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Series GSE4716 Query DataSets for GSE4716
Status Public on Jan 20, 2007
Title Gene expression-based, individualized outcome prediction for surgically treated lung cancer patients
Organism Homo sapiens
Experiment type Expression profiling by array
Summary Individualized outcome prediction classifiers were successfully constructed through expression profiling of a total of 8,644 genes in 50 non-small cell lung cancer (NSCLC) cases, which had been consecutively operated on within a defined short period of time and followed up more than five years. The resultant classifier of NSCLCs yielded 82% accuracy for forecasting survival or death five years after surgery of a given patient. In addition, since two major histologic classes may differ in terms of outcome-related expression signatures, histologic type-specific outcome classifiers were also constructed. The resultant highly predictive classifiers, designed specifically for non-squamous cell carcinomas, showed a prediction accuracy of more than 90% independent of disease stage. In addition to the presence of heterogeneities in adenocarcinomas, our unsupervised hierarchical clustering analysis revealed for the first time the existence of clinicopathologically relevant subclasses of squamous cell carcinomas with marked differences in their invasive growth and prognosis. This finding clearly suggests that NSCLCs comprise distinct subclasses with considerable heterogeneities even within one histologic type. Overall, these findings should advance not only our understanding of the biology of lung cancer but also our ability to individualize post-operative therapies based on the predicted outcome.
Keywords: cell type comparison and prognosis prediction
 
Overall design In the study presented here, a consecutively operated, well-defined cohort of 50 NSCLC cases, followed up more than five years, was used to acquire expression profiles of a total of 8,644 unique genes, leading to the successful construction of supervised learning method-based individualized outcome prediction classifiers with high accuracy. In addition, the identification by means of unsupervised hierarchical clustering analysis of two distinct subclasses of squamous cell carcinomas with interesting histologic distinctions and a significant difference in their prognosis is also reported.
 
Contributor(s) Tomida S, Koshikawa K, Yatabe Y, Harano T, Ogura N, Mitsudomi T, Some M, Yanagisawa K, Takahashi T, Osada H, Takahashi T
Citation(s) 15064725
Submission date Apr 25, 2006
Last update date Mar 16, 2012
Contact name Takashi Takahashi
Organization name Aichi Cancer Center
Street address 1-1 Kanokoden, Chikusa-ku
City Nagoya
State/province Aichi
ZIP/Postal code 464-8681
Country Japan
 
Platforms (2)
GPL3694 GeneFilter Human Microarray Release I (GF200)
GPL3696 GeneFilter Human Microarray Release II (GF201)
Samples (100)
GSM106447 Patient 1 GF200 001
GSM106448 Patient 2 GF200 002
GSM106449 Patient 3 GF200 003
Relations
BioProject PRJNA95603

Clinical Data header descriptions
Sample #
Survival Period
status after 5 years
HIST ad - adenocarcinoma, la - large cell carcinoma, sq - squamous cell carcinoma
AGE
SEX
pStage pathologic stage
pT primary tumor stage
pN nodal status

Data table
Sample # Survival Period status after 5 years HIST AGE SEX pStage pT pN
001 60 Alive SQ 61 Male IIB 3 0
002 7 Dead SQ 63 Male IIIA 2 2
003 60 Alive LA 68 Male IB 2 0
004 44 Dead AD 71 Male IB 2 0
005 60 Alive AD 49 Female IA 1 0
006 56 Dead AD 51 Female IIIA 2 2
007 60 Alive AD 51 Female IIA 1 1
008 40 Dead AD 67 Female IIIA 1 2
009 60 Alive AD 52 Male IIIA 2 2
010 60 Alive LA 69 Male IIA 1 1
011 7 Dead AD 66 Male IIB 2 1
012 60 Alive AD 71 Female IA 1 0
013 60 Alive AD 62 Female IIIB 4 0
014 17 Dead AD 47 Female IIIA 2 2
015 60 Alive AD 60 Female IA 1 0
016 60 Alive AD 64 Female IB 2 0
017 52 Dead SQ 55 Male IB 2 0
018 60 Alive SQ 75 Male IB 2 0
019 60 Alive AD 57 Male IIIA 2 2
020 60 Alive SQ 65 Male IA 1 0

Total number of rows: 50

Table truncated, full table size 1 Kbytes.




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