Virtual Library
Start Your Search
Alan Nelson
Author of
-
+
P3.03 - Chemotherapy/Targeted Therapy (ID 719)
- Event: WCLC 2017
- Type: Poster Session with Presenters Present
- Track: Chemotherapy/Targeted Therapy
- Presentations: 2
- Moderators:
- Coordinates: 10/18/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)
-
+
P3.03-016 - Morphometric Genotyping Identifies Lung Cancer Cells Harboring Target Mutations; Cell-CT® Platform Detects Gene Abnormalities (ID 9491)
09:30 - 09:30 | Presenting Author(s): Alan Nelson
- 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.
-
+
P3.03-026 - Cell-CT® Differential Detection of Dysplastic Bronchial Epithelial Cells from Patient Explants (ID 10219)
09:30 - 09:30 | Author(s): Alan Nelson
- Abstract
Background:
Chemoprevention could have a great impact on lung cancer prevention. While Iloprost treatment has shown a significant reduction of dysplasia in former smokers, the identification of patients who would benefit from the drug is seriously hampered due to the need to use invasive diagnostic procedures in patients who are typically asymptomatic. Published clinical data shows that non-invasive sputum analysis using the Cell-CT platform detects early stage lung cancer with high sensitivity (92%) and specificity (95%). This abstract reports the development of cell classifiers that distinguish cultured human lung dysplastic explants from malignant and normal sputum cells. This study represents a first important step toward developing a non-invasive diagnostic test for detecting patients with moderate to severe bronchial dysplasia who may then be treated with chemopreventive drugs such as Iloprost.
Method:
To achieve diagnostic classifications, sputum from patients without lung cancer (“normal cells”), small cell lung cancer and five adenocarcinoma cell lines, and cultured bronchial explants from three patients with moderate to severe dysplasia were analyzed using the Cell-CT.
Result:
15,000 normal cells from sputum, 500 malignant cells from each of the five lung cancer cell lines and 264 cells from patient dysplastic explants were analyzed using Cell-CT platform, measuring 704 structural biomarkers to sub-classify the cancer cells by abnormality and dysplastic status. Cell classifiers were operated to drive the highest specificity (avoidance of false positives). The area under ROC (aROC), sensitivity and specificity for each classifier were:Cell Classifiers aROC Sensitivity % Specificity % Lung Cancer cell lines 0.999 93% 99.99 Cells from patient dysplastic explants 0.995 86% 99.99
Conclusion:
These results show strong discrimination by the Cell-CT in classifying normal cells from sputum versus cells from lung dysplastic explants and lung cancer cell lines grown in culture. These data suggest that a non-invasive test using sputum liquid biopsy analyzed on the Cell-CT platform could enable the detection of dysplasia in patients who would benefit from chemoprevention drug therapy.
-
+
P3.05 - Early Stage NSCLC (ID 721)
- Event: WCLC 2017
- Type: Poster Session with Presenters Present
- Track: Early Stage NSCLC
- Presentations: 1
- Moderators:
- Coordinates: 10/18/2017, 09:30 - 16:00, Exhibit Hall (Hall B + C)
-
+
P3.05-002 - The Effect of Nodule Size on the Sensitivity of the LuCED® Test for Lung Cancer (ID 9597)
09:30 - 09:30 | Author(s): Alan Nelson
- Abstract
Background:
The LuCED® test is based on analysis of sputum by the Cell-CT® platform that computes 3D images of cells with isometric resolution, allowing orientation-independent measurements of 704 3D structural biomarkers to generate a probabilistic score to identify abnormal cells. that was consistent by tumor histology and stage. Early stage tumors are generally smaller in size. One view is that smaller tumors might exfoliate fewer abnormal cells into sputum, making early stage tumor detection less likely. Here, we test the hypothesis that tumor size is a primary determinant of LuCED sensitivity.
Method:
Sputum samples from 74 biopsy confirmed non-small cell lung cancer cases were studied. The tumor size (mm) was characterized as the maximum tumor dimension supplied by the clinic. The numbers of bronchial epithelial cells and abnormal cells in sputum were measured and confirmed by cytological review. Tumor cell prevalence was characterized as (abnormal cells)/(bronchial epithelial cells) and plotted versus tumor size to assess any trend towards lower abnormal cell prevalence with decreasing tumor size.
Result:
The figures show the abnormal cell prevalence and the log of prevalence versus tumor size. Figure 1
Conclusion:
No trend was observed that might support the hypothesis that lower abnormal cell prevalence would occur with smaller tumor size. Moreover, variance in abnormal cell prevalence for any tumor size is large, suggesting that factors other than tumor size are more important in determining prevalence. There is no evidence to suggest that the LuCED test sensitivity decreases for smaller tumors, and this further suggests that early stage cancer, where tumors might be smaller, can still be detected. Published data shows that the LuCED test is 92% sensitive to stage 1 lung cancer.
