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Common human cancer genes discovered by integrated gene-expression analysis. PLoS One 2007 Nov 07;2(11):e1149



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Scopus ID

2-s2.0-41149106140   63 Citations


BACKGROUND: Microarray technology enables a standardized, objective assessment of oncological diagnosis and prognosis. However, such studies are typically specific to certain cancer types, and the results have limited use due to inadequate validation in large patient cohorts. Discovery of genes commonly regulated in cancer may have an important implication in understanding the common molecular mechanism of cancer.

METHODS AND FINDINGS: We described an integrated gene-expression analysis of 2,186 samples from 39 studies to identify and validate a cancer type-independent gene signature that can identify cancer patients for a wide variety of human malignancies. The commonness of gene expression in 20 types of common cancer was assessed in 20 training datasets. The discriminative power of a signature defined by these common cancer genes was evaluated in the other 19 independent datasets including novel cancer types. QRT-PCR and tissue microarray were used to validate commonly regulated genes in multiple cancer types. We identified 187 genes dysregulated in nearly all cancerous tissue samples. The 187-gene signature can robustly predict cancer versus normal status for a wide variety of human malignancies with an overall accuracy of 92.6%. We further refined our signature to 28 genes confirmed by QRT-PCR. The refined signature still achieved 80% accuracy of classifying samples from mixed cancer types. This signature performs well in the prediction of novel cancer types that were not represented in training datasets. We also identified three biological pathways including glycolysis, cell cycle checkpoint II and plk3 pathways in which most genes are systematically up-regulated in many types of cancer.

CONCLUSIONS: The identified signature has captured essential transcriptional features of neoplastic transformation and progression in general. These findings will help to elucidate the common molecular mechanism of cancer, and provide new insights into cancer diagnostics, prognostics and therapy.

Author List

Lu Y, Yi Y, Liu P, Wen W, James M, Wang D, You M


Pengyuan Liu PhD Adjunct Professor in the Physiology department at Medical College of Wisconsin
Ming You MD, PhD Associate Provost, Professor in the Pharmacology and Toxicology department at Medical College of Wisconsin

MESH terms used to index this publication - Major topics in bold

Gene Expression Profiling
Reverse Transcriptase Polymerase Chain Reaction
jenkins-FCD Prod-484 8aa07fc50b7f6d102f3dda2f4c7056ff84294d1d