Sensitive and affordable diagnostic assay for the quantitative detection of anaplastic lymphoma kinase (ALK) alterations in patients with non-small cell lung cancer
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Elisa Dama1,2, Micol Tillhon1, Giovanni Bertalot1, Francesca de Santis1,8, Flavia Troglio1,9, Simona Pessina3, Antonio Passaro4, Salvatore Pece1,5, Filippo de Marinis4, Patrizia Dell’Orto3, Giuseppe Viale3,5, Lorenzo Spaggiari5,6, Pier Paolo Di Fiore1,5,7, Fabrizio Bianchi1,10, Massimo Barberis3, Manuela Vecchi1,7
1Molecular Medicine Program, European Institute of Oncology, Milan, Italy
2Division of Epidemiology and Biostatistics, European Institute of Oncology, Milan, Italy
3Department of Pathology, European Institute of Oncology, Milan, Italy
4Division of Thoracic Oncology, European Institute of Oncology, Milan, Italy
5DIPO, Department of Hemato-Oncology and Oncology, University of Milan, Milan, Italy
6Division of Thoracic Surgery, European Institute of Oncology, Milan, Italy
7IFOM, the FIRC Institute of Molecular Oncology, Milan, Italy
8Present address: Advanced Cell Diagnostics, Segrate, Milan, Italy
9Present address: Division of Immunology, Transplantantion and Infectious Disease, Leukocyte Biology Unit, San Raffaele Scientific Institute, Milan, Italy
10Present address: Institute for Stem-cell Biology, Regenerative Medicine and Innovative Therapies (ISBReMIT), IRCCS Casa Sollievo della Sofferenza, Foggia, Italy
Manuela Vecchi, email: firstname.lastname@example.org
Keywords: ALK, RT-qPCR, inverse prediction, FFPE NSCLC, cytology specimens
Received: January 04, 2016 Accepted: April 25, 2016 Published: May 19, 2016
Accurate detection of altered anaplastic lymphoma kinase (ALK) expression is critical for the selection of lung cancer patients eligible for ALK-targeted therapies. To overcome intrinsic limitations and discrepancies of currently available companion diagnostics for ALK, we developed a simple, affordable and objective PCR-based predictive model for the quantitative measurement of any ALK fusion as well as wild-type ALK upregulation. This method, optimized for low-quantity/-quality RNA from FFPE samples, combines cDNA pre-amplification with ad hoc generated calibration curves. All the models we derived yielded concordant predictions when applied to a cohort of 51 lung tumors, and correctly identified all 17 ALK FISH-positive and 33 of the 34 ALK FISH-negative samples. The one discrepant case was confirmed as positive by IHC, thus raising the accuracy of our test to 100%. Importantly, our method was accurate when using low amounts of input RNA (10 ng), also in FFPE samples with limited tumor cellularity (5–10%) and in FFPE cytology specimens. Thus, our test is an easily implementable diagnostic tool for the rapid, efficacious and cost-effective screening of ALK status in patients with lung cancer.
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