Annexin A2 and alpha actinin 4 expression correlates with metastatic potential of primary endometrial cancer

Deciphering the potential of proteomic-based biomarkers in women's reproductive diseases: empowering precision medicine in gynecology

CONTEXT

Gynecological disorders represent a complex set of malignancies that result from a diverse array of molecular changes affecting the lives of over a million women worldwide. Ovarian, Endometrial, and Cervical cancers, Endometriosis, PCOS are the most prevalent ones that pose a grave threat to women's health. Proteomics has emerged as an invaluable tool for developing novel biomarkers, screening methods, and targeted therapeutic agents for gynecological disorders. Some of these biomarkers have been approved by the FDA, but regrettably, they have a constrained diagnostic accuracy in early-stage diagnosis as all of these biomarkers lack sensitivity and specificity. Lately, high-throughput proteomics technologies have made significant strides, allowing for identification of potential biomarkers with improved sensitivity and specificity. However, limited successes have been shown with translation of these discoveries into clinical practice.

OBJECTIVE

This review aims to provide a comprehensive overview of the current and potential protein biomarkers for gynecological cancers, endometriosis and PCOS, discusses recent advances and challenges, and highlights future directions for the field.

CONCLUSION

We propose that proteomics holds great promise as a powerful tool to revolutionize the fight against female reproductive diseases and can ultimately improve personalized patient outcomes in women's biomedicine.

Serum Proteomic Profiles of Patients with High and Low Risk of Endometrial Cancer Recurrence

Endometrial cancer is the most common gynecological cancer worldwide. Classifying endometrial cancer into low- or high-risk groups based on the following features is recommended: tumor grade, lymphovascular space invasion, myometrial involvement, and non-endometrioid histology. Despite the recent progress in molecular profiling of endometrial cancer, a substantial group of patients are misclassified based on the current criteria. This study aimed to identify proteins that could be used as biomarkers for the stratification of endometrial cancer patients into low- or high-risk groups. The proteomic analysis of serum samples from endometrial cancer patients was performed using matrix-assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS). The data were then analyzed using chemometric algorithms to identify potential biomarkers. Nineteen precursor ions were identified as fragments of eighteen proteins which included (1) connective tissue matrix proteins, (2) cytoskeletal proteins, and (3) innate immune system molecules and stress proteins. These biomarkers could be used to stratify the high- and low-risk patients, thus enabling more precise treatment decisions.

Label-Free Quantification Mass Spectrometry Identifies Protein Markers of Chemotherapy Response in High-Grade Serous Ovarian Cancer

Eighty percent of ovarian cancer patients initially respond to chemotherapy, but the majority eventually experience a relapse and die from the disease with acquired chemoresistance. In addition, 20% of patients do not respond to treatment at all, as their disease is intrinsically chemotherapy resistant. Data-independent acquisition nano-flow liquid chromatography-mass spectrometry (DIA LC-MS) identified the three protein markers: gelsolin (GSN), calmodulin (CALM1), and thioredoxin (TXN), to be elevated in high-grade serous ovarian cancer (HGSOC) tissues from patients that responded to chemotherapy compared to those who did not; the differential expression of the three protein markers was confirmed by immunohistochemistry. Analysis of the online GENT2 database showed that mRNA levels of GSN, CALM1, and TXN were decreased in HGSOC compared to fallopian tube epithelium. Elevated levels of GSN and TXN mRNA expression correlated with increased overall and progression-free survival, respectively, in a Kaplan-Meier analysis of a large online repository of HGSOC patient data. Importantly, differential expression of the three protein markers was further confirmed when comparing parental OVCAR-5 cells to carboplatin-resistant OVCAR-5 cells using DIA LC-MS analysis. Our findings suggest that GSN, CALM1, and TXN may be useful biomarkers for predicting chemotherapy response and understanding the mechanisms of chemotherapy resistance. Proteomic data are available via ProteomeXchange with identifier PXD033785.

Mass spectrometry imaging in gynecological cancers: the best is yet to come

Mass spectrometry imaging (MSI) enables obtaining multidimensional results simultaneously in a single run, including regiospecificity and m/z values corresponding with specific proteins, peptides, lipids, etc. The knowledge obtained in this way allows for a multifaceted analysis of the studied issue, e.g., the specificity of the neoplastic process and the search for new therapeutic targets. Despite the enormous possibilities, this relatively new technique in many aspects still requires the development or standardization of analytical protocols (from collecting biological material, through sample preparation, analysis, and data collection, to data processing). The introduction of standardized protocols for MSI studies, with its current potential to extend diagnostic and prognostic capabilities, can revolutionize clinical pathology. As far as identifying ovarian cancer subtypes can be challenging, especially in poorly differentiated tumors, developing MSI-based algorithms may enhance determining prognosis and tumor staging without the need for extensive surgery and optimize the choice of subsequent therapy. MSI might bring new solutions in predicting response to treatment in patients with endometrial cancer. Therefore, MSI may help to revolutionize the future of gynecological oncology in terms of diagnostics, treatment, and predicting the response to therapy. This review will encompass several aspects, e.g., contemporary discoveries in gynecological cancer research utilizing MSI, indicates current challenges, and future perspectives on MSI.

A Protocol for the Acquisition of Comprehensive Proteomics Data from Single Cases Using Formalin-Fixed Paraffin Embedded Sections

The molecular analysis of small or rare patient tissue samples is challenging and often limited by available technologies and resources, such as reliable antibodies against a protein of interest. Although targeted approaches provide some insight, here, we describe the workflow of two complementary mass spectrometry approaches, which provide a more comprehensive and non-biased analysis of the molecular features of the tissue of interest. Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) generates spatial intensity maps of molecular features, which can be easily correlated with histology. Additionally, liquid chromatography tandem mass spectrometry (LC-MS/MS) can identify and quantify proteins of interest from a consecutive section of the same tissue. Here, we present data from concurrent precancerous lesions from the endometrium and fallopian tube of a single patient. Using this complementary approach, we monitored the abundance of hundreds of proteins within the precancerous and neighboring healthy regions. The method described here represents a useful tool to maximize the number of molecular data acquired from small sample sizes or even from a single case. Our initial data are indicative of a migratory phenotype in these lesions and warrant further research into their malignant capabilities.

Knockdown of Annexin A2 Enhances Radiosensitivity by Increasing G2/M-Phase Arrest, Apoptosis and Activating the p38 MAPK-HSP27 Pathway in Nasopharyngeal Carcinoma

Annexin A2 (ANXA2) has been found to be involved in cancer proliferation, metastasis and prognosis; however, its exact role in nasopharyngeal carcinoma (NPC) radioresistance remains unknown. We found that ANXA2 expression was correlated with prognosis in NPC patients, and longer overall survival in NPC patients with low ANXA2 expression than those with high ANXA2 expression. ANXA2 knockdown increased the radiosensitivity in radioresistant NPC cells, and ANXA2 overexpression decreased the radiosensitivity in NPC cells. Knocking-down ANXA2 expression increased the irradiation-induced apoptosis of radioresistant NPC cells, and ANXA2 overexpression decreased the irradiation-induced apoptosis of NPC cells. ANXA2 knockdown induced G2/M phase arrest in NPC cells post-irradiation, and ANXA2 overexpression abrogated G2/M phase arrest in NPC cells post-irradiation. ANXA2 overexpression resulted in inhibition of the p38 MAPK-HSP27 pathway, while ANXA2 knockdown resulted in activation of the p38 MAPK-HSP27 pathway. In addition, ANXA2 knockdown increased the radiosensitivity of the xenografted tumors in nude mice. Our data demonstrate that knockdown of Annexin A2 enhanced radiosensitivity in NPC by increasing G2/M-phase arrest, apoptosis and activating the p38 MAPK-HSP27 pathway. ANXA2 may be a promising target used to overcome radioresistance in NPC.

Cancer Tissue Classification Using Supervised Machine Learning Applied to MALDI Mass Spectrometry Imaging

Simple Summary

Classic histopathological examination of tissues remains the mainstay for cancer diagnosis and staging. However, in some cases histopathologic analysis yields ambiguous results, leading to inconclusive disease classification. We set out to explore the diagnostic potential of mass spectrometry-based imaging for tumour classification based on proteomic fingerprints. Combining mass spectrometry with supervised machine learning, we were able to distinguish colorectal tumor from normal tissue with an overall accuracy of 98%. In addition, this approach was able to predict the presence of lymph node metastasis in primary tumour of endometrial cancer with an overall accuracy of 80%. These results highlight the potential of this technology to determine the optimal treatment for cancer patients to reduce morbidity and improve patients’ outcomes.

Abstract

Matrix assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) can determine the spatial distribution of analytes such as protein distributions in a tissue section according to their mass-to-charge ratio. Here, we explored the clinical potential of machine learning (ML) applied to MALDI MSI data for cancer diagnostic classification using tissue microarrays (TMAs) on 302 colorectal (CRC) and 257 endometrial cancer (EC)) patients. ML based on deep neural networks discriminated colorectal tumour from normal tissue with an overall accuracy of 98% in balanced cross-validation (98.2% sensitivity and 98.6% specificity). Moreover, our machine learning approach predicted the presence of lymph node metastasis (LNM) for primary tumours of EC with an accuracy of 80% (90% sensitivity and 69% specificity). Our results demonstrate the capability of MALDI MSI for complementing classic histopathological examination for cancer diagnostic applications.

Proteomic Analysis of Pre-Invasive Serous Lesions of the Endometrium and Fallopian Tube Reveals Their Metastatic Potential

Serous endometrial cancer (SEC) and high grade serous ovarian cancer (HGSOC) are aggressive gynecological malignancies with high rates of metastasis and poor prognosis. Endometrial intraepithelial carcinoma (EIC), the precursor for SEC, and serous tubal intraepithelial carcinoma (STIC), believed to be the precursor lesion for HGSOC, can also be associated with intraabdominal spread. To provide insight into the etiology of these precancerous lesions and to explore the potential molecular mechanisms underlying their metastatic behavior, we performed a proteomic mass spectrometry analysis in a patient with synchronous EIC and STIC. Through histological and molecular identification of precancerous lesions followed by laser capture microdissection, we were able to identify over 450 proteins within the precancerous lesions and adjacent healthy tissue. The proteomic analysis of STIC and EIC showed remarkable overlap in the proteomic patterns, reflecting early neoplastic changes in proliferation, loss of polarity and attachment. Our proteomic analysis showed that both EIC and STIC, despite being regarded as premalignant lesions, have metastatic potential, which correlates with the common presentation of invasive serous gynecological malignancies at advanced stage.

Altered N-linked glycosylation in endometrial cancer

It is well established that cell surface glycans play a vital role in biological processes and their altered form can lead to carcinogenesis. Mass spectrometry-based techniques have become prominent for analysing N-linked glycans, for example using matrix-assisted laser desorption/ionization mass spectrometry (MALDI MS). Additionally, MALDI MS can be used to spatially map N-linked glycans directly from cancer tissue using a technique termed MALDI MS imaging (MALDI MSI). This powerful technique combines mass spectrometry and histology to visualise the spatial distribution of N-linked glycans on a single tissue section. Here, we performed N-glycan MALDI MSI on six endometrial cancer (EC) formalin-fixed paraffin-embedded (FFPE) tissue sections and tissue microarrays (TMA) consisting of eight EC patients with lymph node metastasis (LNM) and twenty without LNM. By doing so, several putative N-linked glycan compositions were detected that could significantly distinguish normal from cancerous endometrium. Furthermore, a complex core-fucosylated N-linked glycan was detected that could discriminate a primary tumour with and without LNM. Structural identification of these putative N-linked glycans was performed using porous graphitized carbon liquid chromatography tandem mass spectrometry (PGC-LC-MS/MS). Overall, we observed higher abundance of oligomannose glycans in tumour compared to normal regions with AUC ranging from 0.85-0.99, and lower abundance of complex N-linked glycans with AUC ranges from 0.03-0.28. A comparison of N-linked glycans between primary tumours with and without LNM indicated a reduced abundance of a complex core-fucosylated N-glycan (Hex)₂(HexNAc)₂(Deoxyhexose)₁+(Man)₃(GlcNAc)₂, in primary tumour with associated lymph node metastasis. In summary, N-linked glycan MALDI MSI can be used to differentiate cancerous endometrium from normal, and endometrial cancer with LNM from endometrial cancer without.

The mechanobiome: a goldmine for cancer therapeutics

Cancer progression is dependent on heightened mechanical adaptation, both for the cells' ability to change shape and to interact with varying mechanical environments. This type of adaptation is dependent on mechanoresponsive proteins that sense and respond to mechanical stress, as well as their regulators. Mechanoresponsive proteins are part of the mechanobiome, which is the larger network that constitutes the cell's mechanical systems that are also highly integrated with many other cellular systems, such as gene expression, metabolism, and signaling. Despite the altered expression patterns of key mechanobiome proteins across many different cancer types, pharmaceutical targeting of these proteins has been overlooked. Here, we review the biochemistry of key mechanoresponsive proteins, specifically nonmuscle myosin II, α-actinins, and filamins, as well as the partnering proteins 14-3-3 and CLP36. We also examined a wide range of data sets to assess how gene and protein expression levels of these proteins are altered across many different cancer types. Finally, we determined the potential of targeting these proteins to mitigate invasion or metastasis and suggest that the mechanobiome is a goldmine of opportunity for anticancer drug discovery and development.

Uncovering Tumor-Stroma Inter-relationships Using MALDI Mass Spectrometry Imaging

Tumorigenesis involves a complex interplay between genetically modified cancer cells and their adjacent normal tissue, the stroma. We used an established breast cancer mouse model to investigate this inter-relationship. Conditional activation of Rho-associated protein kinase (ROCK) in a model of mammary tumorigenesis enhances tumor growth and progression by educating the stroma and enhancing the production and remodeling of the extracellular matrix. We used peptide matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI) to quantify the proteomic changes occurring within tumors and their stroma in their regular spatial context. Peptides were ranked according to their ability to discriminate between the two groups, using a receiver operating characteristic tool. Peptides were identified by liquid chromatography tandem mass spectrometry, and protein expression was validated by quantitative immunofluorescence using an independent set of tumor samples. We have identified and validated four key proteins upregulated in ROCK-activated mammary tumors relative to those expressing kinase-dead ROCK, namely, collagen I, α-SMA, Rab14, and tubulin-β4. Rab14 and tubulin-β4 are expressed within tumor cells, whereas collagen I is localized within the stroma. α-SMA is predominantly localized within the stroma but is also expressed at higher levels in the epithelia of ROCK-activated tumors. High expression of COL1A, the gene encoding the pro-α 1 chain of collagen, correlates with cancer progression in two human breast cancer genomic data sets, and high expression of COL1A and ACTA2 (the gene encoding α-SMA) are associated with a low survival probability (COLIA, p = 0.00013; ACTA2, p = 0.0076) in estrogen receptor-negative breast cancer patients. To investigate whether ROCK-activated tumor cells cause stromal cancer-associated fibroblasts (CAFs) to upregulate expression of collagen I and α-SMA, we treated CAFs with medium conditioned by primary mammary tumor cells in which ROCK had been activated. This led to abundant production of both proteins in CAFs, clearly highlighting the inter-relationship between tumor cells and CAFs and identifying CAFs as the potential source of high levels of collagen 1 and α-SMA and associated enhancement of tissue stiffness. Our research emphasizes the capacity of MALDI-MSI to quantitatively assess tumor-stroma inter-relationships and to identify potential prognostic factors for cancer progression in human patients, using sophisticated mouse cancer models.

Mass Spectrometric (MS) Analysis of Proteins and Peptides

The human genome is sequenced and comprised of ~30,000 genes, making humans just a little bit more complicated than worms or flies. However, complexity of humans is given by proteins that these genes code for because one gene can produce many proteins mostly through alternative splicing and tissue-dependent expression of particular proteins. In addition, post-translational modifications (PTMs) in proteins greatly increase the number of gene products or protein isoforms. Furthermore, stable and transient interactions between proteins, protein isoforms/proteoforms and PTM-ed proteins (protein-protein interactions, PPI) add yet another level of complexity in humans and other organisms. In the past, all of these proteins were analyzed one at the time. Currently, they are analyzed by a less tedious method: mass spectrometry (MS) for two reasons: 1) because of the complexity of proteins, protein PTMs and PPIs and 2) because MS is the only method that can keep up with such a complex array of features. Here, we discuss the applications of mass spectrometry in protein analysis.

Egg White as a Quality Control in Matrix-Assisted Laser Desorption/Ionization Mass Spectrometry Imaging (MALDI-MSI)

The strength of MALDI-MSI is to analyze and visualize spatial intensities of molecular features from an intact tissue. The distribution of the intensities can then be visualized within a single tissue section or compared in between sections, acquired consecutively. This method can be reliably used to reveal physiological structures and has the potential to identify molecular details, which correlate with biological outcomes. MALDI-MSI implementation in clinical laboratories requires the ability to ensure method quality and validation to meet diagnostic expectations. To be able to get consistent qualitative and quantitative results, standardized sample preparation and data acquisition are of highest priority. We have previously shown that the deposition of internal standards onto the tissue section during sample preparation can be used to improve the mass accuracy of monitored m/z features across the sample. Here, we present the use of external and internal controls for the quality check of sample preparation and data acquisition, which is particularly relevant when either many spectra are acquired during a single MALDI-MSI experiment or data from independent experiments are processed together. To monitor detector performance and sample preparation, we use egg white as an external control for peptide and N-glycan MALDI-MSI throughout the experiment. We have also identified endogenous peptides from cytoskeletal proteins, which can be reliably monitored in gynecological tissue samples. Lastly, we summarize our standard quality control workflow designed to produce reliable and comparable MALDI-MSI data from single sections and tissue microarrays (TMAs).

The Emerging Role of Cytoskeletal Proteins as Reliable Biomarkers

Cytoskeletal proteins are essential building blocks of cells. More than 100 cytoskeletal and cytoskeleton-associated proteins are known and for some, their function and regulation are understood in great detail. Apart from cell shape and support, they facilitate many processes such as intracellular signaling and transport, and cancer related processes such as proliferation, migration, and invasion. During the last decade, comparative proteomic studies have identified cytoskeletal proteins as in vitro markers for tumor progression and metastasis. Here, these results are summarized and a number of unrelated studies are highlighted, identifying the same cytoskeletal proteins as potential biomarkers. These findings might indicate that the abundance of these potential markers of tumor progression is associated with the biological outcome and are independent of the cancer origin. This correlates well with recently published results from the Cancer Genome Atlas, indicating that cancers show remarkable similarities in their analyzed molecular information, independent of their organ of origin. It is postulated that the quantification of cytoskeletal proteins in healthy tissues, tumors, in adjacent tissues, and in stroma, is a great source of molecular information, which might not only be used to classify tumors, but more importantly to predict patients' outcome or even best treatment choices.

Expression of p53 and PTEN in human primary endometrial carcinomas: Clinicopathological and immunohistochemical analysis and study of their concomitant expression

Endometrial carcinoma is a common malignancy of the female genital tract. Alterations in the expression levels of various oncogenes and tumor suppressor genes serve important roles in the carcinogenesis and biological behavior of endometrial carcinoma. The aim of the present study was to evaluate the combination and individual expression of p53 and phosphatase and tensin homolog (PTEN) protein in human endometrial carcinoma. In addition, the correlation of these proteins with clinicopathological parameters was also assessed. Retrospective immunohistochemical analysis of the expression of p53 and PTEN tumor suppressor proteins was conducted in 99 women with endometrial carcinoma. The overall rate of p53 and PTEN positivity was 89 and 77%, respectively, according to the sum of stain intensity and scores of immunopositive cells. The sum of p53 positivity correlated strongly with PTEN expression (ρ=0.256; P=0.044). The concomitant sum of p53 and PTEN expression was identified in 45% of patients with endometrial adenocarcinoma. Notably, the sum of the immunohistochemical expression of p53 was significantly correlated with patient age (P=0.037), histologic type (P=0.008), histologic grade (P=0.002) and fallopian and/or ovarian invasion (P=0.014). Furthermore, PTEN expression was associated with myometrial invasion (ρ=−0.377; P=0.002) and clinical stage (P=0.019). In addition, concomitant p53 and PTEN expression was correlated with patient age (P=0.008) and histologic differentiation (P=0.028). The findings indicated a correlation between the expression of p53 and PTEN in endometrial adenocarcinoma, which suggested an intrinsic association between expression levels of these tumor suppressor genes. The study also suggested that concomitant p53 and PTEN expression contributed in characterizing the tumor behavior of endometrial carcinoma. Taken together, the present study suggested the combined expression of p53 and PTEN in the development of high-grade endometrial carcinoma in older patients. In addition, the findings indicated activation of different molecular pathways in the tumor progression between low-grade and high-grade endometrial carcinomas.

Proteomic Characterization of Epithelial-Like Extracellular Vesicles in Advanced Endometrial Cancer

Endometrial cancer (EC) is the most frequent gynecological cancer. Tumor dissemination affecting ∼20% of EC patients is characterized at the primary carcinoma by epithelial-to-mesenchymal transition (EMT) associated with myometrial infiltration. At distant sites, the interaction of circulating tumor cells (CTCs) with the microenvironment is crucial for metastatic colonization, with a participation of the extracellular vesicles (EVs). We comprehensively approached these primary and secondary sites to study the impact of tumor EVs on the metastatic efficiency of CTCs in EC. Tumor EVs in circulation reproduce the epithelial phenotype predominant in the primary carcinoma, whereas CTCs are characterized by an EMT phenotype. We modeled this EMT-related clinical scenario in the Hec1A endometrial cell line and characterized the epithelial-like EVs in circulation by SILAC proteome analysis. The identification of proteins involved in cell-cell and cell-matrix interaction and binding, together with in vitro evidence of an improved adhesion of CTC to a functionalized endothelium, suggests a contribution of the epithelial-like EVs in the homing of CTCs at metastatic sites. Accordingly, adhesion protein LGALS3BP was found to be significantly enriched in circulating EVs from a cohort of EC patients with a high risk of recurrence by targeted proteomics (multiple reaction monitoring), highlighting its potential in liquid biopsy in EC.

Proteome Imaging: From Classic to Modern Mass Spectrometry-Based Molecular Histology

In order to overcome the limitations of classic imaging in Histology during the actually era of multiomics, the multi-color "molecular microscope" by its emerging "molecular pictures" offers quantitative and spatial information about thousands of molecular profiles without labeling of potential targets. Healthy and diseased human tissues, as well as those of diverse invertebrate and vertebrate animal models, including genetically engineered species and cultured cells, can be easily analyzed by histology-directed MALDI imaging mass spectrometry. The aims of this review are to discuss a range of proteomic information emerging from MALDI mass spectrometry imaging comparative to classic histology, histochemistry and immunohistochemistry, with applications in biology and medicine, concerning the detection and distribution of structural proteins and biological active molecules, such as antimicrobial peptides and proteins, allergens, neurotransmitters and hormones, enzymes, growth factors, toxins and others. The molecular imaging is very well suited for discovery and validation of candidate protein biomarkers in neuroproteomics, oncoproteomics, aging and age-related diseases, parasitoproteomics, forensic, and ecotoxicology. Additionally, in situ proteome imaging may help to elucidate the physiological and pathological mechanisms involved in developmental biology, reproductive research, amyloidogenesis, tumorigenesis, wound healing, neural network regeneration, matrix mineralization, apoptosis and oxidative stress, pain tolerance, cell cycle and transformation under oncogenic stress, tumor heterogeneity, behavior and aggressiveness, drugs bioaccumulation and biotransformation, organism's reaction against environmental penetrating xenobiotics, immune signaling, assessment of integrity and functionality of tissue barriers, behavioral biology, and molecular origins of diseases. MALDI MSI is certainly a valuable tool for personalized medicine and "Eco-Evo-Devo" integrative biology in the current context of global environmental challenges.

Site-to-Site Reproducibility and Spatial Resolution in MALDI-MSI of Peptides from Formalin-Fixed Paraffin-Embedded Samples

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.

Cytokine-Induced Killer Cells Express CD39, CD38, CD203a, CD73 Ectoenzymes and P1 Adenosinergic Receptors

Cytokine-induced killer (CIK) cells, a heterogeneous T cell population obtained by in vitro differentiation of peripheral blood mononuclear cells (PBMC), represent a promising immunological approach in cancer. Numerous studies have explored the role of CD38, CD39, CD203a/PC-1, and CD73 in generating extracellular adenosine (ADO) and thus in shaping the tumor niche in favor of proliferation. The findings shown here reveal that CIK cells are able to produce extracellular ADO via traditional (CD39/CD73) and/or alternative (CD38/CD203a/CD73 or CD203a/CD73) pathways. Transcriptome analysis showed the mRNA expression of these molecules and their modulation during PBMC to CIK differentiation. When PBMC from normal subjects or cancer bearing patients were differentiated into CIK cells under normoxic conditions, CD38 and CD39 were greatly up-regulated while the number of CD203a, and CD73 positive cells underwent minor changes. Since hypoxic conditions are often found in tumors, we asked whether CD39, CD38, CD203a, and CD73 expressed by CIK cells were modulated by hypoxia. PBMC isolated from cancer patients and differentiated into CIK cells in hypoxic conditions did not show relevant changes in CD38, CD39, CD73, CD203a, and CD26. CIK cells also expressed A₁, A_2A, and A_2B ADO receptors and they only underwent minor changes as a consequence of hypoxia. The present study sheds light on a previously unknown functional aspect of CIK cells, opening the possibility of pharmacologically modulated ADO-generating ectoezymes to improve CIK cells performance.