Evidence map›Paper›PMID 29046389›Full record

ArticleMolecular & cellular proteomics : MCP2017

The Antibody Repertoire of Colorectal Cancer.

Seong Won Cha, Stefano Bonissone, Seungjin Na, Pavel A Pevzner, Vineet Bafna

Open access · hybridAbstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.2field-weighted citation impact, top 37% 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

5 citing papers in PubMed, 12 citations in OpenAlex.

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  5. Review
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 at 2 institutions in 1 country.

Seong Won ChaFrom the ‡Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, California.ORCID http://orcid.org/0000-0001-6732-8471
Stefano Bonissone§Digital Proteomics, LLC, La Jolla, California.
Seungjin Na¶Department of Computer Science and Engineering, University of California, San Diego, La Jolla, California 92037.ORCID http://orcid.org/0000-0002-5159-2048
Pavel A Pevzner¶Department of Computer Science and Engineering, University of California, San Diego, La Jolla, California 92037.ORCID http://orcid.org/0000-0002-0418-165X
Vineet Bafna¶Department of Computer Science and Engineering, University of California, San Diego, La Jolla, California 92037 vbafna@cs.ucsd.edu.ORCID http://orcid.org/0000-0002-5810-6241
University of California San Diego · USAbterra Biosciences (United States) · US

Funding

TrainingP41GM103484 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PEVZNER, PAVEL A · 2012 to 2018
$8.7M
CENTER FOR COMPUTATIONAL MASS-SPECTROMETRYP41RR024851 · NCRR · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PEVZNER, PAVEL A · 2008 to 2011
$5.2M
Computational methods for detecting patterns of complex genomic variationR01GM114362 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Vineet Bafna · 2016 to 2026
$3.1M
NCRR NIH HHS P41 RR024851NIGMS NIH HHS P41 GM103484NIGMS NIH HHS R01 GM114362
6 · The paper itself

Abstract

Immunotherapy is becoming increasingly important in the fight against cancers, using and manipulating the body's immune response to treat tumors. Understanding the immune repertoire-the collection of immunological proteins-of treated and untreated cells is possible at the genomic, but technically difficult at the protein level. Standard protein databases do not include the highly divergent sequences of somatic rearranged immunoglobulin genes, and may lead to miss identifications in a mass spectrometry search. We introduce a novel proteogenomic approach, AbScan, to identify these highly variable antibody peptides, by developing a customized antibody database construction method using RNA-seq reads aligned to immunoglobulin (Ig) genes.AbScan starts by filtering transcript (RNA-seq) reads that match the template for Ig genes. The retained reads are used to construct a repertoire graph using the "split" de Bruijn graph: a graph structure that improves on the standard de Bruijn graph to capture the high diversity of Ig genes in a compact manner. AbScan corrects for sequencing errors, and converts the graph to a format suitable for searching with MS/MS search tools. We used AbScan to create an antibody database from 90 RNA-seq colorectal tumor samples. Next, we used proteogenomic analysis to search MS/MS spectra of matched colorectal samples from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) against the AbScan generated database. AbScan identified 1,940 distinct antibody peptides. Correlating with previously identified Single Amino-Acid Variants (SAAVs) in the tumor samples, we identified 163 pairs (antibody peptide, SAAV) with significant cooccurrence pattern in the 90 samples. The presence of coexpressed antibody and mutated peptides was correlated with survival time of the individuals. Our results suggest that AbScan (https://github.com/csw407/AbScan.git) is an effective tool for a proteomic exploration of the immune response in cancers.

Indexed as

AlgorithmsCell Line, TumorColorectal NeoplasmsDatabases, GeneticDatabases, ProteinGenomicsHumansImmunoglobulinsPeptidesProteomicsSequence Analysis, RNATandem Mass SpectrometryImmunoglobulinsPeptides

Identifiers

PMID29046389
PMCPMC5724175
OpenAlexW2952851998

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.