A principal component analysis of the TCGA data for 15 cancer localizations leads to the following results: The effective dimensionality of the region spanned by normal tissues and tumors in the gene expression state space is around 10 (out of a huge initial space with more than 60000 genes). Gene expression profiles uniquely distinguish between normal and cancer states. For any given tissue, the cancer state is a kind of attractor in the gene expression state space with at least 2500 highly differentially-expressed genes and a power-like tail in the expression distribution function. With regard to this 4 \% quantile of genes, pairs of localizations share between 314 and 1889 genescharacterizing the tumor state. The gene expression landscape shows distances between pairs of tumor localizations which inversely correlate with the number of shared genes. The most significantly altered top pathway in the cancer state is related to the "Extracellular URLanization" .
A principal component analysis of the TCGA data for 15 cancer localizations unveils the following qualitative facts about tumors: 1) The state of a tissue in gene expression space may be described by a few variables. In particular, there is a single variable describing the progression from a normal tissue to a tumor. 2) Each cancer localization is characterized by a gene expression profile, in which genes have specific weights in the definition of the cancer state. There are no less than 2500 differentially-expressed genes , which lead to power-like tails in the expression distribution functions. 3) Tumors in different localizations share hundreds or even thousands of differentially expressed genes. There are 6 genes common to the 15 studied tumor localizations. 4 ) The tumor region is a kind of attractor. Tumors in advanced stages converge to this region independently of patient age or genetic variability. 5) There is a landscape of cancer in gene expression space with an approximate border separating normal tissues from tumors .
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leads to the following results: The effective dimensionality of the region spanned by normal tissues and tumors in the gene expression state space is around 10 (out of a huge initial space with more than 60000 genes). Gene expression profiles uniquely distinguish between normal and cancer states. For any given tissue, the cancer state is a kind of attractor in the gene expression state space with at least
unveils the following qualitative facts about tumors: 1) The state of a tissue in gene expression space may be described by a few variables. In particular, there is a single variable describing the progression from a normal tissue to a tumor. 2) Each cancer localization is characterized by a gene expression profile, in which genes have specific weights in the definition of the cancer state. There are no less than
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\% quantile of genes, pairs of localizations share between 314 and 1889 genescharacterizing the
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state. The gene expression landscape shows distances between pairs of tumor localizations which inversely correlate with the number of shared genes. The most significantly altered top pathway in the cancer state is related to the "Extracellular URLanization"
region is a kind of attractor. Tumors in advanced stages converge to this region independently of patient age or genetic variability. 5) There is a landscape of cancer in gene expression space with an approximate border separating normal tissues from tumors