ArticleThe Journal of molecular diagnostics : JMD2011
Performance and clinical evaluation of the 92-gene real-time PCR assay for tumor classification.
Article in The Journal of molecular diagnostics : JMD, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 46 papers, 5 of them syntheses that pooled it.
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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.
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Who cites it
46 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- SEOM-GECOD clinical guideline for cancer of unknown primary (update 2025).Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Guideline
- SEOM-GECOD clinical guideline for unknown primary cancer (2021).Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2022Guideline
- SEOM-GETTHI clinical guideline for the practical management of molecular platforms (2021).Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2022Guideline
- Genomic and epigenomic biomarkers in colorectal cancer: From diagnosis to therapy.Advances in cancer research · 2021Pooled it
- SEOM clinical guideline on unknown primary cancer (2017).Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2018Guideline
- Gene expression profiling identifies responsive patients with cancer of unknown primary treated with carboplatin, paclitaxel, and everolimus: NCCTG N0871 (alliance).Annals of oncology : official journal of the European Society for Medical Oncology · 2016Trial
- Cancer of unknown primary: the evolution of tissue of origin identification in the artificial intelligence era.Biomarker research · 2026Review
- Molecular-Guided Precision Oncology in Cancer of Unknown Primary: A State-of-the-Art Perspective.Journal of personalized medicine · 2026Review
- Rethinking cancer of unknown primary: from diagnostic challenge to targeted treatment.Nature reviews. Clinical oncology · 2025Review
- GPSai: A Clinically Validated AI Tool for Tissue of Origin Prediction during Routine Tumor Profiling.Cancer research communications · 2025Article
- Clinical characteristics and survival analysis of cancer of unknown primary.Oncology letters · 2025Article
- Highly Multiplexed Tissue Imaging in Precision Oncology and Translational Cancer Research.Cancer discovery · 2024Review
- Image-based deep learning model using DNA methylation data predicts the origin of cancer of unknown primary.Neoplasia (New York, N.Y.) · 2024Article
- Advances in Cancer Research: Current and Future Diagnostic and Therapeutic Strategies.Biosensors · 2024Review
- A cross-cohort computational framework to trace tumor tissue-of-origin based on RNA sequencing.Scientific reports · 2023Article
- DNA methylation profiling to determine the primary sites of metastatic cancers using formalin-fixed paraffin-embedded tissues.Nature communications · 2023Article
- Validation of a Transcriptome-Based Assay for Classifying Cancers of Unknown Primary Origin.Molecular diagnosis & therapy · 2023Article
- Cancer of unknown primary site in the mandibular region: A case report.Oncology letters · 2023Article
- Deciphering the origin and therapeutic targets of cancer of unknown primary: a case report that illustrates the power of integrative whole-exome and transcriptome sequencing analysis.Frontiers in oncology · 2023Article
- A comparison of DNA sequencing and gene expression profiling to assist tissue of origin diagnosis in cancer of unknown primary.The Journal of pathology · 2023Article
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Authors and funding
6 authors.
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Abstract
Accurate determination of cancer origin is necessary to guide optimal treatment but remains a diagnostic challenge. Gene expression profiling technologies have aided the classification of tumors and, therefore, could be applied in conjunction with clinicopathologic correlates to improve accuracy. We report an expanded version of the previously described 92-gene assay to classify 30 main tumor types and 54 histological subtypes, with coverage of ≥95% of all solid tumors based on incidence. Increased tissue coverage was achieved through expansion of a reference tumor database containing 2,206 specimens, with a median of 62 samples per main tumor type. The 92-gene classification algorithm demonstrated sensitivities of 87% and 85% for 30 main types and 54 histological subtypes, respectively, in leave-one-out cross validation, and 83% in a test set of 187 tumors representing 28 of the 30 main cancer types. These findings provide further support that broad and diverse tumor classification can be performed using a relatively compact gene set. An additional 300 consecutive cases submitted for clinical testing were profiled to characterize clinical utility in a real-world setting: the 92-gene assay confirmed 78% of samples having a single suspected primary tumor and provided a single molecular prediction in 74% of cases with two or more differential diagnoses. Further development of the 92-gene RT-PCR assay has resulted in a significant expansion in reportable tumor types and histological features with strong performance characteristics and supports the use of molecular classification as an objective standardized adjunct to current methods.
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