Evidence map›Paper›PMID 32117226›Full record

ReviewFrontiers in immunology2020

Computational Prediction and Validation of Tumor-Associated Neoantigens.

Vladimir Roudko, Benjamin Greenbaum, Nina Bhardwaj

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in immunology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 79 papers.

0numbers the graph read from it
0cells of the map it votes in
79citing papers in PubMed
6.6field-weighted citation impact, top 2% 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

79 citing papers in PubMed, 121 citations in OpenAlex.

  1. Personalized neoantigen mRNA vaccines for pancreatic cancer: the role of lipid nanoparticle delivery systems.Daru : journal of Faculty of Pharmacy, Tehran University of Medical Sciences · 2026
    Review
  2. Ensembles ofbioRxiv : the preprint server for biology · 2026
    Article
  3. Human Organoids as a Novel Tool for Vaccine Study.Advanced healthcare materials · 2026
    Review
  4. Review
  5. Molecular origin, discovery, validation and application of neoantigens.Asian journal of pharmaceutical sciences · 2026
    Review
  6. Review
  7. Review
  8. Review
  9. Computational Methods for Cancer Neoantigen Prediction.Methods in molecular biology (Clifton, N.J.) · 2026
    Article
  10. Review
  11. Review
  12. Article
  13. Article
  14. Personalizing DNA Cancer Vaccines.Journal of personalized medicine · 2025
    Review
  15. Article
  16. Article
  17. Review
  18. Review
  19. Article
  20. Review

19 more citing papers are in PubMed but not listed here.

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

3 authors at 2 institutions in 1 country.

Vladimir RoudkoDepartment of Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai Hospital, New York, NY, United States.
Benjamin GreenbaumCenter for Computational Immunology, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai Hospital, New York, NY, United States.
Nina BhardwajDepartment of Hematology and Medical Oncology, Icahn School of Medicine at Mount Sinai Hospital, New York, NY, United States.
Icahn School of Medicine at Mount Sinai · USMount Sinai Hospital · US

Funding

THE TISCH CANCER INSTITUTE - CANCER CENTER SUPPORT GRANTP30CA196521 · NCI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI Ramon E Parsons · 2015 to 2026
$35.4M
Modulating anti-HIV immunity by plasmacytoid dendritic cellsR01AI081848 · NIAID · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI BHARDWAJ, NINA · 2010 to 2021
$4.5M
NK cell exhaustion in metastatic melanomaR01CA201189 · NCI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI BHARDWAJ, NINA · 2016 to 2020
$2.1M
Matrix metalloproteinase-2 modulates inflammation via TLR2R01CA180913 · NCI · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · PI BHARDWAJ, NINA · 2014 to 2018
$1.8M
NCI NIH HHS P30 CA196521NCI NIH HHS R01 CA180913NCI NIH HHS R01 CA201189NIAID NIH HHS R01 AI081848
6 · The paper itself

Abstract

Tumor progression is typically accompanied by an accumulation of driver and passenger somatic mutations. A handful of those mutations occur in protein coding genes which introduce non-synonymous polymorphisms. Certain substitutions may give rise to novel, tumor-associated antigens or neoantigens, presentable by cancer cells to the host adaptive immune system. As antigen recognition is the core of an effective immune response, the identification of patient tumor specific antigens derived from transformed cells is of importance for immunotherapeutic approaches. Recent technological advances in DNA sequencing of tumor genomes, advances in gene expression analysis, algorithm development for antigen predictions and methods for T-cell receptor (TCR) repertoire sequencing have facilitated the selection of candidate immunogenic neoantigens. In this regard, multiple research groups have reported encouraging results of neoantigen-based cancer vaccines that generate tumor antigen specific immune responses, both in mouse models and clinical trials. Additionally, both the quantity and quality of neoantigens has been shown to have predictive value for clinical outcomes in checkpoint-blockade immunotherapy in certain tumor types. Neoantigen recognition by vaccination or through adoptive T cell therapy may have unprecedented potential to advance cancer immunotherapy in combination with other approaches. In our review we discuss three parameters regarding neoantigens: computational methods for epitope prediction, experimental methods for epitope immunogenicity validation and future directions for improvement of those methods. Within each section, we will describe the advantages and limitations of existing methods as well as highlight pressing fundamental problems to be addressed.

Indexed as

AnimalsAntigens, NeoplasmCancer VaccinesDisease Models, AnimalEpitopesExome SequencingHumansImmune Checkpoint InhibitorsImmunogenicity, VaccineImmunotherapy, AdoptiveMiceMutationNeoplasmsVaccinationAntigens, NeoplasmCancer VaccinesEpitopesImmune Checkpoint InhibitorsHLA-alleleMHC-I epitopeneoantigenTCRWES

Identifiers

PMID32117226
PMCPMC7025577
OpenAlexW3002909206

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.