Evidence map›Paper›PMID 42238456›Full record

ArticlemedRxiv : the preprint server for health sciences2026

CBFB mutations predict endocrine therapy benefit in estrogen receptor-positive breast cancer.

Adar Yaacov, Gal Passi, Roni Gillis, Daniela Katz, Albert Grinshpun

Abstract readPreprint
In one paragraph

Article in medRxiv : the preprint server for health sciences, 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

5 authors.

Adar YaacovHelmsley Cancer Center, Shaare Zedek Medical Center, Jerusalem, Israel.ORCID 0000-0002-6106-2307
Gal PassiThe Rachel and Selim Benin School of Computer Science and Engineering, The Hebrew University of Jerusalem, Jerusalem, Israel.
Roni GillisHelmsley Cancer Center, Shaare Zedek Medical Center, Jerusalem, Israel.
Daniela KatzHelmsley Cancer Center, Shaare Zedek Medical Center, Jerusalem, Israel.
Albert GrinshpunHelmsley Cancer Center, Shaare Zedek Medical Center, Jerusalem, Israel.

Funding

ChimeraX -- Next Generation Visualization and Analysis Software for Multiscale ModelingR01GM129325 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI FERRIN, THOMAS E · 2018 to 2025
$5.2M
NIGMS NIH HHS R01 GM129325
6 · The paper itself

Abstract

Purpose: Beyond estrogen receptor (ER) positivity, no genomic biomarker reliably identifies ER+ breast cancer patients who derive differential benefit from endocrine therapy (ET). We performed an unbiased genomic screen to discover genes predicting ET response and characterized the top candidate across clinical settings, treatment modalities, and an independent validation cohort. Experimental Design: We screened 240 genes in 1,197 metastatic ET-treated patients from the MSK-CHORD clinical genomics database using Cox proportional hazards regression with false discovery rate (FDR) correction. The top candidate, core-binding factor subunit beta (CBFB), was characterized across four cohorts defined by disease setting (metastatic/adjuvant) and treatment (ET/chemotherapy), with multivariable adjustment, gene-by-treatment interaction testing, left-truncation sensitivity analysis for guarantee-time bias, and external validation in METABRIC (N = 1,499 ER+). Results: CBFB mutations (prevalence, ~5%) were the only gene associated with improved time to progression (TTP). In metastatic ET patients, CBFB-mutated tumors (n = 80) demonstrated significantly longer TTP (hazard ratio [HR], 0.44; 95% CI, 0.29-0.67; P = .0002, FDR q = .010) with no chemotherapy benefit (HR, 1.16; P = .65). The gene-by-treatment interaction was significant (HR, 0.37; P = .009). Effects were robust to multivariable adjustment (HR, 0.46-0.50), independent of histology, and preserved under left-truncated Cox regression (HR, 0.38). In the adjuvant setting, CBFB mutations predicted improved recurrence-free survival (HR, 0.52; 95% CI, 0.31-0.85; P = .010), with no effect under chemotherapy. In METABRIC, CBFB mutations predicted improved ER+ overall survival (HR, 0.52; P = 9.3 × 10 Conclusions: CBFB mutations identify ~5% of ER+ breast cancers with exceptional ET benefit. As CBFB is included on all major cancer gene panels, this biomarker requires no additional testing infrastructure for clinical implementation.

Indexed as

breast cancerCBFBendocrine therapyMETABRICMSK-CHORDpredictive biomarker

Identifiers

PMID42238456
PMCPMC13228653

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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.