Evidence map›Paper›PMID 33257508›Full record

ArticleMolecular cancer research : MCR2021

A New Pipeline to Predict and Confirm Tumor Neoantigens Predict Better Response to Immune Checkpoint Blockade.

Yelena Lazdun, Han Si, Todd Creasy, Koustubh Ranade, Brandon W Higgs, Katie Streicher, Nicholas M Durham

Open access · bronzeAbstract read
PubMed Publisher
In one paragraph

Article in Molecular cancer research : MCR, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.6field-weighted citation impact, top 34% 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

7 citing papers in PubMed, 11 citations in OpenAlex.

  1. Dual mRNA nanoparticles strategy for enhanced pancreatic cancer treatment and β-elemene combination therapy.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  2. Shifting cold to hot tumors by nanoparticle-loaded drugs and products.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2025
    Review
  3. Review
  4. Article
  5. Review
  6. A Bayesian network meta-analysis of comparison of cancer therapeutic vaccines for melanoma.Journal of the European Academy of Dermatology and Venereology : JEADV · 2021
    Review
  7. Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 2 countries.

Yelena Lazdun *Translational Functional Genomics, AstraZeneca, Gaithersburg, Maryland.ORCID https://orcid.org/0000-0002-3388-2607
Han Si *Translational Bioinformatics, AstraZeneca, Gaithersburg, Maryland.
Todd CreasyTranslational Bioinformatics, AstraZeneca, Gaithersburg, Maryland.
Koustubh RanadeTranslational Medicine, Oncology R&D, AstraZeneca, Gaithersburg, Maryland.
Brandon W HiggsTranslational Bioinformatics, AstraZeneca, Gaithersburg, Maryland.
Katie StreicherTranslational Medicine, Oncology R&D, AstraZeneca, Gaithersburg, Maryland.
Nicholas M DurhamTranslational Functional Genomics, AstraZeneca, Gaithersburg, Maryland. nicholas.durham@astrazeneca.com.
AstraZeneca (Netherlands) · NLAstraZeneca (Poland) · PL

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mutations that drive oncogenesis in cancer can generate neoantigens that may be recognized by the immune system. Identification of these neoantigens remains challenging due to the complexity of the MHC antigen and T-cell receptor interaction. Here, we describe the development of a systematic approach to efficiently identify and validate immunogenic neoantigens. Whole-exome sequencing of tissue from a patient with melanoma was used to identify nonsynonymous mutations, followed by MHC binding prediction and identification of tumor clonal architecture. The top 18 putative class I neoantigens were selected for immunogenicity testing via a novel

Indexed as

Antigens, NeoplasmHumansImmune Checkpoint InhibitorsNeoplasmsAntigens, NeoplasmImmune Checkpoint Inhibitors

Identifiers

PMID33257508
OpenAlexW3108826060

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.