MALDI imaging mass spectrometry reveals COX7A2, TAGLN2 and S100-A10 as novel prognostic markers in Barrett's adenocarcinoma

Mitochondrial Proteins as Metabolic Biomarkers and Sites for Therapeutic Intervention in Primary and Metastatic Cancers

Accelerated aerobic glycolysis is one of the main metabolic alterations in cancer, associated with malignancy and tumor growth. Although glycolysis is one of the most studied properties of tumor cells, recent studies demonstrate that oxidative phosphorylation (OxPhos) is the main ATP provider for the growth and development of cancer. In this last regard, the levels of mRNA and protein of OxPhos enzymes and transporters (including glutaminolysis, acetate and ketone bodies catabolism, free fatty acid β-oxidation, Krebs Cycle, respiratory chain, phosphorylating system- ATP synthase, ATP/ADP translocator, Pi carrier) are altered in tumors and cancer cells in comparison to healthy tissues and organs, and non-cancer cells. Both energy metabolism pathways are tightly regulated by transcriptional factors, oncogenes, and tumor-suppressor genes, all of which dictate their protein levels depending on the micro-environmental conditions and the type of cancer cell, favoring cancer cell adaptation and growth. In the present review paper, variation in the mRNA and protein levels as well as in the enzyme/ transporter activities of the OxPhos machinery is analyzed. An integral omics approach to mitochondrial energy metabolism pathways may allow for identifying their use as suitable, reliable biomarkers for early detection of cancer development and metastasis, and for envisioned novel, alternative therapies.

A systems biology approach to pathogenesis of gastric cancer: gene network modeling and pathway analysis

BACKGROUND

Gastric cancer (GC) ranks among the most common malignancies worldwide. This study aimed to find critical genes/pathways in GC pathogenesis.

METHODS

Gene interactions were analyzed, and the protein-protein interaction network was drawn. Then enrichment analysis of the hub genes was performed and network cluster analysis and promoter analysis of the hub genes were done. Age/sex analysis was done on the identified genes.

RESULTS

Eleven hub genes in GC were identified in the current study (ATP5A1, ATP5B, ATP5D, MT-ATP8, COX7A2, COX6C, ND4, ND6, NDUFS3, RPL8, and RPS16), mostly involved in mitochondrial functions. There was no report on the ATP5D, ND6, NDUFS3, RPL8, and RPS16 in GC. Our results showed that the most affected processes in GC are the metabolic processes, and the oxidative phosphorylation pathway was considerably enriched which showed the significance of mitochondria in GC pathogenesis. Most of the affected pathways in GC were also involved in neurodegenerative diseases. Promoter analysis showed that negative regulation of signal transduction might play an important role in GC pathogenesis. In the analysis of the basal expression pattern of the selected genes whose basal expression presented a change during the age, we found that a change in age may be an indicator of changes in disease insurgence and/or progression at different ages.

CONCLUSIONS

These results might open up new insights into GC pathogenesis. The identified genes might be novel diagnostic/prognostic biomarkers or potential therapeutic targets for GC. This work, being based on bioinformatics analysis act as a hypothesis generator that requires further clinical validation.

Emerging Computational Methods in Mass Spectrometry Imaging

Mass spectrometry imaging (MSI) is a powerful analytical technique that generates maps of hundreds of molecules in biological samples with high sensitivity and molecular specificity. Advanced MSI platforms with capability of high-spatial resolution and high-throughput acquisition generate vast amount of data, which necessitates the development of computational tools for MSI data analysis. In addition, computation-driven MSI experiments have recently emerged as enabling technologies for further improving the MSI capabilities with little or no hardware modification. This review provides a critical summary of computational methods and resources developed for MSI data analysis and interpretation along with computational approaches for improving throughput and molecular coverage in MSI experiments. This review is focused on the recently developed artificial intelligence methods and provides an outlook for a future paradigm shift in MSI with transformative computational methods.

The nature compound dehydrocrenatidine exerts potent antihepatocellular carcinoma by destroying mitochondrial complexes in vitro and in vivo

Cumulative evidence indicates that mitochondria dysfunction plays an important role in tumour treatment. Given the limited efficacy and toxicity of current mitochondria-targeted drugs, research into effective mitochondria-targeted anticancer agents remains an irresistible general trend. In this study, it was found that dehydrocrenatidine (DEC), a β-carbolin alkaloid isolated from Picrasma quassiodes, displays a promising growth inhibitory effect in vitro and in vivo by inducing apoptosis of hepatocellular carcinoma (HCC) cells. Mechanistically, we provided that the possible target of DEC against HCC cells was determined by isobaric labels for relative and absolute quantification assay and validated them using further experiments. The results suggested that DEC can target and regulate the function of mitochondrial complexes I, III and IV, affecting oxidative phosphorylation and ultimately leading to mitochondrial dysfunction to exert its anti-HCC effects. In addition, the combination of DEC and sorafenib showed a synergistic effect and was also associated with mitochondrial dysfunction. Importantly, DEC did not show significant toxicity in mice. This study provided a new insight into underlying mechanisms in DEC-treated HCC cells, suggesting that DEC might be a mitochondrial targeting lead compound.

Machine learning for grading and prognosis of esophageal dysplasia using mass spectrometry and histological imaging

BACKGROUND

Barrett's esophagus (BE) is a precursor lesion of esophageal adenocarcinoma and may progress from non-dysplastic through low-grade dysplasia (LGD) to high-grade dysplasia (HGD) and cancer. Grading BE is of crucial prognostic value and is currently based on the subjective evaluation of biopsies. This study aims to investigate the potential of machine learning (ML) using spatially resolved molecular data from mass spectrometry imaging (MSI) and histological data from microscopic hematoxylin and eosin (H&E)-stained imaging for computer-aided diagnosis and prognosis of BE.

METHODS

Biopsies from 57 patients were considered, divided into non-dysplastic (n = 15), LGD non-progressive (n = 14), LGD progressive (n = 14), and HGD (n = 14). MSI experiments were conducted at 50 × 50 μm spatial resolution per pixel corresponding to a tile size of 96x96 pixels in the co-registered H&E images, making a total of 144,823 tiles for the whole dataset.

RESULTS

ML models were trained to distinguish epithelial tissue from stroma with area-under-the-curve (AUC) values of 0.89 (MSI) and 0.95 (H&E)) and dysplastic grade (AUC of 0.97 (MSI) and 0.85 (H&E)) on a tile level, and low-grade progressors from non-progressors on a patient level (accuracies of 0.72 (MSI) and 0.48 (H&E)).

CONCLUSIONS

In summary, while the H&E-based classifier was best at distinguishing tissue types, the MSI-based model was more accurate at distinguishing dysplastic grades and patients at progression risk, which demonstrates the complementarity of both approaches. Data are available via ProteomeXchange with identifier PXD028949.

Identification of novel genes involved in apoptosis of HIV-infected macrophages using unbiased genome-wide screening

Background

Macrophages, besides resting latently infected CD4+ T cells, constitute the predominant stable, major non-T cell HIV reservoirs. Therefore, it is essential to eliminate both latently infected CD4+ T cells and tissue macrophages to completely eradicate HIV in patients. Until now, most of the research focus is directed towards eliminating latently infected CD4+ T cells. However, few approaches have been directed at killing of HIV-infected macrophages either in vitro or in vivo. HIV infection dysregulates the expression of many host genes essential for the survival of infected cells. We postulated that exploiting this alteration may yield novel targets for the selective killing of infected macrophages.

Methods

We applied a pooled shRNA-based genome-wide approach by employing a lentivirus-based library of shRNAs to screen novel gene targets whose inhibition should selectively induce apoptosis in HIV-infected macrophages. Primary human MDMs were infected with HIV-eGFP and HIV-HSA viruses. Infected MDMs were transfected with siRNAs specific for the promising genes followed by analysis of apoptosis by flow cytometry using labelled Annexin-V in HIV-infected, HIV-exposed but uninfected bystander MDMs and uninfected MDMs. The results were analyzed using student’s t-test from at least four independent experiments.

Results

We validated 28 top hits in two independent HIV infection models. This culminated in the identification of four target genes, Cox7a2, Znf484, Cstf2t, and Cdk2, whose loss-of-function induced apoptosis preferentially in HIV-infected macrophages. Silencing these single genes killed significantly higher number of HIV-HSA-infected MDMs compared to the HIV-HSA-exposed, uninfected bystander macrophages, indicating the specificity in the killing of HIV-infected macrophages. The mechanism governing Cox7a2-mediated apoptosis of HIV-infected macrophages revealed that targeting respiratory chain complex II and IV genes also selectively induced apoptosis of HIV-infected macrophages possibly through enhanced ROS production.

Conclusions

We have identified above-mentioned novel genes and specifically the respiratory chain complex II and IV genes whose silencing may cause selective elimination of HIV-infected macrophages and eventually the HIV-macrophage reservoirs. The results highlight the potential of the identified genes as targets for eliminating HIV-infected macrophages in physiological environment as part of an HIV cure strategy.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12879-021-06346-7.

An Essential NRP1-Mediated Role for Tagln2 in Gastric Cancer Angiogenesis

Knowledge about the precise biological role and underlying mechanism of Tagln2 in tumor progression is relatively limited, especially in angiogenesis focused on tumor derived endothelial cells (ECs) has rarely been reported. Here, the function, molecular mechanism and potential clinical value of Tagln2 in gastric cancer (GC) angiogenesis were investigated. GC tissue microarrays were used to assess the expression of Tagln2 in ECs. The relationships between expression and clinicopathological features were analyzed to evaluate the clinical value of Tagln2. Gain- and loss-of-function approaches were performed in ECs to investigate the functions of Tagln2 in angiogenesis. A combination of angiogenesis antibody array, RNA-Seq analyses and a series of in vitro experiments were performed to reveal the proangiogenic mechanism mediated by NRP1. Immunohistochemistry performed on an independent tissue chip (n=75) revealed significant upregulation of Tagln2 in tumor-derived ECs which were specifically immunolabeled with CD34. Additionally, high Tagln2 levels correlated significantly with the presence of lymph node as well as distant metastases. Gain- and loss-of-function approaches highlighted the function of Tagln2 in promoting EC proliferation, motility, and capillary-like tube formation and in reducing apoptosis. Tagln2 upregulation led to significantly increased mRNA and protein levels of NRP1 and subsequently activated the NRP1/VEGFR2 and downstream MAPK signaling pathways. These data indicate the importance of Tagln2 in angiogenesis, as a potential therapeutic target, and as a candidate prognostic marker in GC.

Alteration of protein expression and spliceosome pathway activity during Barrett's carcinogenesis

BACKGROUND

Barrett's esophagus (BE) is a known precursor lesion and the strongest risk factor for esophageal adenocarcinoma (EAC), a common and lethal type of cancer. Prediction of risk, the basis for efficient intervention, is commonly solely based on histologic examination. This approach is challenged by problems such as inter-observer variability in the face of the high heterogeneity of dysplastic tissue. Molecular markers might offer an additional way to understand the carcinogenesis and improve the diagnosis-and eventually treatment. In this study, we probed significant proteomic changes during dysplastic progression from BE into EAC.

METHODS

During endoscopic mucosa resection, epithelial and stromal tissue samples were collected by laser capture microdissection from 10 patients with normal BE and 13 patients with high-grade dysplastic/EAC. Samples were analyzed by mass spectrometry-based proteomic analysis. Expressed proteins were determined by label-free quantitation, and gene set enrichment was used to find differentially expressed pathways. The results were validated by immunohistochemistry for two selected key proteins (MSH6 and XPO5).

RESULTS

Comparing dysplastic/EAC to non-dysplastic BE, we found in equal volumes of epithelial tissue an overall up-regulation in terms of protein abundance and diversity, and determined a set of 226 differentially expressed proteins. Significantly higher expressions of MSH6 and XPO5 were validated orthogonally and confirmed by immunohistochemistry.

CONCLUSIONS

Our results demonstrate that disease-related proteomic alterations can be determined by analyzing minute amounts of cell-type-specific collected tissue. Further analysis indicated that alterations of certain pathways associated with carcinogenesis, such as micro-RNA trafficking, DNA damage repair, and spliceosome activity, exist in dysplastic/EAC.

Evaluation of the Aortopathy in the Ascending Aorta: The Novelty of Using Matrix-Assisted Laser Desorption/Ionization Imaging

PURPOSE

Histopathological evaluation presents conflicting reports regarding aortic abnormalities. The authors aim to present proof-of-concept study to explore the feasibility of matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI-IMS) in combination with histopathology for characterizing alterations in the aneurysmal ascending formalin-fixed paraffin-embedded (FFPE) aorta tissue.

EXPERIMENTAL DESIGN

The authors assess FFPE specimens from patients with a dilated aorta and bicuspid aortic valve (BAV), those with a standard tricuspid aortic valve (TAV), and those with Marfan syndrome (MFS) via histopathology and grade the conditions for elastic fiber fragmentation (EFF) and MALDI-IMS. The proteins using liquid chromatographic-mass spectrometry are identified and the results are confirmed by immunohistochemistry.

RESULTS

There is significant difference in terms of EFF between MFS and BAV, and TAV and BAV. Characteristic peptide signatures and m/z values in the EFF facilitate the characterization among the aortic specimens of BAV, MFS, and TAV. The m/z values from the aortic alpha smooth muscle actin and myosin heavy chains significantly increase in BAV compared with MFS and TAV. These findings are confirmed by immunohistochemistry.

CONCLUSION

The results represent a strategy that uses MALDI-IMS in combination with histopathology as promising approaches to characterize spatial alteration in the structure of the aneurysmal ascending aorta.

Multiplex enzyme activity imaging by MALDI-IMS of substrate library conversions

Enzymes are fundamental to biological processes and involved in most pathologies. Here we demonstrate the concept of simultaneously mapping multiple enzyme activities (EA) by applying enzyme substrate libraries to tissue sections and analyzing their conversion by matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS). To that end, we spray-applied a solution of 20 naturally derived peptides that are known substrates for proteases, kinases, and phosphatases to zinc-fixed paraffin tissue sections of mouse kidneys. After enzyme conversion for 5 to 120 min at 37 °C and matrix application, the tissue sections were imaged by MALDI-IMS. We could image incubation time-dependently 16 of the applied substrates with differing signal intensities and 12 masses of expected products. Utilizing inherent enzyme amplification, EA-IMS can become a powerful tool to locally study multiple, potentially even lowly expressed, enzyme activities, networks, and their pharmaceutical modulation. Differences in the substrate detectability highlight the need for future optimizations.

Molecular signatures of tumor progression in myxoid liposarcoma identified by N-glycan mass spectrometry imaging

Myxoid liposarcoma (MLS) is the second most common subtype of liposarcoma, accounting for ~6% of all sarcomas. MLS is characterized by a pathognomonic FUS-DDIT3, or rarely EWSR1-DDIT3, gene fusion. The presence of ≥5% hypercellular round cell areas is associated with a worse prognosis for the patient and is considered high grade. The prognostic significance of areas with moderately increased cellularity (intermediate) is currently unknown. Here we have applied matrix-assisted laser desorption/ionization mass spectrometry imaging to analyze the spatial distribution of N-linked glycans on an MLS microarray in order to identify molecular markers for tumor progression. Comparison of the N-glycan profiles revealed that increased relative abundances of high-mannose type glycans were associated with tumor progression. Concomitantly, an increase of the average number of mannoses on high-mannose glycans was observed. Although overall levels of complex-type glycans decreased, an increase of tri- and tetra-antennary N-glycans was observed with morphological tumor progression and increased tumor histological grade. The high abundance of tri-antennary N-glycan species was also associated with poor disease-specific survival. These findings mirror recent observations in colorectal cancer, breast cancer, ovarian cancer, and cholangiocarcinoma, and are in line with a general role of high-mannose glycans and higher-antennary complex-type glycans in cancer progression.

Downregulation of transgelin 2 promotes breast cancer metastasis by activating the reactive oxygen species/nuclear factor‑κB signaling pathway

Transgelin 2 (TAGLN2) is a cytoskeletal protein of the calponin family. Abnormal expression of TAGLN2 was observed in various types of cancer. Our previous study reported that TAGLN2 expression was reduced in lymph node-positive breast cancer patients; however, the role of TAGLN2 in breast cancer metastasis remains unknown. In the present study, the role of TAGLN2 in breast cancer metastasis was investigated in vitro and in vivo via Transwell migration, luciferase and flow cytometry assays, and a mouse xenograft model. Proteins interacting with TAGLN2 were identified via co-immunoprecipitation assays and liquid chromatography/mass spectrometry, and the signaling pathway associated with the effects of TAGLN2 was investigated. Additionally, western blotting and reverse transcription-quantitative polymerase chain reaction were performed to further explore the potential pathway in which TAGLN2 may be involved and the mechanism underlying its effects in breast cancer metastasis. The present study reported that TAGLN2 expression was increased by 11.4-fold in patients without distant metastasis compared with those positive for distant metastasis. Knockdown of TAGLN2 resulted in increased cell migration in vitro and promoted lung metastasis in vivo. Additionally, overexpression of TAGLN2 suppressed lung metastasis in a mouse model. Peroxiredoxin 1 (PRDX1), an important reactive oxygen species (ROS) regulator, was revealed to interact with TAGLN2. In addition, mitochondrial redistribution and PRDX1 downregulation were reported following TAGLN2 silencing, which promoted ROS production and nuclear factor (NF)-κB activation in breast cancer cells. This induced the expression of metastasis-associated genes, including C-X-C chemokine receptor 4, matrix metalloproteinase (MMP)1 and MMP2. The present study proposed TAGLN2 to function as a tumor suppressor and that loss of TAGLN2 may promote the metastasis of breast cancer by activating the ROS/NF-κB signaling pathway.

Transgelin-2 expression in breast cancer and its relationships with clinicopathological features and patient outcome

BACKGROUND

Transgelin-2 is an actin-binding protein that is widely expressed in various tissues and organs of the body, and reportedly may participate in the development and progression of multiple cancers. However, the clinical significance of transgelin-2 still remains controversial. We, therefore, aimed to determine the expression of transgelin-2 in breast cancer as well as its correlation with the tumorigenesis, progression and prognosis of human breast cancer.

METHODS

We collected tissues of 58 breast cancer patients from our hospital and 1090 samples from The Cancer Genome Atlas (TCGA) database. X-tile software was used to divide the transgelin-2 mRNA expression level in the database, logistic regression model was used to identify independent factors influencing transgelin-2 mRNA expression, and then Cox regression and Kaplan-Meier analysis were used to find factors that influence survival of breast cancer.

RESULTS

Transgelin-2 was significantly overexpressed in breast cancer tissues from our hospital and receiver operating characteristic (ROC) curve indicated that transgelin-2 may have diagnostic value. Meanwhile, estrogen receptor (ER) was in inverse correlation with transgelin-2 protein and mRNA expression, and transgelin-2 expression was positively correlated with Ki67 in breast cancer tissues. Logistic regression model revealed that TNM stage, ER and progesterone receptor (PR) status were independent factors for transgelin-2 mRNA expression. Patients with high transgelin-2 mRNA expression showed a poor survival and the trend was statistically significant only in ER-negative patients.

CONCLUSIONS

Transgelin-2 was expressed significantly higher in breast cancer cells and correlated with some clinicopathological factors. High transgelin-2 expression might predict poor prognosis for ER-negative patients.

Mass spectrometry imaging for clinical research - latest developments, applications, and current limitations

Mass spectrometry is being used in many clinical research areas ranging from toxicology to personalized medicine. Of all the mass spectrometry techniques, mass spectrometry imaging (MSI), in particular, has continuously grown towards clinical acceptance. Significant technological and methodological improvements have contributed to enhance the performance of MSI recently, pushing the limits of throughput, spatial resolution, and sensitivity. This has stimulated the spread of MSI usage across various biomedical research areas such as oncology, neurological disorders, cardiology, and rheumatology, just to name a few. After highlighting the latest major developments and applications touching all aspects of translational research (i.e. from early pre-clinical to clinical research), we will discuss the present challenges in translational research performed with MSI: data management and analysis, molecular coverage and identification capabilities, and finally, reproducibility across multiple research centers, which is the largest remaining obstacle in moving MSI towards clinical routine.

Unraveling local tissue changes within severely injured skeletal muscles in response to MSC-based intervention using MALDI Imaging mass spectrometry

Pre-clinical and clinical studies are now beginning to demonstrate the high potential of cell therapies in enhancing muscle regeneration. We previously demonstrated functional benefit after the transplantation of autologous bone marrow mesenchymal stromal cells (MSC-TX) into a severe muscle crush trauma model. Despite our increasing understanding of the molecular and cellular mechanisms underlying MSC's regenerative function, little is known about the local molecular alterations and their spatial distribution within the tissue after MSC-TX. Here, we used MALDI imaging mass spectrometry (MALDI-IMS) in combination with multivariate statistical strategies to uncover previously unknown peptide alterations within severely injured skeletal muscles. Our analysis revealed that very early molecular alterations in response to MSC-TX occur largely in the region adjacent to the trauma and only to a small extent in the actual trauma region. Using "bottom up" mass spectrometry, we subsequently identified the proteins corresponding to the differentially expressed peptide intensity distributions in the specific muscle regions and used immunohistochemistry to validate our results. These findings extend our current understanding about the early molecular processes of muscle healing and highlights the critical role of trauma adjacent tissue during the early therapeutic response upon treatment with MSC.

Transgelin-2 is a novel target of KRAS-ERK signaling involved in the development of pancreatic cancer

Background

The KRAS mutation is the driving force of pancreatic ductal adenocarcinoma (PDAC). Downstream effectors of KRAS signal pathways are crucial to the development of PDAC. The purpose of this study was to investigate the relationship between KRAS mutation and transgelin-2. Transgelin-2 is highly expressed in PDAC tissues compared with adjacent normal tissues. The underlying mechanism for upregulating transgelin-2 is largely unknown.

Methods

Expression of transgelin-2 was analyzed by microarray data and qRT-PCR. The effect of KRAS signaling on transgelin-2 expression was examined in PDAC cells in the presence or absence of the ERK inhibitor. The interaction of transgelin-2 with ERK was confirmed by immunoprecipitation. ERK-mediated Phosphorylation of transglein-2 was detected by in vivo and in vitro kinase assays. The gain-of-function and loss-of-function approaches were used to examine the role of phosphorylation of transgelin-2 on cell proliferation. Phosphorylation of transgelin-2 was detected by immunohistochemistry in PDAC tissues.

Results

Here we found transgelin-2 expression was induced by KRAS mutation. In the case of KRAS mutation, ERK2 interacted with 29–31 amino acids of transgelin-2 and subsequently phosphorylated the S145 residue of transgelin-2. S145 phosphorylation of transgelin-2 played important roles in cell proliferation and tumorigenesis of PDAC. In addition, S145 phosphorylation of transgelin-2 was associated with a poor prognosis in patients with PDAC.

Conclusions

This study indicated that KRAS-ERK-mediated transeglin-2 phosphorylation played an important role in the development of PDAC. Inhibition of transgelin-2 phosphorylation may be a potential therapeutic strategy for targeting PDAC with KRAS mutation.

High throughput and accurate serum proteome profiling by integrated sample preparation technology and single-run data independent mass spectrometry analysis

Mass spectrometry (MS)-based serum proteome analysis is extremely challenging due to its high complexity and dynamic range of protein abundances. Developing high throughput and accurate serum proteomic profiling approach capable of analyzing large cohorts is urgently needed for biomarker discovery. Herein, we report a streamlined workflow for fast and accurate proteomic profiling from 1μL of blood serum. The workflow combined an integrated technique for highly sensitive and reproducible sample preparation and a new data-independent acquisition (DIA)-based MS method. Comparing with standard data dependent acquisition (DDA) approach, the optimized DIA method doubled the number of detected peptides and proteins with better reproducibility. Without protein immunodepletion and prefractionation, the single-run DIA analysis enables quantitative profiling of over 300 proteins with 50min gradient time. The quantified proteins span more than five orders of magnitude of abundance range and contain over 50 FDA-approved disease markers. The workflow allowed us to analyze 20 serum samples per day, with about 358 protein groups per sample being identified. A proof-of-concept study on renal cell carcinoma (RCC) serum samples confirmed the feasibility of the workflow for large scale serum proteomic profiling and disease-related biomarker discovery.

BIOLOGICAL SIGNIFICANCE

Blood serum or plasma is the predominant specimen for clinical proteomic studies while the analysis is extremely challenging for its high complexity. Many efforts had been made in the past for serum proteomics for maximizing protein identifications, whereas few have been concerned with throughput and reproducibility. Here, we establish a rapid, robust and high reproducible DIA-based workflow for streamlined serum proteomic profiling from 1μL serum. The workflow doesn't need protein depletion and pre-fractionation, while still being able to detect disease-relevant proteins accurately. The workflow is promising in clinical application, because the usage of small sample amounts makes blood testing much less invasive, the fully integrated sample preparation by the SISPROT technology greatly improve sample preparation throughput and reproducibility, and the scan feature of DIA method provides a way to convert nonrenewable clinical specimens into permanent digital proteome maps which could be easily reanalyzed.

MALDI MSI of MeLiM melanoma: Searching for differences in protein profiles

Background

Treatment of advanced cutaneous melanoma remains challenging, and new data on melanoma biology are required. The most widely accepted criteria for the prognostic evaluation of melanoma are histopathological and clinical parameters, and the identification of additional tumor markers is thus of paramount importance. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI), an important tool in cancer research, is useful for unraveling the molecular profile of melanoma.

Methodology/Principal findings

In this report, we used the melanoma-bearing Libechov minipig (MeLiM), a unique animal model that allows observation of the complete spontaneous regression of invasive cutaneous melanoma, to investigate i) the differences between melanoma and healthy skin protein profiles and ii) the proteins potentially involved in spontaneous regression. The MeLiM tissues were cryosected, histologically characterized, analyzed by MALDI MSI, and immunohistologically stained. Multivariate statistical analyses of the MALDI MSI data revealed ten relevant m/z ions, of which the expression levels varied significantly among the studied MeLiM tissues. These ion peaks were used to create mass ion images/maps and visualize the differences between tumor and healthy skin specimens, as well as among histologically characterized tissue regions.

Conclusions/Significance

Protein profiles comprising ten statistically significant mass ion peaks useful for differentiating cutaneous melanoma and healthy skin tissues were determined. Peaks at m/z 3044, 6011, 6140 and 10180 were overexpressed in melanoma compared with healthy skin tissue. More specifically, m/z 6140 was expressed at significantly (p < 0.05) higher levels in normally growing melanoma regions than in regions with early and late spontaneous regression. This study demonstrates the clinical utility of MALDI MSI for the analysis of tissue cryosections at a molecular level.

Matrix-Assisted Laser Desorption/Ionisation Mass Spectrometry Imaging in the Study of Gastric Cancer: A Mini Review

Gastric cancer (GC) is one of the leading causes of cancer-related deaths worldwide and the disease outcome commonly depends upon the tumour stage at the time of diagnosis. However, this cancer can often be asymptomatic during the early stages and remain undetected until the later stages of tumour development, having a significant impact on patient prognosis. However, our comprehension of the mechanisms underlying the development of gastric malignancies is still lacking. For these reasons, the search for new diagnostic and prognostic markers for gastric cancer is an ongoing pursuit. Modern mass spectrometry imaging (MSI) techniques, in particular matrix-assisted laser desorption/ionisation (MALDI), have emerged as a plausible tool in clinical pathology as a whole. More specifically, MALDI-MSI is being increasingly employed in the study of gastric cancer and has already elucidated some important disease checkpoints that may help us to better understand the molecular mechanisms underpinning this aggressive cancer. Here we report the state of the art of MALDI-MSI approaches, ranging from sample preparation to statistical analysis, and provide a complete review of the key findings that have been reported in the literature thus far.

Overexpression of COX7A2 is associated with a good prognosis in patients with glioma

Cytochrome c oxidase subunit 7A2 (COX7A2) is a nuclear-encoded polypeptide involved in assembly and regulation of cytochrome c oxidase (COX). Changes in the respiratory chain as big complex are known to be associated with cancer, but little research has been performed to discover COX7A2 as a prognostic marker in glioma. In the present study, we investigated COX7A2 expression and its prognostic significance in glioma. Glioma surgical tissue samples were taken from 126 patients who had been followed up from 4 to 51 months. Immunohistochemistry were used to test COX7A2 expression in the 126 tumor samples. Eighty-six of 126 (68.3%) paraffin-embedded glioma biopsies showed high expression of COX7A2. Statistical analysis displayed that there was significant difference of COX7A2 expression level in patients categorized according to WHO classification. Kaplan-Meier survival analysis revealed that patients with higher COX7A2 expression had longer overall survival time and better prognosis. R2: microarray analysis based on Tumor Glioma French 284 database, Tumor Glioblastoma TCGA 540 database, and Tumor Glioma Kawaguchi 50 database testified that high expression of COX7A2 is associated with a good prognosis in patients with glioma. Multivariate analysis showed that COX7A2 high expression was an independent prognostic indicator for survival. Our results suggest that COX7A2 could be served as a valuable prognostic marker of glioma.

High-grade sarcoma diagnosis and prognosis: Biomarker discovery by mass spectrometry imaging

The combination of high heterogeneity, both intratumoral and intertumoral, with their rarity has made diagnosis, prognosis of high-grade sarcomas difficult. There is an urgent need for more objective molecular biomarkers, to differentiate between the many different subtypes, and to also provide new treatment targets. Mass spectrometry imaging (MSI) has amply demonstrated its ability to identify potential new markers for patient diagnosis, survival, metastasis and response to therapy in cancer research. In this study, we investigated the ability of MALDI-MSI of proteins to distinguish between high-grade osteosarcoma (OS), leiomyosarcoma (LMS), myxofibrosarcoma (MFS) and undifferentiated pleomorphic sarcoma (UPS) (Ntotal = 53). We also investigated if there are individual proteins or protein signatures that are statistically associated with patient survival. Twenty diagnostic protein signals were found characteristic for specific tumors (p ≤ 0.05), amongst them acyl-CoA-binding protein (m/z 11 162), macrophage migration inhibitory factor (m/z 12 350), thioredoxin (m/z 11 608) and galectin-1 (m/z 14 633) were assigned. Another nine protein signals were found to be associated with overall survival (p ≤ 0.05), including proteasome activator complex subunit 1 (m/z 9753), indicative for non-OS patients with poor survival; and two histone H4 variants (m/z 11 314 and 11 355), indicative of poor survival for LMS patients.

Transgelin-2 is upregulated on activated B-cells and expressed in hyperplastic follicles in lupus erythematosus patients

Transgelin-2 (TAGLN2) is an actin-binding protein that controls actin stability and promotes T cell activation. TAGLN2 is also expressed on B-cells but its function in B-cells is unknown. We found that TAGLN2-expressing B-cells were localized in the germinal center (GC) of secondary lymphoid tissues and TAGLN2 mRNA was significantly upregulated after IgM+IgG stimulation in primary human B-cells, suggesting that TAGLN2 was upregulated upon B-cell activation. In support of this, lymph nodes (LNs) from patients with systemic lupus erythematosus (SLE), in which the intense GC activity have been recognized, showed increased TAGLN2 expression in B-cells compared to control LNs. Moreover, TAGLN2⁺B-cells were distributed widely not only in the GC but also in the perifollicular areas in SLE LNs. In contrast, CD19⁺ B-cells and CD19⁺CD27⁺ memory-B cells in peripheral blood of SLE patients showed no increase in TAGLN2 mRNA. Two-photon excitation microscopy of Raji cells demonstrated that TAGLN2 colocalized with F-actin and moved together to the periphery upon stimulation. TAGLN2-knockdown in Raji cells resulted in impaired phosphorylation of PLCγ2 leading to inhibition of cell migration. Microarray analysis of TAGLN2-knockdown Raji cells showed decreased expression of the genes associated with immune function including CCR6 and as well as of those associated with regulation of the actin cytoskeleton including ABI2, compared to controls. These results suggest that TAGLN2 might regulate activation and migration of B-cells, in particular, the entry of activated B-cells into the follicle. We also suggest that TAGLN2 could be used as a marker for activated B-cells.

Quantitative Shotgun Proteomics Unveils Candidate Novel Esophageal Adenocarcinoma (EAC)-specific Proteins

Esophageal cancer is the eighth most common cancer worldwide and the majority of patients have systemic disease at presentation. Esophageal adenocarcinoma (OAC), the predominant subtype in western countries, is largely resistant to current chemotherapy regimens. Selective markers are needed to enhance clinical staging and to allow targeted therapies yet there are minimal proteomic data on this cancer type. After histological review, lysates from OAC and matched normal esophageal and gastric samples from seven patients were subjected to LC MS/MS after tandem mass tag labeling and OFFGEL fractionation. Patient matched samples of OAC, normal esophagus, normal stomach, lymph node metastases and uninvolved lymph nodes were used from an additional 115 patients for verification of expression by immunohistochemistry (IHC).

Over six thousand proteins were identified and quantified across samples. Quantitative reproducibility was excellent between technical replicates and a moderate correlation was seen across samples with the same histology. The quantitative accuracy was verified across the dynamic range for seven proteins by immunohistochemistry (IHC) on the originating tissues. Multiple novel tumor-specific candidates are proposed and EPCAM was verified by IHC.

This shotgun proteomic study of OAC used a comparative quantitative approach to reveal proteins highly expressed in specific tissue types. Novel tumor-specific proteins are proposed and EPCAM was demonstrated to be specifically overexpressed in primary tumors and lymph node metastases compared with surrounding normal tissues. This candidate and others proposed in this study could be developed as tumor-specific targets for novel clinical staging and therapeutic approaches.

MALDI IMS and Cancer Tissue Microarrays

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) technology creates a link between the molecular assessment of numerous molecules and the morphological information about their special distribution. The application of MALDI IMS on formalin-fixed paraffin-embedded (FFPE) tissue microarrays (TMAs) is suitable for large-scale discovery analyses. Data acquired from FFPE TMA cancer samples in current research are very promising, and applications for routine diagnostics are under development. With the current rapid advances in both technology and applications, MALDI IMS technology is expected to enter into routine diagnostics soon. This chapter is intended to be comprehensive with respect to all aspects and considerations for the application of MALDI IMS on FFPE cancer TMAs with in-depth notes on technical aspects.

Applications of Mass Spectrometry Imaging to Cancer

Pathologists play an essential role in the diagnosis and prognosis of benign and cancerous tumors. Clinicians provide tissue samples, for example, from a biopsy, which are then processed and thin sections are placed onto glass slides, followed by staining of the tissue with visible dyes. Upon processing and microscopic examination, a pathology report is provided, which relies on the pathologist's interpretation of the phenotypical presentation of the tissue. Targeted analysis of single proteins provide further insight and together with clinical data these results influence clinical decision making. Recent developments in mass spectrometry facilitate the collection of molecular information about such tissue specimens. These relatively new techniques generate label-free mass spectra across tissue sections providing nonbiased, nontargeted molecular information. At each pixel with spatial coordinates (x/y) a mass spectrum is acquired. The acquired mass spectrums can be visualized as intensity maps displaying the distribution of single m/z values of interest. Based on the sample preparation, proteins, peptides, lipids, small molecules, or glycans can be analyzed. The generated intensity maps/images allow new insights into tumor tissues. The technique has the ability to detect and characterize tumor cells and their environment in a spatial context and combined with histological staining, can be used to aid pathologists and clinicians in the diagnosis and management of cancer. Moreover, such data may help classify patients to aid therapy decisions and predict outcomes. The novel complementary mass spectrometry-based methods described in this chapter will contribute to the transformation of pathology services around the world.

Mass Spectrometry Imaging for the Investigation of Intratumor Heterogeneity

One of the big clinical challenges in the treatment of cancer is the different behavior of cancer patients under guideline therapy. An important determinant for this phenomenon has been identified as inter- and intratumor heterogeneity. While intertumor heterogeneity refers to the differences in cancer characteristics between patients, intratumor heterogeneity refers to the clonal and nongenetic molecular diversity within a patient. The deciphering of intratumor heterogeneity is recognized as key to the development of novel therapeutics or treatment regimens. The investigation of intratumor heterogeneity is challenging since it requires an untargeted molecular analysis technique that accounts for the spatial and temporal dynamics of the tumor. So far, next-generation sequencing has contributed most to the understanding of clonal evolution within a cancer patient. However, it falls short in accounting for the spatial dimension. Mass spectrometry imaging (MSI) is a powerful tool for the untargeted but spatially resolved molecular analysis of biological tissues such as solid tumors. As it provides multidimensional datasets by the parallel acquisition of hundreds of mass channels, multivariate data analysis methods can be applied for the automated annotation of tissues. Moreover, it integrates the histology of the sample, which enables studying the molecular information in a histopathological context. This chapter will illustrate how MSI in combination with statistical methods and histology has been used for the description and discovery of intratumor heterogeneity in different cancers. This will give evidence that MSI constitutes a unique tool for the investigation of intratumor heterogeneity, and could hence become a key technology in cancer research.

Mass Spectrometry Imaging in Oncology Drug Discovery

Over the last decade mass spectrometry imaging (MSI) has been integrated in to many areas of drug discovery and development. It can have significant impact in oncology drug discovery as it allows efficacy and safety of compounds to be assessed against the backdrop of the complex tumour microenvironment. We will discuss the roles of MSI in investigating compound and metabolite biodistribution and defining pharmacokinetic -pharmacodynamic relationships, analysis that is applicable to all drug discovery projects. We will then look more specifically at how MSI can be used to understand tumour metabolism and other applications specific to oncology research. This will all be described alongside the challenges of applying MSI to industry research with increased use of metrology for MSI.

Rapid Mass Spectrometry Imaging to Assess the Biochemical Profile of Pituitary Tissue for Potential Intraoperative Usage

Pituitary adenomas are relatively common intracranial neoplasms that are frequently treated with surgical resection. Rapid visualization of pituitary tissue remains a challenge as current techniques either produce little to no information on hormone-secreting function or are too slow to practically aid in intraoperative or even perioperative decision-making. Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) represents a powerful method by which molecular maps of tissue samples can be created, yielding a two-dimensional representation of the expression patterns of small molecules and proteins from biologic samples. In this chapter, we review the use of MALDI MSI, its application to the characterization of the pituitary gland, and its potential applications for guiding the management of pituitary adenomas.

Typing of colon and lung adenocarcinoma by high throughput imaging mass spectrometry

In advanced tumor stages, diagnosis is frequently made from metastatic tumor tissue. In some cases, the identification of the tumor of origin may be difficult by histology alone. In this setting, immunohistochemical and molecular biological methods are often required. In a subset of tumors definite diagnosis cannot be achieved. Thus, additional new diagnostic methods are required for precise tumor subtyping. Mass spectrometric methods are of special interest for the discrimination of different tumor types. We investigated whether it is possible to discern adenocarcinomas of colon and lung using high-throughput imaging mass spectrometry on formalin-fixed paraffin-embedded tissue microarrays. 101 primary adenocarcinoma of the colon and 91 primary adenocarcinoma of the lung were used to train a Linear Discriminant Analysis model. Results were validated on an independent set of 116 colonic and 75 lung adenocarcinomas. In the validation cohort 109 of 116 patients with colonic and 67 of 75 patients with lung adenocarcinomas were correctly classified. The ability to define proteomic profiles capable to discern different tumor types promises a valuable tool in cancer diagnostics and might complement current approaches. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

A new classification method for MALDI imaging mass spectrometry data acquired on formalin-fixed paraffin-embedded tissue samples

Matrix-assisted laser desorption/ionization imaging mass spectrometry (MALDI IMS) shows a high potential for applications in histopathological diagnosis, and in particular for supporting tumor typing and subtyping. The development of such applications requires the extraction of spectral fingerprints that are relevant for the given tissue and the identification of biomarkers associated with these spectral patterns. We propose a novel data analysis method based on the extraction of characteristic spectral patterns (CSPs) that allow automated generation of classification models for spectral data. Formalin-fixed paraffin embedded (FFPE) tissue samples from N=445 patients assembled on 12 tissue microarrays were analyzed. The method was applied to discriminate primary lung and pancreatic cancer, as well as adenocarcinoma and squamous cell carcinoma of the lung. A classification accuracy of 100% and 82.8%, resp., could be achieved on core level, assessed by cross-validation. The method outperformed the more conventional classification method based on the extraction of individual m/z values in the first application, while achieving a comparable accuracy in the second. LC-MS/MS peptide identification demonstrated that the spectral features present in selected CSPs correspond to peptides relevant for the respective classification. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

MALDI imaging mass spectrometry - From bench to bedside

Today, pathologists face many challenges in defining the precise morphomolecular diagnosis and in guiding clinicians to the optimal patients' treatment. To achieve this goal, increasingly, classical histomorphological methods have to be supplemented by high throughput molecular assays. Since MALDI imaging mass spectrometry (IMS) enables the assessment of spatial molecular arrangements in tissue sections, it goes far beyond microscopy in providing hundreds of different molecular images from a single scan without the need of target-specific reagents. Thus, this technology has the potential to uncover new markers for diagnostic purposes or markers that correlate with disease severity as well as prognosis and therapeutic response. Additionally, in the future MALDI IMS based classifiers measured with this technology in real time in the diagnostic setting might be applicable in the routine diagnostic setting. In this review, recently published studies that show the usefulness, advantages, and applicability of MALDI IMS in different fields of pathology (diagnosis, prognosis and treatment response) are highlighted. This article is part of a Special Issue entitled: MALDI Imaging, edited by Dr. Corinna Henkel and Prof. Peter Hoffmann.

Current status of proteomics of esophageal carcinoma

INTRODUCTION

Esophageal cancer (EC) is one of the most common causes of cancer-related death worldwide. Identifying suitable biomarkers for early diagnosis as well as predicting lymph node metastasis, prognosis and the therapeutic response of EC is essential for the effective and efficient management for EC. There is an urgent need to develop effective, novel approaches for patients who do not respond to conventional treatment. Areas covered: EC is characterized by the presence of two main histological types such as squamous cell carcinoma and adenocarcinoma, which differ in their response to treatments and prognosis. Thus, this review describes the latest research into biomarkers and novel treatment targets generated by cancer proteomics for the two main histological types. Finally, the main difficulties facing the translation of biomarkers and novel treatment targets into the clinical settings are discussed. Expert commentary: EC proteomics have provided useful results and, after their validation, novel clinical tools should be developed to improve the clinical outcomes for EC patients.

High-mass-resolution MALDI mass spectrometry imaging of metabolites from formalin-fixed paraffin-embedded tissue

Formalin-fixed and paraffin-embedded (FFPE) tissue specimens are the gold standard for histological examination, and they provide valuable molecular information in tissue-based research. Metabolite assessment from archived tissue samples has not been extensively conducted because of a lack of appropriate protocols and concerns about changes in metabolite content or chemical state due to tissue processing. We present a protocol for the in situ analysis of metabolite content from FFPE samples using a high-mass-resolution matrix-assisted laser desorption/ionization fourier-transform ion cyclotron resonance mass spectrometry imaging (MALDI-FT-ICR-MSI) platform. The method involves FFPE tissue sections that undergo deparaffinization and matrix coating by 9-aminoacridine before MALDI-MSI. Using this platform, we previously detected ∼1,500 m/z species in the mass range m/z 50-1,000 in FFPE samples; the overlap compared with fresh frozen samples is 72% of m/z species, indicating that metabolites are largely conserved in FFPE tissue samples. This protocol can be reproducibly performed on FFPE tissues, including small samples such as tissue microarrays and biopsies. The procedure can be completed in a day, depending on the size of the sample measured and raster size used. Advantages of this approach include easy sample handling, reproducibility, high throughput and the ability to demonstrate molecular spatial distributions in situ. The data acquired with this protocol can be used in research and clinical practice.

MALDI mass spectrometry imaging: A cutting-edge tool for fundamental and clinical histopathology

Histopathological diagnoses have been done in the last century based on hematoxylin and eosin staining. These methods were complemented by histochemistry, electron microscopy, immunohistochemistry (IHC), and molecular techniques. Mass spectrometry (MS) methods allow the thorough examination of various biocompounds in extracts and tissue sections. Today, mass spectrometry imaging (MSI), and especially matrix-assisted laser desorption ionization (MALDI) imaging links classical histology and molecular analyses. Direct mapping is a major advantage of the combination of molecular profiling and imaging. MSI can be considered as a cutting edge approach for molecular detection of proteins, peptides, carbohydrates, lipids, and small molecules in tissues. This review covers the detection of various biomolecules in histopathological sections by MSI. Proteomic methods will be introduced into clinical histopathology within the next few years.

Annexin A2 and S100A10 are independent predictors of serous ovarian cancer outcome

Annexin A2, a calcium phospholipid binding protein, has been shown to play an important role in ovarian cancer metastasis. This study examined whether annexin A2 and S100A10 can be used as prognostic markers in serous ovarian cancer. ANXA2 and S100A10 gene expressions were assessed in publicly available ovarian cancer data sets and annexin A2 and S100A10 protein expressions were assessed by immunohistochemistry in a uniform cohort of stage III serous ovarian cancers (n = 109). Kaplan-Meier and Cox regression analyses were performed to assess the relationship between annexin A2 or S100A10 messenger RNA (mRNA) and protein expressions with clinical outcome. High ANXA2 mRNA levels in stage III serous ovarian cancers were associated with reduced progression-free survival (PFS; P = 0.023) and overall survival (OS; P = 0.0038), whereas high S100A10 mRNA levels predicted reduced OS (P = 0.0019). Using The Cancer Genome Atlas data sets, ANXA2 but not S100A10 expression was associated with higher clinical stage (P = 0.005), whereas both ANXA2 and S100A10 expressions were associated with the mesenchymal molecular subtype (P < 0.0001). Kaplan-Meier and Cox regression analyses showed that high stromal annexin A2 immunostaining was significantly associated with reduced PFS (P = 0.013) and OS (P = 0.044). Moreover, high cytoplasmic S100A10 staining was significantly associated with reduced OS (P = 0.027). Multivariate Cox regression analysis showed stromal annexin A2 (P = 0.009) and cytoplasmic S100A10 (P = 0.016) levels to be independent predictors of OS. Patients with high stromal annexin A2 and high cytoplasmic S100A10 expressions had a 3.4-fold increased risk of progression (P = 0.02) and 7.9-fold risk of ovarian cancer death (P = 0.04). Our findings indicate that together annexin A2 and S100A10 expressions are powerful predictors of serous ovarian cancer outcome.

The tumor-suppressive function of miR-1 by targeting LASP1 and TAGLN2 in esophageal squamous cell carcinoma

OBJECTIVE

This study determined the expression of microRNA-1 in esophageal squamous cell carcinoma (ESCC) tissue and cell lines to evaluate its effects on clinicopathological parameters and its target genes LASP1 and TAGLN2.

METHODS

The expression of miR-1, lasp1, and tagln2 was detected in 55 ESCC tissues and adjacent normal tissues by reverse transcription-polymerase chain reaction (RT-PCR). The association between miR-1, lasp1, and tagln2 expression and clinicopathological characteristics was observed. MicroRNA-1 (mimics-miR-1) and its inhibitor (Inhibitor-miR-1) were transfected into esophageal cancer cells KYSE 510 and Eca 109; cell proliferation, migration, and invasion assays were carried out. Plasmid construction and dual-luciferase reporter assay were also carried out to indicate whether LASP1 and TAGLN2 were miR-1 target genes. The expression of LASP1 and TAGLN2 was detected with Western blot methods in cell lines, by immunohistochemistry in ESCC tissue.

RESULTS

The gene expression level of microRNA-1 in cancer tissues was significantly lower than that in adjacent normal tissues (P < 0.01). The expression of miR-1 in ESCC was correlated with involvement of lymph nodes (P = 0.002), histologic classification (P = 0.000), and vessel invasion (P = 0.022). The expression of lasp1 and tagln2 increased in cancer tissues compared with in adjacent normal tissues (P < 0.05). MiR-1 suppresses the cell growth, migration, and invasion in vitro. The expression of LASP1 and TAGLN2 decreased in mimics-miR-1 transfected cells, and increased in inhibitor-miR-1 transfected cells. Luciferase reporter assay confirmed that LASP1 and TAGLN2 mRNA actually had the target sites of miR-1.

CONCLUSIONS

miR-1 suppresses cell proliferation, invasiveness, metastasis, and progression of ESCC by binding its targeted genes LASP1 and TAGLN2.

The use of matrix coating assisted by an electric field (MCAEF) to enhance mass spectrometric imaging of human prostate cancer biomarkers

In this work, we combined a newly developed matrix coating technique - matrix coating assisted by an electric field (MCAEF) and matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) to enhance the imaging of peptides and proteins in tissue specimens of human prostate cancer. MCAEF increased the signal-to-noise ratios of the detected proteins by a factor of 2 to 5, and 232 signals were detected within the m/z 3500-37500 mass range on a time-of-flight mass spectrometer and with the sinapinic acid MALDI matrix. Among these species, three proteins (S100-A9, S100-A10, and S100-A12) were only observed in the cancerous cell region and 14 proteins, including a fragment of mitogen-activated protein kinase/extracellular signal-regulated kinase kinase kinase 2, a fragment of cAMP-regulated phosphoprotein 19, 3 apolipoproteins (C-I, A-I, and A-II), 2 S100 proteins (A6 and A8), β-microseminoprotein, tumor protein D52, α-1-acid glycoprotein 1, heat shock protein β-1, prostate-specific antigen, and 2 unidentified large peptides at m/z 5002.2 and 6704.2, showed significantly differential distributions at the p < 0.05 (t-test) level between the cancerous and the noncancerous regions of the tissue. Among these 17 species, the distributions of apolipoprotein C-I, S100-A6, and S100-A8 were verified by immunohistological staining. In summary, this study resulted in the imaging of the largest group of proteins in prostate cancer tissues by MALDI-MS reported thus far, and is the first to show a correlation between S100 proteins and prostate cancer in a MS imaging study. The successful imaging of the three proteins only found in the cancerous tissues, as well as those showing differential expressions demonstrated the potential of MCAEF-MALDI/MS for the in situ detection of potential cancer biomarkers. Copyright © 2015 John Wiley & Sons, Ltd.

Identification and verification of transgelin-2 as a potential biomarker of tumor-derived lung-cancer endothelial cells by comparative proteomics

To investigate heterogeneity of endothelial cells (ECs) in the tumor microenvironment and biomarkers for antitumor angiogenesis therapy, high-purity (>98%) normal (NECs) and tumor-derived CD105(+) ECs (TECs) were purified from a mouse Lewis lung carcinoma model bearing 0.5 cm tumors by immunomagnetic separation. Proteomics analysis revealed that 48 proteins (28 upregulated and 20 downregulated) were differentially regulated by at least 1.5-fold in TECs, and that these proteins were involved in metabolism, energy pathways, protein folding, cell growth and/or functioned as structural constituents of the cytoskeleton. Upregulation of heat shock protein 60 (Hspd1) and transgelin-2 (Tagln2) was revealed in TECs, and by immunohistochemistry (IHC) in paired tissues from 30 consecutive lung cancer (LC) patients. Higher expression levels of Hspd1, Tagln2 were detected in microvascular ECs of paratumor and tumor tissues than in paired normal counterparts. Stronger Tagln2 staining was associated with clinical stage, tumor size, and histological neural invasion. Higher Hspd1 (area under the curve [AUC], 0.82) and lower Tagln2 (AUC, 0.90) levels were detected in LC patient sera. Pearson correlation analysis revealed a positive correlation between serum Hspd1 and Tagln2 levels. In conclusion, higher Tagln2 levels were associated with tumor development, lymph node metastasis, and neural invasion in LC and may thus serve as a potential biomarker of tumor angiogenesis.

SIGNIFICANCE

High-purity endothelial cells (normal and tumor derived) were prepared to characterize ECs heterogeneity in the tumor microenvironment and to explore biomarkers of early stages of tumor development by proteomics. Candidate proteins Hspd1 and Tagln2, were further verification in the sera and tumor tissues of lung cancer patients. Moreover, higher Tagln2 was significantly associated with clinical tumor development, metastasis, and neural invasion. All these results indicated a crucial role for Tagln2 in TECs for tumor development and metastasis.

MALDI mass spectrometry imaging analysis of pituitary adenomas for near-real-time tumor delineation

We present a proof of concept study designed to support the clinical development of mass spectrometry imaging (MSI) for the detection of pituitary tumors during surgery. We analyzed by matrix-assisted laser desorption/ionization (MALDI) MSI six nonpathological (NP) human pituitary glands and 45 hormone secreting and nonsecreting (NS) human pituitary adenomas. We show that the distribution of pituitary hormones such as prolactin (PRL), growth hormone (GH), adrenocorticotropic hormone (ACTH), and thyroid stimulating hormone (TSH) in both normal and tumor tissues can be assessed by using this approach. The presence of most of the pituitary hormones was confirmed by using MS/MS and pseudo-MS/MS methods, and subtyping of pituitary adenomas was performed by using principal component analysis (PCA) and support vector machine (SVM). Our proof of concept study demonstrates that MALDI MSI could be used to directly detect excessive hormonal production from functional pituitary adenomas and generally classify pituitary adenomas by using statistical and machine learning analyses. The tissue characterization can be completed in fewer than 30 min and could therefore be applied for the near-real-time detection and delineation of pituitary tumors for intraoperative surgical decision-making.

Label-free quantitative phosphorylation analysis of human transgelin2 in Jurkat T cells reveals distinct phosphorylation patterns under PKA and PKC activation conditions

Background

Transgelin2, one of cytoskeletal actin binding proteins has recently been suggested to be involved in the formation of immune synapses. Although detailed function of transgelin2 is largely unknown, interactions between transgelin2 and actin appear to be important in regulating cellular functions of transgelin2. Because protein phosphorylation can change ability to interact with other proteins, comprehensive phosphorylation analysis of transgelin2 will be helpful in understanding its functional mechanisms.

Results

Here, a specific protein label-free quantitative phosphorylation analysis method combining immuno-precipitation, IMAC phosphopeptide enrichment technique and label-free relative quantification analysis was used to monitor the phosphorylation changes of transgelin2 overexpressed in Jurkat T cells under protein kinase C (PKC) and protein kinase A (PKA) activation conditions, two representative intracellular signalling pathways of immune cell activation and homeostasis. A total of six serine/threonine phosphorylation sites were identified including threonine-84, a novel phosphorylation site. Notably, distinct phosphorylation patterns of transgelin2 under the two kinase activation conditions were observed. Most phosphorylation sites showing specific kinase-dependent phosphorylation changes were discretely located in two previously characterized actin-binding regions: actin-binding site (ABS) and calponin repeat domain (CNR). PKC activation increased phosphorylation of threonine-180 and serine-185 in the CNR, and PKA activation increased phosphorylation of serine-163 in the ABS.

Conclusions

Multiple actin-binding regions of transgelin2 participate to accomplish its full actin-binding capability, and the actin-binding affinity of each actin-binding region appears to be modulated by specific kinase-dependent phosphorylation changes. Accordingly, different actin-binding properties or cellular functions of transgelin2 may result from distinct intracellular signalling events under immune response activation or homeostasis conditions.

Electronic supplementary material

The online version of this article (doi:10.1186/s12953-015-0070-9) contains supplementary material, which is available to authorized users.

Reverse Phase Protein Arrays-Quantitative Assessment of Multiple Biomarkers in Biopsies for Clinical Use

Reverse Phase Protein Arrays (RPPA) represent a very promising sensitive and precise high-throughput technology for the quantitative measurement of hundreds of signaling proteins in biological and clinical samples. This array format allows quantification of one protein or phosphoprotein in multiple samples under the same experimental conditions at the same time. Moreover, it is suited for signal transduction profiling of small numbers of cultured cells or cells isolated from human biopsies, including formalin fixed and paraffin embedded (FFPE) tissues. Owing to the much easier sample preparation, as compared to mass spectrometry based technologies, and the extraordinary sensitivity for the detection of low-abundance signaling proteins over a large linear range, RPPA have the potential for characterization of deregulated interconnecting protein pathways and networks in limited amounts of sample material in clinical routine settings. Current aspects of RPPA technology, including dilution curves, spotting, controls, signal detection, antibody validation, and calculation of protein levels are addressed.