Gene Expression Profiling to Identify the Histogenetic Origin of Metastatic Adenocarcinomas of Unknown Primary

Horlings, Hugo M.; Laar, Ryan K. van; Kerst, Jan-Martijn; Helgason, Helgi H.; Wesseling, Jelle; Hoeven, J.J.M. van der; Warmoes, Marc O.; Floore, Arno; Witteveen, Anke; Lahti-Domenici, Jaana; Glas, Annuska M.; Veer, Laura J. van’t; Jong, Daphne de

doi:10.1200/jco.2007.14.6969

Cited by 173 publications

(130 citation statements)

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“…38,39 Recent work suggested the use of large panels of mRNA features for identification of tumor tissue of origin. 9,10,14,15 Our test uses a significantly smaller number of tissue-specific microRNA biomarkers, set forth in a straightforward classification scheme, which provides specific tissue origins in a majority of cases. Cases with consensus classifications are accurately identified with a higher confidence.…”

Section: Discussionmentioning

confidence: 99%

“…[4][5][6][7] The application of molecular diagnostics to the identification of tumor tissue of origin has received substantial recent attention. [8][9][10][11][12] Most studies of molecular diagnosis of tissue of origin used messenger RNA (mRNA) profiling of tumor samples. 8,[13][14][15] MicroRNAs, 21-23-nucleotide-long functional RNAs, have an important function in tissue differentiation 16,17 and tumorigenesis, 18,19 and have highly tissue-specific expression patterns.…”

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confidence: 99%

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Validation of a microRNA-based qRT-PCR test for accurate identification of tumor tissue origin

et al. 2010

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Identification of the tissue of origin of a tumor is vital to its management. Previous studies showed tissuespecific expression patterns of microRNA and suggested that microRNA profiling would be useful in addressing this diagnostic challenge. MicroRNAs are well preserved in formalin-fixed, paraffin-embedded (FFPE) samples, further supporting this approach. To develop a standardized assay for identification of the tissue origin of FFPE tumor samples, we used microarray data from 504 tumor samples to select a shortlist of 104 microRNA biomarker candidates. These 104 microRNAs were profiled by proprietary quantitative reverse transcriptase polymerase chain reaction (qRT-PCR) on 356 FFPE tumor samples. A total of 48 microRNAs were chosen from this list of candidates and used to train a classifier. We developed a clinical test for the identification of the tumor tissue of origin based on a standardized protocol and defined the classification criteria. The test measures expression levels of 48 microRNAs by qRT-PCR, and predicts the tissue of origin among 25 possible classes, corresponding to 17 distinct tissues and organs. The biologically motivated classifier combines the predictions generated by a binary decision tree and K-nearest neighbors (KNN). The classifier was validated on an independent, blinded set of 204 FFPE tumor samples, including nearly 100 metastatic tumor samples. The test predictions correctly identified the reference diagnosis in 85% of the cases. In 66% of the cases the two algorithm predictions (tree and KNN) agreed on a single-tissue origin, which was identical to the reference diagnosis in 90% of cases. Thus, a qRT-PCR test based on the expression profile of 48 tissue-specific microRNAs allows accurate identification of the tumor tissue of origin.

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Section: Discussionmentioning

confidence: 99%

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confidence: 99%

Validation of a microRNA-based qRT-PCR test for accurate identification of tumor tissue origin

et al. 2010

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“…46 Indeed, pancreatic cancer is the most difficult type of carcinoma of unknown primary to identify using our method as well as all published methods. 8,24,[47][48][49][50] Additional research is needed to successfully translate the 154-gene signature from gene expression microarray to real-time reverse transcription polymerase chain reaction assays, thus allowing broader access and utilization in the clinical setting. In routine practice, most diagnostic materials are formalin-fixed and paraffin-embedded; thus, it will be highly interesting to assess the usefulness of the 154-gene signature in formalin-fixed and paraffin-embedded samples.…”

Section: Discussionmentioning

confidence: 99%

“…7 Histological examination, particularly immunohistochemistry, is the cornerstone to identify the tumor of origin. However, even with the best experts and the most advanced technology, the primary site can be identified in only 20-30% of patients with cancer of unknown primary, 8 and the results can be subjective.…”

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confidence: 99%

Pan-cancer transcriptome analysis reveals a gene expression signature for the identification of tumor tissue origin

Xu¹,

Chen²,

et al. 2016

Modern Pathology

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Carcinoma of unknown primary, wherein metastatic disease is present without an identifiable primary site, accounts for~3-5% of all cancer diagnoses. Despite the development of multiple diagnostic workups, the success rate of primary site identification remains low. Determining the origin of tumor tissue is, thus, an important clinical application of molecular diagnostics. Previous studies have paved the way for gene expression-based tumor type classification. In this study, we have established a comprehensive database integrating microarray-and sequencing-based gene expression profiles of 16 674 tumor samples covering 22 common human tumor types. From this pan-cancer transcriptome database, we identified a 154-gene expression signature that discriminated the origin of tumor tissue with an overall leave-one-out cross-validation accuracy of 96.5%. The 154-gene expression signature was first validated on an independent test set consisting of 9626 primary tumors, of which 97.1% of cases were correctly classified. Furthermore, we tested the signature on a spectrum of diagnostically challenging tumors. An overall accuracy of 92% was achieved on the 1248 tumor specimens that were poorly differentiated, undifferentiated or from metastatic tumors. Thus, we have identified a 154-gene expression signature that can accurately classify a broad spectrum of tumor types. This gene panel may hold a promise to be a useful additional tool for the determination of the tumor origin.

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“…9,10 To date, several gene expression-based tests have demonstrated the potential value of this approach in identifying the primary site. 4,[11][12][13][14][15][16][17][18][19][20][21][22][23][24] One microarray-based test uses 2000-GEP to identify a tumour's primary site using formalin-fixed paraffin-embedded (FFPE) specimens (Tissue of Origin test, Response Genetics, Inc., Los Angeles, CA). 24 The test compares the RNA profile of a tumour FFPE specimen to established RNA profiles of 15 known tissues.…”

Section: Introductionmentioning

confidence: 99%

Cost-effectiveness of using a gene expression profiling test to aid in identifying the primary tumour in patients with cancer of unknown primary

et al. 2016

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We aimed to investigate the cost-effectiveness of a 2000-gene-expression profiling (GEP) test to help identify the primary tumor site when clinicopathological diagnostic evaluation was inconclusive in patients with cancer of unknown primary (CUP). We built a decision-analytic-model to project the lifetime clinical and economic consequences of different clinical management strategies for CUP. The model was parameterized using follow-up data from the Manitoba Cancer Registry, cost data from Manitoba Health administrative databases and secondary sources. The 2000-GEP-based strategy compared to current clinical practice resulted in an incremental cost-effectiveness ratio (ICER) of $44,151 per quality-adjusted life years (QALY) gained. The total annual-budget impact was $36.2 million per year. A value-of-information analysis revealed that the expected value of perfect information about the test's clinical impact was $4.2 million per year. The 2000-GEP test should be considered for adoption in CUP. Field evaluations of the test are associated with a large societal benefit.

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Gene Expression Profiling to Identify the Histogenetic Origin of Metastatic Adenocarcinomas of Unknown Primary

Cited by 173 publications

References 32 publications

Validation of a microRNA-based qRT-PCR test for accurate identification of tumor tissue origin

Validation of a microRNA-based qRT-PCR test for accurate identification of tumor tissue origin

Pan-cancer transcriptome analysis reveals a gene expression signature for the identification of tumor tissue origin

Cost-effectiveness of using a gene expression profiling test to aid in identifying the primary tumour in patients with cancer of unknown primary

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