Evidence map›Paper›PMID 30936076›Full record

ArticleCancer research2019

Going Beyond the Sequences: TCR Binding Patterns at the Service of Cancer Detection.

Vincent Zoete, George Coukos

Abstract readComment
PubMed Publisher
In one paragraph

Article in Cancer research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. T Cell Receptor Repertoires AcquiredFrontiers in immunology · 2021
    Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Vincent ZoeteLudwig Institute for Cancer Research - Lausanne Branch, University of Lausanne, Lausanne, Épalinges, Switzerland.
George CoukosLudwig Institute for Cancer Research - Lausanne Branch, University of Lausanne, Lausanne, Épalinges, Switzerland. George.Coukos@chuv.ch.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deep sequencing of T-cell receptors enables the comprehensive profiling of lymphocyte populations and the characterization of the repertoire of T-cell responses against tumors, which could be applied to diagnose cancers. Ostmeyer and colleagues introduce a novel approach to characterize TCR patterns correlating with antigen recognition. By projecting the large TCR sequence space into a handful of biophysicochemical descriptors for key residues and seeking TCRs with similar antigen-binding capabilities even in the absence of identical amino acids, this approach presents several advantages over current methods.

Indexed as

High-Throughput Nucleotide SequencingProtein BindingReceptors, Antigen, T-CellT-LymphocytesReceptors, Antigen, T-Cell

Identifiers

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.