Evidence map›Paper›PMID 29606147›Full record

ArticleJournal of translational medicine2018

Baseline antibody profiles predict toxicity in melanoma patients treated with immune checkpoint inhibitors.

Michael F Gowen, Keith M Giles, Danny Simpson, Jeremy Tchack, Hua Zhou, Una Moran, Zarmeena Dawood, Anna C Pavlick, Shaohui Hu, Melissa A Wilson and 4 more

Abstract read
In one paragraph

Article in Journal of translational medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 85 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
85citing papers in PubMed, 1 pooled it
–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

85 citing papers in PubMed, 1 synthesis or guideline pooled it.

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  18. The Current and Future of Biomarkers of Immune Related Adverse Events.Rheumatic diseases clinics of North America · 2024
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25 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

14 authors.

Michael F GowenThe Ronald O. Perelman Department of Dermatology, New York University School of Medicine, New York, NY, USA.
Keith M GilesThe Ronald O. Perelman Department of Dermatology, New York University School of Medicine, New York, NY, USA.
Danny SimpsonDivision of Epidemiology, New York University School of Medicine, New York, NY, USA.
Jeremy TchackThe Ronald O. Perelman Department of Dermatology, New York University School of Medicine, New York, NY, USA.
Hua ZhouApplied Bioinformatics Core, New York University School of Medicine, New York, NY, USA.
Una MoranThe Ronald O. Perelman Department of Dermatology, New York University School of Medicine, New York, NY, USA.
Zarmeena DawoodThe Ronald O. Perelman Department of Dermatology, New York University School of Medicine, New York, NY, USA.
Anna C PavlickDivision of Hematology & Oncology, Perlmutter Cancer Center, New York University School of Medicine, New York, NY, USA.
Shaohui HuCDI Laboratories, Baltimore, MD, USA.
Melissa A WilsonDivision of Hematology & Oncology, Perlmutter Cancer Center, New York University School of Medicine, New York, NY, USA.
Hua ZhongDepartment of Population Health, New York University School of Medicine, New York, NY, USA.
Michelle KrogsgaardDepartment of Pathology, New York University School of Medicine, 522 First Ave., Smilow Research Building 1311, New York, NY, 10016, USA. michelle.krogsgaard@nyumc.org.
Tomas KirchhoffDivision of Epidemiology, New York University School of Medicine, New York, NY, USA.
Iman OsmanThe Ronald O. Perelman Department of Dermatology, New York University School of Medicine, New York, NY, USA. iman.osman@nyumc.org.ORCID 0000-0002-1472-1971

Funding

Vaccine FacilityP30CA016087 · NCI · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI ANIRBAN MAITRA · 1985 to 2026
$83.1M
NCI NIH HHS P30 CA016087NYU Langone Medical Center P30CA016087
6 · The paper itself

Abstract

backgroundImmune checkpoint inhibitors (anti-CTLA-4, anti-PD-1, or the combination) enhance anti-tumor immune responses, yielding durable clinical benefit in several cancer types, including melanoma. However, a subset of patients experience immune-related adverse events (irAEs), which can be severe and result in treatment termination. To date, no biomarker exists that can predict development of irAEs.

methodsWe hypothesized that pre-treatment antibody profiles identify a subset of patients who possess a sub-clinical autoimmune phenotype that predisposes them to develop severe irAEs following immune system disinhibition. Using a HuProt human proteome array, we profiled baseline antibody levels in sera from melanoma patients treated with anti-CTLA-4, anti-PD-1, or the combination, and used support vector machine models to identify pre-treatment antibody signatures that predict irAE development.

resultsWe identified distinct pre-treatment serum antibody profiles associated with severe irAEs for each therapy group. Support vector machine classifier models identified antibody signatures that could effectively discriminate between toxicity groups with > 90% accuracy, sensitivity, and specificity. Pathway analyses revealed significant enrichment of antibody targets associated with immunity/autoimmunity, including TNFα signaling, toll-like receptor signaling and microRNA biogenesis.

conclusionsOur results provide the first evidence supporting a predisposition to develop severe irAEs upon immune system disinhibition, which requires further independent validation in a clinical trial setting.

Indexed as

AgedAntibodies, NeoplasmFemaleHumansImmunotherapyMaleMelanomaProteomicsReproducibility of ResultsAntibodies, NeoplasmAntibodiesBiomarkerImmunotherapyMelanomaToxicity

Identifiers

PMID29606147
PMCPMC5880088

What OpenQuestion holds

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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.