Identification of Hypoxia-Regulated Proteins Using MALDI-Mass Spectrometry Imaging Combined with Quantitative Proteomics

Hypoxia is present in most solid tumors and is clinically correlated with increased metastasis and poor patient survival. While studies have demonstrated the role of hypoxia and hypoxia-regulated proteins in cancer progression, no attempts have been made to identify hypoxia-regulated proteins using quantitative proteomics combined with MALDI-mass spectrometry imaging (MALDI-MSI). Here we present a comprehensive hypoxic proteome study and are the first to investigate changes in situ using tumor samples. In vitro quantitative mass spectrometry analysis of the hypoxic proteome was performed on breast cancer cells using stable isotope labeling with amino acids in cell culture (SILAC). MS analyses were performed on laser-capture microdissected samples isolated from normoxic and hypoxic regions from tumors derived from the same cells used in vitro. MALDI-MSI was used in combination to investigate hypoxia-regulated protein localization within tumor sections. Here we identified more than 100 proteins, both novel and previously reported, that were associated with hypoxia. Several proteins were localized in hypoxic regions, as identified by MALDI-MSI. Visualization and data extrapolation methods for the in vitro SILAC data were also developed, and computational mapping of MALDI-MSI data to IHC results was applied for data validation. The results and limitations of the methodologies described are discussed. 2014 American Chemical Societ

Multiple Statistical Analysis Techniques Corroborate Intratumor Heterogeneity in Imaging Mass Spectrometry Datasets of Myxofibrosarcoma

MALDI mass spectrometry can generate profiles that contain hundreds of biomolecular ions directly from tissue. Spatially-correlated analysis, MALDI imaging MS, can simultaneously reveal how each of these biomolecular ions varies in clinical tissue samples. The use of statistical data analysis tools to identify regions containing correlated mass spectrometry profiles is referred to as imaging MS-based molecular histology because of its ability to annotate tissues solely on the basis of the imaging MS data. Several reports have indicated that imaging MS-based molecular histology may be able to complement established histological and histochemical techniques by distinguishing between pathologies with overlapping/identical morphologies and revealing biomolecular intratumor heterogeneity. A data analysis pipeline that identifies regions of imaging MS datasets with correlated mass spectrometry profiles could lead to the development of novel methods for improved diagnosis (differentiating subgroups within distinct histological groups) and annotating the spatio-chemical makeup of tumors. Here it is demonstrated that highlighting the regions within imaging MS datasets whose mass spectrometry profiles were found to be correlated by five independent multivariate methods provides a consistently accurate summary of the spatio-chemical heterogeneity. The corroboration provided by using multiple multivariate methods, efficiently applied in an automated routine, provides assurance that the identified regions are indeed characterized by distinct mass spectrometry profiles, a crucial requirement for its development as a complementary histological tool. When simultaneously applied to imaging MS datasets from multiple patient samples of intermediate-grade myxofibrosarcoma, a heterogeneous soft tissue sarcoma, nodules with mass spectrometry profiles found to be distinct by five different multivariate methods were detected within morphologically identical regions of all patient tissue samples. To aid the further development of imaging MS based molecular histology as a complementary histological tool the Matlab code of the agreement analysis, instructions and a reduced dataset are included as supporting information

Reporting Recommendations for Tumor Marker Prognostic Studies (REMARK): Explanation and Elaboration

The REMARK “elaboration and explanation” guideline, by Doug Altman and colleagues, provides a detailed reference for authors on important issues to consider when designing, conducting, and analyzing tumor marker prognostic studies

Sample treatment for tissue proteomics in cancer, toxicology, and forensics

Since the birth of proteomics science in the 1990, the number of applications and of sample preparation methods has grown exponentially, making a huge contribution to the knowledge in life science disciplines. Continuous improvements in the sample treatment strategies unlock and reveal the fine details of disease mechanisms, drug potency, and toxicity as well as enable new disciplines to be investigated such as forensic science. This chapter will cover the most recent developments in sample preparation strategies for tissue proteomics in three areas, namely, cancer, toxicology, and forensics, thus also demonstrating breath of application within the domain of health and well-being, pharmaceuticals, and secure societies. In particular, in the area of cancer (human tumor biomarkers), the most efficient and multi-informative proteomic strategies will be covered in relation to the subsequent application of matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) and liquid extraction surface analysis (LESA), due to their ability to provide molecular localization of tumor biomarkers albeit with different spatial resolution. With respect to toxicology, methodologies applied in toxicoproteomics will be illustrated with examples from its use in two important areas: the study of drug-induced liver injury (DILI) and studies of effects of chemical and environmental insults on skin, i.e., the effects of irritants, sensitizers, and ionizing radiation. Within this chapter, mainly tissue proteomics sample preparation methods for LC-MS/MS analysis will be discussed as (i) the use of LC-MS/MS is majorly represented in the research efforts of the bioanalytical community in this area and (ii) LC-MS/MS still is the gold standard for quantification studies. Finally, the use of proteomics will also be discussed in forensic science with respect to the information that can be recovered from blood and fingerprint evidence which are commonly encountered at the scene of the crime. The application of proteomic strategies for the analysis of blood and fingerprints is novel and proteomic preparation methods will be reported in relation to the subsequent use of mass spectrometry without any hyphenation. While generally yielding more information, hyphenated methods are often more laborious and time-consuming; since forensic investigations need quick turnaround, without compromising validity of the information, the prospect to develop methods for the application of quick forensic mass spectrometry techniques such as MALDI-MS (in imaging or profiling mode) is of great interest

Novel molecular tumour classification using MALDI-mass spectrometry imaging of tissue micro-array

The development of tissue micro-array (TMA) technologies provides insights into high-throughput analysis of proteomics patterns from a large number of archived tumour samples. In the work reported here, matrix-assisted laser desorption/ionisation-ion mobility separation-mass spectrometry (MALDI-IMS-MS) profiling and imaging methodology has been used to visualise the distribution of several peptides and identify them directly from TMA sections after on-tissue tryptic digestion. A novel approach that combines MALDI-IMS-MSI and principal component analysis-discriminant analysis (PCA-DA) is described, which has the aim of generating tumour classification models based on protein profile patterns. The molecular classification models obtained by PCA-DA have been validated by applying the same statistical analysis to other tissue cores and patient samples. The ability to correlate proteomic information obtained from samples with known and/or unknown clinical outcome by statistical analysis is of great importance, since it may lead to a better understanding of tumour progression and aggressiveness and hence improve diagnosis, prognosis as well as therapeutic treatments. The selectivity, robustness and current limitations of the methodology are discussed

Investigation of protein induction in tumour vascular targeted strategies by MALDI MSI.

Characterising the protein signatures in tumours following vascular-targeted therapy will help determine both treatment response and resistance mechanisms. Here, mass spectrometry imaging and MS/MS with and without ion mobility separation have been used for this purpose in a mouse fibrosarcoma model following treatment with the tubulin-binding tumour vascular disrupting agent, combretastatin A-4-phosphate (CA-4-P). Characterisation of peptides after in situ tissue tryptic digestion was carried out using Matrix-Assisted Laser Desorption/Ionisation-Mass Spectrometry (MALDI-MS) and Matrix-Assisted Laser Desorption/Ionisation-Ion Mobility Separation-Mass Spectrometry Imaging (MALDI IMS-MSI) to observe the spatial distribution of peptides. Matrix-Assisted Laser Desorption/Ionisation-Ion Mobility Separation-Tandem Mass Spectrometry (MALDI-IMS-MS/MS) of peaks was performed to elucidate any pharmacological responses and potential biomarkers. By taking tumour samples at a number of time points after treatment gross changes in the tissue were indicated by changes in the signal levels of certain peptides. These were identified as arising from haemoglobin and indicated the disruption of the tumour vasculature. It was hoped that the use of PCA-DA would reveal more subtle changes taking place in the tumour samples however these are masked by the dominance of the changes in the haemoglobin signals

Introduction of a 20 kHz Nd:YVO4 laser into a hybrid quadrupole time-of-flight mass spectrometer for MALDI-MS imaging

A commercial hybrid quadrupole time-of-flight mass spectrometer has been modified for high-speed matrix-assisted laser desorption ionisation (MALDI) imaging using a short-pulse optical technology Nd:YVO4 laser. The laser operating in frequency-tripled mode (lambda=355 nm) is capable of delivering 1.5-ns pulses of energy at up to 8 mu J at 510 kHz and 3 mu J at 20 kHz. Experiments to improve beam homogeneity and reduce laser speckle by mechanical vibration of the fibre-optic laser delivery system are reported along with data from trial and tissue imaging experiments using the modified instrument. The laser appeared to yield best results for MALDI-MS imaging experiments when operating at repetition rates 5-10 kHz. Combining this with raster imaging allowed images of rat brain sections to be recorded in 37 min. Similarly, images of the distribution of peptides in "on-tissue" digest experiments from tumour tissues were recorded in 1 h and 30 min rather than the 8h acquisition time previously used. A brief investigation of targeted protein analysis/imaging by multiple reaction monitoring experiments "on-tissue" is reported. A total of 26 transitions were recorded over a 3-s cycle time and images of abundant proteins were successfully recorded

MALDI-ion mobility separation-mass spectrometry imaging of glucose-regulated protein 78 kDa (Grp78) in human formalin-fixed, paraffin-embedded pancreatic adenocarcinoma tissue Sections

MALDI-mass spectrometry imaging (MALDI-MSI) is a technique that allows proteomic information, that is, the spatial distribution and identification of proteins, to be obtained directly from tissue sections. The use of in situ enzymatic digestion as a sample pretreatment prior to MALDI-MSI analysis has been found to be useful for retrieving protein identification directly from formalin-fixed, paraffin-embedded (ffpe) tissue sections. Here, an improved method for the study of the distribution and the identification of peptides obtained after in situ digestion of fppe pancreatic tumor tissue sections by using MALDI-mass spectrometry imaging coupled with ion mobility separation (IMS) is described. MALDI-IMS-MS images of peptide obtained from pancreatic tumor tissue sections allowed the localization of tumor regions within the tissue section, while minimizing the peak interferences which were observed with conventional MALDI-TOF MSI. The use of ion mobility separation coupled with MALDI-MSI improved the selectivity and specificity of the method and, hence, enabled both the localization and in situ identification of glucose regulated protein 78 kDa (Grp78), a tumor biomarker, within pancreatic tumor tissue sections. These findings were validated using immunohistochemical staining