Evidence map›Paper›PMID 42774612›Full record

ReviewFrontiers in immunology2026

Emerging biomarkers of immune checkpoint inhibitor toxicity in triple-negative breast cancer: a mini-review.

Erin McGillivray, Savannah Kane, Armina Saadatkhah, Kay T Yeung

Abstract readReview
In one paragraph

Review in Frontiers in immunology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Erin McGillivrayDepartment of Internal Medicine, Moores Cancer Center, University of California, San Diego, La Jolla, CA, United States.
Savannah KaneUniversity of California, San Diego, School of Medicine, La Jolla, CA, United States.
Armina SaadatkhahUniversity of California, San Diego, School of Medicine, La Jolla, CA, United States.
Kay T YeungDepartment of Internal Medicine, Moores Cancer Center, University of California, San Diego, La Jolla, CA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Immune checkpoint inhibitors (ICI) have revolutionized the treatment of TNBC, leading to durable responses and improved survival. With the adoption of immunotherapy into high-risk early-stage and selected metastatic triple-negative breast cancer (TNBC), clinicians' ability to recognize and treat immune-related adverse events has become increasingly important. There is no prospectively validated or FDA-approved predictive biomarker of toxicity; however, candidate biomarkers involving circulating blood counts, immune-cell phenotypes, cytokines, transcriptomics, immune age, germline genetics, human leukocyte antigen genotypes, autoantibodies, and the gut microbiome have been described, with many more currently under investigation. Most evidence remains exploratory and is derived from non-TNBC populations. Going forward, incorporating these investigational tools within prospective TNBC trials and validating them in real-world, multicenter TNBC cohorts are critical to ensure these predictive biomarkers translate into clinically useful tools for risk-adapted monitoring. This mini-review highlights the current landscape of predictive biomarkers of ICI toxicity, with a focus on TNBC.

Indexed as

Biomarkers, TumorImmune Checkpoint InhibitorsTriple Negative Breast NeoplasmsFemaleHumansBiomarkers, TumorImmune Checkpoint InhibitorsbiomarkersICI-related toxicityimmune checkpoint inhibitorsimmune-related adverse eventstriple-negative breast cancer

Identifiers

PMID42774612
PMCPMC13595102

What OpenQuestion holds

Textmetadata
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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.