Evidence map›Paper›PMID 37478804›Full record

ReviewMolecular aspects of medicine2023

Advances in vaccine development for cancer prevention and treatment in Lynch Syndrome.

Ana M Bolivar, Fahriye Duzagac, Krishna M Sinha, Eduardo Vilar

Registry-linked trialOpen access · greenAbstract readReview
In one paragraph

Review in Molecular aspects of medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07510308 (A Clinical Trial Evaluating the Safety, Tolerability, and Preliminary Antitumor Activity of MSH2-/- Tumor Cell Vaccines in Patients With Advanced pMMR Colorectal Cancer.), which is not on this map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed
4.8field-weighted citation impact, top 5% 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.

NCT07510308 phase1recruitingnot on this mapstarted 2026, after this paper: background citation

A Clinical Trial Evaluating the Safety, Tolerability, and Preliminary Antitumor Activity of MSH2-/- Tumor Cell Vaccines in Patients With Advanced pMMR Colorectal Cancer.

TypeinterventionalSponsorWest China HospitalRan2026 to 2027Enrolled9ConditionspMMR/MSS Advanced Colorectal CancerArmsLow Dose MSH2-/- tumor cell vaccine, Medium Dose MSH2-/- tumor cell vaccine, High dose MSH2-/- tumor cell vaccine
3 · Its place in the literature

Who cites it

12 citing papers in PubMed, 19 citations in OpenAlex.

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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

4 authors at 1 institution in 1 country.

Ana M BolivarDepartment of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Fahriye DuzagacDepartment of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Krishna M SinhaDepartment of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Eduardo VilarDepartment of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Clinical Cancer Genetics Program, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. Electronic address: EVilar@mdanderson.org.
The University of Texas MD Anderson Cancer Center · US

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI DIANE BODURKA · 1985 to 2026
$290.8M
Project 3: Inhibiting Oxidative Phosphorylation in Pancreatic CancerP50CA221707 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI KOPETZ, SCOTT · 2019 to 2023
$11.0M
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
Cancer Immune-Interception for Lynch SyndromeR01CA257375 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI LIPKIN, STEVEN M, VILAR SANCHEZ, EDUARDO · 2021 to 2025
$3.3M
Cancer Immune-Interception in a Spontaneous Non-Human Primate Model of Lynch SyndromeR01CA260761 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI STANTON BRADLEY GRAY, Eduardo Vilar Sanchez · 2022 to 2026
$3.3M
Translational Genomics and Precision Medicine in Cancer Training ProgramT32CA217789 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Subrata Sen · 2018 to 2026
$2.2M
NCI NIH HHS P30 CA016672NCI NIH HHS P50 CA221707NCI NIH HHS R01 CA257375NCI NIH HHS R01 CA260761NCI NIH HHS T32 CA217789NCI NIH HHS U01 CA233056
6 · The paper itself

Abstract

Lynch Syndrome (LS) is one of the most common hereditary cancer syndromes, and is caused by mutations in one of the four DNA mismatch repair (MMR) genes, namely MLH1, MSH2, MSH6 and PMS2. Tumors developed by LS carriers display high levels of microsatellite instability, which leads to the accumulation of large numbers of mutations, among which frameshift insertion/deletions (indels) within microsatellite (MS) loci are the most common. As a result, MMR-deficient (MMRd) cells generate increased rates of tumor-specific neoantigens (neoAgs) that can be recognized by the immune system to activate cancer cell killing. In this context, LS is an ideal disease to leverage immune-interception strategies. Therefore, the identification of these neoAgs is an ongoing effort for the development of LS cancer preventive vaccines. In this review, we summarize the computational methods used for in silico neoAg prediction, including their challenges, and the experimental techniques used for in vitro validation of their immunogenicity. In addition, we outline results from past and on-going vaccine clinical trials and highlight avenues for improvement and future directions.

Indexed as

Colorectal Neoplasms, Hereditary NonpolyposisDNA-Binding ProteinsHumansMismatch Repair Endonuclease PMS2MutL Protein Homolog 1Vaccine DevelopmentDNA-Binding ProteinsMismatch Repair Endonuclease PMS2MutL Protein Homolog 1Cancer vaccinesColorectal cancerImmune preventionLynch SyndromeMMR deficiencyNeoantigens

Identifiers

PMID37478804
PMCPMC10528439
OpenAlexW4384993390

What OpenQuestion holds

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Registered trials

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.