Discovery and Validation of Novel Protein Biomarkers in Ovarian Cancer Patient Urine

Mass spectrometry-based proteomic approaches for salivary protein biomarkers discovery and dental caries diagnosis: A critical review

Dental caries is a multifactorial chronic disease resulting from the intricate interplay among acid-generating bacteria, fermentable carbohydrates, and several host factors such as saliva. Saliva comprises several proteins which could be utilized as biomarkers for caries prevention, diagnosis, and prognosis. Mass spectrometry-based salivary proteomics approaches, owing to their sensitivity, provide the opportunity to investigate and unveil crucial cariogenic pathogen activity and host indicators and may demonstrate clinically relevant biomarkers to improve caries diagnosis and management. The present review outlines the published literature of human clinical proteomics investigations on caries and extensively elucidates frequently reported salivary proteins as biomarkers. This review also discusses important aspects while designing an experimental proteomics workflow. The protein-protein interactions and the clinical relevance of salivary proteins as biomarkers for caries, together with uninvestigated domains of the discipline are also discussed critically.

Proteomics Defines Plasma Biomarkers for the Early Diagnosis of Biliary Atresia

Early diagnosis of biliary atresia (BA) is crucial for improving the chances of survival and preserving the liver function of pediatric patients with BA. Herein, we performed proteomics analysis using data-independent acquisition (DIA) and parallel reaction monitoring (PRM) to explore potential biomarkers for the early diagnosis of BA compared to other non-BA jaundice cases. Consequently, we detected and validated differential protein expression in the plasma of patients with BA compared to the plasma of patients with intrahepatic cholestasis. Bioinformatics analysis revealed the enriched biological processes characteristic of BA by identifying the differential expression of specific proteins. Signaling pathway analysis revealed changes in the expression levels of proteins associated with an alteration in immunoglobulin levels, which is indicative of immune dysfunction in BA. The combination of polymeric immunoglobulin receptor expression and immunoglobulin lambda variable chain (IGL c2225_light_IGLV1-47_IGLJ2), as revealed via machine learning, provided a useful early diagnostic model for BA, with a sensitivity of 0.8, specificity of 1, accuracy of 0.89, and area under the curve value of 0.944. Thus, our study identified a possible effective plasma biomarker for the early diagnosis of BA and could help elucidate the underlying mechanisms of BA.

Paradigm shift in biomarker translation: a pipeline to generate clinical grade biomarker candidates from DIA-MS discovery

Clinical biomarker development has been stymied by inaccurate protein quantification from mass spectrometry (MS) discovery data and a prolonged validation process. To mitigate these issues, we created the Targeted Extraction Assessment of Quantification (TEAQ) software package. This innovative tool uses the discovery cohort analysis to select precursors, peptides, and proteins that adhere to established targeted assay criteria. TEAQ was applied to Data-Independent Acquisition MS data from plasma samples acquired on an Orbitrap™ Astral™ MS. Identified precursors were evaluated for linearity, specificity, repeatability, reproducibility, and intra-protein correlation from 11-point loading curves under three throughputs, to develop a resource for clinical-grade targeted assays. From a clinical cohort of individuals with inflammatory bowel disease (n=492), TEAQ successfully identified 1116 signature peptides for 327 quantifiable proteins from 1180 identified proteins. Embedding stringent selection criteria adaptable to targeted assay development into the analysis of discovery data will streamline the transition to validation and clinical studies.

Association of serum Ly6/PLAUR domain-containing protein 1 levels with skin sclerosis in systemic sclerosis

Systemic sclerosis (SSc) is a connective tissue disease characterized by aberrant immune activation, vascular injury, and fibrosis of the skin and internal organs. Ly6/PLAUR domain-containing protein 1 (LYPD1) was reported to be secreted and to have various physiological functions such as anti-angiogenic effects. Here we investigated serum LYPD1 levels in SSc patients and the association of serum LYPD1 levels with clinical features of SSc. Serum samples were obtained from 75 SSc patients and 22 healthy individuals as controls. We measured serum LYPD1 levels using enzyme-linked immunosorbent assay kits. Then, the relationship between serum LYPD1 levels and clinical features of SSc was analyzed. Serum LYPD1 levels in diffuse cutaneous SSc (dcSSc) patients were significantly higher than those in the limited cutaneous SSc (lcSSc) patients (median [25-75th percentiles], 1693.43 [1086.61-1917.57] vs. 904.55 [714.356-1285.56] pg/mL), while there were no significant differences in the serum LYPD1 levels between lcSSc and healthy controls (904.55 [714.356-1285.56] vs. 750.71 pg/mL [544.00-912.14]). Further analysis revealed that serum LYPD1 levels in patients correlated with skin thickness scores and serum interleukin (IL)-6 levels, which were known to reflect the extent of skin thickening in SSc. Moreover, serum LYPD1 levels showed a decrease with improvement in skin thickness after treatment, along with a decrease in serum IL-6 levels. These results indicate that LYPD1 might be a potential marker for monitoring skin sclerosis and evaluating the efficacy of skin fibrosis treatment in SSc patients.

Recent progress in mass spectrometry-based urinary proteomics

Serum or plasma is frequently utilized in biomedical research; however, its application is impeded by the requirement for invasive sample collection. The non-invasive nature of urine collection makes it an attractive alternative for disease characterization and biomarker discovery. Mass spectrometry-based protein profiling of urine has led to the discovery of several disease-associated biomarkers. Proteomic analysis of urine has not only been applied to disorders of the kidney and urinary bladder but also to conditions affecting distant organs because proteins excreted in the urine originate from multiple organs. This review provides a progress update on urinary proteomics carried out over the past decade. Studies summarized in this review have expanded the catalog of proteins detected in the urine in a variety of clinical conditions. The wide range of applications of urine analysis-from characterizing diseases to discovering predictive, diagnostic and prognostic markers-continues to drive investigations of the urinary proteome.

High-Grade Serous Ovarian Cancer-A Risk Factor Puzzle and Screening Fugitive

High-grade serous ovarian cancer (HGSOC) is the most lethal tumor of the female genital tract. Despite extensive studies and the identification of some precursor lesions like serous tubal intraepithelial cancer (STIC) or the deviated mutational status of the patients (BRCA germinal mutation), the pathophysiology of HGSOC and the existence of particular risk factors is still a puzzle. Moreover, a lack of screening programs results in delayed diagnosis, which is accompanied by a secondary chemo-resistance of the tumor and usually results in a high recurrence rate after the primary therapy. Therefore, there is an urgent need to identify the substantial risk factors for both predisposed and low-risk populations of women, as well as to create an economically and clinically justified screening program. This paper reviews the classic and novel risk factors for HGSOC and methods of diagnosis and prediction, including serum biomarkers, the liquid biopsy of circulating tumor cells or circulating tumor DNA, epigenetic markers, exosomes, and genomic and proteomic biomarkers. The novel future complex approach to ovarian cancer diagnosis should be devised based on these findings, and the general outcome of such an approach is proposed and discussed in the paper.

Mass Spectrometry-based Proteomics of Epithelial Ovarian Cancers: a Clinical Perspective

Increasing proteomic studies focused on epithelial ovarian cancer (EOC) have attempted to identify early disease biomarkers, establish molecular stratification, and discover novel druggable targets. Here we review these recent studies from a clinical perspective. Multiple blood proteins have been used clinically as diagnostic markers. The ROMA test integrates CA125 and HE4, while the OVA1 and OVA2 tests analyze multiple proteins identified by proteomics. Targeted proteomics has been widely used to identify and validate potential diagnostic biomarkers in EOCs, but none has yet been approved for clinical adoption. Discovery proteomic characterization of bulk EOC tissue specimens has uncovered a large number of dysregulated proteins, proposed new stratification schemes, and revealed novel targets of therapeutic potential. A major hurdle facing clinical translation of these stratification schemes based on bulk proteomic profiling is intra-tumor heterogeneity, namely that single tumor specimens may harbor molecular features of multiple subtypes. We reviewed over 2500 interventional clinical trials of ovarian cancers since 1990, and cataloged 22 types of interventions adopted in these trials. Among 1418 clinical trials which have been completed or are not recruiting new patients, about 50% investigated chemotherapies. Thirty-seven clinical trials are at phase 3 or 4, of which 12 focus on PARP, 10 on VEGFR, 9 on conventional anti-cancer agents, and the remaining on sex hormones, MEK1/2, PD-L1, ERBB, and FRα. Although none of the foregoing therapeutic targets were discovered by proteomics, newer targets discovered by proteomics, including HSP90 and cancer/testis antigens, are being tested also in clinical trials. To accelerate the translation of proteomic findings to clinical practice, future studies need to be designed and executed to the stringent standards of practice-changing clinical trials. We anticipate that the rapidly evolving technology of spatial and single-cell proteomics will deconvolute the intra-tumor heterogeneity of EOCs, further facilitating their precise stratification and superior treatment outcomes.

Discovery of therapeutic targets of quercetin for endometrial carcinoma patients infected with COVID-19 through network pharmacology

Purpose

Aimed to identify the anti-uterine corpus endometrial carcinoma (UCEC) function and characterize the mechanism of quercetin in the treatment of patients infected with COVID-19 via integrated in silico analysis.

Methods

The Cancer Genome Atlas and Genotype Tissue Expression databases were applied to obtain differentially expressed genes of UCEC and non-tumor tissue. Several in silico methods such as network pharmacology, functional enrichment analysis, Cox regression analyses, somatic mutation analysis, immune infiltration and molecular docking were used to investigate and analysis the biological targets, functions and mechanisms of anti-UCEC/COVID-19 of quercetin. Multiple methods such as CCK8 assay, Transwell assay and western blotting were performed to test proliferation, migration, and protein level of UCEC (HEC-1 and Ishikawa) cells.

Results

Functional analysis disclosed that quercetin against UCEC/COVID-19 mainly by ‘biological regulation’, ‘response to stimulus’, and ‘regulation of cellular process’. Then, regression analyses indicated that 9 prognostic genes (including ANPEP, OAS1, SCGB1A1, HLA‐A, NPPB, FGB, CCL2, TLR4, and SERPINE1) might play important roles in quercetin for treating UCEC/COVID-19. Molecular docking analysis revealed that the protein products of 9 prognostic genes were the important anti-UCEC/COVID-19 biological targets of quercetin. Meanwhile, the proliferation and migration of UCEC cells were inhibited by quercetin. Moreover, after treatment with quercetin, the protein level of ubiquitination-related gene ISG15 was decreased in UCEC cells in vitro.

Conclusions

Taken together, this study provides new treatment option for UCEC patients infected with COVID-19. Quercetin may work by reducing the expression of ISG15 and participating in ubiquitination-related pathways.

Urine CA125 and HE4 for the Detection of Ovarian Cancer in Symptomatic Women

The symptoms of ovarian cancer are vague, and current risk assessment tools such as serum CA125 and transvaginal ultrasound scan fail to reliably detect the disease early. This study aimed to evaluate urine CA125 and HE4 as diagnostic biomarkers for ovarian cancer in symptomatic women. Paired urine and serum samples were collected from women undergoing treatment for ovarian cancer (cases) or investigations for gynaecological symptoms (controls). Biomarkers were measured using an automated chemiluminescent enzyme immunoassay analyser. Standard diagnostic accuracy metrics were calculated. In total, 114 women were included, of whom 17 (15%) were diagnosed with an epithelial ovarian malignancy. Levels of urine CA125 and HE4 were significantly elevated in women with ovarian cancer compared to controls [CA125: 8.5 U/mL (IQR: 2.4-19.5) vs. 2.3 U/mL (IQR: 1.0-6.4), p = 0.01. HE4: 12.0 nmol/L (IQR: 10.3-23.1) vs. 6.7 nmol/L (IQR: 3.4-13.6), p = 0.006]. Urine CA125 and HE4 detected ovarian cancer with an AUC of 0.69 (95% CI: 0.55-0.82) and 0.71 (95% CI: 0.69-0.82), respectively (p = 0.73). A combination of urine CA125 and HE4 at optimal thresholds had a sensitivity of 82.4% (95% CI: 56.6-96.2) and was comparable to the sensitivity of serum CA125 [88.2% (95% CI: 63.6-98.5)]. Larger studies are required to confirm our findings, standardise urine collection, and evaluate optimal biomarker thresholds. Urine CA125 and HE4 may be useful non-invasive diagnostic tools to triage women for formal ovarian cancer investigations.

Urine CA125 and HE4 for the Triage of Symptomatic Women with Suspected Endometrial Cancer

A simple, noninvasive and accurate detection tool that can triage women with suspected endometrial cancer for definitive testing will transform patient care. The aim of this study was to evaluate urine CA125 and HE4 levels for the detection of endometrial cancer in symptomatic women. This was a cross-sectional diagnostic accuracy study of 153 symptomatic women who underwent urgent diagnostic investigations for suspected endometrial cancer at a large gynecological cancer center. Urine samples were collected prior to routine clinical procedures. Urine CA125 and HE4 levels were determined using automated chemiluminescent enzyme immunoassays. Univariate and multivariable receiver operating characteristic (ROC) curve analyses were performed. Urine CA125 and HE4 were discovered to be significantly elevated in women with endometrial cancer, compared to controls (p < 0.001 and p = 0.01, respectively). Urine CA125 and HE4 detected endometrial cancer with an area under the ROC curve (AUC) of 0.89 (0.81, 0.98) and 0.69 (0.55, 0.83), respectively. CA125 exhibited good discriminatory potential for Type I and early-stage tumors (AUC 0.93 and 0.90, respectively). A diagnostic model that combined urine CA125 and transvaginal ultrasound-measured endometrial thickness predicted endometrial cancer with an AUC of 0.96 (0.91, 1.00). Urine CA125 displays potential as a diagnostic tool for symptomatic women with suspected endometrial cancer. When combined with transvaginal ultrasound-measured endometrial thickness, this patient-friendly, urine-based test could help triage women for invasive diagnostics or safe reassurance, reducing costs and improving patient experience.

Label-Free Quantification (LFQ) of Fecal Proteins for Potential Pregnancy Detection in Polar Bears

Reliable pregnancy diagnostics would be beneficial for monitoring polar bear (Ursus maritimus) populations both in situ and ex situ, but currently there is no method of non-invasive pregnancy detection in this species. Recent reports in several carnivore species described the identification of fecal proteins that may serve as pregnancy biomarkers; however, repeatability has been limited. The objective of the current analysis was to utilize an unbiased, antibody-free, label-free method for the identification and quantification of fecal proteins to determine if differences associated with pregnancy are detectable in polar bears. Protein was extracted from fecal samples (n = 48) obtained from parturient (n = 6) and non-parturient (n = 6) profiles each at four timepoints: pre-breeding season, embryonic diapause, early placental pregnancy, and mid-placental pregnancy. Protein was prepared and analyzed on the Thermo Orbitrap Eclipse nanoLC-MS/MS system. A total of 312 proteins was identified and quantified; however, coefficients of variation (CV) were high for both abundance ratio variability (384.8 ± 61.0% SEM) and within group variability (86.8 ± 1.5%). Results of this study suggest that the inconsistencies in specific protein concentrations revealed previously by antibody-based assays may not be due to that methodology’s limitations, but rather, are reflective of true variation that exists among samples.

The Role of Mesothelin Expression in Serous Ovarian Carcinoma: Impacts on Diagnosis, Prognosis, and Therapeutic Targets

Mesothelin (MSLN) is a protein expressed in the mesothelial cell lining of the pleura, peritoneum, and pericardium; its biological functions in normal cells are still unknown. Experimental studies using knockout mice have suggested that this molecule does not play an important role in development and reproduction. In contrast, it has been observed that this molecule is produced in abnormal amounts in several malignant neoplasms, such as mesotheliomas and pancreatic adenocarcinomas. Many molecular studies have also demonstrated that mesothelin is overexpressed in HSOCs. Here, we discuss the current knowledge of mesothelin and focus on its role in clinical and pathological diagnoses, as well as its impact on the prognosis of HSOC. Moreover, regarding the binding of MSLN to the ovarian cancer antigen CA125, which has been demonstrated in many studies, we also report on signal transduction pathways that may play an important role in the spread and neoplastic progression of this lethal neoplasm. Given that mesothelin is overexpressed in many solid tumours and has antigenic properties, this molecule could be considered an antigenic target for the treatment of many malignancies. Consequently, we also review the literature to report on mesothelin-targeting therapies for HSOC that have been recently investigated in many clinical studies.

Cancer Detection Using an Artificial Secretable MicroRNA Found in Blood and Urine

Biomarkers can potentially help in the detection and prognosis of diseases such as cancer, its recurrence, predicting response to therapy, and monitoring of response during and/or after treatment. Endogenous tumor blood biomarkers suffer from low concentrations that are not distinguishable from background noise and, if identified, the localization of the biomarker production site is not known. The use of exogenously introduced or artificial biomarkers can eliminate these issues. In this study, we show that cancer cells can be made to produce an artificial secreted microRNA (Sec-miR) that can be detected in media from cells in culture, and from both blood and urine in living mice. In culture, we show that chaining a number of Sec-miR sequences in a plasmid and transfecting cells with the plasmids could increase Sec-miR secretion as the number of sequences increases. Tumor induction in mice with a stably transfected HeLa cell line shows the presence and significant increase in the Sec-miR with time and tumor growth in plasma (p < 0.001, R2 = 0.5542). The relative half-life of the Sec-miR was seen to be 1.2 h in the plasma of living mice and was seen to appear in urine within 12 h. The transgene for the Sec-miR within a minicircle was introduced via the tail-vein into subcutaneous tumor-bearing mice. As the tumor growth increased with time, further in vivo transfection of the Sec-miR minicircles showed an increase in Sec-miR in both plasma and urine (R2 = 0.4546). This study demonstrated that an exogenous Sec-miR biomarker would allow for early tumor detection using in vitro diagnostics techniques.

OUP accepted manuscript

Currently, the only definitive method for diagnosing ovarian cancer involves histological examination of tissue obtained at time of surgery or by invasive biopsy. Blood has traditionally been the biofluid of choice in ovarian cancer biomarker discovery; however, there has been a growing interest in exploring urinary biomarkers, particularly as it is non-invasive. In this systematic review, we present the diagnostic accuracy of urinary biomarker candidates for the detection of ovarian cancer. A comprehensive literature search was performed using the MEDLINE/PubMed and EMBASE, up to 1 April 2021. All included studies reported the diagnostic accuracy using sensitivity and/or specificity and/or receiver operating characteristics (ROC) curve. Risk of bias and applicability of included studies were assessed using the QUADAS-2 tool. Twenty-seven studies were included in the narrative synthesis. Protein/peptide biomarkers were most commonly described (n = 18), with seven studies reporting composite scores of multiple protein-based targets. The most frequently described urinary protein biomarker was HE4 (n = 5), with three studies reporting a sensitivity and specificity > 80%. Epigenetic (n = 1) and metabolomic/organic compound biomarkers (n = 8) were less commonly described. Overall, six studies achieved a sensitivity and specificity of >90% and/or an AUC > 0.9. Evaluation of urinary biomarkers for the detection of ovarian cancer is a dynamic and growing field. Currently, the most promising biomarkers are those that interrogate metabolomic pathways and organic compounds, or quantify multiple proteins. Such biomarkers require external validation in large, prospective observational studies before they can be implemented into clinical practice.

Systematic proteomics analysis of lysine acetylation reveals critical features of placental proteins in pregnant women with preeclampsia

Preeclampsia (PE) is a dangerous hypertensive disorder that occurs during pregnancy. The specific aetiology and pathogenesis of PE have yet to be clarified. To better reveal the specific pathogenesis of PE, we characterized the proteome and acetyl proteome (acetylome) profile of placental tissue from PE and normal-term pregnancy by label-free quantification proteomics technology and PRM analysis. In this research, 373 differentially expressed proteins (DEPs) were identified by proteome analysis. Functional enrichment analysis revealed significant enrichment of DEPs related to angiogenesis and the immune system. COL12A1, C4BPA and F13A1 may be potential biomarkers for PE diagnosis and new therapeutic targets. Additionally, 700 Kac sites were identified on 585 differentially acetylated proteins (DAPs) by acetylome analyses. These DAPs may participate in the occurrence and development of PE by affecting the complement and coagulation cascades pathway, which may have important implications for better understand the pathogenesis of PE. In conclusion, this study systematically analysed the reveals critical features of placental proteins in pregnant women with PE, providing a resource for exploring the contribution of lysine acetylation modification to PE.

lncRNA cytoskeleton regulator reduces non‑small cell lung cancer radiosensitivity by downregulating miRNA‑206 and activating prothymosin α

The present study aimed to explore the role of the long noncoding RNA cytoskeleton regulator (CYTOR) in non-small cell lung cancer (NSCLC) radiosensitivity by manipulating the microRNA (miR)-206/prothymosin α (PTMA) axis. First, 58 pairs of NSCLC and paracancerous tissues, normal human lung epithelial cells and NSCLC cells were collected to analyze CYTOR expression and the relation- ship between CYTOR and NSCLC prognosis. Subsequently, CYTOR expression in radioresistant cells was assessed. Radioresistant cells with low CYTOR expression and parental cells with high CYTOR expression were established. Functional assays were then performed to assess changes in cell radiosensitivity after irradiation treatment. Subsequently, the downstream mechanism of CYTOR was explored. The binding interactions between CYTOR and miR-206 and between miR-206 and PTMA were predicted and certified. Xenograft transplantation was applied to confirm the role of CYTOR in the radiosensitivity of NSCLC. CYTOR was overexpressed in NSCLC and was associated with poor prognosis. CYTOR was further upregulated in NSCLC cells with radioresistance. CYTOR knockdown enhanced the radiosensitivity of NSCLC cells, while overexpression of CYTOR led to the opposite result. Mechanistically, CYTOR specifically bound to miR-206 and silencing CYTOR promoted miR-206 to enhance the radiosensitivity of NSCLC cells. PTMA is a target of miR-206 and silencing CYTOR inhibited PTMA expression via miR-206, thus promoting radiosensitivity of NSCLC cells. CYTOR knockdown also enhanced NSCLC cell radiosensitivity in vivo. CYTOR was highly expressed in NSCLC, while silencing CYTOR potentiated NSCLC cell radiosensitivity by upregulating miR-206 and suppressing PTMA. The present study preliminarily revealed the role of CYTOR in radiotherapy sensitivity of NSCLC and provided a novel potential target for the clinical treatment of NSCLC.

Identification of Protein Changes in the Urine of Hypothyroid Patients Treated with Thyroxine Using Proteomics Approach

The thyroid gland and thyroid hormones control a multitude of homeostatic functions including maintenance of fluid and electrolyte balance and normal functioning of the kidneys. Thyroid dysfunction alters the sytemic hemodynamic and metabolic balance, thereby affecting the kidney. In this study, we aimed to identify and characterize the urinary proteome of the patients with hypothyroidism. An untargeted proteomic approach with network analysis was used to identify changes in total urinary proteome in patients with newly diagnosed overt hypothyroidism. Urine samples were collected from nine age-matched patients' before and after l-thyroxine treatment. Differences in the abundance of urinary proteins between hypothyroid and euthyroid states were determined using a two-dimensional difference in gel electrophoresis (2D-DIGE) coupled to matrix-assisted laser desorption and ionization time-of-flight (MALDI TOF) mass spectrometry. Alterations in the abundance of urinary proteins, analyzed by Progenesis software, revealed statistically significant differential abundance in a total of 49 spots corresponding to 42 proteins, 28 up and 14 down (≥1.5-fold change, analysis of variance (ANOVA), p ≤ 0.05). The proteins identified in the study are known to regulate processes related to transport, acute phase response, oxidative stress, generation of reactive oxygen species, cellular proliferation, and endocytosis. Bioinformatic analysis using Ingenuity Pathway Analysis (IPA) identified dysregulation of pathways related to amino acid metabolism, molecular transport, and small-molecule biochemistry and involved the MAPK kinase, vascular endothelial growth factor (VEGF), PI3 kinase/Akt, protein kinase C (PKC), signaling pathways. The identified proteins were involved in the regulation of thyroglobulin (Tg) and thyrotropin (TSH) metabolism. Alterations in their levels indicate the presence of a compensatory mechanism aimed at increasing the regulation of Tg in the hypothyroid state.

Identification of novel protein-coding sequences in Eucalyptus grandis plants by high-resolution mass spectrometry

Eucalyptus species are widely used in the forestry industry, and a significant increase in the number of sequences available in database repositories has been observed for these species. In proteomics, a protein is identified by correlating the theoretical fragmentation spectrum derived from genomic/transcriptomic data against the experimental fragmentation mass spectrum acquired from large-scale analysis of protein mixtures. Proteogenomics is an alternative approach that can identify novel proteins encoded by regions previously considered as non-coding. This study aimed to confidently identify and confirm the existence of previously unknown protein-coding sequences in the Eucalyptus grandis genome. To this end, we used a modified spectral correlation strategy and a dedicated de novo peptide sequencing pipeline. Upon the strategy used here, we confidently identified 41 novel peptide forms and six peptides containing at least one single amino acid substitution. The most representative genomic class of novel peptides was identified as originating from alternative reading frames. In contrast, no clear single amino acid substitution pattern was identified. Validation of the identifications was carried out using a parallel reaction monitoring approach that provided further mass spectrometry support for the existence of the novel peptide sequences. Data are available via ProteomeXchange with identifier PXD022110.

Review: Detection and quantification of proteins in human urine

Extensive medical research showed that patients, with high protein concentration in urine, have various kinds of kidney diseases, referred to as proteinuria. Urinary protein biomarkers are useful for diagnosis of many health conditions – kidney and cardio vascular diseases, cancers, diabetes, infections. This review focuses on the instrumental quantification (electrophoresis, chromatography, immunoassays, mass spectrometry, fluorescence spectroscopy, the infrared spectroscopy, and Raman spectroscopy) of proteins (the most of all albumin) in human urine matrix. Different techniques provide unique information on what constituents of the urine are. Due to complex nature of urine, a separation step by electrophoresis or chromatography are often used for proteomics study of urine. Mass spectrometry is a powerful tool for the discovery and the analysis of biomarkers in urine, however, costs of the analysis are high, especially for quantitative analysis. Immunoassays, which often come with fluorescence detection, are major qualitative and quantitative tools in clinical analysis. While Infrared and Raman spectroscopies do not give extensive information about urine, they could become important tools for the routine clinical diagnostics of kidney problems, due to rapidness and low-cost. Thus, it is important to review all the applicable techniques and methods related to urine analysis. In this review, a brief overview of each technique's principle is introduced. Where applicable, research papers about protein determination in urine are summarized with the main figures of merits, such as the limit of detection, the detectable range, recovery and accuracy, when available.

•

Urinary protein biomarkers are useful for diagnosis of many conditions: kidney and cardio vascular diseases, cancers.

•

Liquid chromatography – mass spectroscopy is a powerful tool for urine proteomics, but used mostly in science.

•

Immunoassays are widely used in both clinical and bio-analytical laboratories.

•

IR and Raman spectroscopies are promising tools for diagnostics of urine due to low-cost and rapidness.

Insights Into the Role of Mesothelin as a Diagnostic and Therapeutic Target in Ovarian Carcinoma

Ovarian malignancies remain the leading cause of death in female gynecological tumors. More than 70% of patients are diagnosed with advanced stage with extensive metastatic lesions in abdominal cavity due to lack of symptoms in early stage and sensitive diagnostic approaches. Mesothelin (MSLN), a glycosylphosphatidylinositol-anchored membrane glycoprotein, participates in cell adhesion, tumor progression, metastasis, and drug resistance. Despite this, the mechanism is still poorly understood. The differential expression pattern of MSLN in normal and cancer tissues makes it a promising target for diagnosis and therapeutic applications. Several clinical trials are underway to evaluate the safety and efficacy of MSLN-targeted drugs, including CAR T cells, immunotoxin, antibody-drug conjugates, and vaccine. This review is aimed to briefly discuss the characteristics of MSLN and the latest progress in MSLN targeting therapies.

Human follicular fluid proteome reveals association between overweight status and oocyte maturation abnormality

Background

Human follicular fluid (HFF), which is composed by essential proteins required for the follicle development, provides an important microenvironment for oocyte maturation. Recently, overweight status has been considered as a detrimental impact factor on oocyte maturation, but whether HFF proteome could provide protein markers for assessing overweight-based oocyte maturation deficiency is still unknown.

Methods

To reveal the HFF-based molecular characteristics associated with abnormal oocyte maturation, an iTRAQ-based comparative proteomic analysis was performed to investigate different HFF protein expression profiles from normal weight women and overweight status women.

Results

Two hundred HFF proteins were quantified in our data, of which 43% have not been overlapped by two previous publications. Compared with the HFF proteins of normal weight women, 22 up-regulated HFF proteins and 21 down-regulated HFF proteins were found in the overweight status women. PANTHER database showed these altered HFF proteins participated in development, metabolism, immunity, and coagulation, and STRING database demonstrated their complicated interaction networks. The confidence of proteomic outcome was verified by Western blot analysis of WAP four-disulfide core domain protein 2 (WFDC2), lactotransferrin (LTF), prostate-specific antigen (KLK3), fibronectin (FN1), and glyceraldehyde 3-phosphate dehydrogenase (GAPDH). Further, ELISA assay indicated WFDC2 might be a potentially useful candidate HFF marker for the diagnosis of oocyte maturation arrest caused by overweight status.

Conclusions

Our work provided a new complementary high-confidence HFF dataset involved in oocyte maturation, and these altered HFF proteins might have clinical relevance and diagnostic and prognostic value for abnormal oocyte maturation in overweight status women.

Update on urine as a biomarker in cancer: a necessary review of an old story

Introduction: Cancer causes thousands of deaths worldwide each year. Therefore, monitoring of health status and the early diagnosis of cancer using noninvasive assays, such as the analysis of molecular biomarkers in urine, is essential. However, effective biomarkers for early diagnosis of cancer have not been established in many types of cancer.Areas covered: In this review, we discuss recent findings with regard to the use of urine composition as a biomarker in eleven types of cancer. We also highlight the use of urine biomarkers for improving early diagnosis.Expert opinion: Urinary biomarkers have been applied for clinical application of early diagnosis. The main limitation is a lack of integrated approaches for identification of new biomarkers in most cancer. The utilization of urinary biomarker detection will be promoted by improved detection methods and new data from different types of cancers. With the development of precision medicine, urinary biomarkers will play an increasingly important clinical role. Future early diagnosis would benefit from changes in the utilization of urinary biomarkers.

Proteomic Profiles and Biological Processes of Relapsed vs. Non-Relapsed Pediatric Hodgkin Lymphoma

The identification of circulating proteins associated with relapse in pediatric Hodgkin lymphoma (HL) may help develop predictive biomarkers. We previously identified a set of predictive biomarkers by difference gel electrophoresis. Here we used label-free quantitative liquid chromatography-mass spectrometry (LC-MS/MS) on plasma collected at diagnosis from 12 children (age 12–16 years) with nodular sclerosis HL, including six in whom the disease relapsed within 5 years of treatment in the LH2004 trial. Plasma proteins were pooled in groups of three, separately for non-relapsing and relapsing HL, and differentially abundant proteins between the two disease states were identified by LC-MS/MS in an explorative and validation design. Proteins with a fold change in abundance >1.2 or ≤0.8 were considered “differentially abundant”. LC-MS/MS identified 60 and 32 proteins that were more abundant in non-relapsing and relapsing HL plasma, respectively, in the explorative phase; these numbers were 39 and 34 in the validation phase. In both analyses, 11 proteins were more abundant in non-relapsing HL (e.g., angiotensinogen, serum paraoxonase/arylesterase 1, transthyretin), including two previously identified by difference gel electrophoresis (antithrombin III and α-1-antitrypsin); seven proteins were more abundant in relapsing HL (e.g., fibronectin and thrombospondin-1), including two previously identified proteins (fibrinogen β and γ chains). The differentially abundant proteins participated in numerous biological processes, which were manually grouped into 10 biological classes and 11 biological regulatory subclasses. The biological class Lipid metabolism, and its regulatory subclass, included angiotensinogen and serum paraoxonase/arylesterase 1 (more abundant in non-relapsing HL). The biological classes Immune system and Cell and extracellular matrix architecture included fibronectin and thrombospondin-1 (more abundant in relapsing HL). These findings deepen our understanding of the molecular scenario underlying responses to therapy and provide new evidence about these proteins as possible biomarkers of relapse in pediatric HL.

Long Non-Coding RNA HULC Promotes the Development of Breast Cancer Through Regulating LYPD1 Expression by Sponging miR-6754-5p

Introduction

Long non-coding RNAs (lncRNAs) were found to regulate many biological processes including cancer development, immunology and other diseases. LncRNA HULC was found to be oncogenes in many cancer progression. However, the role of HULC in the regulation of breast cancer remains unclear.

Methods

The expression of HULC and miR-6754-5p was examined by RT-PCR. Through knockdown of HULC, we found that the proliferation abilities coupled with migration and invasion abilities were significantly decreased. And also, we verified that overexpression of miR-6754-5p significantly decreased the proliferation ability of breast cancer cells.

Results

In this study, we found that lncRNA HULC was overexpressed in breast cancer tissues and cell lines compared to normal healthy breast tissues and normal breast cell line. Moreover, the high expression of HULC was associated with metastasis and malignancy of breast cancers. Mechanically, we found that HULC can bind to miR-6754-5p directly through complementary base pairing. Furthermore, we found that HULC regulates the expression of LYPD1 through sponging miR-6754-5p. Moreover, overexpression of LYPD1 can rescue the migration and invasion abilities of breast cancer cells decreased by knockdown of HULC or overexpression of miR-6754-5p.

Conclusion

Our study showed the role of HULC in promoting breast cancer development and explained the detailed molecular mechanisms.

Elevated urine histone 4 levels in women with ovarian endometriosis revealed by discovery and parallel reaction monitoring proteomics

Endometriosis is a common gynecologic disorder and due to a lack of non-invasive detection methods, it can take up to 12 years before an affected woman obtains a diagnosis and receives appropriate treatment. Therefore, the identification of a specific biomarker that can be detected quickly and non-invasively is urgently needed. In this study, the urine proteome, a potentially rich source of biomarkers, is examined in patients with or without endometriosis in an attempt to identify novel protein biomarkers that can be used to diagnose endometriosis. This study is the first to combine tandem mass tags and parallel reaction monitoring approaches to aid in identifying and validating urine biomarkers for endometriosis. The findings presented herein support previous conclusions that endometriosis is a chronic inflammatory disease. Additionally, Histone 4 was identified as a potential biomarker and/or therapeutic target for endometriosis. At a cutoff of 14.2, the area under the curve for H4 was 0.848, with a sensitivity of 70% and specificity of 80%. Moreover, to our knowledge, this is the first study to observe an elevated histone level in body fluids obtained from endometriosis patients. While this study provides a good foundation, further studies are required to further validate the results presented. SIGNIFICANCE: Endometriosis is a common gynecologic disorder and due to a lack of non-invasive detection methods, it can take up to 12 years before an affected woman obtains a diagnosis and receives appropriate treatment. Therefore, the identification of a specific biomarker that can be detected quickly and non-invasively is urgently needed. We believe our results have an important impact on detection and treatment of endometriosis. Firstly, this study is the first to combine tandem mass tags and parallel reaction monitoring approaches to aid in identifying and validating urine biomarkers for endometriosis, which has established the methodology required for subsequent studies. Secondly, this is also the first study to observe an elevated histone level in body fluids obtained from endometriosis patients. Compared with other urine biomarkers reported in literature, histone 4 has a potential to serve as a biomarker of endometriosis and a therapeutic target. Thirdly, our study supports previous conclusions that endometriosis is a chronic inflammatory disease. These findings can warrant further investigation of the pathophysiology of endometriosis.

Intrasurgical Protein Layer on Titanium Arthroplasty Explants: From the Big Twelve to the Implant Proteome

PURPOSE

Aseptic loosening in total joint replacement due to insufficient osteointegration is an unsolved problem in orthopaedics. The purpose of the study is to obtain a picture of the initial protein adsorption layer on femoral endoprosthetic surfaces as the key to the initiation of osseointegration.

EXPERIMENTAL DESIGN

The paper describes the first study of femoral stem explants from patients for proteome analysis of the primary protein layer. After 2 min in situ, the stems are explanted and frozen in liquid nitrogen. Proteins are eluted under reducing conditions and analyzed by LC-MS/MS.

RESULTS

After exclusion of proteins identified by a single peptide, the implant proteome is found to consist of 2802 unique proteins. Of these, 77% are of intracellular origin, 9% are derived from the plasma proteome, 8% from the bone proteome, and four proteins with highest specificity score could be assigned to the bone marrow proteome (transcriptome). The most abundant protein in the adsorbed total protein layer is hemoglobin (8-11%) followed by serum albumin (3.6-6%).

CONCLUSIONS

A detailed knowledge of the initial protein film deposited onto the implants, as demonstrated here for the first time, may help to understand and predict the response of the osseous microenvironment to implant surfaces.

Protein Biomarker Discovery in Non-depleted Serum by Spectral Library-Based Data-Independent Acquisition Mass Spectrometry

In discovery proteomics experiments, tandem mass spectrometry and data-dependent acquisition (DDA) are classically used to identify and quantify peptides and proteins through database searching. This strategy suffers from known limitations such as under-sampling and lack of reproducibility of precursor ion selection in complex proteomics samples, leading to somewhat inconsistent analytical results across large datasets. Data-independent acquisition (DIA) based on fragmentation of all the precursors detected in predetermined isolation windows can potentially overcome this limitation. DIA promises reproducible peptide and protein quantification with deeper proteome coverage and fewer missing values than DDA strategies. This approach is particularly attractive in the field of clinical biomarker discovery, where large numbers of samples must be analyzed. Here, we describe a DIA workflow for non-depleted serum analysis including a straightforward approach through which to construct a dedicated spectral library, and indications on how to optimize chromatographic and mass spectrometry analytical methods to produce high-quality DIA data and results.

Urinary proteomic biomarkers in oncology: ready for implementation?

Introduction: Biomarkers are expected to improve the management of cancer patients by enabling early detection and prediction of therapeutic response. Proteins reflect a molecular phenotype, have high potential as biomarkers, and also are key targets for intervention. Given the ease of collection and proximity to certain tumors, the urinary proteome is a rich source of biomarkers and several proteins have been already implemented. Areas covered: We examined the literature on urine proteins and proteome analysis in oncology from reports published during the last 5 years to generate an overview on the status of urine protein and peptide biomarkers, with emphasis on their actual clinical value. Expert commentary: A few studies report on biomarkers that are ready to be implemented in patient management, among others in bladder cancer and cholangiocarcinoma. These reports are based on multi-marker approaches. A high number of biomarkers, though, has been described in studies with low statistical power. In fact, several of them have been consistently reported across different studies. The latter should be the focus of attention and be tested in properly designed confirmatory and ultimately, prospective investigations. It is expected that multi-marker classifiers for a specific context-of-use, will be the preferred path toward clinical implementation.

Ultrafiltration and size exclusion chromatography combined with asymmetrical-flow field-flow fractionation for the isolation and characterisation of extracellular vesicles from urine

Extracellular vesicles (EVs) have a great potential in clinical applications. However, their isolation from different bodily fluids and their characterisation are currently not optimal or standardised. Here, we report the results of examining the performance of ultrafiltration combined with size exclusion chromatography (UF-SEC) to isolate EVs from urine. The results reveal that UF-SEC is an efficient method and provides high purity. Furthermore, we introduce asymmetrical-flow field-flow fractionation coupled with a UV detector and multi-angle light-scattering detector (AF4/UV-MALS) as a characterisation method and compare it with current methods. We demonstrate that AF4/UV-MALS is a straightforward and reproducible method for determining size, amount and purity of isolated urinary EVs.

Beyond the Biomarker: Understanding the Diverse Roles of Human Epididymis Protein 4 in the Pathogenesis of Epithelial Ovarian Cancer

Human epididymis protein 4 (HE4) is an important clinical biomarker used for the detection of epithelial ovarian cancer (EOC). While much is known about the predictive power of HE4 clinically, less has been reported regarding its molecular role in the progression of EOC. A deeper understanding of HE4’s mechanistic functions may help contribute to the development of novel targeted therapies. Thus far, it has been difficult to recommend HE4 as a therapeutic target owing to the fact that its role in the progression of EOC has not been extensively evaluated. This review summarizes what is collectively known about HE4 signaling and how it functions to promote tumorigenesis, chemoresistance, and metastasis in EOC, with the goal of providing valuable insights that will have the potential to aide in the development of new HE4-targeted therapies.