck Medical University · ATNetwork Italiano Per la Bioterapia Dei Tumori · ITSan Raffaele University of Rome · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Although cancer immunotherapy shows efficacy with adoptive T cell therapy (ACT) and antibody-based immune checkpoint blockade, efficacious therapeutic vaccination of cancer patients with tumor-associated antigens (TAAs) remains largely unmet. Current cancer vaccines utilize nonmutated shared TAAs that may have suboptimal immunogenicity. Experimental evidence underscores the strong immunogenicity of unique TAAs derived from somatically mutated cancer proteins, whose massive characterization has been precluded until recently by technical limitations. The development of cost-effective, high-throughput DNA sequencing approaches makes now possible the rapid identification of all the somatic mutations contained in a cancer cell genome. This method, combined with robust bioinformatics platforms for T cell epitope prediction and established reverse immunology approaches, provides us with an integrated strategy to identify patient-specific unique TAAs in a relatively short time, compatible with their potential use in the clinic. Hence, it is now for the first time possible to quantitatively define the patient's unique tumor antigenome and exploit it for vaccination, possibly in combination with ACT and/or immune checkpoint blockade to further increase immunotherapy efficacy.

Indexed as

ImmunotherapyAnimalsAntigens, NeoplasmHumansLymphocytes, Tumor-InfiltratingNeoplasmsT-LymphocytesAntigens, Neoplasm

Identifiers

PMID25164877
PMCPMC11028785
OpenAlexW2032986687

What OpenQuestion holds

Textmetadata
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.