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Reaching the limits of prognostication in non-small cell lung cancer: an optimized biomarker panel fails to outperform clinical parameters.
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)
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2017 (English)In: Modern Pathology, ISSN 0893-3952, E-ISSN 1530-0285, Vol. 30, no 7, p. 964-977Article in journal (Refereed) Published
Abstract [en]

Numerous protein biomarkers have been analyzed to improve prognostication in non-small cell lung cancer, but have not yet demonstrated sufficient value to be introduced into clinical practice. Here, we aimed to develop and validate a prognostic model for surgically resected non-small cell lung cancer. A biomarker panel was selected based on (1) prognostic association in published literature, (2) prognostic association in gene expression data sets, (3) availability of reliable antibodies, and (4) representation of diverse biological processes. The five selected proteins (MKI67, EZH2, SLC2A1, CADM1, and NKX2-1 alias TTF1) were analyzed by immunohistochemistry on tissue microarrays including tissue from 326 non-small cell lung cancer patients. One score was obtained for each tumor and each protein. The scores were combined, with or without the inclusion of clinical parameters, and the best prognostic model was defined according to the corresponding concordance index (C-index). The best-performing model was subsequently validated in an independent cohort consisting of tissue from 345 non-small cell lung cancer patients. The model based only on protein expression did not perform better compared to clinicopathological parameters, whereas combining protein expression with clinicopathological data resulted in a slightly better prognostic performance (C-index: all non-small cell lung cancer 0.63 vs 0.64; adenocarcinoma: 0.66 vs 0.70, squamous cell carcinoma: 0.57 vs 0.56). However, this modest effect did not translate into a significantly improved accuracy of survival prediction. The combination of a prognostic biomarker panel with clinicopathological parameters did not improve survival prediction in non-small cell lung cancer, questioning the potential of immunohistochemistry-based assessment of protein biomarkers for prognostication in clinical practice.Modern Pathology advance online publication, 10 March 2017; doi:10.1038/modpathol.2017.14.

Place, publisher, year, edition, pages
2017. Vol. 30, no 7, p. 964-977
National Category
Cancer and Oncology Medical Genetics
Identifiers
URN: urn:nbn:se:uu:diva-318128DOI: 10.1038/modpathol.2017.14ISI: 000404718100006PubMedID: 28281552OAI: oai:DiVA.org:uu-318128DiVA, id: diva2:1084176
Funder
Swedish Cancer Society
Available from: 2017-03-23 Created: 2017-03-23 Last updated: 2018-04-11Bibliographically approved
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
Keyword
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: 2018-05-09

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Djureinovic, DijanaMattsson, Johanna Sofia MargaretaLa Fleur, LinneaEkman, SimonStåhle, ElisabethPonten, FredrikBotling, JohanMicke, Patrick

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Djureinovic, DijanaMattsson, Johanna Sofia MargaretaLa Fleur, LinneaEkman, SimonStåhle, ElisabethPonten, FredrikBotling, JohanMicke, Patrick
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Department of Immunology, Genetics and PathologyExperimental and Clinical OncologyCentre for Research and Development, GävleborgThoracic SurgeryUCR-Uppsala Clinical Research Center
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