Evidence map›Paper›PMID 35732349›Full record

ReviewJournal for immunotherapy of cancer2022

Vaccines for immunoprevention of DNA mismatch repair deficient cancers.

Alejandro Hernandez-Sanchez, Mark Grossman, Kevin Yeung, Shizuko S Sei, Steven Lipkin, Matthias Kloor

Open access · goldAbstract readReview
In one paragraph

Review in Journal for immunotherapy of cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed, 1 pooled it
6.3field-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

22 citing papers in PubMed, 1 synthesis or guideline pooled it, 45 citations in OpenAlex.

  1. Pooled it
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  14. Colorectal Cancer Chemoprevention: A Dream Coming True?International journal of molecular sciences · 2023
    Review
  15. Article
  16. Article
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  18. A Focused Clinical Review of Lynch Syndrome.Cancer management and research · 2023
    Review
  19. Review
  20. 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

6 authors at 3 institutions in 2 countries.

Alejandro Hernandez-SanchezDepartment of Applied Tumor Biology, University Hospital Heidelberg Institute of Pathology, Heidelberg, Germany.ORCID 0000-0001-9522-6595
Mark GrossmanDepartment of Medicine, Weill Cornell Medicine, New York, New York, USA.
Kevin YeungDepartment of Medicine, Weill Cornell Medicine, New York, New York, USA.
Shizuko S SeiDivision of Cancer Prevention, National Cancer Institute, Bethesda, Maryland, USA.
Steven LipkinDepartment of Medicine, Weill Cornell Medicine, New York, New York, USA stl2012@med.cornell.edu.
Matthias KloorUniversity Hospital Heidelberg, Institute of Pathology, Department of Applied Tumor Biology, Heidelberg, Germany.
Cornell University · USHeidelberg University · DENational Cancer Institute · US

Funding

Disparities in COVID Disease Severity and Outcomes in New York CityUL1TR002384 · NCATS · WEILL MEDICAL COLL OF CORNELL UNIV · PI JULIANNE L IMPERATO-MCGINLEY · 2017 to 2026
$86.2M
Neoantigen Vaccination for Lynch Syndrome ImmunopreventionU01CA233056 · NCI · WEILL MEDICAL COLL OF CORNELL UNIV · PI LIPKIN, STEVEN M, VILAR SANCHEZ, EDUARDO · 2018 to 2022
$3.8M
NCATS NIH HHS UL1 TR002384NCI NIH HHS U01 CA233056
6 · The paper itself

Abstract

The development of cancer vaccines to induce tumor-antigen specific immune responses was sparked by the identification of antigens specific to or overexpressed in cancer cells. However, weak immunogenicity and the mutational heterogeneity in many cancers have dampened cancer vaccine successes. With increasing information about mutational landscapes of cancers, mutational neoantigens can be predicted computationally to elicit strong immune responses by CD8 +cytotoxic T cells as major mediators of anticancer immune response. Neoantigens are potentially more robust immunogens and have revived interest in cancer vaccines. Cancers with deficiency in DNA mismatch repair have an exceptionally high mutational burden, including predictable neoantigens. Lynch syndrome is the most common inherited cancer syndrome and is caused by DNA mismatch repair gene mutations. Insertion and deletion mutations in coding microsatellites that occur during DNA replication include tumorigenesis drivers. The induced shift of protein reading frame generates neoantigens that are foreign to the immune system. Mismatch repair-deficient cancers and Lynch syndrome represent a paradigm population for the development of a preventive cancer vaccine, as the mutations induced by mismatch repair deficiency are predictable, resulting in a defined set of frameshift peptide neoantigens. Furthermore, Lynch syndrome mutation carriers constitute an identifiable high-risk population. We discuss the pathogenesis of DNA mismatch repair deficient cancers, in both Lynch syndrome and sporadic microsatellite-unstable cancers. We review evidence for pre-existing immune surveillance, the three mechanisms of immune evasion that occur in cancers and assess the implications of a preventive frameshift peptide neoantigen-based vaccine. We consider both preclinical and clinical experience to date. We discuss the feasibility of a cancer preventive vaccine for Lynch syndrome carriers and review current antigen selection and delivery strategies. Finally, we propose RNA vaccines as having robust potential for immunoprevention of Lynch syndrome cancers.

Indexed as

Cancer VaccinesColorectal Neoplasms, Hereditary NonpolyposisBrain NeoplasmsColorectal NeoplasmsDNA Mismatch RepairHumansImmunotherapyNeoplastic Syndromes, HereditaryCancer VaccinesCD8-Positive T-LymphocytesGenetic MarkersImmunogenicity, Vaccine

Identifiers

PMID35732349
PMCPMC9226910
OpenAlexW4283276048

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.