Serum Proteomic Profiling in Patients with Bladder Cancer

Liquid biopsy in urothelial carcinoma: Detection techniques and clinical applications

The types of urothelial carcinoma (UC) include urothelial bladder cancer and upper tract urothelial carcinoma. Current diagnostic techniques cannot meet the needs of patients. Liquid biopsy is an accurate method of determining the molecular profile of UC and is a cutting-edge and popular technique that is expected to complement existing detection techniques and benefit patients with UC. Circulating tumor cells, cell-free DNA, cell-free RNA, extracellular vesicles, proteins, and metabolites can be found in the blood, urine, or other bodily fluids and are examined during liquid biopsies. This article focuses on the components of liquid biopsies and their clinical applications in UC. Liquid biopsies have tremendous potential in multiple aspects of precision oncology, from early diagnosis and treatment monitoring to predicting prognoses. They may therefore play an important role in the management of UC and precision medicine.

Blood-based liquid biopsy: insights into early detection, prediction, and treatment monitoring of bladder cancer

Bladder cancer (BC) is a clinical challenge worldwide with late clinical presentation, poor prognosis, and low survival rates. Traditional cystoscopy and tissue biopsy are routine methods for the diagnosis, prognosis, and monitoring of BC. However, due to the heterogeneity and limitations of tumors, such as aggressiveness, high cost, and limited applicability of longitudinal surveillance, the identification of tumor markers has attracted significant attention in BC. Over the past decade, liquid biopsies (e.g., blood) have proven to be highly efficient methods for the discovery of BC biomarkers. This noninvasive sampling method is used to analyze unique tumor components released into the peripheral circulation and allows serial sampling and longitudinal monitoring of tumor progression. Several liquid biopsy biomarkers are being extensively studied and have shown promising results in clinical applications of BC, including early detection, detection of microscopic residual disease, prediction of recurrence, and response to therapy. Therefore, in this review, we aim to provide an update on various novel blood-based liquid biopsy markers and review the advantages and current limitations of liquid biopsy in BC therapy. The role of blood-based circulating tumor cells, circulating tumor DNA, cell-free RNA, exosomes, metabolomics, and proteomics in diagnosis, prognosis, and treatment monitoring, and their applicability to the personalized management of BC, are highlighted.

Proteomics for Early Detection of Non-Muscle-Invasive Bladder Cancer: Clinically Useful Urine Protein Biomarkers

Bladder cancer is the fourth most common cancer in men, and most cases are non-muscle-invasive. A high recurrence rate is a critical problem in non-muscle-invasive bladder cancer. The availability of few urine tests hinders the effective detection of superficial and small bladder tumors. Cystoscopy is the gold standard for diagnosis; however, it is associated with urinary tract infections, hematuria, and pain. Early detection is imperative, as intervention influences recurrence. Therefore, urinary biomarkers need to be developed to detect these bladder cancers. Recently, several protein candidates in the urine have been identified as biomarkers. In the present narrative review, the current status of the development of urinary protein biomarkers, including FDA-approved biomarkers, is summarized. Additionally, contemporary proteomic technologies, such as antibody-based methods, mass-spectrometry-based methods, and machine-learning-based diagnosis, are reported. Furthermore, new strategies for the rapid and correct profiling of potential biomarkers of bladder cancer in urine are introduced, along with their limitations. The advantages of urinary protein biomarkers and the development of several related technologies are highlighted in this review. Moreover, an in-depth understanding of the scientific background and available protocols in research and clinical applications of the surveillance of non-muscle bladder cancer is provided.

Proteomics Investigations of Potential Protein Biomarkers in Sera of Rabbits Infected With Schistosoma japonicum

Schistosomiasis is a chronic parasitic disease that continues to be a pressing public health problem in many developing countries. The primary pathological damage from the disease is granuloma and fibrosis caused by egg aggregation, and early treatment can effectively prevent the occurrence of liver fibrosis. Therefore, it is very important to identify biomarkers that can be used for early diagnosis of Schistosoma japonicum infection. In this study, a label-free proteomics method was performed to observe the alteration of proteins before infection, 1 and 6 weeks after infection, and 5 and 7 weeks after treatment. A total of 10 proteins derived from S. japonicum and 242 host-derived proteins were identified and quantified as significantly changed. Temporal analysis was carried out to further analyze potential biomarkers with coherent changes during infection and treatment. The results revealed biological process changes in serum proteins compared to infection and treatment groups, which implicated receptor-mediated endocytosis, inflammatory response, and acute-phase response such as mannan-binding lectin serine peptidase 1, immunoglobulin, and collagen. These findings offer guidance for the in-depth analysis of potential biomarkers of schistosomiasis, host protein, and early diagnosis of S. japonicum and its pathogenesis. Data are available via ProteomeXchange with identifier PXD029635.

Peptide barcodes in dogs affected by mitral valve disease with and without pulmonary hypertension using MALDI-TOF MS and LC-MS/MS

Mitral valve disease (MVD) is an important and most frequently acquired heart disease found in dogs. MVD is classified into different stages according to its severity. There is a challenge in differentiation between asymptomatic and symptomatic stages of the MVD. Moreover, pulmonary hypertension (PH) is a common complication in dogs affected by MVD. In clinical practice, there are also some limitations to identify PH. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a technique that can characterize specific patterns of peptide mass called peptide barcodes from various samples. Besides, in combination with liquid chromatography-tandem mass spectrometry (LC-MS/MS), potential peptide sequences associated with specific conditions could be identified. The present study aimed to use MALDI-TOF coupled with LC-MS/MS to characterize specific peptide barcodes and potential peptide candidates in serum samples from healthy dogs, dogs with MVD stage B (MVD B, asymptomatic stage), MVD stage C (MVD C, symptomatic stage), MVD stage B with PH (MVD B PH), and MVD stage C with PH (MVD C PH). Discrete clusters of the 5 sample groups were identified by 3D plot analysis. Peptide barcodes also revealed differences in peptide patterns among the 5 groups. Six amino acid sequences of peptide candidates at 1,225.60, 1,363.85, 1,688.71, 1789.52, 2020.21, and 2156.42 Da were identified as part of the proteins CLCN1, CLUL1, EDNRA, PTEN, SLC39A7, and CLN6, respectively. The network interactions between these discovered proteins and common cardiovascular drugs were also investigated. These results demonstrate that MALDI-TOF MS has promise as an optional technique for diagnosing dogs affected by asymptomatic and symptomatic stages of MVD with and without PH. Further studies are required to identify peptide barcodes in dogs with other diseases to create peptide barcode databases in veterinary medicine before using this method as a novel diagnostic tool in the future.

Novel serum peptide model revealed by MALDI-TOF-MS and its diagnostic value in early bladder cancer

BACKGROUND

Bladder cancer is the ninth most common cancer worldwide and has high morbidity and mortality. We aimed to search for potential serum peptide biomarkers and establish a diagnostic model for early bladder cancer.

METHODS

A total of 67 bladder cancer patients and 64 healthy volunteers were randomly divided into a training set and testing set 1. There were 30 hematuria patients used as testing set 2. Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry based on weak cation exchange magnetic beads was used to obtain and analyze the serum peptide profiles between bladder cancer patients and healthy volunteers in the training set. Serum peptide diagnostic model through a k-nearest neighbor algorithm, was established and validated, and significantly differentially expressed protein biomarkers were ultimately identified.

RESULTS

We constructed a diagnostic model containing five peptides (m/z 1954.9, m/z 2081.0, m/z 3938.3, m/z 3946.5, and m/z 4268.8). In the training set, the area under the curve (AUC) value of the five-peptide model was 0.923, and the sensitivity and specificity was 93.75% and 96.77%, respectively. In testing set 1, the sensitivity and specificity was 91.43% and 90.91%, respectively, and the specificity of testing set 2 was 73.33%. For early-stage bladder cancer, the sensitivity and specificity was 92.31% and 93.75%, respectively; the sensitivity of early low-grade bladder cancer was 90.00%; and the AUC value was 0.944.

CONCLUSION

The five-peptide diagnostic model established in this study had high sensitivity and specificity, especially in the diagnosis of early bladder cancer, and could differentiate between healthy volunteers and hematuria patients.

Proteomic research and diagnosis in bladder cancer: state of the art review

Purpose:

Proteomic biomarkers have been emerging as alternative methods to the gold standard procedures of cystoscopy and urine cytology in the diagnosis and surveillance of bladder cancer (BC). This review aims to update the state of the art of proteomics research and diagnosis in BC.

Materials and Methods:

We reviewed the current literature related to BC research on urinary, tissue, blood and cell line proteomics, using the Pubmed database.

Findings:

Two urinary protein biomarkers are FDA-approved (NMP22® and BTA® tests), only if performed along with cystoscopy for surveillance after initial diagnosis, but not in the primary diagnostic setting due to high false-positive rates in case of infections, stones and hematuria. There are a great number of non-FDA approved proteins being studied, with good preliminary results; panels of proteins seem valuable tools to be refined in ongoing trials. Blood proteins are a bigger challenge, because of the complexity of the serum protein profile and the scarcity of blood proteomic studies in BC. Previous studies with the BC tissue proteome do not correlate well with the urinary proteome, likely due to the tumor heterogeneity. Cell line proteomic research helps in the understanding of basic mechanisms that drive BC development and progression; the main difficulty is culturing low-grade tumors in vitro, which represents the majority of BC tumors in clinical practice.

Conclusion:

Protein biomarkers have promising value in the diagnosis, surveillance and prognostic of BC. Urine is the most appropriate body fluid for biomarker research in BC due to its easiness of sampling, stability and enrichment of shed and secreted tumor-specific proteins. Panels of biomarkers may exhibit higher sensitivity than single proteins in the diagnosis of BC at larger populations due to clinical and tumor heterogeneity. Prospective clinical trials are warranted to validate the relevance of proteomic data in the clinical management of BC.

[Mass spectrometry-applications in pathology]

BACKGROUND

Currently, more complex and extensive diagnostic pathology work-up of sometimes only limited sample material is necessary to ensure optimal patient treatment. This often includes genomic analyses. However, dynamic changes within an organism or tumor can be better reflected at the protein level. Therefore, proteomic technologies would seem to be the solution.

OBJECTIVES

To evaluate the application of different proteomic techniques to analyze body fluids and tissue samples with regards to implementation in diagnostics.

MATERIALS AND METHODS

All studies utilized mass spectrometry-based methods in order to achieve differentiation of a number of different patient groups in various diseases.

RESULTS

Whereas classical proteomic methods are particularly suitable for analyzing serum samples in order to diagnose bladder cancer or chronic hepatitis C, tissue analyses would require prior tissue lyses, thus erasing possible information to be obtained from histology. Imaging mass spectrometry offers a solution as it allows for the analysis of an intact tissue section. Possible applications and the added benefit of this method could be shown using various examples of tumors (prostate cancer, Hodgkin's lymphoma, cervical cancer, and different types of adenocarcinomas).

CONCLUSIONS

Mass spectrometry-based technologies allow diagnostic confirmation with high sensitivity and specificity. In comparison to routine diagnostic approaches, results can be achieved faster, using less sample material, and with comparable accuracy.

Integrated Fourier Transform Infrared Imaging and Proteomics for Identification of a Candidate Histochemical Biomarker in Bladder Cancer

Histopathological differentiation between severe urocystitis with reactive urothelial atypia and carcinoma in situ (CIS) can be difficult, particularly after a treatment that deliberately induces an inflammatory reaction, such as intravesical instillation of Bacillus Calmette-Guèrin. However, precise grading in bladder cancer is critical for therapeutic decision making and thus requires reliable immunohistochemical biomarkers. Herein, an exemplary potential biomarker in bladder cancer was identified by the novel approach of Fourier transform infrared imaging for label-free tissue annotation of tissue thin sections. Identified regions of interest are collected by laser microdissection to provide homogeneous samples for liquid chromatography-tandem mass spectrometry-based proteomic analysis. This approach afforded label-free spatial classification with a high accuracy and without interobserver variability, along with the molecular resolution of the proteomic analysis. Cystitis and invasive high-grade urothelial carcinoma samples were analyzed. Three candidate biomarkers were identified and verified by immunohistochemistry in a small cohort, including low-grade urothelial carcinoma samples. The best-performing candidate AHNAK2 was further evaluated in a much larger independent verification cohort that also included CIS samples. Reactive urothelial atypia and CIS were distinguishable on the basis of the expression of this newly identified and verified immunohistochemical biomarker, with a sensitivity of 97% and a specificity of 69%. AHNAK2 can differentiate between reactive urothelial atypia in the setting of an acute or chronic cystitis and nonmuscle invasive-type CIS.

Serum proteomic profiling for autism using magnetic bead-assisted matrix-assisted laser desorption ionization time-of-flight mass spectrometry: a pilot study

BACKGROUND

The pathogenesis of autism spectrum disorders remains elusive and currently there are no diagnostic or predictive biomarkers in autism available. Proteomic profiling has been used in a wide range of neurodevelopmental disorder studies, which could produce deeper perceptions of the molecular bases behind certain disease and potentially becomes useful in discovering biomarkers in autism spectrum disorders.

METHODS

Serum samples were collected from autistic children about 3 years old in age (n = 32) and healthy controls (n = 20) in similar age and gender. The samples were identified specific proteins that are differentially expressed by magnetic bead-based pre-fractionation and matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-ToF-MS).

RESULTS

Eight protein peaks were significantly different in autistic children from the healthy controls (P < 0.0001). The two peaks with the most significant differences were 6428 and 7758 Da in size.

CONCLUSION

According to differences in serum protein profiles between the autistic children and healthy controls, this study identified a set of differentially expressed proteins those are significant for further evaluation and might function as biomarkers in autism.

Intermediate and low abundant protein analysis of vitamin D deficient obese and non-obese subjects by MALDI-profiling

Obesity is a pathological condition caused by genetic and environmental factors, including vitamin D deficiency, which increases the risk of developing cardiovascular disorders and diabetes. This case-control study was designed to verify whether serum profiles could be identified differentiating obese and non-obese Saudis characterized by vitamin D deficiency and pathological levels of triglycerides, high-density lipoprotein cholesterol and high total cholesterol levels. The serum protein profiles of 64 vitamin D deficient (serum 25(OH)D < 50nmol/L) individuals with metabolic syndrome and with (n = 31; BMI ≥ 30) or without (n = 33; BMI < 30) obesity were analyzed by a quantitative label-free mass spectrometry approach (MALDI-profiling), combined with different serum immunodepletion strategies (Human7 and Human14 immuno-chromatographies), to analyze the intermediate- and low-abundant protein components. The analysis of intermediate-abundant proteins (Human7) in obese vs. non-obese subjects identified 14 changed peaks (p < 0.05) in the m/z range 1500–35000. Furthermore, the Human14 depletion provided new profiles related to obesity (121 changed peaks). Among changed peaks, 11 were identified in the m/z range 1500–4000 Da by high-resolution tandem mass spectrometry, belonging to apolipoprotein CIII, apolipoprotein B100, alpha-1-antichymotrypsin and complement C3. Data herein show that distinct protein profiles identify specific peptides belonging to lipid metabolism and inflammation processes that are associated with obesity and vitamin D deficiency.

Mass spectrometry-based serum peptidome profiling accurately and reliably predicts outcomes of pemetrexed plus platinum chemotherapy in patients with advanced lung adenocarcinoma

BACKGROUND

Although pemetrexed plus cis/carboplatin has become the most effective chemotherapy regimen for patients with advanced lung adenocarcinoma, predictive biomarkers are not yet available, and new tools to identify chemosensitive patients who would likely benefit from this treatment are desperately needed. In this study, we constructed and validated predictive peptide models using the serum peptidome profiles of two datasets.

METHODS

One hundred eighty-three patients treated with first-line platinum-based pemetrexed treatment for advanced lung adenocarcinoma were retrospectively enrolled and randomized into the training (n = 92) or validation (n = 91) set, and pre-treatment serum samples were analyzed using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and ClinProTools software. Serum peptidome profiles from the training set were used to identify potential predictive peptide biomarkers and construct a predictive peptide model for accurate group discrimination; which was then used to classify validation samples into "good" and "poor" outcome groups. The clinical outcomes of objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), and overall survival (OS) were analyzed based on the classification result.

RESULTS

Eight potential peptide biomarkers were identified. A predictive peptide model based on four distinct m/z features (2,142.12, 3,316.19, 4,281.94, and 6,624.02 Da) was developed based on the clinical outcomes of training set patients after first-line pemetrexed plus platinum treatment. In the validation set, the good group had significantly higher ORR (49.1% vs. 8.3%, P <0.001) and DCR (96.4% vs. 47.2%, P <0.001), and longer PFS (7.3 months vs. 2.7 months, P <0.001) vs. the poor group. However, the model did not predict OS (13.6 months vs. 12.7 months, P = 0.0675).

CONCLUSION

Our predictive peptide model could predict pemetrexed plus platinum treatment outcomes in patients with advanced lung adenocarcinoma and might thus facilitate appropriate patient selection. Further studies are needed to confirm these findings.

The impact of advanced proteomics in the search for markers and therapeutic targets of bladder cancer

Bladder cancer is the most common cancer of the urinary tract and can be avoided through proper surveillance and monitoring. Several genetic factors are known to contribute to the progression of bladder cancer, many of which produce molecules that serve as cancer biomarkers. Blood, urine, and tissue are commonly analyzed for the presence of biomarkers, which can be derived from either the nucleus or the mitochondria. Recent advances in proteomics have facilitated the high-throughput profiling of data generated from bladder cancer-related proteins or peptides in parallel with high sensitivity and specificity, providing a wealth of information for biomarker discovery and validation. However, the transmission of screening results from one laboratory to another remains the main disadvantage of these methods, a fact that emphasizes the need for consistent and standardized procedures as suggested by the Human Proteome Organization. This review summarizes the latest discoveries and progress of biomarker identification for the early diagnosis, projected prognosis, and therapeutic response of bladder cancer, informs the readers of the current status of proteomic-based biomarker findings, and suggests avenues for future work.

Circulating Biomarkers in Bladder Cancer

Bladder cancer is a molecularly heterogeneous disease characterized by multiple unmet needs in the realm of diagnosis, clinical staging, monitoring and therapy. There is an urgent need to develop precision medicine for advanced urothelial carcinoma. Given the difficulty of serial analyses of metastatic tumor tissue to identify resistance and new therapeutic targets, development of non-invasive monitoring using circulating molecular biomarkers is critically important. Although the development of circulating biomarkers for the management of bladder cancer is in its infancy and may currently suffer from lower sensitivity of detection, they have inherent advantages owing to non-invasiveness. Additionally, circulating molecular alterations may capture tumor heterogeneity without the sampling bias of tissue biopsy. This review describes the accumulating data to support further development of circulating biomarkers including circulating tumor cells, cell-free circulating tumor (ct)-DNA, RNA, micro-RNA and proteomics to improve the management of bladder cancer.

[Preliminary Study of Differentially Expressed Serum Peptides of Advanced NSCLC Patients Responsive to EGFR-TKI and Their Clinical Significance]

背景与目的

本研究旨在应用基质辅助激光解析离子化-时间飞行质谱仪（matrix-assisted laser desorption ionization time-of-?ight mass spectrometry, MALDI-TOF-MS）检测晚期非小细胞肺癌（non-small cell lung cancer, NSCLC）患者在接受表皮生长因子受体酪氨酸激酶抑制剂（epidermal growth factorreceptor tyrosine kinase inhibitors, EGFR-TKIs）治疗过程中血清多肽的变化并探索其临床意义。

方法

收集34例接受EGFR-TKI治疗的晚期NSCLC患者TKI治疗前、最佳疗效时及疾病进展后的自身配对血清样本102份。处理血清样本并应用MALDI-TOF-MS检测，得到质谱图后使用CPT统计软件进行分析，鉴定出差异多肽，并对其临床意义进行分析。

结果

34例接受EGFR-TKI治疗的患者无完全缓解（complete response, CR）患者，部分缓解（partial response, PR）11例，疾病稳定（stable disease, SD）23例，中位无进展生存期（progression-free survival, PFS）为8.0个月（95%CI: 6.6-11.2）；中位总生存期（overall survival, OS）为11.4个月（95%CI: 10.6-16.5）。对TKI治疗的三个不同时间点的血清进行质谱检测，结果显示三个时间点多肽指纹图谱均不相同；配对分析最佳疗效时与基线时质谱数据经CPT软件共鉴定出差异多肽峰87个，筛选出两组间有统计学差异[P < 0.001、曲线下面积（area under curve, AUC）≥0.9]的多肽峰1个；疾病进展时与基线时共鉴定出差异多肽峰96个，筛选出两组间有统计学差异（P < 0.001, AUC≥0.9）的多肽峰3个；最佳疗效时与疾病进展时共鉴定出差异多肽峰115个，筛选出两组间有统计学差异（P < 0.001, AUC≥0.9）的多肽峰4个。

结论

NSCLC患者TKI治疗过程中血清多肽存在动态变化，差异多肽可能与治疗效果、疾病进展相关，差异多肽的特性、临床意义需进一步鉴定和验证。

Challenges in biomarker discovery with MALDI-TOF MS

MALDI-TOF MS technique is commonly used in system biology and clinical studies to search for new potential markers associated with pathological conditions. Despite numerous concerns regarding a sample preparation or processing of complex data, this strategy is still recognized as a popular tool and its awareness has risen in the proteomic community over the last decade. In this review, we present comprehensive application of MALDI mass spectrometry with special focus on profiling research. We also discuss major advantages and disadvantages of universal sample preparation methods such as micro-SPE columns, immunodepletion or magnetic beads, and we show the potential of nanostructured materials in capturing low molecular weight subproteomes. Furthermore, as the general protocol considerably affects spectra quality and interpretation, an alternative solution for improved ion detection, including hydrophobic constituents, data processing and statistical analysis is being considered in up-to-date profiling pattern. In conclusion, many reports involving MALDI-TOF MS indicated highly abundant proteins as valuable indicators, and at the same time showed the inaccuracy of available methods in the detection of low abundant proteome that is the most interesting from the clinical perspective. Therefore, the analytical aspects of sample preparation methods should be standardized to provide a reproducible, low sample handling and credible procedure.

Proteomic study of benign and malignant pleural effusion

BACKGROUND

Lung adenocarcinoma can easily cause malignant pleural effusion which was difficult to discriminate from benign pleural effusion. Now there was no biomarker with high sensitivity and specificity for the malignant pleural effusion.

PURPOSE

This study used proteomics technology to acquire and analyze the protein profiles of the benign and malignant pleural effusion, to seek useful protein biomarkers with diagnostic value and to establish the diagnostic model.

METHODS

We chose the weak cationic-exchanger magnetic bead (WCX-MB) to purify peptides in the pleural effusion, used matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) to obtain peptide expression profiles from the benign and malignant pleural effusion samples, established and validated the diagnostic model through a genetic algorithm (GA) and finally identified the most promising protein biomarker.

RESULTS

A GA diagnostic model was established with spectra of 3930.9 and 2942.8 m/z in the training set including 25 malignant pleural effusion and 26 benign pleural effusion samples, yielding both 100 % sensitivity and 100 % specificity. The accuracy of diagnostic prediction was validated in the independent testing set with 58 malignant pleural effusion and 34 benign pleural effusion samples. Blind evaluation was as follows: the sensitivity was 89.6 %, specificity 88.2 %, PPV 92.8 %, NPV 83.3 % and accuracy 89.1 % in the independent testing set. The most promising peptide biomarker was identified successfully: Isoform 1 of caspase recruitment domain-containing protein 9 (CARD9), with 3930.9 m/z, was decreased in the malignant pleural effusion.

CONCLUSIONS

This model is suitable to discriminate benign and malignant pleural effusion and CARD9 can be used as a new peptide biomarker.

Developing proteomic biomarkers for bladder cancer: towards clinical application

Clinical use of proteomic biomarkers has the potential to substantially improve the outcomes of patients with bladder cancer. An unmet clinical need evidently exists for noninvasive biomarkers, which might enable improvements in both the diagnosis and prognosis of patients with bladder cancer, as well as improved monitoring of patients for the presence of recurrence. Urine is considered the optimal noninvasive source of proteomic biomarkers in patients with bladder cancer. Currently, a number of single-protein biomarkers have been detected in urine and tissue using a variety of proteomic techniques, each having specific conceptual considerations and technical implications. Promising preclinical data are available for several of these proteins; however, the combination of single urinary proteins into multimarker panels might better encompass the molecular heterogeneity of bladder cancer within this patient population, and prove more effective in clinical use.

Diagnostic model of saliva peptide finger print analysis of oral squamous cell carcinoma patients using weak cation exchange magnetic beads

Whole saliva (WS) was used for diagnosis of oral squamous cell carcinoma (OSCC); two polypeptides may be used for OSCC diagnosis.

Saliva diagnostics utilizing nanotechnology and molecular technologies to detect oral squamous cell carcinoma (OSCC) has become an attractive field of study. However, no specific methods have been established. To refine the diagnostic power of saliva peptide fingerprints for the early detection of OSCC, we screened the expression spectrum of salivary peptides in 40 T1 stage OSCC patients (and healthy controls) using MALDI-TOF-MS combined with magnetic beads. Fifty proteins showed significantly different expression levels in the OSCC samples (P<0.05). Potential biomarkers were also predicted. The novel diagnostic proteomic model with m/z peaks of 1285.6 Da and 1432.2 Da are of certain value for early diagnosis of OSCC.

Identification of peptide regions of SERPINA1 and ENOSF1 and their protein expression as potential serum biomarkers for gastric cancer

This study aimed to detect potential serum biomarkers for gastric cancer. In the present study, we used magnetic bead-based purification and matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry to detect potential serum markers in 70 gastric cancer (GC) patients compared with 72 healthy controls. On average, up to 81 peaks, of which 11 were significantly different m/z peaks (fold change >1.5; P < 0.001, Wilcoxon rank sum test) between GC group and healthy controls were detected. Two potential gastric serum biomarkers (m/z values of 1546.02 and 5335.08), with higher and specific expression in GC patients were further identified as peptide regions of SERPINA1 and ENOSF1. Enzyme-linked immunosorbent assays (ELISAs) were used to analyze 210 additional serum samples obtained from 36 healthy volunteers, 36 GC patients, 30 GU patients, 36 nonsmall-cell lung cancer (NSCLC) patients, 36 clear-cell renal cell carcinoma (CCRCC) patients, and 36 pancreatic cancer patients to verify the expression of SERPINA1 and ENOSF1 in GC sera. The suitability of the present method for gastric serum proteomic analysis was demonstrated and led to the identification of two peptide regions and their corresponding proteins as potential serum biomarkers for the serum detection of GC.

[Search for potential gastric cancer biomarkers using low molecular weight blood plasma proteome profiling by mass spectrometry]

Gastric cancer, one of the most widespread malignant tumors, still lacks reliable serum/plasma biomarkers of its early detection. In this study we have developed, unified, and tested a new methodology for search of gastric cancer biomarkers based on profiling of low molecular weight proteome (LMWP) (1-17 kDa). This approach included three main components: sample pre-fractionation, matrix-assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS), data analysis by a bioinformatics software package. Applicability and perspectives of the developed approach for detection of potential gastric cancer markers during LMWP analysis have been demonstrated using 69 plasma samples from patients with gastric cancer (stages I-IV) and 238 control samples. The study revealed peptides/polypeptides, which may be potentially used for detection of this pathology.

Urinary peptidomics identifies potential biomarkers for major depressive disorder

Major depressive disorder (MDD) is a debilitating psychiatric illness with no available objective laboratory-based diagnostic test. In this study, matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS)-based peptidomics was applied to identify potential urinary diagnostic biomarkers for MDD. A training set of 42 first-episode drug-naive MDD patients and 28 age- and gender-matched healthy controls (HC) was used to develop a peptide diagnostic pattern. Then, the diagnostic efficacy of this pattern was assessed in an independent blinded test set consisting of 24 MDD patients and 13 age- and gender-matched HC. A combination of five potential biomarkers was identified, yielding a sensitivity of 91.7% and specificity of 84.6% in the test set. Moreover, the protein precursors of four of the five peptides were identified by tandem mass spectrometric analysis: serum albumin, apolipoprotein A-I, protein AMBP, and basement membrane-specific heparan sulfate proteoglycan core protein. Taken together, the peptide pattern may be valuable for establishing an objective laboratory-based diagnostic test for MDD.

Low- and high-grade bladder cancer appraisal via serum-based proteomics approach

OBJECTIVE

To address the shortcomings of urine cytology and cystoscopy for screening and grading of urinary bladder cancer (BC) we applied a serum-based proteomics approach as a surrogate tactic for rapid BC probing.

METHODS

This study was performed on 90 sera samples comprising of low-grade (LG, n=33) and high-grade (HG, n=32) BC, and healthy controls (HC, n=25). Two-dimensional gel electrophoresis (2DE) tactic was executed to describe serum proteome. MALDI-TOF-MS (MS) was used to identify the characteristics of aberrantly expressed proteins in 2DE and validated using Western blot (WB) and ELISA approach. Receiver operating characteristics (ROC) curve analysis was also performed to determine the clinical usefulness of these proteins to discriminate among LG, HG and HC cohorts.

RESULTS

This comprehensive approach of 2DE, MS, WB and ELISA reveals five differentially expressed proteins. Among them two biomarkers (S100A8 and S100A9) were able to accurately (ROC, 0.946) distinguish 81% of BC (LG+HG) cases compared to HC with highest sensitivity and specificity. With a comparable tactic, two biomarkers (S100A8 and S100A4) were able to precisely (ROC, 0.941) discriminate 92% of LG cases from HG with utmost sensitivity and specificity.

CONCLUSIONS

Serum proteomics probing appears to be an encouraging and least-invasive tactic for screening and grading of BC.

A proteomics approach to the identification of plasma biomarkers for latent tuberculosis infection

A proteomic analysis was performed to screen the potential latent tuberculosis infection (LTBI) biomarkers. A training set of spectra was used to generate diagnostic models, and a blind testing set was used to determine the accuracy of the models. Candidate peptides were identified using nano-liquid chromatography-electrospray ionization–tandem mass spectrometry. Based on the training set results, 3 diagnostic models recognized LTBI subjects with good cross-validation accuracy. In the blind testing set, LTBI subjects could be identified with sensitivities and specificities of 85.20% to 88.90% and 85.7% to 100%, respectively. Additionally, 14 potential LTBI biomarkers were identified, and all proteins were identified for the first time through proteomics in the plasma of healthy, latently infected individuals. In all, proteomic pattern analyses can increase the accuracy of LTBI diagnosis, and the data presented here provide novel insights into potential mechanisms involved in LTBI.

A multiplex biomarker approach for the diagnosis of transitional cell carcinoma from canine urine

Transitional cell carcinoma (TCC), the most common cancer of the urinary bladder in dogs, is usually diagnosed at an advanced disease stage with limited response to chemotherapy. Commercial screening tests lack specificity and current diagnostic procedures are invasive. A proof of concept pilot project for analyzing the canine urinary proteome as a noninvasive diagnostic tool for TCC identification was conducted. Urine was collected from 12 dogs in three cohorts (healthy, urinary tract infection, TCC) and analyzed using liquid chromatography tandem mass spectrometry. The presence of four proteins (macrophage capping protein, peroxiredoxin 5, heterogeneous nuclear ribonucleoproteins A2/B, and apolipoprotein A1) was confirmed via immunoblot. Of the total 379 proteins identified, 96 were unique to the TCC group. A statistical model, designed to evaluate the accuracy of this multiplex biomarker approach for diagnosis of TCC, predicted the presence of disease with 90% accuracy.

MALDI-TOF MS as evolving cancer diagnostic tool: a review

Recent developments in mass spectrometry have introduced clinical proteomics to the forefront of diseases diagnosis, offering reliable, robust and efficient analytical method for biomarker discovery and monitoring. MALDI-TOF is a powerful tool for surveying proteins and peptides comprising the realm for clinical analysis. MALDI-TOF has the potential to revolutionize cancer diagnostics by facilitating biomarker discovery, enabling tissue imaging and quantifying biomarker levels. Healthy (control) and cancerous tissues can be analyzed on the basis of mass spectrometry (MALDI-TOF) imaging to identify cancer-specific changes that may prove to be clinically useful. We review MALDI-TOF profiling techniques as tools for detection of cancer biomarkers in various cancers. We mainly discuss recent advances including period from 2011 to 2013.

Serum proteomic study on EGFR-TKIs target treatment for patients with NSCLC

Background

Although epidermal growth factor receptor (EGFR)-tyrosine kinase inhibitors (TKIs) are widely used for EGFR mutated non-small-cell lung cancer (NSCLC) patients, tumor sample availability and heterogeneity of the tumor remain challenging for physicians’ selection of these patients. Here, we developed a serum proteomic classifier based on matrix assisted laser desorption ionization time of flight mass spectrometry (MALDI-TOF-MS) to predict the clinical outcome of patients treated with EGFR-TKIs.

Method

A total of 68 patients were included in this study. All patients received EGFR-TKIs as second or third line treatment and blood samples were collected before treatment. Using magnetic bead assisted serum peptide capture coupled to MALDI-TOF-MS, pretreatment serum from 24 NSCLC patients was analyzed to develop a proteomic classifier (training set). In a blinded test set with 44 patients, each sample was classified into “good” or “poor” groups using this classifier. Survival analysis of each group was done based on this classification.

Result

A 3-peptide proteomic classifier was developed from the training set. In the testing set, the classifier was able to distinguish patients of “good” or “poor” outcomes with 93% accuracy, sensitivity, and specificity. The overall survival and progression free survival of the predicted good group were found to be significantly longer than the poor group, not only in the whole population but also in certain subgroups, such as pathological adenocarcinoma and nonsmokers. With respect to the tumor samples available for EGFR mutation detection, all eight EGFR mutant tumors and three of the 12 wild type EGFR tumors were classified as good while nine of the 12 wild type EGFR tumors were classified as poor.

Conclusion

The current study has shown that a proteomic classifier can predict the outcome of patients treated with EGFR-TKIs and may aid in patient selection in the absence of available tumor tissue. Further studies are necessary to confirm these findings.

Bladder cancer detection and monitoring: assessment of urine- and blood-based marker tests

Bladder cancer is one of the most prevalent cancers worldwide, but the treatment and management of this disease can be very successful if the disease is detected early. The development of molecular assays that could diagnose bladder cancer accurately, and at an early stage, would be a significant advance. Ideally, such molecular assays would be applicable to non-invasively obtained body fluids, and be designed not only for diagnosis but also for monitoring disease recurrence and response to treatment. In this article, we assess the performance of current diagnostic assays for bladder cancer and discuss some of the emerging biomarkers that could be developed to augment current bladder cancer detection strategies.

Diagnostic model of saliva peptide finger print analysis of primary Sjögren's syndrome patients by using weak cation exchange magnetic beads

Saliva diagnostics has become an attractive field utilizing nanotechnology and molecular technologies for pSS (primary Sjögren's syndrome). However, no specific methods have been established. To refine the diagnostic power of the saliva peptide finger print for the early detection of pSS, we screened the expression spectrum of salivary peptides in pSS patients by using mass spectrometry MALDI-TOF-MS (matrix-assisted laser-desorption ionization-time-of-flight MS) combined with magnetic bead. The present study was comprised 12 pSS patients and 13 healthy controls and broken down to two different phases. In the initial ‘exploratory phase’, we enrolled seven pSS patients with eight age- and sex-matched healthy volunteers. Proteomics analysis of the unstimulated salivary samples was conducted to generate proportional peptide mass fingerprints. A diagnostic model was established. The testing cohort of the second ‘validation phase’ was represented by five pSS patients and five age- and sex-matched healthy controls. The diagnostic power of this diagnostic panel was then validated. The results showed seven m/z (mass-to-charge) ratio peaks with significant differences. Five peptides were up-regulated and two down-regulated in the pSS patients compared with matched healthy subjects. In the validation phase, four out of five pSS patients were diagnosed as pSS, and four of the five healthy controls were diagnosed as healthy controls, respectively. Potential biomarkers were also primarily predicted. The novel diagnostic proteomic model with m/z peaks 1068.1 Da, 1196.2 Da, 1738.4 Da, 3375.3 Da, 3429.3 Da, 3449.7 Da and 3490.6 Da is of certain value for early diagnosis of pSS.

Serum proteomic profiling for the early diagnosis of colorectal cancer

No ideal serum biomarker currently exists for the early diagnosis of colorectal cancer (CRC). Magnetic bead-based fractionation coupled with MALDI-TOF MS was used to screen serum samples from CRC patients, healthy controls, and other cancer patients. A diagnostic model with five proteomic features (m/z 1778.97, 1866.16, 1934.65, 2022.46, and 4588.53) was generated using Fisher algorithm with best performance. The Fisher-based model could discriminate CRC patients from the controls with 100% (46/46) sensitivity and 100% (35/35) specificity in the training set, 95.6% (43/45) sensitivity and 83.3% (35/42) specificity in the test set. We further validated the model with 94.4% (254/269) sensitivity and 75.5% (83/110) specificity in the external independent group. In other cancers group, the Fisher-based model classified 25 of 46 samples (54.3%) as positive and the other 21 as negative. With FT-ICR-MS, the proteomic features of m/z 1778.97, 1866.16, 1934.65, and 2022.46, of which intensities decreased significantly in CRC, were identified as fragments of complement C3f. Therefore, the Fisher-based model containing five proteomic features was able to effectively differentiate CRC patients from healthy controls and other cancers with a high sensitivity and specificity, and may be CRC-specific. Serum complement C3f, which was significantly decreased in CRC group, may be relevant to the incidence of CRC.

Predicting metachronous liver metastasis from colorectal cancer using serum proteomic fingerprinting

BACKGROUND

There are currently no accurate predictive markers of metachronous liver metastasis (MLM) from colorectal cancer.

METHODS

Magnetic bead-based fractionation coupled with mass spectrometry analysis was used to compare serum samples from 64 patients with MLM and 64 without recurrence or metastasis for at least 3 y after radical colorectal surgery (NM). A total of 40 MLM and 40 NM serum samples were randomly selected to build a decision tree, and the remainder were tested as blinded samples. Selected peptides were identified.

RESULTS

The patients in the two groups were matched for gender, age, tumor location, TNM staging, and histologic differentiation grade. Preoperative serum carcinoembryonic antigen retained no independent power to predict MLM. The decision tree model with eight proteomic features (m/z 3315, 6637, 1207, 1466, 4167, 4210, 2660, and 4186) correctly classified 33 of 40 NM sera (82.5%) and 32 of 40 MLM sera (80%) in the training set and 19 of 24 NM sera (79.2%) and 17 of 24 MLM sera (70.8%) in the test set. The peptides were identified as fragments of alpha-fetoprotein, complement C4-A, fibrinogen alpha, eukaryotic peptide chain release factor GTP-binding subunit ERF3B, and angiotensinogen.

CONCLUSIONS

In patients matched for gender, age, tumor location, TNM staging, and histologic differentiation grade, preoperative carcinoembryonic antigen retained no independent power to predict MLM. The decision tree model of eight proteomic features demonstrated promising value for predicting MLM in patients who underwent radical resection of colorectal cancer.

Identification of novel low molecular weight serum peptidome biomarkers for non-small cell lung cancer (NSCLC)

AIM

To identify discriminating protein patterns in serum samples among non-small cell lung cancer (NSCLC), chronic obstructive pulmonary disease (COPD), pneumonia, and healthy controls. To discover specific low molecular weight (LMW) serum peptidome biomarkers and establish a diagnostic pattern for NSCLCby using proteomic technology.

METHODS

We used magnetic bead-based separation followed by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) to identify patients with NSCLC, COPD, and pneumonia. A total of 154 serum samples were analyzed in this study, among which there were 60 serum samples from NSCLC patients, 30 from patients with other lung-related diseases (16 pneumonia patients and 14 patients with COPD) as disease controls, and 64 from healthy volunteers as healthy control. The mass spectra, analyzed using ClinProTools software, distinguished between cancer patients and healthy individuals based on GA algorithm model.

RESULTS

In this study, we generated numerous discriminating m/z peaks as well as disease-specific discrimination peaks. A set of five potential biomarkers (m/z: 7,763.24, 1,012.61, 4,153.16, 1,450.55, and 2,878.89) could be used as the diagnostic biomarkers to distinguish NSCLCpatients from healthy controls. In the training set, patients with NSCLC could be identified with sensitivity of 97.5% and specificity of 98.8%. Similar results were obtained in the testing set, showing 80.7% sensitivity and 91.2% specificity.

CONCLUSION

Our study demonstrated that a combined application of magnetic beads with MALDI-TOF MS technique was suitable for identification of serum biomarkers for NSCLC.

Serum peptidomic biomarkers for pulmonary metastatic melanoma identified by means of a nanopore-based assay

The significant mortality rate associated with metastatic melanoma, which exceeds the number of deaths attributed to the primary tumor, is primarily due to poor diagnosis and increased resistance to systemic therapy. Early detection and treatment of invasive melanoma are therefore crucial to increase survival rates. Low molecular weight proteins and peptides have garnered significant interest as biomarker candidates as they potentially represent a snap shot of pathological condition within the body and, by extension, the organism as a whole. We have developed a nanoporous silica-based platform to segregate the low molecular weight from the high molecular weight protein fraction to aid in the detection of peptides from serum samples using mass spectrometry. The combination of sample treatment with our platform, MALDI-TOF MS and following biostatistical analysis led to the discovery and identification of 27 peptides that are potential biomarkers associated with the development of pulmonary metastatic melanoma. We strongly believe our findings can assist to discover stage-specific peptide signatures and lead to more specific and personalized treatments for patients suffering from pulmonary metastatic melanoma.

Magnetic bead-based salivary peptidome profiling for periodontal-orthodontic treatment

Background

Patients with periodontitis seek periodontal-orthodontic treatment to address certain functional and aesthetic problems. However, little is known of the effect of periodontitis on orthodontic treatment. Thus, we compared the differences in peptide mass fingerprints of orthodontic patients with and without periodontitis by MALDI-TOF MS using a magnetic bead-based peptidome analysis of saliva samples. In this way, we aimed to identify and explore a panel of differentially-expressed specific peptides.

Results

Saliva samples from 24 patients (eight orthodontic patients without periodontitis, eight with periodontitis and another eight with periodontitis but no orthodontic treatment) were analyzed, and peptide mass fingerprints were created by scanning MS signals using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) combined with magnetic beads. Nine mass peaks showed significant differences. Orthodontic patients in the group without periodontal disease showed higher mass peaks for seven peptides of the nine, whereas the mass peaks for the other two peptides were higher in the periodontal-orthodontic patients. Besides, these differentially-expressed peptides were sequenced.

Conclusions

The elucidated candidate biomarkers indicated interactions between periodontal condition and orthodontic treatment and their contributions to the changes of saliva protein profiles. Our results provide novel insight into the altered salivary protein profile during periodontal-orthodontic treatment, and may lead to the development of a therapeutic monitoring strategy for periodontics and orthodontics.

Discovery of potential bladder cancer biomarkers by comparative urine proteomics and analysis

OBJECTIVE

We searched for bladder tumor markers by analyzing urine samples from patients with bladder cancer and from normal controls.

METHODS

Proteins in urine samples of patients with bladder cancer and with normal controls were systematically examined by 2-dimensional electrophoresis combined with matrix-assisted laser desorption ionization time-of-flight mass spectrometry. The expression of the protein apolipoprotein A-I (apoA-I) was confirmed by Western blot analysis and further evaluated.

RESULTS

We successfully obtained the 2-dimensional electrophoresis gel maps of urinary proteins in patients with bladder cancer and in normal controls. Thirty differentially expressed protein spots were successfully matched by matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Combined with the SWISS-PROT database, only 14 proteins (beta-2-microglobulin, fatty acid-binding protein adipocyte, gelsolin, isoform 1 of gelsolin, myoglobin, isoform 2 of fibrinogen alpha chain, apoA-I, prostaglandin D(2) synthase 21 kDa [brain], protein AMBP, transthyretin, keratin type II cytoskeletal 1, type II cytoskeletal 8, putative uncharacterized protein ALB, putative uncharacterized protein MASP2 [fragment]) were identified, including 2 putative proteins. Furthermore, apoA-I was confirmed by Western blot analysis, and the high level of apoA-I was found in urine samples from patients with bladder tumors compared with normal controls.

CONCLUSIONS

Analysis of urinary proteome may be a feasible, noninvasive, and efficient strategy for searching for potential bladder tumor biomarkers. A significant relationship of expressed apoA-I was established between bladder cancer and normal controls. We concluded that 14 differential spots included the apoA-I and would be potential urinary biomarkers for the diagnosis and surveillance of bladder cancer.

Magnetic bead-based salivary peptidome profiling analysis during orthodontic treatment durations

Orthodontic treatment induces various biological responses, including tooth movement and remodeling of alveolar bone. Although some studies have investigated the contribution of orthodontic procedures to changes in saliva conditions, little is known about the effects of different treatment durations on the saliva proteome. To identify the discriminating protein profiles in unstimulated whole saliva of orthodontic patients with different treatment durations, we used matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) combined with magnetic bead, and peptide mass fingerprints were created by scanning MS signals. Saliva samples from 40 patients (10 in each of four groups: the group without an appliance and groups under treatment for 2, 7, and 12 months) were analyzed. The results showed eight mass peaks with significant differences. Furthermore, mass peak intensities at proteins 1817.7, 2010.7, 2744 and 2710.2 Da represented a steady time-dependent increasing trend, whereas protein 4134 Da exhibited a decreasing tendency. Differential expression of the peptidome profile also occurred in the multiple comparisons, and we established a fitting model. Thus, the potential discriminating biomarkers investigated in this study reflected the complicated changes in periodontal tissues during orthodontic treatment and indicated dynamic interactions between orthodontic treatment and the saliva proteome. The results provide novel insights into alterations in salivary proteins due to different orthodontic treatment durations and may lead to the development of a therapeutic monitoring strategy for orthodontics.

Comparison of plasma from healthy nonsmokers, smokers, and lung cancer patients: pattern-based differentiation profiling of low molecular weight proteins and peptides by magnetic bead technology with MALDI-TOF MS

CONTEXT

Smoking is the major contributor of lung cancer (LC), which accounts for millions of death.

OBJECTIVE

This study focused on the correlation between the proteomic profiling of LC patients, and healthy nonsmokers and smokers.

METHOD

Pattern-based peptide profiling of 186 plasma samples was performed through reversed-phase chromatography-18 magnetic bead fractionation coupled with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry analysis and resulted data were evaluated statistically by ClinProTool.

RESULTS

Marker peaks at m/z 1760, 5773, 5851, 2940, and 7172 were found with an excellent statistical figure.

CONCLUSION

Selected marker peaks can be served as a differentiated tool of LC patients with high sensitivity and specificity.

From proteomic multimarker profiling to interesting proteins: thymosin-β(4) and kininogen-1 as new potential biomarkers for inflammatory hepatic lesions

Despite tremendous efforts in disclosing the pathophysiological and epidemiological factors associated with liver fibrogenesis, non-invasive diagnostic measures to estimate the clinical outcome and progression of liver fibrogenesis are presently limited. Therefore, there is a mandatory need for methodologies allowing the reasonable and reliable assessment of the severity and/or progression of hepatic fibrogenesis. We here performed proteomic serum profiling by matrix-assisted laser desorption ionization time-of-flight mass spectrometry in 179 samples of patients chronically infected with hepatitis C virus and 195 control sera. Multidimensional analysis of spectra allowed the definition of algorithms capable to distinguish class-specific protein expression profiles in serum samples. Overall about 100 peaks could be detected per single spectrum. Different algorithms including protein peaks in the range of 2000 and 10,000 Da were generated after pre-fractionation on a weak cation exchange surface. A specificity of 93% with a sensitivity of 86% as mean of the test set results was found, respectively. The nature of three of these protein peaks that belonged to kininogen-1 and thymosin-β₄ was further analysed by tandem mass spectrometry (MS)/MS. We further found that kininogen-1 mRNA was significantly down-regulated in cirrhotic livers. We have identified kininogen-1 and thymosin-β₄ as potential new biomarkers for human chronic hepatitis C and conclude that serum profiling is a reliable technique to identify hepatitis-associated expression patterns. Based on the high throughput capability, the identified differential protein panel may serve as a diagnostic marker and warrants further validation in larger cohorts.

Proteomic tissue profiling for the improvement of grading of noninvasive papillary urothelial neoplasia

OBJECTIVES

In 2004, a novel grading system for papillary non-invasive bladder cancer was introduced; low grade (LG) and high grade (HG) in lieu of the former G1, G2, G3. This change allowed for increased reproducibility as well as diminished interobserver variability in histopathological grading among individual pathologists. Matrix Assisted Laser Desorption/Ionization Time of Flight Imaging Mass Spectrometry (MALDI TOF IMS) was evaluated as an automatic and objective tool to assist grading of urothelial neoplasms and to facilitate accuracy.

DESIGN AND METHODS

To separate G1 (LG, n=27) and G3 (HG, n=21) papillary tumors MALDI TOF IMS was performed using an appropriate algorithm. Thereafter, the automatic assignment of a separate G2 (n=31) group was completed.

RESULTS

G1 (LG) and G3 (HG) tumors were separated with an overall cross validation of 97.18%. G2 tumors indicated a true positive rate of 78.3% for LG and 87.5% for HG, respectively.

CONCLUSIONS

MALDI TOF IMS is a powerful support tool to ascertain pathological diagnosis/grading.

Assessment of high-throughput high-resolution MALDI-TOF-MS of urinary peptides for the detection of muscle-invasive bladder cancer

PURPOSE

There is a need for better biomarkers to both detect bladder cancer and distinguish muscle-invasive (stage T2+) from non-invasive (stage Ta/T1) disease. We assess whether MALDI-TOF-MS of the urine peptidome can achieve this.

EXPERIMENTAL DESIGN

We analysed urine from 751 patients with bladder cancer and 127 patients without bladder cancer. Endogenous peptide profiling was performed using a Bruker Ultraflextreme MALDI-TOF-MS.

RESULTS

Significant differences were seen between the spectra of urine from patients with and without T2+ disease. Albumin, total protein and haematuria were also elevated in T2+ patients. Haematuria was detected in 39% of patients with Ta/T1 disease and in 77% of patients with T2+ disease. Class prediction models based on MALDI data produced areas under receiver-operator characteristic curves of up to 0.76 but did not significantly outperform a model based on total protein alone. Many peptides significantly associated with invasive disease are fragments of abundant blood proteins and are also associated with haematuria.

CONCLUSIONS AND CLINICAL RELEVANCE

Microscopic haematuria is strongly associated with invasive disease; even traces of blood/plasma strongly influence the urinary peptidome. This needs to be taken into consideration when using 'omic' methods to search for urinary biomarkers as blood proteins may give false-positive results.

Mass spectrometry of peptides and proteins from human blood

It is difficult to convey the accelerating rate and growing importance of mass spectrometry applications to human blood proteins and peptides. Mass spectrometry can rapidly detect and identify the ionizable peptides from the proteins in a simple mixture and reveal many of their post-translational modifications. However, blood is a complex mixture that may contain many proteins first expressed in cells and tissues. The complete analysis of blood proteins is a daunting task that will rely on a wide range of disciplines from physics, chemistry, biochemistry, genetics, electromagnetic instrumentation, mathematics and computation. Therefore the comprehensive discovery and analysis of blood proteins will rank among the great technical challenges and require the cumulative sum of many of mankind's scientific achievements together. A variety of methods have been used to fractionate, analyze and identify proteins from blood, each yielding a small piece of the whole and throwing the great size of the task into sharp relief. The approaches attempted to date clearly indicate that enumerating the proteins and peptides of blood can be accomplished. There is no doubt that the mass spectrometry of blood will be crucial to the discovery and analysis of proteins, enzyme activities, and post-translational processes that underlay the mechanisms of disease. At present both discovery and quantification of proteins from blood are commonly reaching sensitivities of ∼1 ng/mL.

Bladder cancer determination via two urinary metabolites: a biomarker pattern approach

The purpose of this study was to use metabonomic profiling to identify a potential specific biomarker pattern in urine as a noninvasive bladder cancer (BC) detection strategy. A liquid chromatography-mass spectrometry based method, which utilized both reversed phase liquid chromatography and hydrophilic interaction chromatography separations, was performed, followed by multivariate data analysis to discriminate the global urine profiles of 27 BC patients and 32 healthy controls. Data from both columns were combined, and this combination proved to be effective and reliable for partial least squares-discriminant analysis. Following a critical selection criterion, several metabolites showing significant differences in expression levels were detected. Receiver operating characteristic analysis was used for the evaluation of potential biomarkers. Carnitine C9:1 and component I, were combined as a biomarker pattern, with a sensitivity and specificity up to 92.6% and 96.9%, respectively, for all patients and 90.5% and 96.9%, respectively for low-grade BC patients. Metabolic pathways of component I and carnitine C9:1 are discussed. These results indicate that metabonomics is a practicable tool for BC diagnosis given its high efficacy and economization. The combined biomarker pattern showed better performance than single metabolite in discriminating bladder cancer patients, especially low-grade BC patients, from healthy controls.

Serum peptidome profiling in patients with gastric cancer

To identify discriminating protein patterns in serum samples between gastric cancer patients (early and advanced stages) and healthy controls. We used magnetic bead-based separation followed by matrix-assisted laser desorption ionization (MALDI) time-of-flight (TOF) mass spectrometry (MS) to identify patients with gastric cancer. In total, serum samples from 62 gastric cancer patients (32 in the training set and 30 in the test set; 19 of which had early-stage tumors and 43 of which had advanced-stage tumors) and 64 healthy controls (32 in the training set and 32 in the test set) were analyzed. The mass spectra, analyzed using ClinProTools software, distinguished between cancer patients and healthy individuals based on three different algorithm models. In the training set, patients with gastric cancer could be identified with a mean sensitivity of 94.7% and a mean specificity of 99%. Similar results were obtained with the test set, showing 79.3% sensitivity and 86.5% specificity. Our study demonstrates the high sensitivity and specificity of screening serum protein patterns using MALDI-TOF MS for the identification of patients with gastric cancer.

[Current knowledge in molecular pathology of urothelial cancer]

Results of molecular pathology have supported changes in the 2004 WHO classification of urothelial cancer. Since then new molecular data such as the distribution pattern of the fibroblast growth factor receptor 3 (FGFR3) has further supported the principle of low and high grade entities of urothelial carcinoma. Animal experiments with knockout mice and conditional knockout systems reveal important parallels to humans and results emphasize the cellular context as a trigger for malignancy. One special feature of the urothelium is its high protection of the urothelial cells by members of the retinoblastoma gene family, efficiently inhibiting invasion even in the presence of p53 mutations. In search of the tumor stem cell phenotype the basal cell phenotype is the focus of attention providing a high clonogenic potential. At the same time detailed analysis of the distribution of mutations in the mitochondrial genome within the urothelium will help to gain insight into the spreading of normal cell or tumor cell clones. The overall data in urological oncology provide evidence that diagnostic and prognostic tools for urothelial cancer can only be reached with multiparametric approaches.