ArticleMolecular oncology2021
MicroRNA expression profiling with a droplet digital PCR assay enables molecular diagnosis and prognosis of cancers of unknown primary.
Article in Molecular oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.
- New techniques to identify the tissue of origin for cancer of unknown primary in the era of precision medicine: progress and challenges.Briefings in bioinformatics · 2024Pooled it
- Role of liquid biopsy in the multimodal assessment and treatment of esophageal cancer: a surgical perspective.Updates in surgery · 2026Article
- Cancer of unknown primary: the evolution of tissue of origin identification in the artificial intelligence era.Biomarker research · 2026Review
- Management and survival of patients with cancer of unknown primary discussed by a French national multidisciplinary tumour board: a retrospective analysis.The Lancet regional health. Europe · 2026Article
- Cancer of unknown primary genomic profiling from cell-free DNA provides insights into CUP biology and vulnerabilities.Frontiers in medicine · 2026Article
- MicroRNAs in neurodegenerative diseases: from molecular mechanisms to clinical biomarkers, detection methods and therapeutic strategies-advances and challenges.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2025Review
- Emerging biomarkers for early cancer detection and diagnosis: challenges, innovations, and clinical perspectives.European journal of medical research · 2025Review
- Advancements in Diagnostics and Therapeutics for Cancer of Unknown Primary in the Era of Precision Medicine.MedComm · 2025Review
- Review
- Progress in Precision Medicine for Head and Neck Cancer.Cancers · 2024Review
- Synergic activity of FGFR2 and MEK inhibitors in the treatment of FGFR2-amplified cancers of unknown primary.Molecular therapy : the journal of the American Society of Gene Therapy · 2024Article
- Deep Learning-Based Identification of Tissue of Origin for Carcinomas of Unknown Primary Using MicroRNA Expression: Algorithm Development and Validation.JMIR bioinformatics and biotechnology · 2024Article
- Advances in Cancer Research: Current and Future Diagnostic and Therapeutic Strategies.Biosensors · 2024Review
- A Systematic Review of Diagnostic and Prognostic Biomarkers for Head and Neck Cancer of Unknown Primary: An Unmet Clinical Need.Diagnostics (Basel, Switzerland) · 2023Review
- MicroRNA and Metabolic Profiling of a Primary Ovarian Neuroendocrine Carcinoma Pulmonary-Type Reveals a High Degree of Similarity with Small Cell Lung Cancer.Non-coding RNA · 2022Article
- Skin Cancer Research Goes Digital: Looking for Biomarkers within the Droplets.Journal of personalized medicine · 2022Review
- Machine learning-based tissue of origin classification for cancer of unknown primary diagnostics using genome-wide mutation features.Nature communications · 2022Article
- Small RNA Sequencing Identifies a Six-MicroRNA Signature Enabling Classification of Brain Metastases According to their Origin.Cancer genomics & proteomicsArticle
Corrections and comments
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Authors and funding
18 authors at 8 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metastasis is responsible for the majority of cancer-related deaths. Particularly, challenging is the management of metastatic cancer of unknown primary site (CUP), whose tissue of origin (TOO) remains undetermined even after extensive investigations and whose therapy is rather unspecific and poorly effective. Molecular approaches to identify the most probable TOO of CUPs can overcome some of these issues. In this study, we applied a predetermined set of 89 microRNAs (miRNAs) to infer the TOO of 53 metastatic cancers of unknown or uncertain origin. The miRNA expression was assessed with droplet digital PCR in 159 samples, including primary tumors from 17 tumor classes (reference set) and metastases of known and unknown origin (test set). We combined two different statistical models for class prediction to obtain the most probable TOOs: the nearest shrunken centroids approach of Prediction Analysis of Microarrays (PAMR) and the least absolute shrinkage and selection operator (LASSO) models. The molecular test was successful for all formalin-fixed paraffin-embedded samples and provided a TOO identification within 1 week from the biopsy procedure. The most frequently predicted origins were gastrointestinal, pancreas, breast, lung, and bile duct. The assay was applied also to multiple metastases from the same CUP, collected from different metastatic sites: The predictions showed a strong agreement, intrinsically validating our assay. The final CUPs' TOO prediction was compared with the clinicopathological hypothesis of primary site. Moreover, a panel of 13 miRNAs proved to have prognostic value and be associated with overall survival in CUP patients. Our study demonstrated that miRNA expression profiling in CUP samples could be employed as diagnostic and prognostic test. Our molecular analysis can be performed on request, concomitantly with standard diagnostic workup and in association with genetic profiling, to offer valuable indications about the possible primary site, thereby supporting treatment decisions.
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