Evidence map›Paper›PMID 30515270›Full record

ReviewOncotarget2018

Attaining threshold antibody cytotoxicity for selective tumor cell destruction: an opinion article.

Victor I Seledtsov, Galina V Seledtsova

Open access · diamondAbstract readReview
In one paragraph

Review in Oncotarget, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.2field-weighted citation impact, top 47% 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

4 citing papers in PubMed, 10 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. 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

2 authors at 2 institutions in 1 country.

Victor I Seledtsovlmmanuel Kant Baltic Federal University, Kaliningrad, Russia.
Galina V SeledtsovaInstitute for Fundamental and Clinical Immunology, Novosibirsk, Russia.
Immanuel Kant Baltic Federal University · RUResearch Institute of Fundamental and Clinical Immunology · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We propose a novel immunotherapeutic paradigm that justifies application of several antibodies to various membrane-associated antigens to achieve a critical threshold density of immune complexes on the surface of cancer cells sufficient for triggering downstream cytolytic pathways. Indeed, some cancer-associated antigens (such as cancer/testis antigens) were found to be expressed on many cancer (but not normal) cells, with their baseline membrane expression levels being originally quite low for some of them, or even further down-regulated due to immune-driven cell selection. To achieve the mandatory threshold density of membrane-associated immune complexes on malignant cells, the concept stipulates combined application of antibodies specific for a cancer-associated antigen along with antibodies against an antigen expressed not only on tumor, but also on normal cells. In the proposed scenario it is of vital importance that the latter antibodies should be applied in suboptimal dosage to exclude the destruction of normal cells devoid of a cancer-associated antigen. Malignant cells often co-express antigens not present concurrently on normal cells at high levels. In such cases, suboptimal dosages of antibodies specific for those antigens could also be applied to achieve cumulative effect leading to selective destruction of tumour cells. Hence, the described immunotherapeutic technology could be used metaphorically speaking as a kind of 'immunological knife', which is capable of highly selective destruction of cancer cells without destroying normal cells.

Indexed as

antibody-mediated cytotoxicityimmune complextherapeutic antibodytumor destruction

Identifiers

PMID30515270
PMCPMC6254663
OpenAlexW2899691059

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.