Serum proteome profiling of pancreatitis using recombinant antibody microarrays reveals disease‐associated biomarker signatures

Sandström, Anna; Andersson, Roland; Segersvärd, Ralf; Löhr, Matthias; Borrebaeck, Carl; Wingren, Christer

doi:10.1002/prca.201200051

Cited by 28 publications

(19 citation statements)

References 63 publications

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“…Next, the array-to-array variations were handled by using a semiglobal normalization approach [25, 38, 40, 41]. Thus, the coefficient of variation (CV) was calculated for each analyte and ranked.…”

Section: Methodsmentioning

confidence: 99%

Tumor tissue protein signatures reflect histological grade of breast cancer

et al. 2017

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Histological grade is one of the most commonly used prognostic factors for patients diagnosed with breast cancer. However, conventional grading has proven technically challenging, and up to 60% of the tumors are classified as histological grade 2, which represents a heterogeneous cohort less informative for clinical decision making. In an attempt to study and extend the molecular puzzle of histologically graded breast cancer, we have in this pilot project searched for additional protein biomarkers in a new space of the proteome. To this end, we have for the first time performed protein expression profiling of breast cancer tumor tissue, using recombinant antibody microarrays, targeting mainly immunoregulatory proteins. Thus, we have explored the immune system as a disease-specific sensor (clinical immunoproteomics). Uniquely, the results showed that several biologically relevant proteins reflecting histological grade could be delineated. In more detail, the tentative biomarker panels could be used to i) build a candidate model classifying grade 1 vs. grade 3 tumors, ii) demonstrate the molecular heterogeneity among grade 2 tumors, and iii) potentially re-classify several of the grade 2 tumors to more like grade 1 or grade 3 tumors. This could, in the long-term run, lead to improved prognosis, by which the patients could benefit from improved tailored care.

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Section: Methodsmentioning

confidence: 99%

Tumor tissue protein signatures reflect histological grade of breast cancer

et al. 2017

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“…The results showed that a mean CV value of 12% (range 5 to 27%) (by omitting one antibody clone the range was reduced to 5 to 21%) was obtained. In comparison, the established and (more) optimized conventional antibody microarrays regularly display a spot-to-spot variability of <10% (recombinant antibody microarrays) [36] and <20% (polyclonal and monoclonal antibody microfuture science group Miniaturization of multiplexed planar recombinant antibody arrays for serum protein profiling Research Article…”

Section: Resultsmentioning

confidence: 99%

“…A representative correlation plot, illustrated for the data associated with array layout A, is also shown in Figure 1B. In comparison, conventional antibody microarrays regularly display R 2 -values of > 0.9 (recombinant antibody microarrays) [4,36] and > 0.7 (polyclonal and monoclonal antibody microarrays) [38].…”

Section: Scfv Layout a Scfv Layout Bmentioning

confidence: 99%

Miniaturization of Multiplexed Planar Recombinant Antibody Arrays for Serum Protein Profiling

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Amro³

et al. 2014

Bioanalysis

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“…Differential diagnosis of PDAC vs. pancreatitis is sometimes difficult and addressed by us in a previous study where late stage PDAC could be discriminated from a combined control group of different pancreatic inflammatory indications, as well as healthy individuals (Wingren et al., 2012). Following this, an additional study was conducted on pancreatitis subtypes, where we identified protein signatures specific for acute, chronic and autoimmune pancreatitis (Sandstrom et al., 2012). The lack of pancreatitis samples is a limitation of the current study.…”

Section: Discussionmentioning

confidence: 99%

Plasma protein profiling in a stage defined pancreatic cancer cohort – Implications for early diagnosis

et al. 2016

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Pancreatic ductal adenocarcinoma (PDAC) is a disease where detection preceding clinical symptoms significantly increases the life expectancy of patients. In this study, a recombinant antibody microarray platform was used to analyze 213 Chinese plasma samples from PDAC patients and normal control (NC) individuals. The cohort was stratified according to disease stage, i.e. resectable disease (stage I/II), locally advanced (stage III) and metastatic disease (stage IV). Support vector machine analysis showed that all PDAC stages could be discriminated from controls and that the accuracy increased with disease progression, from stage I to IV. Patients with stage I/II PDAC could be discriminated from NC with high accuracy based on a plasma protein signature, indicating a possibility for early diagnosis and increased detection rate of surgically resectable tumors.

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Serum proteome profiling of pancreatitis using recombinant antibody microarrays reveals disease‐associated biomarker signatures

Cited by 28 publications

References 63 publications

Tumor tissue protein signatures reflect histological grade of breast cancer

Tumor tissue protein signatures reflect histological grade of breast cancer

Miniaturization of Multiplexed Planar Recombinant Antibody Arrays for Serum Protein Profiling

Plasma protein profiling in a stage defined pancreatic cancer cohort – Implications for early diagnosis

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