Search

Background: We hypothesized that a serum proteomic profile predictive of survival benefit in non–small cell lung cancer patients treated with epidermal growth factor receptor tyrosine kinase inhibitors (EGFR-TKI) reflects tumor EGFR dependency regardless of site of origin or class of therapeutic agent.Methods: Pretreatment serum or plasma from 230 patients treated with cetuximab, EGFR-TKIs, or chemotherapy for recurrent/metastatic head and neck squamous cell carcinoma (HNSCC) or colorectal cancer (CRC) were analyzed by mass spectrometry. Each sample was classified into “good” or “poor” groups using VeriStrat, and survival analyses of each cohort were done based on this classification. For the CRC cohort, this classification was correlated with the tumor EGFR ligand levels and KRAS mutation status.Results: In the EGFR inhibitor–treated cohorts, the classification predicted survival (HNSCC: gefitinib, P = 0.007 and erlotinib/bevacizumab, P = 0.02; CRC: cetuximab, P = 0.0065) whereas the chemotherapy cohort showed no survival difference. For CRC patients, tumor EGFR ligand RNA levels were significantly associated with the proteomic classification, and combined KRAS and proteomic classification provided improved survival classification.Conclusions: Serum proteomic profiling can detect clinically significant tumor dependence on the EGFR pathway in non–small cell lung cancer, HNSCC, and CRC patients treated with either EGFR-TKIs or cetuximab. This classification is correlated with tumor EGFR ligand levels and provides a clinically practical way to identify patients with diverse cancer types most likely to benefit from EGFR inhibitors. Prospective studies are necessary to confirm these findings. Cancer Epidemiol Biomarkers Prev; 19(2); 358–65

Supplementary Data from Identification of Markers of Taxane Sensitivity Using Proteomic and Genomic Analyses of Breast Tumors from Patients Receiving Neoadjuvant Paclitaxel and Radiation

Purpose: To identify molecular markers of pathologic response to neoadjuvant paclitaxel/radiation treatment, protein and gene expression profiling were done on pretreatment biopsies.Experimental Design: Patients with high-risk, operable breast cancer were treated with three cycles of paclitaxel followed by concurrent paclitaxel/radiation. Tumor tissue from pretreatment biopsies was obtained from 19 of the 38 patients enrolled in the study. Protein and gene expression profiling were done on serial sections of the biopsies from patients that achieved a pathologic complete response (pCR) and compared to those with residual disease, non-pCR (NR).Results: Proteomic and validation immunohistochemical analyses revealed that α-defensins (DEFA) were overexpressed in tumors from patients with a pCR. Gene expression analysis revealed that MAP2, a microtubule-associated protein, had significantly higher levels of expression in patients achieving a pCR. Elevation of MAP2 in breast cancer cell lines led to increased paclitaxel sensitivity. Furthermore, expression of genes that are associated with the basal-like, triple-negative phenotype were enriched in tumors from patients with a pCR. Analysis of a larger panel of tumors from patients receiving presurgical taxane-based treatment showed that DEFA and MAP2 expression as well as histologic features of inflammation were all statistically associated with response to therapy at the time of surgery.Conclusion: We show the utility of molecular profiling of pretreatment biopsies to discover markers of response. Our results suggest the potential use of immune signaling molecules such as DEFA as well as MAP2, a microtubule-associated protein, as tumor markers that associate with response to neoadjuvant taxane–based therapy. Clin Cancer Res; 16(2); 681–90

Supplementary Tables 1-4 from Lung Cancer Diagnosis from Proteomic Analysis of Preinvasive Lesions

Supplementary Figure 2 from Lung Cancer Diagnosis from Proteomic Analysis of Preinvasive Lesions

Supplementary Methods, Figure Legends 1-3 from Lung Cancer Diagnosis from Proteomic Analysis of Preinvasive Lesions

Early detection may help improve survival from lung cancer. In this study, our goal was to derive and validate a signature from the proteomic analysis of bronchial lesions that could predict the diagnosis of lung cancer. Using previously published studies of bronchial tissues, we selected a signature of nine matrix-assisted laser desorption ionization mass spectrometry (MALDI MS) mass-to-charge ratio features to build a prediction model diagnostic of lung cancer. The model was based on MALDI MS signal intensity (MALDI score) from bronchial tissue specimens from our 2005 published cohort of 51 patients. The performance of the prediction model in identifying lung cancer was tested in an independent cohort of bronchial specimens from 60 patients. The probability of having lung cancer based on the proteomic analysis of the bronchial specimens was characterized by an area under the receiver operating characteristic curve of 0.77 (95% CI 0.66–0.88) in this validation cohort. Eight of the nine features were identified and validated by Western blotting and immunohistochemistry. These results show that proteomic analysis of endobronchial lesions may facilitate the diagnosis of lung cancer and the monitoring of high-risk individuals for lung cancer in surveillance and chemoprevention trials. Cancer Res; 71(8); 3009–17. ©2011 AACR.

Supplementary Figure 1 from Lung Cancer Diagnosis from Proteomic Analysis of Preinvasive Lesions

Supplementary Figure 3 from Lung Cancer Diagnosis from Proteomic Analysis of Preinvasive Lesions

Impairments in carbohydrate, lipid, and amino acid metabolism drive features of plaque instability. However, where these impairments occur within the atheroma remains largely unknown. Therefore, we sought to characterize the spatial distribution of metabolites within stable and unstable atherosclerosis in both the fibrous cap and necrotic core. Atherosclerotic tissue specimens were scored based on the Stary classification scale and subdivided into stable and unstable atheromas. After performing mass spectrometry imaging (MSI) on these samples, we identified over 850 metabolite-related peaks. Using MetaboScape, METASPACE, and HMDB, we confidently annotated 170 of these metabolites and found over 60 of these were different between stable and unstable atheroma. We then integrated these results with an RNA-sequencing dataset comparing stable and unstable human atherosclerosis. Upon integrating our MSI results with the RNA-seq dataset, we discovered that pathways related to lipid metabolism and long-chain fatty acids were enriched in stable plaques, whereas reactive oxygen species, aromatic amino acid, and tryptophan metabolism were increased in unstable plaques. Acylcarnitines and acylglycines were increased in stable plaques whereas tryptophan metabolites were enriched in unstable plaques. Evaluating spatial differences in stable plaques revealed lactic acid in the necrotic core, whereas pyruvic acid was elevated in the fibrous cap. In unstable plaques, 5-hydroxyindole-acetic acid was enriched in the fibrous cap. Our work herein represents the first step to defining an atlas of metabolic pathways involved in plaque destabilization in human atherosclerosis. We anticipate this will be a valuable resource and open new avenues of research in cardiovascular disease.GRAPHICAL ABSTRACT

Background Differentiation of lymphocytic-plasmacytic enteropathy (LPE) from small cell lymphoma (SCL) in cats can be challenging. Hypothesis/objective Histology-guided mass spectrometry (HGMS) is a suitable method for the differentiation of LPE from SCL in cats. Animals Forty-one cats with LPE and 52 cats with SCL. Methods This is a retrospective clinicopathologic study. Duodenal tissue samples of 17 cats with LPE and 22 cats with SCL were subjected to HGMS, and the acquired data were used to develop a linear discriminate analysis (LDA) machine learning algorithm. The algorithm was subsequently validated using a separate set of 24 cats with LPE and 30 cats with SCL. Cases were classified as LPE or SCL based on a consensus by an expert panel consisting of 5-7 board-certified veterinary specialists. Histopathology, immunohistochemistry, and clonality testing were available for all cats. The panel consensus classification served as a reference for the calculation of test performance parameters. Results Relative sensitivity, specificity, and accuracy of HGMS were 86.7% (95% confidence interval [CI]: 74.5%-98.8%), 91.7% (95% CI: 80.6%-100%), and 88.9% (95% CI: 80.5%-97.3%), respectively. Comparatively, the clonality testing had a sensitivity, specificity, and accuracy of 85.7% (95% CI: 72.8%-98.7%), 33.3% (95% CI: 14.5%-52.2%), and 61.5% (95% CI: 48.3%-74.8%) relative to the panel decision. Conclusions and clinical importance Histology-guided mass spectrometry was a reliable technique for the differentiation of LPE from SCL in duodenal formalin-fixed paraffin-embedded samples of cats and might have advantages over tests currently considered state of the art.

Mass spectrometry imaging provides a powerful approach for the direct analysis and spatial visualization of molecules in tissue sections. Using matrix-assisted laser desorption/ionization mass spectrometry, intact protein imaging has been widely investigated for biomarker analysis and diagnosis in a variety of tissue types and diseases. However, blood-rich or highly vascular tissues present a challenge in molecular imaging due to the high ionization efficiency of hemoglobin, which leads to ion suppression of endogenous proteins. Here, we describe a protocol to selectively reduce hemoglobin signal in blood-rich tissues that can easily be integrated into mass spectrometry imaging workflows.

Post-translational O-glycosylation of proteins via the addition of N-acetylglucosamine (O-GlcNAc) is a regulator of many aspects of cellular physiology. Processes driven by perturbed dynamics of O-GlcNAcylation modification have been implicated in cancer development. Variability in O-GlcNAcylation is emerging as a metabolic biomarker of many cancers. Here, we evaluate the use of MALDI-mass spectrometry imaging (MSI) to visualize the location of O-GlcNAcylated proteins in tissue sections by mapping GlcNAc that has been released by the enzymatic hydrolysis of glycoproteins using an O-GlcNAc hydrolase. We use this strategy to monitor O-GlcNAc within hepatic VX2 tumor tissue. We show that increased O-GlcNAc is found within both viable tumor and tumor margin regions, implicating GlcNAc in tumor progression.

Purpose Distinguishing benign nevi from malignant melanoma using current histopathological criteria may be very challenging and is one the most difficult areas in dermatopathology. The goal of this study was to identify proteomic differences, which would more reliably differentiate between benign and malignant melanocytic lesions. Methods We performed histolpathology - guided mass spectrometry (HGMS) profiling analysis on formalin-fixed, paraffin embedded tissue samples to identify differences at the proteomic level between different types of benign nevi and melanomas. A total of 756 cases, of which 357 cases of melanoma and 399 benign nevi, were included in the study. The specimens originated from both biopsies (376 samples) and tissue microarray (TMA) cores (380 samples). After obtaining mass spectra from each sample, classification models were built using a training set of biopsy specimens from 111 nevi and 100 melanomas. The classification algorithm developed on the training data set was validated on an independent set of 288 nevi and 257 melanomas from both biopsies and TMA cores. Results In the melanoma cohort, 239/257 (93%) cases classified correctly in the validation set, 3/257 (1.2%) classified incorrectly, and 15/257 (5.8%) classified as indeterminate. In the cohort of nevi, 282/288 (98%) cases classified correctly, 1/288 (0.3%) classified incorrectly, and 5/288 (1.7%) were indeterminate. HGMS showed a sensitivity of 98.76% and specificity of 99.65% in determining benign vs malignant. Conclusion HGMS proteomic analysis is an objective and reliable test with minimal tissue requirements, which can be a helpful ancillary test in the diagnosis of challenging melanocytic lesions.

Intra-tumor heterogeneity (ITH) of human tumors is important for tumor progression, treatment response, and drug resistance. However, the spatial distribution of ITH remains incompletely understood. Here, we present spatial analysis of ITH in lung adenocarcinomas from 147 patients using multi-region mass spectrometry of5,000 regions, single-cell copy number sequencing of ~2,000 single cells, and cyclic immunofluorescence of10 million cells. We identified two distinct spatial patterns among tumors, termed clustered and random geographic diversification (GD). These patterns were observed in the same samples using both proteomic and genomic data. The random proteomic GD pattern, which is characterized by decreased cell adhesion and lower levels of tumor-interacting endothelial cells, was significantly associated with increased risk of recurrence or death in two independent patient cohorts. Our study presents comprehensive spatial mapping of ITH in lung adenocarcinoma and provides insights into the mechanisms and clinical consequences of GD.

Primary liver cancer, or hepatocellular carcinoma (HCC), is a major worldwide cause of death from carcinoma. Most patients are not candidates for surgery and medical therapies, including new immunotherapies, have not shown major improvements since the modest benefit seen with the introduction of sorafenib over a decade ago. Locoregional therapies for intermediate stage disease are not curative but provide some benefit. However, upon close scrutiny, there is still residual disease in most cases. We review the current status for treatment of intermediate stage disease, summarize the literature on correlative histopathology, and discuss emerging methods at micro-, nano-, and pico-scales to improve therapy. These include transarterial hyperthermia methods and thermoembolization, along with microfluidics model systems and new applications of mass spectrometry imaging for label-free analysis of pharmacokinetics and pharmacodynamics.

Mass spectrometry imaging can be successfully used for skin cancer diagnosis, particularly for the diagnosis of challenging melanocytic lesions. This method analyzes proteins within benign and malignant melanocytic tumor cells and, based on their differences, which constitute a unique molecular signature of 5 to 20 proteins, can render a diagnosis of benign nevus versus malignant melanoma. Mass spectrometry imaging may assist in the differentiation between metastases and nevi as well as between proliferative nodules in nevi and melanoma arising in a nevus. In the difficult area of atypical Spitzoid neoplasms, mass spectrometry diagnosis can predict clinical outcome better than histopathology.

Histopathological interpretation of proliferative nodules occurring in association with congenital melanocytic nevi can be very challenging due to their similarities with congenital malignant melanoma and malignant melanoma arising in association with congenital nevi. We hereby report a diagnostically challenging case of congenital melanocytic nevus with proliferative nodules and ulcerations, which was originally misdiagnosed as congenital malignant melanoma. Subsequent histopathological examination in consultation by one of the authors (R.L.) and mass spectrometry imaging analysis rendered a diagnosis of congenital melanocytic nevus with proliferative nodules. In this case, mass spectrometry imaging, a novel method capable of distinguishing benign from malignant melanocytic lesions on a proteomic level, was instrumental in making the diagnosis of a benign nevus. We emphasize the importance of this method as an ancillary tool in the diagnosis of difficult melanocytic lesions.

A 37-year-old pregnant woman presented with a 2-cm irregular reddish nodule on her left upper arm during pregnancy. A biopsy from the lesion showed a 2.2-mm thick malignant melanoma with intravascular invasion, 25 mitosis/mm(2) and no ulceration. Following induction of labor, the patient underwent re-excision with sentinel lymph node biopsy. This showed no residual melanoma and no lymph node metastasis. The newborn boy had multiple pigmented lesions on the trunk, some of which were large and irregular. Two were biopsied and histologic examination showed dense dermal proliferation of medium sized melanocytes with multiple mitotic figures and no maturation with their descent into the dermis, raising suspicion of transplacental metastases. Examination of the placenta failed to show metastatic lesions. Multiplex polymerase chain reaction (PCR)-based genotyping, including testing for amelogenin locus for sex chromosome determination, demonstrated the presence of Y chromosome material in the melanocytes of the newborn's lesions excluding maternal origin. A diagnosis of congenital nevi was rendered. Subsequently, Imaging Mass Spectrometric analysis of the mother's lesion showed proteomic signature expression indicative of malignant melanoma, whereas the two lesions in the newborn showed changes indicative of nevi. This case demonstrates the utility of genotyping and Mass Spectrometry analysis in this challenging clinical scenario.

Background Wilms tumor (WT) is the most common childhood kidney cancer worldwide and arises in children of black African ancestry with greater frequency and severity than other race groups. A biologic basis for this pediatric cancer disparity has not been previously determined. We hypothesized that unique molecular fingerprints might underlie the variable incidence and distinct disease characteristics of WT observed between race groups. Study Design To evaluate molecular disparities between WTs of different race groups, the Children's Oncology Group provided 80 favorable histology specimens divided evenly between black and white patients and matched for disease characteristics. As a surrogate of black sub-Saharan African patients, we also analyzed 18 Kenyan WT specimens. Tissues were probed for peptide profiles using matrix-assisted laser desorption ionization time of flight imaging mass spectrometry. To control for histologic variability within and between specimens, cellular regions were analyzed separately as triphasic (containing blastema, epithelia, and stroma), blastema only, and stroma only. Data were queried using ClinProTools and statistically analyzed. Results Peptide profiles, detected in triphasic WT regions, recognized race with good accuracy, which increased for blastema- or stroma-only regions. Peptide profiles from North American WTs differed between black and white race groups but were far more similar in composition than Kenyan specimens. Individual peptides were identified that also associated with WT patient and disease characteristics (eg, treatment failure and stage). Statistically significant peptide fragments were used to sequence proteins, revealing specific cellular signaling pathways and candidate drug targets. Conclusions Wilms tumor specimens arising among different race groups show unique molecular fingerprints that could explain disparate incidences and biologic behavior and that could reveal novel therapeutic targets.

Purpose To facilitate the transition of MALDI–MS Imaging (MALDI–MSI) from basic science to clinical application, it is necessary to analyze formalin‐fixed paraffin‐embedded (FFPE) tissues. The aim is to improve in situ tryptic digestion for MALDI–MSI of FFPE samples and determine if similar results would be reproducible if obtained from different sites. Experimental Design FFPE tissues (mouse intestine, human ovarian teratoma, tissue microarray of tumor entities sampled from three different sites) are prepared for MALDI–MSI. Samples are coated with trypsin using an automated sprayer then incubated using deliquescence to maintain a stable humid environment. After digestion, samples are sprayed with CHCA using the same spraying device and analyzed with a rapifleX MALDI Tissuetyper at 50 µm spatial resolution. Data are analyzed using flexImaging, SCiLS, and R. Results Trypsin application and digestion are identified as sources of variation and loss of spatial resolution in the MALDI–MSI of FFPE samples. Using the described workflow, it is possible to discriminate discrete histological features in different tissues and enabled different sites to generate images of similar quality when assessed by spatial segmentation and PCA. Conclusions and Clinical Relevance Spatial resolution and site‐to‐site reproducibility can be maintained by adhering to a standardized MALDI–MSI workflow.

Purpose Although Crohn's colitis (CC) and ulcerative colitis (UC) share several clinical features, they have different causes, mechanisms of tissue damage, and treatment options. Therefore, the accurate diagnosis is of paramount importance in terms of medical care. The distinction between CC/UC is made on the basis of clinical, radiologic, endoscopic, and pathologic interpretations but cannot be differentiated in up to 15% of inflammatory bowel disease patients. Correct management of this “indeterminate colitis” depends on the accuracy of future, and yet not known, destination diagnosis (CC/UC). Experimental design We have developed a proteomic methodology that has the potential to discriminate between UC/CC. The histologic layers of 62 confirmed UC/CC tissues were analyzed using MALDI-MS for proteomic profiling. Results A Support Vector Machine algorithm consisting of 25 peaks was able to differentiate spectra from CC and UC with 76.9% spectral accuracy when using a leave-20%-out cross-validation. Application of the model to the entire dataset resulted in accurate classification of 19/26 CC patients and 36/36 UC patients when using a 2/3 correct cutoff. A total of 114 peaks were found to have Wilcoxin rank sum p-values of less than 0.05. Conclusion and clinical relevance This information may provide new avenues for the development of novel personalized therapeutic targets.

Teratogenic effects of polymethylmethacrylate cement at levels used during routine orthopaedic procedures have never been reported, however the hypothetical risk remains a major concern among female surgeons. Our aim was to determine if methyl methacrylate is detectible in the serum during routine cement exposure. Methods: Twenty healthy volunteers were exposed during the mixing of polymethylmethacrylate cement in a simulated operating room environment. Forty serum samples were obtained during the expected peak inhalational exposure and levels of methyl methacrylate were assessed utilizing headspace gas chromatography mass spectrometry. Results: Methyl methacrylate was not detected in any of the forty experimental specimens. Conclusions: With a detection level of 0.5 ppm, methyl methacrylate is undetectable in the serum during routine mixing of polymethylmethacrylate cement.

A key barrier to identifying tissue biomarkers of clear cell renal cell carcinoma is the heterogeneity of protein expression in tissue. However, by providing spectra for every 0.05 mm(2) area of tissue, imaging mass spectrometry reveals the spatial distribution of peptides. We determined whether this approach could be used to identify and map protein signatures of clear cell renal cell carcinoma.We constructed 2 tissue microarrays with 2 cores each of matched tumor and normal tissue from the nephrectomy specimens of 70 patients with clear cell renal cell carcinoma. Samples were analyzed by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry. In each tissue microarray peptide signatures were identified that differentiated cancer from normal tissue. The signatures were then cross validated. Mass spectrometry/mass spectrometry sequencing was performed to determine the identity of select, differentially expressed peptides. Immunohistochemistry was used for validation.In each tissue microarray peptide signatures were identified that had 94.7% to 98.5% classification accuracy for each 0.05 mm(2) spot (spectrum) and 96.9% to 100% accuracy for each tissue core. Cross validation across tissue microarrays revealed a classification accuracy of 82.6% to 84.7% for each spot and 88.9% to 92.4% for each core. We identified vimentin, histone 2A.X and α-enolase as proteins with greater expression in cancer tissue. This was validated by immunohistochemistry.Imaging mass spectrometry identified and mapped specific peptides that accurately distinguished malignant from normal renal tissue. This demonstrates its potential as a novel, high throughput approach to clear cell renal cell carcinoma biomarker discovery. Given the multiple pathways and known heterogeneity involved in tumors such as clear cell renal cell carcinoma, multiple peptide signatures that maintain their spatial relationships may outperform traditional protein biomarkers.

BACKGROUND: Previously, using imaging mass spectrometry (IMS), we discovered proteomic differences between Spitz nevi and Spitzoid melanomas. OBJECTIVE: We sought to determine whether IMS can assist in the classification of diagnostically challenging atypical Spitzoid neoplasms (ASN), to compare and correlate the IMS and histopathological diagnoses with clinical behavior. METHODS: We conducted a retrospective collaborative study involving centers from 11 countries and 11 US institutions analyzing 102 ASNs by IMS. Patients were divided into clinical groups 1 to 4 representing best to worst clinical behavior. The association among IMS findings, histopathological diagnoses, and clinical groups was assessed. RESULTS: There was a strong association between a diagnosis of Spitzoid melanoma by IMS and lesions categorized as clinical groups 2, 3, and 4 (recurrence of disease, metastases, or death) compared with clinical group 1 (no recurrence or metastasis beyond a sentinel node) (P < .0001). Older age and greater tumor thickness were strongly associated with poorer outcome (P = .01). CONCLUSIONS: IMS diagnosis of ASN better predicted clinical outcome than histopathology. Diagnosis of Spitzoid melanoma by IMS was strongly associated with aggressive clinical behavior. IMS analysis using a proteomic signature may improve the diagnosis and prediction of outcome/risk stratification for patients with ASN.

The pathogenesis of idiopathic pulmonary hypertension is poorly understood. This paper utilized histology-based Matrix-Assisted Laser Desorption Ionization Mass Spectrometry (MALDI MS) to identify as-yet unknown proteins that may be associated with the structural changes in the pulmonary arterial walls of patients with IPAH. The technology identified significant increases in two fragments of histone H1 in the IPAH cases compared to controls. This finding was further examined using immunofluorescence techniques applied to sections from IPAH and control pulmonary arteries. In addition, cultured pulmonary artery smooth muscle cells (PASMCs) were utilized for Western analysis of histone H1 and importin β and importin 7, immunoprecipitation and assessment of nucleosomal repeat length (NRL). Immunofluorescence techniques revealed that nuclear expression of histone H1 was decreased and the chromatin was less compact in the IPAH cases than in the controls; furthermore, some cases showed a marked increase in cytoplasmic histone H1 expression. Using nuclear and cytoplasmic fractions of cultured PASMCs, we confirmed the reduction in histone H1 in the nucleus and an increase in the cytoplasm in IPAH cells compared to controls. Immunoprecipitation demonstrated a decreased association of histone H1 with importin β while importin 7 was unchanged in the IPAH cells compared to controls. The assessment of NRL revealed that the distance between nucleosomes was increased by ~20 bp in IPAH compared to controls. We conclude that at least two factors contribute to the reduction in nuclear histone H1-fragmentation of the protein and decreased import of histone H1 into the nucleus by importins. We further suggest that the decreased nuclear H1 contributes the less compact nucleosomal pattern in IPAH and this, in turn, contributes to the increase in NRL.

To identify and image protein biomarker candidates in the synovial tissue of patients with rheumatoid arthritis (RA) and patients with osteoarthritis (OA).A novel matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) technique was applied to the analysis of synovial tissue. Patients were classified according to the American College of Rheumatology (ACR) criteria for RA. Frozen sections were stained to obtain morphological data. Serial sections were desiccated, and spotted with matrix for MALDI analysis. Ions generated by laser irradiation of the tissue were separated in time, based on their m/z ratio, and were subsequently detected. IMS was used in a 'profiling' mode to detect discrete spots for rapid evaluation of proteomic patterns in various tissue compartments. Photomicrographs of the stained tissue images were reviewed by a pathologist. Areas of interest (10 discrete areas/compartment) were marked digitally and the histology-annotated images were merged to form a photomicrograph of the section taken before the MALDI measurement. Pixel coordinates of these areas were transferred to a robotic spotter, the matrix was spotted, and the coordinates of the spots were transferred to a mass spectrometer for spectral acquisition. The data generated were then subjected to biocomputation analysis to reveal the biomarker candidates.Several peaks (m/z) consistent in mass with calgranulins, defensins, and thymosins were detected and their distribution in various synovial compartments (synovial lining and sublining layer) was demonstrated.MALDI IMS is a powerful tool for the rapid detection of numerous proteins (in situ proteomics) and was applied here for the analysis of the distribution of proteins in synovial tissue sections.

Sub-Saharan African children have an increased incidence of Wilms' tumor (WT) and experience alarmingly poor outcomes. Although these outcomes are largely due to inadequate therapy, we hypothesized that WT from this region exhibits features of biological aggressiveness that may warrant broader implementation of high-risk therapeutic protocols. We evaluated 15 Kenyan WT (KWT) for features of aggressive disease (blastemal predominance and Ki67/cellular proliferation) and treatment resistance (anaplasia and p53 immunopositivity). To explore the additional biological features of KWT, we determined the mutational status of the CTNNB1/β-catenin and WT1 genes and performed immunostaining for markers of Wnt pathway activation (β-catenin) and nephronic progenitor cell self-renewal (WT1, CITED1 and SIX2). We characterized the proteome of KWT using imaging mass spectrometry (IMS). The results were compared to histology- and age-matched North American WT (NAWT) controls. For patients with KWT, blastemal predominance was noted in 53.3% and anaplasia in 13%. We detected increased loss to follow-up (p = 0.028), disease relapse (p = 0.044), mortality (p = 0.001) and nuclear unrest (p = 0.001) in patients with KWT compared to controls. KWT and NAWT showed similar Ki67/cellular proliferation. We detected an increased proportion of epithelial nuclear β-catenin in KWT (p = 0.013). All 15 KWT specimens were found to harbor wild-type CTNNB1/β-catenin, and one contained a WT1 nonsense mutation. WT1 was detected by immunostaining in 100% of KWT, CITED1 in 80% and SIX2 in 80%. IMS revealed a molecular signature unique to KWT that was distinct from NAWT. The African WT specimens appear to express markers of adverse clinical behavior and treatment resistance and may require alternative therapies or implementation of high-risk treatment protocols.

Background Wilms tumor (WT) is thought to arise in children of Black African ancestry with greater frequency than in Whites. To clarify the biological basis for race disparities in WT, we first verified that Black children residing in Tennessee have an increased incidence of WT, and second, established molecular profiles in WT that are specific to race. Materials and Methods To assess race disparities in WT epidemiology, the Tennessee Cancer Registry (TCR) was queried for all in-state patients less than 20 y of age and registered between 1999 and 2008. To explore race disparities in WT biology, six Black and four White WT specimens acquired in Tennessee were analyzed using imaging mass spectrometry (IMS). Results TCR data show that Black children are over-represented among WT patients (29%) relative to all other childhood cancers (18.5%; P = 0.01). WT ranked the fifth most common cancer diagnosis among Blacks, but ninth among Whites. The diagnosis of WT occurred 79% more frequently among Blacks ( n = 28) than Whites ( n = 69; P = 0.01), and proportionally more Blacks tended to present with distant disease. Although overall survival from WT was not statistically different between Blacks (92.9%) and Whites (94.0%), Black males showed the lowest survival (85%; P = 0.21). IMS analysis identified peptide spectra from both WT blastema and stroma that independently classify specimens according to race with greater than 80% accuracy. Conclusions In Tennessee, Black children appear more susceptible than Whites to develop WT. Race-specific molecular profiles can be determined that may help to clarify pathways of Wilms tumorigenesis and the biological basis for race disparities in WT incidence and biology.

Differentiating ulcerative colitis (UC) from Crohn's colitis (CC) can be difficult and may lead to inaccurate diagnoses in up to 30% of inflammatory bowel disease (IBD) patients. Much of the diagnostic uncertainty arises from the overlap of clinical and histologic features. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) permits a histology-directed cellular protein analysis of tissues. As a pilot study, we evaluated the ability of histology-directed MALDI-MS to determine the proteomic patterns for potential differences between CC and UC specimens.Mucosal and submucosal layers of CC and UC colon resection samples were analyzed after histologic assessment. To determine whether MALDI-MS would distinguish inflammation, the uninflamed (n = 21) versus inflamed submucosa (n = 22) were compared in UC and the uninflamed (n = 17) versus inflamed submucosa (n = 20) in CC. To determine whether there were proteomic differences between the colitides, the uninflamed UC submucosa (n = 21) was compared versus the uninflamed CC submucosa (n = 17), the inflamed UC submucosa (n = 22) was compared versus the inflamed CC submucosa (n = 20), and inflamed UC mucosa versus inflamed CC mucosa. Pairwise statistics comparisons of the subsets were performed.Pairwise comparative analyses of the clinical groups allowed identifying subsets of features important for classification. Comparison of inflamed versus uninflamed CC submucosa showed two significant peaks: m/z 6445 (P = 0.0003) and 12692 (P = 0.003). In the case of inflamed versus uninflamed UC submucosa, several significant differentiating peaks were found, but classification was worse. Comparisons of the proteomic spectra of inflamed submucosa between UC and CC identified two discrete significant peaks: m/z 8773 (P = 0.006) and 9245 (P = 0.0009). Comparisons of the proteomic spectra of uninflamed submucosa between UC and CC identified three discrete significant peaks: m/z 2778 (P = 0.005), 9232 (P = 0.005), and 9519 (P = 0.005). No significantly different features were found between UC and CC inflamed mucosa.MALDI-MS was able to distinguish CC and UC specimens while profiling the colonic submucosa. Further analyses and protein identification of the differential protein peaks may aid in accurately diagnosing IBD and developing appropriate personalized therapies.

The molecular complexity of biological tissue and the spatial and temporal variation in the biological processes involved in human disease requires new technologies and new approaches in order to provide insight into disease processes. Imaging mass spectrometry is an effective tool that provides molecular images of tissues in the molecular discovery process. The analysis of human tissue presents special challenges and limitations because the heterogeneity among human tissues and diseases is much greater than that observed in animal models, and discoveries made in animal tissues might not translate well to the human counterpart. In this article, we briefly review the challenges of imaging human tissue using mass spectrometry and suggest approaches to address these issues.

Primary biliary cirrhosis (PBC), primary sclerosing cholangitis (PSC) and autoimmune hepatitis (AIH) are the major forms of autoimmune liver diseases each characterized by the destruction of a specific liver cell type and the presence of differing auto-antibodies. We took a proteomic approach utilizing in situ matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS) to obtain profiles directly from liver samples of patients with PBC, PSC, AIH and controls. The ability to precisely localize the region for acquisition of MALDI MS allowed us to obtain profiles from bile ducts, inflammatory infiltrates and hepatocytes from each biopsy sample. Analysis tools developed to identify peaks and compare peaks across diseases and cell types were used to develop models to classify the samples. Using an initial set of testing samples from PBC patients and controls, we identified unique peaks present in bile ducts, inflammatory infiltrates and hepatocytes that could classify samples in a validation cohort with 88-91% accuracy. Interestingly, profiles of PSC and AIH did not differ significantly from PBC. Identification of proteins in these peaks may represent novel autoantigens or effector molecules. These findings illustrate the potential of a proteomic approach to autoimmune diseases with in situ MALDI MS.

12018Background: ALK tyrosine kinase inhibitors (TKIs) yield a significant tumor response in advanced ALK+ non-small cell lung cancer (NSCLC), that is often rapid and remarkable. Nonetheless, acqui...

Imaging MS (IMS) has emerged as a powerful tool for biomarker discovery. A key advantage of this technique is its ability to probe the proteome directly from a tissue section with preservation of the spatial relationships of the sample and minimal sample preparation. This allows for direct correlation of protein expression with histology. Here, we present the latest developments in imaging MS and their relevance to clinical mass spectral analysis. IMS allows for high throughput analysis of tissue samples and is fully compatible with biostatistical analysis without prior knowledge of protein expression. Several studies are presented of applications in which direct tissue mass spectral analysis has provided insight into clinical questions not readily available by other means. Examples include the determination of lymph node status from investigation of primary breast tumors, prediction of response of breast tumors to chemotherapy, classification and prediction of progression of lung lesions, and exploration of 'molecular' margins in invasive disease.

MALDI imaging mass spectrometry (IMS) has become a valuable tool for the investigation of the content and distribution of molecular species in tissue specimens. Numerous methodological improvements have been made to optimize tissue section preparation and matrix deposition protocols, as well as MS data acquisition and processing. In particular for proteomic analyses, washing the tissue sections before matrix deposition has proven useful to improve spectral qualities by increasing ion yields and the number of signals observed. We systematically explore here the effects of several solvent combinations for washing tissue sections. To minimize experimental variability, all of the measurements were performed on serial sections cut from a single mouse liver tissue block. Several other key steps of the process such as matrix deposition and MS data acquisition and processing have also been automated or standardized. To assess efficacy, after each washing procedure the total ion current and number of peaks were counted from the resulting protein profiles. These results were correlated to on-tissue measurements obtained for lipids. Using similar approaches, several selected washing procedures were also tested for their ability to extend the lifetime as well as revive previously cut tissue sections. The effects of these washes on automated matrix deposition and crystallization behavior as well as their ability to preserve tissue histology were also studied. Finally, in a full-scale IMS study, these washing procedures were tested on a human renal cell carcinoma biopsy.

Phenotypic differences between otherwise similar tumors arising from different gynecologic locations may be highly significant in understanding the underlying driver molecular events at each site and may potentially offer insights into differential responses to treatment. In this study, the authors sought to identify and quantify phenotypic differences between ovarian clear cell carcinoma (OCCC) and endometrial clear cell carcinoma (ECCC) using a proteomic approach. Tissue microarrays were constructed from tumor samples of 108 patients (54 ECCCs and 54 OCCCs). Formalin-fixed samples on microarray slides were analyzed by matrix-assisted laser desorption/ionization mass spectrometry, and 730 spectral peaks were generated from the combined data set. A linear mixed-effect model with random intercept was used to generate 93 (12.7%) peaks that were significantly different between OCCCs and ECCCs at the fold cutoffs of 1.5 and 0.667 and an adjusted P value cutoff of 1.0 × 10(-10). Liquid chromatography-tandem mass spectrometry was performed on selected cores from each group, and peptides identified therefrom were compared with lists of statistically significant peaks from the aforementioned linear mixed-effects model to find matches within 0.2 Da. A total of 53 candidate proteins were thus identified as being differentially expressed in OCCCs and ECCCs, 45 (85%) of which were expressed at higher levels in ECCCs than OCCCs. These proteins were functionally diverse and did not highlight a clearly dominant cellular theme or molecular pathway. Although ECCCs and OCCCs are very similar, some phenotypic differences are demonstrable. Additional studies of these differentially expressed proteins may ultimately clarify the significance of these differences.

The 2013 Children's Oncology Group (COG) blueprint for renal tumor research challenges investigators to develop new, risk-specific biological therapies for unfavorable histology and higher-risk Wilms tumor (WT) in an effort to close a persistent survival gap and to reduce treatment toxicities. As an initial response to this call from the COG, we used imaging mass spectrometry to determine peptide profiles of WT associated with adverse outcomes.We created a WT tissue microarray containing 2-mm punches of formalin-fixed, paraffin-embedded specimens archived from 48 sequentially treated WT patients at our institutions. Imaging mass spectrometry was performed to compare peptide spectra between three patient groups as follows: unfavorable versus favorable histology, treatment success versus failure, and COG higher- versus lower-risk disease. Statistically significant peptide peaks differentiating groups were identified and incorporated into a predictive model using a genetic algorithm.One hundred thirty-one peptide peaks were differentially expressed in unfavorable versus favorable histology WT (P0.05). Two hundred three peaks differentiated treatment failure from success (P0.05). Seventy-one peaks differentiated COG higher-risk disease from the very-low, low, and standard-risk groups (P0.05). These peaks were used to develop predictive models that could differentiate among patient groups 98.49%, 94.46%, and 98.55% of the time, respectively. Spectral patterns were internally cross-validated using a leave-20% out model.Peptide spectra can discriminate adverse behavior of WT. After future external validation and refinement, these models could be used to predict WT behavior and to stratify intensity of chemotherapy regimens. Furthermore, peptides discovered in the model could be sequenced to identify potential risk-specific drug targets.

Glutathione S-transferases (GSTs) are involved in many stress responses in plants, for example, participating in the detoxification of xenobiotics and limiting oxidative damage. Studies examining the regulation of this gene family in diverse plant species have focused primarily on RNA expression. A proteomics method was developed to identify GSTs expressed in Arabidopsis seedlings and to determine how the abundance of these proteins changed in response to copper, a promoter of oxidative stress, and benoxacor, a herbicide safener. Eight GSTs were identified in seedlings grown under control conditions, and only one, AtGSTU19, was induced by benoxacor. In contrast, four GSTs, AtGSTF2, AtGSTF6, AtGSTF7, and AtGSTU19, were significantly more abundant in copper-treated seedlings. The different responses to these treatments may reflect the potential for copper to affect many more aspects of plant growth and physiology compared with a herbicide safener. Differences between RNA and protein expression of GSTs indicate that both transcriptional and translational mechanisms are involved in regulation of GSTs under these conditions.

A 37-year-old pregnant woman presented with a 2-cm irregular reddish nodule on her left upper arm during pregnancy. A biopsy from the lesion showed a 2.2-mm thick malignant melanoma with intravascular invasion, 25 mitosis/mm(2) and no ulceration. Following induction of labor, the patient underwent re-excision with sentinel lymph node biopsy. This showed no residual melanoma and no lymph node metastasis. The newborn boy had multiple pigmented lesions on the trunk, some of which were large and irregular. Two were biopsied and histologic examination showed dense dermal proliferation of medium sized melanocytes with multiple mitotic figures and no maturation with their descent into the dermis, raising suspicion of transplacental metastases. Examination of the placenta failed to show metastatic lesions. Multiplex polymerase chain reaction (PCR)-based genotyping, including testing for amelogenin locus for sex chromosome determination, demonstrated the presence of Y chromosome material in the melanocytes of the newborn's lesions excluding maternal origin. A diagnosis of congenital nevi was rendered. Subsequently, Imaging Mass Spectrometric analysis of the mother's lesion showed proteomic signature expression indicative of malignant melanoma, whereas the two lesions in the newborn showed changes indicative of nevi. This case demonstrates the utility of genotyping and Mass Spectrometry analysis in this challenging clinical scenario.