Identifying prostate carcinoma by MALDI-Imaging

Schwamborn, Kristina; Krieg, René C.; Reska, Marcus; Jakse, G.; Knuechel, Ruth; Wellmann, Axel

doi:10.3892/ijmm.20.2.155

Cited by 102 publications

(127 citation statements)

References 28 publications

Supporting

Mentioning

122

Contrasting

Order By: Relevance

“…Since the concept of directly identifying molecules on tissues using MALDI ion sources was proposed at the end of the 1990s (Caprioli et al 1997), MALDI imaging mass spectrometry has been used in many clinical applications (Cornett et al 2006;El Ayed et al 2010;Lemaire et al 2006a, b;Pevsner et al 2009;Schwamborn et al 2007;Schwartz et al 2004;Seeley and Caprioli 2008). A decade of developments in instrumentation and chemistry has been required to achieve optimal extraction, detection, and spatial resolution when mapping compounds at the tissue level (Franck et al 2009a, b;Lemaire et al 2006a, b;2007a;van Remoortere et al 2010).…”

Section: Introductionmentioning

confidence: 99%

The C-terminal fragment of the immunoproteasome PA28S (Reg alpha) as an early diagnosis and tumor-relapse biomarker: evidence from mass spectrometry profiling

Longuespée

Boyon

Castellier

et al. 2012

Histochem Cell Biol

View full text Add to dashboard Cite

This study reports on the C-terminal fragment of the 11S proteasome activator complex (PA28 or Reg alpha), a novel ovarian-specific biomarker of early and late stages of ovarian cancer (OVC) relapse, in patient biopsies after chemotherapy. A total of 179 tissue samples were analyzed: 8 stage I, 55 stage III-IV, 10 relapsed serous carcinomas, 25 mucinous carcinomas and 12 borderline and 68 benign ovarian tissue samples. This fragment was detected by MALDI mass spectrometry profiling in conjunction with a novel extraction method using hexafluoroisopropanol (1,1,1,3,3,3-hexafluoro-2-propanol; HFIP) solvents for protein solubilization and by immunohistochemistry using a specific antibody directed against the C-terminal fragment of PA28. Due to its specific cellular localization, this fragment is a suitable candidate for early OVC diagnosis, patient prognosis and follow-up during therapy and discriminating borderline cancers. Statistical analyses performed for this marker at different OVC stages reflect a prevalence of 77.66 ± 8.77 % (with a correlation coefficient value p \ 0.001 of 0.601 between OVC and benign tissue). This marker presents a prevalence of 88 % in the case of tumor relapse and is detected at 80.5 % in stage I and 81.25 % ± 1.06 in stage III-IV of OVC. The correlation value for the different OVC stages is p \ 0.001 of 0.998. Taken together, this report constitutes the first evidence of a novel OVC-specific marker.

show abstract

Section: Introductionmentioning

confidence: 99%

The C-terminal fragment of the immunoproteasome PA28S (Reg alpha) as an early diagnosis and tumor-relapse biomarker: evidence from mass spectrometry profiling

Longuespée

Boyon

Castellier

et al. 2012

Histochem Cell Biol

View full text Add to dashboard Cite

show abstract

“…In turn, m/z abundance patterns that discriminate different physiological or pathological conditions might be used as diagnostic or even prognostic markers (13,14). In recent years, MALDI IMS of proteins has been successfully applied to different cancer types from the brain (15), breast (16,17), kidney (18), prostate (19), and skin (20). Furthermore, the technique has been applied in the context of colon inflammation (21), embryonic development (22), Alzheimer's disease (23), and amyotrophic lateral sclerosis (24).…”

Section: Matrix-assisted Laser Desorption/ionization Imaging Mass Spementioning

confidence: 99%

Comprehensive Identification of Proteins from MALDI Imaging

Maier

Hahne

Gholami

et al. 2013

Molecular & Cellular Proteomics

View full text Add to dashboard Cite

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) is a powerful tool for the visualization of proteins in tissues and has demonstrated considerable diagnostic and prognostic value. One main challenge is that the molecular identity of such potential biomarkers mostly remains unknown. We introduce a generic method that removes this issue by systematically identifying the proteins embedded in the MALDI matrix using a combination of bottom-up and top-down proteomics. The analyses of ten human tissues lead to the identification of 1400 abundant and soluble proteins constituting the set of proteins detectable by MALDI IMS including >90% of all IMS biomarkers reported in the literature. Top-down analysis of the matrix proteome identified 124 mostly N-and C-terminally fragmented proteins indicating considerable protein processing activity in tissues. All protein identification data from this study as well as the IMS literature has been deposited into MaTisse, a new publically available database, which we anticipate will become a valuable resource for the IMS community. Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) 1 is an emerging technique that can be described as a multi-color molecular microscope as it allows visualizing the distribution of many molecules as mass to charge (m/z) signals in parallel in situ (1). Originally described some 15 years ago (2) the method has been successfully adapted to different analyte classes including small molecule drugs (3), metabolites (4), lipids (5), proteins (6), and peptides (7) using e.g. formalin fixed paraffin embedded (FFPE) as well as fresh frozen tissue (8). Because the tissue stays intact in the process, MALDI IMS is compatible with histochemistry (9) as well as immunohistochemistry and thus adds an additional dimension of molecular information to classical microscopy based tissue analysis (10). Imaging of proteins is appealing as it conceptually allows determining the localization and abundance of proteoforms (11) that naturally occur in the tissue under investigation including modifications such as phosphorylation, acetylation, or ubiquitination, protease mediated cleavage or truncation (12). Therefore a proteinous m/z species detected by MALDI IMS can be viewed as an in situ molecular probe of a particular biological process. In turn, m/z abundance patterns that discriminate different physiological or pathological conditions might be used as diagnostic or even prognostic markers (13,14). In recent years, MALDI IMS of proteins has been successfully applied to different cancer types from the brain (15), breast (16, 17), kidney (18), prostate (19), and skin (20). Furthermore, the technique has been applied in the context of colon inflammation (21), embryonic development (22), Alzheimer's disease (23), and amyotrophic lateral sclerosis (24). With a few notable exceptions (13, 14, 16 -18, 20, 24 -30), the identity of the proteins constituting the observed characteristic m/z patters has generally remained e...

show abstract

“…This allowed a parallel assessment of the histopathological features seen under the light microscope and the proteome profiles obtained by MALDI imaging. 18,19 Subsequently, non-neoplastic mucosa was marked to allow a better understanding of the molecular images ( Figure 1B; note the presence of muscularis mucosa in the center of the section). Subsequently, mass signals were selected by manual inspection of the data set to match the main visible features of the tissue.…”

Section: Maldi Imaging Analysis Of Selected Sectionsmentioning

confidence: 99%

MALDI Imaging Combined with Hierarchical Clustering as a New Tool for the Interpretation of Complex Human Cancers

et al. 2008

View full text Add to dashboard Cite

Proteomics analyses have been exploited for the discovery of novel biomarkers for the early recognition and prognostic stratification of cancer patients. These analyses have now been extended to whole tissue sections by using a new tool, that is, MALDI imaging. This allows the spatial resolution of protein and peptides and their allocation to histoanatomical structures. Each MALDI imaging data set contains a large number of proteins and peptides, and their analysis can be quite tedious. We report here a new approach for the analysis of MALDI imaging results. Mass spectra are classified by hierarchical clustering by similarity and the resulting tissue classes are compared with the histology. The same approach is used to compare data sets of different patients. Tissue sections of gastric cancer and non-neoplastic mucosa obtained from 10 patients were forwarded to MALDI-Imaging. The in situ proteome expression was analyzed by hierarchical clustering and by principal component analysis (PCA). The reconstruction of images based on principal component scores allowed an unsupervised feature extraction of the data set. Generally, these images were in good agreement with the histology of the samples. The hierarchical clustering allowed a quick and intuitive access to the multidimensional information in the data set. It allowed a quick selection of spectra classes representative for different tissue features. The use of PCA for the comparison of MALDI spectra from different patients showed that the tumor and non-neoplastic mucosa are separated in the first three principal components. MALDI imaging in combination with hierarchical clustering allows the comprehensive analysis of the in situ cancer proteome in complex human cancers. On the basis of this cluster analysis, classification of complex human tissues is possible and opens the way for specific and cancer-related in situ biomarker analysis and identification.

show abstract

Identifying prostate carcinoma by MALDI-Imaging

Cited by 102 publications

References 28 publications

The C-terminal fragment of the immunoproteasome PA28S (Reg alpha) as an early diagnosis and tumor-relapse biomarker: evidence from mass spectrometry profiling

The C-terminal fragment of the immunoproteasome PA28S (Reg alpha) as an early diagnosis and tumor-relapse biomarker: evidence from mass spectrometry profiling

Comprehensive Identification of Proteins from MALDI Imaging

MALDI Imaging Combined with Hierarchical Clustering as a New Tool for the Interpretation of Complex Human Cancers

Contact Info

Product

Resources

About