Use of anchorchip-time-of-flight spectrometry technology to screen tumor biomarker proteins in serum for small cell lung cancer

Du, Jianjun; Yang, Shuanying; Lin, Xiuli; Bu, Lina; Nan, Yandong; Huo, Shufen; Shang, Wei

doi:10.1186/1746-1596-5-60

Cited by 14 publications

(16 citation statements)

References 13 publications

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“…There are several studies published where MALDI/SELDI-based analyses of the low-molecular-weight fraction of serum/plasma proteome were applied for identification of peptide signatures specific for patients with head and neck cancer (30)(31)(32)(33)(34), colorectal cancer (19,(35)(36)(37)(38) and lung cancer (39)(40)(41)(42)(43)(44). All these works proposed differentiating peptides and multi-peptide signatures that discriminated between specimens collected from cancer patients and healthy donors, yet such cancer signatures were built of apparently different spectral components.…”

Section: Discussionmentioning

confidence: 99%

Comparison of peptide cancer signatures identified by mass spectrometry in serum of patients with head and neck, lung and colorectal cancers: Association with tumor progression

Pietrowska

Polańska²,

Suwiński³

et al. 2011

Int J Oncol

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Abstract. Mass spectrometry-based analyses of the lowmolecular-weight fraction of serum proteome allow identifying proteome profiles (signatures) that are potentially useful in detection and diagnostics of cancer. Here we compared serum proteome profiles of healthy donors and patients with three different types of cancer aiming to identify peptide signatures that were either common for all cancer samples or specific for cancer type. Blood samples were collected before start of the therapy from patients with head and neck squamous cell cancer, colorectal adenocarcinoma and non-small cell lung cancer, and from a corresponding group of healthy volunteers. Mass profiles of the serum proteome were recorded in the range between 2 and 13 kDa using MALDI-ToF spectrometry and 131 identified peptide ions were used for statistical analyses. Similar degrees of overall similarities were observed in all intra-group and inter-group analyses when general features of serum proteome profiles were compared between individual samples. However, classifiers built of selected spectral components allowed differentiation between healthy donors and three groups of cancer patients with 69-74% sensitivity and 82-84% specificity. There were two common peptide species (3766 and 5867 Da) with increased levels in all cancer samples. Several spectral components permitted differentiation between lung cancer samples and either head and neck cancer or colorectal cancer samples, but two latter types of samples could not be properly discriminated. Abundance of spectral components that putatively corresponded to fragments of serum amyloid A (11511 and 11667 Da) was highest in lung cancer samples, yet increased levels of these peptides appeared to generally associate with more advanced cancer cases. We concluded that certain components of serum peptide signatures are common for different cancer signatures and putatively reflect general response of organism to the disease, yet other components of such signatures are more specific and most likely correspond to clinical stage of the malignancy. IntroductionThe low-molecular-weight fraction of the blood proteome appears to be a promising source of novel biomarkers of human diseases. Thus, mass spectrometry (MS) methods, which allow characterization of this particular component of human proteome, emerge as a valuable tool of clinical proteomics and disease diagnostics (1-5). The proteomics approach that takes into consideration characteristic features of the whole proteome but does not rely on particular protein, is called proteome pattern analysis or proteome profiling. In this approach specific proteome signatures are built based on several peptide/protein components, which can be exemplified by ions registered at defined m/z values in the mass spectrum. Such signatures can be used for sample identification and classification even though their particular components may lack differentiating power when analyzed separately (6-9). Matrix-assisted laser desorption/ionization spectrometry (MALDI), and its deri...

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Section: Discussionmentioning

confidence: 99%

Comparison of peptide cancer signatures identified by mass spectrometry in serum of patients with head and neck, lung and colorectal cancers: Association with tumor progression

Pietrowska

Polańska²,

Suwiński³

et al. 2011

Int J Oncol

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“…Prior studies of honeybee venom employing both "bottom-up" and "topdown" strategies led to identification of only six known venom proteins and three unknown protein components, not identified earlier (Matysiak et al, 2011b;Peiren et al, 2005). Although, PAC targets are dedicated for the rapid screening analysis, many reports have shown that application of the classical AnchorChip MALDI plate facilitates better results (Du et al, 2010;Leung and Pitts, 2008;Zhang et al, 2008Zhang et al, , 2007. This plate, according to the manufacturer is preferred for high-throughput MALDI measurements that are performed in unattended, fully automatic mode.…”

Section: Honeybee Venom Analysis Applying Shotgun Proteomic Approachmentioning

confidence: 97%

Shotgun proteome analysis of honeybee venom using targeted enrichment strategies

Matysiak

Hajduk

Pietrzak

et al. 2014

Toxicon

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“…Interestingly, low-molecular-weight peptides, such as S100A8 and fibrinogen, have been recognized to play important roles in physiologic and pathologic processes and could be used as relevant biomarker candidates (23,24). Recently, the mass spectrum that directly detects and differentiates short peptides has offered a promising approach for peptidomic biomarker discovery (8,12,(25)(26)(27).…”

Section: Discussionmentioning

confidence: 99%

Serum peptidome patterns of hepatocellular carcinoma based on magnetic bead separation and mass spectrometry analysis

Li¹,

He²,

Fan³

et al. 2015

Turk J Gastroenterol

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Background/Aims: The only hope for a cure from hepatocellular carcinoma (HCC) rests on early diagnosis. The present study aims to determine serum peptidome patterns for early diagnosis of HCC. Materials and Methods: To identify novel peptidome patterns for diagnosing HCC, serum from31 healthy volunteers and 32 HCC patients were subjected to a comparative proteomic analysis using a ClinProt Kit combined with mass spectrometry (MS). This approach allows the determination of peptidome patterns that are able to differentiate the HCC from healthy volunteers. For further validation, the diagnostic and differential diagnostic capabilities of the peptidome patterns were verified blindly by an independent group of sera consisted of 31 HCC, 23 liver fibrosis and 33 healthy volunteers. Results: A Quick Classifier Algorithm was used to construct the peptidome patterns for the identification of HCC from the control samples. One of the identified peaks at m/z 7771 was used to construct the peptidome patterns with almost 100% accuracy. Furthermore, the peptidome patterns could also differentiate the validation group with high accuracy. Conclusion: These results suggest that the ClinProt Kit combined with MS achieves significantly high accuracy for HCC diagnosis and differential diagnosis.

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Use of anchorchip-time-of-flight spectrometry technology to screen tumor biomarker proteins in serum for small cell lung cancer

Cited by 14 publications

References 13 publications

Comparison of peptide cancer signatures identified by mass spectrometry in serum of patients with head and neck, lung and colorectal cancers: Association with tumor progression

Comparison of peptide cancer signatures identified by mass spectrometry in serum of patients with head and neck, lung and colorectal cancers: Association with tumor progression

Shotgun proteome analysis of honeybee venom using targeted enrichment strategies

Serum peptidome patterns of hepatocellular carcinoma based on magnetic bead separation and mass spectrometry analysis

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