Tumor classification of six common cancer types based on proteomic profiling by MALDI imaging

In clinical diagnostics, it is of outmost importance to correctly identify the source of a metastatic tumor, especially if no apparent primary tumor is present. Tissue-based proteomics might allow correct tumor classification. As a result, we performed MALDI imaging to generate proteomic signatures for different tumors. These signatures were used to classify common cancer types. At first, a cohort comprised of tissue samples from six adenocarcinoma entities located at different organ sites (esophagus, breast, colon, liver, stomach, thyroid gland, n = 171) was classified using two algorithms for a training and test set. For the test set, Support Vector Machine and Random Forest yielded overall accuracies of 82.74 and 81.18%, respectively. Then, colon cancer liver metastasis samples (n = 19) were introduced into the classification. The liver metastasis samples could be discriminated with high accuracy from primary tumors of colon cancer and hepatocellular carcinoma. Additionally, colon cancer liver metastasis samples could be successfully classified by using colon cancer primary tumor samples for the training of the classifier. These findings demonstrate that MALDI imaging-derived proteomic classifiers can discriminate between different tumor types at different organ sites and in the same site.

SNP array profiling of childhood adrenocortical tumors reveals distinct pathways of tumorigenesis and highlights candidate driver genes

Childhood adrenocortical tumors (ACT) are rare malignancies, except in southern Brazil, where a higher incidence rate is associated to a high frequency of the founder R337H TP53 mutation. To date, copy number alterations in these tumors have only been analyzed by low-resolution comparative genomic hybridization.

A proteome signature for intrauterine growth restriction derived from multifactorial analysis of mass spectrometry-based cord blood serum profiling

Intrauterine growth restriction (IUGR) is defined as a condition in which the fetus does not reach its genetically given growth potential, resulting in low birth weight. IUGR is an important cause of perinatal morbidity and mortality, thus contributing substantially to medically indicated preterm birth in order to prevent fetal death. We subjected umbilical cord blood serum samples either belonging to the IUGR group (n = 15) or to the control group (n = 15) to fractionation by affinity chromatography using a bead system with hydrophobic interaction capabilities. So prepared protein mixtures were analyzed by MALDI-TOF mass spectrometric profiling. The six best differentiating ion signals at m/z 8205, m/z 8766, m/z 13 945, m/z 15 129, m/z 15 308, and m/z 16 001 were collectively assigned as IUGR proteome signature. Separation confidence of our IUGR proteome signature reached a sensitivity of 0.87 and a specificity of 0.93. Assignment of ion signals in the mass spectra to specific proteins was substantiated by SDS-PAGE in conjunction with peptide mass fingerprint analysis of cord blood serum proteins. One constituent of this proteome signature, apolipoprotein C-III(0) , a derivative lacking glycosylation, has been found more abundant in the IUGR cord blood serum samples, irrespective of gestational age. Hence, we suggest apolipoprotein C-III(0) as potential key-marker of the here proposed IUGR proteome signature, as it is a very low-density lipoprotein (VLDL) and high-density lipoprotein (HDL) member and as such involved in triglyceride metabolism that itself is discussed as being of importance in IUGR pathogenesis. Our results indicate that subtle alterations in protein glycosylation need to be considered for improving our understanding of the pathomechanisms in IUGR.

Urinary metabolite profiling reveals CYP1A2-mediated metabolism of NSC686288 (aminoflavone)

NSC686288 [aminoflavone (AF)], a candidate chemotherapeutic agent, possesses a unique antiproliferative profile against tumor cells. Metabolic bioactivation of AF by drug-metabolizing enzymes, especially CYP1A monooxygenases, has been implicated as an underlying mechanism for its selective cytotoxicity in several cell culture-based studies. However, in vivo metabolism of AF has not been investigated in detail. In this study, the structural identities of 13 AF metabolites (12 of which are novel) in mouse urine or from microsomal incubations, including three monohydroxy-AFs, two dihydroxy-AFs and their sulfate and glucuronide conjugates, as well as one N-glucuronide, were determined by accurate mass measurements and liquid chromatography-tandem mass spectrometry fragmentation patterns, and a comprehensive map of the AF metabolic pathways was constructed. Significant differences between wild-type and Cyp1a2-null mice, within the relative composition of urinary metabolites of AF, demonstrated that CYP1A2-mediated regioselective oxidation was a major contributor to the metabolism of AF. Comparisons between wild-type and CYP1A2-humanized mice further revealed interspecies differences in CYP1A2-mediated catalytic activity. Incubation of AF with liver microsomes from all three mouse lines and with pooled human liver microsomes confirmed the observations from urinary metabolite profiling. Results from enzyme kinetic analysis further indicated that in addition to CYP1A P450s, CYP2C P450s may also play some role in the metabolism of AF.

Gene expression profiling reveals consistent differences between clinical samples of human leukaemias and their model cell lines

Microarray gene expression profiles of fresh clinical samples of chronic myeloid leukaemia in chronic phase, acute promyelocytic leukaemia and acute monocytic leukaemia were compared with profiles from cell lines representing the corresponding types of leukaemia (K562, NB4, HL60). In a hierarchical clustering analysis, all clinical samples clustered separately from the cell lines, regardless of leukaemic subtype. Gene ontology analysis showed that cell lines chiefly overexpressed genes related to macromolecular metabolism, whereas in clinical samples genes related to the immune response were abundantly expressed. These findings must be taken into consideration when conclusions from cell line-based studies are extrapolated to patients.

Dental CT imaging as a screening tool for dental profiling: advantages and limitations

The use of dental processing software for computed tomography (CT) data (Dentascan) is described on postmortem (pm) CT data for the purpose of pm identification. The software allows reconstructing reformatted images comparable to conventional panoramic dental radiographs by defining a curved reconstruction line along the teeth on oblique images. Three corpses that have been scanned within the virtopsy project were used to test the software for the purpose of dental identification. In every case, dental panoramic images could be reconstructed and compared to antemortem radiographs. The images showed the basic component of teeth (enamel, dentin, and pulp), the anatomic structure of the alveolar bone, missing or unerupted teeth as well as restorations of the teeth that could be used for identification. When streak artifacts due to metal-containing dental work reduced image quality, it was still necessary to perform pm conventional radiographs for comparison of the detailed shape of the restoration. Dental identification or a dental profiling seems to become possible in a noninvasive manner using the Dentascan software.

Profiling of alterations in platelet proteins during storage of platelet concentrates

BACKGROUND: The quality of platelet concentrates (PCs) is primarily determined in vitro by selective methods (e.g., pH, aggregometry), which provide only limited information on certain platelet (PLT) characteristics. In contrast, proteomic technologies provide a comprehensive overview of the PLT proteome. High interassay variability, however, limits meaningful assessment of samples taken from the same product over time or before and after processing. STUDY DESIGN AND METHODS: Differential in-gel electrophoresis (DIGE) and mass spectrometry were applied to analyze changes in the PLT proteome during storage of PCs. RESULTS: DIGE provides a comprehensive and reproducible overview of the cytoplasmic PLT proteome (median standard deviation of protein spot intensities, 5%-9%). Although 97 percent of cytosolic PLT proteins remained unchanged over a 9-day storage period, septin 2 showed characteristic alterations that preceded by several days more widespread alterations affecting numerous other proteins. Also beta-actin and gelsolin are potential marker proteins for changes in the PLT proteome. Interestingly septin 2 and gelsolin are affected during apoptosis, indicating that apoptosis in PCs may have an impact on PLT storage. CONCLUSION: DIGE is a tool for comprehensively assessing the impact of storage on the global proteome profile of therapeutic PCs. Most of the changes detected are in high-abundance PLT proteins.

Expression profiling with RNA from formalin-fixed, paraffin-embeeded material

Background Molecular characterization of breast and other cancers by gene expression profiling has corroborated existing classifications and revealed novel subtypes. Most profiling studies are based on fresh frozen (FF) tumor material which is available only for a limited number of samples while thousands of tumor samples exist as formalin-fixed, paraffin-embedded (FFPE) blocks. Unfortunately, RNA derived of FFPE material is fragmented and chemically modified impairing expression measurements by standard procedures. Robust protocols for isolation of RNA from FFPE material suitable for stable and reproducible measurement of gene expression (e.g. by quantitative reverse transcriptase PCR, QPCR) remain a major challenge. Results We present a simple procedure for RNA isolation from FFPE material of diagnostic samples. The RNA is suitable for expression measurement by QPCR when used in combination with an optimized cDNA synthesis protocol and TaqMan assays specific for short amplicons. The FFPE derived RNA was compared to intact RNA isolated from the same tumors. Preliminary scores were computed from genes related to the ER response, HER2 signaling and proliferation. Correlation coefficients between intact and partially fragmented RNA from FFPE material were 0.83 to 0.97. Conclusion We developed a simple and robust method for isolating RNA from FFPE material. The RNA can be used for gene expression profiling. Expression measurements from several genes can be combined to robust scores representing the hormonal or the proliferation status of the tumor.