Towards real-time metabolic profiling of a biopsy specimen during a surgical operation by 1H high resolution magic angle spinning nuclear magnetic resonance: a case report
© Piotto et al; licensee BioMed Central Ltd. 2012
Received: 10 August 2011
Accepted: 18 January 2012
Published: 18 January 2012
Providing information on cancerous tissue samples during a surgical operation can help surgeons delineate the limits of a tumoral invasion more reliably. Here, we describe the use of metabolic profiling of a colon biopsy specimen by high resolution magic angle spinning nuclear magnetic resonance spectroscopy to evaluate tumoral invasion during a simulated surgical operation.
Biopsy specimens (n = 9) originating from the excised right colon of a 66-year-old Caucasian women with an adenocarcinoma were automatically analyzed using a previously built statistical model.
Metabolic profiling results were in full agreement with those of a histopathological analysis. The time-response of the technique is sufficiently fast for it to be used effectively during a real operation (17 min/sample). Metabolic profiling has the potential to become a method to rapidly characterize cancerous biopsies in the operation theater.
A 66-year-old Caucasian women presented to our hospital with anemia (hemoglobin 9.1 g/dL, hematocrit 31%) and an abdominal scanner examination revealed the presence of a tumor in her ascending colon. Our patient underwent an open right hemicolectomy with radical lymphadenectomy. The tumor was diagnosed in histopathology as a differentiated adenocarcinoma with angio-, lympho- (2/13) and neuroinvasion and staged as pT4aN1M0 according to the tumor-node-metastasis classification. Molecular analysis of the samples revealed microsatellites-stable tumor with p53 gene alteration. No tumor infiltration was observed in the margin of the resected colon.
Nine biopsy specimens from our patient's segmental colon resection were prepared in 30 μL inserts (preparation time, two minutes per insert) and inserted into a 500 MHz NMR magnet (for detailed experimental procedure see ). One-dimensional HRMAS NMR data were then acquired under exactly the same conditions as the ones used to build the statistical model (3°C, rotation speed 3502 Hz, total experiment time 14 minutes). Immediately after data acquisition, the peak integral within each 0.01 ppm region was computed and normalized with respect to the total integral of the spectrum in the 4.7 ppm to 0.5 ppm region using AMIX software (Bruker GmbH, Germany). Datasets were then imported into the SIMCA P 11.0 software (Umetrics AB, Umeå, Sweden), pre-processed using unit variance scaling and input into the previously described statistical model. The model then automatically classified, without any human intervention, the nine samples as either cancerous or control (data analysis time, one minute).
Adenocarcinoma are characterized, in decreasing order of importance, by a higher amount of taurine, glutamate and aspartate than control biopsy specimens, which contain more myo-inositol and glucose. Although a detailed analysis of the metabolic pathways affected in ardenocarcinoma cells is out of the scope of this manuscript, it is clear that our results are in full agreement with the Warburg phenomenon  since adenocarcinoma cells are clearly depleted in glucose. Figure 3 presents the 1H HRMAS NMR spectra corresponding precisely to the biopsy specimens analyzed by histopathology. The higher content of the metabolites taurine (3.42 ppm), glutamate (2.34 ppm) and aspartate (2.80 ppm) is clearly visible in the spectra of tumoral cells, whereas the intensity of myo-inositol (4.05 ppm) and glucose (4.65 ppm) increases significantly in the control biopsy specimens. Thus, the results obtained show that metabolic profiling is indeed able to provide real-time analysis of biopsy samples.
The total time per sample in our case for a full analysis, which consists of sample preparation, data acquisition and statistical analysis, is about 17 minutes per sample. Interestingly, this time is equivalent to that typically observed in the case of an extemporaneous histological analysis but still needs to be reduced in the context of an operation. Realistically, future progress in sample preparation, data acquisition and analysis should be able to reduce this time to less than 10 minutes per biopsy sample. In that respect, automation and simultaneous analysis of multiple samples will play a crucial role for the future development of these techniques.
Adenocarcinoma of the colon was chosen as a test case for this study for two reasons. First, the segmental colon resection allows the preparation of several biopsies with different levels of tumoral cell infiltration, in particular at the level of the transitional zones. Second, we have previously developed a robust statistical model for this kind of pathology. This model was essential for the success of the current analysis. From a medical point of view, the approach presented here could have some extremely important applications in areas of surgery that require a surgical strategy to be decided under intraoperative conditions, or in cases where it is extremely difficult to delineate with adequate precision the exact zone of tumoral infiltration. Neurosurgery or surgery of the pancreas, in particular, is a field that would benefit immensely from this kind of technology. The prospects of real-time metabolic profiling by HRMAS NMR are therefore extremely promising and methodological as well as technical developments should make this type of analysis even faster.
Written informed consent was obtained from the patient for publication of this case report and any accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal.
high resolution magic angle spinning
nuclear magnetic resonance.
This work is part of the CARMeN project which permitted the installation of the first HRMAS NMR spectrometer (500 MHz) in a hospital environment at the end of 2007 in the University Hospitals of Strasbourg (Hôpital de Hautepierre). The CARMeN project is supported by grants from Région Alsace, Oséo, Bruker BioSpin, Communauté Urbaine de Strasbourg, Conseil Départemental du Bas-Rhin, Hôpitaux Universitaires de Strasbourg, and Université de Strasbourg. The technical assistance of the Tumor Bio-bank (Centre de Resources Biologiques) of the University Hospitals of Strasbourg is gratefully acknowledged.
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