MicroRNAs accurately identify cancer tissue origin

By N. Rosenfeld, Ranit Aharonov, E. Meiri, S. Rosenwald, Y. Spector, M. Zepeniuk, H. Benjamin, Norberto Shabes, S. Tabak, Asaf Levy and 23 more. Nature Biotechnology, 2008

1,016 citations recorded by the source corpus.

Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/5487c1a27f6713ff5d38a8e889f095b8bbf1813f

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Cancer Research

In Molecular Biology

Citations in the corpus

MicroRNAs and cancer: short RNAs go a long way. (2009, background): “The initial findings are encouraging, as it appears that miRNA-based classification is more efficient at identifying the tissue of origin of poorly differentiated cancers than is mRNA profiling (Lu et al., 2005; Rosenfeld et al., 2008).”
MicroRNAs in cancer: small molecules with a huge impact. (2009, background): “Interestingly, it has been recently observed that primary tumors and metastasis from the same tissue show a similar pattern of microRNA expression.(74) Being a more accurate classifier than mRNA expression studies, microRNA profiling has thus revealed the potential to solve one of the most demanding”
Laser induced self-N-doped porous graphene as an electrochemical biosensor for femtomolar miRNA detection (2020, background): “MicroRNAs (miRNAs, ~22 nucleotides) are small noncoding, single-stranded RNA molecules that play regulatory roles in cell development, differentiation, proliferation, apoptosis and stress responses and are recognized as important biomarkers for cancer and other complex diseases [10,11].”
Serum MicroRNAs Are Promising Novel Biomarkers (2008, methodology): “Furthermore, microRNAs are emerging as highly tissuespecific biomarkers [14,15] with potential clinical applicability for defining the cancer origin of metastases, as we have shown recently [16].”
Non‐coding RNAs: regulators of disease (2010, result): “For example, in some cases the expression profiles of miRNAs, in contrast to those of protein-coding mRNAs, are able to accurately identify the origin of poorly differentiated tumours and carcinomas [198,199].”
MicroRNAs — the micro steering wheel of tumour metastases (2009, methodology): “By using a combination of microarray and real-time PCR on 400 paraffin-embedded and fresh-frozen samples from 22 different tumour tissues and metastases including CUP cases, Rosenfeld and colleagues showed that a classifier based on 48 miRNAs reached over 90% classification accuracy for most tissue ”
MicroRNA dysregulation in cancer: diagnostics, monitoring and therapeutics. A comprehensive review (2012, neutral): “One study, for example, developed a classiﬁer of 48 miRNAs from a sample of 336 primary and metastatic tumours, and was able to use this classiﬁer to accurately predict the tissue origin in 86% of a blind test set, including 77% of the metastatic tumours (Rosenfeld et al, 2008).”
MicroRNAs in body fluids—the mix of hormones and biomarkers (2011, positive): “Metastatic cancers of unknown primary origin were classified with >90% accuracy based on an expression profile of 48 miRNAs”
Circulating Exosomal microRNAs as Biomarkers of Colon Cancer (2014, background): “Dysfunction of miRNAs is found in various cancers and the endogenous expression profiles of miRNAs can be used to classify cancer types [7,8].”
MicroRNA based Pan-Cancer Diagnosis and Treatment Recommendation (2017, methodology): “[10] studied miRNAs from tumor and metastatic cancer to prove that they could predict the cancer tissue of origin (22 tumor types into 7 different tissue types) using KNN and decision tree classifiers.”