TY - JOUR
T1 - Two subclasses of lung squamous cell carcinoma with different gene expression profiles and prognosis identified by hierarchical clustering and non-negative matrix factorization
AU - Inamura, Kentaro
AU - Fujiwara, Takeshi
AU - Hoshida, Yujin
AU - Isagawa, Takayuki
AU - Jones, Michael H.
AU - Virtanen, Carl
AU - Shimane, Miyuki
AU - Satoh, Yukitoshi
AU - Okumura, Sakae
AU - Nakagawa, Ken
AU - Tsuchiya, Eiju
AU - Ishikawa, Shumpei
AU - Aburatani, Hiroyuki
AU - Nomura, Hitoshi
AU - Ishikawa, Yuichi
N1 - Funding Information:
We thank Mr Shogo Yamamoto for technical advice and suggestions; Mr Atsushi Kobayashi, Ms Mio Kato, Ms Kazuko Yokokawa, Mr Motoyoshi Iwakoshi, Ms Miyuki Kogure, and Ms Tomoyo Kakita for their technical assistance; and Ms Chisato Kakuta for secretarial work. Parts of this study were supported financially by Grants-in-Aid from the Ministry of Education, Culture, Sports, Science; and Technology, and by grants from the Ministry of Health, Labour and Welfare, the Smoking Research Foundation, and the Vehicle Racing Commemorative Foundation.
PY - 2005/10/27
Y1 - 2005/10/27
N2 - Current clinical and histopathological criteria used to define lung squamous cell carcinomas (SCCs) are insufficient to predict clinical outcome. To make a clinically useful classification by gene expression profiling, we used a 40 386 element cDNA microarray to analyse 48 SCC, nine adenocarcinoma, and 30 normal lung samples. Initial analysis by hierarchical clustering (HC) allowed division of SCCs into two distinct subclasses. An additional independent round of HC induced a similar partition and consensus clustering with the non-negative matrix factorization approach indicated the robustness of this classification. Kaplan-Meier analysis with the log-rank test pointed to a nonsignificant difference in survival (P=0.071), but the likelihood of survival to 6 years was significantly different between the two groups (40.5 vs 81.8%, P=0.014, Z-test). Biological process categories characteristic for each subclass were identified statistically and upregulation of cell-proliferation-related genes was evident in the subclass with poor prognosis. In the subclass with better survival, genes involved in differentiated intracellular functions, such as the MAPKKK cascade, ceramide metabolism, or regulation of transcription, were upregulated. This work represents an important step toward the identification of clinically useful classification for lung SCC.
AB - Current clinical and histopathological criteria used to define lung squamous cell carcinomas (SCCs) are insufficient to predict clinical outcome. To make a clinically useful classification by gene expression profiling, we used a 40 386 element cDNA microarray to analyse 48 SCC, nine adenocarcinoma, and 30 normal lung samples. Initial analysis by hierarchical clustering (HC) allowed division of SCCs into two distinct subclasses. An additional independent round of HC induced a similar partition and consensus clustering with the non-negative matrix factorization approach indicated the robustness of this classification. Kaplan-Meier analysis with the log-rank test pointed to a nonsignificant difference in survival (P=0.071), but the likelihood of survival to 6 years was significantly different between the two groups (40.5 vs 81.8%, P=0.014, Z-test). Biological process categories characteristic for each subclass were identified statistically and upregulation of cell-proliferation-related genes was evident in the subclass with poor prognosis. In the subclass with better survival, genes involved in differentiated intracellular functions, such as the MAPKKK cascade, ceramide metabolism, or regulation of transcription, were upregulated. This work represents an important step toward the identification of clinically useful classification for lung SCC.
KW - Hierarchical clustering
KW - Lung
KW - Non-negative matrix factorization
KW - Squamous cell carcinoma
KW - cDNA microarray
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U2 - 10.1038/sj.onc.1208858
DO - 10.1038/sj.onc.1208858
M3 - Article
C2 - 16007138
AN - SCOPUS:27644465419
SN - 0950-9232
VL - 24
SP - 7105
EP - 7113
JO - Oncogene
JF - Oncogene
IS - 47
ER -