Genome wide identification of recessive cancer genes by combinatorial mutation analysis.
We devised a novel procedure to identify human cancer genes acting in a recessive manner. Our strategy was to combine the contributions of the different types of genetic alterations to loss of function: amino-acid substitutions, frame-shifts, gene deletions. We studied over 20,000 genes in 3 Gigabases of coding sequences and 700 array comparative genomic hybridizations. Recessive genes were scored according to nucleotide mismatches under positive selective pressure, frame-shifts and genomic deletions in cancer. Four different tests were combined together yielding a cancer recessive p-value for each studied gene. One hundred and fifty four candidate recessive cancer genes (p-value < 1.5 x 10(-7), FDR = 0.39) were identified. Strikingly, the prototypical cancer recessive genes TP53, PTEN and CDKN2A all ranked in the top 0.5% genes. The functions significantly affected by cancer mutations are exactly overlapping those of known cancer genes, with the critical exception for the absence of tyrosine kinases, as expected for a recessive gene-set.
Data Mining for Analysis of Microarrays, Università degli Studi, Ferrara, Italy.
Stefano
S
Volinia
Nicoletta
N
Mascellani
Jlenia
J
Marchesini
Angelo
A
Veronese
Elizabeth
E
Ormondroyd
Hansjuerg
H
Alder
Jeff
J
Palatini
Massimo
M
Negrini
Carlo M
CM
Croce
D019943:Amino Acid Substitution; D004252:DNA Mutational Analysis / Q000379:methods*; D030561:Databases, Nucleic Acid; D020224:Expressed Sequence Tags; D052138:Genes, Neoplasm; D005808:Genes, Recessive; D016678:Genome; D006801:Humans; D046228:Microarray Analysis; D008969:Molecular Sequence Data; D009154:Mutation; D009369:Neoplasms / Q000235:genetics*