Evidence map›Paper›PMID 41840398›Full record

ArticleJournal of translational medicine2026

Optimal conditions for quantification of IRF4 mRNA and protein as a correlative biomarker in clinical cancer studies.

Joshua D Hartman, Silvia Vicenzi, Alexander A Tong, Lara C Avsharian, Ashni A Vora, Caitlin Costello, Ida Deichaite, Leslie A Crews

Abstract read
In one paragraph

Article in Journal of translational medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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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

8 authors.

Joshua D HartmanDivision of Regenerative Medicine, Department of Medicine; University of California San Diego, La Jolla, CA, 92093, USA.ORCID 0000-0002-0664-5630
Silvia VicenziDivision of Regenerative Medicine, Department of Medicine; University of California San Diego, La Jolla, CA, 92093, USA.
Alexander A TongDivision of Regenerative Medicine, Department of Medicine; University of California San Diego, La Jolla, CA, 92093, USA.
Lara C AvsharianDivision of Regenerative Medicine, Department of Medicine; University of California San Diego, La Jolla, CA, 92093, USA.
Ashni A VoraDivision of Regenerative Medicine, Department of Medicine; University of California San Diego, La Jolla, CA, 92093, USA.
Caitlin CostelloMoores Cancer Center, University of California San Diego, La Jolla, CA, 92093, USA.
Ida DeichaiteMoores Cancer Center, University of California San Diego, La Jolla, CA, 92093, USA.
Leslie A CrewsDivision of Regenerative Medicine, Department of Medicine; University of California San Diego, La Jolla, CA, 92093, USA. lcrews@ucsd.edu.ORCID 0000-0003-0704-0067

Funding

VIRAL MALIGNANCYP30CA023100 · NCI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI DIANE M SIMEONE · 1985 to 2026
$124.9M
Core transcriptional regulators of malignant stem cell generation in multiple myelomaR37CA252040 · NCI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Leslie A Crews · 2021 to 2026
$2.3M
NCI NIH HHS P30 CA023100NCI NIH HHS R37 CA252040
6 · The paper itself

Abstract

backgroundThe transcription factor interferon-regulatory factor-4 (IRF4) has recently been highlighted as a valuable biomarker due to its common dysregulation and association with poor prognoses in hematological malignancies such as multiple myeloma (MM). With several clinical programs for the inhibition of IRF4 currently in development, determination of the optimal sample collection conditions and quantification methods will facilitate optimal selection of patients for these treatments, along with enabling robust monitoring of their molecular responses to IRF4 inhibitory agents over time.

methodsUsing peripheral blood samples from healthy donors, we evaluated IRF4 mRNA and protein stability across a range of pre-analytical conditions including blood collection tube type (comparing EDTA, Paxgene ccfDNA, and Na Citrate), sample processing interval (24 to 48 hours after sample collection), and cell population isolated (total mononuclear cells, CD3+ T lymphocytes, CD14+ monocytes, and CD19+ B lymphocytes). We sought to further determine the extent to which post-processing variables such as cell yield, RNA yield, and housekeeping gene (ACTB versus HSPA5 and ATF4) selection may influence measurements of IRF4 mRNA and protein abundance. RNA and protein quantification endpoints included qRT-PCR and intranuclear flow cytometric analyses, respectively, to characterize the cell surface and intracellular molecular signatures.

resultsIn qRT-PCR biomarker studies, we found that human IRF4 expression was detectable in all cell fractions (PBMCs, CD19+ B cells and CD3+ T cells) evaluated and tube types tested (Na Citrate, EDTA, Paxgene ccfDNA). However, transcript stability of hIRF4 and the well-established reference gene β-actin (ACTB), as inferred from raw quantification cycle (Cq) values, varied substantially across tube types and between processing delay time points. mRNA levels of IRF4 along with an alternate, MM-optimized, reference gene, HSPA5, were determined to exhibit optimal stability in samples collected in Na Citrate preservative tubes. This tube type also offered the highest stability of immune cell surface antigens across 24–48-hour processing delays. Intranuclear IRF4 protein levels were remarkably stable in all cell populations tested across all tube types, with the highest relative expression in CD14+ and CD19+ fractions, and lowest in CD3+ fractions, in this cohort of healthy donors.

conclusionsOverall, Na Citrate tubes maintained the stability of IRF4 mRNA and protein expression even after sample processing intervals of up to 48 hours post-collection. Furthermore, IRF4 protein appears to be slightly more stable than mRNA after variable processing delays, but both analytes are expected to be detectable and relatively stable in clinical samples, thus enabling reliable analysis of IRF4 as a molecular biomarker in clinical samples collected from multiple sites and shipped to a central laboratory.

Indexed as

Biomarkers, TumorInterferon Regulatory FactorsHumansInterferon Regulatory Factor-4Protein StabilityRNA, MessengerBiomarkers, TumorInterferon Regulatory Factor-4Interferon Regulatory FactorsRNA, MessengerIRF4Molecular biomarkersMyelomaPeripheral bloodProcessing variables

Identifiers

PMID41840398
PMCPMC13104480

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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.