Extending the information content of the MALDI analysis of biological fluids via multi-million shot analysis

Abstract

IntroductionReliable measurements of the protein content of biological fluids like serum or plasma can provide valuable input for the development of personalized medicine tests. Standard MALDI analysis typically only shows high abundance proteins, which limits its utility for test development. It also exhibits reproducibility issues with respect to quantitative measurements. In this paper we show how the sensitivity of MALDI profiling of intact proteins in unfractionated human serum can be substantially increased by exposing a sample to many more laser shots than are commonly used. Analytical reproducibility is also improved.MethodsTo assess what is theoretically achievable we utilized spectra from the same samples obtained over many years and combined them to generate MALDI spectral averages of up to 100,000,000 shots for a single sample, and up to 8,000,000 shots for a set of 40 different serum samples. Spectral attributes, such as number of peaks and spectral noise of such averaged spectra were investigated together with analytical reproducibility as a function of the number of shots. We confirmed that results were similar on MALDI instruments from different manufacturers.ResultsWe observed an expected decrease of noise, roughly proportional to the square root of the number of shots, over the whole investigated range of the number of shots (5 orders of magnitude), resulting in an increase in the number of reliably detected peaks. The reproducibility of the amplitude of these peaks, measured by CV and concordance analysis also improves with very similar dependence on shot number, reaching median CVs below 2% for shot numbers > 4 million. Measures of analytical information content and association with biological processes increase with increasing number of shots.ConclusionsWe demonstrate that substantially increasing the number of laser shots in a MALDI-TOF analysis leads to more informative and reliable data on the protein content of unfractionated serum. This approach has already been used in the development of clinical tests in oncology.

Definition and Independent Validation of a Proteomic-Classifier in Ovarian Cancer

“…Previous studies have examined in detail the analytical reproducibility of Deep MALDI mass spectra [14]. Using the same mass spectrometer and spectral acquisition procedures, it was shown, for a similar set of 298 mass spectral features as used in this work, that the median CV across features was 2.3% with interquartile range 1.4-5.0%.…”

“…Here we used the Deep MALDI method of mass spectrometry, resulting in a deeper probing of the proteome, by increasing the signal-to-noise ratio of the measurements and an increased number of measurable circulating proteins from human blood samples [ 14 ]. This technique has recently been used for outcome stratification of patients receiving immunotherapy [ 34 , 35 , 36 ].…”

“…Spectral acquisition and processing were performed by using the Deep MALDI method of mass spectrometry on a SimulToF mass spectrometer (SimulTof Systems, Marlborough, MA, USA). This approach, requiring only 3 µL of plasma, allows a for deeper probing of the proteome (i.e., assessment of peaks spanning a higher range of intensities) than is possible with conventional MALDI methods, by exposing the samples to many more laser "shots" (400,000, as compared with typically 1000-10,000) [14] (see Figure 5).…”

“…To address the unmet need for non-invasive tests to select patients likely not to respond to standard treatment in EOC [5], we here describe the development and independent validation of an MS-based plasma proteomic classifier that stratifies patients with primary EOC prior to standard treatment. As standardization and optimization of protocols are of utmost importance in cancer research, we made use of a Matrix-Assisted Laser Desorption/Ionization (MALDI)-TOF platform and the Deep MALDI method of MS, extending the observable dynamic range in a single workflow [14]. These processed spectral data were combined with clinical outcome data, using a machine learning approach optimized for the personalized medicine setting, where there are typically more measured attributes than patient samples [15,16].…”

Mass Spectrometry-Based Multivariate Proteomic Tests for Prediction of Outcomes on Immune Checkpoint Blockade Therapy: The Modern Analytical Approach

“…Matrix-Assisted Laser Desorption/Ionization (MALDI) Time of Flight (TOF) mass spectrometry is a suitable tool for developing proteomic tests, as it provides a high throughput platform for the reproducible measurement of circulating proteins and peptides [41]. Although in its standard application it is limited by relatively low sensitivity, it is possible to vastly increase the information content of MALDI-TOF spectra by applying Deep MALDI ® technology, which dramatically increases signal-to-noise ratio and is characterized by high sensitivity and high reproducibility of protein peak amplitudes and relative quantitation [42]. Due to the rich representation of host response proteins in the circulating proteome, Deep MALDI spectra from serum and plasma are especially amenable data sources for creating multivariate tests reflecting the immune status of patients that may be associated with response to immunotherapy.…”