Evidence map›Paper›PMID 42735455›Full record

ArticleESMO open2026

Tumor genomic landscape of older patients with metastatic breast cancer

H Gupta, K D Brantley, T Grinda, R A Freedman, A Kodali, G J Kirkner, M E Hughes, A Higgins, A B Newman, S Avdulla and 8 more

Abstract read
In one paragraph

Article in ESMO open, 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

18 authors.

H GuptaDepartment of Medicine, Albert Einstein College of Medicine, Bronx, USA; Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, USA; Breast Oncology Program, Dana-Farber Brigham Cancer Center, Boston, USA; Broad Institute of Harvard and MIT, Cambridge, USA.
K D BrantleyDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, USA; Breast Oncology Program, Dana-Farber Brigham Cancer Center, Boston, USA; Department of Medicine, Harvard Medical School, Boston, USA. Electronic address: Kristen_brantley@dfci.harvard.edu.
T GrindaDepartment of Medical Oncology, Gustave Roussy, Villejuif, France.
R A FreedmanDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, USA; Breast Oncology Program, Dana-Farber Brigham Cancer Center, Boston, USA; Department of Medicine, Harvard Medical School, Boston, USA.
A KodaliDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, USA; Breast Oncology Program, Dana-Farber Brigham Cancer Center, Boston, USA.
G J KirknerDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, USA; Breast Oncology Program, Dana-Farber Brigham Cancer Center, Boston, USA.
M E HughesDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, USA; Breast Oncology Program, Dana-Farber Brigham Cancer Center, Boston, USA; Yale Cancer Center, New Haven, USA.
A HigginsDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, USA; Department of Medicine, Brigham and Women's Hospital, Boston, USA.
A B NewmanDepartment of Medicine, Brigham and Women's Hospital, Boston, USA.
S AvdullaDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, USA; Breast Oncology Program, Dana-Farber Brigham Cancer Center, Boston, USA.
J FilesDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, USA; Breast Oncology Program, Dana-Farber Brigham Cancer Center, Boston, USA.
G SuggsDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, USA; Breast Oncology Program, Dana-Farber Brigham Cancer Center, Boston, USA.
S M TolaneyDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, USA; Breast Oncology Program, Dana-Farber Brigham Cancer Center, Boston, USA; Department of Medicine, Harvard Medical School, Boston, USA.
D DillonBroad Institute of Harvard and MIT, Cambridge, USA; Department of Medicine, Harvard Medical School, Boston, USA; Department of Medicine, Brigham and Women's Hospital, Boston, USA.
L ShollDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, USA.
A C Garrido-CastroDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, USA; Breast Oncology Program, Dana-Farber Brigham Cancer Center, Boston, USA; Department of Medicine, Harvard Medical School, Boston, USA.
A D CherniackDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, USA; Broad Institute of Harvard and MIT, Cambridge, USA; Department of Medicine, Harvard Medical School, Boston, USA.
N U LinDepartment of Medical Oncology, Dana-Farber Cancer Institute, Boston, USA; Breast Oncology Program, Dana-Farber Brigham Cancer Center, Boston, USA; Department of Medicine, Harvard Medical School, Boston, USA.

Funding

Tissue and Pathology CoreP50CA168504 · NCI · DANA-FARBER CANCER INST · PI LEIF W ELLISEN, NANCY U LIN · 2013 to 2026
$30.1M
NCI NIH HHS P50 CA168504
6 · The paper itself

Abstract

backgroundMetastatic breast cancer (MBC) in older patients has distinct clinical and histologic characteristics. Elucidating the genomic basis of MBC helps identify potential therapeutic targets to improve outcomes for older patients with MBC. PATIENTS AND

methodsUsing a prospective database and targeted DNA sequencing (OncoPanel), we examined MBC's genomic landscape in older patients (age ≥70 years at MBC diagnosis) and compared findings with those in younger (aged <50 years) and middle-aged (aged 50-69 years) patients. After classifying single nucleotide variants (SNVs) and copy number variations (CNVs) as oncogenic (via OncoKB), the frequencies of SNVs and CNVs, tumor mutational burden (TMB), and oncogenic signaling pathways were compared by age group using Fisher's exact tests. We estimated the association between continuous age at MBC diagnosis and mutations via multivariate logistic regression analysis, adjusting for race, stage at initial diagnosis, subtype, histology, and sample tested (primary versus metastatic).

resultsOur study included 2379 patients [853 (35%) younger, 1311 (55%) middle-aged, and 215 (9%) older] who underwent OncoPanel testing between 2013 and 2020. The most frequent tumor alterations in older patients were SNVs in PIK3CA (44%), TP53 (33%), CDH1 (22%) and amplifications in CCND1 (18%). After adjustment, older age was associated with higher frequency of SNVs in CDH1 [odds ratio (OR) = 1.43, 95% confidence interval (CI) 1.21-1.68, q < 0.001], MAP3K1 [OR = 1.30, 95% CI 1.10-1.54, q = 0.008], and PIK3CA [OR = 1.21, 95% CI 1.11-1.31, q < 0.001] and fewer SNVs in TP53 [OR = 0.84, 95% CI 0.77-0.91, q < 0.001]. Patients in the older group were more likely to have tumors with ≥10 mutations/megabase than the youngest patients (26% versus 17%, P = 0.003).

conclusionsIn this large cohort of patients with MBC, the tumor genomic landscape differed between older and younger patients even after accounting for tumor subtype. Older patients were more likely to have high-TMB and PIK3CA-mutated tumors, highlighting the importance of genomic testing for treatment applications in this population.

Indexed as

agemetastatic breast cancerNGSolderPI3KCATMB

Identifiers

PMID42735455
PMCPMC13594736

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