Competing magnetic orders in a bilayer Hubbard model with ultracold atoms.

Fermionic atoms in optical lattices have served as a useful model system in which to study and emulate the physics of strongly correlated matter. Driven by the advances of high-resolution microscopy, the current research focus is on two-dimensional systems1-3, in which several quantum phases-such as antiferromagnetic Mott insulators for repulsive interactions4-7 and charge-density waves for attractive interactions8-have been observed. However, the lattice structure of real materials, such as bilayer graphene, is composed of coupled layers and is therefore not strictly two-dimensional, which must be taken into account in simulations. Here we realize a bilayer Fermi-Hubbard model using ultracold atoms in an optical lattice, and demonstrate that the interlayer coupling controls a crossover between a planar antiferromagnetically ordered Mott insulator and a band insulator of spin-singlets along the bonds between the layers. We probe the competition of the magnetic ordering by measuring spin-spin correlations both within and between the two-dimensional layers. Our work will enable the exploration of further properties of coupled-layer Hubbard models, such as theoretically predicted superconducting pairing mechanisms9,10.

Panomics reveals patient individuality as the major driver of colorectal cancer progression.

BACKGROUND: Colorectal cancer (CRC) is one of the most prevalent cancers, with over one million new cases per year. Overall, prognosis of CRC largely depends on the disease stage and metastatic status. As precision oncology for patients with CRC continues to improve, this study aimed to integrate genomic, transcriptomic, and proteomic analyses to identify significant differences in expression during CRC progression using a unique set of paired patient samples while considering tumour heterogeneity. METHODS: We analysed fresh-frozen tissue samples prepared under strict cryogenic conditions of matched healthy colon mucosa, colorectal carcinoma, and liver metastasis from the same patients. Somatic mutations of known cancer-related genes were analysed using Illumina's TruSeq Amplicon Cancer Panel; the transcriptome was assessed comprehensively using Clariom D microarrays. The global proteome was evaluated by liquid chromatography-coupled mass spectrometry (LC‒MS/MS) and validated by two-dimensional difference in-gel electrophoresis. Subsequent unsupervised principal component clustering, statistical comparisons, and gene set enrichment analyses were calculated based on differential expression results. RESULTS: Although panomics revealed low RNA and protein expression of CA1, CLCA1, MATN2, AHCYL2, and FCGBP in malignant tissues compared to healthy colon mucosa, no differentially expressed RNA or protein targets were detected between tumour and metastatic tissues. Subsequent intra-patient comparisons revealed highly specific expression differences (e.g., SRSF3, OLFM4, and CEACAM5) associated with patient-specific transcriptomes and proteomes. CONCLUSION: Our research results highlight the importance of inter- and intra-tumour heterogeneity as well as individual, patient-paired evaluations for clinical studies. In addition to changes among groups reflecting CRC progression, we identified significant expression differences between normal colon mucosa, primary tumour, and liver metastasis samples from individuals, which might accelerate implementation of precision oncology in the future.

Contribution of Interneuron Subtype-Specific GABAergic Signaling to Emergent Sensory Processing in Mouse Somatosensory Whisker Barrel Cortex.

Mammalian neocortex is important for conscious processing of sensory information with balanced glutamatergic and GABAergic signaling fundamental to this function. Yet little is known about how this interaction arises despite increasing insight into early GABAergic interneuron (IN) circuits. To study this, we assessed the contribution of specific INs to the development of sensory processing in the mouse whisker barrel cortex, specifically the role of INs in early speed coding and sensory adaptation. In wild-type animals, both speed processing and adaptation were present as early as the layer 4 critical period of plasticity and showed refinement over the period leading to active whisking onset. To test the contribution of IN subtypes, we conditionally silenced action-potential-dependent GABA release in either somatostatin (SST) or vasoactive intestinal peptide (VIP) INs. These genetic manipulations influenced both spontaneous and sensory-evoked cortical activity in an age- and layer-dependent manner. Silencing SST + INs reduced early spontaneous activity and abolished facilitation in sensory adaptation observed in control pups. In contrast, VIP + IN silencing had an effect towards the onset of active whisking. Silencing either IN subtype had no effect on speed coding. Our results show that these IN subtypes contribute to early sensory processing over the first few postnatal weeks.

Protein Expression of AEBP1, MCM4, and FABP4 Differentiate Osteogenic, Adipogenic, and Mesenchymal Stromal Stem Cells.

Mesenchymal stem cells (MSCs) gain an increasing focus in the field of regenerative medicine due to their differentiation abilities into chondrocytes, adipocytes, and osteoblastic cells. However, it is apparent that the transformation processes are extremely complex and cause cellular heterogeneity. The study aimed to characterize differences between MSCs and cells after adipogenic (AD) or osteoblastic (OB) differentiation at the proteome level. Comparative proteomic profiling was performed using tandem mass spectrometry in data-independent acquisition mode. Proteins were quantified by deep neural networks in library-free mode and correlated to the Molecular Signature Database (MSigDB) hallmark gene set collections for functional annotation. We analyzed 4108 proteins across all samples, which revealed a distinct clustering between MSCs and cell differentiation states. Protein expression profiling identified activation of the Peroxisome proliferator-activated receptors (PPARs) signaling pathway after AD. In addition, two distinct protein marker panels could be defined for osteoblastic and adipocytic cell lineages. Hereby, overexpression of AEBP1 and MCM4 for OB as well as of FABP4 for AD was detected as the most promising molecular markers. Combination of deep neural network and machine-learning algorithms with data-independent mass spectrometry distinguish MSCs and cell lineages after adipogenic or osteoblastic differentiation. We identified specific proteins as the molecular basis for bone formation, which could be used for regenerative medicine in the future.

Optogenetic activation of parvalbumin and somatostatin interneurons selectively restores theta-nested gamma oscillations and oscillation-induced spike timing-dependent long-term potentiation impaired by amyloid ß oligomers.

BACKGROUND: Abnormal accumulation of amyloid ß1-42 oligomers (AßO1-42), a hallmark of Alzheimer's disease, impairs hippocampal theta-nested gamma oscillations and long-term potentiation (LTP) that are believed to underlie learning and memory. Parvalbumin-positive (PV) and somatostatin-positive (SST) interneurons are critically involved in theta-nested gamma oscillogenesis and LTP induction. However, how AßO1-42 affects PV and SST interneuron circuits is unclear. Through optogenetic manipulation of PV and SST interneurons and computational modeling of the hippocampal neural circuits, we dissected the contributions of PV and SST interneuron circuit dysfunctions on AßO1-42-induced impairments of hippocampal theta-nested gamma oscillations and oscillation-induced LTP. RESULTS: Targeted whole-cell patch-clamp recordings and optogenetic manipulations of PV and SST interneurons during in vivo-like, optogenetically induced theta-nested gamma oscillations in vitro revealed that AßO1-42 causes synapse-specific dysfunction in PV and SST interneurons. AßO1-42 selectively disrupted CA1 pyramidal cells (PC)-to-PV interneuron and PV-to-PC synapses to impair theta-nested gamma oscillogenesis. In contrast, while having no effect on PC-to-SST or SST-to-PC synapses, AßO1-42 selectively disrupted SST interneuron-mediated disinhibition to CA1 PC to impair theta-nested gamma oscillation-induced spike timing-dependent LTP (tLTP). Such AßO1-42-induced impairments of gamma oscillogenesis and oscillation-induced tLTP were fully restored by optogenetic activation of PV and SST interneurons, respectively, further supporting synapse-specific dysfunctions in PV and SST interneurons. Finally, computational modeling of hippocampal neural circuits including CA1 PC, PV, and SST interneurons confirmed the experimental observations and further revealed distinct functional roles of PV and SST interneurons in theta-nested gamma oscillations and tLTP induction. CONCLUSIONS: Our results reveal that AßO1-42 causes synapse-specific dysfunctions in PV and SST interneurons and that optogenetic modulations of these interneurons present potential therapeutic targets for restoring hippocampal network oscillations and synaptic plasticity impairments in Alzheimer's disease.

CalibraCurve: A Tool for Calibration of Targeted MS-Based Measurements.

Targeted proteomics techniques allow accurate quantitative measurements of analytes in complex matrices with dynamic linear ranges that span up to 4-5 orders of magnitude. Hence, targeted methods are promising for the development of robust protein assays in several sensitive areas, for example, in health care. However, exploiting the full method potential requires reliable determination of the dynamic range along with related quantification limits for each analyte. Here, a software named CalibraCurve that enables an automated batch-mode determination of dynamic linear ranges and quantification limits for both targeted proteomics and similar assays is presented. The software uses a variety of measures to assess the accuracy of the calibration, namely precision and trueness. Two different kinds of customizable graphs are created (calibration curves and response factor plots). The accuracy measures and the graphs offer an intuitive, detailed, and reliable opportunity to assess the quality of the model fit. Thus, CalibraCurve is deemed a highly useful and flexible tool to facilitate the development and control of reliable SRM/MRM-MS-based proteomics assays.

Attractive and repulsive Fermi polarons in two dimensions.

The dynamics of a single impurity in an environment is a fundamental problem in many-body physics. In the solid state, a well known case is an impurity coupled to a bosonic bath (such as lattice vibrations); the impurity and its accompanying lattice distortion form a new entity, a polaron. This quasiparticle plays an important role in the spectral function of high-transition-temperature superconductors, as well as in colossal magnetoresistance in manganites. For impurities in a fermionic bath, studies have considered heavy or immobile impurities which exhibit Anderson's orthogonality catastrophe and the Kondo effect. More recently, mobile impurities have moved into the focus of research, and they have been found to form new quasiparticles known as Fermi polarons. The Fermi polaron problem constitutes the extreme, but conceptually simple, limit of two important quantum many-body problems: the crossover between a molecular Bose-Einstein condensate and a superfluid with BCS (Bardeen-Cooper-Schrieffer) pairing with spin-imbalance for attractive interactions, and Stoner's itinerant ferromagnetism for repulsive interactions. It has been proposed that such quantum phases (and other elusive exotic states) might become realizable in Fermi gases confined to two dimensions. Their stability and observability are intimately related to the theoretically debated properties of the Fermi polaron in a two-dimensional Fermi gas. Here we create and investigate Fermi polarons in a two-dimensional, spin-imbalanced Fermi gas, measuring their spectral function using momentum-resolved photoemission spectroscopy. For attractive interactions, we find evidence for a disputed pairing transition between polarons and tightly bound dimers, which provides insight into the elementary pairing mechanism of imbalanced, strongly coupled two-dimensional Fermi gases. Additionally, for repulsive interactions, we study novel quasiparticles--repulsive polarons--the lifetime of which determines the possibility of stabilizing repulsively interacting Fermi systems.

Observation of a pairing pseudogap in a two-dimensional Fermi gas.

Pairing of fermions is ubiquitous in nature, underlying many phenomena. Examples include superconductivity, superfluidity of (3)He, the anomalous rotation of neutron stars, and the crossover between Bose-Einstein condensation of dimers and the BCS (Bardeen, Cooper and Schrieffer) regime in strongly interacting Fermi gases. When confined to two dimensions, interacting many-body systems show even more subtle effects, many of which are not understood at a fundamental level. Most striking is the (as yet unexplained) phenomenon of high-temperature superconductivity in copper oxides, which is intimately related to the two-dimensional geometry of the crystal structure. In particular, it is not understood how the many-body pairing is established at high temperature, and whether it precedes superconductivity. Here we report the observation of a many-body pairing gap above the superfluid transition temperature in a harmonically trapped, two-dimensional atomic Fermi gas in the regime of strong coupling. Our measurements of the spectral function of the gas are performed using momentum-resolved photoemission spectroscopy, analogous to angle-resolved photoemission spectroscopy in the solid state. Our observations mark a significant step in the emulation of layered two-dimensional strongly correlated superconductors using ultracold atomic gases.

Left-right dissociation of hippocampal memory processes in mice.

Left-right asymmetries have likely evolved to make optimal use of bilaterian nervous systems; however, little is known about the synaptic and circuit mechanisms that support divergence of function between equivalent structures in each hemisphere. Here we examined whether lateralized hippocampal memory processing is present in mice, where hemispheric asymmetry at the CA3-CA1 pyramidal neuron synapse has recently been demonstrated, with different spine morphology, glutamate receptor content, and synaptic plasticity, depending on whether afferents originate in the left or right CA3. To address this question, we used optogenetics to acutely silence CA3 pyramidal neurons in either the left or right dorsal hippocampus while mice performed hippocampus-dependent memory tasks. We found that unilateral silencing of either the left or right CA3 was sufficient to impair short-term memory. However, a striking asymmetry emerged in long-term memory, wherein only left CA3 silencing impaired performance on an associative spatial long-term memory task, whereas right CA3 silencing had no effect. To explore whether synaptic properties intrinsic to the hippocampus might contribute to this left-right behavioral asymmetry, we investigated the expression of hippocampal long-term potentiation. Following the induction of long-term potentiation by high-frequency electrical stimulation, synapses between CA3 and CA1 pyramidal neurons were strengthened only when presynaptic input originated in the left CA3, confirming an asymmetry in synaptic properties. The dissociation of hippocampal long-term memory function between hemispheres suggests that memory is routed via distinct left-right pathways within the mouse hippocampus, and provides a promising approach to help elucidate the synaptic basis of long-term memory.

Quantitative Tissue Proteomics Analysis Reveals Versican as Potential Biomarker for Early-Stage Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is one of the most aggressive tumors, and the treatment outcome of this disease is improved when the cancer is diagnosed at an early stage. This requires biomarkers allowing an accurate and early tumor diagnosis. To identify potential markers for such applications, we analyzed a patient cohort consisting of 50 patients (50 HCC and 50 adjacent nontumorous tissue samples as controls) using two independent proteomics approaches. We performed label-free discovery analysis on 19 HCC and corresponding tissue samples. The data were analyzed considering events known to take place in early events of HCC development, such as abnormal regulation of Wnt/b-catenin and activation of receptor tyrosine kinases (RTKs). 31 proteins were selected for verification experiments. For this analysis, the second set of the patient cohort (31 HCC and corresponding tissue samples) was analyzed using selected (multiple) reaction monitoring (SRM/MRM). We present the overexpression of ATP-dependent RNA helicase (DDX39), Fibulin-5 (FBLN5), myristoylated alanine-rich C-kinase substrate (MARCKS), and Serpin H1 (SERPINH1) in HCC for the first time. We demonstrate Versican core protein (VCAN) to be significantly associated with well differentiated and low-stage HCC. We revealed for the first time the evidence of VCAN as a potential biomarker for early-HCC diagnosis.

Boolean modeling techniques for protein co-expression networks in systems medicine.

INTRODUCTION: Application of systems biology/systems medicine approaches is promising for proteomics/biomedical research, but requires selection of an adequate modeling type. AREAS COVERED: This article reviews the existing Boolean network modeling approaches, which provide in comparison with alternative modeling techniques several advantages for the processing of proteomics data. Application of methods for inference, reduction and validation of protein co-expression networks that are derived from quantitative high-throughput proteomics measurements is presented. It's also shown how Boolean models can be used to derive system-theoretic characteristics that describe both the dynamical behavior of such networks as a whole and the properties of different cell states (e.g. healthy or diseased cell states). Furthermore, application of methods derived from control theory is proposed in order to simulate the effects of therapeutic interventions on such networks, which is a promising approach for the computer-assisted discovery of biomarkers and drug targets. Finally, the clinical application of Boolean modeling analyses is discussed. Expert commentary: Boolean modeling of proteomics data is still in its infancy. Progress in this field strongly depends on provision of a repository with public access to relevant reference models. Also required are community supported standards that facilitate input of both proteomics and patient related data (e.g. age, gender, laboratory results, etc.).

Equation of State of the Two-Dimensional Hubbard Model.

The subtle interplay between kinetic energy, interactions, and dimensionality challenges our comprehension of strongly correlated physics observed, for example, in the solid state. In this quest, the Hubbard model has emerged as a conceptually simple, yet rich model describing such physics. Here we present an experimental determination of the equation of state of the repulsive two-dimensional Hubbard model over a broad range of interactions 0≲U/t≲20 and temperatures, down to k_{B}T/t=0.63(2) using high-resolution imaging of ultracold fermionic atoms in optical lattices. We show density profiles, compressibilities, and double occupancies over the whole doping range, and, hence, our results constitute benchmarks for state-of-the-art theoretical approaches.

X-chromosomal 21-indel marker panel in German and Baltic populations.

In order to verify specific biallelic X-indels and their characteristic properties in distinct populations, one German and three Baltic population groups (Estonia, Latvia, and Lithuania) have been analyzed by a short amplicon method, which also enables detection of degraded DNA samples. To combine 21 indels in a single multiplex PCR, all products were arranged according to their expected amplicon length (~40-160 bp) on the basis of three different fluorochromes. Separation of PCR products was carried out in a single capillary electrophoresis. Data evaluating was performed including five further indel markers which have already been tested in identical samples, resulting in altogether 26 markers. The majority of the genetic material showed combinations of insertion elements (L-fragments). Combinations of deletion elements (S-fragments) in contrast occurred with significant lower ratios. Hardy-Weinberg equilibrium (HWE) was observed for all markers except for MID1361 and MID329. This was attributed to an insufficient number of samples. For two known linkage groups within the 26-indel set (MID357-MID356 and MID3690-MID3719-MID2089), haplotype data were determined. A pairwise comparison of German and Baltic allele frequencies did not show significant deviation. This result indicates a possible genetic association between all four population groups. The calculated biostatistical parameters show high forensic efficiency for this set of indel markers. In a segregation analysis investigating 194 meiosis, no mutations have been detected regarding expected transmission patterns.

A trapped single ion inside a Bose-Einstein condensate.

Improved control of the motional and internal quantum states of ultracold neutral atoms and ions has opened intriguing possibilities for quantum simulation and quantum computation. Many-body effects have been explored with hundreds of thousands of quantum-degenerate neutral atoms, and coherent light-matter interfaces have been built. Systems of single or a few trapped ions have been used to demonstrate universal quantum computing algorithms and to search for variations of fundamental constants in precision atomic clocks. Until now, atomic quantum gases and single trapped ions have been treated separately in experiments. Here we investigate whether they can be advantageously combined into one hybrid system, by exploring the immersion of a single trapped ion into a Bose-Einstein condensate of neutral atoms. We demonstrate independent control over the two components of the hybrid system, study the fundamental interaction processes and observe sympathetic cooling of the single ion by the condensate. Our experiment calls for further research into the possibility of using this technique for the continuous cooling of quantum computers. We also anticipate that it will lead to explorations of entanglement in hybrid quantum systems and to fundamental studies of the decoherence of a single, locally controlled impurity particle coupled to a quantum environment.

Identification of novel biomarker candidates for the immunohistochemical diagnosis of cholangiocellular carcinoma.

The aim of this study was the identification of novel biomarker candidates for the diagnosis of cholangiocellular carcinoma (CCC) and its immunohistochemical differentiation from benign liver and bile duct cells. CCC is a primary cancer that arises from the epithelial cells of bile ducts and is characterized by high mortality rates due to its late clinical presentation and limited treatment options. Tumorous tissue and adjacent non-tumorous liver tissue from eight CCC patients were analyzed by means of two-dimensional differential in-gel electrophoresis and mass-spectrometry-based label-free proteomics. After data analysis and statistical evaluation of the proteins found to be differentially regulated between the two experimental groups (fold change ≥ 1.5; p value ≤ 0.05), 14 candidate proteins were chosen for determination of the cell-type-specific expression profile via immunohistochemistry in a cohort of 14 patients. This confirmed the significant up-regulation of serpin H1, 14-3-3 protein sigma, and stress-induced phosphoprotein 1 in tumorous cholangiocytes relative to normal hepatocytes and non-tumorous cholangiocytes, whereas some proteins were detectable specifically in hepatocytes. Because stress-induced phosphoprotein 1 exhibited both sensitivity and specificity of 100%, an immunohistochemical verification examining tissue sections of 60 CCC patients was performed. This resulted in a specificity of 98% and a sensitivity of 64%. We therefore conclude that this protein should be considered as a potential diagnostic biomarker for CCC in an immunohistochemical application, possibly in combination with other candidates from this study in the form of a biomarker panel. This could improve the differential diagnosis of CCC and benign bile duct diseases, as well as metastatic malignancies in the liver.

Analysis of disease-associated protein expression using quantitative proteomics­fibulin-5 is expressed in association with hepatic fibrosis.

Hepatic fibrosis and cirrhosis are major health problems worldwide. Until now, highly invasive biopsy remains the diagnostic gold standard despite many disadvantages. To develop noninvasive diagnostic assays for the assessment of liver fibrosis, it is urgently necessary to identify molecules that are robustly expressed in association with the disease. We analyzed biopsied tissue samples from 95 patients with HBV/HCV-associated hepatic fibrosis using three different quantification methods. We performed a label-free proteomics discovery study to identify novel disease-associated proteins using a subset of the cohort (n = 27). Subsequently, gene expression data from all available clinical samples were analyzed (n = 77). Finally, we performed a targeted proteomics approach, multiple reaction monitoring (MRM), to verify the disease-associated expression in samples independent from the discovery approach (n = 68). We identified fibulin-5 (FBLN5) as a novel protein expressed in relation to hepatic fibrosis. Furthermore, we confirmed the altered expression of microfibril-associated glycoprotein 4 (MFAP4), lumican (LUM), and collagen alpha-1(XIV) chain (COL14A1) in association to hepatic fibrosis. To our knowledge, no tissue-based quantitative proteomics study for hepatic fibrosis has been performed using a cohort of comparable size. By this means, we add substantial evidence for the disease-related expression of the proteins examined in this study.

The amino acid's backup bone - storage solutions for proteomics facilities.

Proteomics methods, especially high-throughput mass spectrometry analysis have been continually developed and improved over the years. The analysis of complex biological samples produces large volumes of raw data. Data storage and recovery management pose substantial challenges to biomedical or proteomic facilities regarding backup and archiving concepts as well as hardware requirements. In this article we describe differences between the terms backup and archive with regard to manual and automatic approaches. We also introduce different storage concepts and technologies from transportable media to professional solutions such as redundant array of independent disks (RAID) systems, network attached storages (NAS) and storage area network (SAN). Moreover, we present a software solution, which we developed for the purpose of long-term preservation of large mass spectrometry raw data files on an object storage device (OSD) archiving system. Finally, advantages, disadvantages, and experiences from routine operations of the presented concepts and technologies are evaluated and discussed. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

A practical data processing workflow for multi-OMICS projects.

Multi-OMICS approaches aim on the integration of quantitative data obtained for different biological molecules in order to understand their interrelation and the functioning of larger systems. This paper deals with several data integration and data processing issues that frequently occur within this context. To this end, the data processing workflow within the PROFILE project is presented, a multi-OMICS project that aims on identification of novel biomarkers and the development of new therapeutic targets for seven important liver diseases. Furthermore, a software called CrossPlatformCommander is sketched, which facilitates several steps of the proposed workflow in a semi-automatic manner. Application of the software is presented for the detection of novel biomarkers, their ranking and annotation with existing knowledge using the example of corresponding Transcriptomics and Proteomics data sets obtained from patients suffering from hepatocellular carcinoma. Additionally, a linear regression analysis of Transcriptomics vs. Proteomics data is presented and its performance assessed. It was shown, that for capturing profound relations between Transcriptomics and Proteomics data, a simple linear regression analysis is not sufficient and implementation and evaluation of alternative statistical approaches are needed. Additionally, the integration of multivariate variable selection and classification approaches is intended for further development of the software. Although this paper focuses only on the combination of data obtained from quantitative Proteomics and Transcriptomics experiments, several approaches and data integration steps are also applicable for other OMICS technologies. Keeping specific restrictions in mind the suggested workflow (or at least parts of it) may be used as a template for similar projects that make use of different high throughput techniques. This article is part of a Special Issue entitled: Computational Proteomics in the Post-Identification Era. Guest Editors: Martin Eisenacher and Christian Stephan.

Proteomic differences between hepatocellular carcinoma and nontumorous liver tissue investigated by a combined gel-based and label-free quantitative proteomics study.

Proteomics-based clinical studies have been shown to be promising strategies for the discovery of novel biomarkers of a particular disease. Here, we present a study of hepatocellular carcinoma (HCC) that combines complementary two-dimensional difference in gel electrophoresis (2D-DIGE) and liquid chromatography (LC-MS)-based approaches of quantitative proteomics. In our proteomic experiments, we analyzed a set of 14 samples (7 × HCC versus 7 × nontumorous liver tissue) with both techniques. Thereby we identified 573 proteins that were differentially expressed between the experimental groups. Among these, only 51 differentially expressed proteins were identified irrespective of the applied approach. Using Western blotting and immunohistochemical analysis the regulation patterns of six selected proteins from the study overlap (inorganic pyrophosphatase 1 (PPA1), tumor necrosis factor type 1 receptor-associated protein 1 (TRAP1), betaine-homocysteine S-methyltransferase 1 (BHMT)) were successfully verified within the same sample set. In addition, the up-regulations of selected proteins from the complements of both approaches (major vault protein (MVP), gelsolin (GSN), chloride intracellular channel protein 1 (CLIC1)) were also reproducible. Within a second independent verification set (n = 33) the altered protein expression levels of major vault protein and betaine-homocysteine S-methyltransferase were further confirmed by Western blots quantitatively analyzed via densitometry. For the other candidates slight but nonsignificant trends were detectable in this independent cohort. Based on these results we assume that major vault protein and betaine-homocysteine S-methyltransferase have the potential to act as diagnostic HCC biomarker candidates that are worth to be followed in further validation studies.