Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

Machine learning-based tissue of origin classification for cancer of unknown primary diagnostics using genome-wide mutation features.

Nature communications - 11 Jul 2022

Nguyen Luan, Van Hoeck Arne, Cuppen Edwin

Abstract excerpt

Cancers of unknown primary (CUP) origin account for ∼3% of all cancer diagnoses, whereby the tumor tissue of origin (TOO) cannot be determined. Using a uniformly processed dataset encompassing 6756 whole-genome sequenced primary and metastatic tumors, we develop Cancer of Unknown Primary Location Resolver (CUPLR), a random forest TOO classifier that employs 511 features based on simple and complex somatic driver...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Cancer Diagnosis and Treatment
Share to Cancer Genomics and Diagnostics

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Share to Genome

Share to Machine Learning

Share to Mutation

Share to Neoplasms, Unknown Primary

Share to Tumors and Oncological Cases

Source

Open in PubMed Open full text

Identifiers

PMID: 35817764
DOI: 10.1038/s41467-022-31666-w
PMCID: PMC9273599

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Machine learning-based tissue of origin classification for cancer of unknown primary diagnostics using genome-wide mutation features.PMID 35817764Read ↗

Machine learning-based tissue of origin classification for cancer of unknown primary diagnostics using genome-wide mutation featuresSemantic proximity Read ↗

Machine learning-based tissue of origin classification for cancer of unknown primary diagnostics using genome-wide mutation featuresSemantic proximity Read ↗

Tumor-Origin.com: A Machine Learning Platform for Predicting Tumor Tissue of Origin from Somatic Mutation ProfilesSemantic proximity Read ↗

A machine learning framework to trace tumor tissue-of-origin of 13 types of cancer based on DNA somatic mutation.Semantic proximity Read ↗

Whole genome sequencing improves tissue of origin diagnosis and treatment options for cancer of unknown primarySemantic proximity Read ↗

Cancer of unknown primary.Semantic proximity Read ↗

Validation of a transcriptome-based assay for classifying cancers of unknown primary originSemantic proximity Read ↗

Whole genome sequencing improves tissue-of-origin diagnosis and treatment options for cancer of unknown primarySemantic proximity Read ↗

A comparison of DNA sequencing and gene expression profiling to assist tissue of origin diagnosis in cancer of unknown primarySemantic proximity Read ↗

Machine learning analysis using 77,044 genomic and transcriptomic profiles to accurately predict tumor typeSemantic proximity Read ↗

CUPiD: A cfDNA methylation-based tissue-of-origin classifier for Cancers of Unknown PrimarySemantic proximity Read ↗

Utilizing Electronic Health Records (EHR) and Tumor Panel Sequencing to Demystify Prognosis of Cancer of Unknown Primary (CUP) patientsSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.