Evidence map›Paper›PMID 40802536›Full record

ArticleCancer2025

Mutational analysis of primary and advanced chordoma tissue using next-generation sequencing.

Josh Chan, Joseph K Kendal, Zhenfeng Duan, Al Ferreira, Alireza Samiei, Scott D Nelson, Arun Singh, Elizabeth L Lord, Brooke Crawford, Nicholas M Bernthal and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Review
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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

11 authors.

Josh ChanDepartment of Surgery, Section of Orthopaedic Surgery, University of Calgary, Calgary, Alberta, Canada.ORCID https://orcid.org/0009-0003-4336-3733
Joseph K KendalDepartment of Surgery, Section of Orthopaedic Surgery, University of Calgary, Calgary, Alberta, Canada.ORCID https://orcid.org/0000-0001-9440-2294
Zhenfeng DuanDepartment of Orthopedics, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida, USA.ORCID https://orcid.org/0000-0001-7276-3910
Al FerreiraDepartment of Orthopedics, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida, USA.
Alireza SamieiDepartment of Orthopaedic Surgery, University of California, Los Angeles, Los Angeles, California, USA.
Scott D NelsonDepartment of Orthopaedic Surgery, University of California, Los Angeles, Los Angeles, California, USA.
Arun SinghDepartment of Orthopaedic Surgery, University of California, Los Angeles, Los Angeles, California, USA.
Elizabeth L LordDepartment of Orthopaedic Surgery, University of California, Los Angeles, Los Angeles, California, USA.
Brooke CrawfordDepartment of Orthopedics, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida, USA.
Nicholas M BernthalDepartment of Orthopaedic Surgery, University of California, Los Angeles, Los Angeles, California, USA.
Francis J HornicekDepartment of Orthopedics, Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, Florida, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundChordomas are rare ectodermal bone malignancies derived from transformed notochordal remnants. Histologic variants include conventional (80%-90%), chondroid (5%-15%), and dedifferentiated (2%-8%). Because chordomas are relatively resistant to chemotherapy and radiotherapy, novel targeted agents are needed to expand treatment approaches and improve outcomes. This study analyzes the genomic landscape of chordoma and identifies potential pathogenic and druggable targets.

methodsEighty-six tumor samples derived from chordoma patients treated at Massachusetts General Hospital, University of California, Los Angeles, and the University of Miami were included. Tumor specimens were sent for comprehensive molecular profiling using next-generation sequencing. The most frequently mutated genes were identified and categorized by subtype, and microsatellite instability and programmed death ligand-1 (PD-L1) staining were assessed.

resultsHistologic subtypes included 70 conventional (81.4%), nine chondroid (10.5%), and seven dedifferentiated chordomas (8.1%). The most common mutations were cyclin-dependent kinase inhibitor 2A/B (CDKN2A/B) (28 of 86, 33%), low-density lipoprotein receptor-related protein 1B (10 of 86, 12%), polybromo-1 (9 of 86, 11%), and epidermal growth factor receptor (EGFR) (8 of 86, 9%). By subtype, CDKN2A/B mutation was most common in conventional chordoma (24 of 70, 34%), and chondroid chordoma (3 of 9, 33%). CDKN2A/B and EGFR mutations were most common in dedifferentiated chordoma (2/7, 29%). Microsatellite instability was not detected in seven of 69 (10.1%) samples. PD-L1 staining of tumor and immune cells was scarce, with scores <1 in 38 of 41 (92.7%) and 22 of 25 (88%) patients, respectively.

conclusionsThis study provides a robust, high-dimensional sequencing assessment from 86 chordoma tissue samples and a descriptive overview of the genomic landscape of this rare, difficult to treat malignancy. Future studies should include in vitro assessment of gain and loss of function of frequently altered pathways to validate these findings.

Indexed as

Bone NeoplasmsChordomaHigh-Throughput Nucleotide SequencingMutationAdolescentAdultAgedAged, 80 and overB7-H1 AntigenBiomarkers, TumorChildDNA Mutational AnalysisFemaleHumansMaleMicrosatellite InstabilityB7-H1 AntigenBiomarkers, TumorCD274 protein, humanCDKN2A/Bchordomamolecular profilingmutational analysisnext‐generation sequencingPD‐L1

Identifiers

PMID40802536
PMCPMC12348310

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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.