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Molecular classification of human carcinomas by use of gene expression signatures.

Publication ,  Journal Article
Su, AI; Welsh, JB; Sapinoso, LM; Kern, SG; Dimitrov, P; Lapp, H; Schultz, PG; Powell, SM; Moskaluk, CA; Frierson, HF; Hampton, GM
Published in: Cancer research
October 2001

Classification of human tumors according to their primary anatomical site of origin is fundamental for the optimal treatment of patients with cancer. Here we describe the use of large-scale RNA profiling and supervised machine learning algorithms to construct a first-generation molecular classification scheme for carcinomas of the prostate, breast, lung, ovary, colorectum, kidney, liver, pancreas, bladder/ureter, and gastroesophagus, which collectively account for approximately 70% of all cancer-related deaths in the United States. The classification scheme was based on identifying gene subsets whose expression typifies each cancer class, and we quantified the extent to which these genes are characteristic of a specific tumor type by accurately and confidently predicting the anatomical site of tumor origin for 90% of 175 carcinomas, including 9 of 12 metastatic lesions. The predictor gene subsets include those whose expression is typical of specific types of normal epithelial differentiation, as well as other genes whose expression is elevated in cancer. This study demonstrates the feasibility of predicting the tissue origin of a carcinoma in the context of multiple cancer classes.

Duke Scholars

Published In

Cancer research

EISSN

1538-7445

ISSN

0008-5472

Publication Date

October 2001

Volume

61

Issue

20

Start / End Page

7388 / 7393

Related Subject Headings

  • RNA, Neoplasm
  • Predictive Value of Tests
  • Oncology & Carcinogenesis
  • Oligonucleotide Array Sequence Analysis
  • Neoplasms
  • Male
  • Humans
  • Gene Expression Regulation, Neoplastic
  • Gene Expression Profiling
  • Female
 

Citation

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MLA
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Su, A. I., Welsh, J. B., Sapinoso, L. M., Kern, S. G., Dimitrov, P., Lapp, H., … Hampton, G. M. (2001). Molecular classification of human carcinomas by use of gene expression signatures. Cancer Research, 61(20), 7388–7393.
Su, A. I., J. B. Welsh, L. M. Sapinoso, S. G. Kern, P. Dimitrov, H. Lapp, P. G. Schultz, et al. “Molecular classification of human carcinomas by use of gene expression signatures.Cancer Research 61, no. 20 (October 2001): 7388–93.
Su AI, Welsh JB, Sapinoso LM, Kern SG, Dimitrov P, Lapp H, et al. Molecular classification of human carcinomas by use of gene expression signatures. Cancer research. 2001 Oct;61(20):7388–93.
Su, A. I., et al. “Molecular classification of human carcinomas by use of gene expression signatures.Cancer Research, vol. 61, no. 20, Oct. 2001, pp. 7388–93.
Su AI, Welsh JB, Sapinoso LM, Kern SG, Dimitrov P, Lapp H, Schultz PG, Powell SM, Moskaluk CA, Frierson HF, Hampton GM. Molecular classification of human carcinomas by use of gene expression signatures. Cancer research. 2001 Oct;61(20):7388–7393.

Published In

Cancer research

EISSN

1538-7445

ISSN

0008-5472

Publication Date

October 2001

Volume

61

Issue

20

Start / End Page

7388 / 7393

Related Subject Headings

  • RNA, Neoplasm
  • Predictive Value of Tests
  • Oncology & Carcinogenesis
  • Oligonucleotide Array Sequence Analysis
  • Neoplasms
  • Male
  • Humans
  • Gene Expression Regulation, Neoplastic
  • Gene Expression Profiling
  • Female