HarmonizR enables data harmonization across independent proteomic datasets with appropriate handling of missing values.

Dataset integration is common practice to overcome limitations in statistically underpowered omics datasets. Proteome datasets display high technical variability and frequent missing values. Sophisticated strategies for batch effect reduction are lacking or rely on error-prone data imputation. Here we introduce HarmonizR, a data harmonization tool with appropriate missing value handling. The method exploits the structure of available data and matrix dissection for minimal data loss, without data imputation. This strategy implements two common batch effect reduction methods-ComBat and limma (removeBatchEffect()). The HarmonizR strategy, evaluated on four exemplarily analyzed datasets with up to 23 batches, demonstrated successful data harmonization for different tissue preservation techniques, LC-MS/MS instrumentation setups, and quantification approaches. Compared to data imputation methods, HarmonizR was more efficient and performed superior regarding the detection of significant proteins. HarmonizR is an efficient tool for missing data tolerant experimental variance reduction and is easily adjustable for individual dataset properties and user preferences.

Circulating Cellular Communication Network Factor 1 Protein as a Sensitive Liquid Biopsy Marker for Early Detection of Breast Cancer.

BACKGROUND: Despite recent progress in liquid biopsy technologies, early blood-based detection of breast cancer is still a challenge. METHODS: We analyzed secretion of the protein cellular communication network factor 1 (CCN1, formerly cysteine-rich angiogenic inducer 61) in breast cancer cell lines by an enzyme-linked immunosorbent assay (ELISA). Soluble CCN1 in the plasma (2.5 µL) of 544 patients with breast cancer and 427 healthy controls was analyzed by ELISA. The breast cancer samples were acquired at the time of primary diagnosis prior to neoadjuvant therapy or surgery. A classifier was established on a training cohort of patients with breast cancer and age-adapted healthy controls and further validated on an independent cohort comprising breast cancer patients and healthy controls. Samples from patients with benign breast diseases were investigated as additional controls. Samples from patients with acute heart diseases (n = 127) were investigated as noncancer controls. The diagnostic accuracy was determined by receiver operating characteristic using the parameters area under the curve, sensitivity, and specificity. RESULTS: CCN1 was frequently secreted by breast cancer cell lines into the extracellular space. Subsequent analysis of clinical blood samples from patients with breast cancer and age-adjusted healthy controls revealed an overall specificity of 99.0% and sensitivity of 80.0% for cancer detection. Remarkably, 81.5% of small T1 cancers were already CCN1-positive, while CCN1 concentrations in patients with benign breast lesions were below the threshold for breast cancer detection. CONCLUSIONS: Circulating CCN1 is a potentially novel blood biomarker for the detection of breast cancer at the earliest invasive stage.

Differential regulation of extracellular matrix proteins in three recurrent liver metastases of a single patient with colorectal cancer.

Colorectal cancer (CRC) patients suffer from the second highest mortality among all cancer entities. In half of all CRC patients, colorectal cancer liver metastases (CRLM) can be observed. Metastatic colorectal cancer is associated with poor overall survival and limited treatment options. Even after successful surgical resection of the primary tumor, metachronous liver metastases occur in one out of eight cases. The only available curative intended treatment is hepatic resection, but metachronous CRLM frequently recur after approximately 1 year. In this study, we performed a proteome analysis of three recurrent liver metastases of a single CRC patient by mass spectrometry. Despite surgical resection of the primary CRC and adjuvant chemotherapy plus cetuximab treatment, the patient developed three metachronous CRLM which occurred consecutively after 9, 21 and 31 months. We identified a set of 1132 proteins expressed in the three metachronous CRLM, of which 481 were differentially regulated, including 81 proteins that were associated with the extracellular matrix (ECM). 56 ECM associated proteins were identified as upregulated in the third metastasis, 26 (46%) of which were previously described as negative prognostic markers in CRC, including tenascin C, nidogen 1, fibulin 1 and vitronectin. These data may reflect an ascending trend of malignancy from the first to the third metachronous colorectal cancer liver metastasis. Additionally, the results indicate different ECM phenotypes for recurrent metachronous metastasis, associated with different grades of malignancy and highlights the importance of individual analysis of molecular features in different, consecutive metastatic events in a single patient.

Mass Spectrometric Comparison of HPV-Positive and HPV-Negative Oropharyngeal Cancer.

Squamous cell carcinoma of the head and neck (HNSCC) consist of two distinct biological entities. While the numbers of classical, tobacco-induced HNSCC are declining, tumors caused by human papillomavirus (HPV) infection are increasing in many countries. HPV-positive HNSCC mostly arise in the oropharynx and are characterized by an enhanced sensitivity towards radiotherapy and a favorable prognosis. To identify molecular differences between both entities on the protein level, we conducted a mass spectrometric comparison of eight HPV-positive and nine HPV-negative oropharyngeal tumors (OPSCC). Overall, we identified 2051 proteins, of which 31 were found to be differentially expressed. Seventeen of these can be assorted to three functional groups, namely DNA replication, nuclear architecture and cytoskeleton regulation, with the differences in the last group potentially reflecting an enhanced migratory and invasive capacity. Furthermore, a number of identified proteins have been described to directly impact on DNA double-strand break repair or radiation sensitivity (e.g., SLC3A2, cortactin, RBBP4, Numa1), offering explanations for the differential prognosis. The unequal expression of three proteins (SLC3A2, MCM2 and lamin B1) was confirmed by immunohistochemical staining using a tissue microarray containing 205 OPSCC samples. The expression levels of SLC3A2 and lamin B1 were found be of prognostic relevance in patients with HPV-positive and HPV-negative OPSCC, respectively.

Mass Spectrometric Lipid Profiles of Picosecond Infrared Laser-Generated Tissue Aerosols Discriminate Different Brain Tissues.

BACKGROUND AND OBJECTIVES: A picosecond infrared laser (PIRL) has recently been demonstrated to cut biological tissue without scar formation based on the minimal destructive action on the surrounding cells. During cutting with PIRL, the irradiated tissue is ablated by a cold vaporization process termed desorption by impulsive vibrational excitation. In the resulting aerosol, all molecules are dissolved in small droplets and even labile biomolecules like proteins remain intact after ablation. It is hypothesized that these properties enable the PIRL in combination with mass spectrometry as an intelligent laser scalpel for guided surgery. In this study, it was tested if PIRL-generated tissue aerosols are applicable for direct analysis with mass spectrometry, and if the acquired mass spectra can be used to discriminate different brain areas. MATERIALS AND METHODS: Brain tissues were irradiated with PIRL. The aerosols were collected and directly infused into a mass spectrometer via electrospray ionization without any sample preparation or lipid extraction. RESULTS: The laser produced clear cuts with no marks of burning. Lipids from five different classes were identified in the mass spectra of all samples. By principal component analysis the different brain areas were clearly distinguishable from each other. CONCLUSIONS: The results demonstrate the potential for real-time analysis of lipids with a PIRL-based laser scalpel, coupled to a mass spectrometer, for the discrimination of tissues during surgeries. Lasers Surg. Med. © 2019 Wiley Periodicals, Inc.

Understanding Protein Networks Using Vester's Sensitivity Model.

Magnesium-based biomaterials belong to the third generation of biomaterials that are also bioactive. These smart materials combine bioactivity and biodegradability, and elicit specific cellular responses at the molecular level. In fact, osteoinductive properties have been observed in mesenchymal stem cells in the presence of Magnesium. The mechanistic understanding of the physiological effects however, remains a difficult task as Mg is involved in a multitude of biological reactions. The study of protein interactions may shed light on the molecular processes in Mg-stimulated cells, therefore, suitable data mining tools are required to analyze the large amount data generated via proteomics. Protein compositions over time between two conditions (human mesenchymal stem cells cultured with and without Mg degradation products) were analyzed using Vester's Sensitivity Model. Proteins whose dynamics significantly change from one setup to the other were classified into four categories: passive, active, critical, and buffering according to their regulatory activity. In this work, we demonstrated the use of Vester's Sensitivity Model as an appropriate data mining tool. Protein network analyses highlighted the primary role of Mg-based implant degradation on cell metabolism without deleterious effect on cell viability. Furthermore, key proteins involved in calcium-dependant cellular activities were emphasized leading to further studies.

Proteome analysis of human mesenchymal stem cells undergoing chondrogenesis when exposed to the products of various magnesium-based materials degradation.

Treatment of physeal fractures (15%-30% of all paediatric fractures) remains a challenge as in approximately 10% of the cases, significant growth disturbance may occur. Bioresorbable Magnesium-based implants represent a strategy to minimize damage (i.e., load support until bone healing without second surgery). Nevertheless, the absence of harmful effects of magnesium-implants and their degradation products on the growth plate should be confirmed. Here, the proteome of human mesenchymal stem cells undergoing chondrogenesis was evaluated when exposed to the products of various Magnesium-based materials degradation. The results of this study indicate that the materials induced regulation of proteins associated with cell chondrogenesis and cartilage formation, which should be beneficial for cartilage regeneration.

Differential Proteome Analysis of Human Neuroblastoma Xenograft Primary Tumors and Matched Spontaneous Distant Metastases.

Metastasis formation is the major cause for cancer-related deaths and the underlying mechanisms remain poorly understood. In this study we describe spontaneous metastasis xenograft mouse models of human neuroblastoma used for unbiased identification of metastasis-related proteins by applying an infrared laser (IR) for sampling primary tumor and metastatic tissues, followed by mass spectrometric proteome analysis. IR aerosol samples were obtained from ovarian and liver metastases, which were indicated by bioluminescence imaging (BLI), and matched subcutaneous primary tumors. Corresponding histology proved the human origin of metastatic lesions. Ovarian metastases were commonly larger than liver metastases indicating differential outgrowth capacities. Among ~1,900 proteins identified at each of the three sites, 55 proteins were differentially regulated in ovarian metastases while 312 proteins were regulated in liver metastases. There was an overlap of 21 and 7 proteins up- and down-regulated at both metastatic sites, respectively, most of which were so far not related to metastasis such as LYPLA2, EIF4B, DPY30, LGALS7, PRPH, and NEFM. Moreover, we established in vitro sublines from primary tumor and metastases and demonstrate differences in cellular protrusions, migratory/invasive potential and glycosylation. Summarized, this work identified several novel putative drivers of metastasis formation that are tempting candidates for future functional studies.

Application of Displacement Chromatography to Online Two-Dimensional Liquid Chromatography Coupled to Tandem Mass Spectrometry Improves Peptide Separation Efficiency and Detectability for the Analysis of Complex Proteomes.

The complexity of mammalian proteomes is a challenge in bottom-up proteomics. For a comprehensive proteome analysis, multidimensional separation strategies are necessary. Online two-dimensional liquid chromatography-tandem mass spectrometry (2D-LC-MS/MS) combining strong cation exchange (SCX) in the first dimension with reversed-phase (RP) chromatography in the second dimension provides a powerful approach to analyze complex proteomes. Although the combination of SCX with RP chromatography provides a good orthogonality, only a moderate separation is achieved in the first dimension for peptides with two (+2) or three (+3) positive charges. The aim of this study was to improve the performance of online SCX-RP-MS/MS by applying displacement chromatography to the first separation dimension. Compared to gradient chromatography mode (GCM), displacement chromatography mode (DCM) was expected to improve the separation of +2-peptides and +3-peptides, thus reducing complexity and increasing ionization and detectability. The results show that DCM provided a separation of +2-peptides and +3-peptides in remarkably sharp zones with a low degree of coelution, thus providing fractions with significantly higher purities compared to GCM. In particular, +2-peptides were separated over several fractions, which was not possible to achieve in GCM. The better separation in DCM resulted in a higher reproducibility and significantly higher identification rates for both peptides and proteins including a 2.6-fold increase for +2-peptides. The higher number of identified peptides in DCM resulted in significantly higher protein sequence coverages and a considerably higher number of unique peptides per protein. Compared to conventionally used salt-based GCM, DCM increased the performance of online SCX-RP-MS/MS and enabled comprehensive proteome profiling in the low microgram range.

Quantitative Lipid Droplet Proteome Analysis Identifies Annexin A3 as a Cofactor for HCV Particle Production.

Lipid droplets are vital to hepatitis C virus (HCV) infection as the putative sites of virion assembly, but morphogenesis and egress of virions remain ill defined. We performed quantitative lipid droplet proteome analysis of HCV-infected cells to identify co-factors of that process. Our results demonstrate that HCV disconnects lipid droplets from their metabolic function. Annexin A3 (ANXA3), a protein enriched in lipid droplet fractions, strongly impacted HCV replication and was characterized further: ANXA3 is recruited to lipid-rich fractions in HCV-infected cells by the viral core and NS5A proteins. ANXA3 knockdown does not affect HCV RNA replication but severely impairs virion production with lower specific infectivity and higher density of secreted virions. ANXA3 is essential for the interaction of viral envelope E2 with apolipoprotein E (ApoE) and for trafficking, but not lipidation, of ApoE in HCV-infected cells. Thus, we identified ANXA3 as a regulator of HCV maturation and egress.

Quantitative proteomics unveiled: Regulation of DNA double strand break repair by EGFR involves PARP1.

BACKGROUND: EGFR inhibition blocks DNA double strand break (DSB) repair but the detailed mechanisms are still unclear. We asked whether EGFR inhibition blocks DSB repair by reducing the X-ray-induced phosphorylation of repair proteins using a phosphoproteomic approach. MATERIALS AND METHODS: Using UT-SCC5 and SAS head and neck cancer cells we established a differential phosphoproteomic approach for quantitative analysis of DNA repair proteins by stable isotope labeling with amino acids. Nuclear phosphoproteins were isolated and analyzed by liquid chromatography/tandem mass spectrometry. Erlotinib, PD98059 and olaparib were used to inhibit EGFR, MEK1/2 and PARP1, respectively. PARP1 was knocked down by siRNA. DSB repair was measured by quantifying residual 53BP1 foci. RESULTS: Over 150 nuclear phosphoproteins were quantified after irradiation, including 24 DNA repair proteins. Two of these, including PARP1, were consistently reduced in both cell lines upon erlotinib treatment. PARP1 inhibition or knock-down and EGFR inhibition resulted in an analog number of residual foci which was not further increased by combination of both strategies. MEK1/2 inhibition with or without blockage of EGFR or PARP1 caused similar effects. CONCLUSION: We have established a powerful, quantitative phosphoproteomic approach to investigate regulatory mechanisms in DSB repair, dependent on protein phosphorylation after irradiation. Using this approach we have identified PARP1 as a mediator of EGFR/MEK-dependent regulation of DSB repair.

Ultrafast extraction of proteins from tissues using desorption by impulsive vibrational excitation.

A picosecond IR laser (PIRL) can be used to blast proteins out of tissues through desorption by impulsive excitation (DIVE) of intramolecular vibrational states of water molecules in the cell in less than a millisecond. With PIRL-DIVE proteins covering a range of a few kDa up to several MDa are extracted in high quantities compared to conventional approaches. The chemical composition of extracted proteins remains unaltered and even enzymatic activities are maintained.

MALDI imaging-based identification of prognostically relevant signals in bladder cancer using large-scale tissue microarrays.

OBJECTIVE: Although most patients with urinary bladder cancer present with noninvasive and low-malignant stages of the disease, about 20% eventually develop life-threatening metastatic tumors. This study was designed to evaluate the potential of matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging (MSI) to identify molecular markers predicting the clinical course of bladder cancer. MATERIALS AND METHODS: We employed MALDI-MSI to a bladder cancer tissue microarray including paraffin-embedded tissue samples from 697 patients with clinical follow-up data to search for prognostically relevant associations. RESULTS: Analysis of our MALDI imaging data revealed 40 signals in the mass spectra (m/z signals) associated with epithelial structures. The presence of numerous m/z signals was statistically related to one or several phenotypical findings including tumor aggressiveness (stage, grade, or nodal status; 30 signals), solid (5 signals) or papillary (3 signals) growth patterns, and increased (6 signals) or decreased (12 signals) cell proliferation, as determined by Ki-67 immunohistochemistry. Two signals were linked with tumor recurrence in noninvasive (pTa category) tumors, of which one was also related to progression from pTa-category to pT1-category disease. The absence of one m/z signal was linked with decreased survival in the subset of 102 muscle-invasive cancers. CONCLUSION: Our data demonstrate the suitability of combining MSI and large-scale tissue microarrays to simultaneously identify and validate clinically useful molecular markers in urinary bladder cancer.

MALDI imaging on tissue microarrays identifies molecular features associated with renal cell cancer phenotype.

AIM: To identify molecular features associated with clinico-pathological parameters in renal cell cancer. MATERIALS AND METHODS: Matrix-assisted laser desorption/ionization (MALDI) mass spectrometry imaging was employed for a kidney cancer tissue microarray containing tissue samples from 789 patients for which clinical follow-up data were available. RESULTS: A comparison of mass spectrometric signals with clinico-pathological features revealed significant differences between papillary and clear cell renal cell cancer. Within the subgroup of clear cell RCC, statistical associations with tumor stage (seven signals, p<0.01 each), Fuhrman grade (seven signals, p<0.0001 each), and presence of lymph node metastases (10 signals, p<0.01 each) were found. In addition, the presence of one signal was significantly linked to shortened patient survival (p=0.0198). CONCLUSION: Our data pinpoint towards various molecules with potential relevance in renal cell cancer. They also demonstrate that the combination of the MALDI mass spectrometry imaging and large-scale tissue microarray platforms represents a powerful approach to identify clinically-relevant molecular cancer features.

MALDI imaging on large-scale tissue microarrays identifies molecular features associated with tumour phenotype in oesophageal cancer.

AIMS: Matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) and tissue microarray (TMA) technologies were jointly utilized to search for molecular features associated with clinicopathological parameters in oesophageal cancer. METHODS AND RESULTS: Two TMAs from formalin-fixed tissue samples, including 300 adenocarcinomas and 177 squamous cell carcinomas with clinical follow-up data, were analysed. MALDI-MSI analysis revealed 72 distinct mass per charge (m/z) signals associated with tumour cells, 48 of which were found in squamous cell carcinomas only, and 12 of which were specific for adenocarcinomas. In adenocarcinomas, six signals were linked to early-stage (pT1-T2) tumours (two signals) and the presence (one signal) or absence (three signals) of lymph node metastasis. In squamous cell carcinomas, 24 signals were strongly linked to different phenotypic features, including tumour stage (four signals), histological grade (four signals), and lymph node metastasis (three signals). CONCLUSIONS: The high number of m/z signals that were found to be significantly linked to one or more phenotypic features of oesophageal cancer highlights the power of MALDI-MSI in the analysis of high-density TMAs. The data also emphasise substantial biological differences between adenocarcinomas and squamous cell carcinomas.

MALDI mass spectrometric imaging based identification of clinically relevant signals in prostate cancer using large-scale tissue microarrays.

To identify molecular features associated with clinico-pathological parameters and TMPRSS2-ERG fusion status in prostate cancer, we employed MALDI mass spectrometric imaging (MSI) to a prostate cancer tissue microarray (TMA) containing formalin-fixed, paraffin-embedded tissues samples from 1,044 patients for which clinical follow-up data were available. MSI analysis revealed 15 distinct mass per charge (m/z)-signals associated to epithelial structures. A comparison of these signals with clinico-pathological features revealed statistical association with favorable tumor phenotype such as low Gleason grade, early pT stage or low Ki67 labeling Index (LI) for four signals (m/z 700, m/z 1,502, m/z 1,199 and m/z 3,577), a link between high Ki67LI for one signal (m/z 1,013) and a relationship with prolonged time to PSA recurrence for one signal (m/z 1,502; p = 0.0145). Multiple signals were associated with the ERG-fusion status of our cancers. Two of 15 epithelium-associated signals including m/z 1,013 and m/z 1,502 were associated with detectable ERG expression and five signals (m/z 644, 678, 1,044, 3,086 and 3,577) were associated with ERG negativity. These observations are in line with substantial molecular differences between fusion-type and non-fusion type prostate cancer. The signals observed in this study may characterize molecules that play a role in the development of TMPRSS2-ERG fusions, or alternatively reflect pathways that are activated as a consequence of ERG-activation. The combination of MSI and large-scale TMAs reflects a powerful approach enabling immediate prioritization of MSI signals based on associations with clinico-pathological and molecular data.