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Multiplex plasma protein profiling identifies novel markers to discriminate patients with adenocarcinoma of the lung
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. (Patrick Micke)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. (Patrick Micke)
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Surgical Sciences.
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. (Patrick Micke)
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(English)Manuscript (preprint) (Other academic)
Abstract [en]

Background:The overall prognosis of non-small cell lung cancer (NSCLC) is poor, and currently only patients with localized disease are potentially curable. Therefore, preferably non-invasively determined biomarkers that detect NSCLC patients at early stages of the disease are of high clinical relevance. The aim of this study was to identify and validate novel protein markers in plasma using the highly sensitive DNA-assisted multiplex proximity extension assay (PEA) to discriminate NSCLC from other lung diseases. 

Methods:Plasma samples were collected from a total of 343 patients who underwent surgical resection for different lung diseases, including 144 patients with lung adenocarcinoma (LAC),68 patients with non-malignant lung disease, 83 with lung metastasis of colorectal cancers and 48 patients with typical carcinoid. One microliter of plasma was analyzed using PEA, allowing detection and quantification of 92 established cancer related proteins. The concentrations of the plasma proteins were compared between disease groups.

Results:The comparison between LAC and benign samples revealed significantly different plasma levels for four proteins; CXL17, CEACAM5, VEGFR2 and ERBB3 (adjusted p-value < 0.05). A multi-parameter classifier was developed to discriminate between samples from LAC patients and from patients with non-malignant lung conditions. With a bootstrap aggregated decision tree algorithm (TreeBagger) a sensitivity of 93% and specificity of 64% was achieved to detect LAC in this risk population. 

Conclusion:By applying the highly sensitive PEA, reliable protein profiles could be determined in microliter amounts of plasma. We further identified proteins that demonstrated different plasma concentration in defined disease groups and developed a signature that holds potential to be included in a screening assay for early lung cancer detection. 

Keywords [en]
lung cancer, tumor markers, blood, serum, screening, biomarker
National Category
Medical and Health Sciences
Identifiers
URN: urn:nbn:se:uu:diva-347805OAI: oai:DiVA.org:uu-347805DiVA, id: diva2:1195946
Available from: 2018-04-07 Created: 2018-04-07 Last updated: 2018-04-11
In thesis
1. Transcriptomic and Proteomic Analysis of Tumor Markers in Tissue and Blood from Patients with Lung Cancer
Open this publication in new window or tab >>Transcriptomic and Proteomic Analysis of Tumor Markers in Tissue and Blood from Patients with Lung Cancer
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Despite recent treatment advancements, the survival outcome remains poor for the majority of patients with non-small cell lung cancer (NSCLC). The aim of this thesis was to evaluate protein expression to predict prognosis and identify biomarkers that can be used as targets for immunotherapy or for early detection of NSCLC.

In Paper I an optimized immunohistochemistry (IHC)-based prognostic model was developed for NSCLC. The prognostic performance of the model was compared to the clinicopathological parameters that are used in the clinical setting to predict outcome. The protein model failed to outperform clinicopathological parameters in predicting survival outcome questioning the potential of IHC-based assessment of prognostic markers in NSCLC.

In Paper II the human testis-specific proteome was profiled using RNA-sequencing (RNA-seq) data from testis and 26 other organs. More than 1000 genes demonstrated a testis-enriched expression pattern which makes testis the tissue with the most tissue-specific genes. The majority of the testis-enriched genes were previously poorly described and were further profiled by IHC. This analysis provides a starting point to increase the molecular understanding of testicular biology.

In Paper III the profiling of cancer-testis antigens (CTAs) was performed in NSCLC by using RNA-seq data from 32 normal organs and NSCLC. Ninety genes showed CTA expression profiles. The transcriptomic data were validated by IHC for several CTAs. The comprehensive analysis of CTAs can guide biomarker studies or help to identify targets for immunotherapeutic strategies.

In Paper IV the reactivity of CTAs was evaluated by measuring the abundance of autoantibodies in plasma from patients with NSCLC and benign lung diseases. Twenty-nine CTAs demonstrated exclusive reactivity in NSCLC and six of them were reactive in an independent NSCLC cohort. These findings suggest that some CTAs are immunogenic and could be utilized in immunotherapy.

In Paper V an immunoassay was used on lung adenocarcinoma plasma samples and samples from benign lung diseases. The plasma levels of 92 cancer related proteins were used to build a model that discriminated lung adenocarcinoma from benign controls with a sensitivity of 93% and a specificity of 64%. The results indicate that this assay is promising for the early detection of NSCLC.

In summary, this thesis presents an integrative analysis of lung cancer tissue and blood samples to characterize NSCLC on the transcriptomic and proteomic level and to identify cancer specific proteins.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2018. p. 52
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1463
Keywords
non-small cell lung cancer, prognostic biomarkers, cancer-testis antigens, prediction model, tumor markers, autoantibodies, testis, screening
National Category
Medical and Health Sciences
Research subject
Pathology
Identifiers
urn:nbn:se:uu:diva-348349 (URN)978-91-513-0328-4 (ISBN)
Public defence
2018-06-08, Rudbecksalen, Rudbecklaboratoriet, Dag Hammarskjölds väg 20, Uppsala, 09:00 (English)
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Supervisors
Available from: 2018-05-09 Created: 2018-04-11 Last updated: 2018-10-08

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