Detection of Ovarian Cancer Using Samples Sourced from the Vaginal Microenvironment

AbstractMass spectrometry (MS) offers high levels of specificity and sensitivity in clinical applications, and we have previously been able to demonstrate that matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) MS is capable of distinguishing two-component biological mixtures at low limits of detection. Ovarian cancer is notoriously difficult to detect due to the lack of any screening methods for early detection. By sampling a local microenvironment, such as the vaginal fluids, a MS based method is presented that was capable of monitoring disease progression from vaginally collected, local samples from tumor bearing mice. A murine xenograft model of high grade serous ovarian carcinoma (HGSOC) was used for this study and vaginal lavages were obtained from mice on a weekly basis throughout disease progression and subjected to our MALDI-TOF MS workflow followed by statistical analyses. Proteins in the 4-20 kDa region of the mass spectrum could consistently be measured to yield a fingerprint that correlated with disease progression over time. These fingerprints were found to be statistically stable across all mice with the protein fingerprint converging towards the end point of the study. MALDI-TOF MS serves as a unique analytical technique for measuring a sampled vaginal microenvironment in a specific and sensitive manner for the detection of HGSOC in a murine model.

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Application analysis of MALDI-TOF MS in rapid identification of anaerobic bacteria

10.21203/rs.2.9661/v1 ◽

2019 ◽

Author(s):

Ying Li ◽

Mingzhu Shan ◽

Zuobin Zhu ◽

Xuhua Mao ◽

Mingju Yan ◽

...

Keyword(s):

Fixed Effects ◽

Meta Analysis ◽

Anaerobic Bacteria ◽

Identification Accuracy ◽

P Value ◽

Correct Identification ◽

Maldi Tof Ms ◽

Analytical Technique ◽

Maldi Tof ◽

Tof Ms

Abstract BACKGROUND: Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has been rapidly developed and widely used as an analytical technique in the clinical laboratories with high accuracy in the identification of microorganisms. METHOD: This study was designed to evaluate MALDI-TOF MS for identification of clinical pathogenic anaerobes. RESULT: Twenty-eight studies covering 6685 strains of anaerobic bacteria were included in this meta-analysis. Fixed-effects models based on the P-value and the I-squared were used for meta-analysis to consider the possibility of heterogeneity between studies. Statistical analyses were performed by using STATA 12.0. Results shown that the identification accuracy of MALDI-TOF MS at species was 84% (I2 = 98.0%, P < 0.1), genus was 92% (I2 = 96.6%, P < 0.1). Thereinto, the identification accuracy of Bacteroides was the highest at 96% with a 95% CI of 95% to 97%. Next were Lactobacillus spp., Parabacteroides spp., Clostridium spp., Propionibacterium spp., Prevotella spp., Veillonella spp. and Peptostreptococcus spp., and their correct identification rates were all above 90%, while the accuracy of rare anaerobic bacteria was lower. Meanwhile, the overall capabilitys of two MALDI-TOF MS systems were different. The identification accuracy rate of VITEK MS was 90%, compared to 86% by the MALDI biotyper system. CONCLUSON: In summary, our research showed that MALDI-TOF-MS was satisfactory in the identification of genus in clinical pathogenic anaerobic bacteria. However, this method still suffered from different drawbacks in the identification of the rare anaerobes and species levels of common anaerobic bacteria.

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Application of MALDI-TOF MS to rapid identification of anaerobic bacteria

10.21203/rs.2.9661/v5 ◽

2019 ◽

Author(s):

Ying Li ◽

Mingzhu Shan ◽

Zuobin Zhu ◽

Xuhua Mao ◽

Mingju Yan ◽

...

Keyword(s):

Fixed Effects ◽

Meta Analysis ◽

Anaerobic Bacteria ◽

Identification Accuracy ◽

P Value ◽

Correct Identification ◽

Maldi Tof Ms ◽

Analytical Technique ◽

Maldi Tof ◽

Tof Ms

Abstract Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has been rapidly developed and widely used as an analytical technique in clinical laboratories with high accuracy in microorganism identification. OBJECTIVE: To validate the efficacy of MALDI-TOF MS in identification of clinical pathogenic anaerobes. METHODS: Twenty-eight studies covering 6685 strains of anaerobic bacteria were included in this meta-analysis. Fixed-effects models based on the P -value and the I-squared were used for meta-analysis to consider the possibility of heterogeneity between studies. Statistical analyses were performed by using STATA 12.0. RESULTS : The identification accuracy of MALDI-TOF MS was 84% for species (I 2 = 98.0%, P < 0.1), and 92% for genus (I 2 = 96.6%, P < 0.1). Thereinto, the identification accuracy of Bacteroides was the highest at 96% with a 95% CI of 95-97%, followed by Lactobacillus spp., Parabacteroides spp., Clostridium spp., Propionibacterium spp., Prevotella spp., Veillonella spp. and Peptostreptococcus spp., and their correct identification rates were all above 90%, while the accuracy of rare anaerobic bacteria was relatively low. Meanwhile, the overall capabilities of two MALDI-TOF MS systems were different. The identification accuracy rate was 90% for VITEK MS vs . 86% for MALDI biotyper system. CONCLUSIONS: Our research showed that MALDI-TOF-MS was satisfactory in genus identification of clinical pathogenic anaerobic bacteria. However, this method still suffers from different drawbacks in precise identification of rare anaerobe and species levels of common anaerobic bacteria. Key words : MALDI-TOF MS , anaerobec, bacteria identification

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Comparison of MALDI-TOF-MS and RP-HPLC as Rapid Screening Methods for Wheat Lines With Altered Gliadin Compositions

Frontiers in Plant Science ◽

10.3389/fpls.2020.600489 ◽

2020 ◽

Vol 11 ◽

Author(s):

You-Ran Jang ◽

Kyoungwon Cho ◽

Sewon Kim ◽

Jae-Ryeong Sim ◽

Su-Bin Lee ◽

...

Keyword(s):

Celiac Disease ◽

Mutation Breeding ◽

Rapid Screening ◽

Food Allergies ◽

Screening Methods ◽

Maldi Tof Ms ◽

Maldi Tof ◽

Rp Hplc ◽

Wheat Lines ◽

Tof Ms

The wheat gliadins are a complex group of flour proteins that can trigger celiac disease and serious food allergies. As a result, mutation breeding and biotechnology approaches are being used to develop new wheat lines with reduced immunogenic potential. Key to these efforts is the development of rapid, high-throughput methods that can be used as a first step in selecting lines with altered gliadin contents. In this paper, we optimized matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) and reversed-phase high-performance liquid chromatography (RP-HPLC) methods for the separation of gliadins from Triticum aestivum cv. Chinese Spring (CS). We evaluated the quality of the resulting profiles using the complete set of gliadin gene sequences recently obtained from this cultivar as well as a set of aneuploid lines in CS. The gliadins were resolved into 13 peaks by MALDI-TOF-MS. α- or γ-gliadins that contain abundant celiac disease epitopes and are likely targets for efforts to reduce the immunogenicity of flour were found in several peaks. However, other peaks contained multiple α- and γ-gliadins, including one peak with as many as 12 different gliadins. In comparison, separation of proteins by RP-HPLC yielded 28 gliadin peaks, including 13 peaks containing α-gliadins and eight peaks containing γ-gliadins. While the separation of α- and γ-gliadins gliadins achieved by RP-HPLC was better than that achieved by MALDI-TOF-MS, it was not possible to link peaks with individual protein sequences. Both MALDI-TOF-MS and RP-HPLC provided adequate separation of ω-gliadins. While MALDI-TOF-MS is faster and could prove useful in studies that target specific gliadins, RP-HPLC is an effective method that can be applied more broadly to detect changes in gliadin composition.

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Performance of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) in diagnosis of ovarian cancer: a systematic review and meta-analysis

Journal of Ovarian Research ◽

10.1186/s13048-019-0605-2 ◽

2020 ◽

Vol 13 (1) ◽

Author(s):

Kexin Li ◽

Yuqing Pei ◽

Yue Wu ◽

Yi Guo ◽

Wei Cui

Keyword(s):

Ovarian Cancer ◽

Meta Analysis ◽

Laser Desorption ◽

Laser Desorption Ionization ◽

Ionization Time ◽

Maldi Tof Ms ◽

Maldi Tof ◽

Flight Mass Spectrometry ◽

Tof Ms ◽

Matrix Assisted Laser

Abstract Background To evaluate the diagnostic performance of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS) for ovarian cancer. Patients and methods A thorough research was conducted in PubMed, Web of Science and Embase (until November 2018) to identify studies evaluating the accuracy of MALDI-TOF-MS for ovarian cancer. Using Meta-Disc1.4, Review Manager 5.3 and Stata 15.1 software to analyze the pooled results: sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and 95% confidence intervals (CI). The summary receiver operating characteristic curves (SROC) and area under the curve (AUC) show the overall performance of MALDI-TOF-MS. Results Eighteen studies were included in the meta-analysis. Methodological quality analysis of the included studies showed that these articles were at low risk of bias and applicability concerns in total. Summary estimates of the diagnostic parameters were as follows: sensitivity, 0.77 (95% CI: 0.73–0.80); specificity, 0.72 (95% CI: 0.70–0.74), PLR, 2.80 (95% CI: 2.41–3.24); NLR, 0.30 (95% CI: 0.22–0.40) and DOR, 10.71 (95% CI: 7.81–14.68). And the AUC was 0.8336. Egger’s test showed no significant publication bias in this meta-analysis. Conclusion In conclusion, MALDI-TOF-MS shows a good ability for diagnosing ovarian cancer. Further evaluation and optimization of standardized procedures are necessary for complete relying on MALDI-TOF-MS to diagnose ovarian cancer.

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Identification of serum biomarkers for ovarian cancer using MALDI–TOF-MS combined with magnetic beads

International Journal of Clinical Oncology ◽

10.1007/s10147-011-0259-6 ◽

2011 ◽

Vol 17 (2) ◽

pp. 89-95 ◽

Cited By ~ 9

Author(s):

Shengjun Wu ◽

Kai Xu ◽

Guang Chen ◽

Jun Zhang ◽

Zhiwei Liu ◽

...

Keyword(s):

Ovarian Cancer ◽

Magnetic Beads ◽

Serum Biomarkers ◽

Maldi Tof Ms ◽

Maldi Tof ◽

Tof Ms

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Application of MALDI-TOF MS to rapid identification of anaerobic bacteria

10.21203/rs.2.9661/v4 ◽

2019 ◽

Author(s):

Ying Li ◽

Mingzhu Shan ◽

Zuobin Zhu ◽

Xuhua Mao ◽

Mingju Yan ◽

...

Keyword(s):

Fixed Effects ◽

Meta Analysis ◽

Anaerobic Bacteria ◽

Identification Accuracy ◽

P Value ◽

Correct Identification ◽

Maldi Tof Ms ◽

Analytical Technique ◽

Maldi Tof ◽

Tof Ms

Abstract BACKGROUND: Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has been rapidly developed and widely used as an analytical technique in clinical laboratories with high accuracy in microorganism identification. OBJECTIVE: To validate the efficacy of MALDI-TOF MS in identification of clinical pathogenic anaerobes. METHODS: Twenty-eight studies covering 6685 strains of anaerobic bacteria were included in this meta-analysis. Fixed-effects models based on the P -value and the I-squared were used for meta-analysis to consider the possibility of heterogeneity between studies. Statistical analyses were performed by using STATA 12.0. RESULTS : The identification accuracy of MALDI-TOF MS was 84% for species (I 2 = 98.0%, P < 0.1), and 92% for genus (I 2 = 96.6%, P < 0.1). Thereinto, the identification accuracy of Bacteroides was the highest at 96% with a 95% CI of 95-97%, followed by Lactobacillus spp., Parabacteroides spp., Clostridium spp., Propionibacterium spp., Prevotella spp., Veillonella spp. and Peptostreptococcus spp., and their correct identification rates were all above 90%, while the accuracy of rare anaerobic bacteria was relatively low. Meanwhile, the overall capabilities of two MALDI-TOF MS systems were different. The identification accuracy rate was 90% for VITEK MS vs . 86% for MALDI biotyper system. CONCLUSIONS: Our research showed that MALDI-TOF-MS was satisfactory in genus identification of clinical pathogenic anaerobic bacteria. However, this method still suffers from different drawbacks in precise identification of rare anaerobe and species levels of common anaerobic bacteria. Key words : MALDI-TOF MS , anaerobec, bacteria identification

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Application of MALDI-TOF MS to rapid identification of anaerobic bacteria

BMC Infectious Diseases ◽

10.1186/s12879-019-4584-0 ◽

2019 ◽

Vol 19 (1) ◽

Cited By ~ 6

Author(s):

Ying Li ◽

Mingzhu Shan ◽

Zuobin Zhu ◽

Xuhua Mao ◽

Mingju Yan ◽

...

Keyword(s):

Fixed Effects ◽

Meta Analysis ◽

Anaerobic Bacteria ◽

Rapid Identification ◽

Identification Accuracy ◽

Correct Identification ◽

Maldi Tof Ms ◽

Analytical Technique ◽

Maldi Tof ◽

Tof Ms

Abstract Background Matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) has been rapidly developed and widely used as an analytical technique in clinical laboratories with high accuracy in microorganism identification. Objective To validate the efficacy of MALDI-TOF MS in identification of clinical pathogenic anaerobes. Methods Twenty-eight studies covering 6685 strains of anaerobic bacteria were included in this meta-analysis. Fixed-effects models based on the P-value and the I-squared were used for meta-analysis to consider the possibility of heterogeneity between studies. Statistical analyses were performed by using STATA 12.0. Results The identification accuracy of MALDI-TOF MS was 84% for species (I2 = 98.0%, P < 0.1), and 92% for genus (I2 = 96.6%, P < 0.1). Thereinto, the identification accuracy of Bacteroides was the highest at 96% with a 95% CI of 95–97%, followed by Lactobacillus spp., Parabacteroides spp., Clostridium spp., Propionibacterium spp., Prevotella spp., Veillonella spp. and Peptostreptococcus spp., and their correct identification rates were all above 90%, while the accuracy of rare anaerobic bacteria was relatively low. Meanwhile, the overall capabilities of two MALDI-TOF MS systems were different. The identification accuracy rate was 90% for VITEK MS vs. 86% for MALDI biotyper system. Conclusions Our research showed that MALDI-TOF-MS was satisfactory in genus identification of clinical pathogenic anaerobic bacteria. However, this method still suffers from different drawbacks in precise identification of rare anaerobe and species levels of common anaerobic bacteria.

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Direct Identification of Urinary Tract Pathogens from Urine Samples, Combining Urine Screening Methods and Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass Spectrometry

Journal of Clinical Microbiology ◽

10.1128/jcm.02832-15 ◽

2016 ◽

Vol 54 (4) ◽

pp. 988-993 ◽

Cited By ~ 42

Author(s):

Melania Íñigo ◽

Andreu Coello ◽

Gema Fernández-Rivas ◽

Belén Rivaya ◽

Jessica Hidalgo ◽

...

Keyword(s):

Laser Desorption ◽

Urine Samples ◽

Screening Methods ◽

Gram Negative Bacteria ◽

Laser Desorption Ionization ◽

Ionization Time ◽

Maldi Tof Ms ◽

Maldi Tof ◽

Flight Mass Spectrometry ◽

Tof Ms

Early diagnosis of urinary tract infections (UTIs) is essential to avoid inadequate or unnecessary empirical antibiotic therapy. Microbiological confirmation takes 24 to 48 h. The use of screening methods, such as cytometry and automated microscopic analysis of urine sediment, allows the rapid prediction of negative samples. In addition, matrix-assisted laser desorption ionization–time of flight mass spectrometry (MALDI-TOF MS) is a widely established technique in clinical microbiology laboratories used to identify microorganisms. We evaluated the ability of MALDI-TOF MS to identify microorganisms from direct urine samples and the predictive value of automated analyzers for the identification of microorganisms in urine by MALDI-TOF MS. A total of 451 urine samples from patients with suspected UTIs were first analyzed using the Sysmex UF-1000iflow cytometer, an automatic sediment analyzer with microscopy (SediMax), culture, and then processed by MALDI-TOF MS with a simple triple-centrifuged procedure to obtain a pellet that was washed and centrifuged and finally applied directly to the MALDI-TOF MS plate. The organisms in 336 samples were correctly identified, mainly those with Gram-negative bacteria (86.10%). No microorganisms were misidentified, and noCandidaspp. were correctly identified. Regarding the data from autoanalyzers, the best bacteriuria cutoffs were 1,000 and 200 U/μl for UF-1000iand SediMax, respectively. It was concluded that the combination of a urine screening method and MALDI-TOF MS provided a reliable identification from urine samples, especially in those containing Gram-negative bacteria.

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Peptides Generated Ex Vivo from Serum Proteins by Tumor-Specific Exopeptidases Are Not Useful Biomarkers in Ovarian Cancer

Clinical Chemistry ◽

10.1373/clinchem.2009.133363 ◽

2010 ◽

Vol 56 (2) ◽

pp. 262-271 ◽

Cited By ~ 27

Author(s):

John F Timms ◽

Rainer Cramer ◽

Stephane Camuzeaux ◽

Ali Tiss ◽

Celia Smith ◽

...

Keyword(s):

Ovarian Cancer ◽

Serum Proteins ◽

Ex Vivo ◽

Clinical Samples ◽

Healthy Controls ◽

Test Set ◽

Maldi Tof Ms ◽

Maldi Tof ◽

Peptide Profiles ◽

Tof Ms

Abstract Background: The serum peptidome may be a valuable source of diagnostic cancer biomarkers. Previous mass spectrometry (MS) studies have suggested that groups of related peptides discriminatory for different cancer types are generated ex vivo from abundant serum proteins by tumor-specific exopeptidases. We tested 2 complementary serum profiling strategies to see if similar peptides could be found that discriminate ovarian cancer from benign cases and healthy controls. Methods: We subjected identically collected and processed serum samples from healthy volunteers and patients to automated polypeptide extraction on octadecylsilane-coated magnetic beads and separately on ZipTips before MALDI-TOF MS profiling at 2 centers. The 2 platforms were compared and case control profiling data analyzed to find altered MS peak intensities. We tested models built from training datasets for both methods for their ability to classify a blinded test set. Results: Both profiling platforms had CVs of approximately 15% and could be applied for high-throughput analysis of clinical samples. The 2 methods generated overlapping peptide profiles, with some differences in peak intensity in different mass regions. In cross-validation, models from training data gave diagnostic accuracies up to 87% for discriminating malignant ovarian cancer from healthy controls and up to 81% for discriminating malignant from benign samples. Diagnostic accuracies up to 71% (malignant vs healthy) and up to 65% (malignant vs benign) were obtained when the models were validated on the blinded test set. Conclusions: For ovarian cancer, altered MALDI-TOF MS peptide profiles alone cannot be used for accurate diagnoses.

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