Abstract 741: Rapid detection of necrosis in breast cancer withex vivoandin situmass spectrometry analysis methods

Cancer Research(2017)

引用 0|浏览0
暂无评分
摘要
Necrosis is a form of cell death that is often associated with highly aggressive forms of cancer, is of prognostic value in treatment planning. Mass Spectrometry (MS) is a highly sensitive analytic platform capable of providing a molecular profile of cancer on the basis of mass to charge (m/z) ratio of tissue constituent molecules. MS analysis of ex vivo tissue slices from metastatic murine xenograft tumors from LM2-4 cell line with Desorption Electrospray Ionization Mass Spectrometry (DESI-MS) allowed direct comparisons with histology images to determine the molecular profile of necrotic tissues. The necrotic tissue is characterized by the presence of a ceramide absent from the viable cancer regions. The spatial distribution of this ion fully correlated to necrotic areas from pathology in additional independent tumor samples examined. The same ion was detected from in situ necrotic tissue using tissue aerosols generated by hand-held ablation probes coupled to evaporative ionization interface in only a few seconds of sampling. These developments further establish MS as a novel tool for rapid pathology that is highly complementary to current histology based methods widely used in characterization of cancer in both imaging mode (to provide spatial information on cancer border) and profiling mode (to provide information on cancer type and subtype); all based on unique molecular profile associated with each cancer type and subtype. Current efforts in creating cancer molecular profile libraries will facilitate translation. Citation Format: Arash Zarrine-Afsar, Bindesh Shrestha, Alessandra Tata, Michael Woolman, Manuela Ventura, Nicholas Bernards, Milan Ganguly, Howard Ginsberg, Jinzi Zheng, Emma Bluemke. Rapid detection of necrosis in breast cancer with ex vivo and in situ mass spectrometry analysis methods [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 741. doi:10.1158/1538-7445.AM2017-741
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要