Diagnostic Assay Based on hsa-miR-205 Expression Distinguishes Squamous From Nonsquamous Non–Small-Cell Lung Carcinoma

Lebanony, Danit; Benjamin, H.; Gilad, Shlomit; Ezagouri, Meital; Dov, Avital; Ashkenazi, Karin; Gefen, N. E.; Izraeli, Shai; Rechavi, Gideon; Pass, Harvey I.; Nonaka, Daisuke; Li, Junjie; Spector, Yael; Rosenfeld, Nitzan; Chajut, Ayelet; Cohen, Dalia; Aharonov, Ranit; Mansukhani, Mahesh

doi:10.1200/jco.2008.19.4134

Cited by 362 publications

(320 citation statements)

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“…27 A recently described diagnostic test for sub-classification of non-small cell lung carcinoma uses this same technology. 23 We previously showed the performance and reproducibility of this platform, as well as the correlation of data obtained to microRNA arrays. 23,24,26 This qRT-PCR platform was used to measure the 104 candidate microRNAs in a training set of 356 FFPE tumor samples (Table 1).…”

Section: Tissue Classification By Microrna Qrt-pcrmentioning

confidence: 95%

“…23 We previously showed the performance and reproducibility of this platform, as well as the correlation of data obtained to microRNA arrays. 23,24,26 This qRT-PCR platform was used to measure the 104 candidate microRNAs in a training set of 356 FFPE tumor samples (Table 1). We used a feature selection and classification approach that is based on biologic and pathologic assumptions, 26 and identifies expression patterns that are useful for classification by grouping tissues into meaningful subsets in the form of a binary decision tree (henceforth 'tree').…”

Section: Tissue Classification By Microrna Qrt-pcrmentioning

confidence: 95%

“…qRT-PCR was performed as described, 23,27 using probes for the 104 candidate microRNAs, of which five were tested with two different forward primers, and for U6 snoRNA.…”

Section: Qrt-pcrmentioning

confidence: 99%

“…The information from both microarray datasets was analyzed, comparing microRNA differential expression between different subgroups of tissues using the exploratory methodologies described in our earlier study, 26 and used to generate a shortlist of 104 candidate microRNA biomarkers that showed specific expression in subsets of tissues, as well as in subsets of histological types, such as hsa-miR-205, which was previously shown to be highly expressed in squamous cell carcinoma. 23 …”

Section: Concept Development and Microrna Selection Using Microarraysmentioning

confidence: 99%

“…[20][21][22] The unique expression profiles of microRNAs characteristic of each tissue and the malignancies arising in them can permit their accurate identification. [23][24][25][26] MicroRNAs are also stable in tissue, stored frozen or as formalinfixed, paraffin-embedded (FFPE) samples, and in serum. [27][28][29] In an earlier work, we showed that a biologically motivated classifier based on expression of a relatively small number of tissue-specific microRNAs allows tumor tissues of origin to be accurately identified.…”

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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: Tissue Classification By Microrna Qrt-pcrmentioning

confidence: 95%

Section: Tissue Classification By Microrna Qrt-pcrmentioning

confidence: 95%

“…qRT-PCR was performed as described, 23,27 using probes for the 104 candidate microRNAs, of which five were tested with two different forward primers, and for U6 snoRNA.…”

Section: Qrt-pcrmentioning

confidence: 99%

Section: Concept Development and Microrna Selection Using Microarraysmentioning

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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Micro RNAs in Cancer

Munker

Calin

2011

Encyclopedia of Life Sciences

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Initially considered an epiphenomenon, micro ribonucleic acids (also called miRNAs) and other small noncoding RNA molecules are now considered major players in cell biology. MiRNAs regulate gene expression through effects on translation, transcription and chromatin modification. Multiple miRNAs are dysregulated in human cancer and affect the proliferation and apoptosis, metastatic behaviour, invasiveness and phenotype of cancer cells. Virtually every cell type and cancer have a particular expression pattern of miRNA expression. This miRNA profile permits to classify cancer and often gives prognostic information. Profiling based on miRNAs may be more specific and robust than profiling based on mRNAs. MiRNAs can be studied in virtually all tissues including plasma. More work is necessary, but miRNAs have already improved our understanding of the pathogenesis of cancer and appear promising for diagnostic purposes as biomarkers and for the development of new genetic treatments. Key Concepts: MicroRNAs regulate gene expression. MicroRNAs are important in the pathogenesis and progression of human cancer. MicroRNAs can function as tumour suppressors and as tumour promoters (oncomirs). MicroRNAs can serve as biomarkers for cancer and may become useful for the treatment of cancer.

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MicroRNA s in Cancer

Munker¹,

Shackelford²,

Calin³

2016

Encyclopedia of Life Sciences

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Initially considered an epiphenomenon, micro ribonucleic acids (also called miRNAs) and other small noncoding RNA molecules are now considered major players in cell biology. MiRNAs regulate gene expression through effects on translation, transcription and chromatin modification. Multiple miRNAs are dysregulated in human cancer and affect cellular proliferation, apoptosis, metastasis and tumour invasion and the phenotype of cancer cells. Virtually every cell type and cancer has a specific miRNA expression pattern. This unique miRNA expression pattern allows the classification of specific cancer types and often gives prognostic information. Profiling based on miRNAs may be more specific and robust than profiling based on mRNAs. MiRNAs can be studied in virtually all tissues including plasma. More work is required, but miRNAs have already improved our understanding of the pathogenesis of cancer and tumour progression and appear promising as novel diagnostic biomarkers. Finally, they may be of value in the development of new genetic treatments. Key Concepts MicroRNAs regulate gene expression. MicroRNAs are important in the pathogenesis and progression of human cancers. MicroRNAs can function as tumour suppressors and as tumour promoters (oncomirs). Cancers of different origin have specific microRNA expression patterns, allowing molecular characterisation. MicroRNAs can serve as biomarkers for cancer and may become useful for the treatment of cancer. MicroRNA analysis may give prognostic information and be of use in subtyping histologically similar tumours into less and more clinically aggressive categories. Exosomes contain microRNAs and processing enzymes and mediate some of the biological effects of microRNAs.

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Diagnostic Assay Based on hsa-miR-205 Expression Distinguishes Squamous From Nonsquamous Non–Small-Cell Lung Carcinoma

Abstract: Hsa-miR-205 is a highly accurate marker for lung cancer of squamous histology. The standardized diagnostic assay presented here can provide highly accurate subclassification of NSCLC patients.

Cited by 362 publications

References 36 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

Micro RNAs in Cancer

MicroRNA s in Cancer

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