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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 universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för immunologi, genetik och patologi, Klinisk och experimentell patologi. (Fredrik Pontén)
Uppsala universitet, Medicinska och farmaceutiska vetenskapsområdet, Medicinska fakulteten, Institutionen för immunologi, genetik och patologi, Klinisk och experimentell patologi. (Patrick Micke)ORCID-id: 0000-0002-5294-7808
Vise andre og tillknytning
2017 (engelsk)Inngår i: Modern Pathology, ISSN 0893-3952, E-ISSN 1530-0285, Vol. 30, nr 7, s. 964-977Artikkel i tidsskrift (Fagfellevurdert) 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.

sted, utgiver, år, opplag, sider
2017. Vol. 30, nr 7, s. 964-977
HSV kategori
Forskningsprogram
Patologi
Identifikatorer
URN: urn:nbn:se:uu:diva-318128DOI: 10.1038/modpathol.2017.14ISI: 000404718100006PubMedID: 28281552OAI: oai:DiVA.org:uu-318128DiVA, id: diva2:1084176
Forskningsfinansiär
Swedish Cancer SocietyTilgjengelig fra: 2017-03-23 Laget: 2017-03-23 Sist oppdatert: 2019-03-29bibliografisk kontrollert
Inngår i avhandling
1. Transcriptomic and Proteomic Analysis of Tumor Markers in Tissue and Blood from Patients with Lung Cancer
Åpne denne publikasjonen i ny fane eller vindu >>Transcriptomic and Proteomic Analysis of Tumor Markers in Tissue and Blood from Patients with Lung Cancer
2018 (engelsk)Doktoravhandling, med artikler (Annet vitenskapelig)
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.

sted, utgiver, år, opplag, sider
Uppsala: Acta Universitatis Upsaliensis, 2018. s. 52
Serie
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1463
Emneord
non-small cell lung cancer, prognostic biomarkers, cancer-testis antigens, prediction model, tumor markers, autoantibodies, testis, screening
HSV kategori
Forskningsprogram
Patologi
Identifikatorer
urn:nbn:se:uu:diva-348349 (URN)978-91-513-0328-4 (ISBN)
Disputas
2018-06-08, Rudbecksalen, Rudbecklaboratoriet, Dag Hammarskjölds väg 20, Uppsala, 09:00 (engelsk)
Opponent
Veileder
Tilgjengelig fra: 2018-05-09 Laget: 2018-04-11 Sist oppdatert: 2018-10-08

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