Abstract LB-175: The malignancy associated change hypothesis tested through 3D cellular imaging
| Autor: | Alan C. Nelson, Celeste Hamilton, Rahul Katdare, Laimonas Kelbauskas, Timothy J Bell, Chris Presley, Michael Meyer, Sussman Daniel J |
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| Rok vydání: | 2018 |
| Předmět: | |
| Zdroj: | Cancer Research. 78:LB-175 |
| ISSN: | 1538-7445 0008-5472 |
| Popis: | Early detection remains by far the most reliable and potent strategy in curing lung cancer. Many current approaches, however, are limited by poor sensitivity or specificity that increase health care costs and potentially risk patient health through unneeded and invasive procedures. The association between cell morphology and cancer has been established in the cytology literature. However, the tumor field effect potentially introduces subtle changes into non-tumor cells that reside in the tumor microenvironment. This phenomenon has given rise to the malignancy associated change (MAC) hypothesis. The Cell-CT™ platform and LuCED® test represent a promising new method for detecting lung cancer with high (92%) sensitivity and (95%) specificity that is based on alterations in cellular morphology. We present a study of 3D morphological alterations in non-tumor cells obtained from sputum of healthy subjects and biopsy confirmed lung cancer patients. Three major cell types were analyzed from 235 patients: bronchial epithelial columnar, squamous intermediate, and mature macrophages (dust cells). We used the Cell-CT platform to measure over 700 different structural biosignatures for each cell. A classifier to test the degree to which the features discriminate between cells from normal or cancer patients was developed and its performance characterized by the area under the ROC curve (aROC) (Table 1). Hierarchical clustering analysis revealed biosignatures of nuclear chromatin organization to be the most differentiating between macrophages from healthy subjects and patients with cancer. Table 1. Classifier development and performance characteristics Cell TypeNumber of cells from cancer patientsNumber of cells from normal patientsSupervised Learning – aROCSquamous Intermediate4,6849530.70Macrophages7,2191,3660.75Columnar cells11,7742,9110.80 Our results confirm the MAC hypothesis based on 3D cellular imaging and suggest that cancer presence in the lung can be detected in patient's sputum based on the morphologic alterations in non-tumor cells. This is important as cancer cells are rare in early stages of cancer, posing challenges in terms of detection sensitivity and specificity. Further work will emphasize boosting of the performance figures above based on the combination of results from the differing methods presented. Citation Format: Michael Meyer, Laimonas Kelbauskas, Rahul Katdare, Chris Presley, Celeste Hamilton, Daniel Sussman, Tim Bell, Alan Nelson. The malignancy associated change hypothesis tested through 3D cellular imaging [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr LB-175. |
| Databáze: | OpenAIRE |
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