Evidence map›Paper›PMID 30510237›Full record

ArticleNature genetics2019

Accounting for proximal variants improves neoantigen prediction.

Jasreet Hundal, Susanna Kiwala, Yang-Yang Feng, Connor J Liu, Ramaswamy Govindan, William C Chapman, Ravindra Uppaluri, S Joshua Swamidass, Obi L Griffith, Elaine R Mardis and 1 more

Abstract read
In one paragraph

Article in Nature genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 1 pooled it
–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

30 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Trial
  3. Article
  4. Computational Methods for Cancer Neoantigen Prediction.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
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  16. Frontiers in oncology · 2022
    Article
  17. Engineering neoantigen vaccines to improve cancer personalized immunotherapy.International journal of biological sciences · 2022
    Review
  18. Article
  19. Article
  20. 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

11 authors.

Jasreet HundalMcDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA.ORCID http://orcid.org/0000-0002-2584-5320
Susanna KiwalaMcDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA.ORCID http://orcid.org/0000-0003-4378-7328
Yang-Yang FengMcDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA.ORCID http://orcid.org/0000-0002-6347-6749
Connor J LiuMcDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA.
Ramaswamy GovindanSiteman Cancer Center, Washington University School of Medicine, St. Louis, MO, USA.
William C ChapmanDepartment of Surgery, Washington University School of Medicine, St. Louis, MO, USA.
Ravindra UppaluriDepartment of Surgery/Otolaryngology, Brigham and Women's Hospital and Dana-Farber Cancer Institute, Boston, MA, USA.
S Joshua SwamidassDepartment of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA.
Obi L GriffithMcDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA.ORCID http://orcid.org/0000-0002-0843-4271
Elaine R MardisInstitute for Genomic Medicine, Nationwide Children's Hospital, Columbus, OH, USA. elaine.mardis@nationwidechildrens.org.
Malachi GriffithMcDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO, USA. mgriffit@wustl.edu.ORCID http://orcid.org/0000-0002-6388-446X

Funding

Genomic and Functional Identification of Chemotherapy Resistance Mechanisms in Small Cell Lung CancerU01CA231844 · NCI · WASHINGTON UNIVERSITY · PI GOVINDAN, RAMASWAMY, GRIFFITH, OBI L. · 2018 to 2022
$3.1M
Immunotherapeutic responses to neoantigens in head and neck cancerR01DE027736 · NIDCR · DANA-FARBER CANCER INST · PI UPPALURI, RAVINDRA · 2018 to 2022
$2.9M
GENOMIC INSIGHTS AND THERAPEUTIC TARGETING OF ORAL CANCER TUMOR INITIATING CELLSR01DE024403 · NIDCR · WASHINGTON UNIVERSITY · PI UPPALURI, RAVINDRA · 2014 to 2018
$1.9M
DATA AND TOOLS FOR MODELING METABOLISM AND REACTIVITYR01LM012222 · NLM · WASHINGTON UNIVERSITY · PI MILLER, GROVER P, SWAMIDASS, SANJAY JOSHUA · 2016 to 2019
$1.5M
Computationally modeling the impact of ontogeny on drug metabolic fateR01LM012482 · NLM · UNIV OF ARKANSAS FOR MED SCIS · PI MILLER, GROVER P, SWAMIDASS, SANJAY JOSHUA · 2016 to 2019
$1.3M
DEVELOPMENT OF INFORMATICS RESOURCES FOR INTERPRETATION OF CLINICALLY ACTIONABLE VARIANTS IN CANCERU01CA209936 · NCI · WASHINGTON UNIVERSITY · PI GRIFFITH, OBI L. · 2016 to 2018
$1.0M
Integrated Analysis & Interpretation of Whole Genome Exome & Transcriptome SequenR00HG007940 · NHGRI · WASHINGTON UNIVERSITY · PI GRIFFITH, MALACHI · 2017 to 2019
$724k
DEFINING THE REGULATORY, NON-CODING, MUTATIONAL LANDSCAPE OF BREAST CANCERK22CA188163 · NCI · WASHINGTON UNIVERSITY · PI GRIFFITH, OBI L. · 2014 to 2016
$515k
NCI NIH HHS K22 CA188163NCI NIH HHS U01 CA209936NCI NIH HHS U01 CA231844NHGRI NIH HHS R00 HG007940NIDCR NIH HHS R01 DE024403NIDCR NIH HHS R01 DE027736NLM NIH HHS R01 LM012222NLM NIH HHS R01 LM012482
6 · The paper itself

Abstract

Recent efforts to design personalized cancer immunotherapies use predicted neoantigens, but most neoantigen prediction strategies do not consider proximal (nearby) variants that alter the peptide sequence and may influence neoantigen binding. We evaluated somatic variants from 430 tumors to understand how proximal somatic and germline alterations change the neoantigenic peptide sequence and also affect neoantigen binding predictions. On average, 241 missense somatic variants were analyzed per sample. Of these somatic variants, 5% had one or more in-phase missense proximal variants. Without incorporating proximal variant correction for major histocompatibility complex class I neoantigen peptides, the overall false discovery rate (incorrect neoantigens predicted) and the false negative rate (strong-binding neoantigens missed) across peptides of lengths 8-11 were estimated as 0.069 (6.9%) and 0.026 (2.6%), respectively.

Indexed as

Antigens, NeoplasmGenetic VariationHistocompatibility Antigens Class IHumansImmunotherapyNeoplasmsAntigens, NeoplasmHistocompatibility Antigens Class I

Identifiers

PMID30510237
PMCPMC6309579

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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.