Search

The glycoform of a therapeutic monoclonal antibody (mAb) has a significant impact on its effector function as well as its safety and pharmacokinetics. Glycoform heterogeneity is influenced by various factors, including the producing cells and cell culture processes. Therefore, accurate glycoform characterization is essential for drug design, process optimization, manufacturing, and quality control of therapeutic mAbs. In this study, we developed a fast, quantitative, and highly sensitive analytical platform for glycan profiling by supercritical fluid chromatography-tandem mass spectrometry (SFC-MS/MS) and applied the technique to the glycan structural analysis of mAbs. To achieve both the highest sensitivity and the most comprehensive glycan profiling, we integrated our energy-resolved oxonium ion monitoring (Erexim) method with SFC-MS to construct a new SFC-Erexim technology. An 8 min analysis of bevacizumab, nivolumab, ramucirumab, rituximab, and trastuzumab by SFC-Erexim detected a total of 102 glycoforms, with a detection limit of 5 attomoles. The dynamic range of glycan abundance was over 6 orders of magnitude for bevacizumab analysis by SFC-Erexim compared to 3 orders of magnitude for conventional fluorescence HPLC analysis. This method revealed the glycan profile characteristics and lot-to-lot heterogeneity of various therapeutic mAbs. We were also able to detect a series of structural variations in pharmacologically important glycan structures. The SFC-MS-based glycoform profiling method will provide an ideal platform for the in-depth analysis of precise glycan structure and abundance.

To identify liquid biomarkers that predict clinical outcomes of epidermal growth factor receptor-tyrosine kinase inhibitor (EGFR-TKI), we enrolled patients with EGFR gene mutation-positive non-small-cell lung cancer who were intended to receive gefitinib treatment. Using plasma samples obtained prior to gefitinib treatment from 12 enrolled patients, we performed comprehensive proteomic analysis of plasma exosomes to explore proteins correlating with tumor reduction rate (TRR), progression-free survival (PFS), or overall survival (OS). Of the detected 1769 proteins, 119, 130, or 119 proteins demonstrated a strong correlation (|r| > 0.5) with TRR, PFS, or OS, respectively. Interestingly, 34 (29%), 41 (32%), or 27 (23%) of them, respectively, were functionally involved in the regulation of the immune response. CD8α chain was consistently listed as a molecule positively correlated with PFS and OS, suggesting that the long-lasting effects of gefitinib may be due to the antitumor effects of CD8 + T cells, as well as the induction of immunogenic apoptosis of tumor cells by blocking the EGFR signaling pathway. Notably, Doking Protein 3 (DOK3), a molecule involved in B-cell receptor signaling, and some immunoglobulin and complement molecules exhibited a clear correlation with PFS longevity of gefitinib treatment. Indeed, the strong expression of DOK3 in B cells was confirmed within tertiary lymphoid structures of lung cancer tissues derived from patients with long PFS. These findings suggest that the patients with active B-cell and T-cell immunity as a host immunological feature are more likely to benefit from gefitinib therapy. Circulating exosomal DOK3 has the potential as a predictive marker of response to gefitinib indicating this immunological feature., (© 2022 The Authors. Cancer Science published by John Wiley & Sons Australia, Ltd on behalf of Japanese Cancer Association.)

Understanding the properties of human leukocyte antigen (HLA) peptides (immunopeptides) is essential for precision cancer medicine, while the direct identification of immunopeptides from small biopsies of clinical tissues by mass spectrometry (MS) is still confronted with technical challenges. Here, to overcome these hindrances, high-field asymmetric waveform ion mobility spectrometry (FAIMS) is introduced to conduct differential ion mobility (DIM)-MS by seamless gas-phase fractionation optimal for scarce samples. By established DIM-MS for immunopeptidomics analysis, on average, 42.9 mg of normal and tumor colorectal tissues from identical patients (n = 17) were analyzed, and on average 4921 immunopeptides were identified. Among these 44,815 unique immunopeptides, two neoantigens, KRAS-G12V and CPPED1-R228Q, were identified. These neoantigens were confirmed by synthetic peptides through targeted MS in parallel reaction monitoring (PRM) mode. Comparison of the tissue-based personal immunopeptidome revealed tumor-specific processing of immunopeptides. Since the direct identification of neoantigens from tumor tissues suggested that more potential neoantigens have yet to be identified, we screened cell lines with known oncogenic KRAS mutations and identified 2 more neoantigens that carry KRAS-G12V. These results indicated that the established FAIMS-assisted DIM-MS is effective in the identification of immunopeptides and potential recurrent neoantigens directly from scarce samples such as clinical tissues., (© 2022. The Author(s).)

Accumulating scientific evidences strongly support the importance of cancer-derived extracellular vesicles (EV) in organization of tumor microenvironment and metastatic niches, which are also considered as ideal tools for cancer liquid biopsy. To uncover the full scope of proteomic information packaged within EVs secreted directly from human colorectal cancer, we cultured surgically resected viable tissues and obtained tissue-exudative EVs (Te-EV). Our quantitative profiling of 6,307 Te-EV proteins and 8,565 tissue proteins from primary colorectal cancer and adjacent normal mucosa ( n = 17) allowed identification of a specific cargo in colorectal cancer-derived Te-EVs, high-affinity cationic amino acid transporter 1 (CAT1, P = 5.0 × 10 -3 , fold change = 6.2), in addition to discovery of a new class of EV markers, VPS family proteins. The EV sandwich ELISA confirmed escalation of the EV-CAT1 level in plasma from patients with colorectal cancer compared with healthy donors ( n = 119, P = 3.8 × 10 -7 ). Further metabolomic analysis revealed that CAT1-overexpressed EVs drastically enhanced vascular endothelial cell growth and tubule formation via upregulation of arginine transport and downstream NO metabolic pathway. These findings demonstrate the potency of CAT1 as an EV-based biomarker for colorectal cancer and its functional significance on tumor angiogenesis. IMPLICATIONS: This study provides a proteome-wide compositional dataset for viable colorectal cancer tissue-derived EVs and especially emphasizes importance of EV-CAT1 as a key regulator of angiogenesis., (©2021 American Association for Cancer Research.)

Recent proteome analyses have provided a comprehensive overview of various posttranslational modifications (PTMs); however, PTMs involving protein citrullination remain unclear. We performed a proteomic analysis of citrullinated proteins, and we identified more than 100 PAD4 (peptidyl arginine deiminase 4) substrates. Approximately one-fifth of the PAD4 substrates contained an RG/RGG motif, and PAD4 competitively inhibited the methylation of the RGG motif in FET proteins (FUS, EWS, and TAF15) and hnRNPA1, which are causative genes for ALS (amyotrophic lateral sclerosis). PAD4-mediated citrullination significantly inhibited the aggregation of FET proteins, a frequently observed feature in neurodegenerative diseases. FUS protein levels in arsenic-induced stress granules were significantly increased in Padi4 -/- mouse embryonic fibroblasts (MEFs). Moreover, rs2240335 was associated with low expression of PADI4 in the brain and a high risk of ALS (p = 0.0381 and odds ratio of 1.072). Our findings suggest that PAD4-mediated RGG citrullination plays a key role in protein solubility and ALS pathogenesis., (Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.)

Cancer-associated extracellular vesicles (EVs) are intimately involved in establishment of tumor microenvironment and occurrence of metastasis. However, previous studies have mainly relied on experiments with cultured cell lines or mouse models, making it difficult to gain a full understanding of EV functions in human body. Hence, we extracted EVs directly from surgically resected viable clear cell renal cell carcinoma (ccRCC) tissues and adjacent normal renal tissues (n = 20). Quantitative LC/MS analysis identified 3,871 tissue-exudative EV (Te-EV) proteins, among which azurocidin (AZU1) was highly enriched in tumor Te-EVs (p = 2.85 × 10 -3 , fold-change = 31.59). Importantly, AZU1 content was also significantly higher in serum EVs from ccRCC patients compared to those from healthy donors. We further found that ccRCC-derived EVs had AZU1-dependent membrane permeabilizing activity for the vascular endothelial cell layer. Thus Te-EVs should be ideal resource for investigation of physiological EV functions., (© 2017 UICC.)

Objectives: To evaluate the accuracy of an algorithm identifying newly diagnosed immune thrombocytopenia (ITP) patients in the French national health insurance database (SNIIRAM)., Methods: The source of data was the SNIIRAM of Midi-Pyrenees region (southwest of France, three million inhabitants). Data of patients with at least one ITP code (D69.3 code of the International Classification of Disease, version 10) were extracted between January 1, 2012, and December 31, 2014. We used an algorithm that identifies newly diagnosed primary ITPs. Medical charts of incident ITPs were reviewed. Positive predictive values (PPVs) of identification of true, incident, and primary ITP cases were estimated., Results: Of the 168 patients selected, 161 were true ITP cases yielding a PPV of 95.8% (95% confidence interval-95% CI: 92.8-98.8). Among them, 128 were truly incident according to symptom onset date and 134 according to the diagnosis date yielding PPVs of 79.5% (95% CI: 73.2-85.7) and 83.2% (95% CI: 77.4-89.0), respectively. Median time between estimated diagnosis date by the algorithm and true diagnosis date was 0 days (interquartile range: 0 to 15)., Conclusions: This study showed a very good PPV of this algorithm identifying incident primary ITP patients in the SNIIRAM., (© 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

The transcription factor p53 is at the core of a built-in tumor suppression system that responds to varying degrees of stress input and is deregulated in most human cancers. Befitting its role in maintaining cellular fitness and fidelity, p53 regulates an appropriate set of target genes in response to cellular stresses. However, a comprehensive understanding of this scheme has not been accomplished. We show that argininosuccinate synthase 1 ( ASS1 ), a citrulline-aspartate ligase in de novo arginine synthesis pathway, was directly transactivated by p53 in response to genotoxic stress, resulting in the rearrangement of arginine metabolism. Furthermore, we found that x-ray irradiation promoted the systemic induction of Ass1 and concomitantly increased plasma arginine levels in p53 +/+ mice but not in p53 -/- mice. Notably, Ass1 +/- mice exhibited hypersensitivity to whole-body irradiation owing to increased apoptosis in the small intestinal crypts. Analyses of ASS1 -deficient cells generated using the CRISPR (clustered regularly interspaced short palindromic repeats)-Cas9 (CRISPR-associated 9) system revealed that ASS1 plays a pivotal role in limiting Akt phosphorylation. In addition, aberrant activation of Akt resulting from ASS1 loss disrupted Akt-mediated cell survival signaling activity under genotoxic stress. Building on these results, we demonstrated that p53 induced an intrinsic Akt repressor, ASS1, and the perturbation of ASS1 expression rendered cells susceptible to genotoxic stress. Our findings uncover a new function of p53 in the regulation of Akt signaling and reveal how p53, ASS1, and Akt are interrelated to each other.

Objective: Human T-cell leukemia virus-1 (HTLV-1) associated myelopathy/tropic spastic paraparesis (HAM/TSP) is induced by chronic inflammation in spinal cord due to HTLV-1 infection. Cerebrospinal fluid (CSF) neopterin or proviral load are clinically measured as disease grading biomarkers, however, they are not exactly specific to HAM/TSP. Therefore, we aimed to identify HAM/TSP-specific biomarker molecules and establish a novel less-invasive plasma diagnostic model for HAM/TSP., Methods: Proteome-wide quantitative profiling of CSFs from six asymptomatic HTLV-1 carriers (AC) and 51 HAM/TSP patients was performed. Fourteen severity grade biomarker proteins were further examined plasma enzyme-linked immunosorbent assay (ELISA) assays (n = 71). Finally, we constructed three-factor logistic regression model and evaluated the diagnostic power using 105 plasma samples., Results: Quantitative analysis for 1871 nonredundant CSF proteins identified from 57 individuals defined 14 CSF proteins showing significant correlation with Osame's motor disability score (OMDS). Subsequent ELISA experiments using 71 plasma specimens confirmed secreted protein acidic and rich in cysteine (SPARC) and vascular cell adhesion molecule-1 (VCAM-1) demonstrated the same correlations in plasma (R = -0.373 and R = 0.431, respectively). In this training set, we constructed a HAM/TSP diagnostic model using SPARC, VCAM1, and viral load. Sensitivity and specificity to diagnose HAM/TSP patients from AC (AC vs. OMDS 1-11) were 85.3% and 81.1%, respectively. Importantly, this model could be also useful for determination of therapeutic intervention point (OMDS 1-3 + AC vs. OMDS 4-11), exhibiting 80.0% sensitivity and 82.9% specificity., Interpretation: We propose a novel less-invasive diagnostic model for early detection and clinical stratification of HAM/TSP.

Exosome-mediated signal transportation plays a variety of critical roles in cancer progression and metastasis. From the aspect of cancer diagnosis, circulating exosomes are ideal resources of biomarkers because molecular features of tumor cells are transcribed on them. However, isolating pure exosomes from body fluids is time-consuming and still major challenge to be addressed for comprehensive profiling of exosomal proteins and miRNAs. Here we constructed anti-CD9 antibody-coupled highly porous monolithic silica microtips which allowed automated rapid and reproducible exosome extraction from multiple clinical samples. We applied these tips to explore lung cancer biomarker proteins on exosomes by analyzing 46 serum samples. The mass spectrometric quantification of 1,369 exosomal proteins identified CD91 as a lung adenocarcinoma specific antigen on exosomes, which was further validated with CD9-CD91 exosome sandwich ELISA measuring 212 samples. Our simple device can promote not only biomarker discovery studies but also wide range of omics researches about exosomes.

In prostate cancer diagnosis, PSA test has greatly contributed to the early detection of prostate cancer; however, expanding overdiagnosis and unnecessary biopsies have emerged as serious issues. To explore plasma biomarkers complementing the specificity of PSA test, we developed a unique proteomic technology QUEST-MS (Quick Enrichment of Small Targets for Mass Spectrometry). The QUEST-MS method based on 96-well formatted sequential reversed-phase chromatography allowing efficient enrichment of <20 kDa proteins quickly and reproducibly. Plasma from 24 healthy controls, 19 benign prostate hypertrophy patients, and 73 prostate cancer patients were purified with QUEST-MS and analyzed by LC/MS/MS. Among 153 057 nonredundant peptides, 189 peptides showed prostate cancer specific detection pattern, which included a neurotransmitter polypeptide neuropeptide-Y (NPY). We further validated the screening results by targeted multiple reaction monitoring technology using independent sample set (n = 110). The ROC curve analysis revealed that logistic regression-based combination of NPY, and PSA showed 81.5% sensitivity and 82.2% specificity for prostate cancer diagnosis. Thus QUEST-MS technology allowed comprehensive and high-throughput profiling of plasma polypeptides and had potential to effectively uncover very low abundant tumor-derived small molecules, such as neurotransmitters, peptide hormones, or cytokines.

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.

The mass spectrometry-based peptidomics approaches have proven its usefulness in several areas such as the discovery of physiologically active peptides or biomarker candidates derived from various biological fluids including blood and cerebrospinal fluid. However, to identify biomarkers that are reproducible and clinically applicable, development of a novel technology, which enables rapid, sensitive, and quantitative analysis using hundreds of clinical specimens, has been eagerly awaited. Here we report an integrative peptidomic approach for identification of lung cancer-specific serum peptide biomarkers. It is based on the one-step effective enrichment of peptidome fractions (molecular weight of 1,000-5,000) with size exclusion chromatography in combination with the precise label-free quantification analysis of nano-LC/MS/MS data set using Expressionist proteome server platform. We applied this method to 92 serum samples well-managed with our SOP (standard operating procedure) (30 healthy controls and 62 lung adenocarcinoma patients), and quantitatively assessed the detected 3,537 peptide signals. Among them, 118 peptides showed significantly altered serum levels between the control and lung cancer groups (p<0.01 and fold change >5.0). Subsequently we identified peptide sequences by MS/MS analysis and further assessed the reproducibility of Expressionist-based quantification results and their diagnostic powers by MRM-based relative-quantification analysis for 96 independently prepared serum samples and found that APOA4 273-283, FIBA 5-16, and LBN 306-313 should be clinically useful biomarkers for both early detection and tumor staging of lung cancer. Our peptidome profiling technology can provide simple, high-throughput, and reliable quantification of a large number of clinical samples, which is applicable for diverse peptidome-targeting biomarker discoveries using any types of biological specimens.

The Rice Annotation Project Database (RAP-DB) was created to provide the genome sequence assembly of the International Rice Genome Sequencing Project (IRGSP), manually curated annotation of the sequence, and other genomics information that could be useful for comprehensive understanding of the rice biology. Since the last publication of the RAP-DB, the IRGSP genome has been revised and reassembled. In addition, a large number of rice-expressed sequence tags have been released, and functional genomics resources have been produced worldwide. Thus, we have thoroughly updated our genome annotation by manual curation of all the functional descriptions of rice genes. The latest version of the RAP-DB contains a variety of annotation data as follows: clone positions, structures and functions of 31 439 genes validated by cDNAs, RNA genes detected by massively parallel signature sequencing (MPSS) technology and sequence similarity, flanking sequences of mutant lines, transposable elements, etc. Other annotation data such as Gnomon can be displayed along with those of RAP for comparison. We have also developed a new keyword search system to allow the user to access useful information. The RAP-DB is available at: http://rapdb.dna.affrc.go.jp/ and http://rapdb.lab.nig.ac.jp/.

Orthologs are genes in different species that evolved from a common ancestral gene by speciation. Currently, with the rapid growth of transcriptome data of various species, more reliable orthology information is prerequisite for further studies. However, detection of orthologs could be erroneous if pairwise distance-based methods, such as reciprocal BLAST searches, are utilized. Thus, as a sub-database of H-InvDB, an integrated database of annotated human genes (http://h-invitational.jp/), we constructed a fully curated database of evolutionary features of human genes, called 'Evola'. In the process of the ortholog detection, computational analysis based on conserved genome synteny and transcript sequence similarity was followed by manual curation by researchers examining phylogenetic trees. In total, 18 968 human genes have orthologs among 11 vertebrates (chimpanzee, mouse, cow, chicken, zebrafish, etc.), either computationally detected or manually curated orthologs. Evola provides amino acid sequence alignments and phylogenetic trees of orthologs and homologs. In 'd(N)/d(S) view', natural selection on genes can be analyzed between human and other species. In 'Locus maps', all transcript variants and their exon/intron structures can be compared among orthologous gene loci. We expect the Evola to serve as a comprehensive and reliable database to be utilized in comparative analyses for obtaining new knowledge about human genes. Evola is available at http://www.h-invitational.jp/evola/.

Here we report the new features and improvements in our latest release of the H-Invitational Database (H-InvDB; http://www.h-invitational.jp/), a comprehensive annotation resource for human genes and transcripts. H-InvDB, originally developed as an integrated database of the human transcriptome based on extensive annotation of large sets of full-length cDNA (FLcDNA) clones, now provides annotation for 120 558 human mRNAs extracted from the International Nucleotide Sequence Databases (INSD), in addition to 54 978 human FLcDNAs, in the latest release H-InvDB&#95;4.6. We mapped those human transcripts onto the human genome sequences (NCBI build 36.1) and determined 34 699 human gene clusters, which could define 34 057 (98.1%) protein-coding and 642 (1.9%) non-protein-coding loci; 858 (2.5%) transcribed loci overlapped with predicted pseudogenes. For all these transcripts and genes, we provide comprehensive annotation including gene structures, gene functions, alternative splicing variants, functional non-protein-coding RNAs, functional domains, predicted sub cellular localizations, metabolic pathways, predictions of protein 3D structure, mapping of SNPs and microsatellite repeat motifs, co-localization with orphan diseases, gene expression profiles, orthologous genes, protein-protein interactions (PPI) and annotation for gene families. The current H-InvDB annotation resources consist of two main views: Transcript view and Locus view and eight sub-databases: the DiseaseInfo Viewer, H-ANGEL, the Clustering Viewer, G-integra, the TOPO Viewer, Evola, the PPI view and the Gene family/group.

We present here the annotation of the complete genome of rice Oryza sativa L. ssp. japonica cultivar Nipponbare. All functional annotations for proteins and non-protein-coding RNA (npRNA) candidates were manually curated. Functions were identified or inferred in 19,969 (70%) of the proteins, and 131 possible npRNAs (including 58 antisense transcripts) were found. Almost 5000 annotated protein-coding genes were found to be disrupted in insertional mutant lines, which will accelerate future experimental validation of the annotations. The rice loci were determined by using cDNA sequences obtained from rice and other representative cereals. Our conservative estimate based on these loci and an extrapolation suggested that the gene number of rice is approximately 32,000, which is smaller than previous estimates. We conducted comparative analyses between rice and Arabidopsis thaliana and found that both genomes possessed several lineage-specific genes, which might account for the observed differences between these species, while they had similar sets of predicted functional domains among the protein sequences. A system to control translational efficiency seems to be conserved across large evolutionary distances. Moreover, the evolutionary process of protein-coding genes was examined. Our results suggest that natural selection may have played a role for duplicated genes in both species, so that duplication was suppressed or favored in a manner that depended on the function of a gene.