Matrix-assisted laser desorption/ionization (MALDI) time-of-flight (TOF) techniques are versatile analytical tools used in various areas of medical diagnostics and basic research. Mass spectrometry (MS) has been successfully applied to study microbiological colonies (1–3), plants (4), insects (5), vertebrates including whole animals (6–8), human cells (9,10) and tissues (11,12).

This method allows the analysis of proteins (13,14), peptides (15,16), lipids or phospholipids (6,17–19), carbohydrates or glycoconjugates (20) and exogenous or endogenous small molecules, especially molecules involved in drug metabolism (21–27).

MALDI imaging mass spectrometry (IMS), first described by Caprioli et al (28), links molecular evaluation of numerous analytes and the high sensitivity and selectivity of mass spectrometry with morphological information about spatial distribution of molecules in cells or tissues (29) and thereby provides unbiased visualization of the arrangement of biomolecules in tissue (30).

Since cancer tissue contains all information on proteomic and genetic changes, it represents the best possible sample material for any molecular research (29). Thus, pathology is not only a large field of medical research but also a basis for the diagnosis of various diseases with direct impact on clinical treatment decisions. The information contained in tissues cannot be replaced by investigation of serum or blood (29).

MALDI IMS has been applied to various organ systems and diseases such as cardiovascular- (31), neurologic- (32), or joint disorders (11,33), amyloidosis (34) inflammatory bowel diseases (35), renal diseases (36–38), the field of reproductive medicine (39) and various tumor entities (13,15,40–45). The following review will focus on MALDI IMS in human tumor tissues as well as applications that have a potential in pathology (22).

Despite some technical limitations, mainly in the area of detection limits and instrument sensitivity at high spatial resolution, this method has the potential to improve cancer diagnostics (42). There are several reviews addressing the complete process of MALDI IMS, in particular regarding experimental considerations: sample collection, sample preparation, matrix deposition, ionization process, instrumentation and data processing (22,30,31,46–54).

IMS experiments can generally be performed in two related modes, imaging (57) and profiling (58). Whereas imaging allows correlation with histology, profiling is generally used when tissues are completely homogeneous and, therefore, different compartments do not have to be considered.

Concerning sample collection and sample preparation, workflow solutions have to be exactly defined beginning from the handling of various tissues in the operation theatre, followed by dehydration and paraffin-embedding process as well as deposition of sections onto conductive slides.

Sample handling and preparation are critical to achieve good spectral quality and reproducibility. In the past few years, several groups have worked on strategies to improve the detection of peptides and proteins (55,56); however, optimization and standardization in clinical application to minimize variability of results are still needed.

IMS requires minimal sample preparation for analysis (59). In the past years, there has been a significant improvement in image spatial resolution that is in the range of 20–50 μm and can be improved to up to 5 μm with special techniques (60,61).

Data processing and statistical analysis are of tremendous importance for accurate and reliable results. In the processing step MALDI datasets are typically subjected to smoothing, baseline correction and calibration. Normalization is generally the next step intended to minimize the experimental variation arising from day-to-day instrument fluctuations, or artifacts related to sample preparation (62). Statistical analysis is then performed in order to elucidate spectral features that are consistently associated within a cohort for biomarker discovery or for disease classification. Most statistical methods can be performed using a supervised method requiring at least two groups of spectral data that need to be discriminated or an unsupervised analysis applied without any prior knowledge of the samples to generate a classification model. Principal component analysis (PCA) is a well known method used to describe the variability in the dataset in a reduced number of dimensions (63). The software for data analysis, such as ClinProTools and SCiLS Lab (Bruker Daltonik), MassLynx (Waters) and BioWorks (Thermo Fisher Scientific) is usually commercially available and provided by the manufacturer of the MALDI instruments. In addition, BioMap software (Novartis, Basel, Switzerland) is freely available for calculating basic statistics of the full dataset. Despite the different data analysis approaches that have been developed, there is a need for more advanced biostatistical software in order to be able to handle huge data files (5,000–50,000 spectra).

A new and emerging application is the three-dimensional illustration of organ structures. It has been shown that MALDI IMS can be combined with other imaging modalities such as positron emission tomography (PET) and magnetic resonance imaging (MRI), improving the interpretation of the proteomic data and providing 3D visualization of proteins that may not be apparent with other imaging methods (64,65).

Another promising development represents MS for single cell analysis to determine protein and peptide contents in cells (47).

Combination of MALDI IMS with cytological preparations of oral brush biopsies has been shown by Remmerbach et al (9). These authors could discern non-malignant from malignant cells by MS. Furthermore, IMS could be applied as a specific diagnostic tool for routine cervical cytology specimen (10). Thus, IMS as a relatively new technique is still at an early stage, and technical advances concerning sample preparation and instrumentation will certainly improve specificity and sensitivity and enlarge the potential for further applications.

Contrary to antibody-based methods, target structures do not need to be known when MALDI IMS is applied (52) which makes it a valuable discovery tool, since broad range of proteins may be surveyed simultaneously (67).

Furthermore, MS techniques may have a higher reproducibility between laboratories than immunohistochemistry because human bias is abolished (68).

However, MALDI IMS cannot only be an adjunct tool to immunohistochemistry but also to histochemistry. For examle, it has been shown that the Berlin-blue reaction for the detection of hemosiderin can be replaced by MALDI IMS of ferritin chains (33). Likewise, mucous substances detected by histochemical reactions could be identified applying MS (69) as well as soft tissue constituents (70–72).

The investigation of frozen tissues by MALDI IMS requires immediate freezing, storage at −80°C and rapid cutting (48) enabling the study of proteins, drugs or their metabolites and lipids. Formalin-fixed paraffin-embedded (FFPE) tissues have to be digested and, therefore, allow analysis of peptides only (Fig. 1). Although frozen samples are easier to be analyzed and imaged as they do not require multiple steps for sample preparation (deparaffination and antigen retrieval), handling and storage of frozen specimens has disadvantages, since proteins are degraded during repeated freeze-thaw cycles and there is a need for expensive freezers.

Despite the difficulties in sample handling, numerous reports have described the application of MALDI IMS on whole sections (12,13,43,44,57,73–78) and even on small biopsy samples of fresh frozen tissue (79).

Millions of FFPE tissues of various diseases including numerous cancer tissues are available in the archives of institutes of pathology. These samples are well documented and include information on patient treatments, treatment response, disease progression and other relevant clinical data (51).

One of the advantages of using fixed specimens is that FFPE tissues are well suited for tissue microarray (TMA) construction, where multiple FFPE core biopsies can be assembled in a single paraffin block. The direct analysis of FFPE TMA using MALDI IMS allows the analysis of multiple tissue samples in a single experiment (67,80). This high-throughput method was used to investigate gastric (16), pancreatic (81), non-small cell lung (67), prostate (82), renal cancer (15) and to discriminate pancreatic from breast cancer tissues (83). The correlation of MALDI IMS data with histology can be performed by two methods: either by staining a serial section with hematoxylin and eosin (H&E) (67) or by staining the tissue after the MALDI experiment, since the tissue is not destroyed during the laser ionization process (47).

There are many techniques used in the study of proteins, such as western blot analysis, liquid chromatography and reverse phase protein arrays (84–87).

The most common approach to identify proteins using MS technique is the bottom-up approach achieved through protein separation/isolation, proteolytic digestion, sequencing of peptides by LC-MS/MS, and matching the peptides to genome-based protein databases (88–90). Another approach is top-down, where proteins of interest are isolated from a complex protein mixture and directly fragmented in the mass spectrometer without previous digestion of proteins. This approach provides direct measurement of the molecular masses of the intact proteins (91,92). An alternative method for protein identification is on-tissue digestion, where tissue samples are in situ digested so that proteins of interest can be isolated and directly fragmented from the tissue section using MALDI MS/MS. This method offers the advantage to identify proteins from a tissue section without separation or homogenization, while preserving the spatial integrity of the tissue sample (30,67). However, protein identification directly from tissue is not always straightforward due to sample complexity and limited sample per unit area, unless peptides are present at high abundance in the sample. Recently, an imageID approach has been developed where consecutive tissue sections are processed in parallel to provide both, protein identification by LC-MS/MS and spatial information by MALDI IMS simultaneously (83) (Fig. 2). New public databases for the identification of proteins such as MSiMass list (93) and MaTisse (94) have been created enabling users to search either for proteins or for m/z values and assign identities to the peaks observed in their experiments. Such databases will improve implementation of MSI in the histopathological and clinical setting.

The biology of a tumor depends not only on tumor cells but also on the interaction with stroma, blood vessels and the immune system (e.g. tumor-associated macrophages and lymphocytes). Homogenization of the tissue sample would lead to loss of information (29). Moreover, when considering personalized medicine, demonstration of tumor heterogeneity (Fig. 3) will be one of the most challenging issues in the future and MALDI IMS seems to be the ideal tool to solve this problem (29,40,95). As an alternative to MALDI IMS in complete tissue sections, captured cells can be mounted directly onto a MALDI target following microdissection thereby maintaining the spatial conformation for IMS (72). DNA- and RNA-based molecular methods have limitations to show tumor heterogeneity since spatial integrity is destroyed during the preparation process of the nucleic acids.

The potential application of MALDI IMS in a clinical workflow has been suggested by Caprioli (96) who stated in 2005 that this method may aid in diagnosis, prognosis and therapy of cancer bringing a new dimension of molecular information into pathological assessment of tissue specimen.

Today, nearly 10 years later, MALDI IMS is considered a powerful technique to evaluate tumor margins, and to acquire information on tumor typing, grading, prognosis and prediction.

MALDI IMS is an objective method to demonstrate molecular tumor margins (resection borders). This was first proposed by Chaurand et al (97). Evidence has shown that adjacent tissue that appears histologically normal may already be molecularly compromised. For example, it has been shown in tumors of the ovary that MALDI analysis could detect two interface-specific proteins, plastin 2 and peroxiredoxin 1 as differentially expressed in the interface zones between tumors and normal tissues, suggesting these proteins as predictive markers for the presence of residual disease (98). Another study on tumor margins was conducted on kidney samples by Oppenheimer et al (44). These authors demonstrated that cells without phenotypic characteristics of tumor cells, have malignant molecular features. Specifically, mass spectral profiles were compared among four different regions of tissue consisting of tumor, margin-tumor, margin-normal and normal. Two statistical methods, the significance analysis of microarrays (SAM) and permutation t-test, were used in this work demonstrating the presence of patterns resembling tumor in the margin-normal microenvironment outside of the histological tumor border. For example, proteins involved in the mitochondrial electron transport system were consistently underexpressed in the tumor as well as in the histologically normal tissue adjacent to the tumor. Another application of MALDI MS dealing with surgical tumor margins has been shown on liver tissue (99). These investigators detected molecular signatures as classifiers of non-tumor and tumor regions that could be applied to the interface between normal liver tissue and hepatocellular carcinoma.

Thus, a potential advantage of IMS for the evaluation of tumor margins is the ability to identify molecular changes that are not detectable by histopathological evaluation alone (47).

Numerous antibodies are often required for the correct diagnosis of a tumor. In the future, pathologists will be confronted more frequently with small biopsies since minimally invasive methods have been emerged in the past. Hence, effective and tissue sparing molecular techniques are important for correct classification of tumors. Despite the introduction of multi-antibody stains in immunohistochemistry, numerous tissue sections are often required for tumor typing. Since only one tissue section is needed when MALDI IMS is applied, this technique is perfect for the evaluation of very small tissue samples, and the remaining tissue is available for further molecular classification such as mutation screening (e.g. in lung tumors).

The combination of MALDI IMS for tumor classification with typing, grading and subsequent application of MALDI TOF techniques for mutation screening would be a very fast, sensitive and cost efficient workflow able to reduce human bias.

Published results indicate that MALDI IMS has the potential to develop into a valuable diagnostic technique that can complement established histological and histochemical as well as immunohistochemical methods. Biomarkers or signal classifiers can be robustly reproduced in different biomedical centers (73).

MALDI IMS for tumor typing has been demonstrated on frozen (13) as well as on FFPE tissue (16,67). It has been shown that classification of 6 common tumor entities was possible using frozen tissue sections (13). Furthermore, squamous carcinoma and adenocarcinoma of the lung (67), papillary and clear cell renal cancer (15) and gastric carcinoma (16) have been subclassified.

MALDI IMS has been successfully used to identify subsets of markers that correlate with cancer progression in several cancers including non-small cell lung cancer (76) and pre-invasive bronchial lesions (43), brain tumors (21,101), breast (58), ovarian (102), renal cancer (15), Barrett’s adenocarcinoma (103), intestinal-type gastric cancer (78), prostate carcinoma (104) lymph node metastasis of melanoma (105), prostate cancer (82), colonic cancer (13), papillary thyroid carcinoma (14) and urothelial neoplasia (106).

The accuracy to discriminate normal, pre-invasive and invasive lung tissues obtained by MALDI IMS was >90% (43).

MS studies have also been used to determine tumor grading. In myxoid sarcomas high-grade tumors could be separated from low-grade tumors. Likewise, MS/MS technique revealed signals specific for poorly differentiated gastric cancer (16).

Additionally, proteomic tissue profiling improved the grading of non-invasive papillary urothelial neoplasia (106). Variation in the protein expression pattern of low-grade and high-grade gliomas could also be demonstrated (107,108).

Besides grading, IMS has been employed to identify early stage disease (79) as well as predictive proteomic signatures for lymph node metastasis in gastric cancer (109). Since hypoxia is related to poor survival and increased frequency of metastasis, one study investigated hypoxia associated protein-patterns and identified around 100 proteins that may serve as prognostic markers (81). Notably, one group could also show MALDI IMS as a tool to identify peptide signals to predict tumor response to molecular targeted therapy in a breast cancer mouse model (110). All of these applications have a great potential to find their way into routine diagnostics, as methods are needed that reduce human bias.

IMS has been used to study drug localization in human tissues as well as in animal models (54,111–119). The visualization and quantitative analysis of the native drug distribution by IMS techniques with enhanced resolution and sensitivity is desirable for evaluating drug effects and optimizing drug design as it has been shown for paclitaxel in tumor-bearing mice (118). Fresh frozen tumor sections from mice bearing BxPC3 pancreatic cancer xenografts, were analyzed by MALDI IMS and LC-MS after paclitaxel (PTX)-incorporating micelle (NK105) administration (50 or 100 mg/kg) at various time-points (15 min, 1, 24, 48 and 72 h). These sections were compared with tumor sections from mice treated with PTX alone at the same time-points as well as untreated mice. MALDI IMS demonstrated that NK105 successfully delivered a large amount of the PTX within the tumor tissue after NK105 injection compared with PTX injection alone. Quantification of PTX and NK105 were evaluated by LC-MS analysis of the extracted drugs from serial tissue sections for MALDI IMS. The content of the PTX released from NK105 was significantly higher and retained for a longer period of time than the free PTX and control (untreated), suggesting that the antitumor activity of NK105 is superior to that of PTX alone. The high sensitivity and selectivity of IMS combined with visualization of molecular spatial distribution in tissue provides a valuable platform in targeted drug and untargeted metabolomic analysis in biological and clinical research (115). IMS is useful in the comparison of different ways of drug delivery to organs and tissues (120).

Another application is the identification of drugs and their metabolites in the primary or metastatic tumor tissue (112). Furthermore, IMS allowed the characterization of the distribution of small molecules in the microenvironment of tissue compartments of tumors isolated from lung cancer patients and rat xenograft tissues (111). Three experimental models were described in the present study for measuring drug localization. In the ‘concentration gradient model’, an entire solid xenograft tumor (lung adenocarcinoma A549) tissue was immersed in a solution of the drug mixture containing tiotropium and erlotinib for 2.5 h. A passive transfer of the drug mixture into solid tissue samples displayed a decreasing concentration gradient toward the center of the tissue. In this model investigators wanted to show the efficiency of transport of drugs through various cell types. For example, the signal intensity of drugs from tumor cells was substantially lower than that from stroma. In the ‘dispersion model’, 10-μm tissue section of resected lung adenocarcinoma specimens were immersed into the drug solution, where either adsorption or adsorption/absorption occurred. In this model, the distribution of erlotinib localized well to the area of tumor cells identified by the pathologist. Finally, in the ‘directed dosage model’ a drug solution was evenly deposited in small spots (~150 μm in diameter) on the tissue surface of adenocarcinoma tumors using a microdispenser-based spotter apparatus. As in the previous model, the localization of erlotinib was found in tumor areas.

As tumor tissue can be resected during the course of therapy, IMS is suitable for the evaluation of treatment efficacy and the therapy may be optimized (113).

To enable readers of the present review a fast overview on application of MALDI IMS to tumor tissue, Table I provides a brief summary of the different studies and findings.

MALDI IMS is a versatile technique which had been applied to various organisms including plants, animals and human tissue. In human tissue and cells, tumor-associated alterations were studied in various entities. MALDI IMS may improve exact determination of tumor margins, tumor typing, grading and prognosis and could have therapeutic implications.

Diagnostic procedures in pathology are based on histology, histochemistry, immunohistochemistry and molecular pathology and will include proteomic techniques like MALDI IMS to improve diagnostic accuracy.

MALDI IMS will extend or replace histochemical techniques such as periodic acid-Schiff- and Prussian blue-reaction as well as methods that highlight connective tissue compounds as Masson’s trichrome reaction. Additionally, we foresee that immunohistochemical methods will be at least partly replaced by IMS. This is of great importance, especially if molecular testing is required for diagnostics and only small tissue biopsies are available for such tests. In this regard, MALDI IMS requires only one tissue section for the analysis, thus adequate remaining tissue is available for additional molecular testing. In this scenario, elaborate molecular testing of DNA and RNA alterations will be performed either by next generation sequencing or by mass spectrometric techniques. Applications of IMS in the clinic are growing as this technology has proved its feasibility and versatility. The implementation of biocomputational tools combined with IMS will allow biostatistical evaluation for determination of molecular signals able to type or grade tumors and will provide information about prognosis. Furthermore, drug distribution in different tissue types and cellular components may be monitored by IMS. To ensure similar sample preparation and processing, robust standard operating procedures need to be developed for the application of IMS in routine histopathology. Quality control will be achieved by interlaboratory validation as well as by sharing large databases of MALDI signatures of tumors or other diseases.