Reference - Detail
| RRC ID | 1367 |
|---|---|
| Author | Jones MH, Virtanen C, Honjoh D, Miyoshi T, Satoh Y, Okumura S, Nakagawa K, Nomura H, Ishikawa Y. |
| Title | Two prognostically significant subtypes of high-grade lung neuroendocrine tumours independent of small-cell and large-cell neuroendocrine carcinomas identified by gene expression profiles. |
| Journal | Lancet |
| Abstract |
BACKGROUND:Classification of high-grade neuroendocrine tumours (HGNT) of the lung currently recognises large-cell neuroendocrine carcinoma (LCNEC) and small-cell lung carcinoma (SCLC) as distinct groups. However, a similarity in histology for these two carcinomas and uncertain clinical course have led to suggestions that a single HGNT classification would be more appropriate. Gene expression profiling, which can reproduce histopathological classification, and often defines new subclasses with prognostic significance, can be used to resolve HGNT classification. METHODS:We used cDNA microarrays with 40?386 elements to analyse the gene expression profiles of 38 surgically resected samples of lung neuroendocrine tumours and 11 SCLC cell lines. Samples of large-cell carcinoma, adenocarcinoma, and normal lung were also included to give a total of 105 samples analysed. The data were subjected to filtering to yield informative genes before unsupervised hierarchical clustering that identified relatedness of tumour samples. FINDINGS:Distinct groups for carcinoids, large-cell carcinoma, adenocarcinoma, and normal lung were readily identified. However, we were unable to distinguish LCNEC from SCLC by gene expression profiling. Three independent rounds of unsupervised hierarchical clustering consistently divided SCLC samples into two main groups with LCNEC samples largely integrated with these groups. Furthermore, patients in one of the groups identified by clustering had a significantly better clinical outcome than the other (83% vs 12% survived for 5 years; p=0.0094. None of the highly proliferative SCLC cell lines subsequently analysed clustered with this good-prognosis group. INTERPRETATION:Our findings show that HGNT of the lung can be classified into two groups independent of SCLC and LCNEC. To this end, we have identified many genes, some of which encode well-characterised markers of cancer that distinguish the HGNT groups. These results have implications for the diagnosis, classification, and treatment of lung neuroendocrine tumours, and provide important insights into their underlying biology. |
| Volume | 363(9411) |
| Pages | 775-81 |
| Published | 2004-3-6 |
| DOI | 10.1016/S0140-6736(04)15693-6 |
| PII | S0140673604156936 |
| PMID | 15016488 |
| MeSH | Biomarkers, Tumor Carcinoma, Large Cell / classification Carcinoma, Large Cell / diagnosis Carcinoma, Large Cell / genetics Carcinoma, Neuroendocrine / classification Carcinoma, Neuroendocrine / diagnosis Carcinoma, Neuroendocrine / genetics* Carcinoma, Small Cell / classification Carcinoma, Small Cell / diagnosis Carcinoma, Small Cell / genetics Gene Expression Profiling / methods Gene Expression Profiling / statistics & numerical data* Gene Expression Regulation, Neoplastic Genetic Markers Humans Lung Neoplasms / classification Lung Neoplasms / diagnosis Lung Neoplasms / genetics* Oligonucleotide Array Sequence Analysis / methods Oligonucleotide Array Sequence Analysis / statistics & numerical data* Prognosis Survival Analysis |
| IF | 60.39 |
| Times Cited | 170 |
| WOS Category | BIOCHEMISTRY & MOLECULAR BIOLOGY |
| Resource | |
| Human and Animal Cells | Lu-165(RCB1184) Lu-130(RCB0465) Lu-135(RCB0468) Lu-139(RCB0469) Lu-140(RCB0470) MS-1(RCB0725) |