A comprehensive peptidome profiling technology for the identification of early detection biomarkers for lung adenocarcinoma

Longitudinal plasma proteomic profiling of EML4-ALK positive lung cancer receiving ALK-TKIs therapy

BACKGROUND

Anaplastic lymphoma kinase-tyrosine kinase inhibitors (ALK-TKIs) has demonstrated remarkable therapeutic effects in ALK-positive non-small cell lung cancer (NSCLC) patients. Identifying prognostic biomarkers can enhance the clinical efficacy of relapsed or refractory patients.

METHODS

We profiled 737 plasma proteins from 159 pre-treatment and on-treatment plasma samples of 63 ALK-positive NSCLC patients using data-independent acquisition-mass spectrometry (DIA-MS). The consensus clustering algorithm was used to identify subtypes with distinct biological features. A plasma-based prognostic model was constructed using the LASSO-Cox method. We performed the Mfuzz analysis to classify the patterns of longitudinal changes in plasma proteins during treatment. 52 baseline plasma samples from another independent ALK-TKI treatment cohort were collected to validate the potential prognostic markers using ELISA.

RESULTS

We identified three subtypes of ALK-positive NSCLC with distinct biological features and clinical efficacy. Patients in subgroup 1 exhibited activated humoral immunity and inflammatory responses, increased expression of positive acute-phase response proteins, and the worst prognosis. Then we constructed and verified a prognostic model that predicts the efficacy of ALK-TKI therapy using the expression levels of five plasma proteins (SERPINA4, ATRN, APOA4, TF, and MYOC) at baseline. Next, we explored the longitudinal changes in plasma protein expression during treatment and identified four distinct change patterns (Clusters 1-4). The longitudinal changes of acute-phase proteins during treatment can reflect the treatment status and tumor progression of patients. Finally, we validated the prognostic efficacy of baseline plasma CRP, SAA1, AHSG, SERPINA4, and TF in another independent NSCLC cohort undergoing ALK-TKI treatment.

CONCLUSIONS

This study contributes to the search for prognostic and drug-resistance biomarkers in plasma samples for ALK-TKI therapy and provides new insights into the mechanism of drug resistance and the selection of follow-up treatment.

Differential toxicity and localization of arginine-rich C9ORF72 dipeptide repeat proteins depend on de-clustering of positive charges

Arginine-rich dipeptide repeat proteins (R-DPRs), poly(PR) and poly(GR), translated from the hexanucleotide repeat expansion in the amyotrophic lateral sclerosis (ALS)-causative C9ORF72 gene, contribute significantly to pathogenesis of ALS. Although both R-DPRs share many similarities, there are critical differences in their subcellular localization, phase separation, and toxicity mechanisms. We analyzed localization, protein-protein interactions, and phase separation of R-DPR variants and found that sufficient segregation of arginine charges is necessary for nucleolar distribution. Proline not only efficiently separated the charges, but also allowed for weak, but highly multivalent binding. In contrast, because of its high flexibility, glycine cannot fully separate the charges, and poly(GR) behaves similarly to the contiguous arginines, being trapped in the cytoplasm. We conclude that the amino acid that spaces the arginine charges determines the strength and multivalency of the binding, leading to differences in localization and toxicity mechanisms.

Apolipoprotein A-IV Has Bi-Functional Actions in Alcoholic Hepatitis by Regulating Hepatocyte Injury and Immune Cell Infiltration

Alcohol abuse can lead to alcoholic hepatitis (AH), a worldwide public health issue with high morbidity and mortality. Here, we identified apolipoprotein A-IV (APOA4) as a biomarker and potential therapeutic target for AH. APOA4 expression was detected by Gene Expression Omnibus (GEO) databases, Immunohistochemistry, and qRT-PCR in AH. Bioinformatics Methods (protein-protein interaction (PPI) network, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and Gene Set Enrichment Analysis (GSEA) were used to show down-stream gene and pathways of APOA4 in AH. AML-12 cells were used to evaluate the biological function of APOA4 using an ELISA kit (AST, ALT, and IL-1β) and flow cytometry (ROS activity). Both in vivo and in vitro, APOA4 expression was significantly elevated in the AH model induced by alcohol (ETOH). AML-12 cell damage was specifically repaired by APOA4 deficiency, while AST, ALT, and IL-1β activity that was increased by ETOH (200 µmol, 12 h) were suppressed. APOA4 inhibition increased intracellular ROS induced by ETOH, which was detected by flow cytometry. Functional and PPI network analyses showed Fcgamma receptor (FCGR) and platelet activation signaling were potential downstream pathways. We identified CIDEC as a downstream gene of APOA4. The CIDEC AUC values for the ROC curves were 0.861. At the same time, APOA4 silencing downregulated the expression of CIDEC, whereas the knockdown of CIDEC did not influence the expression of APOA4 in AML-12 cells. Collectively, APOA4 regulates CIDEC expression and immune cell infiltration and may hold great potential as a biomarker and therapeutic target for AH.

Serum phosphopeptide profiling for colorectal cancer diagnosis using liquid chromatography-mass spectrometry

RATIONALE

The identification and evaluation of novel biomarkers are essential to clinical diagnosis and prognosis of colorectal cancer (CRC). Serum phosphopeptides have been recognized as a potential signature pool for cancers; therefore, we aim to profile the expression of serum phosphopeptides and to evaluate their feasibility in CRC diagnosis.

METHODS

We conducted the characterization and absolute quantification of endogenous phosphopeptides in sera using liquid chromatography-mass spectrometry analysis in combination with enrichment of phosphopeptides by ZrAs-Fe₃ O₄ @SiO₂ nanoparticles and use of deuterium-labeled standards. Differentially expressed analysis of four phosphopeptides was performed, generating a two-phosphopeptide-based biomarker, L_F3-4 , by logistic regression analysis, where L_F3-4 is equal to (5.85 - 5.13 × [F3] - 3.57 × [F4]), and [F3] and [F4] are the concentration of phosphopeptides DpSGEGDFLAEGGGVR and ADpSGEGDFLAEGGGVR in sera, respectively.

RESULTS

The L_F3-4 values showed significant difference in CRC cases compared with controls, and yielded a specificity of 100%, leading to correct classification of 56 (93%) out of 60 CRC patients, including 12 (92.3%) of 13 CRC cases in stage I. Double-blind validation showed that 97.5% of CRC cases were discriminated accurately.

CONCLUSIONS

The L_F3-4 value was firstly verified to be a potential biomarker for CRC diagnosis, and may expand our view in underlying mechanisms for CRC.

A Circulating Risk Score, Based on Combined Expression of Exo-miR-130a-3p and Fibrinopeptide A, as Predictive Biomarker of Relapse in Resectable Non-Small Cell Lung Cancer Patients

Simple Summary

To date, the five-year survival rate of early stages of non-small cell lung cancer (NSCLC) is still disappointing and reliable prognostic factors are mandatory. Here, we performed in-depth high-throughput analyses of plasma circulating markers, including exosomal microRNAs and peptidome to identify a prognostic score. The miRnome profile selected the Exo-miR-130a-3p as the most overexpressed in relapsed patients. Peptidome analysis identified four progressively more degraded forms of fibrinopeptide A (FpA), which were depleted in relapse patients. Notably, a stepwise algorithm selected Exo-miR-130a-3p and the greatest FpA (2–16) to build a prognostic score, where high-risk patients had 18 months of median disease-free survival. Overexpression of miR-130a-3p cells led to a deregulation of pathways such as angiogenesis as well as the coagulation and metalloprotease, which might be linked to FpA reduction. The risk score integrating circulating markers may help clinicians predict early-stage NSCLC patients who are more likely to relapse after surgery.

Abstract

To date, the 5-year overall survival rate of 60% for early-stage non-small cell lung cancer (NSCLC) is still unsatisfactory. Therefore, reliable prognostic factors are needed. Growing evidence shows that cancer progression may depend on an interconnection between cancer cells and the surrounding tumor microenvironment; hence, circulating molecules may represent promising markers of cancer recurrence. In order to identify a prognostic score, we performed in-depth high-throughput analyses of plasma circulating markers, including exosomal microRNAs (Exo-miR) and peptides, in 67 radically resected NSCLCs. The miRnome profile selected the Exo-miR-130a-3p as the most overexpressed in relapsed patients. Peptidome analysis identified four progressively more degraded forms of fibrinopeptide A (FpA), which were depleted in progressing patients. Notably, stepwise Cox regression analysis selected Exo-miR-130a-3p and the greatest FpA (2-16) to build a score predictive of recurrence, where high-risk patients had 18 months of median disease-free survival. Moreover, in vitro transfections showed that higher levels of miR-130a-3p lead to a deregulation of pathways involved in metastasis and angiogenesis, including the coagulation process and metalloprotease increase which might be linked to FpA reduction. In conclusion, by integrating circulating markers, the identified risk score may help clinicians predict early-stage NSCLC patients who are more likely to relapse after primary surgery.

The Patterning and Proportion of Charged Residues in the Arginine-Rich Mixed-Charge Domain Determine the Membrane-Less Organelle Targeted by the Protein

Membrane-less organelles (MLOs) are formed by biomolecular liquid–liquid phase separation (LLPS). Proteins with charged low-complexity domains (LCDs) are prone to phase separation and localize to MLOs, but the mechanism underlying the distributions of such proteins to specific MLOs remains poorly understood. Recently, proteins with Arg-enriched mixed-charge domains (R-MCDs), primarily composed of R and Asp (D), were found to accumulate in nuclear speckles via LLPS. However, the process by which R-MCDs selectively incorporate into nuclear speckles is unknown. Here, we demonstrate that the patterning of charged amino acids and net charge determines the targeting of specific MLOs, including nuclear speckles and the nucleolus, by proteins. The redistribution of R and D residues from an alternately sequenced pattern to uneven blocky sequences caused a shift in R-MCD distribution from nuclear speckles to the nucleolus. In addition, the incorporation of basic residues in the R-MCDs promoted their localization to the MLOs and their apparent accumulation in the nucleolus. The R-MCD peptide with alternating amino acids did not undergo LLPS, whereas the blocky R-MCD peptide underwent LLPS with affinity to RNA, acidic poly-Glu, and the acidic nucleolar protein nucleophosmin, suggesting that the clustering of R residues helps avoid their neutralization by D residues and eventually induces R-MCD migration to the nucleolus. Therefore, the distribution of proteins to nuclear speckles requires the proximal positioning of D and R for the mutual neutralization of their charges.

Nano liquid chromatography, an updated review

Low flow chromatography has a rich history of innovation but has yet to reach widespread implementation in bioanalytical applications. Improvements in pump technology, microfluidic connections, and nano-electrospray sources for mass spectrometry have laid the groundwork for broader application, and innovation in this space has accelerated in recent years. This article reviews the instrumentation used for nano-flow liquid chromatography , the types of columns employed, and strategies for multi-dimensionality of separations, which is key to the future state of the technique to the high-throughput needs of modern bioanalysis. An update of the current applications where nano-LC is widely used, such as proteomics and metabolomics, is discussed. But the trend towards biopharmaceutical development of increasingly complex, targeted, and potent therapeutics for the safe treatment of disease drives the need for ultimate selectivity and sensitivity of our analytical platforms for targeted quantitation in a regulated space. The selectivity needs are best addressed by mass spectrometric detection, especially at high resolutions, and exquisite sensitivity is provided by nano-electrospray ionization as the technology continues to evolve into an accessible, robust, and easy to use platform.

Order controls disordered droplets: structure-function relationships in C9orf72-derived poly(PR)

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) have been thought as two distinct neurodegenerative diseases. However, recent genetic screening and careful investigations found the genetic and pathological overlap among these disorders. Hexanucleotide expansions in intron 1 of C9orf72 are a leading cause of familial ALS and familial FTD. These expansions facilitate the repeat-associated non-ATG initiated translation (RAN translation), producing five dipeptide repeat proteins (DRPs), including Arg-rich poly(PR: Pro-Arg) and poly-(GR: Gly-Arg) peptides. Arg is a positively charged, highly polar amino acid that facilitates interactions with anionic molecules such as nucleic acids and acidic amino acids via electrostatic forces and aromatic amino acids via cation-pi interaction, suggesting that Arg-rich DRPs underlie the pathophysiology of ALS via Arg-mediated molecular interactions. Arg-rich DRPs have also been reported to induce neurodegeneration in cellular and animal models via multiple mechanisms; however, it remains unclear why the Arg-rich DRPs exhibit such diverse toxic properties, because not all Arg-rich peptides are toxic. In this mini-review, we discuss the current understanding of the pathophysiology of Arg-rich C9orf72 DRPs and introduce recent findings on the role of Arg distribution as a determinant of the toxicity and its contribution to the pathogenesis of ALS.

Phase separation and toxicity of C9orf72 poly(PR) depends on alternate distribution of arginine

Arg (R)-rich dipeptide repeat proteins (DPRs; poly(PR): Pro-Arg and poly(GR): Gly-Arg), encoded by a hexanucleotide expansion in the C9ORF72 gene, induce neurodegeneration in amyotrophic lateral sclerosis (ALS). Although R-rich DPRs undergo liquid-liquid phase separation (LLPS), which affects multiple biological processes, mechanisms underlying LLPS of DPRs remain elusive. Here, using in silico, in vitro, and in cellulo methods, we determined that the distribution of charged Arg residues regulates the complex coacervation with anionic peptides and nucleic acids. Proteomic analyses revealed that alternate Arg distribution in poly(PR) facilitates entrapment of proteins with acidic motifs via LLPS. Transcription, translation, and diffusion of nucleolar nucleophosmin (NPM1) were impaired by poly(PR) with an alternate charge distribution but not by poly(PR) variants with a consecutive charge distribution. We propose that the pathogenicity of R-rich DPRs is mediated by disturbance of proteins through entrapment in the phase-separated droplets via sequence-controlled multivalent protein-protein interactions.

Pathophysiological Implications of Urinary Peptides in Hepatocellular Carcinoma

Simple Summary

In this study, the application of capillary electrophoresis mass spectrometry enabled identification of 31 urinary peptides significantly associated with hepatocellular carcinoma diagnosis and prognosis. Further assessment of these peptides lead to prediction of cellular proteases involved in their development namely Meprin A subunit α and Kallikrein-6. Subsequent identification of the proteases was verified by immunohistochemistry in normal liver, cirrhosis and hepatocellular carcinoma. Histopathological assessment of the proteases revealed numerical gradient staining signifying their involvement in liver fibrosis and hepatocellular carcinoma formation. The discovered urinary peptides offered a potential noninvasive tool for diagnosis and prognosis of hepatocellular carcinoma.

Abstract

Hepatocellular carcinoma (HCC) is known to be associated with protein alterations and extracellular fibrous deposition. We investigated the urinary proteomic profiles of HCC patients in this prospective cross sectional multicentre study. 195 patients were recruited from the UK (Coventry) and Germany (Hannover) between 1 January 2013 and 30 June 2019. Out of these, 57 were HCC patients with a background of liver cirrhosis (LC) and 138 were non-HCC controls; 72 patients with LC, 57 with non-cirrhotic liver disease and 9 with normal liver function. Analysis of the urine samples was performed by capillary electrophoresis (CE) coupled to mass spectrometry (MS). Peptide sequences were obtained and 31 specific peptide markers for HCC were identified and further integrated into a multivariate classification model. The peptide model demonstrated 79.5% sensitivity and 85.1% specificity (95% CI: 0.81–0.93, p < 0.0001) for HCC and 4.1-fold increased risk of death (95% CI: 1.7–9.8, p = 0.0005). Proteases potentially involved in HCC progression were mapped to the N- and C-terminal sequence motifs of the CE-MS peptide markers. In silico protease prediction revealed that kallikrein-6 (KLK6) elicits increased activity, whilst Meprin A subunit α (MEP1A) has reduced activity in HCC compared to the controls. Tissue expression of KLK6 and MEP1A was subsequently verified by immunohistochemistry.

Hypertensive disorders of pregnancy: Strategy to develop clinical peptide biomarkers for more accurate evaluation of the pathophysiological status of this syndrome

Hypertensive disorders of pregnancy (HDP) is the most common and widely known as serious complication of pregnancy. As this syndrome is a major leading cause of maternal, fetal, and neonatal morbidity/mortality worldwide, many studies have sought to identify candidate molecules as potential disease biomarkers (DBMs) for use in clinical examinations. Accumulating evidence over the past 2 decades that the many proteolytic peptides appear in human humoral fluids, including peripheral blood, in association with an individual's health condition. This review provides the potential utility of peptidomic analysis for monitoring for pathophysiological status in HDP, and presents an overview of current status of peptide quantification technology. Especially, the technical limitations of the methods used for DBM discovery in the blood are discussed.

Recent advances in mass spectrometry-based approaches for proteomics and biologics: Great contribution for developing therapeutic antibodies

Since the turn of the century, mass spectrometry (MS) technologies have continued to improve dramatically, and advanced strategies that were impossible a decade ago are increasingly becoming available. The basic characteristics behind these advancements are MS resolution, quantitative accuracy, and information science for appropriate data processing. The spectral data from MS contain various types of information. The benefits of improving the resolution of MS data include accurate molecular structural-derived information, and as a result, we can obtain a refined biomolecular structure determination in a sequential and large-scale manner. Moreover, in MS data, not only accurate structural information but also the generated ion amount plays an important rule. This progress has greatly contributed a research field that captures biological events as a system by comprehensively tracing the various changes in biomolecular dynamics. The sequential changes of proteome expression in biological pathways are very essential, and the amounts of the changes often directly become the targets of drug discovery or indicators of clinical efficacy. To take this proteomic approach, it is necessary to separate the individual MS spectra derived from each biomolecule in the complexed biological samples. MS itself is not so infinite to perform the all peak separation, and we should consider improving the methods for sample processing and purification to make them suitable for injection into MS. The above-described characteristics can only be achieved using MS with any analytical instrument. Moreover, MS is expected to be applied and expand into many fields, not only basic life sciences but also forensic medicine, plant sciences, materials, and natural products. In this review, we focus on the technical fundamentals and future aspects of the strategies for accurate structural identification, structure-indicated quantitation, and on the challenges for pharmacokinetics of high-molecular-weight protein biopharmaceuticals.

Current and Prospective Protein Biomarkers of Lung Cancer

Lung cancer is a malignant lung tumor with various histological variants that arise from different cell types, such as bronchial epithelium, bronchioles, alveoli, or bronchial mucous glands. The clinical course and treatment efficacy of lung cancer depends on the histological variant of the tumor. Therefore, accurate identification of the histological type of cancer and respective protein biomarkers is crucial for adequate therapy. Due to the great diversity in the molecular-biological features of lung cancer histological types, detection is impossible without knowledge of the nature and origin of malignant cells, which release certain protein biomarkers into the bloodstream. To date, different panels of biomarkers are used for screening. Unfortunately, a uniform serum biomarker composition capable of distinguishing lung cancer types is yet to be discovered. As such, histological analyses of tumor biopsies and immunohistochemistry are the most frequently used methods for establishing correct diagnoses. Here, we discuss the recent advances in conventional and prospective aptamer based strategies for biomarker discovery. Aptamers like artificial antibodies can serve as molecular recognition elements for isolation detection and search of novel tumor-associated markers. Here we will describe how these small synthetic single stranded oligonucleotides can be used for lung cancer biomarker discovery and utilized for accurate diagnosis and targeted therapy. Furthermore, we describe the most frequently used in-clinic and novel lung cancer biomarkers, which suggest to have the ability of differentiating between histological types of lung cancer and defining metastasis rate.

Evaluation of plasma peptides extraction methods by high-resolution mass spectrometry

Monitoring of peptides offers a promising approach for the discovery of novel biomarkers, which might be valuable for detection, treatment and prevention of large variety of diseases. Development of highly effective methods for plasma peptide extraction remains an important task. In the current study, we applied different types of plasma peptide extraction approaches to reveal efficient methods which would provide the highest peptide yield. We used different combinations of plasma treatment with acetonitrile and/or urea/guanidine, protein precipitation by acetone, gel-filtration, ultrafiltration, and two types of solid phase extraction. The extracted peptides were analyzed by LC-MS/MS. The obtained results suggest that several methods, including differential solubilization, organic precipitation, as well as some variants of ultrafiltration and solid phase extraction, provide effective plasma peptide enrichment convenient for further LC-MS/MS analysis. Alas, most of the identified peptides were extracted by only one of the applied methods. Hence, it seems reasonable to consider several methods to increase the possibility of novel biomarker discovery.

Evaluation of serum phosphopeptides as potential biomarkers of gastric cancer

A serum phosphopeptide (DpSGEGDFLAEGGGVR) was demonstrated to be a potential biomarker for gastric cancer diagnosis, particularly for early stage cases.

Novel Biomarker Proteins in Chronic Lymphocytic Leukemia: Impact on Diagnosis, Prognosis and Treatment

In many cancers, cells undergo re-programming of metabolism, cell survival and anti-apoptotic defense strategies, with the proteins mediating this reprogramming representing potential biomarkers. Here, we searched for novel biomarker proteins in chronic lymphocytic leukemia (CLL) that can impact diagnosis, treatment and prognosis by comparing the protein expression profiles of peripheral blood mononuclear cells from CLL patients and healthy donors using specific antibodies, mass spectrometry and binary logistic regression analyses and other bioinformatics tools. Mass spectrometry (LC-HR-MS/MS) analysis identified 1,360 proteins whose expression levels were modified in CLL-derived lymphocytes. Some of these proteins were previously connected to different cancer types, including CLL, while four other highly expressed proteins were not previously reported to be associated with cancer, and here, for the first time, DDX46 and AK3 are linked to CLL. Down-regulation expression of two of these proteins resulted in cell growth inhibition. High DDX46 expression levels were associated with shorter survival of CLL patients and thus can serve as a prognosis marker. The proteins with modified expression include proteins involved in RNA splicing and translation and particularly mitochondrial proteins involved in apoptosis and metabolism. Thus, we focused on several metabolism- and apoptosis-modulating proteins, particularly on the voltage-dependent anion channel 1 (VDAC1), regulating both metabolism and apoptosis. Expression levels of Bcl-2, VDAC1, MAVS, AIF and SMAC/Diablo were markedly increased in CLL-derived lymphocytes. VDAC1 levels were highly correlated with the amount of CLL-cancerous CD19+/CD5+ cells and with the levels of all other apoptosis-modulating proteins tested. Binary logistic regression analysis demonstrated the ability to predict probability of disease with over 90% accuracy. Finally, based on the changes in the levels of several proteins in CLL patients, as revealed from LC-HR-MS/MS, we could distinguish between patients in a stable disease state and those who would be later transferred to anti-cancer treatments. The over-expressed proteins can thus serve as potential biomarkers for early diagnosis, prognosis, new targets for CLL therapy, and treatment guidance of CLL, forming the basis for personalized therapy.

Secretomes are a potential source of molecular targets for cancer therapies and indicate that APOE is a candidate biomarker for lung adenocarcinoma metastasis

Identifying patients at high risk of metastasis is a major challenge in lung adenocarcinoma (ADC) therapy, therefore discovery of noninvasive biomarkers and therapeutic targets is urgent. We found significant differences between the secretomes of differentially expressed proteins in lung ADC cell lines, clinical tissue samples and serum plasma samples with high and low metastatic potential. In particular, Apolipoprotein E (APOE) levels were three-times greater in cells with lymph node metastases (LNM) than those without. Our study indicates that APOE is a potential indicator of metastatic lung ADC and that secretomes may offer a valuable resource for biomarkers of lung ADC with LNM.

Respiratory Proteomics Today: Are Technological Advances for the Identification of Biomarker Signatures Catching up with Their Promise? A Critical Review of the Literature in the Decade 2004-2013

To improve the knowledge on a variety of severe disorders, research has moved from the analysis of individual proteins to the investigation of all proteins expressed by a tissue/organism. This global proteomic approach could prove very useful: (i) for investigating the biochemical pathways involved in disease; (ii) for generating hypotheses; or (iii) as a tool for the identification of proteins differentially expressed in response to the disease state. Proteomics has not been used yet in the field of respiratory research as extensively as in other fields, only a few reproducible and clinically applicable molecular markers, which can assist in diagnosis, having been currently identified. The continuous advances in both instrumentation and methodology, which enable sensitive and quantitative proteomic analyses in much smaller amounts of biological material than before, will hopefully promote the identification of new candidate biomarkers in this area. The aim of this report is to critically review the application over the decade 2004-2013 of very sophisticated technologies to the study of respiratory disorders. The observed changes in protein expression profiles from tissues/fluids of patients affected by pulmonary disorders opens the route for the identification of novel pathological mediators of these disorders.

Glycoproteomic strategies: From discovery to clinical application of cancer carbohydrate biomarkers

Carbohydrate antigens are the most frequently and traditionally used biomarkers for cancer, such as CA19-9, CA125, DUPAN-II, AFP-L3, and many others. The diagnostic potential of them was simply based on the cancer-specific alterations of glycan structures on particular glycoproteins in serum/plasma. In spite of the facts that glycosylation disorders are feasible for cancer biomarkers and glycomic analysis technologies to explore them have been rapidly developed, it remains difficult to sensitively screen glycan structure changes on cancer-associated glycoproteins from clinical specimens. Moreover, a lot of additional issues should be appropriately addressed for the clinical application of newly identified glycosylation biomarkers, including analytical throughput, quantitative confirmation of structural changes, and biological explanation for the alterations. In the last decade, significant improvement of mass spectrometric techniques is being made in the aspects of both hardware spec and preanalytical purification procedures for glycoprotein analysis. Here we review potential approaches to perform comprehensive analysis of glycoproteomic biomarker screening from serum/plasma and to realize high-throughput validation of site-specific oligosaccharide variations. The power and problems of mass spectrometric applications on the clinical use of carbohydrate biomarkers are also discussed in this review.

Preapoptotic protease calpain-2 is frequently suppressed in adult T-cell leukemia

Adult T-cell leukemia (ATL) is one of the most aggressive hematologic malignancies caused by human T-lymphotropic virus type 1 (HTLV-1) infection. The prognosis of ATL is extremely poor; however, effective strategies for diagnosis and treatment have not been established. To identify novel therapeutic targets and diagnostic markers for ATL, we employed focused proteomic profiling of the CD4(+)CD25(+)CCR4(+) T-cell subpopulation in which HTLV-1-infected cells were enriched. Comprehensive quantification of 14 064 peptides and subsequent 2-step statistical analysis using 29 cases (6 uninfected controls, 5 asymptomatic carriers, 9 HTLV-1-associated myelopathy/tropical spastic paraparesis patients, 9 ATL patients) identified 91 peptide determinants that statistically classified 4 clinical groups with an accuracy rate of 92.2% by cross-validation test. Among the identified 17 classifier proteins, α-II spectrin was drastically accumulated in infected T cells derived from ATL patients, whereas its digestive protease calpain-2 (CAN2) was significantly downregulated. Further cell cycle analysis and cell growth assay revealed that rescue of CAN2 activity by overexpressing constitutively active CAN2 (Δ(19)CAN2) could induce remarkable cell death on ATL cells accompanied by reduction of α-II spectrin. These results support that proteomic profiling of HTLV-1-infected T cells could provide potential diagnostic biomarkers and an attractive resource of therapeutic targets for ATL.

Serum biomarkers identification by mass spectrometry in high-mortality tumors

Cancer affects millions of people worldwide. Tumor mortality is substantially due to diagnosis at stages that are too late for therapies to be effective. Advances in screening methods have improved the early diagnosis, prognosis, and survival for some cancers. Several validated biomarkers are currently used to diagnose and monitor the progression of cancer, but none of them shows adequate specificity, sensitivity, and predictive value for population screening. So, there is an urgent need to isolate novel sensitive, specific biomarkers to detect the disease early and improve prognosis, especially in high-mortality tumors. Proteomic techniques are powerful tools to help in diagnosis and monitoring of treatment and progression of the disease. During the last decade, mass spectrometry has assumed a key role in most of the proteomic analyses that are focused on identifying cancer biomarkers in human serum, making it possible to identify and characterize at the molecular level many proteins or peptides differentially expressed. In this paper we summarize the results of mass spectrometry serum profiling and biomarker identification in high mortality tumors, such as ovarian, liver, lung, and pancreatic cancer.

Sample preparation techniques for the untargeted LC-MS-based discovery of peptides in complex biological matrices

Although big progress has been made in sample pretreatment over the last years, there are still considerable limitations when it comes to overcoming complexity and dynamic range problems associated with peptide analyses from biological matrices. Being the little brother of proteomics, peptidomics is a relatively new field of research aiming at the direct analysis of the small proteins, called peptides, many of which are not amenable for typical trypsin-based analytics. In this paper, we present an overview of different techniques and methods currently used for reducing a sample's complexity and for concentrating low abundant compounds to enable successful peptidome analysis. We focus on techniques which can be employed prior to liquid chromatography coupled to mass spectrometry for peptide detection and identification and indicate their advantages as well as their shortcomings when it comes to the untargeted analysis of native peptides from complex biological matrices.

State-of-the-art MS technology applications in lung disease

Two frontline MS technologies, which have recently gained much attention, are discussed within the scope of this review. Besides a brief summary on the contemporary state of lung cancer and chronic obstructive pulmonary disease, the principles of multiple reaction monitoring and matrix assisted laser desorption ionization (MALDI) MS imaging are presented. A comprehensive overview of quantitative mass spectrometry applications is provided, covering multiple reaction monitoring assay developments for analysis of proteins (biomarkers) and low-molecular-weight compounds (drugs) with a special focus on the disease areas of lung cancer and chronic obstructive pulmonary disease. The MALDI-MS imaging applications are discussed similarly, providing references to studies conducted on lung tissues in order to localize drug compounds and protein biomarkers.