Evidence map›Paper›PMID 39079791›Full record

ReviewHematology/oncology clinics of North America2024

Advances in Vaccines for Melanoma.

Can Cui, Patrick A Ott, Catherine J Wu

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Hematology/oncology clinics of North America, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–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

10 citing papers in PubMed.

  1. Review
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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

3 authors.

Can CuiDepartment of Medicine, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
Patrick A OttHarvard Medical School, Boston, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
Catherine J WuHarvard Medical School, Boston, MA, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA; Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA. Electronic address: catherine_wu@dfci.harvard.edu.

Funding

Personal tumor neoantigens for immunity against chronic lymphocytic leukemiaR01CA155010 · NCI · DANA-FARBER CANCER INST · PI Catherine Ju-Ying Wu · 2011 to 2026
$9.6M
Dissecting neoepitope-specific clonal T cell populations in advanced melanoma patients vaccinated with personal neoantigen peptides partnered with local and systemic immune checkpoint InhibitionR01CA229261 · NCI · DANA-FARBER CANCER INST · PI Patrick Alexander Ott · 2018 to 2026
$3.8M
NCI NIH HHS R01 CA155010NCI NIH HHS R01 CA229261
6 · The paper itself

Abstract

Personalized neoantigen vaccines have achieved major advancements in recent years, with studies in melanoma leading progress in the field. Early clinical trials have demonstrated their feasibility, safety, immunogenicity, and potential efficacy. Advances in sequencing technologies and neoantigen prediction algorithms have substantively improved the identification and prioritization of neoantigens. Innovative delivery platforms now support the rapid and flexible production of vaccines. Several ongoing efforts in the field are aimed at improving the integration of large datasets, refining the training of prediction models, and ensuring the functional validation of vaccine immunogenicity.

Indexed as

Antigens, NeoplasmCancer VaccinesMelanomaHumansImmunotherapyPrecision MedicineAntigens, NeoplasmCancer VaccinesImmunotherapyMelanomaNeoantigenPersonalized cancer vaccine

Identifiers

PMID39079791
PMCPMC11524149

What OpenQuestion holds

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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.