Rna-seq for blood-based pan-cancer diagnostics

Access through your institution Buy or subscribe To establish their method, platelet samples from healthy controls (_n_=55), patients with early, localized tumours (_n_=39) and patients with

advanced, metastatic tumours (_n_=189) were collected, covering 6 different tumour types (lung, colorectal, brain, pancreatic, hepatobiliary and breast cancer). SMARTer mRNA amplification

followed by sequencing and selection of spliced RNA reads yielded ∼5,000 differentially expressed protein-coding and non-coding RNAs between patients with tumours and healthy controls.

Selection of a classifier-specific gene list of 1,072 RNAs combined with the use of a custom machine-learning algorithm allowed discrimination of the presence versus the absence of cancer

with a sensitivity (proportion of correctly identified positives) of ∼97%, a specificity (proportion of correctly identified negatives) of ∼94% and an accuracy of ∼95%. By contrast, the use

of random classifiers had no predictive power. Thus, nearly all cancer patients — regardless of the type of tumour — have abnormal platelet RNA profiles and are identified by the algorithm.

Next, tumour-specific gene lists were selected by unsupervised hierarchical clustering of differentially expressed RNAs between the six different cancer types. Combined first and second

ranked classification resulted in an 89% accuracy to classify the tumour types correctly. Finally, the authors assessed whether platelet RNA reflects the molecular profile of the tumour

tissue. Selection of biomarker-specific gene lists allowed the discrimination of _KRAS_ and _EGFR_ mutations, _HER2_ amplification and _MET_ overexpression compared to wild-type sequences in

the platelet RNA profile, which matched the respective tumour DNA analysis. This is a preview of subscription content, access via your institution ACCESS OPTIONS Access through your

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our FAQs * Contact customer support REFERENCES * Best, M. G. et al. RNA-seq of tumor-educated platelets enables blood-based pan-cancer, multiclass and molecular pathway cancer diagnostics.

_Cancer Cell_ http://dx.doi.org/10.1016/j.ccell.2015.09.018 (2015) Download references AUTHOR INFORMATION AUTHORS AND AFFILIATIONS * Associate Editor, Nature Reviews Disease Primers, Liesbet

Lieben Authors * Liesbet Lieben View author publications You can also search for this author inPubMed Google Scholar RIGHTS AND PERMISSIONS Reprints and permissions ABOUT THIS ARTICLE CITE

THIS ARTICLE Lieben, L. RNA-seq for blood-based pan-cancer diagnostics. _Nat Rev Cancer_ 15, 697 (2015). https://doi.org/10.1038/nrc4048 Download citation * Published: 13 November 2015 *

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