In:
Cancer Research, American Association for Cancer Research (AACR), Vol. 75, No. 15_Supplement ( 2015-08-01), p. 212-212
Abstract:
This study concerns the development of a new imaging diagnostic tool for bronchial cancer. This malignancy is a wide-spread cancer in the world, with an increasing incidence. Our objective is to assess the potential of infrared (IR) spectroscopy in the early diagnosis of the bronchial cancer. Our approach is divided into two steps: the first issue aims at highlighting specific spectroscopic markers of the bronchial cancer permitting to detect unambiguously the presence of cancer cells. The second step relies on establishing a chemometric model able to estimate the tumor invasivity of these malignant cells For our approach, we used 4 different bronchial cellular lines displaying different in vitro invasive properties assessed by a modified Boyden chamber assay : the non invasive cell line 16HBE used as a control, the moderate invasive cell line Beas2B and the two highly invasive cell lines BZR and BZRT33. Four samples of each cell line were cultured and embedded in paraffin wax. Slices of 10 μm were prepared on CaF2 windows suitable for IR measurements. The infrared acquisitions were performed with an imager (Bruker, Germany) equipped with a Focal Plane Array detector allowing to image large tissue areas with a spatial resolution of a few micrometers. The IR spectra were processed using chemometric and statistical multivariate treatments. A first stage permitted to correct spectral interferences originated from the paraffin and optical effects. Then, supervised models were established by means of PLS-DA (Partial Least Square Discriminant Analysis) method. A first model, based on sparse-PLS method, was optimized to highlight spectroscopic markers specific of the normal and cancerous states; this model has proved effective in terms of sensibility (96%) and specificity (90%). Based on these promising results, the study will be pursued by the analysis of tissue samples from biopsies and tumor samples. Subsequently, the next investigation will rely on the construction of a second model to model and quantify the aggressiveness level of the cell lines. Citation Format: Vincent D. Gaydou, Myriame Polette, Cyril Gobinet, Claire Kileztky, Michel Manfait, Philippe Birembaut, Olivier Piot. Infrared spectral diagnosis for predictive cancer medicine: application to the early diagnosis and prognosis of preinvasive bronchial intraepithelial lesions. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 212. doi:10.1158/1538-7445.AM2015-212
Type of Medium:
Online Resource
ISSN:
0008-5472
,
1538-7445
DOI:
10.1158/1538-7445.AM2015-212
Language:
English
Publisher:
American Association for Cancer Research (AACR)
Publication Date:
2015
detail.hit.zdb_id:
2036785-5
detail.hit.zdb_id:
1432-1
detail.hit.zdb_id:
410466-3
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