Magnetic Silica-Coated Fluorescent Microspheres (MagSiGlow) for Simultaneous Detection of Tumor-Associated Proteins.

Multiplexed bead assays for solution-phase biosensing often encounter cross-over reactions during signal amplification steps, leading to unwanted false positive and high background signals. Current solutions involve complex custom-designed and costly equipment, limiting their application in simple laboratory setup. In this study, we introduce a straightforward protocol to adapt a multiplexed single-bead assay to standard fluorescence imaging plates, enabling the simultaneous analysis of thousands of reactions per plate. This approach focuses on the design and synthesis of bright fluorescent and magnetic microspheres (MagSiGlow) with multiple fluorescent wavelengths serving as unique detection markers. The imaging-based, single-bead assay, combined with a scripted algorithm, allows the detection, segmentation, and co-localization on average of 7500 microspheres per field of view across five imaging channels in less than one second. We demonstrate the effectiveness of this method with remarkable sensitivity at low protein detection limits (100 pg/mL). This technique showed over 85 % reduction in signal cross-over to the solution-based method after the concurrent detection of tumor-associated protein biomarkers. This approach holds the promise of substantially enhancing high throughput biosensing for multiple targets, seamlessly integrating with rapid image analysis algorithms.

CLINICOPATHOLOGICAL AND IMMUNO-HISTOCHEMICAL CHARACTERIZATION OF GASTROINTESTINAL STROMAL TUMOUR AT FOUR TERTIARY HEALTH CENTERS IN NIGERIA USING CD117, DOG1, AND HER-2 BIOMARKERS.

Introduction: Gastrointestinal stromal tumours (GISTs) are neoplastic lesions that primarily affect the digestive tract and develop from interstitial cells of Cajal. Due to their malignant potential and personalized treatment, these lesions require histopathologic and immunohistochemical characterization. In this investigation, the sex, age, lesional sites of origin, histopathologic types, the prevalence of HER-2 expression, prognostic indices (based on tumour size and mitotic figures), expression of CD117 and DOG1, and characteristics of patients with GIST were all characterized. Methodology: This is a retrospective cross-sectional analysis of GIST cases seen at four tertiary healthcare centers in Nigeria over ten years (2008 to 2017) and investigated utilizing histopathological and immunohistochemical (CD117, DOG1, and HER-2) methods. Result: In this study, there were twenty GIST cases. Notably, the majority (40%) of the cases had tumours with sizes between 7.0 and 8.0, the stomach was the most frequent site (70%) and the spindle cell type of GIST was the most prevalent (80%) histopathological type. Additionally, the stomach was significantly associated with GIST as an origin site (with a P value of 0.001), and 100% and 50% of these tumours were immunoreactive with CD117 and DOG1 respectively. Finally, HER-2 immunoreactivity was negatively stained with GIST tumour. Conclusion: In our study, GISTs most frequently develop in the stomach, and CD117& DOG1 are essential for correctly diagnosing these tumours. However, HER-2 immunoreactivity is a predictive marker of survival for personalized care.

The clinicopathological and prognostic significances of IGF-1R and Livin expression in patients with colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is the third most common cancer worldwide. However, limited effective biomarkers are associated with the tumorigenesis and prognosis of CRC. METHODS: The present study identified potential signatures from The Cancer Genome Atlas (TCGA) database and further validated the identified biomarkers in CRC tissues by immunohistochemistry (IHC). RESULTS: The expression of insulin-like growth factor 1 receptor (IGF-1R) and Livin gene was significantly upregulated in CRC samples compared to the adjacent normal samples in the TCGA dataset. IHC indicated that IGF-1R and Livin protein levels are increased in CRC and adenoma tissues compared to normal tissues. Notably, the IGF-1R protein levels differed significantly between adenoma and CRC. The elevated IGF-1R and Livin expression was associated with CRC clinicopathological features, including age, gender, histological subtype, individual cancer stages, nodal metastasis, and TP53-mutant in TCGA. Additionally, the IGF-1R promoter methylation level was closely related to CRC. Consistent with the TCGA study, IHC indicated that overexpressed IGF-1R and Livin proteins were independent risk factors for stage and metastasis. A marked correlation was established between IGF-1R and Livin expression in CRC, while the survival map showed no significant correlation with CRC. Kaplan-Meier survival curves showed that CRC patients with high IGF-1R or Livin expression had a prolonged overall disease-free survival than those with low expression in TCGA. CONCLUSION: IGF-1R and Livin are associated with CRC tumorigenesis and might be valuable for novel biomarker identification and targeted therapeutic strategy development.

TMEM16A overexpression indicates poor prognosis in colorectal cancer patients.

AIM: to investigate the relationship between TMEM16A and the clinicopathological features and prognosis of patients with colorectal cancer (CRC). METHODS: ninety-six patients with CRC confirmed by pathology after undergoing surgery at the First Affiliated Hospital of Dalian Medical University between June 2009 and December 2011 were enrolled and followed up. The expression of the TMEM16A protein in CRC was detected by immunohistochemistry in 96 cases. The relationship between the expression of the TMEM16A protein in CRC and the clinical features and clinical prognosis were analyzed. RESULTS: there was no correlation between the TMEM16A protein expression and gender, age, tumor location, size and degree of differentiation (p > 0.05). However, the expression of the TMEM16A protein was significantly associated with the depth of invasion, lymph node metastasis and Dukes stage (p < 0.05). Kaplan-Meier survival curves showed that CRC patients with high expression of the TMEM16A protein had a poorer overall survival compared with those with low expression levels (68.2 % vs 92.3 %, X2 = 9.892, p = 0.002). Multivariate Cox regression analysis showed that upregulation of the TMEM16A protein expression is an independent predictive factor for poor prognosis in patients with CRC (p < 0.05, RR = 6.467, 95 % CI: 1.777-23.538). CONCLUSIONS: the expression of the TMEM16A protein in CRC was associated with tumor invasion, lymph node metastasis and Dukes stage. High expression of the TMEM16A protein in CRC can be used as an independent predictive factor for a poor prognosis of patients with CRC.

RPL34-AS1-induced RPL34 inhibits cervical cancer cell tumorigenesis via the MDM2-P53 pathway.

Ribosomal proteins (RPs) are important components of ribosomes and related to the occurrence and development of tumors. However, little is known about the effects of the RP network on cervical cancer (CC). In this study, we screened differentially expressed RPL34 in CC by high-throughput quantitative proteome assay. We found that RPL34 acted as a tumor suppressor and was downregulated in CC and inhibited the proliferation, migration, and invasion abilities of CC cells. Next, we verified that RPL34 regulated the CC through the MDM2-P53 pathway by using Act D medicine, MDM2 inhibitor, and a series of western blotting（WB）assays. Moreover, an antisense lncRNA, RPL34-AS1, regulated the expression of RPL34 and participated in the tumorigenesis of CC. RPL34 can reverse the effect of RPL34-AS1 in CC cells. Finally, by RNA-binding protein immunoprecipitation (RIP) assay we found that eukaryotic initiation factor 4A3 (EIF4A3), which binds to RPL34-AS1, regulated RPL34-AS1 expression in CC. Therefore, our findings indicate that RPL34-AS1-induced RPL34 inhibits CC cell proliferation, invasion, and metastasis through modulation of the MDM2-P53 signaling pathway, which provides a meaningful target for the early diagnosis and treatment of CC.

Examination of FERMT1 expression in placental chorionic villi and its role in HTR8-SVneo cell invasion.

Transmembrane integrin receptors mediate cell-extracellular matrix as well as cell-cell adhesion. As placental trophoblast cells undergo differentiation they display changes in integrin expression or switching, but the mechanism(s) of integrin activation that supports this differentiation is still unknown. The Fermitin family of adapter proteins (FERMT 1-3) are integrin activators that mediate integrin-mediated signaling. In this study, we examined the spatiotemporal pattern of expression of FERMT1 in human chorionic villi throughout gestation and its role in HTR8-SVneo substrate adhesion and invasion. Placental villous tissue was obtained from patients undergoing elective terminations at weeks 8-14, as well as from term deliveries at weeks 37-40 and analyzed by immunofluorescence. Additionally, HTR8-SVneo trophoblast cells were transfected with FERMT1-specific siRNA or non-targeting siRNA (control) and used in cell-substrate adhesion as well as invasion assays. FERMT1 was primarily localized to membrane-associated regions at the base or around the periphery of the villous cytotrophoblast and proximal as well as distal cell column trophoblast. FERMT1 was also localized to endothelial cells of blood vessels in chorionic villi. siRNA-mediated depletion of FERMT1 in HTR8-SVneo cells did not markedly alter HTR8-SVneo cell-substrate adhesion but did significantly decrease invasion (P < 0.05) compared to control cells. These novel findings identify the presence of the integrin activator FERMT1 in trophoblast cells and that FERMT1 can regulate HTR8-SVneo cell invasion. FERMT1 may directly influence integrin activation and the subsequent integrin-mediated signaling and differentiation that underlies the acquisition of the invasive trophoblast phenotype in vivo.

Five long non-coding RNAs establish a prognostic nomogram and construct a competing endogenous RNA network in the progression of non-small cell lung cancer.

BACKGROUND: Accumulating evidence has revealed that long non-coding RNAs (lncRNAs) play vital roles in the progression of non-small cell lung cancer (NSCLC). But the relationship between lncRNAs and survival outcome of NSCLC remains to be explored. Therefore, we attempt to figure out their survival roles and molecular connection in NSCLC. METHODS: By analyzing the transcriptome profiling of NSCLC from TCGA databases, we divided patients into three groups, and identified differentially expressed lncRNAs (DELs) of each group. Next, we explored the prognostic roles of common DELs by univariate and multivariate Cox analysis, Lasson, and Kaplan-Meier analysis. Additionally, we assessed and compared the prognostic accuracy of 5 lncRNAs through ROC curves and AUC values. Ultimately, we detected their potential function by enrichment analysis and molecular connection through establishing a competing endogenous RNA (ceRNA) network. RESULTS: One hundred ninety-seven common DELs were spotted. And we successfully screened out 5 lncRNAs related to the patient's survival, including LINC01833, AC112206.2, FAM83A-AS1, BANCR, and HOTAIR. Combing with age and AJCC stage, we constructed a nomogram that prognostic prediction was superior to the traditional parameters. Furthermore, 275 qualified mRNAs related to 5 lncRNAs were spotted. Functional analysis indicates that these lncRNAs act key roles in the progression of NSCLC, such as P53 and cell cycle signaling pathway. And ceRNA network also suggests that these lncRNAs are tightly connected with tumor progression. CONCLUSIONS: A nomogram and ceRNA network based on 5 lncRNAs indicate that there can effectively predict the overall survival of NSCLC and potentially serve as a therapeutic guide for NSCLC.

Abundance of P-glycoprotein and Breast Cancer Resistance Protein Measured by Targeted Proteomics in Human Epileptogenic Brain Tissue.

Our goal was to measure the absolute differential abundance of key drug transporters in human epileptogenic brain tissue and to compare them between patients and at various distances from the epileptogenic zone within the same patient. Transporter protein abundance was quantified in brain tissue homogenates from patients who underwent epilepsy surgery, using targeted proteomics, and correlations with clinical and tissue characteristics were assessed. Fourteen brain samples (including four epileptogenic hippocampal samples) were collected from nine patients. Among the quantifiable drug transporters, the abundance (median, range) ranked: breast cancer resistance protein (ABCG2/BCRP; 0.55, 0.01-3.26 pmol/g tissue) > P-glycoprotein (ABCB1/MDR1; 0.30, 0.02-1.15 pmol/g tissue) > equilibrative nucleoside transporter 1 (SLC29A1/ENT1; 0.06, 0.001-0.35 pmol/g tissue). The ABCB1/ABCG2 ratio (mean 0.27, range 0.08-0.47) was comparable with literature values from nonepileptogenic brain tissue (mean 0.5-0.8). Transporter abundance was lower in the hippocampi than in the less epileptogenic neocortex of the same patients. ABCG2/BCRP and ABCB1/MDR1 expression strongly correlated with that of glucose transporter 1 (SLC2A1/GLUT1) (r = 0.97, p < 0.001; r = 0.90, p < 0.01, respectively). Low transporter abundance was found in patients with overt vascular pathology, whereas the highest abundance was seen in a sample with normally appearing blood vessels. In conclusion, drug transporter abundance highly varies across patients and between epileptogenic and less epileptogenic brain tissue of the same patient. The strong correlation in abundance of ABCB1/MDR1, ABCG2/BCRP, and SLC2A1/GLUT1 suggests variation in the content of the functional vasculature within the tissue samples. The epileptogenic tissue can be depleted of key drug transport mechanisms, warranting consideration when selecting treatments for patients with drug-resistant epilepsy.

Angiopoietin-2 outperforms other endothelial biomarkers associated with severe acute kidney injury in patients with severe sepsis and respiratory failure.

BACKGROUND: Endothelial dysfunction and injury is a major pathophysiologic feature of sepsis. Sepsis is also the most frequent cause of acute kidney injury (AKI) in critically ill patients. Though most studies of AKI in sepsis have focused on tubular epithelial injury, the role of endothelial dysfunction and injury is less well studied. The goal of this study was first to investigate whether endothelial dysfunction and injury biomarkers were associated with severe AKI in sepsis patients. The second goal was to determine the best performing biomarker for severe AKI and whether this biomarker was associated with severe AKI across different etiologies of sepsis and clinical outcomes. METHODS: We studied adults with severe sepsis and acute respiratory failure (ARF) enrolled in the prospective observational Validating Acute Lung Injury markers for Diagnosis (VALID) study. Plasma endothelial dysfunction and injury biomarkers, including angiopoietin-2, soluble vascular endothelial cadherin (sVE-cadherin), endocan and syndecan-1, were measured at study enrollment. Primary analysis focused on the association between endothelial biomarker levels with severe AKI (defined as Kidney Disease: Improving Global Outcomes [KDIGO] AKI stage 2 or 3), other organ dysfunctions (defined by Brussels organ failure scores), and comparison of pulmonary versus non-pulmonary sepsis. RESULTS: Among 228 sepsis patients enrolled, 141 developed severe AKI. Plasma levels of angiopoietin-2, endocan, sVE-cadherin, and syndecan-1 were significantly higher in sepsis patients with severe AKI compared to those without severe AKI. Among four endothelial biomarkers, only angiopoietin-2 was independently associated with severe AKI (odds ratio 6.07 per log increase, 95% CI 2.34-15.78, p < 0.001). Plasma angiopoietin-2 levels by quartile were significantly higher in sepsis patients with hepatic, coagulation, and circulatory failure. Plasma angiopoietin-2 levels were also significantly higher in patients with non-pulmonary sepsis compared to subjects with pulmonary sepsis. CONCLUSION: Among four biomarkers of endothelial dysfunction and injury, angiopoietin-2 had the most robust independent association with development of severe AKI in patients with severe sepsis and ARF. Plasma angiopoietin-2 levels were also associated with other organ dysfunctions, non-pulmonary sepsis, and death. These findings highlight the importance of early endothelial dysfunction and injury in the pathogenesis of sepsis-induced AKI.

Precise characterization of KRAS4b proteoforms in human colorectal cells and tumors reveals mutation/modification cross-talk.

Mutations of the KRAS gene are found in human cancers with high frequency and result in the constitutive activation of its protein products. This leads to aberrant regulation of downstream pathways, promoting cell survival, proliferation, and tumorigenesis that drive cancer progression and negatively affect treatment outcomes. Here, we describe a workflow that can detect and quantify mutation-specific consequences of KRAS biochemistry, namely linked changes in posttranslational modifications (PTMs). We combined immunoaffinity enrichment with detection by top-down mass spectrometry to discover and quantify proteoforms with or without the Gly13Asp mutation (G13D) specifically in the KRAS4b isoform. The workflow was applied first to isogenic KRAS colorectal cancer (CRC) cell lines and then to patient CRC tumors with matching KRAS genotypes. In two cellular models, a direct link between the knockout of the mutant G13D allele and the complete nitrosylation of cysteine 118 of the remaining WT KRAS4b was observed. Analysis of tumor samples quantified the percentage of mutant KRAS4b actually present in cancer tissue and identified major differences in the levels of C-terminal carboxymethylation, a modification critical for membrane association. These data from CRC cells and human tumors suggest mechanisms of posttranslational regulation that are highly context-dependent and which lead to preferential production of specific KRAS4b proteoforms.

Interfacial interactions of SERS-active noble metal nanostructures with functional ligands for diagnostic analysis of protein cancer markers.

Noble metal nanostructures with designed hot spots have been widely investigated as surface-enhanced Raman spectroscopy (SERS)-active substrates, particularly for selective and sensitive detection of protein cancer markers. For specific target recognition and efficient signal amplification, SERS probe design requires a choice of SERS-active nanostructures as well as their controlled functionalization with Raman dyes and target recognition entities such as antibodies. However, the chemical conjugation of antibodies and Raman dyes to SERS substrates has rarely been discussed to date, despite their substantial roles in detection schemes. The interfacial interactions of metal nanostructures with functional ligands during conjugation are known to be strongly influenced by the various chemical and physical properties of the ligands, such as size, molecular weight, surface charge, 3-dimensional structures, and hydrophilicity/hydrophobicity. In this review, we discuss recent developments in the design of SERS probes over the last 4 years, focusing on their conjugation chemistry for functionalization. A strong preference for covalent bonding is observed with Raman dyes having simpler molecular structures, whereas more complicated ones are non-covalently adsorbed. Antibodies are both covalently and non-covalently bonded to nanostructures, depending on their activity in the SERS probes. Considering that ligand conjugation is highly important for chemical stability, biocompatibility, and functionality of SERS probes, this review is expected to expand the understanding of their interfacial design, leading to SERS as one of the most promising spectroscopic analytical tools for the early detection of protein cancer markers.

Recent Discoveries of Macromolecule- and Cell-Based Biomarkers and Therapeutic Implications in Breast Cancer.

Breast cancer is the most commonly diagnosed cancer type and the leading cause of cancer-related mortality in women worldwide. Breast cancer is fairly heterogeneous and reveals six molecular subtypes: luminal A, luminal B, HER2+, basal-like subtype (ER-, PR-, and HER2-), normal breast-like, and claudin-low. Breast cancer screening and early diagnosis play critical roles in improving therapeutic outcomes and prognosis. Mammography is currently the main commercially available detection method for breast cancer; however, it has numerous limitations. Therefore, reliable noninvasive diagnostic and prognostic biomarkers are required. Biomarkers used in cancer range from macromolecules, such as DNA, RNA, and proteins, to whole cells. Biomarkers for cancer risk, diagnosis, proliferation, metastasis, drug resistance, and prognosis have been identified in breast cancer. In addition, there is currently a greater demand for personalized or precise treatments; moreover, the identification of novel biomarkers to further the development of new drugs is urgently needed. In this review, we summarize and focus on the recent discoveries of promising macromolecules and cell-based biomarkers for the diagnosis and prognosis of breast cancer and provide implications for therapeutic strategies.

Analysis of m6A RNA Methylation-Related Genes in Liver Hepatocellular Carcinoma and Their Correlation with Survival.

N6-methyladenosine (m6A) modification on RNA plays an important role in tumorigenesis and metastasis, which could change gene expression and even function at multiple levels such as RNA splicing, stability, translocation, and translation. In this study, we aim to conduct a comprehensive analysis on m6A RNA methylation-related genes, including m6A RNA methylation regulators and m6A RNA methylation-modified genes, in liver hepatocellular carcinoma, and their relationship with survival and clinical features. Data, which consist of the expression of widely reported m6A RNA methylation-related genes in liver hepatocellular carcinoma from The Cancer Genome Atlas (TCGA), were analyzed by one-way ANOVA, Univariate Cox regression, a protein-protein interaction network, gene enrichment analysis, feature screening, a risk prognostic model, correlation analysis, and consensus clustering analysis. In total, 405 of the m6A RNA methylation-related genes were found based on one-way ANOVA. Among them, DNA topoisomerase 2-alpha (TOP2A), exodeoxyribonuclease 1 (EXO1), ser-ine/threonine-protein kinase Nek2 (NEK2), baculoviral IAP repeat-containing protein 5 (BIRC5), hyaluronan mediated motility receptor (HMMR), structural maintenance of chromosomes protein 4 (SMC4), bloom syndrome protein (BLM), ca-sein kinase I isoform epsilon (CSNK1E), cytoskeleton-associated protein 5 (CKAP5), and inner centromere protein (INCENP), which were m6A RNA methylation-modified genes, were recognized as the hub genes based on the protein-protein interaction analysis. The risk prognostic model showed that gender, AJCC stage, grade, T, and N were significantly different between the subgroup with the high and low risk groups. The AUC, the evaluation parameter of the prediction model which was built by RandomForest, was 0.7. Furthermore, two subgroups were divided by consensus clustering analysis, in which stage, grade, and T differed. We identified the important genes expressed significantly among two clusters, including uridine-cytidine kinase 2 (UCK2), filensin (BFSP1), tubulin-specific chaperone D (TBCD), histone-lysine N-methyltransferase PRDM16 (PRDM16), phosphorylase b ki-nase regulatory subunit alpha (PHKA2), serine/threonine-protein kinase BRSK2 (BRSK2), Arf-GAP with coiled-coil (ACAP3), general transcription factor 3C polypep-tide 2 (GTF3C2), and guanine nucleotide exchange factor MSS4 (RABIF). In our study, the m6A RNA methylation-related genes in liver hepatocellular carcinoma were analyzed systematically, including the expression, interaction, function, and prognostic values, which provided an important theoretical basis for m6A RNA methylation in liver cancer. The nine important m6A-related genes could be prognostic markers in the survival time of patients.

Demethoxycurcumin Suppresses Human Brain Glioblastoma Multiforme GBM 8401 Cell Xenograft Tumor in Nude Mice In Vivo.

Demethoxycurcumin (DMC), a derivate of curcumin, has been shown to induce apoptotic cell death in human glioblastoma multiforme GBM 8401 cells via cell cycle arrest and induction of cell apoptosis. However, there is no report showing DMC suppresses glioblastoma multiforme cells in vivo. In the present study, we investigated the effects of DMC on GBM8401 cells in vivo. At first, we established a luciferase-expressing stable clone named GBM 8401/luc2. Second, mice were inoculated subcutaneously with GBM 8401/luc2 cells to generate a xenograft tumor mice model. After inoculation, tumor volume reached 100-120 mm3, and all mice were randomly divided into three groups: Group I was treated with 110 µL phosphate-buffered solution (PBS) containing 0.1% dimethyl sulfoxide, Group II with 30 mg/kg of DMC, and Group III with 60 mg/kg of DMC. Mice from each group were given the oral treatment of DMC by gavage for 21 days. The body weight and tumor volume were recorded every 3 days. DMC significantly decreased the tumor volumes, and 60 mg/kg treatment showed a higher decrease in tumor volumes than that of 30 mg/kg, However, DMC did not affect the body weights. The photons emitted from mice tumors were detected with Xenogen IVIS imaging system, DMC at both doses decreased the total photon flux and 60 mg/kg treatment of DMC has low total photon flux than that of 30 mg/kg. The tumor volumes and weights in 60 mg/kg treatment of DMC were lower than that of 30 mg/kg. Immunohistochemical analysis was used to measure protein expression of tumors and results showed that DMC treatment led to lightly staining with anti-Bcl-2 and -XIAP and 60 mg/kg treatment of DMC has lighter staining with anti-Bcl-2 and -XIAP than that of 30 mg/kg. The higher dose (60 mg/kg) of DMC has higher signals of cleaved-caspase-3 than that of the lower dose (30 mg/kg). Furthermore, the hematoxylin and eosin (H&E) staining of liver tissues showed no significant difference between DMC-treated and control-groups. Overall, these observations showed that DMC suppressed tumor properties in vivo and DMC may be used against human glioblastoma multiforme in the future.

Clinical Perspective on Proteomic and Glycomic Biomarkers for Diagnosis, Prognosis, and Prediction of Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) is known as a highly aggressive malignant disease. Prognosis for patients is notoriously poor, despite improvements in surgical techniques and new (neo)adjuvant chemotherapy regimens. Early detection of PDAC may increase the overall survival. It is furthermore foreseen that precision medicine will provide improved prognostic stratification and prediction of therapeutic response. In this review, omics-based discovery efforts are presented that aim for novel diagnostic and prognostic biomarkers of PDAC. For this purpose, we systematically evaluated the literature published between 1999 and 2020 with a focus on protein- and protein-glycosylation biomarkers in pancreatic cancer patients. Besides genomic and transcriptomic approaches, mass spectrometry (MS)-based proteomics and glycomics of blood- and tissue-derived samples from PDAC patients have yielded new candidates with biomarker potential. However, for reasons discussed in this review, the validation and clinical translation of these candidate markers has not been successful. Consequently, there has been a change of mindset from initial efforts to identify new unimarkers into the current hypothesis that a combination of biomarkers better suits a diagnostic or prognostic panel. With continuing development of current research methods and available techniques combined with careful study designs, new biomarkers could contribute to improved detection, prognosis, and prediction of pancreatic cancer.

Liquid Biopsies in the Clinical Management of Germ Cell Tumor Patients: State-of-the-Art and Future Directions.

Liquid biopsies constitute a minimally invasive means of managing cancer patients, entailing early diagnosis, follow-up and prediction of response to therapy. Their use in the germ cell tumor field is invaluable since diagnostic tissue biopsies (which are invasive) are often not performed, and therefore only a presumptive diagnosis can be made, confirmed upon examination of the surgical specimen. Herein, we provide an overall review of the current liquid biopsy-based biomarkers of this disease, including the classical, routinely used serum tumor markers-the promising microRNAs rapidly approaching the introduction into clinical practice-but also cell-free DNA markers (including DNA methylation) and circulating tumor cells. Finally, and importantly, we also explore novel strategies and challenges for liquid biopsy markers and methodologies, providing a critical view of the future directions for liquid biopsy tests in this field, highlighting gaps and unanswered questions.

Usefulness of immunohistochemistry to distinguish between secretory carcinoma and acinic cell carcinoma in the salivary gland.

Secretory carcinoma (SC) of the salivary gland is a relatively newly described disease, separate from acinic cell carcinoma (ACC), which frequently displays ETV6-NTRK3 gene fusion. However, the differences between SC and ACC remain unclear. Here, histological reevaluation of 12 formerly diagnosed ACC cases was performed, which yielded a new diagnosis of SC in four cases due to a lack of obvious acinar-like cells. Immunohistochemically, phosphorylated signal transducer and activator of transcription 5 (p-STAT5) was expressed in SC but not in ACC, whereas discovered on GIST-1 (DOG1) was expressed in ACC but not in SC. Molecular analysis was possible in three SC cases, of which two showed the ETV6-NTRK3 fusion transcript on reverse-transcription polymerase chain reaction, as well as breaks in the ETV6 gene on fluorescence in situ hybridization. However, the remaining SC cases did not show this fusion transcript. Recently, several reports have suggested that SC might not be adequately diagnosed if the focus is placed solely on the ETV6-NTRK3 fusion gene due to genetic diversity. In this regard, immunohistochemistry of p-STAT5 and DOG1 is expected to be a useful alternative diagnostic tool to discriminate SC from ACC.

Increased Single-Spectrum Top-Down Protein Sequence Coverage in Trapping Mass Spectrometers with Chimeric Ion Loading.

Fourier transform mass spectrometers routinely provide high mass resolution, mass measurement accuracy, and mass spectral dynamic range. In this work, we utilize 21 T Fourier transform ion cyclotron resonance (FT-ICR) to analyze product ions derived from the application of multiple dissociation techniques and/or multiple precursor ions within a single transient acquisition. This ion loading technique, which we call, "chimeric ion loading", saves valuable acquisition time, decreases sample consumption, and improves top-down protein sequence coverage. In the analysis of MCF7 cell lysate, we show collision-induced dissociation (CID) and electron-transfer dissociation (ETD) on each precursor on a liquid chromatography-mass spectrometry (LC-MS) timescale and improve mean sequence coverage dramatically (CID-only 15% vs chimeric 33%), even during discovery-based acquisition. This approach can also be utilized to multiplex the acquisition of product ion spectra of multiple charge states from a single protein precursor or multiple ETD/proton-transfer reactions (PTR) reaction periods. The analytical utility of chimeric ion loading is demonstrated for top-down proteomics, but it is also likely to be impactful for tandem mass spectrometry applications in other areas.

MS1-Level Proteome Quantification Platform Allowing Maximally Increased Multiplexity for SILAC and In Vitro Chemical Labeling.

Quantitative proteomic platforms based on precursor intensity in mass spectrometry (MS1-level) uniquely support in vivo metabolic labeling with superior quantification accuracy but suffer from limited multiplexity (≤3-plex) and frequent missing quantities. Here we present a new MS1-level quantification platform that allows maximal multiplexing with high quantification accuracy and precision for the given labeling scheme. The platform currently comprises 6-plex in vivo SILAC or in vitro diethylation labeling with a dedicated algorithm and is also expandable to higher multiplexity (e.g., nine-plex for SILAC). For complex samples with broad dynamic ranges such as total cell lysates, our platform performs highly accurately and free of missing quantities. Furthermore, we successfully applied our method to measure protein synthesis rate under heat shock response in human cells by 6-plex pulsed SILAC experiments, demonstrating the unique biological merits of our in vivo platform to disclose translational regulations for cellular response to stress.

DirectMS1: MS/MS-Free Identification of 1000 Proteins of Cellular Proteomes in 5 Minutes.

Proteome characterization relies heavily on tandem mass spectrometry (MS/MS) and is thus associated with instrumentation complexity, lengthy analysis time, and limited duty cycle. It was always tempting to implement approaches that do not require MS/MS, yet they were constantly failing to achieve a meaningful depth of quantitative proteome coverage within short experimental times, which is particularly important for clinical or biomarker-discovery applications. Here, we report on the first successful attempt to develop a truly MS/MS-free method, DirectMS1, for bottom-up proteomics. The method is compared with the standard MS/MS-based data-dependent acquisition approach for proteome-wide analysis using 5 min LC gradients. Specifically, we demonstrate identification of 1 000 protein groups for a standard HeLa cell line digest. The amount of loaded sample was varied in a range from 1 to 500 ng, and the method demonstrated 10-fold higher sensitivity. Combined with the recently introduced Diffacto approach for relative protein quantification, DirectMS1 outperforms most popular MS/MS-based label-free quantitation approaches because of significantly higher protein sequence coverage.