Quantification and localization of oncogenic receptor tyrosine kinase variant transcripts using molecular inversion probes
Abstract Oncogenic membrane receptor tyrosine kinases such as MET and EGFR, or auto-active variants thereof, are important targets for cancer precision therapy. Targeted inhibition of these oncogenic receptors however invariably leads to resistance, resulting from acquisition of resistance-inducing...
Guardado en:
| Autores principales: | , , , , , , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2018
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/a96e3530439a41b7b9df6a5ba6233936 |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| Sumario: | Abstract Oncogenic membrane receptor tyrosine kinases such as MET and EGFR, or auto-active variants thereof, are important targets for cancer precision therapy. Targeted inhibition of these oncogenic receptors however invariably leads to resistance, resulting from acquisition of resistance-inducing mutations or from selective outgrowth of a priori resistant tumour cells. Most applied molecular protocols cannot distinguish between intracellular and intercellular heterogeneity of oncogene (variant) expression, which may lead to misinterpretation of the molecular make-up of a cancer and suboptimal application of targeted therapies. We here combined two related techniques to allow semiquantitative and localized in situ detection of specific transcript splice variants using single molecule molecular inversion probe (smMIP)-based next generation sequencing and padlock probe-based rolling circle amplification, respectively. We show highly specific padlock probe-based multiplex detection of MET, METΔ7-8 and METΔ14 transcripts, lacking exons 7–8 and exon 14 respectively, and of EGFR and the auto-active EGFRvIII, lacking exons 2–7. The combination of quantitative transcript variant detection with smMIPs and transcript localization using padlock probes can be used for detection of oncogenic transcripts on the single-cell level, allowing study of tumour heterogeneity. Visualization of tumour heterogeneity can shed light on the biology underlying drug resistance and potentially improve targeted therapeutics. |
|---|