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R. Mastrangelo
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P3.03 - Chemotherapy/Targeted Therapy (ID 719)
- Event: WCLC 2017
- Type: Poster Session with Presenters Present
- Track: Chemotherapy/Targeted Therapy
- Presentations: 1
- Moderators:
- Coordinates: 10/18/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)
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P3.03-016 - Morphometric Genotyping Identifies Lung Cancer Cells Harboring Target Mutations; Cell-CT® Platform Detects Gene Abnormalities (ID 9491)
09:30 - 09:30 | Author(s): R. Mastrangelo
- Abstract
Background:
The advent of genotype-directed therapy in personalized medicine requires the identification of driver-mutations that are often under-diagnosed due to limitations in tissue biopsy and high false negative rates associated with genomic tests. Studies have demonstrated that the mutation status of cancer cells correlates with changes in cellular morphology. The automated Cell-CT[®] platform produces isometric, high-resolution 3D images of cells in liquid biopsies, such as sputum, where published studies have demonstrated 92% sensitivity to biopsy confirmed lung cancer with 95% specificity. This study reports the development of cell classifiers for lung cancer cell lines that harbor known mutations, helping pave the way to driver-mutation targeted therapy.
Method:
Non-invasive sputum specimens from patients without lung cancer (“normal cells”) and the following cell lines were analyzed using the Cell-CT[®] platform: Small Cell Lung Cancer cell line NCI-H69 Adenocarcinoma cell lines A549 (EGFR wild-type, -c.1_471del471, KRAS- p.G12S) NCI-H1650 (EGFR- p.E746_A750del, CDKN2A- c.1_471del471, TP53- c.673-2A>G) NCI-H1975 (EGFR-T790M, CDKN2A- p.E69*, PIK3CA- p.G118D, TP53- p.R273H) NCI-H2228 (EML4-ALK+, CDKN2A- c.1_471del471, RB1- p.E204fs*10, TP53- p.Q331* high PD-L1).
Result:
15,000 normal cells from sputum and 500 malignant cells from each of the five cancer cell lines were analyzed using Cell-CT[®] platform, measuring 704 structural biomarkers to sub-classify the cancer cells by mutation status. Cell classifiers were operated to drive the highest specificity (avoidance of false positives) while maintaining sensitivity above 50%. The area under ROC (aROC), sensitivity and specificity for each classifier were:Cell Classifiers aROC Sensitivity % Specificity % Small cell lung cancer (NCI-H69) 0.991 74.8 99.98 Adenocarcinoma, EGFR wild-type (A549) 0.950 58.8 99.94 Adenocarcinoma, EGFR – pE746_A750del (NCI-H1650) 0.993 59.6 99.99 Adenocarcinoma, EGFR -T790M (NCI-H1975) 0.972 66.0 99.99 Adenocarcinoma, ALK+ (NCI-H2228) 0.992 76.8 99.97
Conclusion:
This study demonstrates the feasibility of processing non-invasive sputum specimens by the Cell-CT[®] platform to accurately identify driver mutations in cancer cells to promote mutation-directed targeted therapy for the treatment of lung cancer.
