Jialing Zhang (Presenter)
UT Austin
Authorship: Jialing Zhang, Livia S. Eberlin
The University of Texas at Austin
| Short Abstract TP53 gene mutations are the most frequent genetic alterations in cancer, occurring in 20%-30% human breast cancer. Cancer bearing TP53 mutations are prone to be aggressive and are associated with poor overall and disease-free survival in breast cancer. In this study, desorption electrospray ionization mass spectrometry imaging (DESI-MSI) was utilized to chemically map breast cancer tissues, including p53 mutations positive tumor tissues, p53 mutations negative tumor tissues, and normal breast tissues. The methodology allowed prediction of the occurrence of TP53 gene mutations directly from breast cancer tissue based on the detection of specific lipid patterns, and may become a valuable method for assessing p53 status in clinical specimens. |
Long Abstract
Introduction
Since its discovery in 1979, the p53 has been one of the most extensively studied proteins in cancer research. In mammalian cells, p53 plays very important roles in growth arrest and apoptosis and is directly involved in DNA repair, acting as the “guardian of the genome” and “cellular gatekeeper” to maintain tissue homeostasis.[1] Under circumstances of defects of p53 function, tumor suppression will be severely reduced, which increases the likelihood of uncontrolled division of cells. Notably, more than 50% of human cancers contain a mutation or deletion of the p53 gene.[2][3] In breast cancer, p53 mutations tend to be associated with poor overall and disease-free survival, and detection of p53 mutations have become important for the cancer diagnostic process.
Gene sequencing analysis and immunohistochemistry are the two main approaches used to evaluate p53 status. However, due to variable accuracy of these two methods, molecular assessment of p53 mutation status might be incomplete and inconsistent among different studies. In recent years, lipid alterations were found to be a central hallmark in carcinogenesis and showed a significant correlation with p53 mutant cancers.[4][5] Two main strategies are used for lipidomic studies: the traditional liquid chromatography mass spectrometry (LC-MS) approach, and shortgun lipidomics, when samples are directly injected with no separation and subjected to tandem mass spectrometry analysis. But both LC-MS and shortgun lipidomics require extensive sample preparation including the extraction lipids by dissolving the tissue in specific solvents, which is time-consuming. Moreover, neither of these two methods can provide spatial distribution of lipids of the target tissues. Therefore, there is a need for a more accurate and rapid technique to detect the existence of p53 mutations in breast cancer.
In this work, we employed DESI-MSI technique to perform 2D chemical mapping of breast tissue samples in the ambient environment, without the need of extensive sample preparation. This mass spectrometry-based technique offers rich molecular distribution information for a sample in a short time. Three different groups of breast samples, including p53 mutations positive tumor tissues, p53 mutations negative tumor tissues, and normal breast tissues, were studied. When compared to normal and P53 negative breast tissues, distinct lipids patterns were observed in p53 mutant breast tumors.
Methods
Human Breast P53 Positive and Negative Cancer Tissues and Normal Breast Tissues
38 frozen human tissue specimens including cancer (p53 positive and negative) and normal breast tissues were purchased from Asterand Bioscience. Samples were stored in a -80 °C freezer until sectioned. Tissue samples were sectioned at 16-μm-thick sections using a CryoStarTM NX50 cryostat (Thermo Scientific). After sectioning, the glass slides were stored in a -80 °C freezer before use. Protein and gene P53 status was investigated for each tissue sample using immunohistochemistry and gene sequencing, respectively.
DESI-MSI
A commercial DESI-MSI system (Prosolia Inc., Indianapolis, IN) coupled to an LTQ-Orbitrap Elite mass spectrometer (Thermo Fisher Scientific, San Jose, CA) was used for tissue imaging. DESI-MSI was performed in the negative ion mode from m/z 100-1500 using the orbitrap as the mass analyzer. 200 um of spatial resolution was set for the imaging experiments. The histologically compatible solvent system dimethylformamide:acetonitrile (DMF:ACN) 1:1 (vol/vol) was used for analysis, at a flow rate of 0.9 μL/min. The N2 pressure was set to 185 psi.
Histopathology
The same tissue sections analyzed by DESI-MSI were subjected afterward to a standard hematoxylin and eosin (H&E) staining protocol. All of the samples used were frozen before sectioning, sectioned, and imaged by DESI-MSI, and then the same tissue section was fixed in methanol before staining with H&E. Pathologic evaluation of the breast cancer tissue was carried out using light microscopy.
Results and Discussion
Six p53 mutations positive tumor tissues, six p53 mutations negative tumor tissues, and six normal breast tissues were selected as training samples and imaged by DESI-MSI. P53 was assesses by IHC and gene sequencing. Under negative ion mode, rich molecular information was obtained for human breast tissues using an Orbitrap for mass analysis at a resolving power of 60,000. Lipid species such as fatty acid, phosphatidylethanolamine, cardiolipin, phosphatidylglycerol, phosphatidylserine and phosphatidylinositol were observed in the tissues. The same frozen tissue section which was scanned by DESI-MSI was subjected to H&E staining and then evaluated by pathologist. The cancer regions were marked and the mass spectrometric information from the specific area was extracted. When comparing the three sets of breast samples, distinctive mass spectra were observed from p53 positive tissues when compared to p53 negative and normal breast tissues. Note that most of the cancer tissues (both p53 positive and p53 negative) provided higher total abundances of lipid signals than normal breast tissues. Interestingly, we found that the relative intensities of specific lipids were closely depended on the extent of p53 mutant protein found in cancer tissues by IHC. To validate the DESI-MSI methodology for p53 mutation characterization, we obtained an independent set of twenty breast cancer tissues. We observed good agreement between prediction obtained by lipid analysis using DESI-MSI and gene status assesses by both IHC and gene sequencing. We believe the methodology described above could be a promising rapid and accurate clinical tool to predict TP53 gene mutations directly from breast cancer tissue, which will be valuable for guiding the treatment of patients.
References & Acknowledgements:
Acknowledgement
We are grateful for the support from the National Institutes of Health/National Cancer Institute (NIH/NCI) through the K99/R00 Pathway to Independence Award (grant 1K99CA190783-01). The authors also thank Clara L. Feider and Marta Sans Escofet for their assistance with tissues sectioning and helpful discussions.
Reference
[1] Jack T. Zilfou, Scott W. Lowe. Cold Spring Harbor Perspectives Biology 2009, 1: a001883
[2] Philippe Bertheau, Jacqueline Lehmann-Che, Mariana Varna, Anne Dumay, Brigitte Poirot, et al. Breast 2013, 22: S27
[3] Ido Goldstein, Varda Rotter. Trends in Endocrinology and Metabolism 2012, 23: 567-575
[4] Franky Dhaval Shah, Shilin Nandubhai Shukla, Pankaj Manubhai Shah, Hiten R. H. Patel, Prabhudas Shankerbhai Patel. Integrative Cancer Therapies 2008, 7: 33-41
[5] Adam Naguib, Gyula Bencze, Dannielle D. Engle, Iok I.C. Chio, Tali Herzka, Kaitlin Watrud, Szilvia Bencze, David A. Tuveson, Darryl J. Pappin, Lloyd C. Trotman. Cell Reports 2015, 10: 8-19
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