Gene Expression Signature Differentiates Histology But Not Progression Status of Early-Stage NSCLC
Advances in molecular analyses based on high-throughput technologies can contribute to a more accurate classification of non–small cell lung cancer (NSCLC), as well as a better prediction of both the disease course and the efficacy of targeted therapies. Here we set out to analyze whether global gen...
| Main Authors: | , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2017-06-01
|
| Series: | Translational Oncology |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1936523316302479 |
| _version_ | 1819162181526093824 |
|---|---|
| author | Radoslaw Charkiewicz Jacek Niklinski Jürgen Claesen Anetta Sulewska Miroslaw Kozlowski Anna Michalska-Falkowska Joanna Reszec Marcin Moniuszko Wojciech Naumnik Wieslawa Niklinska |
| author_facet | Radoslaw Charkiewicz Jacek Niklinski Jürgen Claesen Anetta Sulewska Miroslaw Kozlowski Anna Michalska-Falkowska Joanna Reszec Marcin Moniuszko Wojciech Naumnik Wieslawa Niklinska |
| author_sort | Radoslaw Charkiewicz |
| collection | DOAJ |
| description | Advances in molecular analyses based on high-throughput technologies can contribute to a more accurate classification of non–small cell lung cancer (NSCLC), as well as a better prediction of both the disease course and the efficacy of targeted therapies. Here we set out to analyze whether global gene expression profiling performed in a group of early-stage NSCLC patients can contribute to classifying tumor subtypes and predicting the disease prognosis. Gene expression profiling was performed with the use of the microarray technology in a training set of 108 NSCLC samples. Subsequently, the recorded findings were validated further in an independent cohort of 44 samples. We demonstrated that the specific gene patterns differed significantly between lung adenocarcinoma (AC) and squamous cell lung carcinoma (SCC) samples. Furthermore, we developed and validated a novel 53-gene signature distinguishing SCC from AC with 93% accuracy. Evaluation of the classifier performance in the validation set showed that our predictor classified the AC patients with 100% sensitivity and 88% specificity. We revealed that gene expression patterns observed in the early stages of NSCLC may help elucidate the histological distinctions of tumors through identification of different gene-mediated biological processes involved in the pathogenesis of histologically distinct tumors. However, we showed here that the gene expression profiles did not provide additional value in predicting the progression status of the early-stage NSCLC. Nevertheless, the gene expression signature analysis enabled us to perform a reliable subclassification of NSCLC tumors, and it can therefore become a useful diagnostic tool for a more accurate selection of patients for targeted therapies. |
| first_indexed | 2024-12-22T17:24:09Z |
| format | Article |
| id | doaj.art-517e71bc21f74656860567eb197dac21 |
| institution | Directory Open Access Journal |
| issn | 1936-5233 |
| language | English |
| last_indexed | 2024-12-22T17:24:09Z |
| publishDate | 2017-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Translational Oncology |
| spelling | doaj.art-517e71bc21f74656860567eb197dac212022-12-21T18:18:46ZengElsevierTranslational Oncology1936-52332017-06-01103450458Gene Expression Signature Differentiates Histology But Not Progression Status of Early-Stage NSCLCRadoslaw Charkiewicz0Jacek Niklinski1Jürgen Claesen2Anetta Sulewska3Miroslaw Kozlowski4Anna Michalska-Falkowska5Joanna Reszec6Marcin Moniuszko7Wojciech Naumnik8Wieslawa Niklinska9Department of Clinical Molecular Biology, Medical University of Bialystok, Waszyngtona 13, Bialystok 15-269, PolandDepartment of Clinical Molecular Biology, Medical University of Bialystok, Waszyngtona 13, Bialystok 15-269, PolandInteruniversity Institute for Biostatistics and Statistical Bioinformatics, Hasselt University, Diepenbeek 3590, BelgiumDepartment of Clinical Molecular Biology, Medical University of Bialystok, Waszyngtona 13, Bialystok 15-269, PolandDepartment of Thoracic Surgery, Medical University of Bialystok, Marii Sklodowskiej-Curie 24a, Bialystok 15-276, PolandDepartment of Clinical Molecular Biology, Medical University of Bialystok, Waszyngtona 13, Bialystok 15-269, PolandDepartment of Medical Pathomorphology, Medical University of Bialystok, Waszyngtona 13, Bialystok 15-269, PolandDepartment of Regenerative Medicine and Immune Regulation, Medical University of Bialystok, Waszyngtona 13, Bialystok, 15-269, PolandDepartment of Clinical Molecular Biology, Medical University of Bialystok, Waszyngtona 13, Bialystok 15-269, Poland; First Department of Lung Diseases, Medical University of Bialystok, Zurawia 14, Bialystok 15-540, PolandDepartment of Histology and Embryology, Medical University of Bialystok, Waszyngtona 13, Bialystok 15-269, Poland; Address all correspondence to: Wieslawa Niklinska, Department of Histology and Embryology, Medical University of Bialystok, Waszyngtona 13, Bialystok 15-269, Poland.Advances in molecular analyses based on high-throughput technologies can contribute to a more accurate classification of non–small cell lung cancer (NSCLC), as well as a better prediction of both the disease course and the efficacy of targeted therapies. Here we set out to analyze whether global gene expression profiling performed in a group of early-stage NSCLC patients can contribute to classifying tumor subtypes and predicting the disease prognosis. Gene expression profiling was performed with the use of the microarray technology in a training set of 108 NSCLC samples. Subsequently, the recorded findings were validated further in an independent cohort of 44 samples. We demonstrated that the specific gene patterns differed significantly between lung adenocarcinoma (AC) and squamous cell lung carcinoma (SCC) samples. Furthermore, we developed and validated a novel 53-gene signature distinguishing SCC from AC with 93% accuracy. Evaluation of the classifier performance in the validation set showed that our predictor classified the AC patients with 100% sensitivity and 88% specificity. We revealed that gene expression patterns observed in the early stages of NSCLC may help elucidate the histological distinctions of tumors through identification of different gene-mediated biological processes involved in the pathogenesis of histologically distinct tumors. However, we showed here that the gene expression profiles did not provide additional value in predicting the progression status of the early-stage NSCLC. Nevertheless, the gene expression signature analysis enabled us to perform a reliable subclassification of NSCLC tumors, and it can therefore become a useful diagnostic tool for a more accurate selection of patients for targeted therapies.http://www.sciencedirect.com/science/article/pii/S1936523316302479 |
| spellingShingle | Radoslaw Charkiewicz Jacek Niklinski Jürgen Claesen Anetta Sulewska Miroslaw Kozlowski Anna Michalska-Falkowska Joanna Reszec Marcin Moniuszko Wojciech Naumnik Wieslawa Niklinska Gene Expression Signature Differentiates Histology But Not Progression Status of Early-Stage NSCLC Translational Oncology |
| title | Gene Expression Signature Differentiates Histology But Not Progression Status of Early-Stage NSCLC |
| title_full | Gene Expression Signature Differentiates Histology But Not Progression Status of Early-Stage NSCLC |
| title_fullStr | Gene Expression Signature Differentiates Histology But Not Progression Status of Early-Stage NSCLC |
| title_full_unstemmed | Gene Expression Signature Differentiates Histology But Not Progression Status of Early-Stage NSCLC |
| title_short | Gene Expression Signature Differentiates Histology But Not Progression Status of Early-Stage NSCLC |
| title_sort | gene expression signature differentiates histology but not progression status of early stage nsclc |
| url | http://www.sciencedirect.com/science/article/pii/S1936523316302479 |
| work_keys_str_mv | AT radoslawcharkiewicz geneexpressionsignaturedifferentiateshistologybutnotprogressionstatusofearlystagensclc AT jacekniklinski geneexpressionsignaturedifferentiateshistologybutnotprogressionstatusofearlystagensclc AT jurgenclaesen geneexpressionsignaturedifferentiateshistologybutnotprogressionstatusofearlystagensclc AT anettasulewska geneexpressionsignaturedifferentiateshistologybutnotprogressionstatusofearlystagensclc AT miroslawkozlowski geneexpressionsignaturedifferentiateshistologybutnotprogressionstatusofearlystagensclc AT annamichalskafalkowska geneexpressionsignaturedifferentiateshistologybutnotprogressionstatusofearlystagensclc AT joannareszec geneexpressionsignaturedifferentiateshistologybutnotprogressionstatusofearlystagensclc AT marcinmoniuszko geneexpressionsignaturedifferentiateshistologybutnotprogressionstatusofearlystagensclc AT wojciechnaumnik geneexpressionsignaturedifferentiateshistologybutnotprogressionstatusofearlystagensclc AT wieslawaniklinska geneexpressionsignaturedifferentiateshistologybutnotprogressionstatusofearlystagensclc |