Evidence map›Paper›PMID 28188495›Full record

ReviewClinical and experimental medicine2017

Cancer treatment and the KIR-HLA system: an overview.

Patrizia Leone, Valli De Re, Angelo Vacca, Franco Dammacco, Vito Racanelli

Abstract readReview
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In one paragraph

Review in Clinical and experimental medicine, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed.

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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

5 authors.

Patrizia LeoneDepartment of Internal Medicine and Clinical Oncology, University of Bari Medical School, Policlinico - 11, Piazza G. Cesare, 70124, Bari, Italy.
Valli De ReBio-Proteomics Facility, Department of Translational Research, Centro di Riferimento Oncologico, National Cancer Institute, Aviano, Italy.
Angelo VaccaDepartment of Internal Medicine and Clinical Oncology, University of Bari Medical School, Policlinico - 11, Piazza G. Cesare, 70124, Bari, Italy.
Franco DammaccoDepartment of Internal Medicine and Clinical Oncology, University of Bari Medical School, Policlinico - 11, Piazza G. Cesare, 70124, Bari, Italy.
Vito RacanelliDepartment of Internal Medicine and Clinical Oncology, University of Bari Medical School, Policlinico - 11, Piazza G. Cesare, 70124, Bari, Italy. vito.racanelli1@uniba.it.ORCID http://orcid.org/0000-0002-8639-1940

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Accumulating evidence indicates that the success of cancer therapy depends not only on a combination of adequate procedures (surgery, chemotherapy and radiotherapy) that aim to eliminate all tumor cells, but also on the functional state of the host immune system. HLA and KIR molecules, in particular, are critical to the interactions between tumor cells and both innate and adaptive immune cells such as NK cells and T cells. Different KIR-HLA gene combinations as well as different HLA expression levels on tumor cells associate with variable tumor prognosis and response to treatment. On the other hand, different therapies have different effects on HLA molecules and immune cell functions regulated by these molecules. Here, we provide an overview of the KIR-HLA system, a description of its alterations with clinical relevance in diverse tumor types, and an analysis of the consequences that conventional cancer therapies may have on it. We also discuss how this knowledge can be exploited to identify potential immunological biomarkers that can help to select patients for tailored therapy.

Indexed as

HLA AntigensHumansNeoplasmsReceptors, KIRTreatment OutcomeHLA AntigensReceptors, KIRCancer treatmentHLAKIRNK cellsT cellsTumor immune evasion

Identifiers

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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.