Evidence map›Paper›PMID 35115362›Full record

ArticleJournal for immunotherapy of cancer2022

Germline biomarkers predict toxicity to anti-PD1/PDL1 checkpoint therapy.

Joanne Weidhaas, Nicholas Marco, Aaron W Scheffler, Anusha Kalbasi, Kirk Wilenius, Emily Rietdorf, Jaya Gill, Mara Heilig, Caroline Desler, Robert K Chin and 9 more

Open access · goldAbstract read
In one paragraph

Article 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 16 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 1 pooled it
2.4field-weighted citation impact, top 9% 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

16 citing papers in PubMed, 1 synthesis or guideline pooled it, 24 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

19 authors at 4 institutions in 3 countries.

Joanne WeidhaasDepartment of Radiation Oncology, University of California Los Angeles, Los Angeles, California, USA JWeidhaas@mednet.ucla.edu.ORCID 0000-0002-5096-3281
Nicholas MarcoDepartment of Biostatistics, UCLA, Los Angeles, California, USA.
Aaron W SchefflerDepartment of Biostatistics, UCLA, Los Angeles, California, USA.
Anusha KalbasiDepartment of Biostatistics, UCLA, Los Angeles, California, USA.ORCID 0000-0001-8692-1457
Kirk WileniusProstate Oncology Specialists, Marina Del Rey, California, USA.
Emily RietdorfDepartment of Radiation Oncology, University of California Los Angeles, Los Angeles, California, USA.
Jaya GillPacific Neuroscience Institute and Saint John's Cancer Institute, Santa Monica, California, USA.
Mara HeiligDepartment of Radiation Oncology, University of California Los Angeles, Los Angeles, California, USA.
Caroline DeslerDepartment of Radiation Oncology, University of California Los Angeles, Los Angeles, California, USA.
Robert K ChinDepartment of Radiation Oncology, University of California Los Angeles, Los Angeles, California, USA.
Tania KaprealianDepartment of Radiation Oncology, University of California Los Angeles, Los Angeles, California, USA.
Susan McCloskeyDepartment of Radiation Oncology, University of California Los Angeles, Los Angeles, California, USA.
Ann RaldowDepartment of Radiation Oncology, University of California Los Angeles, Los Angeles, California, USA.
Naga P RajaAppalachian Regional Healthcare, Hazard, Kentucky, USA.
Santosh KesariPacific Neuroscience Institute and Saint John's Cancer Institute, Santa Monica, California, USA.
Jose CarrilloPacific Neuroscience Institute and Saint John's Cancer Institute, Santa Monica, California, USA.
Alexandra DrakakiDepartment of Urology, Medical Oncology, University of California Los Angeles, Los Angeles, California, USA.
Mark ScholzProstate Oncology Specialists, Marina Del Rey, California, USA.
Donatello TelescaDepartment of Biostatistics, UCLA, Los Angeles, California, USA.
University of California, Los Angeles · USCancer Institute (WIA) · INOncology Specialists · USAppalachian Regional Healthcare · US

Funding

Women's CancersP30CA016042 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI Samuel Wheeler French · 1985 to 2026
$134.5M
UCLA SPORE in Brain CancerP50CA211015 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI David A. Nathanson · 2017 to 2026
$25.2M
Germ-line miRNA binding site variants as biomarkers of toxicity and response to checkpoint inhibitionR01CA238998 · NCI · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI WEIDHAAS, JOANNE B · 2019 to 2023
$1.8M
NCI NIH HHS P30 CA016042NCI NIH HHS P50 CA211015NCI NIH HHS R01 CA238998
6 · The paper itself

Abstract

backgroundThere is great interest in finding ways to identify patients who will develop toxicity to cancer therapies. This has become especially pressing in the era of immune therapy, where toxicity can be long-lasting and life-altering, and primarily comes in the form of immune-related adverse effects (irAEs). Treatment with the first drugs in this class, anti-programmed death 1 (anti-PD1)/programmed death-ligand 1 (PDL1) checkpoint therapies, results in grade 2 or higher irAEs in up to 25%-30% of patients, which occur most commonly within the first 6 months of treatment and can include arthralgias, rash, pruritus, pneumonitis, diarrhea and/or colitis, hepatitis, and endocrinopathies. We tested the hypothesis that germline microRNA pathway functional variants, known to predict altered systemic stress responses to cancer therapies, would predict irAEs in patients across cancer types.

methodsMicroRNA pathway variants were evaluated for an association with grade 2 or higher toxicity using four classifiers on 62 patients with melanoma, and then the panel's performance was validated on 99 patients with other cancer types. Trained classifiers included classification trees, LASSO-regularized logistic regression, boosted trees, and random forests. Final performance measures were reported on the training set using leave-one-out cross validation and validated on held-out samples. The predicted probability of toxicity was evaluated for its association, if any, with response categories to anti-PD1/PDL1 therapy in the melanoma cohort.

resultsA biomarker panel was identified that predicts toxicity with 80% accuracy (F1=0.76, area under the curve (AUC)=0.82) in the melanoma training cohort and 77.6% accuracy (F1=0.621, AUC=0.778) in the pan-cancer validation cohort. In the melanoma cohort, the predictive probability of toxicity was not associated with response categories to anti-PD1/PDL1 therapy (p=0.70). In the same cohort, the most significant biomarker of toxicity in

conclusionsA germline microRNA-based biomarker signature predicts grade 2 and higher irAEs to anti-PD1/PDL1 therapy, regardless of tumor type, in a pan-cancer manner. These findings represent an important step toward personalizing checkpoint therapy, the use of which is growing rapidly.

Indexed as

AgedB7-H1 AntigenFemaleGerm-Line MutationHumansImmunotherapyMaleB7-H1 Antigenautoimmunitygenetic markers

Identifiers

PMID35115362
PMCPMC8804679
OpenAlexW4220950491

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.