Identification of GlcNAcylated alpha-1-antichymotrypsin as an early biomarker in human non-small-cell lung cancer by quantitative proteomic analysis with two lectins

A novel selenium nanocomposite modified by AANL inhibits tumor growth by upregulating CLK2 in lung cancer

Lung cancer is a malignant tumor with high mortality and drug resistance. Therefore, it is urgent to explore natural and nontoxic drugs to treat lung cancer. In this study, the natural active ingredient AANL extracted from Agrocybe aegirita was used to modify nanoselenium by an oxidation-reduction method. Transmission electron microscope detection and infrared spectroscopy showed that a novel selenium nanocomposite named AANL-SeNPs was successfully prepared. The results of nanoscale characterization showed that AANL-SeNPs had good stability and uniform dispersion in aqueous solution by zeta potential and spectrum analysis. At the cellular level, we found that AANL-SeNPs significantly inhibited the cell viability of lung cancer cells, and the cell inhibition rate of 60 nM AANL-SeNPs was 39 % in H157 cells, 67 % in H147 cells, and 62 % in A549 cells. The IC50 value of AANL-SeNPs was 51.85 nM in A549 cells and 81.57 nM in H157 cells. Moreover, AANL-SeNPs could inhibit the cell proliferation and migration, and enhance the sensitivity of lung cancer cells to osimertinib and has no toxic to normal cells. In vivo, AANL-SeNPs significantly slowed tumor growth in tumor-bearing mice by establishing a subcutaneous transplantation tumor model for lung cancer, and the tumor size was smaller and was reduced about 79 % in 2 mg/kg AANL-SeNPs group compared with PBS group. Mechanistically, a total of 38 differentially expressed proteins were identified by data-independent acquisition mass spectrometry. A significantly upregulated protein, CDC-like kinase 2 (CLK2), was screened and validated for further analysis, which showed that the expression levels of CLK2 were increased in H157 and H1437 cells after AANL-SeNPs treatment. The results obtained in this study suggest that a novel selenium nanocomposite AANL-SeNPs, which inhibits lung cancer by upregulating the expression of CLK2.

Protein glycosylation in lung cancer from a mass spectrometry perspective

Lung cancer is a severe disease for which better diagnostic and therapeutic approaches are urgently needed. Increasing evidence implies that aberrant protein glycosylation plays a crucial role in the pathogenesis and progression of lung cancer. Differences in glycosylation patterns have been previously observed between healthy and cancerous samples as well as between different lung cancer subtypes, which suggests untapped diagnostic potential. In addition, understanding the changes mediated by glycosylation may shed light on possible novel therapeutic targets and personalized treatment strategies for lung cancer patients. Mass spectrometry based glycomics and glycoproteomics have emerged as powerful tools for in-depth characterization of changes in protein glycosylation, providing valuable insights into the molecular basis of lung cancer. This paper reviews the literature on the analysis of protein glycosylation in lung cancer using mass spectrometry, which is dominated by manuscripts published over the past 5 years. Studies analyzing N-glycosylation, O-glycosylation, and glycosaminoglycan patterns in tissue, serum, plasma, and rare biological samples of lung cancer patients are highlighted. The current knowledge on the potential utility of glycan and glycoprotein biomarkers is also discussed.

Robust Glycoproteomics Platform Reveals a Tetra-Antennary Site-Specific Glycan Capping with Sialyl-Lewis Antigen for Early Detection of Gastric Cancer

The lack of efficient biomarkers for the early detection of gastric cancer (GC) contributes to its high mortality rate, so it is crucial to discover novel diagnostic targets for GC. Recent studies have implicated the potential of site-specific glycans in cancer diagnosis, yet it is challenging to perform highly reproducible and sensitive glycoproteomics analysis on large cohorts of samples. Here, a highly robust N-glycoproteomics (HRN) platform comprising an automated enrichment method, a stable microflow LC-MS/MS system, and a sensitive glycopeptide-spectra-deciphering tool is developed for large-scale quantitative N-glycoproteome analysis. The HRN platform is applied to analyze serum N-glycoproteomes of 278 subjects from three cohorts to investigate glycosylation changes of GC. It identifies over 20 000 unique site-specific glycans from discovery and validation cohorts, and determines four site-specific glycans as biomarker candidates. One candidate has branched tetra-antennary structure capping with sialyl-Lewis antigen, and it significantly outperforms serum CEA with AUC values > 0.89 compared against < 0.67 for diagnosing early-stage GC. The four-marker panel can provide improved diagnostic performances. Besides, discrimination powers of four candidates are also testified with a verification cohort using PRM strategy. This findings highlight the value of this strong tool in analyzing aberrant site-specific glycans for cancer detection.

Conducting polymer composite-based biosensing materials for the diagnosis of lung cancer: A review

The development of a simple and fast cancer detection method is crucial since early diagnosis is a key factor in increasing survival rates for lung cancer patients. Among several diagnosis methods, the electrochemical sensor is the most promising one due to its outstanding performance, portability, real-time analysis, robustness, amenability, and cost-effectiveness. Conducting polymer (CP) composites have been frequently used to fabricate a robust sensor device, owing to their excellent physical and electrochemical properties as well as biocompatibility with nontoxic effects on the biological system. This review brings up a brief overview of the importance of electrochemical biosensors for the early detection of lung cancer, with a detailed discussion on the design and development of CP composite materials for biosensor applications. The review covers the electrochemical sensing of numerous lung cancer markers employing composite electrodes based on the conducting polyterthiophene, poly(3,4-ethylenedioxythiophene), polyaniline, polypyrrole, molecularly imprinted polymers, and others. In addition, a hybrid of the electrochemical biosensors and other techniques was highlighted. The outlook was also briefly discussed for the development of CP composite-based electrochemical biosensors for POC diagnostic devices.

A diagnostic biomarker of acid glycoprotein 1 for distinguishing malignant from benign pulmonary lesions

BACKGROUND

The acid glycoprotein 1 (AGP1) is downregulated in lung cancer. However, the performance of AGP1 in distinguishing benign from malignant lung lesions is still unknown.

METHODS

The expression of AGP1 in benign diseases and lung cancer samples was detected by Western blot. The receiver operating characteristic curves, bivariate correlation, and multivariate analysis was analyzed by SPSS software.

RESULTS

AGP1 expression levels were significantly downregulated in lung cancer and correlated with carcinoembryonic antigen (CEA), CA199, and CA724 tumor biomarkers. The diagnostic performance of AGP1 for distinguishing malignant from benign pulmonary lesions was better than the other four clinical biomarkers including CEA, squamous cell carcinoma-associated antigen, neuron-specific enolase, and cytokeratin 19 fragment 21-1, with an area under the curve value of 0.713 at 88.8% sensitivity. Furthermore, the multivariate analysis indicated that the variates of thrombin time and potassium significantly affected the AGP1 levels in lung cancer.

CONCLUSIONS

Our study indicates that AGP1 expression is decreased in lung cancer compared to benign samples, which helps distinguish benign and malignant pulmonary lesions.

Overexpression of SERPINA3 suppresses tumor progression by modulating SPOP/NF‑κB in lung cancer

The pathogenesis mechanism of lung cancer is very complex, with high incidence and mortality. Serpin family A member 3 (SERPINA3) expression levels were reduced in the sera of patients with lung cancer and may be a candidate diagnostic and prognostic survival biomarker in lung cancer, as previously reported. However, the detailed biological functions of SERPINA3 in the pathogenesis of lung cancer remain unknown. In the present study, it was aimed to explore the effects of SERPINA3 on the occurrence of lung cancer. SERPINA3 expression was assessed using bioinformatics database analysis and experimental detection. Then, the biological effects of SERPINA3 were investigated in a cell culture system and a xenograft model of human lung cancer. The potential regulatory mechanism of SERPINA3 in lung cancer was explored by data‑independent acquisition mass spectrometry (DIA‑MS) detection and further validated by western blotting (WB). The results indicated that SERPINA3 expression levels were significantly downregulated in lung cancer tissues and cell lines. At the cellular level, it was revealed that overexpressed SERPINA3 inhibited cell growth, proliferation, migration and invasion and promoted the apoptosis of lung cancer cells. Moreover, overexpressed SERPINA3 enhanced the sensitivity of lung cancer cells to osimertinib. In vivo, a xenograft model of human lung cancer was established with BALB/c nude mice. After the injection of A549 cells, the tumor growth of the tumor‑bearing mice in the SERPINA3‑overexpressing group increased more slowly, and the tumor volume was smaller than that in the empty‑vector group. Mechanistically, a total of 65 differentially expressed proteins were identified. It was found that the speckle‑type POZ protein (SPOP) was significantly upregulated in SERPINA3‑overexpressing H157 cells using DIA‑MS detection and analysis. WB validation showed that SPOP expression increased, and NF‑kappaB (NF‑κB) p65 was inhibited in cell lines and tumor tissues of mice when SERPINA3 was overexpressed. The present findings suggest that SERPINA3 is involved in the development of lung cancer and has an antineoplastic role in lung cancer.

SERPINA3: Stimulator or Inhibitor of Pathological Changes

SERPINA3, also called α-1-antichymotrypsin (AACT, ACT), is one of the inhibitors of serine proteases, one of which is cathepsin G. As an acute-phase protein secreted into the plasma by liver cells, it plays an important role in the anti-inflammatory response and antiviral response. Elevated levels of SERPINA3 have been observed in heart failure and neurological diseases such as Alzheimer's disease or Creutzfeldt-Jakob disease. Many studies have shown increased expression levels of the SERPINA3 gene in various types of cancer, such as glioblastoma, colorectal cancer, endometrial cancer, breast cancer, or melanoma. In this case, the SERPINA3 protein is associated with an antiapoptotic function implemented by adjusting the PI3K/AKT or MAPK/ERK 1/2 signal pathways. However, the functions of the SERPINA3 protein are still only partially understood, mainly in the context of cancerogenesis, so it seems necessary to summarize the available information and describe its mechanism of action. In particular, we sought to amass the existing body of research focusing on the description of the underlying mechanisms of various diseases not related to cancer. Our goal was to present an overview of the correct function of SERPINA3 as part of the defense system, which unfortunately easily becomes the "Fifth Column" and begins to support processes of destruction.

The Role of Genomics and Proteomics in Lung Cancer Early Detection and Treatment

Lung cancer is the leading cause of cancer-related death worldwide, with non-small-cell lung cancer (NSCLC) being the primary type. Unfortunately, it is often diagnosed at advanced stages, when therapy leaves patients with a dismal prognosis. Despite the advances in genomics and proteomics in the past decade, leading to progress in developing tools for early diagnosis, targeted therapies have shown promising results; however, the 5-year survival of NSCLC patients is only about 15%. Low-dose computed tomography or chest X-ray are the main types of screening tools. Lung cancer patients without specific, actionable mutations are currently treated with conventional therapies, such as platinum-based chemotherapy; however, resistances and relapses often occur in these patients. More noninvasive, inexpensive, and safer diagnostic methods based on novel biomarkers for NSCLC are of paramount importance. In the current review, we summarize genomic and proteomic biomarkers utilized for the early detection and treatment of NSCLC. We further discuss future opportunities to improve biomarkers for early detection and the effective treatment of NSCLC.

Construction of 2DE Patterns of Plasma Proteins: Aspect of Potential Tumor Markers

The use of tumor markers aids in the early detection of cancer recurrence and prognosis. There is a hope that they might also be useful in screening tests for the early detection of cancer. Here, the question of finding ideal tumor markers, which should be sensitive, specific, and reliable, is an acute issue. Human plasma is one of the most popular samples as it is commonly collected in the clinic and provides noninvasive, rapid analysis for any type of disease including cancer. Many efforts have been applied in searching for “ideal” tumor markers, digging very deep into plasma proteomes. The situation in this area can be improved in two ways—by attempting to find an ideal single tumor marker or by generating panels of different markers. In both cases, proteomics certainly plays a major role. There is a line of evidence that the most abundant, so-called “classical plasma proteins”, may be used to generate a tumor biomarker profile. To be comprehensive these profiles should have information not only about protein levels but also proteoform distribution for each protein. Initially, the profile of these proteins in norm should be generated. In our work, we collected bibliographic information about the connection of cancers with levels of “classical plasma proteins”. Additionally, we presented the proteoform profiles (2DE patterns) of these proteins in norm generated by two-dimensional electrophoresis with mass spectrometry and immunodetection. As a next step, similar profiles representing protein perturbations in plasma produced in the case of different cancers will be generated. Additionally, based on this information, different test systems can be developed.

Biomarkers in Otorhinolaryngology

Biomarkers of otorhinolaryngologic diseases with higher insult over a person’s him/herself and overall health services are summarized in brief. In order to define, diagnose, treat and monitor any disease markers are needed. Otorhinolaryngology (ORL) is interested in special disease entities of the region besides otorhinolaryngologic involvements of the systemic diseases and unique forms of pathologies such as cholesteatoma, Meniere’s disease and otosclerosis. Neoplasia is another heading to deal with. In the following chapter, one will find an overview of molecules that have been used as a biomarker as well as the end points of the present research on the issue relevant with ORL. Day by day, new molecules are being named however, the pathways of action are rather the same. Readers will find the headings related to the most common diseases of the field, informing them about where to look for defining new strategies of understanding of each disease.

Alpha-1-antichymotrypsin as a novel biomarker for diagnosis, prognosis, and therapy prediction in human diseases

The glycoprotein alpha-1-antichymotrypsin (AACT), a serine protease inhibitor, is mainly synthesized in the liver and then secreted into the blood and is involved in the acute phase response, inflammation, and proteolysis. The dysregulation of AACT and its glycosylation levels are associated with tumor progression and recurrence, and could be used as a biomarker for tumor monitoring. In this review, we summarized the expression level, glycosylation modification, and biological characteristics of AACT during inflammation, neurodegenerative or other elderly diseases, and tumorigenesis, as well as, focused on the biological roles of AACT in cancer. The aberrant expression of AACT in cancer might be due to genetic alterations and/or immune by bioinformatics analysis. Moreover, AACT may serve as a diagnostic or prognostic biomarker or therapeutic target in tumors. Furthermore, we found that the expression of AACT was associated with the overall survival of patients with human cancers. Decreased AACT expression was associated with poor survival in patients with liver cancer, increased AACT expression was associated with shorter survival in patients with pancreatic cancer, and decreased AACT expression was associated with shorter survival in patients with early lung cancer. The review confirmed the key roles of AACT in tumorigenesis, suggesting that the glycoprotein AACT may serve as a biomarker for tumor diagnosis and prognosis, and could be a potential therapeutic target for human diseases.

Identification of novel combined biomarkers in the diagnosis of multiple myeloma

PURPOSE

Multiple myeloma (MM) is a haematological malignant disease with a clonal proliferation of plasma cells, and timely surveillance is helpful to improve the survival rate of patients with MM. However, there is a lack of simple and effective biomarkers for the diagnosis, prognosis, and residual disease evaluation of MM.

MATERIAL & METHODS

In the detection cohort, we used the samples from six newly diagnosed MM patients and six control subjects. Plasma proteins were labelled with dimethyl reagents and enriched by lectin AANL6, then the deglycosylated peptides were identified by LC-MS/MS. Differentially expressed proteins were used for further exploration. In the validation cohort, we used 90 newly diagnosed patients with MM and 70 cases of unrelated diseases as controls. The diagnosis performance was analysed by ROC analysis using SPSS.

RESULTS

In this study, we show, using lectin blots with AANL6, that glycosylation levels were higher in MM patients than in controls. After AANL6 enrichment, we detected 58 differentially expressed proteins using quantitative proteomics. We further validated one candidate Fibulin-1 (FBLN1). Using an Elisa assay, we showed that FBLN1 expression was increased in plasma of 90 cases of MM, and which was significantly correlated with DKK1 expression. ROC analysis showed that these two markers had a 95.7% specificity for determining the diagnosis of MM.

CONCLUSION

These data suggest that the MM cases display increased glycosylation after AANL6 enrichment and that the combined expression of FBLN1 and DKK1 can be used as an effective diagnostic biomarker.

The Utility of Differential Scanning Calorimetry Curves of Blood Plasma for Diagnosis, Subtype Differentiation and Predicted Survival in Lung Cancer

Early detection of lung cancer (LC) significantly increases the likelihood of successful treatment and improves LC survival rates. Currently, screening (mainly low-dose CT scans) is recommended for individuals at high risk. However, the recent increase in the number of LC cases unrelated to the well-known risk factors, and the high false-positive rate of low-dose CT, indicate a need to develop new, non-invasive methods for LC detection. Therefore, we evaluated the use of differential scanning calorimetry (DSC) for LC patients' diagnosis and predicted survival. Additionally, by applying mass spectrometry, we investigated whether changes in O- and N-glycosylation of plasma proteins could be an underlying mechanism responsible for observed differences in DSC curves of LC and control subjects. Our results indicate selected DSC curve features could be useful for differentiation of LC patients from controls with some capable of distinction between subtypes and stages of LC. DSC curve features also correlate with LC patients' overall/progression free survival. Moreover, the development of classification models combining patients' DSC curves with selected plasma protein glycosylation levels that changed in the presence of LC could improve the sensitivity and specificity of the detection of LC. With further optimization and development of the classification method, DSC could provide an accurate, non-invasive, radiation-free strategy for LC screening and diagnosis.

Anionic Polysaccharide-Modified Filter Papers for Rapid Isolation of Extracellular Vesicles from Diverse Samples in a Simple Bind-Wash-Elute Manner

Extracellular vesicles (EVs) play a significant role in the pathophysiological process of many diseases, highlighting their values in medical diagnosis and disease monitoring. However, the current EV isolation methods are time-consuming, inconvenient to operate, and incompatible with downstream analyses. Here, we present a novel isolation method employing anionic polysaccharide-modified filter papers for the isolation of EVs (AppiEV) via electrostatic adsorption. A disc of glass fiber-based filter modified with sodium alginate was assembled into a spin column to function as the solid capture phase. In the acidic condition, EVs were induced to carry more positively charged ions, which enable the capture of EVs by the negatively charged filter paper. After a wash, the EVs were released from the spin column using an alkaline elution buffer, which induces the EVs to carry more negative charges. The EVs isolated by AppiEV from cell culture supernatants, plasma, and urine are similar to or even better than those isolated by ultracentrifugation in terms of EV size distribution, protein distribution, and nucleic acid contents. Due to the interference removal of the EV-free RNA and DNA attributed to the negatively charged capture medium, the eluate of AppiEV could be directly used for genetic analysis, including the stem-loop RT-PCR analysis of miR-21 and the allele-specific PCR analysis of mutation genes of EGFR p.L858R and EGFR p.T790M. We believe that AppiEV offers a simple and efficient approach for the isolation of high-quality EVs from various liquid specimens.

Multi-scale supervised clustering-based feature selection for tumor classification and identification of biomarkers and targets on genomic data

Background

The small number of samples and the curse of dimensionality hamper the better application of deep learning techniques for disease classification. Additionally, the performance of clustering-based feature selection algorithms is still far from being satisfactory due to their limitation in using unsupervised learning methods. To enhance interpretability and overcome this problem, we developed a novel feature selection algorithm. In the meantime, complex genomic data brought great challenges for the identification of biomarkers and therapeutic targets. The current some feature selection methods have the problem of low sensitivity and specificity in this field.

Results

In this article, we designed a multi-scale clustering-based feature selection algorithm named MCBFS which simultaneously performs feature selection and model learning for genomic data analysis. The experimental results demonstrated that MCBFS is robust and effective by comparing it with seven benchmark and six state-of-the-art supervised methods on eight data sets. The visualization results and the statistical test showed that MCBFS can capture the informative genes and improve the interpretability and visualization of tumor gene expression and single-cell sequencing data. Additionally, we developed a general framework named McbfsNW using gene expression data and protein interaction data to identify robust biomarkers and therapeutic targets for diagnosis and therapy of diseases. The framework incorporates the MCBFS algorithm, network recognition ensemble algorithm and feature selection wrapper. McbfsNW has been applied to the lung adenocarcinoma (LUAD) data sets. The preliminary results demonstrated that higher prediction results can be attained by identified biomarkers on the independent LUAD data set, and we also structured a drug-target network which may be good for LUAD therapy.

Conclusions

The proposed novel feature selection method is robust and effective for gene selection, classification, and visualization. The framework McbfsNW is practical and helpful for the identification of biomarkers and targets on genomic data. It is believed that the same methods and principles are extensible and applicable to other different kinds of data sets.

Early diagnosis and screening in lung cancer

Lung cancer is the third most diagnosed cancer, but the first cause of cancer-related deaths worldwide. This rather high death rate is due mainly to the fact that most patients are diagnosed with advanced-stage cancer, for which the conventional treatment does not work. The most used screening method for lung cancer is a low-dose CT scan, but it is recommended for specific age populations and it also started different debates on its advantages for lung cancer diagnosis. Over the year, several new techniques have been developed that are less invasive, have lower side effect, and can be implemented at all types of populations. This article aimed to present the advantages and disadvantages of using several methods for lung cancer diagnosis, including analysis of volatile organic compounds, exhaled breath condensate analysis and specific genomic approaches.

Clinical Application of Mass Spectrometry-Based Proteomics in Lung Cancer Early Diagnosis

The current knowledge on proteomic biomarker analysis for the early diagnosis of lung cancer is summarized, underlining the diversity among the results and the current interest in translating research results into clinical practice. A MEDLINE/PubMed literature search to retrieve all the papers published in the last 10 years is performed. Proteomics studies on lung cancer have gathered evidence on the potential role of biomarkers in early diagnosis. Although promising, none of them have proved to be sufficiently reliable to achieve validation. Future research should evolve toward a multipanel analysis of proteins, considering the possibility that individual biomarkers might not be specific enough to diagnose lung cancer, but could be related to oncological conditions.

Proteomic Analysis of Cerebrospinal Fluid From Patients With Extranodal NK-/T-Cell Lymphoma of Nasal-Type With Ethmoidal Sinus Metastasis

Objective: Extranodal natural killer /T-cell lymphoma (ENKTL) is an aggressive and unusual subtype of non-Hodgkin lymphoma (NHL) that it is related with the Epstein-Barr virus (EBV). CSF is considered as an ideal source of high-concenrtation disease-related proteins. We aimed at identifying the proteomic markers changes of CSF in ENKTL patients and used such changes to diagnose ENKTL.

Materials and methods: In this study, CSF samples were acquired from hospitalization patients from the Cancer Center of West China Hospital, Chengdu, China. Comparative proteomic profiling are commonly used to do label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS). And in this study the same method was used to characterize the variety of proteins in ENKTL patients and none-ENKTL people.

Results: In the aggregate, 421 non-excrescent and functional proteins were identified among the samples. Of these proteins, 45 proteins quantified match the involved criteria. HRG, TIMP-1, SERPINA3, FGA, FGG, TF, FGB, APP, and AGT were significantly up-regulated.

Discussion: We discovered that some proteins were significantly up-regulated. Also, these proteins themselves or with others proteins may be potential markers to diagnose ENKTL. The changes of proteomics may be a potential method to precisely identify the pathogenesis of the ENKTL.

Dramatically changed immune-related molecules as early diagnostic biomarkers of non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is the main type of lung cancer, with a low 5-year survival rate because of the absence of effective clinical biomarkers for early diagnosis. Based on the immunosurveillance theory, we proposed that changes in the immune system are more pronounced than tumour-associated antigens during the early stage of cancer. Therefore, a new strategy was designed to screen early diagnostic biomarkers from peripheral leukocytes in early-stage NSCLCs with transcriptome sequencing. A total of 358 immune-related differentially expressed genes were identified between early-NSCLC patients and healthy individuals. Orosomucoid-1 (ORM1, a acute phase protein), the total ORM and chitotriosidase-1 (involved in degradation of chitobiose) were selected for further verification in 210 serum samples by western blotting, ELISA and nephelometry immunoassay (based on immuno-scatter turbidmetry). Receiver operating characteristic curve analysis show that ORM1 and total ORM have excellent diagnostic efficacies, with area under the curve of 0.862 and 0.920, respectively, which significantly distinguished very early-NSCLC (IA) from healthy samples. Flow cytometry results showed that CD15⁺ neutrophils made up 73% of ORM1⁺ peripheral leukocytes. In mouse lung cancer model, serum ORM1, but not liver ORM1, changed significantly in the early stage of NSCLC. ORM1 expression in peripheral leukocytes was regulated by TGF-β and mediated by the TGF-β/Smad signalling pathway. Our results indicated that combined ORM and TGF-β could be a promising clinical biomarker in the diagnosis of early NSCLC.

Proteome of normal human perilymph and perilymph from people with disabling vertigo

The vast majority of hearing loss, the most common sensory impairment, and vertigo, which commonly causes falls, both reflect underlying dysfunction of inner ear cells. Perilymph sampling can thus provide molecular cues to hearing and balance disorders. While such "liquid biopsy" of the inner ear is not yet in routine clinical practice, previous studies have uncovered alterations in perilymph in patients with certain types of hearing loss. However, the proteome of perilymph from patients with intact hearing has been unknown. Furthermore, no complete characterization of perilymph from patients with vestibular dysfunction has been reported. Here, using liquid-chromatography with tandem mass spectrometry, we analyzed samples of normal perilymph collected from three patients with skull base meningiomas and intact hearing. We identified 228 proteins that were common across the samples, establishing a greatly expanded proteome of the previously inferred normal human perilymph. Further comparison to perilymph obtained from three patients with vestibular dysfunction with drop attacks due to Meniere's disease showed 38 proteins with significantly differential abundance. The abundance of four protein candidates with previously unknown roles in inner ear biology was validated in murine cochleae by immunohistochemistry and in situ hybridization: AACT, HGFAC, EFEMP1, and TGFBI. Together, these results motivate future work in characterizing the normal human perilymph and identifying biomarkers of inner ear disease.

Identification a novel clinical biomarker in early diagnosis of human non-small cell lung cancer

Non-small cell lung cancer (NSCLC) is a malignant tumor with high morbidity and mortality. The clinical biomarkers currently used for the early diagnosis of lung cancer have poor sensitivity and specificity. Therefore, it is urgent to identify sensitive biomarkers for the early detection of NSCLC to improve the patient survival of patients. In our previously study, we identified glycoprotein alpha-1-antichymotrypsin (AACT) as an early biomarker of NSCLC. In this study, serum glycopeptides were enriched using the high-GlcNAc-specific binding lectin, AANL/AAL2, for further quantitative proteomics analysis using LC-MS/MS. A total of 55 differentially expressed proteins were identified by using demethylation labelling proteomics. Serum paraoxonase/arylesterase 1 (PON1) was selected for validation by western blotting and lectin-ELISA in samples from 120 enrolled patients. Our data showed that AANL-enriched PON1 has better diagnostic performance than total PON1 in early NSCLC, since it differed between early Stage I tumor samples and tumor-free samples (healthy and benign). Combining AANL-enriched PON1 with carcinoembryonic antigen (CEA) significantly improved the diagnostic specificity of CEA. Moreover, combined AANL-enriched PON1 and AANL-enriched AACT was significantly different between early NSCLC samples and tumor-free samples with an AUC of 0.940, 94.4% sensitivity, and 90.2% specificity. Our findings suggest that combined AANL-enriched PON1 and AANL-enriched AACT is a potential clinical biomarker for the early diagnosis of NSCLC.

Multiplex assay for multiomics advances in personalized-precision medicine

Building the future of precision medicine is the main focus in cancer domain. Clinical trials are moving toward an array of studies that are more adapted to precision medicine. In this domain, there is an enhanced need for biomarkers, monitoring devices, and data-analysis methods. Omics profiling using whole genome, epigenome, transcriptome, proteome, and metabolome can offer detailed information of the human body in an integrative manner. Omes profiles reflect more accurately real-time physiological status. Personalized omics analyses both disease as a whole and the main disease processes, for a better understanding of the individualized health. Through this, multi-omic approaches for health monitoring, preventative medicine, and personalized treatment can be targeted simultaneously and can lead clinicians to have a comprehensive view on the diseasome.

PI3Kδ Is a Therapeutic Target in Hepatocellular Carcinoma

Class I phosphoinositide 3-kinase (PI3K) signaling is a major pathway in human cancer development and progression. Among the four PI3K isoforms, PI3Kα and PI3Kβ are ubiquitously expressed, whereas PI3Kγ and PI3Kδ are found primarily in leukocytes. Until now, PI3K targeting in solid tumors has focused on inhibiting PI3Kα-mediated and PI3Kβ-mediated cancer cell-intrinsic PI3K activity. The role of PI3Kδ in solid tumors is unknown. Here, we evaluated the effects of PI3Kδ using established hepatocellular carcinoma (HCC) cells, malignant hepatocytes derived from patients with advanced HCC, murine models, and HCC tissues using RNA sequencing, quantitative PCR, immunoblotting, immunofluorescence, microarray, liquid chromatography-tandem mass spectrometry, and kinase assay. We established a chemical carcinogenesis model of liver malignancy that reflects the malignant phenotype and the in vivo environment of advanced HCC. In this in vivo advanced HCC-mimic system using HCC cells treated with hydrogen peroxide (H₂ O₂ ), we showed that H₂ O₂ selectively increases PI3Kδ activity while decreasing that of other class I PI3Ks. Blocking PI3Kδ activity with a PI3Kδ inhibitor or small interfering RNA-mediated PI3Kδ gene silencing inhibited HCC-cell proliferation and dampened key features of malignant HCC, including the up-regulation of telomerase reverse transcriptase (TERT). Mechanistically, H₂ O₂ induced oxidative modification of the serpin peptidase inhibitor, serpin peptidase inhibitor (SERPINA3), blocking its ubiquitin-dependent degradation and enhancing its activity as a transcriptional activator of PI3Kδ and TERT. High PI3Kδ levels in HCC were found to correlate with poor survival rates, with human advanced HCC showing positive correlations between the protein levels of oxidized SERPINA3, PI3Kδ, and TERT. Thus, PI3Kδ plays significant roles in malignant liver tumors. Conclusion: Our data identify PI3Kδ inhibition, recently approved for the treatment of human B-cell malignancies, as a potential treatment for HCC.

Compound kushen injection suppresses human acute myeloid leukaemia by regulating the Prdxs/ROS/Trx1 signalling pathway

BACKGROUND

The increase in the levels of reactive oxygen species (ROS) in acute myeloid leukemia (AML) patients has been previously described; thus, it is important to regulate ROS levels in AML.

METHODS

Flow cytometry were used to assess the in vitro effect of compound kushen injection (CKI). Quantitative proteomics were used to analyse the mechanism. The AML patient-derived xenograft (PDX) model were used to evaluate the in vivo effect of CKI.

RESULTS

We found that intracellular ROS levels in AML cells were decreased, the antioxidant capacity were increased when treated with CKI. CKI inhibited the proliferation of AML cells and enhanced the cytotoxicity of AML cells, which has few toxic effects on haematopoietic stem cells (HSCs) and T cells. At the single-cell level, individual AML cells died gradually by CKI treatment on optofluidic chips. CKI promoted apoptosis and arrested cell cycle at G1/G0 phase in U937 cells. Furthermore, higher peroxiredoxin-3 (Prdx3) expression levels were identified in CKI-treated U937 cells through quantitative proteomics detection. Mechanically, the expression of Prdx3 and peroxiredoxin-2 (Prdx2) was up-regulated in CKI-treated AML cells, while thioredoxin 1 (Trx1) was reduced. Laser confocal microscopy showed that the proteins Prdx2 could be Interacted with Trx1 by CKI treatment. In vivo, the survival was longer and the disease was partially alleviated by decreased CD45+ immunophenotyping in peripheral blood in the CKI-treated group in the AML PDX model.

CONCLUSIONS

Antioxidant CKI possess better clinical application against AML through the Prdxs/ROS/Trx1 signalling pathway.

Analysis of the plasma proteome using iTRAQ and TMT-based Isobaric labeling

Over the past decade, chemical labeling with isobaric tandem mass tags, such as isobaric tags for relative and absolute quantification reagents (iTRAQ) and tandem mass tag (TMT) reagents, has been employed in a wide range of different clinically orientated serum and plasma proteomics studies. In this review the scope of these works is presented with attention to the areas of research, methods employed and performance limitations. These applications have covered a wide range of diseases, disorders and infections, and have implemented a variety of different preparative and mass spectrometric approaches. In contrast to earlier works, which struggled to quantify more than a few hundred proteins, increasingly these studies have provided deeper insight into the plasma proteome extending the numbers of quantified proteins to over a thousand.

AANL (Agrocybe aegerita lectin 2) is a new facile tool to probe for O-GlcNAcylation

O-linked N-acetylglucosamine (O-GlcNAcylation) is an important post-translational modification on serine or threonine of proteins, mainly observed in nucleus or cytoplasm. O-GlcNAcylation regulates many cell processes, including transcription, cell cycle, neural development and nascent polypeptide chains stabilization. However, the facile identification of O-GlcNAc is a major bottleneck in O-GlcNAcylation research. Herein, we report that a lectin, Agrocybe aegerita GlcNAc-specific lectin (AANL), also reported as AAL2, can be used as a powerful probe for O-GlcNAc identification. Glycan array analyses and surface plasmon resonance (SPR) assays show that AANL binds to GlcNAc with a dissociation constant (KD) of 94.6 μM, which is consistent with the result tested through isothiocyanate (ITC) assay reported before (Jiang S, Chen Y, Wang M, Yin Y, Pan Y, Gu B, Yu G, Li Y, Wong BH, Liang Y, et al. 2012. A novel lectin from Agrocybe aegerita shows high binding selectivity for terminal N-acetylglucosamine. Biochem J. 443:369-378.). Confocal imaging shows that AANL co-localizes extensively with NUP62, a heavily O-GlcNAcylated and abundant nuclear pore glycoprotein. Furthermore, O-GlcNAc-modified peptides could be effectively enriched in the late flow-through peak from simple samples by using affinity columns Sepharose 4B-AANL or POROS-AANL. Therefore, using AANL affinity column, we identified 28 high-confidence O-linked HexNAc-modified peptides mapped on 17 proteins involving diverse cellular progresses, including transcription, hydrolysis progress, urea cycle, alcohol metabolism and cell cycle. And most importantly, major proteins and sites were not annotated in the dbOGAP database. These results suggest that the AANL lectin is a new useful tool for enrichment and identification of O-GlcNAcylated proteins and peptides.

Serpin peptidase inhibitor, clade A member 3 (SERPINA3), is overexpressed in glioma and associated with poor prognosis in glioma patients

Glioma is the most common and aggressive human primary tumor in the central nervous system. Despite present clinical advancements, median survival time remains poor in this malignant tumor. Serpin peptidase inhibitor, clade A member 3 (SERPINA3), is a member of the serpin superfamily of protease inhibitors. Its aberrant expression has been observed in various tumors. However, its clinical significance and biological function in glioma remain unclear, especially for the prognosis of glioma patients. In this study, we investigated SERPINA3 expression in glioma tissue samples and its significance in predicting the prognosis of glioma patients. SERPINA3 protein expression was studied by immunohistochemistry, while real-time polymerase chain reaction was used to study SERPINA3 mRNA expression. We found that SERPINA3 was upregulated in glioma tissue at both mRNA and protein levels, compared with noncancerous brain tissues. We also found that high SERPINA3 expression in glioma tissues correlated significantly with advanced World Health Organization grade. Univariate and multivariate analyses revealed that high SERPINA3 expression was an independent prognostic factor for poor overall survival of glioma patients. Moreover, our findings were further validated by online Oncomine database. Taken together, our results suggest that SERPINA3 plays an oncogenic role in glioma progression and provide an insight into the application of SERPINA3 as a novel predictor of clinical outcomes and a potential biomarker of glioma.

Integration of Breast Cancer Secretomes with Clinical Data Elucidates Potential Serum Markers for Disease Detection, Diagnosis, and Prognosis

Cancer cells secrete factors that influence adjacent cell behavior and can lead to enhanced proliferation and metastasis. To better understand the role of these factors in oncogenesis and disease progression, estrogen and progesterone receptor positive MCF-7 cells, triple negative breast cancer MDA-MB-231, DT22, and DT28 cells, and MCF-10A non-transformed mammary epithelial cells were grown in 3D cultures. A special emphasis was placed on triple negative breast cancer since these tumors are highly aggressive and no targeted treatments are currently available. The breast cancer cells secreted factors of variable potency that stimulated proliferation of the relatively quiescent MCF-10A cells. The conditioned medium from each cell line was subjected to mass spectrometry analysis and a variety of secreted proteins were identified including glycolytic enzymes, proteases, protease inhibitors, extracellular matrix proteins, and insulin-like growth factor binding proteins. An investigation of the secretome from each cell line yielded clues about strategies used for breast cancer proliferation and metastasis. Some of the proteins we identified may be useful in the development of a serum-based test for breast cancer detection, diagnosis, prognosis, and monitoring.